Search results for: graph recognition

Authors: Baghdasaryan Marinka, Ulikyan Azatuhi

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The efficient usage of the compensation abilities of the electrical drive synchronous motors used in production processes can essentially improve the technical and economic indices of the process.  Reducing the flows of the reactive electrical energy due to the compensation of reactive power allows to significantly reduce the load losses of power in the electrical networks. As a result of analyzing the scientific works devoted to the issues of regulating the excitation of the synchronous motors, the need for comprehensive investigation and estimation of the excitation mode has been substantiated. By means of the obtained transmission functions, in the Simulink environment of the software package MATLAB, the transition processes of the excitation mode have been studied. As a result of obtaining and estimating the graph of the Nyquist plot and the transient process, the necessity of developing the Proportional-Integral-Derivative (PID) regulator has been justified. The transient processes of the system of the PID regulator have been investigated, and the amplitude–phase characteristics of the system have been estimated. The analysis of the obtained results has shown that the regulation indices of the developed system have been improved. The developed system can be successfully applied for regulating the excitation voltage of different-power synchronous motors, operating with a changing load, ensuring a value of the power coefficient close to 1.

Keywords: transition process, synchronous motor, excitation mode, regulator, reactive power

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Authors: Yuta Nakano, Kozo Kajiwara, Atsushi Hori, Takeshi Fujita

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In association with the wave of electric vehicles (EV), low energy consumption systems have become more and more important. One of the key technologies to realize low energy consumption is a dynamic vision sensor (DVS), or we can call it an event sensor, neuromorphic vision sensor and so on. This sensor has several features, such as high temporal resolution, which can achieve 1 Mframe/s, and a high dynamic range (120 DB). However, the point that can contribute to low energy consumption the most is its sparsity; to be more specific, this sensor only captures the pixels that have intensity change. In other words, there is no signal in the area that does not have any intensity change. That is to say, this sensor is more energy efficient than conventional sensors such as RGB cameras because we can remove redundant data. On the other side of the advantages, it is difficult to handle the data because the data format is completely different from RGB image; for example, acquired signals are asynchronous and sparse, and each signal is composed of x-y coordinate, polarity (two values: +1 or -1) and time stamp, it does not include intensity such as RGB values. Therefore, as we cannot use existing algorithms straightforwardly, we have to design a new processing algorithm to cope with DVS data. In order to solve difficulties caused by data format differences, most of the prior arts make a frame data and feed it to deep learning such as Convolutional Neural Networks (CNN) for object detection and recognition purposes. However, even though we can feed the data, it is still difficult to achieve good performance due to a lack of intensity information. Although polarity is often used as intensity instead of RGB pixel value, it is apparent that polarity information is not rich enough. Considering this context, we proposed to use the timestamp information as a data representation that is fed to deep learning. Concretely, at first, we also make frame data divided by a certain time period, then give intensity value in response to the timestamp in each frame; for example, a high value is given on a recent signal. We expected that this data representation could capture the features, especially of moving objects, because timestamp represents the movement direction and speed. By using this proposal method, we made our own dataset by DVS fixed on a parked car to develop an application for a surveillance system that can detect persons around the car. We think DVS is one of the ideal sensors for surveillance purposes because this sensor can run for a long time with low energy consumption in a NOT dynamic situation. For comparison purposes, we reproduced state of the art method as a benchmark, which makes frames the same as us and feeds polarity information to CNN. Then, we measured the object detection performances of the benchmark and ours on the same dataset. As a result, our method achieved a maximum of 7 points greater than the benchmark in the F1 score.

Keywords: event camera, dynamic vision sensor, deep learning, data representation, object recognition, low energy consumption

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Authors: L. Ponomarenko, Rachid Kaouar

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Morocco has rejoined the African Union and more than 30 years after it left the continental body due to the recognition of the Arabic Republic of Western Sahara. Morocco was readmitted after a one year campaign led by the King himself, who was visiting the Eastern African country with the aim to expend the kingdom presence in new region in Africa after that it managed to build a large influence net in the West Africa region. The return of Morocco can be a beginning of a new era in the foreign policy of Morocco, specially, in the policy towards the state-quo of the Western Sahara conflict, which is considerate as one the biggest obstacle for the cooperation and integration process in the region of North Africa. As a member-state of the African Union Morocco has lot more to lose, according to that the Moroccan position must be more flexible.

Keywords: African Union, Algeria, Morocco, North African Region, Western Sahara

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Authors: Hetvi Trivedi

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Technological escalation cannot be negated. The same is true for the benefits of technology. However, such escalation has interfered with the traditional theories of protection under Intellectual Property Rights. Out of the many trends that have disrupted the old-school understanding of Intellectual Property Rights, one is hashtags. What began modestly in the year 2007 has now earned a remarkable status, and coupled with the unprecedented rise in social media the hashtag culture has witnessed a monstrous growth. A tiny symbol on the keypad of phones or computers is now a major trend which also serves companies as a critical investment measure in establishing their brand in the market. Due to this a section of the Intellectual Property Rights- Trademarks is undergoing a humungous transformation with hashtags like #icebucket, #tbt or #smilewithacoke, getting trademark protection. So, as the traditional theories of IP take on the modern trends, it is necessary to understand the change and challenge at a theoretical and proportional level and where need be, question the change. Traditionally, Intellectual Property Rights serves the societal need for intellectual productions that ensure its holistic development as well as cultural, economic, social and technological progress. In a two-pronged effort at ensuring continuity of creativity, IPRs recognize the investment of individual efforts that go into creation by way of offering protection. Commonly placed under two major theories- Utilitarian and Natural, IPRs aim to accord protection and recognition to an individual’s creation or invention which serve as an incentive for further creations or inventions, thus fully protecting the creative, inventive or commercial labour invested in the same. In return, the creator by lending the public the access to the creation reaps various benefits. This way Intellectual Property Rights form a ‘social contract’ between the author and society. IPRs are similarly attached to a social function, whereby individual rights must be weighed against competing rights and to the farthest limit possible, both sets of rights must be treated in a balanced manner. To put it differently, both the society and the creator must be put on an equal footing with neither party’s rights subservient to the other. A close look through doctrinal research, at the recent trend of trademark protection, makes the social function of IPRs seem to be moving far from the basic philosophy. Thus, where technology interferes with the philosophies of law, it is important to check and allow such growth only in moderation, for none is superior than the other. The human expansionist nature may need everything under the sky that can be tweaked slightly to be counted and protected as Intellectual Property- like a common parlance word transformed into a hashtag, however IP in order to survive on its philosophies needs to strike a balance. A unanimous global decision on the judicious use of IPR recognition and protection is the need of the hour.

Keywords: hashtag trademarks, intellectual property, social function, technology

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Authors: Colin Smith, Linsey S Passarella

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Due to the proliferation and decentralized nature of academic publication, no widely accepted scheme exists for organizing papers by their scientific field of study (FoS) to the author’s best knowledge. While many academic journals require author provided keywords for papers, these keywords range wildly in scope and are not consistent across papers, journals, or field domains, necessitating alternative approaches to paper classification. Past attempts to perform field-of-study (FoS) classification on scientific texts have largely used a-hierarchical FoS schemas or ignored the schema’s inherently hierarchical structure, e.g. by compressing the structure into a single layer for multi-label classification. In this paper, we introduce an application of a Layered Neural Network (LNN) to the problem of performing supervised hierarchical classification of scientific fields of study (FoS) on research papers. In this approach, paper embeddings from a pretrained language model are fed into a top-down LNN. Beginning with a single neural network (NN) for the highest layer of the class hierarchy, each node uses a separate local NN to classify the subsequent subfield child node(s) for an input embedding of concatenated paper titles and abstracts. We compare our LNN-FOS method to other recent machine learning methods using the Microsoft Academic Graph (MAG) FoS hierarchy and find that the LNN-FOS offers increased classification accuracy at each FoS hierarchical level.

Keywords: hierarchical classification, layer neural network, scientific field of study, scientific taxonomy

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Authors: Dan Ohev Zion, Alon Cohen

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In recent years, the presence of short-range millimeter-wave radar in civil application has increased significantly. Autonomous driving, security, 3D imaging and high data rate communication systems are a few examples. The next challenge is the integration inside small form-factor devices, such as smartphones (e.g. gesture recognition). The main challenge is implementation of a truly low-power, low-complexity high-resolution radar. The most popular approach is the Frequency Modulated Continuous Wave (FMCW) radar, with an analog multiplication front-end. In this paper, we present an approach for adaptive estimation and correction of impairments of such front-end, specifically implemented using the Six-Port Device (SPD) as the multiplier element. The proposed algorithm was simulated and implemented on a 60 GHz radar lab prototype.

Keywords: radar, FMCW Radar, IQ mismatch, six port

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Authors: Tudor Barbu

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An automatic moment-based texture segmentation approach is proposed in this paper. First, we describe the related work in this computer vision domain. Our texture feature extraction, the first part of the texture recognition process, produces a set of moment-based feature vectors. For each image pixel, a texture feature vector is computed as a sequence of area moments. Second, an automatic pixel classification approach is proposed. The feature vectors are clustered using some unsupervised classification algorithm, the optimal number of clusters being determined using a measure based on validation indexes. From the resulted pixel classes one determines easily the desired texture regions of the image.

Keywords: image segmentation, moment-based, texture analysis, automatic classification, validation indexes

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Authors: Ruchi Agarwal

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The Indian diaspora in Thailand is as ethnically diverse as any other country. Although a relatively small community, the Indian diaspora has long established its roots, some with their fifth generation now living in Thailand. The community has a solid social and economic standing recognized by the host country but lacks connections with its ethnic roots in the home country. The biggest dilemma faced by the younger generation of the Indian diasporic community is the identity crisis. Regardless of being born and brought up in Thailand and possessing Thai citizenship, they do not get recognition as Thais by their Thai counterparts. However, with the Act Asia Policy of the Indian government, there has been an increase in social and political activities organized by old and new Indian associations, bringing new hopes of recognizing the Thai-Indian diasporic community.

Keywords: Indian, Thailand, diaspora, Act East Policy, Thai

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Authors: Zhou Yang, Heli Sun, Jianbin Huang, Jizhong Zhao, Shaojie Qiao

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Traffic prediction is essential in a multitude of ways in modern urban life. The researchers of earlier work in this domain carry out the investigation chiefly with two major focuses: (1) the accurate forecast of future values in multiple time series and (2) knowledge extraction from spatial-temporal correlations. However, two key considerations for traffic prediction are often missed: the completeness of raw data and the full context of the prediction timestamp. Concentrating on the two drawbacks of earlier work, we devise an approach that can address these issues in a two-phase framework. First, we utilize the raw trajectories to a greater extent through building a VLA table and data compression. We obtain the intra-trajectory features with graph-based encoding and the intertrajectory ones with a grid-based model and the technique of back projection that restore their surrounding high-resolution spatial-temporal environment. To the best of our knowledge, we are the first to study direct feature extraction from raw trajectories for traffic prediction and attempt the use of raw data with the least degree of reduction. In the prediction phase, we provide a broader context for the prediction timestamp by taking into account the information that are around it in the training dataset. Extensive experiments on several well-known datasets have verified the effectiveness of our solution that combines the strength of raw trajectory data and prediction context. In terms of performance, our approach surpasses several state-of-the-art methods for traffic prediction.

Keywords: traffic prediction, raw data utilization, context building, data reduction

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Authors: Blaž Likozar, Andraž Pavlišič, Matic Pavlin, Taja Žibert, Aleksandra Zamljen, Sašo Gyergyek, Matej Huš

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Ammonia is gaining recognition as a carbon-free fuel for energy-intensive applications, particularly transportation, industry, and power generation. Due to its physical properties, high energy density of 3 kWh kg-1, and high gravimetric hydrogen capacity of 17.6 wt%, ammonia is an efficient energy vector for green hydrogen, capable of mitigating hydrogen’s storage, distribution, and infrastructure deployment limitations. Chemicalstorage in the form of ammonia provides an efficient and affordable solution for energy storage, which is currently a critical step in overcoming the intermittency of abundant renewable energy sources with minimal or no environmental impact. Experiments were carried out to validate the modelling in a packed bed reactor, which proved to be agreeing.

Keywords: hydrogen, ammonia, catalysis, modelling, kinetics

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Authors: Boon Lee

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Research publication is an essential output of universities because it not only promotes university recognition, it also receives government funding. The history of university research culture has been one of ‘publish or perish’ and universities have consistently encouraged their academics and researchers to produce research articles in reputable journals in order to maintain a level of competitiveness. In turn, the United Kingdom (UK) government funding is determined by the number and quality of research publications. This paper aims to investigate on whether more government funding leads to more quality papers. To that end, the paper employs a Network DEA model to evaluate the UK higher education performance over a period. Sources of efficiency are also determined via second stage regression analysis.

Keywords: efficiency, higher education, network data envelopment analysis, universities

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Authors: Suk-Hyun Yu, Heeyong Kwon

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Recently PM-10 has become a social and global issue. It is one of major air pollutants which affect human health. Therefore, it needs to be forecasted rapidly and precisely. However, PM-10 comes from various emission sources, and its level of concentration is largely dependent on meteorological and geographical factors of local and global region, so the forecasting of PM-10 concentration is very difficult. Neural network model can be used in the case. But, there are few cases of high concentration PM-10. It makes the learning of the neural network model difficult. In this paper, we suggest a simple input balancing method when the data distribution is uneven. It is based on the probability of appearance of the data. Experimental results show that the input balancing makes the neural networks’ learning easy and improves the forecasting rates.

Keywords: artificial intelligence, air quality prediction, neural networks, pattern recognition, PM-10

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Authors: Mairaj Ahmad, L. Paglia, F. Marra, V. Genova, G. Pulci

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This study employed Rene N4 and FSX 414 superalloys, which are used in numerous turbine engine components due of their high strength, outstanding fatigue, creep, thermal, and corrosion-resistant properties. An in-depth examination of corrosion mechanisms with vapor present at high temperature is necessary given the industrial trend toward introducing increasing amounts of hydrogen into combustion chambers in order to boost power generation and minimize pollution in contrast to conventional fuels. These superalloys were oxidized in recent tests for 500, 1000, 2000, 3000 and 4000 hours at 982±5°C temperatures with a steady airflow at a flow rate of 10L/min and 1.5 bar pressure. These superalloys were also examined for wet corrosion for 500, 1000, 2000, 3000, and 4000 hours in a combination of air and water vapor flowing at a 10L/min rate. Weight gain, X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy dispersive x-ray spectroscopy (EDS) were used to assess the oxidation and heat corrosion resistance capabilities of these alloys before and after 500, 1000, and 2000 hours. The oxidation/corrosion processes that accompany the formation of these oxide scales are shown in the graph of mass gain vs time. In both dry and wet oxidation, oxides like Al2O3, TiO2, NiCo2O4, Ni3Al, Ni3Ti, Cr2O3, MnCr2O4, CoCr2O4, and certain volatile compounds notably CrO2(OH)2, Cr(OH)3, Fe(OH)2, and Si(OH)4 are formed.

Keywords: hot corrosion, oxidation, turbine materials, high temperature corrosion, super alloys

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Authors: P. Revathi, T. Mrunalini, K. Padma Priya, P. Ramya, R. Saranya

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During the tough times of covid, those people who were hospitalized found it difficult to always convey what they wanted to or needed to the attendee. Sometimes the attendees might also not be there. In that case, the patients can use simple hand gestures to control electrical appliances (like its set it for a zero watts bulb)and three other gestures for voice note intimation. In this AI-based hand recognition project, NodeMCU is used for the control action of the relay, and it is connected to the firebase for storing the value in the cloud and is interfaced with the python code via raspberry pi. For three hand gestures, a voice clip is added for intimation to the attendee. This is done with the help of Google’s text to speech and the inbuilt audio file option in the raspberry pi 4. All the 5 gestures will be detected when shown with their hands via a webcam which is placed for gesture detection. A personal computer is used for displaying the gestures and for running the code in the raspberry pi imager.

Keywords: onion harvesting, automatic pluging, camera, raspberry pi

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Authors: Seung-Un Chae, Heung-Yul Kim, Sa-Kil Kim

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This paper presents the findings of preliminary study on human control performance in case of fire. The relationship between human control and human decision is studied in decision processes and stress model of human in a fire. Human behavior aspects involved in the decision process during a fire incident. The decision processes appear that six of individual perceptual processes: recognition, validation, definition, evaluation, commitment, and reassessment. Then, human may be stressed in order to get an optimal decision for their activity. This paper explores problems in human control processes and stresses in a catastrophic situation. Thus, the future approach will be concerned to reduce stresses and ambiguous irrelevant information.

Keywords: human reliability, decision processes, stress model, fire

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Authors: Bounoua Nadia, Rebizi Mohamed Nadjib

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Chiral molecules in relation to particular biological roles are stereoselective. Enantiomers differ significantly in their biochemical responses in a biological environment. Despite the current advancement in drug discovery and pharmaceutical biotechnology, the chiral separation of some racemic mixtures continues to be one of the greatest challenges because the available techniques are too costly and time-consuming for the assessment of therapeutic drugs in the early stages of development worldwide. Various nanoparticles became one of the most investigated and explored nanotechnology-derived nanostructures, especially in chirality, where several studies are reported to improve the enantiomeric separation of different racemic mixtures. The production of surface-modified nanoparticles has contributed to these limitations in terms of sensitivity, accuracy, and enantioselectivity that can be optimized and therefore makes these surface-modified nanoparticles convenient for enantiomeric identification and separation.

Keywords: chirality, enantiomeric recognition, selectors, analysis, surface-modified nanoparticles

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Authors: Francis Deinmodei W. Poazi, Jasmine O. Tamunosiki-Amadi, Maurice Fems

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In recent times the resource-based view (RBV) of strategic management has recorded a sizeable attention yet there has not been a considerable scholarly and managerial discourse, debate and attention. As a result, this paper gives special bit of critical reasoning as well as top-notch analyses and relationship between RBV and organizational innovation. The study examines those salient aspects of RBV that basically have the will power in ensuring the organization's capacity to go for innovative capability. In achieving such fit and standpoint, the paper joins other relevant academic discourse and empirical evidence. To this end, a reasonable amount of contributions in setting the ground running for future empirical researches would have been provided. More so, the study is guided and built on the following strength and significance: Firstly, RBV sees resources as heterogeneity which forms a strong point of strength and allows organisations to gain competitive advantage. In order words, competitive advantage can be achieved or delivered to the organization when resources are distinctively utilized in a valuable manner more than the envisaged competitors of the organization. Secondly, RBV is significantly influential in determining the real resources that are available in the organization with a view to locate capabilities within in order to attract more profitability into the organization when applied. Thus, there will be more sustainable growth and success in the ever competitive and emerging market. Thus, to have succinct description of the basic methodologies, the study adopts both qualitative as well as quantitative approach with a view to have a broad samples of opinion in establishing and identifying key and strategic organizational resources to enable managers of resources to gain a competitive advantage as well as generating a sustainable increase and growth in profit. Furthermore, a comparative approach and analysis was used to examine the performance of RBV within the organization. Thus, the following are some of the findings of the study: it is clear that there is a nexus between RBV and growth of competitively viable organizations. More so, in most parts, organizations have heterogeneous resources domiciled in their organizations but not all organizations as it was specifically and intelligently adopting the tenets of RBV to strengthen heterogeneity of resources which allows organisations to gain competitive advantage. Other findings of this study reveal that of managerial perception of RBV with respect to application and transformation of resources to achieve a profitable end. It is against this backdrop, the importance of RBV cannot be overemphasized; the study is strongly convinced and think that RBV view is one focal and distinct approach that is focused on internal to outside strategy which engenders sourcing or generating resources internally as well as having the quest to apply such internally sourced resources diligently to increase or gain competitive advantage.

Keywords: resource-based view, innovation, organisation, recognition significant relationship and theoretical perspective

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Authors: Sukryool Kang, James McConnaughey, Robin Doroshow, Raj Shekhar

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Still’s murmur, a vibratory heart murmur, is the most common normal innocent murmur of childhood. Many children with this murmur are unnecessarily referred for cardiology consultation and testing, which exacts a high cost financially and emotionally on the patients and their parents. Pediatricians to date are not successful at distinguishing Still’s murmur from murmurs of true heart disease. In this paper, we present a new algorithmic approach to distinguish Still’s murmur from pathological murmurs in children. We propose two distinct features, spectral width and signal power, which describe the sharpness of the spectrum and the signal intensity of the murmur, respectively. Seventy pediatric heart sound recordings of 41 Still’s and 29 pathological murmurs were used to develop and evaluate our algorithm that achieved a true positive rate of 97% and false positive rate of 0%. This approach would meet clinical standards in recognizing Still’s murmur.

Keywords: AR modeling, auscultation, heart murmurs, Still's murmur

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Authors: Emily Moore, Dora Amos, Tracy Ellimah, Natasha Parrott

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Postoperative haematoma is a well-recognised complication of thyroid surgery with an incidence of 1-5%. Haematoma formation causes progressive airway obstruction, necessitating emergency bedside haematoma evacuation in up to ¼ of patients. ENT UK, BAETS and DAS have developed consensus guidelines to improve perioperative care, recommending that all healthcare staff interacting with patients undergoing thyroid surgery should be trained in managing post-thyroidectomy haematoma. The aim was to assess the effectiveness of a hybrid simulation model in improving clinician’s confidence in dealing with this surgical emergency. A hybrid simulation was designed, consisting of a standardised patient wearing a part-task trainer to mimic a post-thyroidectomy haematoma in a real patient. The part-task trainer was an adapted C-spine collar with layers of silicone representing the skin and strap muscles and thickened jelly representing the haematoma. Both the skin and strap muscle layers had to be opened in order to evacuate the haematoma. Boxes have been implemented into the appropriate post operative areas (recovery and surgical wards), which contain a printed algorithm designed to assist in remembering a sequence of steps for haematoma evacuation using the ‘SCOOP’ method (skin exposure, cut sutures, open skin, open muscles, pack wound) along with all the necessary equipment to open the front of the neck. Small-group teaching sessions were delivered by ENT and anaesthetic trainees to members of the multidisciplinary team normally involved in perioperative patient care, which included ENT surgeons, anaesthetists, recovery nurses, HCAs and ODPs. The DESATS acronym of signs and symptoms to recognise (difficulty swallowing, EWS score, swelling, anxiety, tachycardia, stridor) was highlighted. Then participants took part in the hybrid simulation in order to practice this ‘SCOOP’ method of haematoma evacuation. Participants were surveyed using a Likert scale to assess their level of confidence pre- and post teaching session. 30 clinicians took part. Confidence (agreed/strongly agreed) in recognition of post thyroidectomy haematoma improved from 58.6% to 96.5%. Confidence in management improved from 27.5% to 89.7%. All participants successfully decompressed the haematoma. All participants agreed/strongly agreed, that the sessions were useful for their learning. Multidisciplinary team simulation teaching is effective at significantly improving confidence in both the recognition and management of postoperative haematoma. Hybrid simulation sessions are useful and should be incorporated into training for clinicians.

Keywords: thyroid surgery, haematoma, teaching, hybrid simulation

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Authors: Moreblessings Shoko

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Polymersomes are materials which are considered as artificial counterparts of natural vesicles. The nanotechnology of such smart nanovesicles is very useful to enhance the efficiency of many therapeutic and diagnostic drugs. Those compounds show a higher stability, flexibility, and mechanical strength to the membrane compared to natural liposomes. Also, they can be designed in detail, the permeability of the membrane can be controlled by different stimuli, and the surface can be functionalized with different biological molecules to facilitate monitoring and target. For this purpose, this study demonstrates the formation of multifunctional and pH sensitive polymersomes and their functionalization with different reactive groups or biomolecules inside and outside of polymersomes´ membrane providing by crossing the membrane and docking/undocking processes for biomedical applications. Overall, they are highly versatile and thus present new opportunities for the design of targeted and selective recognition systems, for example, in mimicking cell functions and in synthetic biology.

Keywords: women, geomatics, challenges, capacity building

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Authors: Agil Gemilang Ramadhan, Novian Triandanu

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Since 1929, the first appearance in sea level, Anak Krakatau volcano growth relatively quickly. During the 80 years up to 2010 has reached the height of 320 meter above sea level. The possibility of catastrophic explosive eruption could happen again if the chemical composition of rocks from the eruption changed from alkaline magma into acid magma. Until now Anak Krakatau volcanic activity is still quite active as evidenced by the frequency of eruptions that produced ash sized pyroclastic deposits - bomb. Purpose of this study was to identify changes in the percentage of rock geochemistry any results eruption of Anak Krakatau volcano to see consistency change the percentage content of silica in the magma that affect the type of volcanic eruptions. Results from this study will be produced in the form of a diagram the data changes the chemical composition of rocks of Anak Krakatau volcano. Changes in the composition of any silica eruption are illustrated in a graph. If the increase in the percentage of silica is happening consistently and it is assumed to increase in the time scale of a few percent, then to achieve silica content of 68 % (acid composition) that will produce an explosive eruption will know the approximate time. All aspects of the factors driving the increased threat of danger to the public should be taken into account. Catastrophic eruption katatropis mitigation can be planned early so that when these disasters happen later, casualties can be minimized.

Keywords: Krakatau volcano, rock geochemistry, catastrophic eruption, mitigation

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Authors: Shao Qi

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The article uses the CiteSpace knowledge graph analysis tool to sort and visualize the journal literature on urban plants and habitats in the Web of Science and China National Knowledge Infrastructure databases. Based on a comprehensive interpretation of the visualization results of various data sources and the description of the intrinsic relationship between high-frequency keywords using knowledge mapping, the research hotspots, processes and evolution trends in this field are analyzed. Relevant case studies are also conducted for the hotspot contents to explore the means of landscape intervention and synthesize the understanding of research theories. The results show that (1) from 1999 to 2022, the research direction of urban plants and habitats gradually changed from focusing on plant and animal extinction and biological invasion to the field of human urban habitat creation, ecological restoration, and ecosystem services. (2) The results of keyword emergence and keyword growth trend analysis show that habitat creation research has shown a rapid and stable growth trend since 2017, and ecological restoration has gained long-term sustained attention since 2004. The hotspots of future research on urban plants and habitats in China may focus on habitat creation and ecological restoration.

Keywords: research trends, visual analysis, habitat creation, ecological restoration

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Authors: Shashi Pingolia

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The paper discusses best practices developed and followed by 07 'Maharatna' Central Public sector Enterprises in India. The paper begins with brief analyses of the contribution of ‘Maharatna’ companies in the growth story of India Inc. Progressively; it enlists Human Resource practices and approach of these 'Maharatna' companies in the areas such as Recruitment, Pay structure, Employee Benefits and Development, Rewards and Recognition practices, Performance Management Systems, etc. In the later part of the paper, HR factors that led some of these 'Maharatna' companies from average employers to 'Best Place at Work' are discussed in brief.

Keywords: central public sector enterprises in India, Maharatna companies in India, human resource management, best place to work

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Authors: Venugopal Kummamuru

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Corporate Governance (CG) is of utmost importance for running a company ethically. It is essential for the growth and success of the corporation. It is intended to increase the accountability of an organization to the larger context of the business environment. The general principles of CG include and are related to Shareholder recognition, Stakeholder interests, and focus on Corporate Social Responsibility (CSR), Clear Board responsibilities, Ethical behavior, and Business transparency. Network Marketing Organizations (NMOs) focus on marketing through direct-sales using people who are associated with the organization but are not their employees. This paper tries to study the importance of Ethics and CSR in an NMO and suggest a basic guideline for CG in NMO(s). This paper could be used as a basis or starting point for conducting an in-depth research to understand the difference in CG practices between NMO(s) and other organizations and define a standard set of guidelines for CG practice.

Keywords: corporate governance, corporate responsibility, direct selling, network marketing

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Authors: Mohamed Hefnawy, Abdulrahman Al-Majed, Aymen Al-Suwailem

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Enantioseparation of drugs with multiple stereogenic centers is challenging. This study objectives to evaluate the efficiency of different mobilized and/or immobilized polysaccharide-based chiral stationary phases to separate enantiomers of some drugs containing multiple stereogenic centers namely indenolol, nadolol, labetalol. The critical mobile phase variables (composition of organic solvents, acid/base ratios) were carefully studied to compare the retention time and elution order of all isomers. Different chromatographic parameters such as capacity factor (k), selectivity (α) and resolution (Rs) were calculated. Experimental conditions and the possible chiral recognition mechanisms have been discussed.

Keywords: HPLC, polysaccharide columns, enantio-resolution, indenolol, nadolol, labetalol

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Authors: Shaleni Bajpai, Nancy Stephan

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Various designs of women’s kurtis with different styles, motifs and prints were available in market but none of the kurtis was found in army print. Mostly army prints are used for men’s wear like jackets, trousers, caps, bags. The main colours available in military prints were beige, parrot green, red, dark blue, light blue, orange, bottle green, pink and the original military green colour. As the original camouflage is banned in civil wears so the different variety and colours were used in this study to popularize army prints in women’s wear. The aim of this project was to construct different styles of women kurti’s with various colours of different military prints. Mood board, inspiration and colour board was prepared to design the kurtis. The fabric used for construction was army printed poplin and crepe. The designing and construction of kurti’s were divided into two categories such as - casual and party wear. Casual wear had simple silhouette like a-line, high-low and waist coat style whereas party wear included princess line, panelled and bandhani style. Structured questionnaire was prepared to assess the acceptance of newly designed kurtis with respect to colour combination, overall appearance and cost. Purposively sampling method was adopted for selection of respondents. Opinion was taken from 100 women of various age groups. The result and analysis was presented through graph and percentage. Kurtis in army print of both the categories were appreciated by the respondents.

Keywords: army, kurti, casual wear, party wear

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Authors: Rachael Collins, George Lafford

Abstract:

We report a case of a generally fit and a well 54-year-old gentleman who presented with a two-day history of worsening left-sided otorrhea, headache, neck stiffness, vomiting and pyrexia on the background of a seven-week history of OE. His condition progressed dramatically as he developed symptoms consistent with acute complete cervical cord syndrome with radiological evidence of skull base osteomyelitis, parapharyngeal, retropharyngeal and paravertebral abscesses and sigmoid sinus thrombus. Ultimately he made a significant, although not complete, recovery. This case is unique in demonstrating how OE can develop into a potentially life-threatening condition. It emphasizes the importance of early diagnosis and treatment of OE, the recognition of ‘red flag’ symptoms and highlights the importance of a multi-disciplinary team (MDT) approach when managing complex complications of OE.

Keywords: ENT, neurology, otology, MDT

Procedia PDF Downloads 149

Authors: Ioanna Taouki, Marie Lallier, David Soto

Abstract:

Metacognition refers to the capacity to reflect upon our own cognitive processes. Although there is an ongoing discussion in the literature on the role of metacognition in learning and academic achievement, little is known about its neurodevelopmental trajectories in early childhood, when children begin to receive formal education in reading. Here, we evaluate the metacognitive ability, estimated under a recently developed Signal Detection Theory model, of a cohort of children aged between 6 and 7 (N=60), who performed three two-alternative-forced-choice tasks (two linguistic: lexical decision task, visual attention span task, and one non-linguistic: emotion recognition task) including trial-by-trial confidence judgements. Our study has three aims. First, we investigated how metacognitive ability (i.e., how confidence ratings track accuracy in the task) relates to performance in general standardized tasks related to students' reading and general cognitive abilities using Spearman's and Bayesian correlation analysis. Second, we assessed whether or not young children recruit common mechanisms supporting metacognition across the different task domains or whether there is evidence for domain-specific metacognition at this early stage of development. This was done by examining correlations in metacognitive measures across different task domains and evaluating cross-task covariance by applying a hierarchical Bayesian model. Third, using robust linear regression and Bayesian regression models, we assessed whether metacognitive ability in this early stage is related to the longitudinal learning of children in a linguistic and a non-linguistic task. Notably, we did not observe any association between students’ reading skills and metacognitive processing in this early stage of reading acquisition. Some evidence consistent with domain-general metacognition was found, with significant positive correlations between metacognitive efficiency between lexical and emotion recognition tasks and substantial covariance indicated by the Bayesian model. However, no reliable correlations were found between metacognitive performance in the visual attention span and the remaining tasks. Remarkably, metacognitive ability significantly predicted children's learning in linguistic and non-linguistic domains a year later. These results suggest that metacognitive skill may be dissociated to some extent from general (i.e., language and attention) abilities and further stress the importance of creating educational programs that foster students’ metacognitive ability as a tool for long term learning. More research is crucial to understand whether these programs can enhance metacognitive ability as a transferable skill across distinct domains or whether unique domains should be targeted separately.

Keywords: confidence ratings, development, metacognitive efficiency, reading acquisition

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Authors: Fatemeh Zeinali Sehrig

Abstract:

This study aimed to evaluate the expression of miR-299-3p, DNMT1, DNMT3A, and DNMT3B in breast cancer samples and investigate their diagnostic significance. Using the GSE40525 and GSE45666, the miR-299-3p expression level was studied in breast cancer tissues. Also, the expression levels of DNMT1, DNMT3A, and DNMT3B were investigated by analyzing GSE61725, GSE86374, and GSE37751 datasets. The target genes were studied in terms of biological processes of molecular functions and cellular components. Consistent with the in silico results, miR-299-3p expression was substantially decreased in breast cancer tissues, and the expression levels of DNMT1, DNMT3A, and DNMT3B were considerably upregulated in breast cancer samples. It was found that the expression levels of miR-299-3p and DNMT1, DNMT3A, and DNMT3B could be valuable diagnostic tools for detecting breast cancer. Also, miR-299-3p downregulation may play a role in DNMT1, DNMT3A, and DNMT3B upregulation in breast cancer.

Keywords: breast cancer, miR-299-3p, DNMTs, GEO database

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Authors: Semeh Ben Salem, Sami Naouali, Moetez Sallami

Abstract:

The increasing amount of collected data has limited the performance of the current analyzing algorithms. Thus, developing new cost-effective algorithms in terms of complexity, scalability, and accuracy raised significant interests. In this paper, a modified effective k-means based algorithm is developed and experimented. The new algorithm aims to reduce the computational load without significantly affecting the quality of the clusterings. The algorithm uses the City Block distance and a new stop criterion to guarantee the convergence. Conducted experiments on a real data set show its high performance when compared with the original k-means version.

Keywords: pattern recognition, global terrorism database, Manhattan distance, k-means clustering, terrorism data analysis

Procedia PDF Downloads 386