Search results for: enabling

Authors: Anjalika Fernando, Banuka Athuraliya

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This paper presents a comprehensive approach for converting Sinhala Sign Language (SSL) into grammatically correct sentences using Natural Language Processing (NLP) techniques in real-time. While previous studies have explored various aspects of SSL translation, the research gap lies in the absence of grammar checking for SSL. This work aims to bridge this gap by proposing a two-stage methodology that leverages deep learning models to detect signs and translate them into coherent sentences, ensuring grammatical accuracy. The first stage of the approach involves the utilization of a Long Short-Term Memory (LSTM) deep learning model to recognize and interpret SSL signs. By training the LSTM model on a dataset of SSL gestures, it learns to accurately classify and translate these signs into textual representations. The LSTM model achieves a commendable accuracy rate of 94%, demonstrating its effectiveness in accurately recognizing and translating SSL gestures. Building upon the successful recognition and translation of SSL signs, the second stage of the methodology focuses on improving the grammatical correctness of the translated sentences. The project employs a Neural Machine Translation (NMT) architecture, consisting of an encoder and decoder with LSTM components, to enhance the syntactical structure of the generated sentences. By training the NMT model on a parallel corpus of Sinhala wrong sentences and their corresponding grammatically correct translations, it learns to generate coherent and grammatically accurate sentences. The NMT model achieves an impressive accuracy rate of 98%, affirming its capability to produce linguistically sound translations. The proposed approach offers significant contributions to the field of SSL translation and grammar correction. Addressing the critical issue of grammar checking, it enhances the usability and reliability of SSL translation systems, facilitating effective communication between hearing-impaired and non-sign language users. Furthermore, the integration of deep learning techniques, such as LSTM and NMT, ensures the accuracy and robustness of the translation process. This research holds great potential for practical applications, including educational platforms, accessibility tools, and communication aids for the hearing-impaired. Furthermore, it lays the foundation for future advancements in SSL translation systems, fostering inclusive and equal opportunities for the deaf community. Future work includes expanding the existing datasets to further improve the accuracy and generalization of the SSL translation system. Additionally, the development of a dedicated mobile application would enhance the accessibility and convenience of SSL translation on handheld devices. Furthermore, efforts will be made to enhance the current application for educational purposes, enabling individuals to learn and practice SSL more effectively. Another area of future exploration involves enabling two-way communication, allowing seamless interaction between sign-language users and non-sign-language users.In conclusion, this paper presents a novel approach for converting Sinhala Sign Language gestures into grammatically correct sentences using NLP techniques in real time. The two-stage methodology, comprising an LSTM model for sign detection and translation and an NMT model for grammar correction, achieves high accuracy rates of 94% and 98%, respectively. By addressing the lack of grammar checking in existing SSL translation research, this work contributes significantly to the development of more accurate and reliable SSL translation systems, thereby fostering effective communication and inclusivity for the hearing-impaired community

Keywords: Sinhala sign language, sign Language, NLP, LSTM, NMT

Procedia PDF Downloads 72

Authors: Efthymios Chondrogiannis, Vassiliki Andronikou, Efstathios Karanastasis, Theodora Varvarigou

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A large amount of data is typically stored in relational databases (DB). The latter can efficiently handle user queries which intend to elicit the appropriate information from data sources. However, direct access and use of this data requires the end users to have an adequate technical background, while they should also cope with the internal data structure and values presented. Consequently the information retrieval is a quite difficult process even for IT or DB experts, taking into account the limited contributions of relational databases from the conceptual point of view. Ontologies enable users to formally describe a domain of knowledge in terms of concepts and relations among them and hence they can be used for unambiguously specifying the information captured by the relational database. However, accessing information residing in a database using ontologies is feasible, provided that the users are keen on using semantic web technologies. For enabling users form different disciplines to retrieve the appropriate data, the design of a Graphical User Interface is necessary. In this work, we will present an interactive, ontology-based, semantically enable web tool that can be used for information retrieval purposes. The tool is totally based on the ontological representation of underlying database schema while it provides a user friendly environment through which the users can graphically form and execute their queries.

Keywords: ontologies, relational databases, SPARQL, web interface

Procedia PDF Downloads 249

Authors: Walid El Kamash

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Sand columns (or granular piles) can be employed as soil strengthening for flexible constructions such as road embankments, oil storage tanks in addition to multistory structures. The challenge of embedding the sand columns in soft soil is that the surrounding soft soil cannot avail the enough confinement stress in order to keep the form of the sand column. Therefore, the sand columns which were installed in such soil will lose their ability to perform needed load-bearing capacity. The encasement, besides increasing the strength and stiffness of the sand column, prevents the lateral squeezing of sands when the column is installed even in extremely soft soils, thus enabling quicker and more economical installation. This paper investigates the improvement in load capacity of the sand column by encasement through a comprehensive parametric study using the 3-D finite difference analysis for the soft clay of soil in Egypt. Moreover, the study was extended to include a comparison study between encased sand column and Deep Mixed columns (DM). The study showed that confining the sand by geosynthetic resulted in an increment of shear strength. That result paid the attention to use encased sand stone rather than deep mixed columns due to relative high permeability of the first material.

Keywords: encased sand column, Deep mixed column, numerical analysis, improving soft soil

Procedia PDF Downloads 349

Authors: Dalhat Binta Dan - Ali

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The reality of the new world economic order and the ever increasing importance of biotechnology in the global economy have necessitated the ratification of the Cartagena Protocol on Biosafety and the recent promulgation of Biosafety Act in Nigeria 2015. The legal regimes are anchored on the need to create an enabling environment for the flourishing of bio-trade and also to ensure the safety of the environment and human health. This paper critically examines the legal framework on biosafety by taking a cursory look at its philosophical foundation, key issues and milestones. The paper argues that the extant laws, though a giant leap in the establishment of a legal framework on biosafety, it posits that the legal framework raises debate and controversy on the difficulties of risk assessment on biodiversity and human health, other challenges includes lack of sound institutional capacity and the regimes direction of a hybrid approach between environmental conservation and trade issues. The paper recommend the need for the country to do more in the area of stimulating awareness and establishment of a sound institutional capacity to enable the law ensure adequate level of protection in the field of safe transfer, handling, and use of genetically modified organisms (GMOs) in Nigeria.

Keywords: Cartagena protocol, biosafety, issues, challenges, biotrade, genetically modified organism (GMOs), environment

Procedia PDF Downloads 299

Authors: Lorna Goulden, Kai M. Hermsen, Jari Isohanni, Mirko Ross, Jef Vanbockryck

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This article introduces disposable identities, with reference use cases and explores possible technical approaches. The proposed approach, when fully developed as an open-source toolkit, enables developers of mobile or web apps to employ a self-sovereign identity and data privacy framework, in order to rebuild trust in digital services by providing greater transparency, decentralized control, and GDPR compliance. With a user interface for the management of self-sovereign identity, digital authorizations, and associated data-driven transactions, the advantage of Disposable Identities is that they may also contain verifiable data such as the owner’s photograph, official or even biometric identifiers for more proactive prevention of identity abuse. These Disposable Identities designed for decentralized privacy management can also be time, purpose and context-bound through a secure digital contract; with verification functionalities based on tamper-proof technology.

Keywords: dentity, trust, self-sovereign, disposable identity, privacy toolkit, decentralised identity, verifiable credential, cybersecurity, data driven business, PETs, GDPRdentity, trust, self-sovereign, disposable identity, privacy toolkit, decentralised identity, verifiable credential, cybersecurity, data driven business, PETs, GDPRI

Procedia PDF Downloads 194

Authors: Mazharuddin Syed Ahmed

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This research presents a framework used to develop The Ara Polytechnic College of Architecture Studies building “Kahukura” which is Green Building certified. This framework integrates the development of a smart building digital twin by utilizing Building Information Modelling (BIM) and its BIM maturity levels, including Levels of Development (LOD), eight dimensions of BIM, Heritage-BIM (H-BIM) and Facility Management BIM (FM BIM). The research also outlines a structured approach to building performance analysis and integration with the circular economy, encapsulated within a five-level digital twin framework. Starting with Level 1, the Descriptive Twin provides a live, editable visual replica of the built asset, allowing for specific data inclusion and extraction. Advancing to Level 2, the Informative Twin integrates operational and sensory data, enhancing data verification and system integration. At Level 3, the Predictive Twin utilizes operational data to generate insights and proactive management suggestions. Progressing to Level 4, the Comprehensive Twin simulates future scenarios, enabling robust “what-if” analyses. Finally, Level 5, the Autonomous Twin, represents the pinnacle of digital twin evolution, capable of learning and autonomously acting on behalf of users.

Keywords: building information modelling, circular economy integration, digital twin, predictive analytics

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Authors: Mohammed Alonazi, Natalia Beloff, Martin White

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This paper presents a proposal for a mobile government adoption and utilization model (MGAUM), which is a framework designed to increase the adoption rate of m-government services in Saudi Arabia. Recent advances in mobile technologies such are Mobile compatibilities, The development of wireless communication, mobile applications and devices are enabling governments to deliver services in new ways to citizens more efficiently and economically. In the last decade, many governments around the globe are utilizing these advances effectively to develop their next generation of e-government services. However, a low adoption rate of m-government services by citizens is a common problem in Arabian countries, including Saudi Arabia. Yet, to our knowledge, very little research has been conducted focused on understanding the factors that influence citizen adoption of these m-government services in this part of the world. A set of social, cultural and technological factors have been identified in the literature, which has led to the formulation of associated research questions and hypotheses. These hypotheses will be tested on Saudi citizens using questionnaires and interview methods based around the technology acceptance model. A key objective of the MGAUM framework is to investigate and understand Saudi citizens perception towards adoption and utilization of m-government services.

Keywords: e-government, m-government, citizen services quality, technology acceptance model, Saudi Arabia, adoption framework.

Procedia PDF Downloads 281

Authors: Peter Joseph Basil Morris, Chhabi Nigam, S. Ramakrishnan, P. Radhakrishna

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This paper brings out the analysis of the airborne Synthetic Aperture Radar (SAR) data using the Range Migration Algorithm (RMA) for the spotlight mode of operation. Unlike in polar format algorithm (PFA), space-variant defocusing and geometric distortion effects are mitigated in RMA since it does not assume that the illuminating wave-fronts are planar. This facilitates the use of RMA for imaging scenarios involving severe differential range curvatures enabling the imaging of larger scenes at fine resolution and at shorter ranges with low center frequencies. The RMA algorithm for the spotlight mode of SAR is analyzed in this paper using the airborne data. Pre-processing operations viz: - range de-skew and motion compensation to a line are performed on the raw data before being fed to the RMA component. Various stages of the RMA viz:- 2D Matched Filtering, Along Track Fourier Transform and Slot Interpolation are analyzed to find the performance limits and the dependence of the imaging geometry on the resolution of the final image. The ability of RMA to compensate for severe differential range curvatures in the two-dimensional spatial frequency domain are also illustrated in this paper.

Keywords: range migration algorithm, spotlight SAR, synthetic aperture radar, matched filtering, slot interpolation

Procedia PDF Downloads 215

Authors: Soofiyan Atar, Adil Shaikh, Sahil Rajpurkar, Pragnesh Bhalala, Aniket Desai, Irfan Siddavatam

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Deep reinforcement learning (deep RL) algorithms leverage the symbolic power of complex controllers by automating it by mapping sensory inputs to low-level actions. Deep RL eliminates the complex robot dynamics with minimal engineering. Deep RL provides high-risk involvement by directly implementing it in real-world scenarios and also high sensitivity towards hyperparameters. Tuning of hyperparameters on a pneumatic quadruped robot becomes very expensive through trial-and-error learning. This paper presents an automated learning control for a pneumatic quadruped robot using sample efficient deep Q learning, enabling minimal tuning and very few trials to learn the neural network. Long training hours may degrade the pneumatic cylinder due to jerk actions originated through stochastic weights. We applied this method to the pneumatic quadruped robot, which resulted in a hopping gait. In our process, we eliminated the use of a simulator and acquired a stable gait. This approach evolves so that the resultant gait matures more sturdy towards any stochastic changes in the environment. We further show that our algorithm performed very well as compared to programmed gait using robot dynamics.

Keywords: model-based reinforcement learning, gait stability, supervised learning, pneumatic quadruped

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Authors: Sherif Keddis, Rafik Mitry, Norbert Schwesinger

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Intelligent networking of devices has rapidly been gaining importance over the past years and with recent advances in the fields of microcontrollers, integrated circuits and wireless communication, low power applications have emerged, enabling this trend even more. Connected devices provide a much larger database thus enabling highly intelligent and accurate systems. Ensuring safe drinking water is one of the fields that require constant monitoring and can benefit from an increased accuracy. Monitoring is mainly achieved either through complex measures, such as collecting samples from the points of use, or through metering systems typically distant to the points of use which deliver less accurate assessments of the quality of water. Constant metering near the points of use is complicated due to their inaccessibility; e.g. buried water pipes, locked spaces, which makes system maintenance extremely difficult and often unviable. The research presented here attempts to overcome this challenge by providing these systems with enough energy through a flow harvester inside the pipe thus eliminating the maintenance requirements in terms of battery replacements or containment of leakage resulting from wiring such systems. The proposed flow harvester exploits the piezoelectric properties of polyvinylidene difluoride (PVDF) films to convert turbulence induced oscillations into electrical energy. It is intended to be used in standard water pipes with diameters between 0.5 and 1 inch. The working principle of the harvester uses a ring shaped bluff body inside the pipe to induce pressure fluctuations. Additionally the bluff body houses electronic components such as storage, circuitry and RF-unit. Placing the piezoelectric films downstream of that bluff body causes their oscillation which generates electrical charge. The PVDF-film is placed as a multilayered wrap fixed to the pipe wall leaving the top part to oscillate freely inside the flow. The warp, which allows for a larger active, consists of two layers of 30µm thick and 12mm wide PVDF layered alternately with two centered 6µm thick and 8mm wide aluminum foil electrodes. The length of the layers depends on the number of windings and is part of the investigation. Sealing the harvester against liquid penetration is achieved by wrapping it in a ring-shaped LDPE-film and welding the open ends. The fabrication of the PVDF-wraps is done by hand. After validating the working principle using a wind tunnel, experiments have been conducted in water, placing the harvester inside a 1 inch pipe at water velocities of 0.74m/s. To find a suitable placement of the wrap inside the pipe, two forms of fixation were compared regarding their power output. Further investigations regarding the number of windings required for efficient transduction were made. Best results were achieved using a wrap with 3 windings of the active layers which delivers a constant power output of 0.53µW at a 2.3MΩ load and an effective voltage of 1.1V. Considering the extremely low power requirements of sensor applications, these initial results are promising. For further investigations and optimization, machine designs are currently being developed to automate the fabrication and decrease tolerance of the prototypes.

Keywords: maintenance-free sensors, measurements at point of use, piezoelectric flow harvesting, universal micro generator, wireless metering systems

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Authors: Soma Gholamveisy, Vahid Mirghavameddin

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Aquaculture activities face wide environmental, social, and economic problems today. To deal with these problems, the aquaculture business, which is already a highly significant agricultural activity, is influenced by sustainability, which can assure the rural community's safety and food health with minimal environmental damage. The objective of this study's systematic review of the literature (SLR) is to look into the use of global perspective Promotion of Sustainable Fisheries and Aquaculture. SLR aims to identify the goals of a promotional system, also one of its main components. This research seeks to empower, increase economic productivity, facilitate, pay more attention to the sustainability of the environment and inform the audience in this regard. A method used to assess hypotheses, condense the results of past studies or verify the consistency of studies. It presents a succinct analysis of original research using an unambiguous and verifiable approach. A thorough repository with a vast array of papers and effective exploration methods are frequently utilized in a systematic literature review, enabling the application of advanced logical statements. A comprehensive literature review was carried out to ensure that the most relevant studies were included. This type of review clarifies publication selection criteria and allows evaluation of the studies conducted and their repetition or extension.

Keywords: systematic review, sustainable, fisheries, aquaculture

Procedia PDF Downloads 58

Authors: Shourav Chowdhury, Subrata Barua, K. M. Naimuddin, Imam Hassan Sajib, Md. Hasan, Shudipta Banik, Muna Das

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Traffic accidents stand as a leading cause of fatalities worldwide, significantly impacting global mortality rates. Accurate classification of road accidents through advanced technological solutions presents a crucial opportunity to revolutionize accident prevention and emergency response strategies. This paper presents an advanced deep-learning methodology customized for the classification of road accidents using CCTV surveillance footage. This real-time dataset, comprising approximately 18,000 frames, has been amassed, which is pivotal for enabling comprehensive research in this field. This substantial dataset is the foundation for these investigative efforts, providing a rich and diverse source for conducting an in-depth analysis of the features. It has achieved a remarkable accuracy of 97% on this dataset through the strategic utilization of transfer learning in conjunction with LSTM (Long short-term memory) techniques. This accomplishment underscores the efficacy of our approach, combining the strengths of transfer learning and LSTM models, resulting in a highly accurate classification system for road accident events.

Keywords: accident, CCTV, footage, long short-term memory, surveillance

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Authors: Galal H. Senussi, Muamar Benisa, Sanja Vasin

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In our business field today, one of the most important issues for any enterprises is cost minimization and profit maximization. Second issue is how to develop a strong and capable model that is able to give us desired forecasting of these two issues. Many researches deal with these issues using different methods. In this study, we developed a model for multi-criteria production program optimization, integrated with Artificial Neural Network. The prediction of the production cost and profit per unit of a product, dealing with two obverse functions at same time can be extremely difficult, especially if there is a great amount of conflict information about production parameters. Feed-Forward Neural Networks are suitable for generalization, which means that the network will generate a proper output as a result to input it has never seen. Therefore, with small set of examples the network will adjust its weight coefficients so the input will generate a proper output. This essential characteristic is of the most important abilities enabling this network to be used in variety of problems spreading from engineering to finance etc. From our results as we will see later, Feed-Forward Neural Networks has a strong ability and capability to map inputs into desired outputs.

Keywords: project profitability, multi-objective optimization, genetic algorithm, Pareto set, neural networks

Procedia PDF Downloads 413

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

Procedia PDF Downloads 74

Authors: Sang Beom Kim, Kyung Ju Kim, Myung Hoon Cho, Ji Hoon Kim, Soo Hyung Kim

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In this study, we systematically investigated the effect of nanoscale energetic materials in formulations of aluminum nanoparticles (Al NPs; heat source)/copper oxide nanoparticles (CuO NPs; oxidizer) on the combustion and gas-generating properties of sodium azide microparticles (NaN3 MPs; gas-generating agent) for potential applications in gas generators. The burn rate of the NaN3 MP/CuO NP composite powder was only ~0.3 m/s. However, the addition of Al NPs to the NaN3 MP/CuO NP matrix caused the rates to reach ~5.3 m/s, respectively. In addition, the N2 gas volume flow rate generated by the ignition of the NaN3 MP/CuO NP composite powder was only ~0.6 L/s, which was significantly increased to ~3.9 L/s by adding Al NPs to the NaN3 MP/CuO NP composite powder. This suggested that the highly reactive NPs, with the assistance of CuO NPs, were effective heat-generating sources enabling the complete thermal decomposition of NaN3 MPs upon ignition. Al NPs were highly effective in the gas generators because of the increased reactivity induced by the reduced particle size. Finally, we successfully demonstrated that a homemade airbag with a specific volume of ~140 mL could be rapidly and fully inflated by the thermal activation of nanoscale energetic material-added gas-generating agents (i.e., NaN3 MP/Al NP/CuO NP composites) within the standard time of ~50 ms for airbag inflation.

Keywords: nanoenergetic materials, aluminum nanoparticles, copper oxide nanoparticles, gas generators

Procedia PDF Downloads 340

Authors: Suppawan Lertpongpakpoom, Anongnat Boonrat, Kunya BoontummoSuppawan

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This descriptive cost analysis aimed to analyze the unit cost of patients in medical intensive care unit. Purposive sampling was used to select 20 nurses, 6 practical nurses, 5 nurses aid and select samples 30 patients. Data were collected from both primary source (activity and average time of nursing care) and secondary source Z bill of payment and patient record). Instruments were cost recording form, activity observation form, and service recording form. Content validity of all instruments were evaluated by three experts (CVI = 0.87). Descriptive statistics was employed for data analysis. The results of the Activity-Based Costing Analysis showed that total activity cost of 4 service types for the patients was 14,776.92 Bath. The highest cost was nursing record was 5,674.78 Bath, followed direct nursing activity was 5,176.18 Bath, medical treatment was 1,976.6 Bath. The lowest cost was management activity was 1,003.64 Bath per visit. The result suggested that Activity-Base Costing Analysis could be applied to give better understanding of cost structure, enabling better consideration wasted expense and non-value-added activity, and improvement of effective utilization.

Keywords: activity-based costing, medical intensive care, nursing care, cost analysis

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Authors: Asmae Chraibi, Rachid Lghoul, Nabil Rhiati

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In the era of Industry 4.0, enterprises are increasingly employing digital technologies in order to improve their product development processes. This research focuses on the strategic deployment of Product Lifecycle Management (PLM) solutions during production as a key tracker of traceability and digital transformation activities. The study explores the integration of PLM within a larger organizational framework, examining its impact on product lifecycle efficiency, corporation, and innovation. Through a comprehensive analysis of a real case study from the automotive industry, this project evaluates the critical success factors and challenges associated with implementing PLM solutions for digital transformation. Moreover, it explores the synergic relationship between PLM and emerging technologies such as 3D experience and SOLIDWORKS, elucidating their combined potential in optimizing production workflows and enabling data-driven decision-making. The study's findings provide global approaches for firms looking to embark on a digital transformation journey by implementing PLM technologies. This research contributes to a better understanding of how PLM can be effectively used to foster innovation and competitiveness in the changing landscape of modern industry by shining light on best practices, critical considerations, and potential obstacles.

Keywords: product lifecyle management (PLM), industry 4.0, traceability, digital transformation, solution, innovation, 3D experience, SOLIDWORKS

Procedia PDF Downloads 38

Authors: Iddrisu Ibrahim, Joseph Atia Ayariga, Junhuan Xu, Daniel A. Abugri, Robertson K. Boakai, Olufemi S. Ajayi

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The recalcitrance of pathogenic bacteria indicates that millions of people who are at risk of infection arising from chronic diseases, surgery, organ transplant, diabetes, and several other debilitating diseases present an aura of potentially untreatable illness due to resistance development. Antimicrobial resistance has successfully become a global health menace, and resistances are often acquired by bacteria through health-care-related incidence (HRI) orchestrated by multi-drug resistant (MDR) and extended drug-resistant pathogens (EDRP). To understand the mechanisms S. Typhimurium uses to resist CDB, we study the abundance of LPS modification, Ergosterols, Mysristic palmitic resistance, Oleic acid resistance of susceptible and resistant S. Typhimurium. Using qPCR, we also analyzed the expression of selected genes known for enabling resistance in S. Typhimurium. We found high abundance of LPS, Ergosterols, Mysristic palmitic resistance, Oleic acid resistance of and high expression of resistant genes in S. Typhimurium compared to the susceptible strain. LPS modification, Ergosterols, Mysristic palmitic resistance, Oleic acid and genes such as Fims, integrons, blaTEM are important indicators of resistance development of S. typhimurium.

Keywords: antimicrobials, resistance, Cannabidiol, Salmonella, blaTEM, fimA, Lipopolysaccharide, Ergosterols

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Authors: Menelik Tilahun Alemu

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Customs administrations are now increasingly regarded as the key border agencies responsible for all transactions related to issues arising from the border crossings of goods and people. Raising revenue has traditionally been high on the agenda of governments, represented by the Ministry of Finance (MOF), because of the critical importance of import duties as a source of budget revenue for many developing countries. Most of these functions are undertaken in close cooperation with other national agencies. Due to the need to make structural reforms that consider the nature of business activities in the world and the needs of consumers, the institution was previously divided into the Ministry of Revenue and the Customs Commission. Accordingly, the Ministry of Revenue is primarily responsible for administering and collecting local taxes, while the Customs Commission is responsible for administering customs matters; It supports exports and collects revenue from it. The National Import and Export Trade Service System is working to make the world more transparent and standardized and adapt to the current situation by formulating various guidelines, rules and procedures to provide a clear, simple, predictable and accessible service to customers. As a result, the commission will be able to streamline the business process by enabling Paperless customer service to support the service delivery technology and eliminate the customer iteration without having to incur unnecessary costs and inconveniences.

Keywords: business, consumers, adapt, transparent

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Authors: Andrew Sutherland

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In many ways, opera is not a natural domain for children. It is hardly surprising that from the thousands of works, comparatively few include roles for children. There are several possibilities for this, the dramatic themes in opera are often about the human condition from the adult perspective; the need for developed voices to project in large, theatrical spaces underpinned by orchestral accompaniment does not naturally suit the child’s voice, and enabling children to cope with long runs of performances on top of their education requires vocal and physical stamina. In more recent times, the involvement of children contributes another layer of difficulty in terms of having access to young singers while adhering to laws that protect their working rights. Despite these points, children have been in opera since its inception in a variety of ways, but their contribution is often undervalued or ignored by musicologists and even the industry itself. In this paper, the phenomenon of children in opera from the late 16th century to the present day is explored through empirical, socio-musicological observations with reference to score analysis. Conclusions are drawn regarding the changing attitudes of composers when scoring for children’s voices in relation to societal developments. From the use of ‘kindertruppen’ in the pre-enlightenment period to Handel’s virtuosic writing for William Savage, to the darkness of the inter-war eras which saw a proliferation of operatic characters for children and the post-war era which saw children as the new frontier of building audiences for opera, the links between changes in society and the inclusion, portrayal and scoring for children in opera are largely congruent.

Keywords: children, musical analysis, opera, sociology

Procedia PDF Downloads 91

Authors: Tesfaye Mengistu

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This thesis aims to investigate the effectiveness of Reinforcement Learning (RL) for Autonomous Energy Management solutions. The study explores the potential of Model Free RL approaches, such as Monte Carlo RL and Q-learning, to improve energy management by autonomously adjusting energy management strategies to maximize efficiency. The research investigates the implementation of RL algorithms for optimizing energy consumption in a single-agent environment. The focus is on developing a framework for the implementation of RL algorithms, highlighting the importance of RL for enabling autonomous systems to adapt quickly to changing conditions and make decisions based on previous experiences. Moreover, the paper proposes RL as a novel energy management solution to address nations' CO2 emission goals. Reinforcement learning algorithms are well-suited to solving problems with sequential decision-making patterns and can provide accurate and immediate outputs to ease the planning and decision-making process. This research provides insights into the challenges and opportunities of using RL for energy management solutions and recommends further studies to explore its full potential. In conclusion, this study provides valuable insights into how RL can be used to improve the efficiency of energy management systems and supports the use of RL as a promising approach for developing autonomous energy management solutions in residential buildings.

Keywords: artificial intelligence, reinforcement learning, monte carlo, energy management, CO2 emission

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Authors: Hamed Zolfaghari, Mojtaba Kord

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Project planners and controllers are frequently faced with the challenge of inadequate software for the preparation of automatic project progress reports based on actual project information updates. They usually make dashboards in Microsoft Excel, which is local and not applicable online. Another shortcoming is that it is not linked to planning software such as Microsoft Project, which lacks the database required for data storage. This study aimed to propose a model for the preparation of reports on automatic online project progress based on actual project information updates by the integration of Primavera P6, SQL database, and Power BI for a construction project. The designed model could be applicable to project planners and controller agents by enabling them to prepare project reports automatically and immediately after updating the project schedule using actual information. To develop the model, the data were entered into P6, and the information was stored on the SQL database. The proposed model could prepare a wide range of reports, such as earned value management, HR reports, and financial, physical, and risk reports automatically on the Power BI application. Furthermore, the reports could be published and shared online.

Keywords: primavera P6, SQL, Power BI, EVM, integration management

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Authors: M. Srilatha, R. Hemalatha, T. Sri Aditya

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Communication of today world is dominated by wireless technology. This is mainly due to the revolutionary development of new wireless communication system generations. The evolving new generations of wireless systems are accommodating the demand through better resource management including improved transmission technologies with optimized communication devices. To keep up with the evolution of technologies, the communication systems must be designed to optimize transparent insertion of newly evolved technologies virtually at all stages of their life cycle. After the insertion of new technologies, the upgraded devices should continue the communication without squalor in quality. The concern of improving spectrum access and spectrum efficiency combined with both the introduction of Software Defined Radios (SDR) and the possibility of the software application to radios has led to an evolution of wireless radio research. The software defined radio term was coined in the 1970s to overcome the problems in the application of software to wireless radios which eliminates the requirement of hardware changes. SDR has become the prime theme of research since it eliminates the drawbacks associated with conventional wireless communication systems implementation. This paper identifies and discusses key enabling technologies and possibility of research and development in SDRs. In addition transmitter and receiver architectures of SDR are also discussed along with their feasibility for reconfigurable radio application.

Keywords: software defined radios, wireless communication, reconfigurable, reconfigurable transmitter, reconfigurable receivers, FPGA, DSP

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Authors: Sabah Mohammed, Jinan Fiaidhi, Darien Sawyer

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Data integration of health through connected services can save lives in the event of a medical emergency or provide efficient and effective interventions for the benefit of the patients through the integration of bedside and bench side clinical research. Such integration will support all wind of change in healthcare by being predictive, pre-emptive, personalized, problem-oriented and participatory. Prototyping a healthcare system that enables data integration has been a big challenge for healthcare for a long time. However, an innovative solution started to emerge by focusing on problem lists where everything can connect the problem list forming a growing graph. This notion was introduced by Dr. Lawrence Weed in early 70’s, but the enabling technologies weren’t mature enough to provide a successful implementation prototype. In this article, we are describing our efforts in prototyping Dr. Lawrence Weed's problem-oriented medical record (POMR) and his patient case schema (SOAP) to shape a prototype for connected health. For this, we are using the TypeGraphQL API and our enterprise-based QL4POMR to describe a Web-Based gateway for healthcare services connectivity. Our prototype has reported success in connecting to the HL7 FHIR medical record and the OpenTarget biomedical repositories.

Keywords: connected health, problem-oriented healthcare record, SOAP, QL4POMR, typegraphQL

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Authors: Bruk Gebregziabher

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The safe and efficient operation of Autonomous Mobile Robots (AMRs) in complex environments, such as manufacturing, logistics, and agriculture, necessitates accurate multiobject tracking and predictive collision avoidance. This paper presents algorithms and techniques for addressing these challenges using Lidar sensor data, emphasizing ensemble Kalman filter. The developed predictive collision avoidance algorithm employs the data provided by lidar sensors to track multiple objects and predict their velocities and future positions, enabling the AMR to navigate safely and effectively. A modification to the dynamic windowing approach is introduced to enhance the performance of the collision avoidance system. The overall system architecture encompasses object detection, multi-object tracking, and predictive collision avoidance control. The experimental results, obtained from both simulation and real-world data, demonstrate the effectiveness of the proposed methods in various scenarios, which lays the foundation for future research on global planners, other controllers, and the integration of additional sensors. This thesis contributes to the ongoing development of safe and efficient autonomous systems in complex and dynamic environments.

Keywords: autonomous mobile robots, multi-object tracking, predictive collision avoidance, ensemble Kalman filter, lidar sensors

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Authors: Toyin Mary Adewumi, Cina Mosito

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Part of enabling learners with special education needs (SEN) to succeed is providing them with adequate support. Support is all activities in a school that enhance its capacity to respond to diversity by making learning contexts and lessons accessible to all learners. The paper reports findings of support provided by teachers to learners with SEN and the pockets of good practice found in the support provided by teachers to these learners in schools in the Amathole West District, Eastern Cape. A purposeful sample, comprising eight teachers, eight principals in eight schools, including one provincial and two district education officials, was selected. Thematic analysis was used for analyzing data gathered through semi-structured interviews. The results established that despite the challenges such as lack of qualifications and training in special education needs, learners with SEN received varied support from teachers which include extra exercises, extra time, special attention during break times or after school hours and homework. The study reveals pockets of good practice in some selected primary schools particularly in the poverty-stricken locations in the Amathole West District. This paper recommends adequate training for teachers for the support of learners with SEN.

Keywords: good practice, learner, special education needs, inclusion, support

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Authors: Qian Liu, Steve Furber

Abstract:

To explore how the brain may recognize objects in its general,accurate and energy-efficient manner, this paper proposes the use of a neuromorphic hardware system formed from a Dynamic Video Sensor~(DVS) silicon retina in concert with the SpiNNaker real-time Spiking Neural Network~(SNN) simulator. As a first step in the exploration on this platform a recognition system for dynamic hand postures is developed, enabling the study of the methods used in the visual pathways of the brain. Inspired by the behaviours of the primary visual cortex, Convolutional Neural Networks (CNNs) are modeled using both linear perceptrons and spiking Leaky Integrate-and-Fire (LIF) neurons. In this study's largest configuration using these approaches, a network of 74,210 neurons and 15,216,512 synapses is created and operated in real-time using 290 SpiNNaker processor cores in parallel and with 93.0% accuracy. A smaller network using only 1/10th of the resources is also created, again operating in real-time, and it is able to recognize the postures with an accuracy of around 86.4% -only 6.6% lower than the much larger system. The recognition rate of the smaller network developed on this neuromorphic system is sufficient for a successful hand posture recognition system, and demonstrates a much-improved cost to performance trade-off in its approach.

Keywords: spiking neural network (SNN), convolutional neural network (CNN), posture recognition, neuromorphic system

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Authors: E. Erdem, M. Şahin, M. Saçak

Abstract:

Smectite is a layered silicate and modified with alkyl ammonium salts to make both the hydrophilic silicate surfaces organophilic, and to expand the clay layers. Thus, a nanocomposite structure can be formed enabling to enter various types of polymers between the layers. In this study, Na-smectite crystals were prepared by purification of bentonite. Benzyltributylammonium bromide (BTBAB) was used as a swelling agent. The mixing time and additive concentration were changed during the swelling process. It was determined that the 4 h of mixing time and 0.2 g of BTBAB were sufficient and the usage of higher amounts of salt did not increase the interlayer space between the clay layers. Then, the conductive poly(o-toluidine) (POT)/smectite nanocomposite was prepared in the presence of swollen Na-smectite using ammonium persulfate (APS) as oxidant in aqueous acidic medium. The POT content and conductivity of the prepared nanocomposite were systematically investigated as a function of polymerization conditions such as the treatment time of swollen smectite in monomer solution and o-toluidine/APS mol ratio. The POT content and conductivity of nanocomposite increased with increasing monomer/oxidant mol ratio up to 1 and did not change at higher ratios. The maximum polymer yield and the highest conductivity value of the composite were 26.0% and 4.0×10-5 S/cm, respectively. The structural and morphological analyses of the POT/smectite nanocomposite were carried out by XRD, FTIR and SEM techniques, respectively.

Keywords: clay, composite, conducting polymer, poly(o-anisidine)

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Authors: Prakash Singh

Abstract:

Being a collegial leader would require such a person to promote an organizational passion that identifies and acknowledges the contribution of every employee. Collegiality is about sharing responsibilities and being accountable for one’s actions. Leaders must therefore be equipped with the knowledge, skills, abilities, beliefs, and dispositions that will allow them to succeed in their organizations. These abilities should not only dwell on cognition alone, but also, equally, on the development of their emotional intelligence (EQ). It is therefore a myth that leaders are entrusted with absolute power to manage all the resources of their organizations. Workers feel confident with leaders who are adaptable, flexible and supportive when it comes to shared decision-making and the devolution of power within the organization. Research strongly supports the notion that a leader requires a high level of EQ in addition to IQ (cognitive intelligence) to achieve the goals of the organization. On the other hand, traditional managers require cognitive abilities and technical skills to get the work done by their employees. This does not imply that management is not important in organizations. However, the approach of managers becomes highly critical when the focus is purely task orientated. Enabling or empowering employees, therefore, is an important aspect in establishing emotionally intelligent collaboration, as the willing and satisfied participation of the employees can be the result of leaders’ commitment to establishing a collegial working environment as demonstrated by their behaviours. This paper therefore analyses why it matters for ideal leaders to be imbued with the traits of EQ and collegiality.

Keywords: collegiality, emotional intelligence, empowering employees, traditional managers

Procedia PDF Downloads 325

Authors: Ogunnaiya Racheal Taiwo

Abstract:

Children's formative years are crucial to their growth; it is, therefore, necessary for all the stakeholders to ensure that the pupils have an enabling quality of life which is essential for realizing their potential. For children to live and grow, they need a secure home, nutritious food, good health care, and quality education. This paper, therefore, investigates the implications of a depressed economy on the classroom learning of Nigerian children as it is clear that Nigeria is currently experiencing the worst economic depression in several decades, which affects a substantial proportion of children. The study is qualitative research, and it adopts a phenomenological approach where the experiences of respondents are examined qualitatively. Three senatorial districts in Oyo State were considered, and 50 teachers, both male, and female were chosen from each senatorial district for an interview through conversational key informants' interviews. The interviewees were recorded, transcribed, and presented using thematic analysis. Findings showed that more children have dropped out since the beginning of the year than in previous years. It was also recorded that learning has become challenging as children now find it harder to acquire learning materials. It was recommended that the government should reimburse early childhood schools to lessen the effect of the inability to purchase materials and pay school fees. It was also recommended that an intervention be made to approach and resolve issues associated with out-of-school children.

Keywords: childhood, classroom, education, depressed economy, poverty

Procedia PDF Downloads 72