Search results for: technology factor

Authors: Mirka Januszkiewicz

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The Regional Municipality of Durham is the upper level of a two-tier municipal and regional structure comprised of eight lower-tier municipalities. With a population of 655,000 in both urban and rural settings, the Region is approximately 2,537 square kilometers neighboring the City of Toronto, Ontario Canada to the east. The Region has been focused on diverting waste from disposal since the development of its Long Term Waste Management Strategy Plan for 2000-2020. With a 54 percent solid waste diversion rate, the focus now is on achieving 70 percent diversion on the path to zero waste using local waste management options whenever feasible. The Region has an Integrated Waste Management System that consists of a weekly curbside collection of recyclable printed paper and packaging and source separated organics; a seasonal collection of leaf and yard waste; a bi-weekly collection of residual garbage; and twice annual collection of intact, sealed household batteries. The Region also maintains three Waste Management Facilities for residential drop-off of household hazardous waste, polystyrene, construction and demolition debris and electronics. Special collection events are scheduled in the spring, summer and fall months for reusable items, household hazardous waste, and electronics. The Region is in the final commissioning stages of an energy from the waste facility for residual waste disposal that will recover energy from non-recyclable wastes. This facility is state of the art and is equipped for installation of carbon capture technology in the future. Despite all of these diversion programs and efforts, there is still room for improvement. Recent residential waste studies revealed that over 50% of the residual waste placed at the curb that is destined for incineration could be recycled. To move towards a zero waste community, the Region is looking to more advanced technologies for extracting the maximum recycling value from residential waste. Plans are underway to develop a pre-sort facility to remove organics and recyclables from the residual waste stream, including the growing multi-residential sector. Organics would then be treated anaerobically to generate biogas and fertilizer products for beneficial use within the Region. This project could increase the Region’s diversion rate beyond 70 percent and enhance the Region’s climate change mitigation goals. Zero waste is an ambitious goal in a changing regulatory and economic environment. Decision makers must be willing to consider new and emerging technologies and embrace change to succeed.

Keywords: municipal waste, residential, waste diversion, zero waste

Procedia PDF Downloads 219

Authors: Sheila S. Silang

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This research seeks to make an impact analysis on multiple intelligence as the basis for differentiated classroom instruction in TLE. It will also address the felt need of how TLE subject could be taught effectively exhausting all the possible means.This study seek the effect of giving different instruction according to the ability of the students in the following objectives: 1. student’s technological skills enhancement, 2. learning potential improvements 3. having better linkage between school and community in a need for soliciting different learning devices and materials for the learner’s academic progress. General Luna, Quezon is composed of twenty seven barangays. There are only two public high schools. We are aware that K-12 curriculum is focused on providing sufficient time for mastery of concepts and skills, develop lifelong learners, and prepare graduates for tertiary education, middle-level skills development, employment, and entrepreneurship. The challenge is with TLE offerring a vast area of specializations, how would Multiple Intelligence play its vital role as basis in classroom instruction in acquiring the requirement of the said curriculum? 1.To what extent do the respondent students manifest the following types of intelligences: Visual-Spatial, Body-Kinesthetic, Musical, Interpersonal, Intrapersonal, Verbal-Linguistic, Logical-Mathematical and Naturalistic. What media should be used appropriate to the student’s learning style? Visual, Printed Words, Sound, Motion, Color or Realia 3. What is the impact of multiple intelligence as basis for differentiated instruction in T.L.E. based on the following student’s ability? Learning Characteristic and Reading Ability and Performance 3. To what extent do the intelligences of the student relate with their academic performance? The following were the findings derived from the study: In consideration of the vast areas of study of TLE, and the importance it plays in the school curriculum coinciding with the expectation of turning students to technologically competent contributing members of the society, either in the field of Technical/Vocational Expertise or Entrepreneurial based competencies, as well as the government’s concern for it, we visualize TLE classroom teachers making use of multiple intelligence as basis for differentiated classroom instruction in teaching the subject .Somehow, multiple intelligence sample such as Linguistic, Logical-Mathematical, Bodily-Kinesthetic, Interpersonal, Intrapersonal, and Spatial abilities that an individual student may have or may not have, can be a basis for a TLE teacher’s instructional method or design.

Keywords: education, multiple, differentiated classroom instruction, impact analysis

Procedia PDF Downloads 445

Authors: Radul Shishkov, Orlin Davchev

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The digital era has revolutionized architectural practices, with building information modeling (BIM) emerging as a pivotal tool for architects, engineers, and construction professionals. However, the transition from traditional methods to BIM-centric approaches poses significant challenges, particularly in the context of existing structures. This research introduces a technical approach to bridge this gap through the development of algorithms that facilitate the automated transformation of 3D point cloud data into detailed BIM models. The core of this research lies in the application of algorithmic modeling and computational design methods to interpret and reconstruct point cloud data -a collection of data points in space, typically produced by 3D scanners- into comprehensive BIM models. This process involves complex stages of data cleaning, feature extraction, and geometric reconstruction, which are traditionally time-consuming and prone to human error. By automating these stages, our approach significantly enhances the efficiency and accuracy of creating BIM models for existing buildings. The proposed algorithms are designed to identify key architectural elements within point clouds, such as walls, windows, doors, and other structural components, and to translate these elements into their corresponding BIM representations. This includes the integration of parametric modeling techniques to ensure that the generated BIM models are not only geometrically accurate but also embedded with essential architectural and structural information. Our methodology has been tested on several real-world case studies, demonstrating its capability to handle diverse architectural styles and complexities. The results showcase a substantial reduction in time and resources required for BIM model generation while maintaining high levels of accuracy and detail. This research contributes significantly to the field of architectural technology by providing a scalable and efficient solution for the integration of existing structures into the BIM framework. It paves the way for more seamless and integrated workflows in renovation and heritage conservation projects, where the accuracy of existing conditions plays a critical role. The implications of this study extend beyond architectural practices, offering potential benefits in urban planning, facility management, and historic preservation.

Keywords: BIM, 3D point cloud, algorithmic modeling, computational design, architectural reconstruction

Procedia PDF Downloads 63

Authors: L. Diogo, A. Legrand, J. Nguyen-Cao, J. Rogeau, S. Bornhofen

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Lenia is a system of cellular automata with continuous states, space and time, which surprises not only with the emergence of interesting life-like structures but also with its beauty. This paper reports ongoing research on a GPU implementation of Lenia using CUDA C++ and OpenGL Interoperability. We demonstrate how CUDA as a low-level GPU programming paradigm allows optimizing performance and memory usage of the Lenia algorithm. A comparative analysis through experimental runs with existing implementations shows that the CUDA implementation outperforms the others by one order of magnitude or more. Cellular automata hold significant interest due to their ability to model complex phenomena in systems with simple rules and structures. They allow exploring emergent behavior such as self-organization and adaptation, and find applications in various fields, including computer science, physics, biology, and sociology. Unlike classic cellular automata which rely on discrete cells and values, Lenia generalizes the concept of cellular automata to continuous space, time and states, thus providing additional fluidity and richness in emerging phenomena. In the current literature, there are many implementations of Lenia utilizing various programming languages and visualization libraries. However, each implementation also presents certain drawbacks, which serve as motivation for further research and development. In particular, speed is a critical factor when studying Lenia, for several reasons. Rapid simulation allows researchers to observe the emergence of patterns and behaviors in more configurations, on bigger grids and over longer periods without annoying waiting times. Thereby, they enable the exploration and discovery of new species within the Lenia ecosystem more efficiently. Moreover, faster simulations are beneficial when we include additional time-consuming algorithms such as computer vision or machine learning to evolve and optimize specific Lenia configurations. We developed a Lenia implementation for GPU using the C++ and CUDA programming languages, and CUDA/OpenGL Interoperability for immediate rendering. The goal of our experiment is to benchmark this implementation compared to the existing ones in terms of speed, memory usage, configurability and scalability. In our comparison we focus on the most important Lenia implementations, selected for their prominence, accessibility and widespread use in the scientific community. The implementations include MATLAB, JavaScript, ShaderToy GLSL, Jupyter, Rust and R. The list is not exhaustive but provides a broad view of the principal current approaches and their respective strengths and weaknesses. Our comparison primarily considers computational performance and memory efficiency, as these factors are critical for large-scale simulations, but we also investigate the ease of use and configurability. The experimental runs conducted so far demonstrate that the CUDA C++ implementation outperforms the other implementations by one order of magnitude or more. The benefits of using the GPU become apparent especially with larger grids and convolution kernels. However, our research is still ongoing. We are currently exploring the impact of several software design choices and optimization techniques, such as convolution with Fast Fourier Transforms (FFT), various GPU memory management scenarios, and the trade-off between speed and accuracy using single versus double precision floating point arithmetic. The results will give valuable insights into the practice of parallel programming of the Lenia algorithm, and all conclusions will be thoroughly presented in the conference paper. The final version of our CUDA C++ implementation will be published on github and made freely accessible to the Alife community for further development.

Keywords: artificial life, cellular automaton, GPU optimization, Lenia, comparative analysis.

Procedia PDF Downloads 41

Authors: Xiujing Chen, Thammananya Sakcharoen, Wilailuk Niyommaneerat

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China's tourism industry is in a state of shock and recovery, although COVID-19 has brought great impact and challenges to the tourism industry. The theory of sustainable development originates from the contradiction of increasing awareness of environmental protection and the pursuit of economic interests. The sustainable development of tourism should consider social, economic, and environmental factors and develop tourism in a planned and targeted way from the overall situation. Guilin is one of the popular tourist cities in China. However, there exist several problems in Guilin tourism, such as low quality of scenic spot construction and low efficiency of tourism resource development. Due to its unwell-managed, Guilin's tourism industry is facing problems such as supply and demand crowding pressure for tourists. According to the data from 2009 to 2019, there is a change in the degree of sustainable development of Guilin tourism. This research aimed to evaluate the sustainable development state of Guilin tourism using the DPSIR (driving force/pressure/state/impact/response) framework and to provide suggestions and recommendations for sustainable development in Guilin. An improved TOPSIS (technology for order preference by similarity to an ideal solution) model based on the entropy weights relationship is applied to the quantitative analysis and to analyze the mechanisms of sustainable development of tourism in Guilin. The DPSIR framework organizes indicators into sub-five categories: of which twenty-eight indicators related to sustainable aspects of Guilin tourism are classified. The study analyzed and summarized the economic, social, and ecological effects generated by tourism development in Guilin from 2009-2019. The results show that the conversion rate of tourism development in Guilin into regional economic benefits is more efficient than that into social benefits. Thus, tourism development is an important driving force of Guilin's economic growth. In addition, the study also analyzed the static weights of 28 relevant indicators of sustainable development of tourism in Guilin and ranked them from largest to smallest. Then it was found that the economic and social factors related to tourism revenue occupy the highest weight, which means that the economic and social development of Guilin can influence the sustainable development of Guilin tourism to a greater extent. Therefore, there is a two-way causal relationship between tourism development and economic growth in Guilin. At the same time, ecological development-related indicators also have relatively large weights, so ecological and environmental resources also have a great influence on the sustainable development of Guilin tourism.

Keywords: DPSIR framework, entropy weights analysis, sustainable development of tourism, TOPSIS analysis

Procedia PDF Downloads 98

Authors: Ohud Adnan Saffar

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This study aims to know the effect of using universal design for learning (UDL) to improve the quality of vocational programme with intellectual disabilities (SID) and the challenges facing this method from the teachers' point of view. The significance of the study: There are comparatively few published studies on UDL in emerging nations. Therefore, this study will encourage the researchers to consider a new approaches teaching. Development of this study will contribute significant information on the cognitively disabled community on a universal scope. In order to collect and evaluate the data and for the verification of the results, this study has been used the mixed research method, by using two groups comparison method. To answer the study questions, we were used the questionnaire, lists of observations, open questions, and pre and post-test. Thus, the study explored the advantages and drawbacks, and know about the impact of using the UDL method on integrating SID with students non-special education needs in the same classroom. Those aims were realized by developing a workshop to explain the three principles of the UDL and train (16) teachers in how to apply this method to teach (12) students non-special education needs and the (12) SID in the same classroom, then take their opinion by using the questionnaire and questions. Finally, this research will explore the effects of the UDL on the teaching of professional photography skills for the SID in Saudi Arabia. To achieve this goal, the research method was a comparison of the performance of the SID using the UDL method with that of female students with the same challenges applying other strategies by teachers in control and experiment groups, we used the observation lists, pre and post-test. Initial results: It is clear from the previous response to the participants that most of the answers confirmed that the use of UDL achieves the principle of inclusion between the SID and students non-special education needs by 93.8%. In addition, the results show that the majority of the sampled people see that the most important advantages of using UDL in teaching are creating an interactive environment with using new and various teaching methods, with a percentage of 56.2%. Following this result, the UDL is useful for integrating students with general education, with a percentage of 31.2%. Moreover, the finding indicates to improve understanding through using the new technology and exchanging the primitive ways of teaching with the new ones, with a percentage of 25%. The result shows the percentages of the sampled people's opinions about the financial obstacles, and it concluded that the majority see that the cost is high and there is no computer maintenance available, with 50%. There are no smart devices in schools to help in implementing and applying for the program, with a percentage of 43.8%.

Keywords: universal design for learning, intellectual disabilities, vocational programme, the challenges facing this method

Procedia PDF Downloads 129

Authors: Komala Arsi, Ann M. Donoghue, Dan J. Donoghue

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Methionine is an essential dietary amino acid necessary to promote growth and health of poultry. Synthetic methionine is commonly used as a supplement in conventional poultry diets and is temporarily allowed in organic poultry feed for lack of natural and organically approved sources of methionine. It has been a challenge to find a natural, sustainable and cost-effective source for methionine which reiterates the pressing need to explore potential alternatives of methionine for organic poultry production. Fish have high concentrations of methionine, but wild-caught fish are expensive and adversely impact wild fish populations. Asian carp (AC) is an invasive species and its utilization has the potential to be used as a natural methionine source. However, to our best knowledge, there is no proven technology to utilize this fish as a methionine source. In this study, we co-extruded Asian carp and soybean meal to form a dry-extruded, methionine-rich AC meal. In order to formulate rations with the novel extruded carp meal, the product was tested on cecectomized roosters for its amino acid digestibility and total metabolizable energy (TMEn). Excreta was collected and the gross energy, protein content of the feces was determined to calculate Total Metabolizable Energy (TME). The methionine content, digestibility and TME values were greater for the extruded AC meal than control diets. Carp meal was subsequently tested as a methionine source in feeds formulated for broilers, and production performance (body weight gain and feed conversion ratio) was assessed in comparison with broilers fed standard commercial diets supplemented with synthetic methionine. In this study, broiler chickens were fed either a control diet with synthetic methionine or a treatment diet with extruded AC meal (8 replicates/treatment; n=30 birds/replicate) from day 1 to 42 days of age. At the end of the trial, data for body weights, feed intake and feed conversion ratio (FCR) was analyzed using one-way ANOVA with Fisher LSD test for multiple comparisons. Results revealed that birds on AC diet had body weight gains and feed intake comparable to diets containing synthetic methionine (P > 0.05). Results from the study suggest that invasive AC-derived fish meal could potentially be an effective and inexpensive source of sustainable natural methionine for organic poultry farmers.

Keywords: Asian carp, methionine, organic, poultry

Procedia PDF Downloads 158

Authors: Astrid Tannert, Anuradha Ramoji, Christina Ebert, Frederike Gladigau, Lorena Tuchscherr, Jürgen Popp, Ute Neugebauer

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Staphylococcus aureus is a facultative intracellular pathogen, which by entering host cells may evade immunologic host response as well as antimicrobial treatment. In that way, S. aureus can cause persistent intracellular infections which are difficult to treat. Depending on the strain, S. aureus may persist at different intracellular locations like the phagolysosome. The first barrier invading pathogens from the blood stream that they have to cross are the endothelial cells lining the inner surface of blood and lymphatic vessels. Upon proceeding from an acute to a chronic infection, intracellular pathogens undergo certain biochemical and structural changes including a deceleration of metabolic processes to adopt for long-term intracellular survival and the development of a special phenotype designated as small colony variant. In this study, the endothelial cell line Ea.hy 926 was used as a model for acute and chronic S. aureus infection. To this end, Ea.hy 926 cells were cultured on QIAscout™ Microraft Arrays, a special graded cell culture substrate that contains around 12,000 microrafts of 200 µm edge length. After attachment to the substrate, the endothelial cells were infected with GFP-expressing S. aureus for 3 weeks. The acute infection and the development of persistent bacteria was followed by confocal laser scanning microscopy, scanning the whole Microraft Array for the presence and for detailed determination of the intracellular location of fluorescent intracellular bacteria every second day. After three weeks of infection representative microrafts containing infected cells, cells with protruded infections and cells that did never show any infection were isolated and fixed for Raman micro-spectroscopic investigation. For comparison, also microrafts with acute infection were isolated. The acquired Raman spectra are correlated with the fluorescence microscopic images to give hints about a) the molecular alterations in endothelial cells during acute and chronic infection compared to non-infected cells, and b) metabolic and structural changes within the pathogen when entering a mode of persistence within host cells. We thank Dr. Ruth Kläver from QIAGEN GmbH for her support regarding QIAscout technology. Financial support by the BMBF via the CSCC (FKZ 01EO1502) and from the DFG via the Jena Biophotonic and Imaging Laboratory (JBIL, FKZ PO 633/29-1, BA 1601/10-1) is highly acknowledged.

Keywords: correlative image analysis, intracellular infection, pathogen-host adaption, Raman micro-spectroscopy

Procedia PDF Downloads 181

Authors: Mina Sadat Orooje, Mohammad Mehdi Latifi, Behnam Fereydooni Eftekhari

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The integration of cutting-edge Internet of Things (IoT) technologies with advanced Artificial Intelligence (AI) systems is revolutionizing healthcare facility management. However, the current landscape of hospital building maintenance suffers from slow, repetitive, and disjointed processes, leading to significant financial, resource, and time losses. Additionally, the potential of Building Information Modeling (BIM) in facility maintenance is hindered by a lack of data within digital models of built environments, necessitating a more streamlined data collection process. This paper presents a robust framework that harmonizes AI with BIM-IoT technology to elevate healthcare Facility Maintenance Management (FMM) and address these pressing challenges. The methodology begins with a thorough literature review and requirements analysis, providing insights into existing technological landscapes and associated obstacles. Extensive data collection and analysis efforts follow to deepen understanding of hospital infrastructure and maintenance records. Critical AI algorithms are identified to address predictive maintenance, anomaly detection, and optimization needs alongside integration strategies for BIM and IoT technologies, enabling real-time data collection and analysis. The framework outlines protocols for data processing, analysis, and decision-making. A prototype implementation is executed to showcase the framework's functionality, followed by a rigorous validation process to evaluate its efficacy and gather user feedback. Refinement and optimization steps are then undertaken based on evaluation outcomes. Emphasis is placed on the scalability of the framework in real-world scenarios and its potential applications across diverse healthcare facility contexts. Finally, the findings are meticulously documented and shared within the healthcare and facility management communities. This framework aims to significantly boost maintenance efficiency, cut costs, provide decision support, enable real-time monitoring, offer data-driven insights, and ultimately enhance patient safety and satisfaction. By tackling current challenges in healthcare facility maintenance management it paves the way for the adoption of smarter and more efficient maintenance practices in healthcare facilities.

Keywords: artificial intelligence, building information modeling, healthcare facility maintenance, internet of things integration, maintenance efficiency

Procedia PDF Downloads 59

Authors: Sameh S. Namnqani, Yaqoob Y. Abobakar, Ahmed M. Alsewehri, Khaled M. AlQethami

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The main objective of this research is to know the impact of the application of the electronic supply system on the performance of the supply department of health organizations. To reach this goal, the study adopted independent variables to measure the dependent variable (performance of the supply department), namely: integration with suppliers, integration with intermediaries and distributors and knowledge of supply size, inventory, and demand. The study used the descriptive method and was aided by the questionnaire tool that was distributed to a sample of workers in the Supply Chain Management Department of King Abdullah Medical City. After the statistical analysis, the results showed that: The 70 sample members strongly agree with the (electronic integration with suppliers) axis with a p-value of 0.001, especially with regard to the following: Opening formal and informal communication channels between management and suppliers (Mean 4.59) and exchanging information with suppliers with transparency and clarity (Mean 4.50). It also clarified that the sample members agree on the axis of (electronic integration with brokers and distributors) with a p-value of 0.001 and this is represented in the following elements: Exchange of information between management, brokers and distributors with transparency, clarity (Mean 4.18) , and finding a close cooperation relationship between management, brokers and distributors (Mean 4.13). The results also indicated that the respondents agreed to some extent on the axis (knowledge of the size of supply, stock, and demand) with a p-value of 0.001. It also indicated that the respondents strongly agree with the existence of a relationship between electronic procurement and (the performance of the procurement department in health organizations) with a p-value of 0.001, which is represented in the following: transparency and clarity in dealing with suppliers and intermediaries to prevent fraud and manipulation (Mean 4.50) and reduce the costs of supplying the needs of the health organization (Mean 4.50). From the results, the study recommended several recommendations, the most important of which are: that health organizations work to increase the level of information sharing between them and suppliers in order to achieve the implementation of electronic procurement in the supply management of health organizations. Attention to using electronic data interchange methods and using modern programs that make supply management able to exchange information with brokers and distributors to find out the volume of supply, inventory, and demand. To know the volume of supply, inventory, and demand, it recommended the application of scientific methods of supply for storage. Take advantage of information technology, for example, electronic data exchange techniques and documents, where it can help in contact with suppliers, brokers, and distributors, and know the volume of supply, inventory, and demand, which contributes to improving the performance of the supply department in health organizations.

Keywords: healthcare supply chain, performance, electronic system, ERP

Procedia PDF Downloads 136

Authors: Ivana Scidà, Francesco Alotto, Anna Osello

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Due to the importance given today to innovation, the education sector is evolving thanks digital technologies. Virtual Reality (VR) can be a potential teaching tool offering many advantages in the field of training and education, as it allows to acquire theoretical knowledge and practical skills using an immersive experience in less time than the traditional educational process. These assumptions allow to lay the foundations for a new educational environment, involving and stimulating for students. Starting from the objective of strengthening the innovative teaching offer and the learning processes, the case study of the research concerns the digitalization of MastrLAB, High Quality Laboratory (HQL) belonging to the Department of Structural, Building and Geotechnical Engineering (DISEG) of the Polytechnic of Turin, a center specialized in experimental mechanical tests on traditional and innovative building materials and on the structures made with them. The MastrLAB-VR has been developed, a revolutionary innovative training tool designed with the aim of educating the class in total safety on the techniques of use of machinery, thus reducing the dangers arising from the performance of potentially dangerous activities. The virtual laboratory, dedicated to the students of the Building and Civil Engineering Courses of the Polytechnic of Turin, has been projected to simulate in an absolutely realistic way the experimental approach to the structural tests foreseen in their courses of study: from the tensile tests to the relaxation tests, from the steel qualification tests to the resilience tests on elements at environmental conditions or at characterizing temperatures. The research work proposes a methodology for the virtualization of technical laboratories through the application of Building Information Modelling (BIM), starting from the creation of a digital model. The process includes the creation of an independent application, which with Oculus Rift technology will allow the user to explore the environment and interact with objects through the use of joypads. The application has been tested in prototype way on volunteers, obtaining results related to the acquisition of the educational notions exposed in the experience through a virtual quiz with multiple answers, achieving an overall evaluation report. The results have shown that MastrLAB-VR is suitable for both beginners and experts and will be adopted experimentally for other laboratories of the University departments.

Keywords: building information modelling, digital learning, education, virtual laboratory, virtual reality

Procedia PDF Downloads 131

Authors: Iulia E. Falcan

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The transition of the European power sector towards a clean, renewable energy (RE) system faces the challenge of meeting power demand in times of low wind speed and low solar radiation, at a reasonable cost. This is likely to be achieved through a combination of 1) energy storage technologies, 2) development of the cross-border power grid, 3) installed overcapacity of RE and 4) dispatchable power sources – such as biomass. This paper uses NASA; derived hourly data on weather patterns of sixteen European countries for the past twenty-five years, and load data from the European Network of Transmission System Operators-Electricity (ENTSO-E), to develop a stochastic optimization model. This model aims to understand the synergies between the four classes of technologies mentioned above and to determine the optimal configuration of the energy technologies portfolio. While this issue has been addressed before, it was done so using deterministic models that extrapolated historic data on weather patterns and power demand, as well as ignoring the risk of an unbalanced grid-risk stemming from both the supply and the demand side. This paper aims to explicitly account for the inherent uncertainty in the energy system transition. It articulates two levels of uncertainty: a) the inherent uncertainty in future weather patterns and b) the uncertainty of fully meeting power demand. The first level of uncertainty is addressed by developing probability distributions for future weather data and thus expected power output from RE technologies, rather than known future power output. The latter level of uncertainty is operationalized by introducing a Conditional Value at Risk (CVaR) constraint in the portfolio optimization problem. By setting the risk threshold at different levels – 1%, 5% and 10%, important insights are revealed regarding the synergies of the different energy technologies, i.e., the circumstances under which they behave as either complements or substitutes to each other. The paper concludes that allowing for uncertainty in expected power output - rather than extrapolating historic data - paints a more realistic picture and reveals important departures from results of deterministic models. In addition, explicitly acknowledging the risk of an unbalanced grid - and assigning it different thresholds - reveals non-linearity in the cost functions of different technology portfolio configurations. This finding has significant implications for the design of the European energy mix.

Keywords: cross-border grid extension, energy storage technologies, energy system transition, stochastic portfolio optimization

Procedia PDF Downloads 170

Authors: Ricardo Torcato, Helder Morais

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The manufacture of crystal glass parts is based on obtaining the rough geometry by blowing and/or injection, generally followed by a set of manual finishing operations using cutting and grinding tools. The forming techniques used do not allow the obtainment, with repeatability, of parts with complex shapes and the finishing operations use intensive specialized labor resulting in high cycle times and production costs. This work aims to explore the digital manufacture of crystal glass parts by investigating new subtractive techniques for the automated, flexible finishing of these parts. Finishing operations are essential to respond to customer demands in terms of crystal feel and shine. It is intended to investigate the applicability of different computerized finishing technologies, namely milling and grinding in a CNC machining center with or without ultrasonic assistance, to crystal processing. Research in the field of grinding hard and brittle materials, despite not being extensive, has increased in recent years, and scientific knowledge about the machinability of crystal glass is still very limited. However, it can be said that the unique properties of glass, such as high hardness and very low toughness, make any glass machining technology a very challenging process. This work will measure the performance improvement brought about by the use of ultrasound compared to conventional crystal grinding. This presentation is focused on the mechanical characterization and analysis of the cutting forces in CNC machining of superior crystal glass (Pb ≥ 30%). For the mechanical characterization, the Vickers hardness test provides an estimate of the material hardness (Hv) and the fracture toughness based on cracks that appear in the indentation. Mechanical impulse excitation test estimates the Young’s Modulus, shear modulus and Poisson ratio of the material. For the cutting forces, it a dynamometer was used to measure the forces in the face grinding process. The tests were made based on the Taguchi method to correlate the input parameters (feed rate, tool rotation speed and depth of cut) with the output parameters (surface roughness and cutting forces) to optimize the process (better roughness using the cutting forces that do not compromise the material structure and the tool life) using ANOVA. This study was conducted for conventional grinding and for the ultrasonic grinding process with the same cutting tools. It was possible to determine the optimum cutting parameters for minimum cutting forces and for minimum surface roughness in both grinding processes. Ultrasonic-assisted grinding provides a better surface roughness than conventional grinding.

Keywords: CNC machining, crystal glass, cutting forces, hardness

Procedia PDF Downloads 154

Authors: Fateme Aysin Anka, Farzad Kiani

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Forced migration is a situation in which people are forced to leave their homes against their will due to political conflicts, wars and conflicts, natural disasters, climate change, economic crises, or other emergencies. This type of migration takes place under conditions where people cannot lead a sustainable life due to reasons such as security, shelter and meeting their basic needs. This type of migration may occur in connection with different factors that affect people's living conditions. In addition to these general and widespread reasons, water security and resources will be one that is starting now and will be encountered more and more in the future. Forced migration may occur due to insufficient or depleted water resources in the areas where people live. In this case, people's living conditions become unsustainable, and they may have to go elsewhere, as they cannot obtain their basic needs, such as drinking water, water used for agriculture and industry. To cope with these situations, it is important to minimize the causes, as international organizations and societies must provide assistance (for example, humanitarian aid, shelter, medical support and education) and protection to address (or mitigate) this problem. From the international perspective, plans such as the Green New Deal (GND) and the European Green Deal (EGD) draw attention to the need for people to live equally in a cleaner and greener world. Especially recently, with the advancement of technology, science and methods have become more efficient. In this regard, in this article, a multidisciplinary case model is presented by reinforcing the water problem with an engineering approach within the framework of the social dimension. It is worth emphasizing that this problem is largely linked to climate change and the lack of a sustainable water management perspective. As a matter of fact, the United Nations Development Agency (UNDA) draws attention to this problem in its universally accepted sustainable development goals. Therefore, an artificial intelligence-based approach has been applied to solve this problem by focusing on the water management problem. The most general but also important aspect in the management of water resources is its correct consumption. In this context, the artificial intelligence-based system undertakes tasks such as water demand forecasting and distribution management, emergency and crisis management, water pollution detection and prevention, and maintenance and repair control and forecasting.

Keywords: water resource management, forced migration, multidisciplinary studies, artificial intelligence

Procedia PDF Downloads 87

Authors: Kasra Afsahi, Maryam Soheilifar, S. Hossein Hosseini

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Background: There is growing evidence that Cerebral Vascular Accident (CVA) can be a consequence of Covid-19 infection. Understanding novel treatment approaches are important in optimizing patient outcomes. Case: This case explores the use of Virtual Reality (VR) in the treatment of a 23-year-old COVID-positive female presenting with left hemiparesis in August 2020. Imaging showed right globus pallidus, thalamus, and internal capsule ischemic stroke. Conventional rehabilitation was started two weeks later, with virtual reality (VR) included. This game-based virtual reality (VR) technology developed for stroke patients was based on upper extremity exercises and functions for stroke. Physical examination showed left hemiparesis with muscle strength 3/5 in the upper extremity and 4/5 in the lower extremity. The range of motion of the shoulder was 90-100 degrees. The speech exam showed a mild decrease in fluency. Mild lower lip dynamic asymmetry was seen. Babinski was positive on the left. Gait speed was decreased (75 steps per minute). Intervention: Our game-based VR system was developed based on upper extremity physiotherapy exercises for post-stroke patients to increase the active, voluntary movement of the upper extremity joints and improve the function. The conventional program was initiated with active exercises, shoulder sanding for joint ROMs, walking shoulder, shoulder wheel, and combination movements of the shoulder, elbow, and wrist joints, alternative flexion-extension, pronation-supination movements, Pegboard and Purdo pegboard exercises. Also, fine movements included smart gloves, biofeedback, finger ladder, and writing. The difficulty of the game increased at each stage of the practice with progress in patient performances. Outcome: After 6 weeks of treatment, gait and speech were normal and upper extremity strength was improved to near normal status. No adverse effects were noted. Conclusion: This case suggests that VR is a useful tool in the treatment of a patient with covid-19 related CVA. The safety of newly developed instruments for such cases provides new approaches to improve the therapeutic outcomes and prognosis as well as increased satisfaction rate among patients.

Keywords: covid-19, stroke, virtual reality, rehabilitation

Procedia PDF Downloads 141

Authors: Kayode A. Olaniyi, Olabanji F. Omotoye, Adeola A. Ogunleye

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Computer system components such as the CPU, the Controllers, and the operating system, work together as a team, and storage or memory is the essential parts of this team apart from the processor. The memory and storage system including processor caches, main memory, and storage, form basic storage component of a computer system. The characteristics of the different types of storage are inherent in the design and the technology employed in the manufacturing. These memory characteristics define the speed, compatibility, cost, volatility, and density of the various storage types. Most computers rely on a hierarchy of storage devices for performance. The effective and efficient use of the memory hierarchy of the computer system therefore is the single most important aspect of computer system design and use. The memory hierarchy is becoming a fundamental performance and energy bottleneck, due to the widening gap between the increasing demands of modern computer applications and the limited performance and energy efficiency provided by traditional memory technologies. With the dramatic development in the computers systems, computer storage has had a difficult time keeping up with the processor speed. Computer architects are therefore facing constant challenges in developing high-speed computer storage with high-performance which is energy-efficient, cost-effective and reliable, to intercept processor requests. It is very clear that substantial advancements in redesigning the existing memory physical and logical structures to meet up with the latest processor potential is crucial. This research work investigates the importance of computer memory (storage) hierarchy in the design of computer systems. The constituent storage types of the hierarchy today were investigated looking at the design technologies and how the technologies affect memory characteristics: speed, density, stability and cost. The investigation considered how these characteristics could best be harnessed for overall efficiency of the computer system. The research revealed that the best single type of storage, which we refer to as ideal memory is that logical single physical memory which would combine the best attributes of each memory type that make up the memory hierarchy. It is a single memory with access speed as high as one found in CPU registers, combined with the highest storage capacity, offering excellent stability in the presence or absence of power as found in the magnetic and optical disks as against volatile DRAM, and yet offers a cost-effective attribute that is far away from the expensive SRAM. The research work suggests that to overcome these barriers it may then mean that memory manufacturing will take a total deviation from the present technologies and adopt one that overcomes the associated challenges with the traditional memory technologies.

Keywords: cache, memory-hierarchy, memory, registers, storage

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Authors: Nelson Ponce Jr., Jonas R. Gazoli, Alessandro Sete, Roberto M. G. Velásquez, Valério L. Borges, Moacir A. S. de Andrade

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The search for increased efficiency in generation systems has been of great importance in recent years to reduce the impact of greenhouse gas emissions and global warming. For clean energy sources, such as the generation systems that use concentrated solar power technology, this efficiency improvement impacts a lower investment per kW, improving the project’s viability. For the specific case of parabolic trough solar concentrators, their performance is strongly linked to their geometric precision of assembly and the individual efficiencies of their main components, such as parabolic mirrors and receiver tubes. Thus, for accurate efficiency analysis, it should be conducted empirically, looking for mounting and operating conditions like those observed in the field. The Brazilian power generation and distribution company Eletrobras Furnas, through the R&D program of the National Agency of Electrical Energy, has developed a plant for testing parabolic trough concentrators located in Aparecida de Goiânia, in the state of Goiás, Brazil. The main objective of this test plant is the characterization of the prototype concentrator that is being developed by the company itself in partnership with Eudora Energia, seeking to optimize it to obtain the same or better efficiency than the concentrators of this type already known commercially. This test plant is a closed pipe system where a pump circulates a heat transfer fluid, also calledHTF, in the concentrator that is being characterized. A flow meter and two temperature transmitters, installed at the inlet and outlet of the concentrator, record the parameters necessary to know the power absorbed by the system and then calculate its efficiency based on the direct solar irradiation available during the test period. After the HTF gains heat in the concentrator, it flows through heat exchangers that allow the acquired energy to be dissipated into the ambient. The goal is to keep the concentrator inlet temperature constant throughout the desired test period. The developed plant performs the tests in an autonomous way, where the operator must enter the HTF flow rate in the control system, the desired concentrator inlet temperature, and the test time. This paper presents the methodology employed for design and operation, as well as the instrumentation needed for the development of a parabolic trough test plant, being a guideline for standardization facilities.

Keywords: parabolic trough, concentrated solar power, CSP, solar power, test plant, energy efficiency, performance characterization, renewable energy

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Authors: Zavkiddin Mirtoshev, Mirabbos Mirkamalov

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We have analyzed the time series of full disk integrated soft X-ray (SXR) and hard X-ray (HXR) emission from the solar corona during 2004 January 1 to 2009 December 31, covering the descending phase of solar cycle 23. We employed the daily X-ray index (DXI) derived from X-ray observations from the Solar X-ray Spectrometer (SOXS) mission in four different energy bands: 4-5.5; 5.5-7.5 keV (SXR) and 15-20; 20-25 keV (HXR). The application of Lomb-Scargle periodogram technique to the DXI time series observed by the Silicium detector in the energy bands reveals several short and intermediate periodicities of the X-ray corona. The DXI explicitly show the periods of 13.6 days, 26.7 days, 128.5 days, 151 days, 180 days, 220 days, 270 days, 1.24 year and 1.54 year periods in SXR as well as in HXR energy bands. Although all periods are above 70% confidence level in all energy bands, they show strong power in HXR emission in comparison to SXR emission. These periods are distinctly clear in three bands but somehow not unambiguously clear in 5.5-7.5 keV band. This might be due to the presence of Ferrum and Ferrum/Niccolum line features, which frequently vary with small scale flares like micro-flares. The regular 27-day rotation and 13.5 day period of sunspots from the invisible side of the Sun are found stronger in HXR band relative to SXR band. However, flare activity Rieger periods (150 and 180 days) and near Rieger period 220 days are very strong in HXR emission which is very much expected. On the other hand, our current study reveals strong 270 day periodicity in SXR emission which may be connected with tachocline, similar to a fundamental rotation period of the Sun. The 1.24 year and 1.54 year periodicities, represented from the present research work, are well observable in both SXR as well as in HXR channels. These long-term periodicities must also have connection with tachocline and should be regarded as a consequence of variation in rotational modulation over long time scales. The 1.24 year and 1.54 year periods are also found great importance and significance in the life formation and it evolution on the Earth, and therefore they also have great astro-biological importance. We gratefully acknowledge support by the Indian Centre for Space Science and Technology Education in Asia and the Pacific (CSSTEAP, the Centre is affiliated to the United Nations), Physical Research Laboratory (PRL) at Ahmedabad, India. This work has done under the supervision of Prof. Rajmal Jain and paper consist materials of pilot project and research part of the M. Tech program which was made during Space and Atmospheric Science Course.

Keywords: corona, flares, solar activity, X-ray emission

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Authors: Arindam Chaudhuri

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Classification of data has been actively used for most effective and efficient means of conveying knowledge and information to users. The prima face has always been upon techniques for extracting useful knowledge from data such that returns are maximized. With emergence of huge datasets the existing classification techniques often fail to produce desirable results. The challenge lies in analyzing and understanding characteristics of massive data sets by retrieving useful geometric and statistical patterns. We propose a supervised parallel fuzzy rough support vector machine (PFRSVM) for data classification in cloud environment. The classification is performed by PFRSVM using hyperbolic tangent kernel. The fuzzy rough set model takes care of sensitiveness of noisy samples and handles impreciseness in training samples bringing robustness to results. The membership function is function of center and radius of each class in feature space and is represented with kernel. It plays an important role towards sampling the decision surface. The success of PFRSVM is governed by choosing appropriate parameter values. The training samples are either linear or nonlinear separable. The different input points make unique contributions to decision surface. The algorithm is parallelized with a view to reduce training times. The system is built on support vector machine library using Hadoop implementation of MapReduce. The algorithm is tested on large data sets to check its feasibility and convergence. The performance of classifier is also assessed in terms of number of support vectors. The challenges encountered towards implementing big data classification in machine learning frameworks are also discussed. The experiments are done on the cloud environment available at University of Technology and Management, India. The results are illustrated for Gaussian RBF and Bayesian kernels. The effect of variability in prediction and generalization of PFRSVM is examined with respect to values of parameter C. It effectively resolves outliers’ effects, imbalance and overlapping class problems, normalizes to unseen data and relaxes dependency between features and labels. The average classification accuracy for PFRSVM is better than other classifiers for both Gaussian RBF and Bayesian kernels. The experimental results on both synthetic and real data sets clearly demonstrate the superiority of the proposed technique.

Keywords: FRSVM, Hadoop, MapReduce, PFRSVM

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Authors: Ole-Christian Galbo Engstrøm, Erik Schou Dreier, Birthe Møller Jespersen, Kim Steenstrup Pedersen

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Grain quality analysis is a multi-parameterized problem that includes a variety of qualitative and quantitative parameters such as grain type classification, damage type classification, and nutrient regression. Currently, these parameters require human inspection, a multitude of instruments employing a variety of sensor technologies, and predictive model types or destructive and slow chemical analysis. This paper investigates the feasibility of applying near-infrared hyperspectral imaging (NIR-HSI) to grain quality analysis. For this study two datasets of NIR hyperspectral images in the wavelength range of 900 nm - 1700 nm have been used. Both datasets contain images of sparsely and densely packed grain kernels. The first dataset contains ~87,000 image crops of bulk wheat samples from 63 harvests where protein value has been determined by the FOSS Infratec NOVA which is the golden industry standard for protein content estimation in bulk samples of cereal grain. The second dataset consists of ~28,000 image crops of bulk grain kernels from seven different wheat varieties and a single rye variety. In the first dataset, protein regression analysis is the problem to solve while variety classification analysis is the problem to solve in the second dataset. Deep convolutional neural networks (CNNs) have the potential to utilize spatio-spectral correlations within a hyperspectral image to simultaneously estimate the qualitative and quantitative parameters. CNNs can autonomously derive meaningful representations of the input data reducing the need for advanced preprocessing techniques required for classical chemometric model types such as artificial neural networks (ANNs) and partial least-squares regression (PLS-R). A comparison between different CNN architectures utilizing 2D and 3D convolution is conducted. These results are compared to the performance of ANNs and PLS-R. Additionally, a variety of preprocessing techniques from image analysis and chemometrics are tested. These include centering, scaling, standard normal variate (SNV), Savitzky-Golay (SG) filtering, and detrending. The results indicate that the combination of NIR-HSI and CNNs has the potential to be the foundation for an automatic system unifying qualitative and quantitative grain quality analysis within a single sensor technology and predictive model type.

Keywords: deep learning, grain analysis, hyperspectral imaging, preprocessing techniques

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Authors: Jilbert Novelero, Oliver Mariano

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In a world where technological evolution and competition to create innovative products are at its peak, problems on Electronic Waste (E-Waste) are now becoming a global concern. E-waste is said to be any electrical or electronic devices that have reached the terminal of its useful life. The major issue are the volume and the raw materials used in crafting E-waste which is non-biodegradable and contains hazardous substances that are toxic to human health and the environment. The objective of this study is to gather baseline data in terms of the composition of E-waste in the solid waste stream and to determine the top 5 E-waste categories in a highly urbanized city. Recommendations in managing these wastes for its reduction were provided which may serve as a guide for acceptance and implementation in the locality. Pasig City was the chosen beneficiary of the research output and through the collaboration of the City Government of Pasig and its Solid Waste Management Office (SWMO); the researcher successfully conducted the Electronic Waste Analysis and Characterization Study (E-WACS) to achieve the objectives. E-WACS that was conducted on April 2019 showed that E-waste ranked 4th which comprises the 10.39% of the overall solid waste volume. Out of 345, 127.24kg which is the total daily domestic waste generation in the city, E-waste covers 35,858.72kg. Moreover, an average of 40 grams was determined to be the E-waste generation per person per day. The top 5 E-waste categories were then classified after the analysis. The category which ranked first is the office and telecommunications equipment that contained the 63.18% of the total generated E-waste. Second in ranking was the household appliances category with 21.13% composition. Third was the lighting devices category with 8.17%. Fourth on ranking was the consumer electronics and batteries category which was composed of 5.97% and fifth was the wires and cables category where it comprised the 1.41% of the average generated E-waste samples. One of the recommendations provided in this research is the implementation of the Pasig City Waste Advantage Card. The card can be used as a privilege card and earned points can be converted to avail of and enjoy services such as haircut, massage, dental services, medical check-up, and etc. Another recommendation raised is for the LGU to encourage a communication or dialogue with the technology and electronics manufacturers and distributors and international and local companies to plan the retrieval and disposal of the E-wastes in accordance with the Extended Producer Responsibility (EPR) policy where producers are given significant responsibilities for the treatment and disposal of post-consumer products.

Keywords: E-waste, E-WACS, E-waste characterization, electronic waste, electronic waste analysis

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Authors: Yanping Liao, Zenan Wu, Ruigang Zhao

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Frequency diverse array (FDA) beamforming is a technology developed in recent years, and its antenna pattern has a unique angle-distance-dependent characteristic. However, the beam is always required to have strong concentration, high resolution and low sidelobe level to form the point-to-point interference in the concentrated set. In order to eliminate the angle-distance coupling of the traditional FDA and to make the beam energy more concentrated, this paper adopts a multi-carrier FDA structure based on proposed power exponential frequency offset to improve the array structure and frequency offset of the traditional FDA. The simulation results show that the beam pattern of the array can form a dot-shape beam with more concentrated energy, and its resolution and sidelobe level performance are improved. However, the covariance matrix of the signal in the traditional adaptive beamforming algorithm is estimated by the finite-time snapshot data. When the number of snapshots is limited, the algorithm has an underestimation problem, which leads to the estimation error of the covariance matrix to cause beam distortion, so that the output pattern cannot form a dot-shape beam. And it also has main lobe deviation and high sidelobe level problems in the case of limited snapshot. Aiming at these problems, an adaptive beamforming technique based on exponential correction for multi-carrier FDA is proposed to improve beamforming robustness. The steps are as follows: first, the beamforming of the multi-carrier FDA is formed under linear constrained minimum variance (LCMV) criteria. Then the eigenvalue decomposition of the covariance matrix is ​​performed to obtain the diagonal matrix composed of the interference subspace, the noise subspace and the corresponding eigenvalues. Finally, the correction index is introduced to exponentially correct the small eigenvalues ​​of the noise subspace, improve the divergence of small eigenvalues ​​in the noise subspace, and improve the performance of beamforming. The theoretical analysis and simulation results show that the proposed algorithm can make the multi-carrier FDA form a dot-shape beam at limited snapshots, reduce the sidelobe level, improve the robustness of beamforming, and have better performance.

Keywords: adaptive beamforming, correction index, limited snapshot, multi-carrier frequency diverse array, robust

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Authors: Masauso Moses Phiri

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Frequent glucose monitoring is essential to the management of diabetes. Plasmonic enzyme-based glucose biosensors have the advantages of greater specificity, simplicity and rapidity. The aim of this study was to develop a rapid plasmonic colorimetric glucose biosensor based on biocatalytic enlargement of AuNS guided by GOx. Gold nanoparticles of 18 nm in diameter were synthesized using the citrate method. Using these as seeds, a modified seeded method for the synthesis of monodispersed gold nanostars was followed. Both the spherical and star-shaped nanoparticles were characterized using ultra-violet visible spectroscopy, agarose gel electrophoresis, dynamic light scattering, high-resolution transmission electron microscopy and energy-dispersive X-ray spectroscopy. The feasibility of a plasmonic colorimetric assay through growth of AuNS by silver coating in the presence of hydrogen peroxide was investigated by several control and optimization experiments. Conditions for excellent sensing such as the concentration of the detection solution in the presence of 20 µL AuNS, 10 mM of 2-(N-morpholino) ethanesulfonic acid (MES), ammonia and hydrogen peroxide were optimized. Using the optimized conditions, the glucose assay was developed by adding 5mM of GOx to the solution and varying concentrations of glucose to it. Kinetic readings, as well as color changes, were observed. The results showed that the absorbance values of the AuNS were blue shifting and increasing as the concentration of glucose was elevated. Control experiments indicated no growth of AuNS in the absence of GOx, glucose or molecular O₂. Increased glucose concentration led to an enhanced growth of AuNS. The detection of glucose was also done by naked-eye. The color development was near complete in ± 10 minutes. The kinetic readings which were monitored at 450 and 560 nm showed that the assay could discriminate between different concentrations of glucose by ± 50 seconds and near complete at ± 120 seconds. A calibration curve for the qualitative measurement of glucose was derived. The magnitude of wavelength shifts and absorbance values increased concomitantly with glucose concentrations until 90 µg/mL. Beyond that, it leveled off. The lowest amount of glucose that could produce a blue shift in the localized surface plasmon resonance (LSPR) absorption maxima was found to be 10 – 90 µg/mL. The limit of detection was 0.12 µg/mL. This enabled the construction of a direct sensitivity plasmonic colorimetric detection of glucose using AuNS that was rapid, sensitive and cost-effective with naked-eye detection. It has great potential for transfer of technology for point-of-care devices.

Keywords: colorimetric, gold nanostars, glucose, glucose oxidase, plasmonic

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Authors: M. J. Ponnambalam

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Physics Outreach in Jamaica has nearly tripled the number of students doing Introductory Calculus-based Physics at the University of the West Indies (UWI, Mona) within 5 years, and thus has shown the importance of Physics Teaching & Learning in Informal Settings. In 1899, the first president of the American Physical Society called Physics, “the science above all sciences.” Sure enough, exactly one hundred years later, Time magazine proclaims Albert Einstein, “Person of the Century.” Unfortunately, Physics seems to be losing that glow in this century. Many countries, big and small, are finding it difficult to attract bright young minds to pursue Physics. At UWI, Mona, the number of students in first year Physics dropped to an all-time low of 81 in 2006, from more than 200 in the nineteen eighties, spelling disaster for the Physics Department! The author of this paper launched an aggressive Physics Outreach that same year, aimed at conveying to the students and the general public the following messages: i) Physics is an exciting intellectual enterprise, full of fun and delight. ii) Physics is very helpful in understanding how things like TV, CD player, car, computer, X-ray, CT scan, MRI, etc. work. iii) The critical and analytical thinking developed in the study of Physics is of inestimable value in almost any field. iv) Physics is the core subject for Science and Technology, and hence of national development. Science Literacy is a ‘must’ for any nation in the 21st century. Hence, the Physics Outreach aims at reaching out to every person, through every possible means. The Outreach work is split into the following target groups: i) Universities, ii) High Schools iii) Middle Schools, iv) Primary Schools, v) General Public, and vi) Physics teachers in High Schools. The programmes, tools and best practices are adjusted to suit each target group. The feedback from each group is highly positive. e.g. In February 2014, the author conducted in 3 Primary Schools the Interactive Show on ‘Science Is Fun’ to stimulate 290 students’ interest in Science – with lively and interesting demonstrations and experiments in a highly interactive way, using dramatization, story-telling and dancing. The feedback: 47% found the Show ‘Exciting’ and 51% found it ‘Interesting’ – totaling an impressive 98%. When asked to describe the Show in their own words, the leading 4 responses were: ‘Fun’ (26%), ‘Interesting’ (20%), ‘Exciting’ (14%) and ‘Educational’ (10%) – confirming that ‘fun’ & ‘education’ can go together. The success of Physics Outreach in Jamaica verifies the following words of Chodos, Associate Executive Officer of the American Physical Society: “If we could get members to go to K-12 schools and levitate a magnet or something, we really think these efforts would bring great rewards.”

Keywords: physics education, physics popularization, UWI, Jamaica

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Authors: Hussaini Tunde Subairu

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Small and Medium Enterprises (SMEs) sectors serve as catalyst for employment generation, national growth, poverty reduction and economic development in developing and developed countries. However, in Nigeria despite copious and plethora of government policies and stimulus schemes directed at SMEs, the sector is still characterized by high rate of failure and discontinuities. This study therefore investigated owners/managers profile, firms characteristics and external factors as possible determinants of SMEs growth from selected SMEs in Kwara State. Primary data were sourced from 200 SMEs respondents registered with the National Association of Small and Medium Enterprises (NASMES) in Kwara State Central Senatorial District. Multiple Regressions Analysis (MRA) was used to analyze the relationship between dependent and independent variables, and pair wise correlation was employed to examine the relationship among independent variables. The Analysis of Variable (ANOVA) was employed to indicate the overall significant of the model The findings revealed that Analysis of variance (ANOVA) put the value of F-statistics at 420.45 and p-value at 0.000 was significant. The values of R2 and Adjusted R2 of 0.9643 and 0.9620 respectively suggested that 96 percent of variations in employment growth were explained by the explanatory variables. The level of technical and managerial education has t- value of 24.14 and p-value of 0.001, length of managers/owners experience in similar trade with t- value of 21.37 and p-value of 0.001, age of managers/owners with t- value of 42.98 and p-value of 0.001, firm age with t- value of 25.91 and p-value of 0.001, numbers of firms in a cluster with t- value of 7.20 and p-value of 0.001, access to formal finance with t-value of 5.56 and p-value of 0.001, firm technology innovation with t- value of 25.32 and p-value of 0.01, institutional support with t- value of 18.89 and p-value of 0.01, globalization with t- value of 9.78 and p-value of 0.01, and infrastructure with t-value of 10.75 and p-value of 0.01. The result also indicated that initial size has t-value of -1.71 and p-value of 0.090 which is consistent with Gibrat’s Law. The study concluded that owners/managers profile, firm specific characteristics and external factors substantially influenced employment growths of SMEs in the study area. Therefore, policy implication should enhance human capital development of SMEs owners/managers, and strengthen fiscal policy thrust through imposition on tariff regime to minimize effect of globalization. Governments at all level must support SMEs growth radically and enhance institutional support for SMEs growth and radically and significantly upgrading key infrastructure as rail/roads, rail, telecommunications, water and power.

Keywords: external factors, firm specific characteristics, owners / manager profile, small and medium enterprises

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Authors: Pavel H. Llamocca, Victoria Lopez

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The main objective of our work is the comparative analysis of environmental data from Open Data bases, belonging to different governments. This means that you have to integrate data from various different sources. Nowadays, many governments have the intention of publishing thousands of data sets for people and organizations to use them. In this way, the quantity of applications based on Open Data is increasing. However each government has its own procedures to publish its data, and it causes a variety of formats of data sets because there are no international standards to specify the formats of the data sets from Open Data bases. Due to this variety of formats, we must build a data integration process that is able to put together all kind of formats. There are some software tools developed in order to give support to the integration process, e.g. Data Tamer, Data Wrangler. The problem with these tools is that they need data scientist interaction to take part in the integration process as a final step. In our case we don’t want to depend on a data scientist, because environmental data are usually similar and these processes can be automated by programming. The main idea of our tool is to build Hadoop procedures adapted to data sources per each government in order to achieve an automated integration. Our work focus in environment data like temperature, energy consumption, air quality, solar radiation, speeds of wind, etc. Since 2 years, the government of Madrid is publishing its Open Data bases relative to environment indicators in real time. In the same way, other governments have published Open Data sets relative to the environment (like Andalucia or Bilbao). But all of those data sets have different formats and our solution is able to integrate all of them, furthermore it allows the user to make and visualize some analysis over the real-time data. Once the integration task is done, all the data from any government has the same format and the analysis process can be initiated in a computational better way. So the tool presented in this work has two goals: 1. Integration process; and 2. Graphic and analytic interface. As a first approach, the integration process was developed using Java and Oracle and the graphic and analytic interface with Java (jsp). However, in order to open our software tool, as second approach, we also developed an implementation with R language as mature open source technology. R is a really powerful open source programming language that allows us to process and analyze a huge amount of data with high performance. There are also some R libraries for the building of a graphic interface like shiny. A performance comparison between both implementations was made and no significant differences were found. In addition, our work provides with an Official Real-Time Integrated Data Set about Environment Data in Spain to any developer in order that they can build their own applications.

Keywords: open data, R language, data integration, environmental data

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Authors: J. O. Ayinde, S. O. Olatunji

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This study assessed rural youth adoption of cassava production technologies in Southwestern, Nigeria. Specifically, it examine the level of awareness and adoption of cassava production technologies by rural youth, determined the extent of usage of cassava production technologies available to the rural youth, examined constrains to the adoption of cassava production technologies by youth and suggested possible solutions. Multistage sampling procedure was adopted for the study. In the first stage, two states were purposively selected in southwest, Nigeria which are Osun and Oyo states due to high level of cassava production and access to cassava production technology in the areas. In the second stage, purposive sampling technique was used to select two local governments each from the states selected which are Ibarapa central (Igbo-Ora) and Ibarapa East (Eruwa) Local Government Areas (LGAs) in Oyo state; and Ife North (Ipetumodu) and Ede South (Oke Ireesi) LGAs in Osun State. In the third stage, proportionate sampling technique was used to randomly select five, four, six and four communities from the selected LGAs respectively representing 20 percent of the rural communities in them, in all 19 communities were selected. In the fourth stage, Snow ball sampling technique was used to select about 7 rural youths in each community selected to make a total of 133 respondents. Validated structured interview schedule was used to elicit information from the respondents. The data collected were analyzed using both descriptive and inferential statistics to summarize and test the hypotheses of the study. The results show that the average age of rural youths participating in cassava production in the study area is 29 ± 2.6 years and 60 percent aged between 30 and 35 years. Also, more male (67.4 %) were involved in cassava production than females (32.6 %). The result also reveals that the average size of farm land of the respondents is 2.5 ± 0.3 hectares. Also, more male (67.4 %) were involved in cassava production than females (32.6 %). Also, extent of usage of the technologies (r = 0.363, p ≤ 0.01) shows significant relationship with level of adoption of the technologies. Household size (b = 0.183; P ≤ 0.01) and membership of social organizations were significant at 0.01 (b = 0.331; P ≤ 0.01) while age was significant at 0.10 (b = 0.097; P ≤ 0.05). On the other hand 0.01, years of residence (b = - 0.063; P ≤ 0.01) and income (b = - 0.204; P ≤ 0.01) had negative values and implies that a unit increase in each of these variables would decrease extent of usage of the Cassava production technologies. It was concluded that the extent of usage of the technologies in the communities will affect the rate of adoption positively and this will change the negative perception of youths on cassava production thereby ensure food security in the study area.

Keywords: assessment, rural youths’, Cassava production technologies, agricultural production, food security

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Authors: Jessica Scher Lisa, Eric Shyman

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Autism spectrum disorder (ASD) is a neuro-developmental disorder that is characterized by persistent deficits in social communication and social interaction (i.e. deficits in social-emotional reciprocity, nonverbal communicative behaviors, and establishing/maintaining social relationships), as well as by the presence of repetitive behaviors and perseverative areas of interest (i.e. stereotyped or receptive motor movements, use of objects, or speech, rigidity, restricted interests, and hypo or hyperactivity to sensory input or unusual interest in sensory aspects of the environment). Additionally, diagnoses of ASD require the presentation of symptoms in the early developmental period, marked impairments in adaptive functioning, and a lack of explanation by general intellectual impairment or global developmental delay (although these conditions may be co-occurring). Over the past several decades, many theories have been developed in an effort to explain the root cause of ASD in terms of atypical central cognitive processes. The field of neuroscience is increasingly finding structural and functional differences between autistic and neurotypical individuals using neuro-imaging technology. One main area this research has focused upon is in visuospatial processing, with specific attention to the notion of ‘weak central coherence’ (WCC). This paper offers an analysis of findings from selected studies in order to explore research that challenges the ‘deficit’ characterization of a weak central coherence theory as opposed to a ‘superiority’ characterization of strong local coherence. The weak central coherence theory has long been both supported and refuted in the ASD literature and has most recently been increasingly challenged by advances in neuroscience. The selected studies lend evidence to the notion of amplified localized perception rather than deficient global perception. In other words, WCC may represent superiority in ‘local processing’ rather than a deficit in global processing. Additionally, the right hemisphere and the specific area of the extrastriate appear to be key in both the visual and lexicosemantic process. Overactivity in the striate region seems to suggest inaccuracy in semantic language, which lends itself to support for the link between the striate region and the atypical organization of the lexicosemantic system in ASD.

Keywords: autism spectrum disorder, neurology, visual processing, weak coherence

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Authors: Saud Hamdan Alshammari

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Photocatalytic water splitting to produce hydrogen (H₂) has obtained significant attention as an environmentally friendly technology. This process, which produces hydrogen from water and sunlight, represents a renewable energy source. Titanium dioxide (TiO₂) plays a critical role in photocatalytic hydrogen production due to its chemical stability, availability, and low cost. Nevertheless, TiO₂'s wide band gap (3.2 eV) limits its visible light absorption and might affect the effectiveness of the photocatalytic. Coupling TiO₂ with other semiconductors is a strategy that can enhance TiO₂ by narrowing its band gap and improving visible light absorption. This paper studies the modification of TiO₂ by coupling it with another semiconductor such as CdS nanoparticles using a reflux reactor and autoclave reactor that helps form a core-shell structure. Characterization techniques, including TEM and UV-Vis spectroscopy, confirmed successful coating of TiO₂ on CdS core, reduction of the band gap from 3.28 eV to 3.1 eV, and enhanced light absorption in the visible region. These modifications are attributed to the heterojunction structure between TiO₂ and CdS.The essential goal of this study is to improve TiO₂ for use in photocatalytic water splitting to enhance hydrogen production. The core-shell TiO₂@CdS nanoparticles exhibited promising results, due to band gap narrowing and improved light absorption. Future work will involve adding Pt as a co-catalyst, which is known to increase surface reaction activity by enhancing proton adsorption. Evaluation of the TiO₂@CdS@Pt catalyst will include performance assessments and hydrogen productivity tests, considering factors such as effective shapes and material ratios. Moreover, the study could be enhanced by studying further modifications to the catalyst and displaying additional performance evaluations. For instance, doping TiO₂ with metals such as nickel (Ni), iron (Fe), and cobalt (Co) and non-metals such as nitrogen (N), carbon (C), and sulfur (S) could positively influence the catalyst by reducing the band gap, enhancing the separation of photogenerated electron-hole pairs, and increasing the surface area, respectively. Additionally, to further improve catalytic performance, examining different catalyst morphologies, such as nanorods, nanowires, and nanosheets, in hydrogen production could be highly beneficial. Optimizing photoreactor design for efficient photon delivery and illumination will further enhance the photocatalytic process. These strategies collectively aim to overcome current challenges and improve the efficiency of hydrogen production via photocatalysis.

Keywords: hydrogen production, photocatalytic, water spliiting, semiconductor, nanoparticles

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Authors: Obaid AlOtaibi, Salman Hussain

Abstract:

Wind energy is associated with many geographical factors including wind speed, climate change, surface topography, environmental impacts, and several economic factors, most notably the advancement of wind technology and energy prices. It is the fastest-growing and least economically expensive method for generating electricity. Wind energy generation is directly related to the characteristics of spatial wind. Therefore, the feasibility study for the wind energy conversion system is based on the value of the energy obtained relative to the initial investment and the cost of operation and maintenance. In Kuwait, wind energy is an appropriate choice as a source of energy generation. It can be used in groundwater extraction in agricultural areas such as Al-Abdali in the north and Al-Wafra in the south, or in fresh and brackish groundwater fields or remote and isolated locations such as border areas and projects away from conventional power electricity services, to take advantage of alternative energy, reduce pollutants, and reduce energy production costs. The study covers the State of Kuwait with an exception of metropolitan area. Climatic data were attained through the readings of eight distributed monitoring stations affiliated with Kuwait Institute for Scientific Research (KISR). The data were used to assess the daily, monthly, quarterly, and annual available wind energy accessible for utilization. The researchers applied the Suitability Model to analyze the study by using the ArcGIS program. It is a model of spatial analysis that compares more than one location based on grading weights to choose the most suitable one. The study criteria are: the average annual wind speed, land use, topography of land, distance from the main road networks, urban areas. According to the previous criteria, the four proposed locations to establish wind farm projects are selected based on the weights of the degree of suitability (excellent, good, average, and poor). The percentage of areas that represents the most suitable locations with an excellent rank (4) is 8% of Kuwait’s area. It is relatively distributed as follows: Al-Shqaya, Al-Dabdeba, Al-Salmi (5.22%), Al-Abdali (1.22%), Umm al-Hayman (0.70%), North Wafra and Al-Shaqeeq (0.86%). The study recommends to decision-makers to consider the proposed location (No.1), (Al-Shqaya, Al-Dabdaba, and Al-Salmi) as the most suitable location for future development of wind farms in Kuwait, this location is economically feasible.

Keywords: Kuwait, renewable energy, spatial analysis, wind energy

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