Search results for: processing individual

Authors: Mohammad Javad Mollakazemi, Farhad Asadi, Aref Ghafouri

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In this paper, we considered and applied parametric modeling for some experimental data of dynamical system. In this study, we investigated the different distribution of output measurement from some dynamical systems. Also, with variance processing in experimental data we obtained the region of nonlinearity in experimental data and then identification of output section is applied in different situation and data distribution. Finally, the effect of the spanning the measurement such as variance to identification and limitation of this approach is explained.

Keywords: Gaussian process, nonlinearity distribution, particle filter, system identification

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Authors: Si-Gwan Kim

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Small-size and low-power sensors with sensing, signal processing and wireless communication capabilities is suitable for the wireless sensor networks. Due to the limited resources and battery constraints, complex routing algorithms used for the ad-hoc networks cannot be employed in sensor networks. In this paper, we propose node-disjoint multi-path hexagon-based routing algorithms in wireless sensor networks. We suggest the details of the algorithm and compare it with other works. Simulation results show that the proposed scheme achieves better performance in terms of efficiency and message delivery ratio.

Keywords: clustering, multi-path, routing protocol, sensor network

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Authors: A. Alexandru, C. A. Alexandru, D. Coardos, E. Tudora

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Big Data (BD) is associated with a new generation of technologies and architectures which can harness the value of extremely large volumes of very varied data through real time processing and analysis. It involves changes in (1) data types, (2) accumulation speed, and (3) data volume. This paper presents the main concepts related to the BD paradigm, and introduces architectures and technologies for BD and BD sets. The integration of BD with the Hadoop Framework is also underlined. BD has attracted a lot of attention in the public sector due to the newly emerging technologies that allow the availability of network access. The volume of different types of data has exponentially increased. Some applications of BD in the public sector in Romania are briefly presented.

Keywords: big data, big data analytics, Hadoop, cloud

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Authors: Yaeji Lim, Hee-Seok Oh

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The coherence analysis measures the linear time-invariant relationship between two data sets and has been studied various fields such as signal processing, engineering, and medical science. However classical coherence analysis tends to be sensitive to outliers and focuses only on mean relationship. In this paper, we generalized cross periodogram to quantile cross periodogram and provide richer inter-relationship between two data sets. This is a general version of Laplace cross periodogram. We prove its asymptotic distribution under the long range process and compare them with ordinary coherence through numerical examples. We also present real data example to confirm the usefulness of quantile coherence analysis.

Keywords: coherence, cross periodogram, spectrum, quantile

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Authors: Rupali Chaudhary

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Shakespeare has been widely revisited by dramatists, critics, filmmakers and scholars around the globe. Shakespeare's kaleidoscopic work has been borrowed and redesigned into resonant patterns by artists, thus weaving myriad manifestations to pick from. Along with adaptation into wholly verbal medium (e.g., translations) the practice of indigenization through performing arts has played a great role in amplifying the reach of plays. The proliferation of Shakespeare's oeuvre commenced with the spread of colonialism itself. The plays illustrating the core values of Western tradition were introduced in the colonies. Therefore, the colonial domination extended to cultural domination. The plays were translated and adapted by the locals at times as it is and sometimes intermingled with the altered landscape and culture. The present paper discusses the global dimensions of Shakespearean cinema along with the historical cinematic shift from silent era to spoken dialogue in multiple languages. The methodology followed is descriptive in nature, and related information is availed from related literature, i.e., books, research articles and films. America and Europe dominated the silent era Shakespearean film production, thereby giving the term 'global' a less broad meaning. Five nations that dominated silent Shakespearean cinema were the United States, England, Italy, France, and Germany. Gradually the work of the exemplary figure with artistic and literary greatness surpassed the boundaries of the colonies and became a global legacy. Presently apart from English speaking nations Shakespearean films have been shot or produced in many of non-Anglophone locales. The findings indicate that when discussing about global dimensions of Shakespearean cinema various factors can be considered: involvement of actors and directors of foreign origin, transportability and universal comprehensibility of visual imagery across geographical borders, commodification of art or West's use of it as a tool of cultural hegemony or promotion of international amity, propagation of interculturalism through individual director's cultural translations and localization of Western art. Understanding of Shakespeare as a global export also depends on how an individual Shakespearean film works. Shakespeare's global appeal for cinema does not reside alone in his exquisite writings, distinctive characters, the setting, the story and the plots that have nurtured cinema since the medium's formative years. Shakespeare's global cinematic appeal is present in the spirit of cinema itself, i.e., the moving images capturing human behaviour and emotions that the plays invoke in audiences.

Keywords: adaptation, global dimensions, Shakespeare, Shakespearean cinema

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Authors: Lily Ye

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The contemporary fashion industry has witnessed the global rise of Chinese fashion designers. China plays more and more important role in this sector globally. One of the key debates in contemporary time is the conception of Chinese fashion. A close look at previous discussions on Chinese fashion reveals that most of them are explored through the lens of cultural knowledge and assumptions, using the dichotomous models of East and West. The results of these studies generate an essentialist and orientalist notion of Chinoiserie and Chinese fashion, which sees individual designers from China as undifferential collective members marked by a unique and fixed set of cultural scripts. This study challenges this essentialist conceptualization and brings fresh insights to the discussion of Chinese fashion identity against the backdrop of globalisation. Different from a culturalist approach to researching Chinese fashion, this paper presents an alternative position to address the research agenda through the mobilisation of Giddens’ (1991) theory of reflexive identity formation, privileging individuals’ agency and reflexivity. This approach to the discussion of identity formation not only challenges the traditional view seeing identity as the distinctive and essential characteristics belonging to any given individual or shared by all members of a particular social category or group but highlights fashion designers’ strategic agency and their role as fashion activist. This study draws evidence from a textual analysis of published stories of a group of established Chinese designers such as Guo Pei, Huishan Zhang, Masha Ma, Uma Wang, and Ma Ke. In line with Giddens’ concept of 'reflexive project of the self', this study uses a narrative methodology. Narratives are verbal accounts or stories relating to experiences of Chinese fashion designers. This approach offers the fashion designers a chance to 'speak' for themselves and show the depths and complexities of their experiences. It also emphasises the nuances of identity formation in fashion designers, whose experiences cannot be captured in neat typologies. Thematic analysis (Braun and Clarke, 2006) is adopted to identify and investigate common themes across the whole dataset. At the centre of the analysis is individuals’ self-articulation of their perceptions, experiences and themselves in relation to culture, fashion and identity. The finding indicates that identity is constructed around anchors such as agency, cultural hybridity, reflexivity and sustainability rather than traditional collective categories such as culture and ethnicity. Thus, the old East-West dichotomy is broken down, and essentialised social categories are challenged by the multiplicity and fragmentation of self and cultural hybridity created within designers’ 'small narratives'.

Keywords: Chinoiserie, fashion identity, fashion activism, narrative inquiry

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Authors: Mitat Uysal, Aynur Uysal

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Artificial Intelligence (AI) is fundamentally driven by mathematics, with many of its core algorithms rooted in mathematical principles such as linear algebra, probability theory, calculus, and optimization techniques. This paper explores the deep connection between AI and mathematics, highlighting the role of mathematical concepts in key AI techniques like machine learning, neural networks, and optimization. To demonstrate this connection, a case study involving the implementation of a neural network using Python is presented. This practical example illustrates the essential role that mathematics plays in training a model and solving real-world problems.

Keywords: AI, mathematics, machine learning, optimization techniques, image processing

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Authors: Saif Al Ghafri, Thomas Hughes, Armand Karimi, Kumarini Seneviratne, Jordan Oakley, Michael Johns, Eric F. May

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Knowledge of the thermophysical properties of complex mixtures at extreme conditions of pressure and temperature have always been essential to the Liquefied Natural Gas (LNG) industry’s evolution because of the tremendous technical challenges present at all stages in the supply chain from production to liquefaction to transport. Each stage is designed using predictions of the mixture’s properties, such as density, viscosity, surface tension, heat capacity and phase behaviour as a function of temperature, pressure, and composition. Unfortunately, currently available models lead to equipment over-designs of 15% or more. To achieve better designs that work more effectively and/or over a wider range of conditions, new fundamental property data are essential, both to resolve discrepancies in our current predictive capabilities and to extend them to the higher-pressure conditions characteristic of many new gas fields. Furthermore, innovative experimental techniques are required to measure different thermophysical properties at high pressures and over a wide range of temperatures, including near the mixture’s critical points where gas and liquid become indistinguishable and most existing predictive fluid property models used breakdown. In this work, we present a wide range of experimental measurements made for different binary and ternary mixtures relevant to LNG processing, with a particular focus on viscosity, surface tension, heat capacity, bubble-points and density. For this purpose, customized and specialized apparatus were designed and validated over the temperature range (200 to 423) K at pressures to 35 MPa. The mixtures studied were (CH4 + C3H8), (CH4 + C3H8 + CO2) and (CH4 + C3H8 + C7H16); in the last of these the heptane contents was up to 10 mol %. Viscosity was measured using a vibrating wire apparatus, while mixture densities were obtained by means of a high-pressure magnetic-suspension densimeter and an isochoric cell apparatus; the latter was also used to determine bubble-points. Surface tensions were measured using the capillary rise method in a visual cell, which also enabled the location of the mixture critical point to be determined from observations of critical opalescence. Mixture heat capacities were measured using a customised high-pressure differential scanning calorimeter (DSC). The combined standard relative uncertainties were less than 0.3% for density, 2% for viscosity, 3% for heat capacity and 3 % for surface tension. The extensive experimental data gathered in this work were compared with a variety of different advanced engineering models frequently used for predicting thermophysical properties of mixtures relevant to LNG processing. In many cases the discrepancies between the predictions of different engineering models for these mixtures was large, and the high quality data allowed erroneous but often widely-used models to be identified. The data enable the development of new or improved models, to be implemented in process simulation software, so that the fluid properties needed for equipment and process design can be predicted reliably. This in turn will enable reduced capital and operational expenditure by the LNG industry. The current work also aided the community of scientists working to advance theoretical descriptions of fluid properties by allowing to identify deficiencies in theoretical descriptions and calculations.

Keywords: LNG, thermophysical, viscosity, density, surface tension, heat capacity, bubble points, models

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Authors: Abbas Cheraghi

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A key predistribution scheme provides one method to distribute secret ahead of time. Blom’s scheme is a symmetric threshold key exchange protocol in cryptography. The scheme was proposed by the Swedish cryptographer Rolf Blom. In this kind of scheme, trusted authority gives each user a secret key and a public identifier, which enables any two users to create independently a shared key for communicating between each other. However, if an attacker can compromise the keys of at least Known numbers of users, he can break the scheme and reconstruct every shared key. In this paper generalized Blom’s Scheme by multivariate Lagrange interpolation formula. This scheme is a form of threshold secret sharing scheme. In this new scheme, the amount of information transmitted by the trusted authority is independent of the numbers of users. In addition, this scheme is unconditionally secure against any individual user.

Keywords: key predistribution, blom’s scheme, secret sharing, unconditional secure

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Authors: Bonnie Clough, Tamara Ownsworth, Vladimir Estivill-Castro, Matt Stainer, Rene Hexel, Andrew Bulmer, Wendy Moyle, Allison Waters, David Neumann, Jayke Bennett

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The success of global vaccination programs is reliant on the uptake of vaccines to achieve herd immunity. Yet, many individuals do not obtain vaccines or venipuncture procedures when needed. Whilst health education may be effective for those individuals who are hesitant due to safety or efficacy concerns, for many of these individuals, the primary concern relates to blood or injection fear or phobia (BII). BII is highly prevalent and associated with a range of negative health impacts, both at individual and population levels. Exposure therapy is an efficacious treatment for specific phobias, including BII, but has high patient dropout and low implementation by therapists. Whilst virtual reality approaches exposure therapy may be more acceptable, they have similarly low rates of implementation by therapists and are often difficult to tailor to an individual client’s needs. It was proposed that a piloted robot may be able to adequately facilitate fear induction and be an acceptable approach to exposure therapy. The current study examined fear induction responses, acceptability, and feasibility of a piloted robot for BII exposure. A Nao humanoid robot was programmed to connect with a virtual reality head-mounted display, enabling live streaming and exploration of real environments from a distance. Thirty adult participants with BII fear were randomly assigned to robot-pilot or virtual reality exposure conditions in a laboratory-based fear exposure task. All participants also completed a computer-based two-dimensional exposure task, with an order of conditions counterbalanced across participants. Measures included fear (heart rate variability, galvanic skin response, stress indices, and subjective units of distress), engagement with a feared stimulus (eye gaze: time to first fixation and a total number of fixations), acceptability, and perceived treatment credibility. Preliminary results indicate that fear responses can be adequately induced via a robot-piloted platform. Further results will be discussed, as will implications for the treatment of BII phobia and other fears. It is anticipated that piloted robots may provide a useful platform for facilitating exposure therapy, being more acceptable than in-vivo exposure and more flexible than virtual reality exposure.

Keywords: anxiety, digital mental health, exposure therapy, phobia, robot, virtual reality

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Authors: Jan Barak, Karel Frana, Joerg Stiller

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This work presents results of moist air condensation in heat exchanger. It describes theoretical knowledge and definition of moist air. Model with geometry of square canal was created for better understanding and post processing of condensation phenomena. Different approaches were examined on this model to find suitable software and model. Obtained knowledge was applied to geometry of real heat exchanger and results from experiment were compared with numerical results. One of the goals is to solve this issue without creating any user defined function in the applied code. It also contains summary of knowledge and outlook for future work.

Keywords: condensation, exchanger, experiment, validation

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Authors: Indu Gaur, Neha Bhadauria, Shilpi Shilpi, Susmita Goswami, Prem D. Sharma, Prabir K. Paul

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The concept of organic agriculture has been accepted as novelty in Indian society, but there is no data available on the human pathogens colonizing plant parts due to such practices. Also, the pattern and mechanism of their colonization need to be understood in order to devise possible strategies for their prevention. In the present study, human pathogenic bacteria were isolated from organically grown tomato plants and five of them were identified as Klebsiella pneumoniae, Enterobacter ludwigii, Serratia fonticola, Stenotrophomonas maltophilia and Chryseobacterium jejuense. Tomato plants were grown in controlled aseptic conditions with 25±1˚C, 70% humidity and 12 hour L/D photoperiod. Six weeks old plants were divided into 6 groups of 25 plants each and treated as follows: Group 1: K. pneumonia, Group 2: E. ludwigii, Group 3: S. fonticola, Group 4: S. maltophilia, Group 5: C. jejuense, Group 6: Sterile distilled water (control). The inoculums for all treatments were prepared by overnight growth with uniform concentration of 108 cells/ml. Leaf samples from above groups were collected at 0.5, 2, 4, 6 and 24 hours post inoculation for the colony forming unit counts (CFU/cm2 of leaf area) of individual pathogens using leaf impression method. These CFU counts were used for the in vivo colonization assay and adherence assay of individual pathogens. Also, resistance of these pathogens to at least 12 antibiotics was studied. Based on these findings S. fonticola was found to be most prominently colonizing the phylloplane of tomato and was further studied. Tomato plants grown in controlled aseptic conditions same as mentioned above were divided into 2 groups of 25 plants each and treated as follows: Group 1: S. fonticola, Group 2: Sterile distilled water (control). Leaf samples from above groups were collected at 0, 24, 48, 72 and 96 hours post inoculation and homogenized in suitable buffers for surface and cell wall protein isolation. Protein samples thus obtained were subjected to isocratic SDS-gel electrophoresis and analyzed. It was observed that presence of S. fonticola could induce the expression of at least 3 additional cell wall proteins at different time intervals. Surface proteins also showed variation in the expression pattern at different sampling intervals. Further identification of these proteins by MALDI-MS and bioinformatics tools revealed the gene(s) involved in the interaction of S. fonticola with tomato phylloplane.

Keywords: cell wall proteins, human pathogenic bacteria, phylloplane, solanum lycopersicum

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Authors: M. Abderrahmane Mograne, Didier Laux, Jean-Yves Ferrandis

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Rheological characterizations of complex liquids like polymer solutions present an important scientific interest for a lot of researchers in many fields as biology, food industry, chemistry. In order to establish master curves (elastic moduli vs frequency) which can give information about microstructure, classical rheometers or viscometers (such as Couette systems) are used. For broadband characterization of the sample, temperature is modified in a very large range leading to equivalent frequency modifications applying the Time Temperature Superposition principle. For many liquids undergoing phase transitions, this approach is not applicable. That is the reason, why the development of broadband spectroscopic methods around room temperature becomes a major concern. In literature many solutions have been proposed but, to our knowledge, there is no experimental bench giving the whole rheological characterization for frequencies about a few Hz (Hertz) to many MHz (Mega Hertz). Consequently, our goal is to investigate in a nondestructive way in very broadband frequency (A few Hz – Hundreds of MHz) rheological properties using longitudinal ultrasonic waves (L waves), a unique experimental bench and a specific container for the liquid: a test tube. More specifically, we aim to estimate the three viscosities (longitudinal, shear and bulk) and the complex elastic moduli (M*, G* and K*) respectively longitudinal, shear and bulk moduli. We have decided to use only L waves conditioned in two ways: bulk L wave in the liquid or guided L waves in the tube test walls. In this paper, we will present first results for very low frequencies using the ultrasonic tracking of a falling ball in the test tube. This will lead to the estimation of shear viscosity from a few mPa.s to a few Pa.s (Pascal second). Corrections due to the small dimensions of the tube will be applied and discussed regarding the size of the falling ball. Then the use of bulk L wave’s propagation in the liquid and the development of a specific signal processing in order to assess longitudinal velocity and attenuation will conduct to the longitudinal viscosity evaluation in the MHz frequency range. At last, the first results concerning the propagation, the generation and the processing of guided compressional waves in the test tube walls will be discussed. All these approaches and results will be compared to standard methods available and already validated in our lab.

Keywords: nondestructive measurement for liquid, piezoelectric transducer, ultrasonic longitudinal waves, viscosities

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Authors: Seyedeh Belin Tavakoly Sany, Rosli Hashim, Majid Rezayi, Aishah Salleh, Omid Safari

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The purpose of this paper is to describe the main characteristics of macroinvertebrate species in response to environmental forcing factors. Overall, 23 species of Mollusca, 4 species of Arthropods, 3 species of Echinodermata and 3 species of Annelida were identified at the 9 sampling stations during four sampling periods. Individual species of Mollusca constituted 36.4% of the total abundance, followed by Arthropods (27.01%), Annelida (34.3%) and Echinodermata (2.4%). The results of Kruskal-Wallis test indicated that a significant difference (p <0.05) in the abundance, richness and diversity of the macro-benthic community in different stations. The correlation analysis revealed that anthropogenic pollution and natural variability caused by these variations in spatial scales.

Keywords: benthic invertebrates, diversity, abundance, West Port

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Authors: Yuzhi Cai

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In this paper, we discuss a Bayesian approach to quantile autoregressive (QAR) time series model estimation and forecasting. Together with a combining forecasts technique, we then predict USD to GBP currency exchange rates. Combined forecasts contain all the information captured by the fitted QAR models at different quantile levels and are therefore better than those obtained from individual models. Our results show that an unequally weighted combining method performs better than other forecasting methodology. We found that a median AR model can perform well in point forecasting when the predictive density functions are symmetric. However, in practice, using the median AR model alone may involve the loss of information about the data captured by other QAR models. We recommend that combined forecasts should be used whenever possible.

Keywords: combining forecasts, MCMC, predictive density functions, quantile forecasting, quantile modelling

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Authors: Khishig-Undrakh Mijgee, Yerkyejan Amanbyek, Yilina, Bayarkhuu Agvaanbayar, Anudari Chingiskhuu

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The study of happiness focuses on how people perceive their well-being, the ways they seek happiness, and the factors that affect their feelings of happiness, including self-esteem, depression, satisfaction, and the quality of life. Researchers also aim to explore the relationship between happiness, self-esteem, depression, satisfaction, and quality of life, with the goal of assessing people's sense of achievement. Happiness is strongly linked to an individual's sense of achievement and overall life satisfaction. In this article, we will discuss the findings of a study that examines the feelings of happiness and the factors that influence them among 562 high school students.

Keywords: happiness, high school students, feelings of happiness, happiness level

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Authors: Chantelle Francis, Karen McKenzie, Charlotte Emmerson

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In the context of the rise in mental health difficulties amongst pupils, this review explores the factors that have been indicated as affecting psychological well-being in mainstream school contexts. Search terms relating to school-based psychological well-being were entered into five databases, and twenty-two studies were included in the review. The results suggested that pupil psychological well-being is affected by both direct and indirect factors. The former included a sense of belonging and inclusion, relationships with teachers, and academic attainment. The latter included family socioeconomic status, whole-school approaches, and individual differences factors, such as gender and Special Educational Needs. The implications for policymakers and practitioners are discussed.

Keywords: psychological wellbeing, mainstream schools, special educational needs, school-based wellbeing

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Authors: Omid Saligheh

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Poly (tri methylene terephthalate) (PTT) nanofibers were prepared by electrospinning, being directly deposited in the form of a random fibers web. The effect of changing processing parameters such as solution concentration and electrospinning voltage on the morphology of the electrospun PTT nanofibers was investigated with scanning electron microscopy (SEM). The electrospun fibers diameter increased with rising concentration and decreased by increasing the electrospinning voltage, thermal and mechanical properties of electrospun fibers were characterized by DSC and tensile testing, respectively.

Keywords: poly tri methylene terephthalate, electrospinning, morphology, thermal behavior, mechanical properties

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Authors: Keshav Rathi, Aakriti Sharma, Vinayak R. Dinesh, Irfan Ramzan Parray

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Scheduling is a basic operating system function since practically all computer resources are scheduled before use. The CPU is one of the most important computer resources. Central Processing Unit (CPU) scheduling is vital because it allows the CPU to transition between processes. A processor is the most significant resource in a computer; the operating system can increase the computer's productivity. The objective of the operating system is to allow as many processes as possible to operate at the same time in order to maximize CPU utilization. The highly efficient CPU scheduler is based on the invention of high-quality scheduling algorithms that meet the scheduling objectives. In this paper, we reviewed various fundamental CPU scheduling algorithms for a single CPU and showed which algorithm is best for the particular situation.

Keywords: computer science, Operating system, CPU scheduling, cpu algorithms

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Authors: Ala Hanetite

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The purpose of this article is to present, by means of a model, the determinants of organisational culture which influence creativity and innovation. A literature study showed that a model, based on the open systems theory and the work of Schein, can offer a holistic approach in describing organisational culture. The relationship between creativity, innovation and culture is discussed in this context. Against the background of this model, the determinants of organisational culture were identified. The determinants are strategy, structure, support mechanisms, behaviour that encourages innovation, and open communication. The influence of each determinant on creativity and innovation is discussed. Values, norms and beliefs that play a role in creativity and innovation can either support or inhibit creativity and innovation depending on how they influence individual and group behaviour. This is also explained in the article.

Keywords: attitudes, creativity, innovation, organisational culture

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Authors: Ionel Botef

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Studies show that, for viable product realisation and maintenance, a spectrum of novel processing technologies and materials to improve performance and reduce costs and environmental impact must constantly be addressed. One of these technologies, namely the cold spray process, has enabled a broad range of coatings and applications, including many that have not been previously possible or commercially practical, hence its potential for new aerospace, electronics, or medical applications. Therefore, the purpose of this paper is to summarise the state of the art of this technology alongside its theoretical and experimental studies, and explore the role and impact of cold spraying on surface engineering.

Keywords: surface engineering, cold spray, ageing aircrafts, corrosion, microchannels, maintenance

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Authors: Ksenia Volkova, Artur Petrosyan, Ignatii Dubyshkin, Alexei Ossadtchi

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Brain-computer interfaces are a growing research field producing many implementations that find use in different fields and are used for research and practical purposes. Despite the popularity of the implementations using non-invasive neuroimaging methods, radical improvement of the state channel bandwidth and, thus, decoding accuracy is only possible by using invasive techniques. Electrocorticography (ECoG) is a minimally invasive neuroimaging method that provides highly informative brain activity signals, effective analysis of which requires the use of machine learning methods that are able to learn representations of complex patterns. Deep learning is a family of machine learning algorithms that allow learning representations of data with multiple levels of abstraction. This study explores the potential of deep learning approaches for ECoG processing, decoding movement intentions and the perception of proprioceptive information. To obtain synchronous recording of kinematic movement characteristics and corresponding electrical brain activity, a series of experiments were carried out, during which subjects performed finger movements at their own pace. Finger movements were recorded with a three-axis accelerometer, while ECoG was synchronously registered from the electrode strips that were implanted over the contralateral sensorimotor cortex. Then, multichannel ECoG signals were used to track finger movement trajectory characterized by accelerometer signal. This process was carried out both causally and non-causally, using different position of the ECoG data segment with respect to the accelerometer data stream. The recorded data was split into training and testing sets, containing continuous non-overlapping fragments of the multichannel ECoG. A deep convolutional neural network was implemented and trained, using 1-second segments of ECoG data from the training dataset as input. To assess the decoding accuracy, correlation coefficient r between the output of the model and the accelerometer readings was computed. After optimization of hyperparameters and training, the deep learning model allowed reasonably accurate causal decoding of finger movement with correlation coefficient r = 0.8. In contrast, the classical Wiener-filter like approach was able to achieve only 0.56 in the causal decoding mode. In the noncausal case, the traditional approach reached the accuracy of r = 0.69, which may be due to the presence of additional proprioceptive information. This result demonstrates that the deep neural network was able to effectively find a representation of the complex top-down information related to the actual movement rather than proprioception. The sensitivity analysis shows physiologically plausible pictures of the extent to which individual features (channel, wavelet subband) are utilized during the decoding procedure. In conclusion, the results of this study have demonstrated that a combination of a minimally invasive neuroimaging technique such as ECoG and advanced machine learning approaches allows decoding motion with high accuracy. Such setup provides means for control of devices with a large number of degrees of freedom as well as exploratory studies of the complex neural processes underlying movement execution.

Keywords: brain-computer interface, deep learning, ECoG, movement decoding, sensorimotor cortex

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Authors: Adrian W. Egger, Savvas P. Triantafyllou, Eleni N. Chatzi

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The scaled boundary finite element method (SBFEM) is a semi-analytical numerical method, which introduces a scaling center in each element’s domain, thus transitioning from a Cartesian reference frame to one resembling polar coordinates. Consequently, an analytical solution is achieved in radial direction, implying that only the boundary need be discretized. The only limitation imposed on the resulting polygonal elements is that they remain star-convex. Further arbitrary p- or h-refinement may be applied locally in a mesh. The polygonal nature of SBFEM elements has been exploited in quadtree meshes to alleviate all issues conventionally associated with hanging nodes. Furthermore, since in 2D this results in only 16 possible cell configurations, these are precomputed in order to accelerate the forward analysis significantly. Any cells, which are clipped to accommodate the domain geometry, must be computed conventionally. However, since SBFEM permits polygonal elements, significantly coarser meshes at comparable accuracy levels are obtained when compared with conventional quadtree analysis, further increasing the computational efficiency of this scheme. The generalized stress intensity factors (gSIFs) are computed by exploiting the semi-analytical solution in radial direction. This is initiated by placing the scaling center of the element containing the crack at the crack tip. Taking an analytical limit of this element’s stress field as it approaches the crack tip, delivers an expression for the singular stress field. By applying the problem specific boundary conditions, the geometry correction factor is obtained, and the gSIFs are then evaluated based on their formal definition. Since the SBFEM solution is constructed as a power series, not unlike mode superposition in FEM, the two modes contributing to the singular response of the element can be easily identified in post-processing. Compared to the extended finite element method (XFEM) this approach is highly convenient, since neither enrichment terms nor a priori knowledge of the singularity is required. Computation of the gSIFs by SBFEM permits exceptional accuracy, however, when combined with hybrid quadtrees employing linear elements, this does not always hold. Nevertheless, it has been shown that crack propagation schemes are highly effective even given very coarse discretization since they only rely on the ratio of mode one to mode two gSIFs. The absolute values of the gSIFs may still be subject to large errors. Hence, we propose a post-processing scheme, which minimizes the error resulting from the approximation space of the cracked element, thus limiting the error in the gSIFs to the discretization error of the quadtree mesh. This is achieved by h- and/or p-refinement of the cracked element, which elevates the amount of modes present in the solution. The resulting numerical description of the element is highly accurate, with the main error source now stemming from its boundary displacement solution. Numerical examples show that this post-processing procedure can significantly improve the accuracy of the computed gSIFs with negligible computational cost even on coarse meshes resulting from hybrid quadtrees.

Keywords: linear elastic fracture mechanics, generalized stress intensity factors, scaled finite element method, hybrid quadtrees

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Authors: Benalia Kouini, Aicha Serier

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Nanocomposites based on polypropylene/polyamide 66 (PP/PA66) nanoblends containing organophilic montmorillonite (OMMT) and maleic anhydride grafted polypropylene (PP-g-MAH) were prepared by melt compounding method followed by injection molding. Two different types of nanoclays were used in this work. DELLITE LVF is the untreated nanoclay and DELLITE 67G is the treated one. The morphology of the nanocomposites was studied using the XR diffraction (XRD). The results indicate that the incorporation of treated nanoclay has a significant effect on the impact strength of PP/PA66 nanocomposites. Furthermore, it was found that XRD results revealed the intercalation, exfoliation of nanaclays of nanocomposites.

Keywords: nNanoclay, Nanocomposites, Polypropylene, Polyamide, melt processing, mechanical properties.

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Authors: Najam U. Saqib

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Self-construal or an individual’s view of him or herself is an important variable by which culture affects the way people think and act. This notion of self-construal is identified with two distinct perspectives on the self. Within the independent construal, the self is seen as different from others, a way of defining the self, prominent in Western societies. The interdependent perspective which is typical for Eastern cultures emphasizes the connectedness of the self to others. The degree of independence-interdependence in one’s self-construal is thought to affect behavior, acceptance of social values, and decision making. This paper manipulates self-construal of Qatari consumers and investigates its effects on accepting incongruent changes in culture as a result of adopting market offerings and behavior that may be perceived as inconsistent with their self-construal. The research recommends strategies for policy makers in Qatar for successful advocacy of initiatives of national importance such as reducing diabetes and obesity by applying self-construal theory.

Keywords: cross-cultural, consumer behavior, self-construal, GCC (Gulf Cooperation Council)

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Authors: Corbel Camille, Le Cerf Flora, Capriz Françoise, Vaillant-Ciszewicz Anne-Julie, Breaud Jean, Guerin Olivier, Corveleyn Xavier

Abstract:

Background: The medical environment can generate stressful and anxiety-provoking situations for patients, particularly during painful care procedures for the older population. These stressful environments have deleterious effects on the quality of care and can even put the patient at risk and set the care team up for failure. The search for a solution is, therefore, imperative. The development of new technologies, such as virtual reality (VR), seems to be an answer to this problem. Objectives: The objective of this study is to compare the effects of virtual reality on pain and anxiety when caring for older hospitalized people with the effects of usual care. More precisely, different individual factors (age, cognitive level, individual preferences, etc.) and different virtual reality universes (personalized or non-personalized) are studied to understand the role of these factors in reducing pain and anxiety during care procedures. The aim of this study is to improve the quality of life of patients and caregivers in their work environment. Method: This mono-centered, randomized, controlled study was conducted from September 2023 to September 2024 on 120 participants recruited from the geriatric departments of the Cimiez Hospital, Nice, France. Participants are randomized into three groups: a control group, a personalized VR group and a non-personalized VR group. Each participant is followed during a painful care session. Data are collected before, during and after the care, using measures of pain (Algoplus and numerical scale) and anxiety (Hospital anxiety scale and numerical scale). Physiological assessments with an oximeter are also performed to collect both heart and respiratory rate measurements. The implementation of the care will be assessed among healthcare providers to evaluate its effects on the difficulty and fatigue associated with the care. Additionally, a questionnaire (System Usability Scale) will be administered at the conclusion of the study to determine the willingness of healthcare providers to integrate VR into their daily care practices. Result: The preliminary results indicate significant effects on anxiety (p=.001) and pain (p=<.001) following the VR intervention during care, as compared to the control group. Conclusion: The preliminary results suggest that VRI appears to be a suitable and effective method for reducing anxiety and pain among older hospitalized individuals compared with standard care. Finally, the experiences of healthcare professionals involved will also be considered to assess the impact of these interventions on working conditions and patient support.

Keywords: anxiety, care, pain, older adults, virtual reality

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Authors: Branimir Jurun, Elza Jurun

Abstract:

The focus of this paper is the description of an instrument called 'Quattuor 45' and defining of wave pressure measurement. Special attention is given to measurement of wave pressure created by the wind speed increasing obtained with the instrument 'Quattuor 45' in the investigated area. The study begins with respect to theoretical attitudes and numerous up to date investigations related to the waves approaching the coast. The detailed schematic view of the instrument is enriched with pictures from ground plan and side view. Horizontal stability of the instrument is achieved by mooring which relies on two concrete blocks. Vertical wave peak monitoring is ensured by one float above the instrument. The synthesis of horizontal stability and vertical wave peak monitoring allows to create a representative database for wave pressure measuring. Instrument ‘Quattuor 45' is named according to the way the database is received. Namely, the electronic part of the instrument consists of the main chip ‘Arduino', its memory, four load cells with the appropriate modules and the wind speed sensor 'Anemometers'. The 'Arduino' chip is programmed to store two data from each load cell and two data from the anemometer on SD card each second. The next part of the research is dedicated to data processing. All measured results are stored automatically in the database and after that detailed processing is carried out in the MS Excel. The result of the wave pressure measurement is synthesized by the unit of measurement kN/m². This paper also suggests a graphical presentation of the results by multi-line graph. The wave pressure is presented on the left vertical axis, while the wind speed is shown on the right vertical axis. The time of measurement is displayed on the horizontal axis. The paper proposes an algorithm for wind speed measurements showing the results for two characteristic winds in the Adriatic Sea, called 'Bura' and 'Jugo'. The first of them is the northern wind that reaches high speeds, causing low and extremely steep waves, where the pressure of the wave is relatively weak. On the other hand, the southern wind 'Jugo' has a lower speed than the northern wind, but due to its constant duration and constant speed maintenance, it causes extremely long and high waves that cause extremely high wave pressure.

Keywords: instrument, measuring unit, waves pressure metering, wind seed measurement

Procedia PDF Downloads 198

Authors: Snehal G. Teli, R. J. Shelke

Abstract:

CNN and MultiUNet models are the framework for the proposed method for enhancing and reconstructing underwater images. Multiscale merging of features and regeneration are both performed by the MultiUNet. CNN collects relevant features. Extensive tests on benchmark datasets show that the proposed strategy performs better than the latest methods. As a result of this work, underwater images can be represented and interpreted in a number of underwater applications with greater clarity. This strategy will advance underwater exploration and marine research by enhancing real-time underwater image processing systems, underwater robotic vision, and underwater surveillance.

Keywords: convolutional neural network, image enhancement, machine learning, multiunet, underwater images

Procedia PDF Downloads 75

Authors: Michal Brazda, Miroslav Urbanek, Martina Koukolikova

Abstract:

This work focuses on the development of functional surfaces and edges for cutting and forming tools created through the Directed Energy Deposition (DED) technology. In the context of growing challenges in modern engineering, additive technologies, especially DED, present an innovative approach to manufacturing tools for forming and cutting. One of the key features of DED is its ability to precisely and efficiently deposit Fully dense metals from powder feedstock, enabling the creation of complex geometries and optimized designs. Gradually, it becomes an increasingly attractive choice for tool production due to its ability to achieve high precision while simultaneously minimizing waste and material costs. Tools created using DED technology gain significant durability through the utilization of high-performance materials such as nickel alloys and tool steels. For high-temperature applications, Nimonic 80A alloy is applied, while for cold applications, M2 tool steel is used. The addition of ceramic materials, such as tungsten carbide, can significantly increase the tool's resistance. The introduction of functionally graded materials is a significant contribution, opening up new possibilities for gradual changes in the mechanical properties of the tool and optimizing its performance in different sections according to specific requirements. In this work, you will find an overview of individual applications and their utilization in the industry. Microstructural analyses have been conducted, providing detailed insights into the structure of individual components alongside examinations of the mechanical properties and tool life. These analyses offer a deeper understanding of the efficiency and reliability of the created tools, which is a key element for successful development in the field of cutting and forming tools. The production of functional surfaces and edges using DED technology can result in financial savings, as the entire tool doesn't have to be manufactured from expensive special alloys. The tool can be made from common steel, onto which a functional surface from special materials can be applied. Additionally, it allows for tool repairs after wear and tear, eliminating the need for producing a new part and contributing to an overall cost while reducing the environmental footprint. Overall, the combination of DED technology, functionally graded materials, and verified technologies collectively set a new standard for innovative and efficient development of cutting and forming tools in the modern industrial environment.

Keywords: additive manufacturing, directed energy deposition, DED, laser, cutting tools, forming tools, steel, nickel alloy

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Authors: Ploysai Ohama, Nuttawadee Hanchengchai, Thiva Saksri

Abstract:

Natural dye extracted from Pterocarpus indicus was applied to a cotton fabric and silk yarn by dyeing processing different eco-friendly mordants. Analytical studies such as UV–VIS spectrophotometry and gravimetric analysis were performed on the extracts. The color of each dyed material was investigated in terms of the CIELAB (L*, a* and b*) and K/S values. Cotton fabric dyed without mordants had a shade of greenish-brown, while those post-mordanted with selected eco-friendly mordants such as alum, lemon juice and limewater result in a variety of brown and darker color shade of fabric.

Keywords: natural dyes, plant materials, dyeing, mordant

Procedia PDF Downloads 415