Search results for: deep drawing

Authors: Arias Fernando, Juan Bojórquez, Edén Bojórquez, Alfredo Reyes-Salazar, Fernando de J. Velarde, Robespierre Chávez, J. Martin Leal, Victor Baca

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The present study focuses on the optimization of different structural systems employed in tall steel buildings, with a specific focus on the city of Acapulco, Guerrero, a region known for its high seismic activity. Using the spectral modal method, analyses were conducted to assess the ability of these buildings to withstand seismic forces and other external loads. After performing a detailed analysis of various models, the results were compared based on various engineering parameters, including maximum interstory drift, base shear, displacements, and the total weight of the structures, the latter being considered as an estimate of the cost of the proposed systems. The findings of this study indicate that steel frames stand out as a viable option for tall buildings in question. However, areas of potential improvement were identified, suggesting opportunities for further optimization of the design and seismic resistance of these structures. This study provides a deep and insightful perspective on the optimization of structural systems in tall steel buildings, offering valuable information for engineers and professionals in the field involved in similar projects.

Keywords: high seismic zone, irregular buildings, optimization design, steel buildings

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Authors: Natalie Delia

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This academic paper investigates the transformative potential of incorporating alternative ways of knowing within the framework of Critical Studies departments. Traditional academic paradigms often prioritize empirical evidence and established methodologies, potentially limiting the scope of critical inquiry. In response to this, our research seeks to illuminate the benefits and challenges associated with integrating alternative epistemologies, such as indigenous knowledge systems, artistic expressions, and experiential narratives. Drawing upon a comprehensive review of literature and case studies, we examine how alternative ways of knowing can enrich and diversify the intellectual landscape of Critical Studies departments. By embracing perspectives that extend beyond conventional boundaries, departments may foster a more inclusive and holistic understanding of critical issues. Additionally, we explore the potential impact on pedagogical approaches, suggesting that alternative ways of knowing can stimulate alternative way of teaching methods and enhance student engagement. Our investigation also delves into the institutional and cultural shifts necessary to support the integration of alternative epistemologies within academic settings. We address concerns related to validation, legitimacy, and the potential clash with established norms, offering insights into fostering an environment that encourages intellectual pluralism. Furthermore, the paper considers the implications for interdisciplinary collaboration and the potential for cultivating a more responsive and socially engaged scholarship. By encouraging a synthesis of diverse perspectives, Critical Studies departments may be better equipped to address the complexities of contemporary issues, encouraging a dynamic and evolving field of study. In conclusion, this paper advocates for a paradigm shift within Critical Studies departments towards a more inclusive and expansive approach to knowledge production. By embracing alternative ways of knowing, departments have the opportunity to not only diversify their intellectual landscape but also to contribute meaningfully to broader societal dialogues, addressing pressing issues with renewed depth and insight.

Keywords: critical studies, alternative ways of knowing, academic department, Wallerstein

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Authors: Shriya Shukla, Lachin Fernando

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Pneumonia, a leading cause of mortality in young children globally, presents significant diagnostic challenges, particularly in resource-limited settings. This study presents an approach to diagnosing pediatric pneumonia using Chest X-Ray (CXR) images, employing a lightweight MobileNetV2 model enhanced with synthetic data augmentation. Addressing the challenge of dataset scarcity and imbalance, the study used a Variational Autoencoder-Generative Adversarial Network (VAE-GAN) to generate synthetic CXR images, improving the representation of normal cases in the pediatric dataset. This approach not only addresses the issues of data imbalance and scarcity prevalent in medical imaging but also provides a more accessible and reliable diagnostic tool for early pneumonia detection. The augmented data improved the model’s accuracy and generalization, achieving an overall accuracy of 95% in pneumonia detection. These findings highlight the efficacy of the MobileNetV2 model, offering a computationally efficient yet robust solution well-suited for resource-constrained environments such as mobile health applications. This study demonstrates the potential of synthetic data augmentation in enhancing medical image analysis for critical conditions like pediatric pneumonia.

Keywords: pneumonia, MobileNetV2, image classification, GAN, VAE, deep learning

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Authors: R. N. Begum, Ambalika Sharma, G. K. Singh

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Identity theft has serious ramifications beyond data and personal information loss. This necessitates the implementation of robust and efficient user identification systems. Therefore, automatic biometric recognition systems are the need of the hour, and ECG-based systems are unquestionably the best choice due to their appealing inherent characteristics. The CNNs are the recent state-of-the-art techniques for ECG-based user identification systems. However, the results obtained are significantly below standards, and the situation worsens as the number of users and types of heartbeats in the dataset grows. As a result, this study proposes a highly accurate and resilient ECG-based person identification system using CNN's dense learning framework. The proposed research explores explicitly the calibre of dense CNNs in the field of ECG-based human recognition. The study tests four different configurations of dense CNN which are trained on a dataset of recordings collected from eight popular ECG databases. With the highest FAR of 0.04 percent and the highest FRR of 5%, the best performing network achieved an identification accuracy of 99.94 percent. The best network is also tested with various train/test split ratios. The findings show that DenseNets are not only extremely reliable but also highly efficient. Thus, they might also be implemented in real-time ECG-based human recognition systems.

Keywords: Biometrics, Dense Networks, Identification Rate, Train/Test split ratio

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Authors: Yathreb Sabsaby

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Energy efficiency retrofitting of existing buildings was long ignored by public authorities who favored energy efficiency policies in new buildings, which are easier to implement. Indeed, retrofitting is more complex and difficult to organize because of the extreme diversity in existing buildings, administrative situations and occupation. Energy efficiency retrofitting of existing buildings has now become indispensable in all economies—even emerging countries—given the constraints imposed by energy security and climate change, and because it represents considerable potential energy savings. Addressing energy efficiency in the existing building stock has been acknowledged as one of the most critical yet challenging aspects of reducing our environmental footprint on the ecosystem. Tripoli, Lebanon chosen as case study area is a typical Mediterranean metropolis in the North Lebanon, where multifamily residential buildings are all around the city. This generally implies that the density of energy demand is extremely high, even the renewable energy facilities are involved, they can just play as a minor energy provider at the current technology level in the single family house. It seems only the low energy design for buildings can be made possible, not the zero energy certainly in developing country. This study reviews the latest research and experience and provides recommendations for deep energy retrofits that aim to save more than 50% of the energy used in a typical Tripoli apartment building.

Keywords: energy-efficiency, existing building, multifamily residential building, retrofit

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Authors: Yasser Mohamed Abdelrahman Tarshany

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The emergence of the digital economy has transformed global business and created new opportunities for growth and development. However, as digital technologies continue to reshape the global economy, there is a growing need to ensure that these transformations are guided by ethical principles that serve the common good. In this context, Maqasid, the Islamic ethical framework that focuses on the higher objectives and values of Shariah, offers a valuable lens for examining the ethical implications of digital transformation. The research objective of this study is to explore the opportunities and challenges of integrating Maqasid into the global digital economy from a business and management perspective. Specifically, the study aims to analyze the ethical implications of digital technologies for the economy and to identify strategies for leveraging Maqasid to promote ethical and socially responsible practices in the digital age. The study adopts a qualitative research methodology, drawing on existing literature and empirical data to develop a conceptual framework for understanding the relationship between Maqasid and the global digital economy. The study also employs case studies and interviews with business leaders and policymakers to explore practical strategies for integrating Maqasid into digital business practices. The research findings reveal that Maqasid can serve as a powerful framework for promoting ethical and socially responsible practices in the digital economy. Specifically, the study identifies several key strategies for leveraging Maqasid in digital business practices, including promoting social justice, protecting privacy and personal data, and ensuring transparency and accountability in business operations. The research outcomes of this study provide a valuable contribution to the field of business and management by demonstrating the importance of integrating ethical principles into the digital economy. Furthermore, the study highlights the potential of Maqasid as a powerful framework for promoting ethical and socially responsible practices in the digital age. Finally, the study suggests several avenues for future research, including exploring the role of Maqasid in promoting digital inclusion and reducing inequality in the global economy.

Keywords: Maqasid, global digital, economy, opportunities, challenges for business, management

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Authors: O. T. Oluriz, O. D. Akinyemi, J. A.Olowofela, O. A. Idowu, S. A. Ganiyu

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This study was carried out using aeromagnetic data which record variation in the magnitude of the earth magnetic field in order to detect local changes in the properties of the underlying geology. The aeromagnetic data (Sheet No. 261) was acquired from the archives of Nigeria Geological Survey Agency of Nigeria, obtained in 2009. The study present estimation of source parameters within an area of about 3,025 square kilometers on geographic latitude to and longitude to within Ibadan and it’s environs in Oyo State, southwestern Nigeria. The area under study belongs to part of basement complex in southwestern Nigeria. Estimation of source parameters of aeromagnetic data was achieve through the application of source imaging parameters (SPI) techniques that provide delineation, depth, dip contact, susceptibility contrast and mineral potentials of magnetic signatures within the region. The depth to the magnetic sources in the area ranges from 0.675 km to 4.48 km. The estimated depth limit to shallow sources is 0.695 km and depth to deep sources is 4.48 km. The apparent susceptibility values of the entire study area obtained ranges from 0.01 to 0.005 [SI]. This study has shown that the magnetic susceptibility within study area is controlled mainly by super paramagnetic minerals.

Keywords: aeromagnetic, basement complex, meta-sediment, precambrian

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Authors: X. F. Sun, X. D. Wen, L. J. Liu, C. C. Wu, Y. H. Jia

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The field reversed closed magnetic field configuration plasmoid has a potential for large thrust and high power propulsion missions such as deep space exploration due to its high plasma density and larger azimuthal current, which will be a most competitive program for the next generation electric propulsion technology. Moreover, without the electrodes, it also has a long lifetime. Thus, the research on this electric propulsion technology is quite necessary. The plasmoid will be formatted and accelerated by applying a rotation magnetic field (RMF) method. And, the essence of this technology lies on the generation of the azimuthal electron currents driven by RMF. Therefore, the effect of RMF current on the plasmoid acceleration efficiency is a concerned problem. In the paper, the influences of the penetration process of RMF in plasma, the relations of frequency and amplitude of input RF power with current strength and the RMF antenna configuration on the plasmoid acceleration efficiency will be given by a two-fluid numerical simulation method. The results show that the radio-frequency and input power have remarkable influence on the formation and acceleration of plasmoid. These results will provide useful advice for the development, and optimized designing of field reversed configuration plasmoid thruster.

Keywords: rotation magnetic field, current driven, plasma penetration, electric propulsion

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Authors: Qasem Qananwah, Ahmad Dagamseh, Hiam AlQuran, Khalid Shaker Ibrahim

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Blood pressure helps the physicians greatly to have a deep insight into the cardiovascular system. The determination of individual blood pressure is a standard clinical procedure considered for cardiovascular system problems. The conventional techniques to measure blood pressure (e.g. cuff method) allows a limited number of readings for a certain period (e.g. every 5-10 minutes). Additionally, these systems cause turbulence to blood flow; impeding continuous blood pressure monitoring, especially in emergency cases or critically ill persons. In this paper, the most important statistical features in the photoplethysmogram (PPG) signals were extracted to estimate the blood pressure noninvasively. PPG signals from more than 40 subjects were measured and analyzed and 12 features were extracted. The features were fed to principal component analysis (PCA) to find the most important independent features that have the highest correlation with blood pressure. The results show that the stiffness index means and standard deviation for the beat-to-beat heart rate were the most important features. A model representing both features for Systolic Blood Pressure (SBP) and Diastolic Blood Pressure (DBP) was obtained using a statistical regression technique. Surface fitting is used to best fit the series of data and the results show that the error value in estimating the SBP is 4.95% and in estimating the DBP is 3.99%.

Keywords: blood pressure, noninvasive optical system, principal component analysis, PCA, continuous monitoring

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Authors: Keivan Davami, Michael Munther, Lloyd Hackel

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The control of properties and material behavior by implementing thermal-mechanical processes is based on mechanical deformation and annealing according to a precise schedule that will produce a unique and stable combination of grain structure, dislocation substructure, texture, and dispersion of precipitated phases. The authors recently developed a thermal-mechanical technique to stabilize the microstructure of additively manufactured nickel-based superalloys even after exposure to high temperatures. However, the mechanism(s) that controls this stability is still under investigation. Laser peening (LP), also called laser shock peening (LSP), is a shock based (50 ns duration) post-processing technique used for extending performance levels and improving service life of critical components by developing deep levels of plastic deformation, thereby generating high density of dislocations and inducing compressive residual stresses in the surface and deep subsurface of components. These compressive residual stresses are usually accompanied with an increase in hardness and enhance the material’s resistance to surface-related failures such as creep, fatigue, contact damage, and stress corrosion cracking. While the LP process enhances the life span and durability of the material, the induced compressive residual stresses relax at high temperatures (>0.5Tm, where Tm is the absolute melting temperature), limiting the applicability of the technology. At temperatures above 0.5Tm, the compressive residual stresses relax, and yield strength begins to drop dramatically. The principal reason is the increasing rate of solid-state diffusion, which affects both the dislocations and the microstructural barriers. Dislocation configurations commonly recover by mechanisms such as climbing and recombining rapidly at high temperatures. Furthermore, precipitates coarsen, and grains grow; virtually all of the available microstructural barriers become ineffective.Our results indicate that by using “cyclic” treatments with sequential LP and annealing steps, the compressive stresses survive, and the microstructure is stable after exposure to temperatures exceeding 0.5Tm for a long period of time. When the laser peening process is combined with annealing, dislocations formed as a result of LPand precipitates formed during annealing have a complex interaction that provides further stability at high temperatures. From a scientific point of view, this research lays the groundwork for studying a variety of physical, materials science, and mechanical engineering concepts. This research could lead to metals operating at higher sustained temperatures enabling improved system efficiencies. The strengthening of metals by a variety of means (alloying, work hardening, and other processes) has been of interest for a wide range of applications. However, the mechanistic understanding of the often complex processes of interactionsbetween dislocations with solute atoms and with precipitates during plastic deformation have largely remained scattered in the literature. In this research, the elucidation of the actual mechanisms involved in the novel cyclic LP/annealing processes as a scientific pursuit is investigated through parallel studies of dislocation theory and the implementation of advanced experimental tools. The results of this research help with the validation of a novel laser processing technique for high temperature applications. This will greatly expand the applications of the laser peening technology originally devised only for temperatures lower than half of the melting temperature.

Keywords: laser shock peening, mechanical properties, indentation, high temperature stability

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Authors: Elida Cena

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Return migration is receiving increased attention as the phenomenon challenges assumptions of natural ‘homecomings’. This talk outlines preliminary findings from an ongoing PhD study which explores return migration of Albanian migrants (aged 30-50 years) and their children (aged 7-18 years). Participants (n=51) were purposively recruited from two Albanian cities with divergent social and economic conditions, and the majority had returned from Greece following the recent economic downturn in that country. Qualitative data were collected through in-depth interviews with respondents aged 13 years and above, and were augmented with focus groups and family case studies. Data collection for case studies was aided by photo elicitation, interviews and participatory techniques (drawing) were employed for children aged 7-12 years. Through a multidisciplinary perspective, findings will uncover experiences of migrants and children upon return, the quest to identify with the originating country and create a sense of belongingness. Narrative analysis reveals that the abrupt return was associated with ambivalent feelings and disillusionment about their (re)settlement for both younger and older participants. Faced with unexpected realities and lack of opportunities, particularly for the children of migrants, Albania is viewed as a ‘transit country’, a temporary solution to escape the crisis in the destination country and move to a more developed western country. Adult return migrants articulate lack of employment and insecurity for the future. Apart from school difficulties, children experience isolation and social exclusion, marked by stigmatized labelling from other peers which exacerbates their belonging. Such mobilities have had deeper effects in complicating family relationships as influenced by many disintegration factors. Feelings of alienation and being emigrant for the second time were common in participants' accounts. Findings concerning the difficulties of individuals (re)connecting with their ethnic background and the impact on their identities are discussed in relation to the literature on return migration and identification.

Keywords: return migration, belonging, identity, disintegration, integration

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Authors: Vasilii V. Ananev

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Oil-and-gas potential of Cuba is found through the discoveries among which there are the most large-scale deposits, such as the Boca de Jaruco and Varadero fields of heavy oils. Currently, the petroleum and petroleum products needs of the island state are satisfied by own sources by less than a half. The prospects of the hydrocarbon resource base development are connected with the adjacent water area of the Gulf of Mexico where foreign companies had been granted license blocks for geological study and further development since 2001. Two Russian companies - JSC Gazprom Neft and OJSC Zarubezhneft, among others, took part in the development of the Cuban part of the Gulf of Mexico. Since 2004, five oil wells have been drilled by various companies in the deep waters of the exclusive economic zone of Cuba. Commercial oil-and-gas bearing prospects have been established in neither of them for both geological and technological reasons. However, only a small part of the water area has been covered by drilling and the productivity of the drill core has been tested at the depth of Cretaceous sediments only. In our opinion, oil-and-gas bearing prospects of the exclusive economic zone of the Republic of Cuba in the Gulf of Mexico remain undervalued and the mentioned water area needs additional geological exploration. The planning of exploration work in this poorly explored region shall be carried out systematically and it shall be based on the results of the regional scientific research.

Keywords: Cuba, catoche, geology, exploration

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Authors: Chandan Deep Singh, Jaimal Singh Khamba, Harleen Kaur

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Eminence, charge, deliverance, modernism, and awareness underlie most manufacturing strategic plan today. Firms have traditionally pursued the above tasks through the implementation of advanced technologies and manufacturing practices, such as Reverse Engineering, Value Engineering, worker empowerment, etc. Recent developments in industry suggest the materialization of another route to manufacturing brilliance, that is, there is an increasing focus by industry regulators and professional bodies on the need to stimulate innovation in a broad range of manufacturing competencies. By ‘competencies’ we mean the methods, equipment and expertise that can be developed as a leading capability in one market sector or application and have real potential to be applied successfully across other sectors or applications as well. Further, competencies are the ability to apply or use a set of related knowledge, skills, and abilities to perform 'critical work functions' or tasks in a defined work setting. Competencies often serve as the basis for skill standards that specify the level of knowledge, skills, and abilities required for success in the workplace as well as potential measurement criteria for assessing competency attainment. The present research is so designed to come up to the level of the expectations of the industrialists, policy makers, designers of the competencies, specially, the manufacturing competencies upon which the whole strategic success of the industry depends.

Keywords: manufacturing competency, strategic success, manufacturing excellence, competitive strategy

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Authors: Elsyed Fath Khalifa, Samer Mohamed Daghash

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The present study was carried out to investigate the structure of the masseter muscle of camel and its attachments to the skull as well as the relationships with its arterial blood supply. Fourteen heads of clinically healthy camels of different ages and sexes were used in the present investigation. The both common carotid arteries of six specimens were cannulated and flushed with warm normal saline solution (0.9%) then injected with red colored neoprine (60%) latex in order to study the pattern of the blood supply to the masseter muscle. Two heads were injected with an eventually mixture of 75gm red lead oxide in 150cc latex and preserved in a cold room for 3-4 days then divided sagittaly along the median plane to avoid super imposition of the arteries. The arteries of the masseter muscle of each half were radiographed. Four heads were used in manual dissection to describe the laminar arrangement of the masseter muscle. The masseter muscle of the camel was very tendinous and was situated far caudally, which enable the camel to open its jaw very wide. In the camel, the masseter muscle was recognized into proper and improper masseter groups. The proper group included the first, second superficial, intermediate and deep masseter layers. The improper group consisted of maxillo-mandibularis and zygomatico-mandibularis. The remaining two heads were used for clearance.

Keywords: anatomy, camel, masseter, lamination, blood supply

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Authors: Vidhu Mitha Goutham, Ruma Mukherjee

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The low availability of well-trained, unlimited, dynamic-access models for specific languages makes it hard for corporate users to adopt quick translation techniques and incorporate them into product solutions. As translation tasks increasingly require a dynamic sequence learning curve; stable, cost-free opensource models are scarce. We survey and compare current translation techniques and propose a modified sequence to sequence model repurposed with attention techniques. Sequence learning using an encoder-decoder model is now paving the path for higher precision levels in translation. Using a Convolutional Neural Network (CNN) encoder and a Recurrent Neural Network (RNN) decoder background, we use Fairseq tools to produce an end-to-end bilingually trained Spanish-English machine translation model including source language detection. We acquire competitive results using a duo-lingo-corpus trained model to provide for prospective, ready-made plug-in use for compound sentences and document translations. Our model serves a decent system for large, organizational data translation needs. While acknowledging its shortcomings and future scope, it also identifies itself as a well-optimized deep neural network model and solution.

Keywords: attention, encoder-decoder, Fairseq, Seq2Seq, Spanish, translation

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Authors: Hao Yuan, Yongjian Shen, Xiangjun He, Yuheng Li, Zhouzhou Zhang, Pengyu Zhang, Minkang Cai

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Remote sensing data can provide support for decision-making in disaster assessment or disaster relief. The traditional processing methods of sensitive targets in remote sensing mapping are mainly based on manual retrieval and image editing tools, which are inefficient. Methods based on deep learning for sensitive target hiding are faster and more flexible. But these methods have disadvantages in training time and cost of calculation. This paper proposed a target hiding model Self Attention (SA) Deepfill, which used self-attention modules to replace part of gated convolution layers in image inpainting. By this operation, the calculation amount of the model becomes smaller, and the performance is improved. And this paper adds free-form masks to the model’s training to enhance the model’s universal. The experiment on an open remote sensing dataset proved the efficiency of our method. Moreover, through experimental comparison, the proposed method can train for a longer time without over-fitting. Finally, compared with the existing methods, the proposed model has lower computational weight and better performance.

Keywords: remote sensing mapping, image inpainting, self-attention mechanism, target hiding

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Authors: Farhat Sultana

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Originality: TQM principles are considered the tools to enhance organizational performance for most organizations. The paper contributes to the literature on the social enterprise because social organizations are still far behind in implementing TQM as compared to other private, public, and nonprofit organizations. Study design: The study is based on the data and information provided by two case studies and one focus group of social enterprises. Purpose: The purpose of the study is to get a deep understating of TQM implementation and to recognize the enablers of TQM in social enterprises that enhance the organizational performance of social enterprises located in UAE. Findings: As per the findings of the study, key enablers of Total Quality management in the case enterprises are leadership support, strategic approach for quality, continuous improvement, process improvement, employee empowerment and customer focus practices, though some inhibitors for TQM implementation such as managerial structure for quality assurance and performance appraisal mechanism are also pointed out by the study. Research limitations: The study findings are only based on two case studies and one focus group, which is not enough to generalize the findings to all social organizations. Practical Implications: Identified TQM enablers can help management to implement TQM successfully in social enterprises. Social implications: The study provides enabling path for Social enterprises to implement TQM to seek quality output to build a better society.

Keywords: TQM, social enterprise, enablers of TQM, UAE

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Authors: Michelangelo Sofo, Giuseppe Labianca

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In recent years, the scientific community's interest in the exploratory analysis of biomedical data has increased exponentially. Considering the field of research of nutritional biologists, the curative process, based on the analysis of clinical data, is a very delicate operation due to the fact that there are multiple solutions for the management of pathologies in the food sector (for example can recall intolerances and allergies, management of cholesterol metabolism, diabetic pathologies, arterial hypertension, up to obesity and breathing and sleep problems). In this regard, in this research work a system was created capable of evaluating various dietary regimes for specific patient pathologies. The system is founded on a mathematical-numerical model and has been created tailored for the real working needs of an expert in human nutrition using the human-centered design (ISO 9241-210), therefore it is in step with continuous scientific progress in the field and evolves through the experience of managed clinical cases (machine learning process). DietAdhoc® is a decision support system nutrition specialists for patients of both sexes (from 18 years of age) developed with an agile methodology. Its task consists in drawing up the biomedical and clinical profile of the specific patient by applying two algorithmic optimization approaches on nutritional data and a symbolic solution, obtained by transforming the relational database underlying the system into a deductive database. For all three solution approaches, particular emphasis has been given to the explainability of the suggested clinical decisions through flexible and customizable user interfaces. Furthermore, the system has multiple software modules based on time series and visual analytics techniques that allow to evaluate the complete picture of the situation and the evolution of the diet assigned for specific pathologies.

Keywords: medical decision support, physiological data extraction, data driven diagnosis, human centered AI, symbiotic AI paradigm

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Authors: Panisa Panyalert

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This research presents the tourism industry at Nakhon Sawan province in an aspect of developing points of attractions and destinations. The author attempts to empirically analyze the tourist destination, Nakhon Sawan, by using components of the tourism inventory include: attraction, accessibility, accommodation and amenity. An understanding of existing tourism product is very important in order to find out strength and weakness by comparing with the nearby well-known tourist destination, Phitsanulok province. Moreover, the hypothetical evolution of a tourist area will be utilized as a framework for indicating stages of the destination in relation to number of tourists. The study uses secondary data of number of tourist arrivals in Nakhon Sawan from 2008 to 2013 receiving from National Statistical Office and Nakhon Sawan Provincial Administration Organization (NPAO) in order to find the stage of destination development, and an in-depth interview with several open-ended questions would be preferred in order to get deep details of necessary data by video recording with ten respondents. The findings are concentrated on potential places and sites, existing tourism product, strength and weakness, and positioning to assist the province to be the destination of tourists’ mind.

Keywords: destination development, destination management, tourism inventory, tourism product

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Authors: Xiaohua Zou, Yongxin Su

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The reasonable operation of heating, ventilation, and air conditioning (HVAC) is of great significance in improving the security, stability, and economy of power system operation. However, the uncertainty of the operating environment, thermal comfort varies by users and rapid decision-making pose challenges for HVAC demand response optimization. In this regard, this paper proposes a reinforcement learning-based method for HVAC demand response optimization considering few-shot personalized thermal comfort (PTC). First, an HVAC DR optimization framework based on few-shot PTC model and DRL is designed, in which the output of few-shot PTC model is regarded as the input of DRL. Then, a few-shot PTC model that distinguishes between awake and asleep states is established, which has excellent engineering usability. Next, based on soft actor criticism, an HVAC DR optimization algorithm considering the user’s PTC is designed to deal with uncertainty and make decisions rapidly. Experiment results show that the proposed method can efficiently obtain use’s PTC temperature, reduce energy cost while ensuring user’s PTC, and achieve rapid decision-making under uncertainty.

Keywords: HVAC, few-shot personalized thermal comfort, deep reinforcement learning, demand response

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Authors: A B M Enamol Hassan

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The forest storing up in Bangladesh is of deep concern to policy analysts because of increasing encroachment that results in deforestation and degradation of the ecosystem. To address these problems, forest-dependent people, as responsible for encroachment, could be involved in the co-management process along with other local stakeholders through a participatory approach. On the basis of this premise, this paper conceptualizes and empirically assesses the integration of all stakeholders in the co-management process through two lenses such as participation and collaboration. The study also analyzed the issues of sustainability in local communities along with examining constraints that limit the processes of integration. The study used a qualitative research method, which included face-to-face interviews with semi-structured questionnaires and field notes following the purposive sampling technique focusing on Comilla Sadar South Upazila (CSSU), Bangladesh. The findings of this paper reveal beneficiaries, Bangladesh Forest Department (BFD) and Union Parishad (UP), come together as leading actors, while NGOs and business entrepreneurs are ignored in the co-management process of social forestry. However, integrated management contributes to the strength of community sustainability, although it has some major limitations causing the matter of concerns among the local communities and policy analysts.

Keywords: integration, participation, collaboration, stakeholders, community sustainability

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Authors: Frew Yirgalem Mane

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This study has examined Africa’s experiment with authoritarian model of development drawing from the experience of Ethiopia. With the tectonic crisis of neoliberal ideology, the dominant policy agenda in Africa pertains to bringing the state back to development. More concretely, countries epitomized by Ethiopia, Rwanda and Uganda have been constructing a highly interventionist state with authoritarian character. The central motive appears to facilitate development and salvage people out of appalling and grinding poverty. Each country warrants closer inspection. However, this study focuses on Ethiopia- a country often applauded as ‘Africa’s Great Run’ for delivering socio-economic success over the past two decades. In fact, inspired by East Asia’s including Chinese model of authoritarian development, Ethiopia orchestrated a vanguard party, centralized rent control system with politicized bureaucracy and militaristic mobilization resources for development. This arrangement may explain Ethiopia economic success story as one the fastest growing countries in the world. However, this paper detected, Ethiopia’s attempt to bring the state back in development has precipitated institutionalization of a new breed of authoritarianism and informalization of public institutions. Ethiopia’s model of state-led development may constitute a noticeable shift away from the vengeful adherence to neoliberal policies. However, the manner the model has been practiced proved to be neither smooth nor appears to address Ethiopia’s aspiration for political and economic transformation. Partly, this can be illustrated by recent widespread grievances that fed into the popular uprising and animated opposition against the state. Sources of the grievance are complex, but they are highly ingrained with the way the authoritarian model of development is functioning and also the model’s dis-functioning in terms of benefiting people. In light of these findings, the study has arrived at the following conclusion. Africa’s attempt to emulate development models from other countries is not such a ‘bad’ thing. However, emulation makes sense if it is contextualized and sensitive to complex local socio-economic interests.

Keywords: Africa, authoritarianism, development, Ethiopia, neoliberalism

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Authors: Todd H. Buxton, Yong G. Lai

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Temperature management in regulated rivers can involve significant expenditures of water to meet the cold-water requirements of species in summer. For this purpose, flows released from Lewiston Dam on the Trinity River in Northern California are 12.7 cms with temperatures around 11oC in July through September to provide adult spring Chinook cold water to hold in deep pools and mature until spawning in fall. The releases are more than double the flow and 10oC colder temperatures than the natural conditions before the dam was built. The high, cold releases provide springers the habitat they require but may suppress the stream food base and limit future populations of salmon by reducing the juvenile fish size and survival to adults via the positive relationship between the two. Field and modeling research was undertaken to explore whether lowering summer releases from Lewiston Dam may promote thermal stratification in river pools so that both the cold-water needs of adult salmon and warmer water requirements of other organisms in the stream biome may be met. For this investigation, a three-dimensional (3D) computational fluid dynamics (CFD) model was developed and validated with field measurements in two deep pools on the Trinity River. Modeling and field observations were then used to identify the flows and temperatures that may form and maintain thermal stratification under different meteorologic conditions. Under low flows, a pool was found to be well mixed and thermally homogenous until temperatures began to stratify shortly after sunrise. Stratification then strengthened through the day until shading from trees and mountains cooled the inlet flow and decayed the thermal gradient, which collapsed shortly before sunset and returned the pool to a well-mixed state. This diurnal process of stratification formation and destruction was closely predicted by the 3D CFD model. Both the model and field observations indicate that thermal stratification maintained the coldest temperatures of the day at ≥2m depth in a pool and provided water that was around 8oC warmer in the upper 2m of the pool. Results further indicate that the stratified pool under low flows provided almost the same daily average temperatures as when flows were an order of magnitude higher and stratification was prevented, indicating significant water savings may be realized in regulated streams while also providing a diversity in water temperatures the ecosystem requires. With confidence in the 3D CFD model, the model is now being applied to a dozen pools in the Trinity River to understand how pool bathymetry influences thermal stratification under variable flows and diurnal temperature variations. This knowledge will be used to expand the results to 52 pools in a 64 km reach below Lewiston Dam that meet the depth criteria (≥2 m) for spring Chinook holding. From this, rating curves will be developed to relate discharge to the volume of pool habitat that provides springers the temperature (<15.6oC daily average), velocity (0.15 to 0.4 m/s) and depths that accommodate the escapement target for spring Chinook (6,000 adults) under maximum fish densities measured in other streams (3.1 m3/fish) during the holding time of year (May through August). Flow releases that meet these goals will be evaluated for water savings relative to the current flow regime and their influence on indicator species, including the Foothill Yellow-Legged Frog, and aspects of the stream biome that support salmon populations, including macroinvertebrate production and juvenile Chinook growth rates.

Keywords: 3D CFD modeling, flow regulation, thermal stratification, chinook salmon, foothill yellow-legged frogs, water managment

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Authors: Girish J. Showkatramani, Arthi M. Krishna, Sashi Nareddi, Naresh Nula, Aaron Pepe, Glen Brown, Greg Gabel, Chris Doninger

Abstract:

Trademark examination and approval is a complex process that involves analysis and review of the design components of the marks such as the visual representation as well as the textual data associated with marks such as marks' description. Currently, the process of identifying marks with similar visual representation is done manually in United States Patent and Trademark Office (USPTO) and takes a considerable amount of time. Moreover, the accuracy of these searches depends heavily on the experts determining the trademark design codes used to catalog the visual design codes in the mark. In this study, we explore several methods to automate trademark design code classification. Based on recent successes of convolutional neural networks in image classification, we have used several different convolutional neural networks such as Google’s Inception v3, Inception-ResNet-v2, and Xception net. The study also looks into other techniques to augment the results from CNNs such as using Open Source Computer Vision Library (OpenCV) to pre-process the images. This paper reports the results of the various models trained on year of annotated trademark images.

Keywords: trademark design code, convolutional neural networks, trademark image classification, trademark image search, Inception-ResNet-v2

Procedia PDF Downloads 232

Authors: Taylor Kolody, Farkhund Iqbal, Rabia Batool, Benjamin Fung, Mohammed Hussaeni, Saiqa Aleem

Abstract:

The rising threat of climate change has led to an increase in public awareness and care about our collective and individual environmental impact. A key component of this impact is our use of cars and other polluting forms of transportation, but it is often difficult for an individual to know how severe this impact is. While there are applications that offer this feedback, they require manual entry of what transportation mode was used for a given trip, which can be burdensome. In order to alleviate this shortcoming, a data from the 2016 TRIPlab datasets has been used to train a variety of machine learning models to automatically recognize the mode of transportation. The accuracy of 89.6% is achieved using single deep neural network model with Gated Recurrent Unit (GRU) architecture applied directly to trip data points over 4 primary classes, namely walking, public transit, car, and bike. These results are comparable in accuracy to results achieved by others using ensemble methods and require far less computation when classifying new trips. The lack of trip context data, e.g., bus routes, bike paths, etc., and the need for only a single set of weights make this an appropriate methodology for applications hoping to reach a broad demographic and have responsive feedback.

Keywords: classification, gated recurrent unit, recurrent neural network, transportation

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Authors: Bing Li, Zhi Li, Yilong Yang

Abstract:

Web classification can promote the quality of service discovery and management in the service repository. It is widely used to locate developers desired services. Although traditional classification methods based on supervised learning models can achieve classification tasks, developers need to manually mark web services, and the quality of these tags may not be enough to establish an accurate classifier for service classification. With the doubling of the number of web services, the manual tagging method has become unrealistic. In recent years, the attention mechanism has made remarkable progress in the field of deep learning, and its huge potential has been fully demonstrated in various fields. This paper designs a multi-head attention graph convolutional network (MHAGCN) service classification method, which can assign different weights to the neighborhood nodes without complicated matrix operations or relying on understanding the entire graph structure. The framework combines the advantages of the attention mechanism and graph convolutional neural network. It can classify web services through automatic feature extraction. The comprehensive experimental results on a real dataset not only show the superior performance of the proposed model over the existing models but also demonstrate its potentially good interpretability for graph analysis.

Keywords: attention mechanism, graph convolutional network, interpretability, service classification, service discovery

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Authors: Anasuya Ghosh, Subhramoy Chaudhury

Abstract:

During routine cadaveric dissection at gross anatomy lab of our institution, a radial artery was found with unusual origin and superficial course. Normally the radial artery takes its origin as one of the terminal branches of brachial artery at the level of the neck of radius. It usually lies along the lateral border of fore arm deep to the brachioradialis muscle. While dissecting a 72-year-old Caucasian female cadaver, it was found that the right sided radial artery originated from the upper part of brachial artery of arm, 2 cm below the lower border of teres major muscle, from the lateral aspect of brachial artery. Then the radial artery superficially crossed the brachial artery and median nerve from lateral to medial direction and rested superficially at the cubital fossa. Embryologically, it can be explained as a failure of disappearance, or abnormal persistence of some insignificant embryonic vessels may give rise to this kind of vascular anomalies. As radial artery is one of the most important upper limb arteries, its variation and related complications are clinically significant. This unusual origin and course of radial artery should be kept in mind by all healthcare providers including surgeons and radiologists during routine venipuncture, orthopedic and plastic surgeries of arm, coronary angiographic procedures in radial approach etc. to prevent unwanted complications.

Keywords: brachial artery anomalies, brachio-radial artery, high origin radial artery, superficial radial artery

Procedia PDF Downloads 325

Authors: Pennisi Stefania, Giuffrida Graziella, Coppa Federica, Iannello Giulia, Cartelli Simone, Lo Faro Riccardo, Ferruggia Greta, Brundo Maria Violetta

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Tissue engineering aims to develop advanced medical devices to restore normal functions of damaged tissue. These devices, even more effective than conventional methods, are called skin substitutes and are configured as drugs to be applied to the damaged area, to heal extensive and deep wounds which could otherwise lead to chronic wounds lasting over time. Among the variety of commercially available skin substitutes, those that have proven to be most effective are those consisting of a bilayer scaffold. The aim of our research was to design a skin substitute which can promote cell proliferation, cell migration and angiogenesis, and which can guarantee timely closure of the wound with satisfactory aesthetic results, in order to avoid the patient excessive pain, risk of contracting infections and long-term hospitalization. The product was tested in vitro using the Scratch Assay. The assay was carried out both on the matrix modified with hyaluronic acid and on the matrix based only on collagen. In both cases, after 48 hours of exposure the wound scratch was almost completely closed in treated cells compared to untreated control.

Keywords: collagen, hyaluronic acid, scratch- wound-healing assay, tissue regeneration

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Authors: Victor Chinecherem Ejeke, Raphael Eze Nnam

Abstract:

The main objective of this research is to produce biodiesel from waste vegetable oil using activated eggshell waste as solid catalysts. A transesterification reaction was performed for the conversion to biodiesel. Waste eggshells were calcined at 700°C, 800°C and 900°C for a time period of 3hrs for the preparation of the renewable catalyst. The calcined waste eggshell catalyst was characterized using X-Ray Florescence (XRF) Spectroscopy, which revealed CaO as the major constituent (90.86%); this was further confirmed by X-Ray Diffraction (XRD) and Fourier Transform Infrared (FTIR) analyses. The prepared catalyst was used for transesterification reaction and the effects of calcination temperature (700 to 900°C), Deep Eutectic Solvent DES loading (3 to 18 wt. %), Waste Egg Shell (WES) catalyst loading (6 to 14 wt. %) on the conversion to biodiesel were studied. The yield of biodiesel using a waste eggshell catalyst (91%) is comparable to conventional catalyst like sodium hydroxide with a yield of 80-90%. The maximum biodiesel production yield was obtained at a specific oil-to methanol molar ratio of 1:10, a temperature of 65°C and a catalyst loading of 14g-wt%. The biodiesel produced was characterized as being composed of methyl Tetradecanoate (C₁₄H₂₈O₂) 30.92% using the Gas Chromatographic (GC-MS) analysis. The fuel properties of the biodiesel (Flashpoint 138ᵒC) were comparable to commercial diesel, and hence it can be used in compression-ignition engines. The results indicated that the catalysts derived from waste eggshell had high potential to be used as biodiesel production catalysts in transesterification of waste vegetable oil with the advantage of reusability and also not requiring water washing steps.

Keywords: waste vegetable oil, catalyst , biodiesel , waste egg shell

Procedia PDF Downloads 211

Authors: Journey Whitfield

Abstract:

This study investigates the United States' ongoing violation of Black Americans' fundamental human rights, as evidenced by mass incarceration, social injustice, and economic deprivation. It argues that the U.S. contravenes Article 9 of the International Covenant on Civil and Political Rights through policies that uphold systemic racism. The analysis dissects current practices within the criminal justice system, social welfare programs, and economic policy, uncovering the racially disparate impacts of seemingly race-neutral policies. This study establishes a clear lineage between past systems of oppression – slavery and Jim Crow – and present-day racial disparities, demonstrating their inextricable link. The thesis proposes that only a comprehensive reparations program for Black Americans can begin to redress these systemic injustices. This program must transcend mere financial compensation, demanding structural reforms within U.S. institutions to dismantle systemic racism and promote transformative justice. This study explores potential forms of reparations, drawing upon historical precedents, comparative case studies from other nations, and contemporary debates within political philosophy and legal studies. The research employs both qualitative and quantitative methods. Qualitative methods include historical analysis of legal frameworks and policy documents, as well as discourse analysis of political rhetoric. Quantitative methods involve statistical analysis of socioeconomic data and criminal justice outcomes to expose racial disparities. This study makes a significant contribution to the existing literature on reparations, human rights, and racial injustice in the United States. It offers a rigorous analysis of the enduring consequences of historical oppression and advocates for bold, justice-centered solutions.

Keywords: Black Americans, reparations, mass incarceration, racial injustice, human rights, united states

Procedia PDF Downloads 58