Search results for: organizational output
1829 Strategic Management Model for High Performance Sports Centers
Authors: Jose Ramon Sanabria Navarro, Yahilina Silveira Perez, Valentin Molina Moreno, Digna Dionisia Perez Bravo
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The general objective of this research is to conceive a model of strategic direction for Latin American high-performance sports centers for the improvement of their results. The sample is 62 managers, 187 trainers, 2930 athletes and 62 expert researchers from centers in Cuba, Venezuela, Ecuador, Colombia and Argentina, for 3241. The measurement instrument includes 12 key variables in the process of management strategies which are consolidated with the factorial analysis and the ANOVA of a factor through the SPSS 24.0. The reliability of the scale obtained an alpha higher than 0.7 in each sample. In this sense, a model is obtained that taxes the deficiencies detected in the diagnosis, based on the needs of the members of these organizations, considering criteria and theories of the strategic direction in the improvement of the organizational results. The validation of the model for high performance sports centers of the countries analyzed aims to develop joint strategies to generate synergies in their operational mode, which leads to enhance the sports organization.Keywords: sports organization, information management, decision making, control
Procedia PDF Downloads 1311828 Fast and Non-Invasive Patient-Specific Optimization of Left Ventricle Assist Device Implantation
Authors: Huidan Yu, Anurag Deb, Rou Chen, I-Wen Wang
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The use of left ventricle assist devices (LVADs) in patients with heart failure has been a proven and effective therapy for patients with severe end-stage heart failure. Due to the limited availability of suitable donor hearts, LVADs will probably become the alternative solution for patient with heart failure in the near future. While the LVAD is being continuously improved toward enhanced performance, increased device durability, reduced size, a better understanding of implantation management becomes critical in order to achieve better long-term blood supplies and less post-surgical complications such as thrombi generation. Important issues related to the LVAD implantation include the location of outflow grafting (OG), the angle of the OG, the combination between LVAD and native heart pumping, uniform or pulsatile flow at OG, etc. We have hypothesized that an optimal implantation of LVAD is patient specific. To test this hypothesis, we employ a novel in-house computational modeling technique, named InVascular, to conduct a systematic evaluation of cardiac output at aortic arch together with other pertinent hemodynamic quantities for each patient under various implantation scenarios aiming to get an optimal implantation strategy. InVacular is a powerful computational modeling technique that integrates unified mesoscale modeling for both image segmentation and fluid dynamics with the cutting-edge GPU parallel computing. It first segments the aortic artery from patient’s CT image, then seamlessly feeds extracted morphology, together with the velocity wave from Echo Ultrasound image of the same patient, to the computation model to quantify 4-D (time+space) velocity and pressure fields. Using one NVIDIA Tesla K40 GPU card, InVascular completes a computation from CT image to 4-D hemodynamics within 30 minutes. Thus it has the great potential to conduct massive numerical simulation and analysis. The systematic evaluation for one patient includes three OG anastomosis (ascending aorta, descending thoracic aorta, and subclavian artery), three combinations of LVAD and native heart pumping (1:1, 1:2, and 1:3), three angles of OG anastomosis (inclined upward, perpendicular, and inclined downward), and two LVAD inflow conditions (uniform and pulsatile). The optimal LVAD implantation is suggested through a comprehensive analysis of the cardiac output and related hemodynamics from the simulations over the fifty-four scenarios. To confirm the hypothesis, 5 random patient cases will be evaluated.Keywords: graphic processing unit (GPU) parallel computing, left ventricle assist device (LVAD), lumped-parameter model, patient-specific computational hemodynamics
Procedia PDF Downloads 1331827 Agent/Group/Role Organizational Model to Simulate an Industrial Control System
Authors: Noureddine Seddari, Mohamed Belaoued, Salah Bougueroua
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The modeling of complex systems is generally based on the decomposition of their components into sub-systems easier to handle. This division has to be made in a methodical way. In this paper, we introduce an industrial control system modeling and simulation based on the Multi-Agent System (MAS) methodology AALAADIN and more particularly the underlying conceptual model Agent/Group/Role (AGR). Indeed, in this division using AGR model, the overall system is decomposed into sub-systems in order to improve the understanding of regulation and control systems, and to simplify the implementation of the obtained agents and their groups, which are implemented using the Multi-Agents Development KIT (MAD-KIT) platform. This approach appears to us to be the most appropriate for modeling of this type of systems because, due to the use of MAS, it is possible to model real systems in which very complex behaviors emerge from relatively simple and local interactions between many different individuals, therefore a MAS is well adapted to describe a system from the standpoint of the activity of its components, that is to say when the behavior of the individuals is complex (difficult to describe with equations). The main aim of this approach is the take advantage of the performance, the scalability and the robustness that are intuitively provided by MAS.Keywords: complex systems, modeling and simulation, industrial control system, MAS, AALAADIN, AGR, MAD-KIT
Procedia PDF Downloads 2401826 Black-Box-Base Generic Perturbation Generation Method under Salient Graphs
Authors: Dingyang Hu, Dan Liu
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DNN (Deep Neural Network) deep learning models are widely used in classification, prediction, and other task scenarios. To address the difficulties of generic adversarial perturbation generation for deep learning models under black-box conditions, a generic adversarial ingestion generation method based on a saliency map (CJsp) is proposed to obtain salient image regions by counting the factors that influence the input features of an image on the output results. This method can be understood as a saliency map attack algorithm to obtain false classification results by reducing the weights of salient feature points. Experiments also demonstrate that this method can obtain a high success rate of migration attacks and is a batch adversarial sample generation method.Keywords: adversarial sample, gradient, probability, black box
Procedia PDF Downloads 1041825 Diversified Farming and Agronomic Interventions Improve Soil Productivity, Soybean Yield and Biomass under Soil Acidity Stress
Authors: Imran, Murad Ali Rahat
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One of the factors affecting crop production and nutrient availability is acidic stress. The most important element decreasing under acidic stress conditions is phosphorus deficiency, which results in stunted growth and yield because of inefficient nutrient cycling. At the Agriculture Research Institute Mingora Swat, Pakistan, tests were carried out for the first time throughout the course of two consecutive summer seasons in 2016 (year 1) and 2017 (year 2) with the goal of increasing crop productivity and nutrient availability under acidic stress. Three organic supplies (peach nano-black carbon, compost, and dry-based peach wastes), three phosphorus rates, and two advantageous microorganisms (Trichoderma and PSB) were incorporated in the experimental treatments. The findings showed that, in conditions of acid stress, peach organic sources had a significant impact on yield and yield components. The application of nano-black carbon produced the greatest thousand seed weight of 164.6 g among organic sources, however the use of phosphorus solubilizing bacteria (PSB) for seed inoculation increased the thousand seed weight of beneficial microbes when compared to Trichoderma soil application. The thousand seed weight was significantly impacted by the quantities of phosphorus. The treatment of 100 kg P ha-1 produced the highest thousand seed weight (167.3 g), which was followed by 75 kg P ha-1 (162.5 g). Compost amendments provided the highest seed yield (2,140 kg ha-1) and were comparable to the application of nano-black carbon (2,120 kg ha-1). With peach residues, the lowest seed output (1,808 kg ha-1) was observed.Compared to seed inoculation with PSB (1,913 kg ha-1), soil treatment with Trichoderma resulted in the maximum seed production (2,132 kg ha-1). Applying phosphorus to the soybean crop greatly increased its output. The highest seed yield (2,364 kg ha-1) was obtained with 100 kg P ha-1, which was comparable to 75 kg P ha-1 (2,335 kg ha-1), while the lowest seed yield (1,569 kg ha-1) was obtained with 50 kg P ha-1. The average values showed that compared to control plots (3.3 g kg-1), peach organic sources produced greatest SOC (10.0 g kg-1). Plots with treated soil had a maximum soil P of 19.7 mg kg-1, while plots under stress had a maximum soil P of 4.8 mg kg-1. While peach compost resulted in the lowest soil P levels, peach nano-black carbon yielded the highest soil P levels (21.6 mg kg-1). Comparing beneficial bacteria with PSB to Trichoderma (18.3 mg/kg-1), the former also shown an improvement in soil P (21.1 mg kg-1). Regarding P treatments, the application of 100 kg P per ha produced significantly higher soil P values (26.8 mg /kg-1), followed by 75 kg P per ha (18.3 mg /kg-1), and 50 kg P ha-1 produced the lowest soil P values (14.1 mg /kg-1). Comparing peach wastes and compost to peach nano-black carbon (13.7 g kg-1), SOC rose. In contrast to PSB (8.8 g kg-1), soil-treated Trichoderma was shown to have a greater SOC (11.1 g kg-1). Higher among the P levels.Keywords: acidic stress, trichoderma, beneficial microbes, nano-black carbon, compost, peach residues, phosphorus, soybean
Procedia PDF Downloads 771824 The Effects of an Intervention Program on Psychosocial Factors and Consequences during the COVID-19 Pandemic in a Chilean Technology Services Company: A Quasi-Experimental Study
Authors: Julio Lavarello-Salinas, Verónica Kramm-Vergara, Pedro Gil-La Orden
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During the COVID-19 pandemic, mental health became a relevant factor in people’s performance within organizations. The aim of this study was to analyze the effects of an organizational intervention program on the psychosocial factors of demands, resources, and the consequences of psychosocial risks in a technology services company during the COVID-19 pandemic. A quasi-experimental study was carried out with 105 employees who took part in an eight-week intervention program divided into two large stages. Pre- and post- measurements were collected using the UNIPSICO Questionnaire, considering its factors of demands, resources, and consequences of psychosocial risks. The Spanish Burnout Inventory (SBI) was also included. The results showed significant improvements in the perception of some psychosocial demand factors, all the resource factors, and all the consequences of psychosocial risks, except the guilt dimension of the SBI. Thus, we can conclude that the program was effective and that the study limitations should be improved in future studies.Keywords: UNIPSICO questionnaire, occupational health, work stress, work psychosocial risk
Procedia PDF Downloads 1051823 Monitoring of Spectrum Usage and Signal Identification Using Cognitive Radio
Authors: O. S. Omorogiuwa, E. J. Omozusi
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The monitoring of spectrum usage and signal identification, using cognitive radio, is done to identify frequencies that are vacant for reuse. It has been established that ‘internet of things’ device uses secondary frequency which is free, thereby facing the challenge of interference from other users, where some primary frequencies are not being utilised. The design was done by analysing a specific frequency spectrum, checking if all the frequency stations that range from 87.5-108 MHz are presently being used in Benin City, Edo State, Nigeria. From the results, it was noticed that by using Software Defined Radio/Simulink, we were able to identify vacant frequencies in the range of frequency under consideration. Also, we were able to use the significance of energy detection threshold to reuse this vacant frequency spectrum, when the cognitive radio displays a zero output (that is decision H0), meaning that the channel is unoccupied. Hence, the analysis was able to find the spectrum hole and identify how it can be reused.Keywords: spectrum, interference, telecommunication, cognitive radio, frequency
Procedia PDF Downloads 2241822 Effects of Sprint Training on Athletic Performance Related Physiological, Cardiovascular, and Neuromuscular Parameters
Authors: Asim Cengiz, Dede Basturk, Hakan Ozalp
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Practicing recurring resistance workout such as may cause changes in human muscle. These changes may be because combination if several factors determining physical fitness. Thus, it is important to identify these changes. Several studies were reviewed to investigate these changes. As a result, the changes included positive modifications in amplified citrate synthase (CS) maximal activity, increased capacity for pyruvate oxidation, improvement on molecular signaling on human performance, amplified resting muscle glycogen and whole GLUT4 protein content, better health outcomes such as enhancement in cardiorespiratory fitness. Sprint training also have numerous long long-term changes inhuman body such as better enzyme action, changes in muscle fiber and oxidative ability. This is important because SV is the critical factor influencing maximal cardiac output and therefore oxygen delivery and maximal aerobic power.Keywords: sprint, training, performance, exercise
Procedia PDF Downloads 3031821 Compact Low-Voltage Biomedical Instrumentation Amplifiers
Authors: Phanumas Khumsat, Chalermchai Janmane
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Low-voltage instrumentation amplifier has been proposed for 3-lead electrocardiogram measurement system. The circuit’s interference rejection technique is based upon common-mode feed-forwarding where common-mode currents have cancelled each other at the output nodes. The common-mode current for cancellation is generated by means of common-mode sensing and emitter or source followers with resistors employing only one transistor. Simultaneously this particular transistor also provides common-mode feedback to the patient’s right/left leg to further reduce interference entering the amplifier. The proposed designs have been verified with simulations in 0.18-µm CMOS process operating under 1.0-V supply with CMRR greater than 80dB. Moreover ECG signals have experimentally recorded with the proposed instrumentation amplifiers implemented from discrete BJT (BC547, BC558) and MOSFET (ALD1106, ALD1107) transistors working with 1.5-V supply.Keywords: electrocardiogram, common-mode feedback, common-mode feedforward, communication engineering
Procedia PDF Downloads 3841820 Piezoelectric and Dielectric Properties of Poly(Vinylideneflouride-Hexafluoropropylene)/ZnO Nanocomposites
Authors: P. Hemalatha, Deepalekshmi Ponnamma, Mariam Al Ali Al-Maadeed
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The Poly(vinylideneflouride-hexafluoropropylene) (PVDF-HFP)/ zinc oxide (ZnO) nanocomposites films were successfully prepared by mixing the fine ZnO particles into PVDF-HFP solution followed by film casting and sandwich techniques. Zinc oxide nanoparticles were synthesized by hydrothermal method. Fourier transform infrared (FT-IR) spectroscopy, X-ray diffraction (XRD) and scanning electron microscopy (SEM) were used to characterize the structure and properties of the obtained nanocomposites. The dielectric properties of the PVDF-HFP/ZnO nanocomposites were analyzed in detail. In comparison with pure PVDF-HFP, the dielectric constant of the nanocomposite (1wt% ZnO) was significantly improved. The piezoelectric co-efficients of the nanocomposites films were measured. Experimental results revealed the influence of filler on the properties of PVDF-HFP and enhancement in the output performance and dielectric properties reflects the ability for energy storage capabilities.Keywords: dielectric constant, hydrothermal, nanoflowers, organic compounds
Procedia PDF Downloads 2861819 Formal History Teaching and Lifeworld Literacies: Developing Transversal Skills as an Embodied Learning Outcomes in Historical Research Projects
Authors: Paul Flynn, Luke O’Donnell
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There is a pressing societal need for educators in formal and non-formal settings to develop pedagogical frameworks, programmes, and interventions that support the development of transversal skills for life beyond the classroom. These skills include communication, collaboration, interpersonal relationship building, problem-solving, and planning, and organizational skills; or lifeworld literacies encountered first hand. This is particularly true for young people aged between 15-18. This demographic represents both the future of society and those best positioned to take advantage of well-designed, structured educational supports within and across formal and non-formal settings. Secondary school history has been identified as an appropriate area of study which deftly develops many of those transversal skills so crucial to positive societal engagement. However, in the formal context, students often challenge history’s relevance to their own lived experience and dismiss it as a study option. In response to such challenges, teachers will often design stimulating lessons which are often well-received. That said, some students continue to question modern-day connections, presenting a persistent and pervasive classroom distraction. The continuing decline in numbers opting to study second-level history indicates an erosion of what should be a critical opportunity to develop all-important lifeworld literacies within formal education. In contrast, students readily acknowledge relevance in non-formal settings where many participants meaningfully engage with history by way of student-focused activities. Furthermore, many do so without predesigned pedagogical aids which support transversal skills development as embodied learning outcomes. As this paper will present, there is a dearth of work pertaining to the circular subject of history and its embodied learning outcomes, including lifeworld literacies, in formal and non-formal settings. While frequently challenging to reconcile formal (often defined by strict curricula and examination processes), and non-formal engagement with history, opportunities do exist. In the Irish context, this is exemplified by a popular university outreach programme: breaking the SEAL. This programme supports second-level history students as they fulfill curriculum requirements in completing a research study report. This report is a student-led research project pulling on communication skills, collaboration with peers and teachers, interpersonal relationships, problem-solving, and planning and organizational skills. Completion of this process has been widely recognized as excellent preparation not only for higher education (third level) but work-life demands as well. Within a formal education setting, the RSR harnesses non-formal learning virtues and exposes students to limited aspects of independent learning that relate to a professional work setting –a lifeworld literacy. Breaking the SEAL provides opportunities for students to enhance their lifeworld literacy by engaging in an independent research and learning process within the protective security of the classroom and its teacher. This paper will highlight the critical role this programme plays in preparing participating students (n=315) for life after compulsory education and presents examples of how lifeworld literacies may be developed through a scaffolded process of historical research and reporting anchored in non-formal contexts.Keywords: history, education, literacy, transversal skills
Procedia PDF Downloads 1681818 International Indigenous Employment Empirical Research: A Community-Based Participatory Research Content Analysis
Authors: Melanie Grier, Adam Murry
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Objective: Worldwide, Indigenous Peoples experience underemployment and poverty at disproportionately higher rates than non-Indigenous people, despite similar rates of employment seeking. Euro-colonial conquest and genocidal assimilation policies are implicated as perpetuating poverty, which research consistently links to health and wellbeing disparities. Many of the contributors to poverty, such as inadequate income and lack of access to medical care, can be directly or indirectly linked to underemployment. Calls have been made to prioritize Indigenous perspectives in Industrial-Organizational (I/O) psychology research, yet the literature on Indigenous employment remains scarce. What does exist is disciplinarily diverse, topically scattered, and lacking evidence of community-based participatory research (CBPR) practices, a research project approach which prioritizes community leadership, partnership, and betterment and reduces the potential for harm. Due to the harmful colonial legacy of extractive scientific inquiry "on" rather than "with" Indigenous groups, Indigenous leaders and research funding agencies advocate for academic researchers to adopt reparative research methodologies such as CBPR to be used when studying issues pertaining to Indigenous Peoples or individuals. However, the frequency and consistency of CBPR implementation within scholarly discourse are unknown. Therefore, this project’s goal is two-fold: (1) to understand what comprises CBPR in Indigenous research and (2) to determine if CBPR has been historically used in Indigenous employment research. Method: Using a systematic literature review process, sixteen articles about CBPR use with Indigenous groups were selected, and content was analyzed to identify key components comprising CBPR usage. An Indigenous CBPR components framework was constructed and subsequently utilized to analyze the Indigenous employment empirical literature. A similar systematic literature review process was followed to search for relevant empirical articles on Indigenous employment. A total of 120 articles were identified in six global regions: Australia, New Zealand, Canada, America, the Pacific Islands, and Greenland/Norway. Each empirical study was procedurally examined and coded for criteria inclusion using content analysis directives. Results: Analysis revealed that, in total, CBPR elements were used 14% of the time in Indigenous employment research. Most studies (n=69; 58%) neglected to mention using any CBPR components, while just two studies discussed implementing all sixteen (2%). The most significant determinant of overall CBPR use was community member partnership (CP) in the research process. Studies from New Zealand were most likely to use CBPR components, followed by Canada, Australia, and America. While CBPR use did increase slowly over time, meaningful temporal trends were not found. Further, CBPR use did not directly correspond with the total number of topical articles published that year. Conclusions: Community-initiated and engaged research approaches must be better utilized in employment studies involving Indigenous Peoples. Future research efforts must be particularly attentive to community-driven objectives and research protocols, emphasizing specific areas of concern relevant to the field of I/O psychology, such as organizational support, recruitment, and selection.Keywords: community-based participatory research, content analysis, employment, indigenous research, international, reconciliation, recruitment, reparative research, selection, systematic literature review
Procedia PDF Downloads 741817 Low Cost Inertial Sensors Modeling Using Allan Variance
Authors: A. A. Hussen, I. N. Jleta
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Micro-electromechanical system (MEMS) accelerometers and gyroscopes are suitable for the inertial navigation system (INS) of many applications due to the low price, small dimensions and light weight. The main disadvantage in a comparison with classic sensors is a worse long term stability. The estimation accuracy is mostly affected by the time-dependent growth of inertial sensor errors, especially the stochastic errors. In order to eliminate negative effect of these random errors, they must be accurately modeled. Where the key is the successful implementation that depends on how well the noise statistics of the inertial sensors is selected. In this paper, the Allan variance technique will be used in modeling the stochastic errors of the inertial sensors. By performing a simple operation on the entire length of data, a characteristic curve is obtained whose inspection provides a systematic characterization of various random errors contained in the inertial-sensor output data.Keywords: Allan variance, accelerometer, gyroscope, stochastic errors
Procedia PDF Downloads 4421816 Factors Affecting the Effectiveness of Management Creativity Using Theory Planned Behavior
Authors: Basheer Ahmad Al-Alwan, Ali Ratib Al-Awamreh, Badar Saif Alhatmi
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The success of organizations in today's rapidly changing business landscape greatly hinges on the effectiveness of management creativity. This research aimed to uncover the elements influencing the effectiveness of management creativity by employing the Theory of Planned Behavior. The study's findings indicate that two significant predictors of management creativity effectiveness are one's attitude towards it and the subjective norms within the organization. Such results are rather important for the organizations and their leaders who would want to increase management creativity. The attitudes of subordinates towards management creativity should be positive if managers wish to cultivate management creativity among their employees, and the organizational culture must also be one that enhances and supports creative thinking. They should also make available all the requisite resources and support required for the implementation of their creative ideas and let employees participate in the decision-making processes in order to increase their sense of control over their creative activities. This research contributes to the literature on managerial creativity by presenting evidence about the effectiveness of managerial creativity and the strategies aimed at increasing the level of creativity in organizations through empirical insights.Keywords: management creativity, attitudes, subjective norms, perceived behavioral control
Procedia PDF Downloads 91815 Branding a Powerful Catalyst for Rural Economic Development
Authors: Mojtaba Borhani
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By employing the unique characteristics of a region, its economy, climate, geography, and culture, rural communities can create distinctive products. This approach not only boosts economic opportunities but also promotes sustainable growth and preserves cultural heritage. A strategic focus on branding and intellectual property (IP) is essential. By developing strong brands, rural areas can differentiate their products, increase their market value, and build consumer loyalty. Moreover, IP protection safeguards the creative and innovative output of rural communities, incentivizing further development. Rural branding can serve as a cornerstone for community empowerment. It can help to prevent rural exodus by providing economic incentives and a strong sense of place. Additionally, by protecting traditional knowledge and cultural expressions, branding contributes to the long-term sustainability of rural livelihoods.Keywords: intellectual property, regional branding, sustainable development, rural economy
Procedia PDF Downloads 241814 Adaptive Filtering in Subbands for Supervised Source Separation
Authors: Bruna Luisa Ramos Prado Vasques, Mariane Rembold Petraglia, Antonio Petraglia
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This paper investigates MIMO (Multiple-Input Multiple-Output) adaptive filtering techniques for the application of supervised source separation in the context of convolutive mixtures. From the observation that there is correlation among the signals of the different mixtures, an improvement in the NSAF (Normalized Subband Adaptive Filter) algorithm is proposed in order to accelerate its convergence rate. Simulation results with mixtures of speech signals in reverberant environments show the superior performance of the proposed algorithm with respect to the performances of the NLMS (Normalized Least-Mean-Square) and conventional NSAF, considering both the convergence speed and SIR (Signal-to-Interference Ratio) after convergence.Keywords: adaptive filtering, multi-rate processing, normalized subband adaptive filter, source separation
Procedia PDF Downloads 4351813 Risk Assessment and Management Using Machine Learning Models
Authors: Lagnajeet Mohanty, Mohnish Mishra, Pratham Tapdiya, Himanshu Sekhar Nayak, Swetapadma Singh
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In the era of global interconnectedness, effective risk assessment and management are critical for organizational resilience. This review explores the integration of machine learning (ML) into risk processes, examining its transformative potential and the challenges it presents. The literature reveals ML's success in sectors like consumer credit, demonstrating enhanced predictive accuracy, adaptability, and potential cost savings. However, ethical considerations, interpretability issues, and the demand for skilled practitioners pose limitations. Looking forward, the study identifies future research scopes, including refining ethical frameworks, advancing interpretability techniques, and fostering interdisciplinary collaborations. The synthesis of limitations and future directions highlights the dynamic landscape of ML in risk management, urging stakeholders to navigate challenges innovatively. This abstract encapsulates the evolving discourse on ML's role in shaping proactive and effective risk management strategies in our interconnected and unpredictable global landscape.Keywords: machine learning, risk assessment, ethical considerations, financial inclusion
Procedia PDF Downloads 721812 Reinforcement Learning the Born Rule from Photon Detection
Authors: Rodrigo S. Piera, Jailson Sales Ara´ujo, Gabriela B. Lemos, Matthew B. Weiss, John B. DeBrota, Gabriel H. Aguilar, Jacques L. Pienaar
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The Born rule was historically viewed as an independent axiom of quantum mechanics until Gleason derived it in 1957 by assuming the Hilbert space structure of quantum measurements [1]. In subsequent decades there have been diverse proposals to derive the Born rule starting from even more basic assumptions [2]. In this work, we demonstrate that a simple reinforcement-learning algorithm, having no pre-programmed assumptions about quantum theory, will nevertheless converge to a behaviour pattern that accords with the Born rule, when tasked with predicting the output of a quantum optical implementation of a symmetric informationally-complete measurement (SIC). Our findings support a hypothesis due to QBism (the subjective Bayesian approach to quantum theory), which states that the Born rule can be thought of as a normative rule for making decisions in a quantum world [3].Keywords: quantum Bayesianism, quantum theory, quantum information, quantum measurement
Procedia PDF Downloads 1091811 Discursivity and Creativity: Implementing Pigrum's Multi-Mode Transitional Practices in Upper Division Creative Production Courses
Authors: Michael Filimowicz, Veronika Tzankova
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This paper discusses the practical implementation of Derek Pigrum’s multi-mode model of transitional practices in the context of upper division production courses in an interaction design curriculum. The notion of teaching creativity directly was connected to a general notion of “discursivity” by which is meant students’ overall ability to discuss, describe, and engage in dialogue about their creative work. We present a study of how Pigrum’s transitional modes can be mapped onto a variety of course activities, and discuss challenges and outcomes of directly engaging student discursivity in their creative output.Keywords: teaching creativity, multi-mode transitional practices, discursivity, rich dialogue, art and design education, pedagogy
Procedia PDF Downloads 5021810 Assessment of Impact of Manpower Training and Development in the Construction Industry
Authors: Olalekan Bamidele Aruleba
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This research assessed the impact of manpower training and development in the construction industry. The aim is to determine the effect of training and development on employees for effective organizational growth in the construction industry to identify the training method for each category of employee in the construction industry, challenges to training and development of workers in the construction industry and impact of manpower training and development on employees and employers. Data for the study were obtained through a well-structured questionnaire administered to building professionals in Nigeria construction firm. Eighty (80) questionnaires were distributed among building professionals in three selected local governments within Ondo State and sixty-four (64) were returned. Data collected were analysed using descriptive statistics and ranking. Findings of the study revealed that in house training and in-service training methods were preferred by most construction industry. It concluded that the attitude of top management and lack of fund was seen as the significant challenges militating against training of employees. The study recommended that manpower training and development must be sustained by all stakeholders in the industry in order to improve workers' productivity; the organization should adopt the right method in training each category of employees and carry out the need assessment for training to avoid training wrong employees.Keywords: construction, development, manpower, training
Procedia PDF Downloads 2341809 Diversification and Risk Management in Non-Profit Organisations: A Case Study
Authors: Manzurul Alam, John Griffiths, David Holloway, Megan Paull, Anne Clear
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Background: This paper investigates the nature of risk management practices in non-profit organizations. It is argued here that the risk exposure of these organizations has increased as a result of their entrepreneurial activities. This study explores how a particular non-profit organization formulates its risk strategies in the face funding restrictions. Design/Method/Approach: The study adopts a case study approach to report the results on how a non-profit organization diversifies its activities, tackles risks arising from such activities and improves performance. Results: The findings show that the organization made structural adjustments and leadership changes which helped to adjust their risk strategies. It also reports the organizational processes to deal with risks arising from both related and unrelated diversification strategies. Implications: Any generalization from this case example needs to be taken with caution as there are significant differences between non-profit organizations operating in different sectors. Originality: The paper makes a significant contribution to the non-profit literature by highlighting the diversification strategies along with risk performance.Keywords: risk management, performance management, non-profit organizations, financial management
Procedia PDF Downloads 5151808 Separating Landform from Noise in High-Resolution Digital Elevation Models through Scale-Adaptive Window-Based Regression
Authors: Anne M. Denton, Rahul Gomes, David W. Franzen
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High-resolution elevation data are becoming increasingly available, but typical approaches for computing topographic features, like slope and curvature, still assume small sliding windows, for example, of size 3x3. That means that the digital elevation model (DEM) has to be resampled to the scale of the landform features that are of interest. Any higher resolution is lost in this resampling. When the topographic features are computed through regression that is performed at the resolution of the original data, the accuracy can be much higher, and the reported result can be adjusted to the length scale that is relevant locally. Slope and variance are calculated for overlapping windows, meaning that one regression result is computed per raster point. The number of window centers per area is the same for the output as for the original DEM. Slope and variance are computed by performing regression on the points in the surrounding window. Such an approach is computationally feasible because of the additive nature of regression parameters and variance. Any doubling of window size in each direction only takes a single pass over the data, corresponding to a logarithmic scaling of the resulting algorithm as a function of the window size. Slope and variance are stored for each aggregation step, allowing the reported slope to be selected to minimize variance. The approach thereby adjusts the effective window size to the landform features that are characteristic to the area within the DEM. Starting with a window size of 2x2, each iteration aggregates 2x2 non-overlapping windows from the previous iteration. Regression results are stored for each iteration, and the slope at minimal variance is reported in the final result. As such, the reported slope is adjusted to the length scale that is characteristic of the landform locally. The length scale itself and the variance at that length scale are also visualized to aid in interpreting the results for slope. The relevant length scale is taken to be half of the window size of the window over which the minimum variance was achieved. The resulting process was evaluated for 1-meter DEM data and for artificial data that was constructed to have defined length scales and added noise. A comparison with ESRI ArcMap was performed and showed the potential of the proposed algorithm. The resolution of the resulting output is much higher and the slope and aspect much less affected by noise. Additionally, the algorithm adjusts to the scale of interest within the region of the image. These benefits are gained without additional computational cost in comparison with resampling the DEM and computing the slope over 3x3 images in ESRI ArcMap for each resolution. In summary, the proposed approach extracts slope and aspect of DEMs at the lengths scales that are characteristic locally. The result is of higher resolution and less affected by noise than existing techniques.Keywords: high resolution digital elevation models, multi-scale analysis, slope calculation, window-based regression
Procedia PDF Downloads 1291807 Mathematical Modeling and Optimization of Burnishing Parameters for 15NiCr6 Steel
Authors: Tarek Litim, Ouahiba Taamallah
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The present paper is an investigation of the effect of burnishing on the surface integrity of a component made of 15NiCr6 steel. This work shows a statistical study based on regression, and Taguchi's design has allowed the development of mathematical models to predict the output responses as a function of the technological parameters studied. The response surface methodology (RSM) showed a simultaneous influence of the burnishing parameters and observe the optimal processing parameters. ANOVA analysis of the results resulted in the validation of the prediction model with a determination coefficient R=90.60% and 92.41% for roughness and hardness, respectively. Furthermore, a multi-objective optimization allowed to identify a regime characterized by P=10kgf, i=3passes, and f=0.074mm/rev, which favours minimum roughness and maximum hardness. The result was validated by the desirability of D= (0.99 and 0.95) for roughness and hardness, respectively.Keywords: 15NiCr6 steel, burnishing, surface integrity, Taguchi, RSM, ANOVA
Procedia PDF Downloads 1911806 Deep-Learning Based Approach to Facial Emotion Recognition through Convolutional Neural Network
Authors: Nouha Khediri, Mohammed Ben Ammar, Monji Kherallah
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Recently, facial emotion recognition (FER) has become increasingly essential to understand the state of the human mind. Accurately classifying emotion from the face is a challenging task. In this paper, we present a facial emotion recognition approach named CV-FER, benefiting from deep learning, especially CNN and VGG16. First, the data is pre-processed with data cleaning and data rotation. Then, we augment the data and proceed to our FER model, which contains five convolutions layers and five pooling layers. Finally, a softmax classifier is used in the output layer to recognize emotions. Based on the above contents, this paper reviews the works of facial emotion recognition based on deep learning. Experiments show that our model outperforms the other methods using the same FER2013 database and yields a recognition rate of 92%. We also put forward some suggestions for future work.Keywords: CNN, deep-learning, facial emotion recognition, machine learning
Procedia PDF Downloads 951805 A Super-Efficiency Model for Evaluating Efficiency in the Presence of Time Lag Effect
Authors: Yanshuang Zhang, Byungho Jeong
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In many cases, there is a time lag between the consumption of inputs and the production of outputs. This time lag effect should be considered in evaluating the performance of organizations. Recently, a couple of DEA models were developed for considering time lag effect in efficiency evaluation of research activities. Multi-periods input(MpI) and Multi-periods output(MpO) models are integrated models to calculate simple efficiency considering time lag effect. However, these models can’t discriminate efficient DMUs because of the nature of basic DEA model in which efficiency scores are limited to ‘1’. That is, efficient DMUs can’t be discriminated because their efficiency scores are same. Thus, this paper suggests a super-efficiency model for efficiency evaluation under the consideration of time lag effect based on the MpO model. A case example using a long-term research project is given to compare the suggested model with the MpO model.Keywords: DEA, super-efficiency, time lag, multi-periods input
Procedia PDF Downloads 4731804 Optimization Design of Single Phase Inverter Connected to the Grid
Authors: Linda Hassaine, Abdelhamid Mraoui, Mohamed Rida Bengourina
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In grid-connected photovoltaic systems, significant improvements can be carried out in the design and implementation of inverters: reduction of harmonic distortion, elimination of the DC component injected into the grid and the proposed control. This paper proposes a control strategy based on PWM switching patterns for an inverter for the photovoltaic system connected to the grid in order to control the injected current. The current injected must be sinusoidal with reduced harmonic distortion. An additional filter is designed to reduce high-order harmonics on the output side. This strategy exhibits the advantages: Simplicity, reduction of harmonics, the size of the line filter, reduction of the memory requirements and power calculation for the control.Keywords: control, inverters, LCL filter, grid-connected photovoltaic system
Procedia PDF Downloads 3251803 Temperature Distribution Control for Baby Incubator System Using Arduino AT Mega 2560
Authors: W. Widhiada, D. N. K. P. Negara, P. A. Suryawan
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The technological advances in the field of health to be very important, especially on the safety of the baby. In this case a lot of premature infants death caused by poorly managed health facilities. Mostly the death of premature baby caused by bacteria since the temperature around the baby is not normal. Related to this, the incubator equipment needs to be important, especially in how to control the temperature in incubator. On/Off controls is used to regulate the temperature distribution in the incubator so that the desired temperature is 36 °C to stay awake and stable. The authors have been observed and analyzed the data to determine the temperature distribution in the incubator using program of MATLAB/Simulink. The output temperature distribution is obtained at 36 °C in 400 seconds using an Arduino AT 2560. This incubator is able to maintain an ambient temperature and maintain the baby's body temperature within normal limits and keep the moisture in the air in accordance with the limit values required in infant incubator.Keywords: on/off control, distribution temperature, Arduino AT 2560, baby incubator
Procedia PDF Downloads 5001802 Energy Harvesting with Zinc Oxide Based Nanogenerator: Design and Simulation Using Comsol-4.3 Software
Authors: Akanksha Rohit, Ujjwala Godavarthi, Anshua Mukherjee
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Nanotechnology is one of the promising sustainable solutions in the era of miniaturization due to its multidisciplinary nature. The most interesting aspect about nanotechnology is its wide ranging applications from electronics to military and biomedical. It tries to connect individuals more closely to the environment. In this paper, concept of parasitic energy harvesting is used in designing nanogenerators using COMSOL 4.3 software. The output of the nanogenerator is optimized using following constraints: ease of availability of the material, fabrication process and cost of the material. The nanogenerator is optimized using ZnO based nanowires, PMMA as insulator and aluminum and silicon as metal electrodes. The energy harvested from the model can be used to power nanobots, several other biomedical sensors and eventually to replace batteries. Thus, advancements in this field can be very challenging but it is the future of the nano era.Keywords: zinc oxide, piezoelectric, PMMA, parasitic energy harvesting, renewable energy engineering
Procedia PDF Downloads 3641801 Corporate Social Responsibility and Students’ Job Performance: A Case Study of Silpakorn University’s Internship Program
Authors: Naritphol Boonyakiat
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This research attempts to investigate the relationship between corporate social responsibility and students’ job performance of the Silpakorn University’s internship program within various organizations. The goal of this study is to fill the literature gap by gaining an understanding of corporate social responsibility that fundamentally relate to students’ job performance within the organizations. Thus, this study will focus on the outcomes that derive from selected employers’ qualitative assessment and evaluation forms from various companies. The results represent the perceptions of students towards the corporate social responsibility aspects and their job performance evaluation from the employers in various organizations. The findings indicate that corporate social responsibility has significant effects on students’ job performance. This study may assist us in gaining a better understanding of the integrated aspects of university and workplace environments to discover how to allocate optimally university’s resources and management approaches to gain benefits from corporate social responsibility practices toward students’ job performance within an organizational setting. Therefore, there is good reason to believe that the findings can contribute to research in the area of CSR and students’ job performance as an essential aspect of long-term success sustainability.Keywords: corporate social responsibility, job performance, university students, internship program
Procedia PDF Downloads 3771800 Semiconductor Variable Wavelength Generator of Near-Infrared-to-Terahertz Regions
Authors: Isao Tomita
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Power characteristics are obtained for laser beams of near-infrared and terahertz wavelengths when produced by difference-frequency generation with a quasi-phase-matched (QPM) waveguide made of gallium phosphide (GaP). A refractive-index change of the QPM GaP waveguide is included in computations with Sellmeier’s formula for varying input wavelengths, where optical loss is also included. Although the output power decreases with decreasing photon energy as the beam wavelength changes from near-infrared to terahertz wavelengths, the beam generation with such greatly different wavelengths, which is not achievable with an ordinary laser diode without the replacement of semiconductor material with a different bandgap one, can be made with the same semiconductor (GaP) by changing the QPM period, where a way of changing the period is provided.Keywords: difference-frequency generation, gallium phosphide, quasi-phase-matching, waveguide
Procedia PDF Downloads 116