Search results for: continuous

Authors: Malathi Iyer, Jayesh Vaidya

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The demographic dividend of India will last for thirty years from now. However, reduction in birth rate, an increase in working population, improvements in medicine and better health practices lead to an ever-expanding elderly population, bringing additional burden to the economy and putting an end to the demographic dividend. To reap the dividend India needs to train the youth for employability. The need of the hour is to improve their life skills which lead the youth to become industrious and have continuous employment. The study will be conducted in perceiving the skill gaps that exist in commerce students for employability. The analysis results indicate the relation between the core study and the right skills for the workforce, with the steps that are taken to open the window for the demographic dividend.

Keywords: demographic dividend, life skills, employability, workforce

Procedia PDF Downloads 521

Authors: Maier Dorin, Maier Andreea

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Today, any organization - regardless of the specific activity - must be prepared to face continuous radical changes, innovation thus becoming a condition of survival in a globalized market. Not all managers have an overall view on the real size of necessary innovation potential. Unfortunately there is still no common (and correct) understanding of the term of innovation among managers. Moreover, not all managers are aware of the need for innovation. This article highlights and analyzes a series of models of innovation processes and their evolution. The models analyzed encompass both the strategic level and the operational one within an organization, indicating performance innovation on each landing. As the literature review shows, there are no easy answers to the innovation process as there are no shortcuts to great results. Successful companies do not have a silver innovative bullet - they do not get results by making one or few things better than others, they make everything better.

Keywords: innovation, innovation process, business success, models of innovation

Procedia PDF Downloads 401

Authors: Vadim Kulikov

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The classical Stroop effect is the phenomenon that it takes more time to name the ink color of a printed word if the word denotes a conflicting color than if it denotes the same color. Over the last 80 years, there have been many variations of the experiment revealing various mechanisms behind semantic, attentional, behavioral and perceptual processing. The Stroop task is known to exhibit asymmetry. Reading the words out loud is hardly dependent on the ink color, but naming the ink color is significantly influenced by the incongruent words. This asymmetry is reversed, if instead of naming the color, one has to point at a corresponding color patch. Another debated aspects are the notions of automaticity and how much of the effect is due to semantic and how much due to response stage interference. Is automaticity a continuous or an all-or-none phenomenon? There are many models and theories in the literature tackling these questions which will be discussed in the presentation. None of them, however, seems to capture all the findings at once. A computational model is proposed which is based on the philosophical idea developed by the author that the mind operates as a collection of different information processing modalities such as different sensory and descriptive modalities, which produce emergent phenomena through mutual interaction and coherence. This is the framework theory where ‘framework’ attempts to generalize the concepts of modality, perspective and ‘point of view’. The architecture of this computational model consists of blocks of neurons, each block corresponding to one framework. In the simplest case there are four: visual color processing, text reading, speech production and attention selection modalities. In experiments where button pressing or pointing is required, a corresponding block is added. In the beginning, the weights of the neural connections are mostly set to zero. The network is trained using Hebbian learning to establish connections (corresponding to ‘coherence’ in framework theory) between these different modalities. The amount of data fed into the network is supposed to mimic the amount of practice a human encounters, in particular it is assumed that converting written text into spoken words is a more practiced skill than converting visually perceived colors to spoken color-names. After the training, the network performs the Stroop task. The RT’s are measured in a canonical way, as these are continuous time recurrent neural networks (CTRNN). The above-described aspects of the Stroop phenomenon along with many others are replicated. The model is similar to some existing connectionist models but as will be discussed in the presentation, has many advantages: it predicts more data, the architecture is simpler and biologically more plausible.

Keywords: connectionism, Hebbian learning, artificial neural networks, philosophy of mind, Stroop

Procedia PDF Downloads 264

Authors: Raya A. Jones

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This paper interrogates online representations of robot companions for children, including promotional material by manufacturers, media articles and technology blogs. The significance of the study lies in its contribution to understanding attitudes to robots. The prospect of childcare robots is particularly controversial ethically, and is associated with emotive arguments. The sampled material is restricted to relatively recent posts (the past three years) though the analysis identifies both continuous and changing themes across the past decade. The method extrapolates social representations theory towards examining the ways in which information about robotic products is provided for the general public. Implications for social acceptance of robot companions for the home and robot ethics are considered.

Keywords: acceptance of robots, childcare robots, ethics, social representations

Procedia PDF Downloads 252

Authors: Chia-Ling Li

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The scope of this article includes the production of 10,000 metric tons of non-phthalate per annum. The production process will include hydrogenation, separation, purification, and recycling of unprocessed feedstock. Based on experimental data, conversion and selectivity were chosen as reaction model parameters. The synthesis and separation processes of non-phthalate and phthalate were established by using Aspen Plus software. The article will be divided into six parts: estimation of physical properties, integration of production processes, purification case study, utility consumption, economic feasibility study and identification of bottlenecks. The purities of products was higher than 99.9 wt. %. Process parameters have important guiding significance to the commercialization of hydrogenation of phthalate.

Keywords: economic analysis, hydrogenation, non-phthalate, process simulation

Procedia PDF Downloads 277

Authors: Rajeev Kumar Bedi, Jaswinder Singh, Sunil Kumar Gupta

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The demand for cloud storage is increasing because users want continuous access their data. Cloud Storage revolutionized the way how users access their data. A lot of cloud storage service providers are available as DropBox, G Drive, and providing limited free storage and for extra storage; users have to pay money, which will act as a burden on users. To avoid the issue of limited free storage, the concept of Multi Cloud Storage introduced. In this paper, we will discuss the limitations of existing Multi Cloud Storage systems for mobile devices.

Keywords: cloud storage, data privacy, data security, multi cloud storage, mobile devices

Procedia PDF Downloads 699

Authors: Taylan Kabbani, Ekrem Duman

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The design of adaptive systems that take advantage of financial markets while reducing the risk can bring more stagnant wealth into the global market. However, most efforts made to generate successful deals in trading financial assets rely on Supervised Learning (SL), which suffered from various limitations. Deep Reinforcement Learning (DRL) offers to solve these drawbacks of SL approaches by combining the financial assets price "prediction" step and the "allocation" step of the portfolio in one unified process to produce fully autonomous systems capable of interacting with its environment to make optimal decisions through trial and error. In this paper, a continuous action space approach is adopted to give the trading agent the ability to gradually adjust the portfolio's positions with each time step (dynamically re-allocate investments), resulting in better agent-environment interaction and faster convergence of the learning process. In addition, the approach supports the managing of a portfolio with several assets instead of a single one. This work represents a novel DRL model to generate profitable trades in the stock market, effectively overcoming the limitations of supervised learning approaches. We formulate the trading problem, or what is referred to as The Agent Environment as Partially observed Markov Decision Process (POMDP) model, considering the constraints imposed by the stock market, such as liquidity and transaction costs. More specifically, we design an environment that simulates the real-world trading process by augmenting the state representation with ten different technical indicators and sentiment analysis of news articles for each stock. We then solve the formulated POMDP problem using the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm, which can learn policies in high-dimensional and continuous action spaces like those typically found in the stock market environment. From the point of view of stock market forecasting and the intelligent decision-making mechanism, this paper demonstrates the superiority of deep reinforcement learning in financial markets over other types of machine learning such as supervised learning and proves its credibility and advantages of strategic decision-making.

Keywords: the stock market, deep reinforcement learning, MDP, twin delayed deep deterministic policy gradient, sentiment analysis, technical indicators, autonomous agent

Procedia PDF Downloads 178

Authors: Jesus David Argueta Moreno, Justa Rufina Martel, Edith Gabriela Carrasco

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The Central American Coffee small, medium, and large corporations search for excellence, sustainability, and continuous improvement, triggers in a still unknown scale the Local expansion, crusading, and franchising strategies towards a more suitable commercial opportunity, where the dynamics of the Central American business displacement can be explained through the markets permeability traits. By considering the previously mentioned, the present study aims to evaluate the franchising potentialities offered by Central American Coffee business scenario, in order to explain dynamics of the business demography phenomena and its relevance on the Central American competitiveness landscape.

Keywords: competitiveness, franchising, business demography, Central American Coffee

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Authors: Wookyong Kwon, Sangmoon Lee

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In this paper, a sampled-data model predictive tracking control method is presented for mobile robots which is modeled as constrained continuous-time linear parameter varying (LPV) systems. The presented sampled-data predictive controller is designed by linear matrix inequality approach. Based on the input delay approach, a controller design condition is derived by constructing a new Lyapunov function. Finally, a numerical example is given to demonstrate the effectiveness of the presented method.

Keywords: model predictive control, sampled-data control, linear parameter varying systems, LPV

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Authors: Jincan Li, Mingyu Gao, Zhiwei He, Yuxiang Yang, Zhongfei Yu, Yuanyuan Liu

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Building an appropriate motion model is crucial for trajectory planning of robots and determines the operational quality directly. An adaptive acceleration and deceleration motion planning based on trigonometric functions for the end-effector of 6-DOF robots in Cartesian coordinate system is proposed in this paper. This method not only achieves the smooth translation motion and rotation motion by constructing a continuous jerk model, but also automatically adjusts the parameters of trigonometric functions according to the variable inputs and the kinematic constraints. The results of computer simulation show that this method is correct and effective to achieve the adaptive motion planning for linear trajectories.

Keywords: kinematic constraints, motion planning, trigonometric function, 6-DOF robots

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Authors: Laggoun Chouki

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In this paper we present the design and mechanisms of the physics process and discuss the performances of continuous gas laser dynamics, based on molecules N2(v=1)→C02(001)(v=3). The main objectives of work in this area are, obtaining the high laser energies in short time durations needed for the feasibility studies the physical principles that can be used to make laser sources capable of delivering high average powers. We note that, in order to reach both objectives, one has to convert electrical or chemical energy into laser energy, using gaseous media. The process generating the wave excited, on the basis of the excited level vibration, Theoretical predictions are compared with experimental results. The feasibility and effectiveness of the proposed method is demonstrated by computer simulation.

Keywords: modelling, lasers, gas, numerical, nozzle

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Authors: Kumiko Inagaki

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Qualitative changes to the undergraduate education have recently become the focus of attention in Japan. This is occurring against the backdrop of declining birthrate and increasing university enrollment, as well as drastic societal changes of advance toward globalization and a knowledge-based society. This paper describes the cases of Japanese universities that promoted various forms of experiential learning around the theme of social participation. The opportunity of learning through practical experience, where students turn their attention to social problems and take pains to consider means of resolving them, creates opportunities to demonstrate “human power” applicable to all sorts of activities the following graduation, thereby guaranteeing students’ continuous growth throughout their careers.

Keywords: career education, experiential learning, subjective learning, university education

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Authors: Ahmed Alghurabi, Mysara Mohyaldinn, Shiferaw Jufar, Obai Younis, Abdullah Abduljabbar

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Erosion modeling equations were typically acquired from regulated experimental trials for solid particles entrained in single-phase or multi-phase flows. Evidently, those equations were later employed to predict the erosion damage caused by the continuous impacts of solid particles entrained in streamflow. It is also well-known that the particle impact angle and velocity do not change drastically in gas-sand flow erosion prediction; hence an accurate prediction of erosion can be projected. On the contrary, high-density fluid flows, such as water flow, through complex geometries, such as sand screens, greatly affect the sand particles’ trajectories/tracks and consequently impact the erosion rate predictions. Particle tracking models and erosion equations are frequently applied simultaneously as a method to improve erosion visualization and estimation. In the present work, computational fluid dynamic (CFD)-based erosion modeling was performed using a commercially available software; ANSYS Fluent. The continuous phase (water flow) behavior was simulated using the realizable K-epsilon model, and the secondary phase (solid particles), having a 5% flow concentration, was tracked with the help of the discrete phase model (DPM). To accomplish a successful erosion modeling, three erosion equations from the literature were utilized and introduced to the ANSYS Fluent software to predict the screen wire-slot velocity surge and estimate the maximum erosion rates on the screen surface. Results of turbulent kinetic energy, turbulence intensity, dissipation rate, the total pressure on the screen, screen wall shear stress, and flow velocity vectors were presented and discussed. Moreover, the particle tracks and path-lines were also demonstrated based on their residence time, velocity magnitude, and flow turbulence. On one hand, results from the utilized erosion equations have shown similarities in screen erosion patterns, locations, and DPM concentrations. On the other hand, the model equations estimated slightly different values of maximum erosion rates of the wire-wrapped screen. This is solely based on the fact that the utilized erosion equations were developed with some assumptions that are controlled by the experimental lab conditions.

Keywords: CFD simulation, erosion rate prediction, material loss due to erosion, water-sand flow

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Authors: S. A. Faizi, S. Yoshitomi

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The optimal design procedure of buckling restrained braces (BRBs) in reinforced concrete (RC) building structures can provide the distribution of horizontal stiffness of BRBs at each story, which minimizes story drift response of the structure under the constraint of specified total stiffness of BRBs. In this paper, a simple rule is proposed to convert continuous horizontal stiffness of BRBs into sectional sizes of BRB which are available from standardized section list assuming realistic structural design stage.

Keywords: buckling restrained brace, building engineering, optimal damper placement, structural engineering

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Authors: Jianwen Li, Hongfang Ma, Weixin Qian, Haitao Zhang, Weiyong Ying

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Methanol-to-propylene conversion was carried out in a continuous-flow fixed-bed reactor over nano-sized HZSM-5 zeolites. The HZSM-5 catalysts were synthesized with different Si/Al ratio and silicon sources, and treated with NaOH. The structural property, morphology, and acidity of catalysts were measured by XRD, N₂ adsorption, FE-SEM, TEM, and NH₃-TPD. The results indicate that the increment of Si/Al ratio decreased the acidity of catalysts and then improved propylene selectivity, while silicon sources had slight impact on the acidity but affected the product distribution. The desilication after alkali treatment could increase intracrystalline mesopores and enhance propylene selectivity.

Keywords: alkali treatment, HZSM-5, methanol-to-propylene, synthesis condition

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Authors: Carlos Alberto Riveros, Edwin Fabián García, Javier Enrique Rivero

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The measured data obtained from sensors in continuous monitoring of civil structures are mainly used for modal identification and damage detection. Therefore when modal identification analysis is carried out the quality in the identification of the modes will highly influence the damage detection results. It is also widely recognized that the usefulness of the measured data used for modal identification and damage detection is significantly influenced by the number and locations of sensors. The objective of this study is the numerical implementation of two widely known optimum sensor placement methods in beam-like structures

Keywords: optimum sensor placement, structural damage detection, modal identification, beam-like structures.

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Authors: Mahbub C. Mishu, Venktesh N. Dubey, Tamas Hickish, Jonathan Cole

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Pressure ulcer is a common problem for today's healthcare industry. It occurs due to external load applied to the skin. Also when the subject is immobile for a longer period of time and there is continuous load applied to a particular area of human body,blood flow gets reduced and as a result pressure ulcer develops. Body support surface has a significant role in preventing ulceration so it is important to know the characteristics of support surface under loading conditions. In this paper we have presented mathematical models of different types of viscoelastic materials and also we have shown the validation of our simulation results with experiments.

Keywords: pressure ulcer, viscoelastic material, mathematical model, experimental validation

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Authors: Vaikunthan Rajaratnam

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Maintaining continuous professional development among clinicians has been a challenge. Hand surgery is a unique speciality with the coming together of orthopaedics, plastics and trauma surgeons. The requirements for a team-based approach to care with the inclusion of other experts such as occupational, physiotherapist and orthotic and prosthetist provide the impetus for the creation of communities of practice. This study analysed the community of practice in hand surgery that was created through a social networking website for professionals. The main objectives were to discover the usefulness of this community of practice created in the platform of the group function of LinkedIn. The second objective was to determine the usability of this platform for the purposes of continuing professional development among members of this community of practice. The methodology used was one of mixed methods which included a quantitative analysis on the usefulness of the social network website as a community of practice, using the analytics provided by the LinkedIn platform. Further qualitative analysis was performed on the various postings that were generated by the community of practice within the social network website. This was augmented by a respondent driven survey conducted online to assess the usefulness of the platform for continuous professional development. A total of 31 respondents were involved in this study. This study has shown that it is possible to create an engaging and interactive community of practice among hand surgeons using the group function of this professional social networking website LinkedIn. Over three years the group has grown significantly with members from multiple regions and has produced engaging and interactive conversations online. From the results of the respondents’ survey, it can be concluded that there was satisfaction of the functionality and that it was an excellent platform for discussions and collaboration in the community of practice with a 69 % of satisfaction. Case-based discussions were the most useful functions of the community of practice. This platform usability was graded as excellent using the validated usability tool. This study has shown that the social networking site LinkedIn’s group function can be easily used as a community of practice effectively and provides convenience to professionals and has made an impact on their practice and better care for patients. It has also shown that this platform was easy to use and has a high level of usability for the average healthcare professional. This platform provided the improved connectivity among professionals involved in hand surgery care which allowed for the community to grow and with proper support and contribution of relevant material by members allowed for a safe environment for the exchange of knowledge and sharing of experience that is the foundation of a community practice.

Keywords: community of practice, online community, hand surgery, lifelong learning, LinkedIn, social media, continuing professional development

Procedia PDF Downloads 316

Authors: Cita Ayeni

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Following countless violations of Human Rights in Nigeria by the various arms and agencies of government; from the Military to the Federal Police and other law enforcement agencies, Nigeria has been riddled with several reports of acts by these agencies against the citizens, ranging from illegal arrest and imprisonment, torture, disappearing, and extrajudicial killings, just to mention a few. This paper, focuses on SARS (Special Anti-Robbery Squad), a division of the Nigeria Police Force, and its reported threats to the people’s security, particularly the Nigerian youths, with continuous violence, extortion, illegal arrest and imprisonment, terror, and extrajudicial activities resulting in maiming and in most cases death, thus infringing on the human rights of the people it’s sworn to protect. This research further analyses how the activities of SARS has over the years instigated fear on the average Nigerian youth, preventing the free participation in daily life, education, job, and individual development, in turn impeding the realization of their full potentials for growth and participation in collective national development. This research analyzes the executive order by the then Acting President (Vice-President) of Nigeria, directing the overhauling of SARS, and its implementation by the Federal Police Force in determining if it’s enough to prevent or put a stop to the continuous Human Rights abuse and threat to the security of the individual citizen. Concluding that although the order by the Acting President was given with an intent to halt the various violations by SARS, and the Inspector General of Police’s (IGP) subsequent action by releasing a statement following the order, the bureaucracy in Nigeria, with a history of incompetency and a return to 'business as usual' after a reduced public outcry, it’s most likely that there will not be adequate follow up put in place and these violations would be slowly 'swept under the rug' with SARS officials not held accountable. It is recommended therefore that the Federal Government through the NPF, following the reforms made, in collaboration with the mentioned Independent Human Rights and civil societies organizations should periodically produce unbiased and publicly accessible reports on the implementation of these reforms and progress made. This will go a long way in assuring the public of actual fulfillment of the restructuring, reduce fear by the youths and restore some public faith in the government.

Keywords: special anti-robbery squad, youths in Nigeria, overhaul, insecurities, human rights violations

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Authors: Mohammad Matin

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Nowadays, one of the basic problems of higher education is a significant decline in the quality of education and reduction in efficiency of training. These research and studies are aiming to assess affecting factors of the erosion of academic quality, including educational environmental and content, social and economic factors, elements of the training, elements of education, family factors, from the perspective of students. The result of such improper competition, totally, has led to the decline of education quality in higher education centers, and in many aspects. The results showed a significant difference between male and female students' perspective for two areas of social and economic factors.

Keywords: higher education, decline, the quality of education, student

Procedia PDF Downloads 341

Authors: Asma Omri, Iheb Sifaoui, Sofiane Sayahi, Hichem Besbes

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Future vehicle systems demand advanced capabilities, notably in-cabin life detection and driver monitoring systems, with a particular emphasis on drowsiness detection. To meet these requirements, several techniques employ artificial intelligence methods based on real-time vital sign measurements. In parallel, Frequency-Modulated Continuous-Wave (FMCW) radar technology has garnered considerable attention in the domains of healthcare and biomedical engineering for non-invasive vital sign monitoring. FMCW radar offers a multitude of advantages, including its non-intrusive nature, continuous monitoring capacity, and its ability to penetrate through clothing. In this paper, we propose a system utilizing the AWR6843AOP radar from Texas Instruments (TI) to extract precise vital sign information. The radar allows us to estimate Ballistocardiogram (BCG) signals, which capture the mechanical movements of the body, particularly the ballistic forces generated by heartbeats and respiration. These signals are rich sources of information about the cardiac cycle, rendering them suitable for heart rate estimation. The process begins with real-time subject positioning, followed by clutter removal, computation of Doppler phase differences, and the use of various filtering methods to accurately capture subtle physiological movements. To address the challenges associated with FMCW radar-based vital sign monitoring, including motion artifacts due to subjects' movement or radar micro-vibrations, Long Short-Term Memory (LSTM) networks are implemented. LSTM's adaptability to different heart rate patterns and ability to handle real-time data make it suitable for continuous monitoring applications. Several crucial steps were taken, including feature extraction (involving amplitude, time intervals, and signal morphology), sequence modeling, heart rate estimation through the analysis of detected cardiac cycles and their temporal relationships, and performance evaluation using metrics such as Root Mean Square Error (RMSE) and correlation with reference heart rate measurements. For dataset construction and LSTM training, a comprehensive data collection system was established, integrating the AWR6843AOP radar, a Heart Rate Belt, and a smart watch for ground truth measurements. Rigorous synchronization of these devices ensured data accuracy. Twenty participants engaged in various scenarios, encompassing indoor and real-world conditions within a moving vehicle equipped with the radar system. Static and dynamic subject’s conditions were considered. The heart rate estimation through LSTM outperforms traditional signal processing techniques that rely on filtering, Fast Fourier Transform (FFT), and thresholding. It delivers an average accuracy of approximately 91% with an RMSE of 1.01 beat per minute (bpm). In conclusion, this paper underscores the promising potential of FMCW radar technology integrated with artificial intelligence algorithms in the context of automotive applications. This innovation not only enhances road safety but also paves the way for its integration into the automotive ecosystem to improve driver well-being and overall vehicular safety.

Keywords: ballistocardiogram, FMCW Radar, vital sign monitoring, LSTM

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Authors: Paula Verdugo-Hernandez, Patricio Cumsille

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We analyze a first-class on the convergence of real number sequences, named hereafter sequences, to foster exploration and discovery of concepts through graphical representations before engaging students in proving. The main goal was to differentiate between sequences and continuous functions-of-a-real-variable and better understand concepts at an initial stage. We applied the analytic frame of mathematical working spaces, which we expect to contribute to extending to sequences since, as far as we know, it has only developed for other objects, and which is relevant to analyze how mathematical work is built systematically by connecting the epistemological and cognitive perspectives, and involving the semiotic, instrumental, and discursive dimensions.

Keywords: convergence, graphical representations, mathematical working spaces, paradigms of real analysis, real number sequences

Procedia PDF Downloads 143

Authors: T. Rajamäki

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In clean room environment molecular contamination in very small concentrations can cause significant harm for the components and processes. This is commonly referred as airborne molecular contamination (AMC). There is a shortage of high sensitivity continuous measurement data for existence and behavior of several of these contaminants. Accordingly, in most cases correlation between concentration of harmful molecules and their effect on processes is not known. In addition, the formation and distribution of contaminating molecules are unclear. In this work sensitive optical techniques are applied in clean room facilities for investigation of concentrations, forming mechanisms and effects of contaminating molecules. Special emphasis is on reactive acid and base gases ammonia (NH3) and hydrogen fluoride (HF). They are the key chemicals in several operations taking place in clean room processes.

Keywords: AMC, clean room, concentration, reactive gas

Procedia PDF Downloads 281

Authors: Allulu Yousef Alturki, Raghad Abdullah Alshafi, Sara Abdulaziz Alghashem, Sahar Saleh Alghamdi, Rasha Saad Suliman, Zeyad Alehaideb, Rizwan Ali

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Cancer is recognized as a worldwide public health concern. Therefore, there is a continuous quest to discover new effective medications with less side-effects. In recent years, researchers have shown an increased interest in medicinal plants as several plant species have shown promising biological activities. Thus, we seek to investigate three medicinal herbs that are commonly-found in the Middle Easternregion and yet have not been explored in depth, including plants belonging to the Rhamnaceae, Polygonaceae, and Apocynaceaeplant families. Initially, we investigated using three types of cancer cell lines for breast, colorectal, and liver cancers. We performed high Content Imaging (HCI)-Apoptosis Assay and ApoTox-Glo™ Triplex Assay on KAIMRC2 and HCT8 cell lines. The highest activity of HCI-Apoptosis Assay was with Calligonumcomosum and Ziziphusnummularia in ethanol, followed by Calotropis procera and Ziziphusnummularia in ethyl acetate. The IC50values for the families of Rhamnaceae, Polygonaceae, and Apocynaceae in HepG2 and HCT8 cell lines ranged from 0.089 to 9.84mg/mL and 0.080to 15.08mg/mL, respectively. Further screening was conducted on an additional two cell lines, namely the MDA-MB-231 and KAIMRC2, for selected seven extracts with the highest activity having IC50values ranged from 0.058 to0.51mg/mL and 0.029 to0.19mg/mL, respectively. Continuous scientific investigations to isolate and characterize the potent bioactive phytochemical(s) are warranted. Funding: The authors acknowledge financial support from King Abdullah International Medical Research Center (KAIMRC), Ministry of National Guard Health Affairs, Riyadh, Kingdom of Saudi Arabia. Institutional Review Board Statement: The study was approved by the Institutional Review Board of the Institutional Review Board of King Abdullah International Medical Research Center (SP21R/463/12, 24 January 2022). Acknowledgments: The authors want to express their gratitude to the College of Pharmacy (COP) at King Saud bin Abdulaziz University for Health Sciences (KSAU-HS) and King Abdullah International Medical Research Center (KAIMRC) for their continued support.

Keywords: rhamnaceae, polygonaceae, apocynaceae, natural products

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Authors: Matthew C. Best

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Linear Multi-Input Multi-Output (MIMO) dynamic models can be identified, with no a priori knowledge of model structure or order, using a new Generalised Identifying Filter (GIF). Based on an Extended Kalman Filter, the new filter identifies the model iteratively, in a continuous modal canonical form, using only input and output time histories. The filter’s self-propagating state error covariance matrix allows easy determination of convergence and conditioning, and by progressively increasing model order, the best fitting reduced-order model can be identified. The method is shown to be resistant to noise and can easily be extended to identification of smoothly nonlinear systems.

Keywords: system identification, Kalman filter, linear model, MIMO, model order reduction

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Authors: Nasser Alsadoun

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Today's companies in Saudi Arabian capital market must comply with strict criteria and adhere to rigid corporate governance rules and continuous disclosure requirements. Unlike other regulators in the region, decision makers of the Capital Market Authority (hereafter CMA) of Saudi Arabia believes that the announcements of economic sanctions and penalties for non-compliance firms will foster more effective regulatory compliance and hence improve the quality of financial reporting. An implied argument put forward by the opponents, however, states that such penalties are unnecessary and stated to be onerous for non-compliance firms. Over that last years, the CMA has publicly announced several economic fines levied on some listed companies for their failing to comply with corporate governance and continuous disclosure regulation clauses, with the amount of fine levied ranges between 50,000 SR to 100,000 SR for each failing. Economic theory suggests that rational investors make decisions based on a cost-benefit principal. The regulatory intervention made by CMA on the announcement of economic sanctions has been costly to the society (economy) hoping that it improves the transparency of financial statements. It is argued, therefore, that threat of regulators and economic sanctions will provide incentives for firms’ managers to report more relevant and reliable accounting information, and the benefit of such announcements is likely to be reflected in the context of the quality of the financial reports. Yet, the economic consequences of the revealed fines announcement for non-compliance firms in Saudi Arabian market have not been examined. Thus, this study attempts to empirically examine whether market participants are pricing the supposed benefits of rigid governance and disclosure rules in the Saudi market. The study employs an event study methodology to assess the impact of CMA economic sanctions announcements on the market price of non-compliance firms. The study also estimates and examines bid–ask spread behavior of violated firms around the CMA announcements. The findings indicate that the CMA fines announcements for failing to comply with governance and disclosure rules do not appear to play any significant role in securities pricing. In addition, tests of bid-ask behavior does not indicate any significant increases in information asymmetry surrounding these announcements. While the CMA has developed many goals to increase the awareness of listed companies with the best governance and disclosure practices, it seems they have to develop more goals to improve market efficiency and increase investors and public awareness.

Keywords: governance and disclosure violations, financial reporting quality, regulatory intervention, market efficiency

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Authors: A. M. Sagir

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Discrete linear multistep block method of uniform order for the solution of first order Initial Value Problems (IVPs) in Ordinary Differential Equations (ODEs) is presented in this paper. The approach of interpolation and collocation approximation are adopted in the derivation of the method which is then applied to first order ordinary differential equations with associated initial conditions. The continuous hybrid formulations enable us to differentiate and evaluate at some grids and off – grid points to obtain four discrete schemes, which were used in block form for parallel or sequential solutions of the problems. Furthermore, a stability analysis and efficiency of the block method are tested on ordinary differential equations, and the results obtained compared favorably with the exact solution.

Keywords: block method, first order ordinary differential equations, hybrid, self-starting

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Authors: Bharath R., Tharun Sai N., Bhuvan G.

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This project focuses on developing a Parallel Computing method aimed at optimizing matrix multiplication through GPU acceleration. Addressing algorithmic challenges, GPU programming intricacies, and integration issues, the project aims to enhance efficiency and scalability. The methodology involves algorithm design, GPU programming, and optimization techniques. Future plans include advanced optimizations, extended functionality, and integration with high-level frameworks. User engagement is emphasized through user-friendly interfaces, open- source collaboration, and continuous refinement based on feedback. The project's impact extends to significantly improving matrix multiplication performance in scientific computing and machine learning applications.

Keywords: matrix multiplication, parallel processing, cuda, performance boost, neural networks

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Authors: M. Yaqub Khan, Usman Shabbir

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History of plasma reveals that continuous struggle of experimentalists and theorists are not fruitful for confinement up to now. It needs a change to bring the research through entropy. Approximately, all the quantities like number density, temperature, electrostatic potential, etc. are connected to entropy. Therefore, it is better to change the way of research. In ion temperature gradient mode with the help of Braginskii model, Boltzmannian electrons, effect of velocity shear is studied inculcating entropy in the magnetoplasma. New dispersion relation is derived for ion temperature gradient mode, and dependence on entropy gradient drift is seen. It is also seen velocity shear enhances the instability but in anomalous transport, its role is not seen significantly but entropy. This work will be helpful to the next step of tokamak and space plasmas.

Keywords: entropy, velocity shear, ion temperature gradient mode, drift

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Authors: C. Mayr, J. Periya, A. Kariminezhad

Abstract:

In this paper, we developed a learning framework for the classification of vulnerable road users (VRU) by their range-Doppler signatures. The frequency-modulated continuous-wave (FMCW) radar raw data is first pre-processed to obtain robust object range-Doppler maps per coherent time interval. The complex-valued range-Doppler maps captured from our outdoor measurements are further fed into a convolutional neural network (CNN) to learn the classification. This CNN has gone through a hyperparameter optimization process for improved learning. By learning VRU range-Doppler signatures, the three classes 'pedestrian', 'dog', and 'noise' are classified with an average accuracy of almost 95%. Interestingly, this classification accuracy holds for a combined longitudinal and lateral object trajectories.

Keywords: machine learning, radar, signal processing, autonomous driving

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