Search results for: mathematical-physics applications

Authors: Sheo K. Mishra, Rajneesh K. Srivastava, R. K. Shukla

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In the present work, we report on the optical properties including UV-vis absorption and photoluminescence (PL) of ZnO nanostructures synthesized by sol-gel method. Structural and morphological investigations have been performed by X-ray diffraction method (XRD) and scanning electron microscopy (SEM). The XRD result confirms the formation of hexagonal wurtzite phase of ZnO nanostructures. The presence of various diffraction peaks suggests polycrystalline nature. The XRD pattern exhibits no additional peak due to by-products such as Zn(OH)2. The average crystallite size of prepared ZnO sample corresponding to the maximum intensity peaks is to be ~38.22 nm. The SEM micrograph shows different nanostructures of pure ZnO. Photoluminescence (PL) spectrum shows several emission peaks around 353 nm, 382 nm, 419 nm, 441 nm, 483 nm and 522 nm. The obtained results suggest that the prepared phosphors are quite suitable for optoelectronic applications.

Keywords: ZnO, sol-gel, XRD, PL

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Authors: Sepdiana W. Rahmawati, Santi A. P. Anggraini

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The world of education has made progress with the various new technologies with help of computer. No exception physics education, especially virtual physics practical work. By doing practical work, memory of physics concept will be more advantageous for student and they will understand the essence of actual physics, not only spiked formula. With help of computers, created a variety of applications that can be used by students to perform virtual practical work and students will start thinking systematically to be able find its own concepts and understand the application of physics.

Keywords: essence of physics, formation concept, physics concept, virtual practical work

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Authors: Alison C. Essary, Victor Trastek

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Introduction: The current state of the health care system in the U.S. is characterized by an unprecedented number of people living with multiple chronic conditions, unsustainable rise in health care costs, inadequate access to care, and wide variation in health outcomes throughout the country. An estimated two-thirds of Americans are living with two or more chronic conditions, contributing to 75% of all health care spending. In 2013, the School for the Science of Health Care Delivery (SHCD) was charged with redesigning the health care system through education and research. Faculty in business, law, and public policy, and thought leaders in health care delivery, administration, public health and health IT created undergraduate, graduate, and executive academic programs to address this pressing need. Faculty and students work across disciplines, and with community partners and employers to improve care delivery and increase value for patients. Methods: Curricula apply content in health care administration and operations within the clinical context. Graduate modules are team-taught by faculty across academic units to model team-based practice. Seminars, team-based assignments, faculty mentoring, and applied projects are integral to student success. Cohort-driven models enhance networking and collaboration. This observational study evaluated two years of admissions data, and one year of graduate data to assess program outcomes and inform the current graduate-level curricula. Descriptive statistics includes means, percentages. Results: Fall 2013, the program received 51 applications. The mean GPA of the entering class of 37 students was 3.38. Ninety-seven percent of the fall 2013 cohort successfully completed the program (n=35). Sixty-six percent are currently employed in the health care industry (n=23). Of the remaining 12 graduates, two successfully matriculated to medical school; one works in the original field of study; four await results on the MCAT or DAT, and five were lost to follow up. Attrition of one student was attributed to non-academic reasons. Fall 2014, the program expanded to include both on-ground and online cohorts. Applications were evenly distributed between on-ground (n=70) and online (n=68). Thirty-eight students enrolled in the on-ground program. The mean GPA was 3.95. Ninety-five percent of students successfully completed the program (n=36). Thirty-six students enrolled in the online program. The mean GPA was 3.85. Graduate outcomes are pending. Discussion: Challenges include demographic variability between online and on-ground students; yet, both profiles are similar in that students intend to become change agents in the health care system. In the past two years, on-ground applications increased by 31%, persistence to graduation is > 95%, mean GPA is 3.67, graduates report admission to six U.S. medical schools, the Mayo Medical School integrates SHCD content within their curricula, and there is national interest in collaborating on industry and academic partnerships. This places SHCD at the forefront of developing innovative curricula in order to improve high-value, patient-centered care.

Keywords: delivery science, education, health care delivery, high-value care, innovation in education, patient-centered

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Authors: Vasant Reddy, Shivani A. Singh, Pravin S. More

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In the present investigation, we demonstrated the fabrication of few-layers of graphene sheets with alkali metal i.e. Rb-G using chemical route method. The obtained materials were characterized by means of chemical, structural and electrical techniques, using the ultraviolet-visible spectroscopy (UV-Vis), Fourier transform infrared spectroscopy (FTIR), X-ray powder diffraction (XRD), scanning electron microscopy (SEM) and 4 points probe, respectively. The XRD studies were carried out to understand the phase of the samples where we found a sharp peak of Rb-G at 26.470. UV-Spectroscopy of Graphene and Rb-modified graphene samples shows the absorption peaks at ~248 nm and ~318 nm respectively. These analyses show that this modified material can be useful for gas sensing applications and to be used in diverse areas.

Keywords: chemical route, graphene, gas sensing, UV-spectroscopy

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Authors: Abdel Hadi Ebraheim

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This paper introduces a new extension of the Inverse Pareto distribution in the framework of Marshal-Olkin (1997) family of distributions. This model is capable of modeling various shapes of aging and failure data. The statistical properties of the new model are discussed. Several methods are used to estimate the parameters involved. Explicit expressions are derived for different types of moments of value in reliability analysis are obtained. Besides, the order statistics of samples from the new proposed model have been studied. Finally, the usefulness of the new model for modeling reliability data is illustrated using two real data sets with simulation study.

Keywords: pareto distribution, marshal-Olkin, reliability, hazard functions, moments, estimation

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Authors: Anwar H. Jarndal, Ahmed S. Elwakil

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In this paper, a fraction-order model for pad parasitic effect of GaN HEMT on Si substrate is developed and validated. Open de-embedding structure is used to characterize and de-embed substrate loading parasitic effects. Unbiased device measurements are implemented to extract parasitic inductances and resistances. The model shows very good simulation for S-parameter measurements under different bias conditions. It has been found that this approach can improve the simulation of intrinsic part of the transistor, which is very important for small- and large-signal modeling process.

Keywords: fractional-order modeling, GaNHEMT, si-substrate, open de-embedding structure

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Authors: Laid Degaa, Bachir Bendjedia, Nassim Rizoug, Abdelkader Saidane

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Energy storage system is a key aspect for the development of clean cars. The work proposed here deals with the modeling of hybrid storage sources composed of a combination of lithium-ion battery and supercapacitors. Simulation results show the performance of the active model for a hybrid source and confirm the feasibility of our approach. In this context, sizing of the electrical energy supply is carried out. The aim of this sizing is to propose an 'optimal' solution that improves the performance of electric vehicles in term of weight, cost and aging.

Keywords: battery, electric vehicles, energy, hybrid storage, supercapacitor

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Authors: Elvira S. Castillo, Surupa Shaw

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This paper explores advanced applications of fluid mechanics in the context of sustainable energy. By examining the integration of fluid dynamics with renewable energy technologies, the research uncovers previously underutilized strategies for improving efficiency. Through theoretical analyses, the study demonstrates how fluid mechanics can be harnessed to optimize renewable energy systems. The findings contribute to expanding knowledge in sustainable energy by offering practical insights and methodologies for future research and technological advancements to address global energy challenges.

Keywords: fluid mechanics, sustainable energy, energy efficiency, green energy

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Authors: Alka Jakhar, Harmanpreet Kaur Sandhu, Samaresh Das

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The Terahertz (THz) technology-based devices are heightening at an alarming rate on account of the wide range of applications in imaging, security, communication, and spectroscopic field. The various available room operational THz detectors, including Golay cell, pyroelectric detector, field-effect transistors, and photoconductive antennas, have some limitations such as narrow-band response, slow response speed, transit time limits, and complex fabrication process. There is an urgent demand to explore new materials and device structures to accomplish efficient THz detection systems. Recently, TMDs including topological semimetals and topological insulators such as PtSe₂, MoTe₂, WSe₂, and PtTe₂ provide novel feasibility for photonic and optical devices. The peculiar properties of these materials, such as Dirac cone, fermions presence, nonlinear optical response, high conductivity, and ambient stability, make them worthy for the development of the THz devices. Here, the platinum telluride (PtTe₂) based devices have been demonstrated for THz detection in the frequency range of 0.1-1 THz. The PtTe₂ is synthesized by direct selenization of the sputtered platinum film on the high-resistivity silicon substrate by using the chemical vapor deposition (CVD) method. The Raman spectra, XRD, and XPS spectra confirm the formation of the thin PtTe₂ film. The PtTe₂ channel length is 5µm and it is connected with a bow-tie antenna for strong THz electric field confinement in the channel. The characterization of the devices has been carried out in a wide frequency range from 0.1-1 THz. The induced THz photocurrent is measured by using lock-in-amplifier after preamplifier. The maximum responsivity is achieved up to 1 A/W under self-biased mode. Further, this responsivity has been increased by applying biasing voltage. This photo response corresponds to low energy THz photons is mainly due to the photo galvanic effect in PtTe₂. The DC current is induced along the PtTe₂ channel, which is directly proportional to the amplitude of the incident THz electric field. Thus, these new topological semimetal materials provide new pathways for sensitive detection and sensing applications in the THz domain.

Keywords: terahertz, detector, responsivity, topological-semimetals

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Authors: Andy Wang

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Personalized learning refers to an educational approach that tailors instruction to meet the unique needs, interests, and abilities of each learner. This method of learning aims at providing students with a customized learning experience that is more engaging, interactive, and relevant to their personal lives. With generative AI technology, the author has developed a Personal Tutoring Bot (PTB) that supports personalized learning. The author is currently testing PTB in his EE 499 – Microelectronics Metrology course. Virtual Reality (VR) and Augmented Reality (AR) provide interactive and immersive learning environments that can engage student in online learning. This paper presents the rationale of integrating VR/AR tools in PTB and discusses challenges and solutions of incorporating VA/AR into the Personal Tutoring Bot (PTB).

Keywords: personalized learning, online education, hands-on practice, VR/AR tools

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Authors: C. Njoku Paul

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This paper deals with systems engineering applications design for offshore oil drilling production platform in the Nigerian Marine Environment. Engineering Design model of the distribution and accumulation of petroleum hydrocarbons discharged into marine environment production platform and sources of impact of an offshore is treated.

Keywords: design of offshore oil drilling production platform, marine, environment, petroleum hydrocarbons

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Authors: Jonathan Sohn

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Deep neural networks (DNNs) have shown state-of-the-art performance for many applications, including computer vision, natural language processing, and speech recognition. Recently, adversarial attacks have been studied in the context of deep neural networks, which aim to alter the results of deep neural networks by modifying the inputs slightly. For example, an adversarial attack on a DNN used for object detection can cause the DNN to miss certain objects. As a result, the reliability of DNNs is undermined by their lack of robustness against adversarial attacks, raising concerns about their use in safety-critical applications such as autonomous driving. In this paper, we focus on studying the adversarial attacks and defenses on DNNs for image classification. There are two types of adversarial attacks studied which are fast gradient sign method (FGSM) attack and projected gradient descent (PGD) attack. A DNN forms decision boundaries that separate the input images into different categories. The adversarial attack slightly alters the image to move over the decision boundary, causing the DNN to misclassify the image. FGSM attack obtains the gradient with respect to the image and updates the image once based on the gradients to cross the decision boundary. PGD attack, instead of taking one big step, repeatedly modifies the input image with multiple small steps. There is also another type of attack called the target attack. This adversarial attack is designed to make the machine classify an image to a class chosen by the attacker. We can defend against adversarial attacks by incorporating adversarial examples in training. Specifically, instead of training the neural network with clean examples, we can explicitly let the neural network learn from the adversarial examples. In our experiments, the digit recognition accuracy on the MNIST dataset drops from 97.81% to 39.50% and 34.01% when the DNN is attacked by FGSM and PGD attacks, respectively. If we utilize FGSM training as a defense method, the classification accuracy greatly improves from 39.50% to 92.31% for FGSM attacks and from 34.01% to 75.63% for PGD attacks. To further improve the classification accuracy under adversarial attacks, we can also use a stronger PGD training method. PGD training improves the accuracy by 2.7% under FGSM attacks and 18.4% under PGD attacks over FGSM training. It is worth mentioning that both FGSM and PGD training do not affect the accuracy of clean images. In summary, we find that PGD attacks can greatly degrade the performance of DNNs, and PGD training is a very effective way to defend against such attacks. PGD attacks and defence are overall significantly more effective than FGSM methods.

Keywords: deep neural network, adversarial attack, adversarial defense, adversarial machine learning

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Authors: Shafaq Rubab

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The primary reason for dropping out of school is associated with students’ lack of motivation in class, especially in mathematics. Digital game-based learning is an approach that is being actively explored; there are very few learning games based on proven instructional design models or frameworks due to which the effectiveness of the learning games suffers. The purpose of this research was twofold: first, developing an appropriate instructional design model and second, evaluating the impact of the instructional design model on students’ motivation. This research contributes significantly to the existing literature in terms of student motivation and the impact of instructional design model in digital game-based learning. The sample size for this study consists of two hundred out-of-school students between the age of 6 and 12 years. The research methodology used for this research was a quasi-experimental approach and data was analyzed by using the instructional material motivational survey questionnaire which is adapted from the Keller Arcs model. Control and experimental groups consisting of two hundred students were analyzed by utilizing instructional material motivational survey (IMMS), and comparison of result from both groups showed the difference in the level of motivation of the students. The result of the research showed that the motivational level of student in the experimental group who were taught by the game was higher than the student in control group (taught by conventional methodology). The mean score of the experimental group against all subscales (attention, relevance, confidence, and satisfaction) of IMMS survey was higher; however, no statistical significance was found between the motivational scores of control and experimental group. The positive impact of game-based learning on students’ level of motivation, as measured in this study, strengthens the case for the use of pedagogically sound instructional design models in the design of interactive learning applications. In addition, the present study suggests learning from interactive, immersive applications as an alternative solution for children, especially in Third World countries, who, for various reasons, do not attend school. The mean score of experimental group against all subscales of IMMS survey was higher; however, no statistical significance was found between motivational scores of control and experimental group.

Keywords: digital game-based learning, students’ motivation, and instructional designing, instructional material motivational survey

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Authors: Mine Koyaz, M. Cem Altun

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Selection of the materials satisfying the expected performances is significantly important for any design. Today, with the constantly evolving and developing technologies, the material options are so wide that the necessity of the use of some support tools in the selection process is arising. Therefore, as a sub process of building element design, a systematic material selection tool is developed, that defines four main steps of the material selection; definition, research, comparison and decision. The main purpose of the tool is being an educational instrument that would show a methodic way of material selection in architectural detailing for the use of architecture students. The tool predefines the possible uses of various material databases and other sources of information on material properties. Hence, it is to be used as a guidance for designers, especially with a limited material knowledge and experience. The material selection tool not only embraces technical properties of materials related with building elements’ functional requirements, but also its sensual properties related with the identity of design and its environmental impacts with respect to the sustainability of the design. The method followed in the development of the tool has two main sections; first the examination and application of the existing methods and second the development of trial versions and their applications. Within the scope of the existing methods; design support tools, methodic approaches for the building element design and material selection process, material properties, material databases, methodic approaches for the decision making process are examined. The existing methods are applied by architecture students and newly graduate architects through different design problems. With respect to the results of these applications, strong and weak sides of the existing material selection tools are presented. A main flow chart of the material selection tool has been developed with the objective to apply the strong aspects of the existing methods and develop their weak sides. Through different stages, a different aspect of the material selection process is investigated and the tool took its final form. Systematic material selection tool, within the building element design process, guides the users with a minimum background information, to practically and accurately determine the ideal material that is to be chosen, satisfying the needs of their design. The tool has a flexible structure that answers different needs of different designs and designers. The trial version issued in this paper shows one of the paths that could be followed and illustrates its application over a design problem.

Keywords: architectural education, building element design, material selection tool, systematic approach

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Authors: Mahnaz Khalafehnilsaz, Rozina Rahnama

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Introduction: The elderly population is growing rapidly, and with this growth comes an increased demand for healthcare services. Artificial intelligence (AI) has the potential to revolutionize the delivery of healthcare services to the elderly population. In this study, the various ways in which AI is used to create health content for elderly people and its transformative impact on the healthcare industry will be explored. Method: A systematic review of the literature was conducted to identify studies that have investigated the role of AI in creating health content specifically for elderly people. Several databases, including PubMed, Scopus, and Web of Science, were searched for relevant articles published between 2000 and 2022. The search strategy employed a combination of keywords related to AI, personalized health content, and the elderly. Studies that utilized AI to create health content for elderly individuals were included, while those that did not meet the inclusion criteria were excluded. A total of 20 articles that met the inclusion criteria were identified. Finding: The findings of this review highlight the diverse applications of AI in creating health content for elderly people. One significant application is the use of natural language processing (NLP), which involves the creation of chatbots and virtual assistants capable of providing personalized health information and advice to elderly patients. AI is also utilized in the field of medical imaging, where algorithms analyze medical images such as X-rays, CT scans, and MRIs to detect diseases and abnormalities. Additionally, AI enables the development of personalized health content for elderly patients by analyzing large amounts of patient data to identify patterns and trends that can inform healthcare providers in developing tailored treatment plans. Conclusion: AI is transforming the healthcare industry by providing a wide range of applications that can improve patient outcomes and reduce healthcare costs. From creating chatbots and virtual assistants to analyzing medical images and developing personalized treatment plans, AI is revolutionizing the way healthcare is delivered to elderly patients. Continued investment in this field is essential to ensure that elderly patients receive the best possible care.

Keywords: artificial intelligence, health content, older adult, healthcare

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Authors: Fatma A. Mohamed, Hend M. Ahmed

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This research explores the antimicrobial effects of dielectric barrier discharge (DBD) oxygen plasma treatment combined with ZnO NPs on the cotton fabric, focusing on various treatment durations (5, 10, 15, 20, and 30 minutes) and discharge powers (15.5–17.35 watts) at flow rate 0.5 l/min. After treatment with oxygen plasma and ZnO NPs, the fabric was printed with green tea (Camellia sinensis) at five different concentrations. The study evaluated the treatment's effectiveness by analyzing surface wettability, specifically through wet-out time and hydrophilicity, as well as measuring contact angles. To investigate the chemical changes on the fabric's surface, attenuated total reflectance–Fourier transform infrared (ATR-FTIR) spectroscopy was employed to identify the functional groups formed as a result of the plasma treatment. This comprehensive approach aims to understand how DBD oxygen plasma treatment and ZnO nanoparticles change cotton fabric properties and enhance its antimicrobial potential, paving the way for innovative applications in textiles. In addition to the chemical analysis, the surface morphology of the O₂ plasma/ZnO NPs-treated cotton fabric was examined using scanning electron microscopy (SEM). FTIR analysis revealed an increase in polar functional groups (-COOH, -OH, and -C≡O) on the fabric's surface, contributing to enhanced hydrophilicity and functionality. The antimicrobial properties were evaluated using qualitative and quantitative methods, including agar plate assays and modified Hoenstein tests against Staphylococcus aureus and Escherichia coli. The results indicated a significant improvement in antimicrobial effectiveness for the cotton fabric treated with plasma and coated with natural extracts, maintaining this efficacy even after four washing cycles. This research demonstrates that utilizing oxygen DBD plasma/ZnO NPs treatment, combined with the absorption of tea and tulsi leaf extracts, presents a promising strategy for developing natural antimicrobial textiles. This approach is particularly relevant given the increasing medical and healthcare demands for effective antimicrobial materials. Overall, the method not only enhances the absorption of plant extracts but also significantly boosts antimicrobial efficacy, offering valuable insights for future textile applications.

Keywords: cotton, ZnO NPs, green tea leaf, antimicrobial avtivity, DBD oxygen plasma

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Authors: J. Tirano, H. Zea, C. Luhrs

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It is well known that titanium dioxide is a semiconductor with several applications in photocatalytic process. Its band gap makes it very interesting in the photoelectrodes manufacturing used in photoelectrochemical cells for hydrogen production, a clean and environmentally friendly fuel. The synthesis of 1D titanium dioxide nanostructures, such as nanotubes, makes possible to produce more efficient photoelectrodes for solar energy to hydrogen conversion. In essence, this is because it increases the charge transport rate, decreasing recombination options. However, its principal constraint is to be mainly sensitive to UV range, which represents a very low percentage of solar radiation that reaches earth's surface. One of the alternatives to modifying the TiO2’s band gap and improving its photoactivity under visible light irradiation is to dope the nanotubes with transition metals. This option requires fabricating efficient nanostructured photoelectrodes with controlled morphology and specific properties able to offer a suitable surface area for metallic doping. Hence, currently one of the central challenges in photoelectrochemical cells is the construction of nanomaterials with a proper band position for driving the reaction while absorbing energy over the VIS spectrum. This research focuses on the synthesis and characterization of Nidoped TiO2 nanotubes for improving its photocatalytic activity in solar energy conversion applications. Initially, titanium dioxide nanotubes (TNTs) with controlled morphology were synthesized by two-step potentiostatic anodization of titanium foil. The anodization was carried out at room temperature in an electrolyte composed of ammonium fluoride, deionized water and ethylene glycol. Consequent thermal annealing of as-prepared TNTs was conducted in the air between 450 °C - 550 °C. Afterwards, the nanotubes were superficially modified by nickel deposition. Morphology and crystalline phase of the samples were carried out by SEM, EDS and XRD analysis before and after nickel deposition. Determining the photoelectrochemical performance of photoelectrodes is based on typical electrochemical characterization techniques. Also, the morphological characterization associated electrochemical behavior analysis were discussed to establish the effect of nickel nanoparticles modification on the TiO2 nanotubes. The methodology proposed in this research allows using other transition metal for nanotube surface modification.

Keywords: dimensionally stable electrode, nickel nanoparticles, photo-electrode, TiO₂ nanotubes

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Authors: Ursula D. C. Resende, Yan G. Santos, Lucas M. de O. Andrade

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The recent and fast development of the internet, wireless, telecommunication technologies and low-power electronic devices has led to an expressive amount of electromagnetic energy available in the environment and the smart applications technology expansion. These applications have been used in the Internet of Things devices, 4G and 5G solutions. The main feature of this technology is the use of the wireless sensor. Although these sensors are low-power loads, their use imposes huge challenges in terms of an efficient and reliable way for power supply in order to avoid the traditional battery. The radio frequency based energy harvesting technology is especially suitable to wireless power sensors by using a rectenna since it can be completely integrated into the distributed hosting sensors structure, reducing its cost, maintenance and environmental impact. The rectenna is an equipment composed of an antenna and a rectifier circuit. The antenna function is to collect as much radio frequency radiation as possible and transfer it to the rectifier, which is a nonlinear circuit, that converts the very low input radio frequency energy into direct current voltage. In this work, a set of rectennas, mounted on a paper substrate, which can be used for the inner coating of buildings and simultaneously harvest electromagnetic energy from the environment, is proposed. Each proposed individual rectenna is composed of a 2.45 GHz patch antenna and a voltage doubler rectifier circuit, built in the same paper substrate. The antenna contains a rectangular radiator element and a microstrip transmission line that was projected and optimized by using the Computer Simulation Software (CST) in order to obtain values of S11 parameter below -10 dB in 2.45 GHz. In order to increase the amount of harvested power, eight individual rectennas, incorporating metamaterial cells, were connected in parallel forming a system, denominated Electromagnetic Wall (EW). In order to evaluate the EW performance, it was positioned at a variable distance from the internet router, and a 27 kΩ resistive load was fed. The results obtained showed that if more than one rectenna is associated in parallel, enough power level can be achieved in order to feed very low consumption sensors. The 0.12 m2 EW proposed in this work was able to harvest 0.6 mW from the environment. It also observed that the use of metamaterial structures provide an expressive growth in the amount of electromagnetic energy harvested, which was increased from 0. 2mW to 0.6 mW.

Keywords: electromagnetic energy harvesting, metamaterial, rectenna, rectifier circuit

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Authors: Ruby Priya, Om Parkash Pandey

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Eu doped Gd₂O₃ phosphors are synthesized via co-precipitation method using ammonia as a precipitating agent. The concentration of the Eu was set as 4 mol% for all the samples. The effect of the surfactants (CTAB, PEG, and SDS) on the structural, morphological and luminescent properties has been studied in details. The as-synthesized phosphors were characterized by X-ray diffraction technique, Field emission scanning electron microscopy, Fourier transformed infrared spectroscopy and photoluminescence technique. It was observed that the surfactants have not changed the crystal structure, but influenced the morphology of as-synthesized phosphors to a great extent. The as-synthesized phosphors are expected to be promising candidates for optoelectronic devices, biosensors, MRI contrast agents and various biomedical applications.

Keywords: co-precipitation, Europium, photoluminescence, surfactants

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Authors: Júlio Cesar Lopes de Oliveira, Carlos Henrique Gonçalves Treviso

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The shortage of the automotive market in relation to options for sources of high power car audio systems, led to development of this work. Thus, we developed a source with stabilized voltage with 4320 W effective power. Designed to the voltage of 14.4 V and a choice of two currents: 30 A load option in battery banks and 300 A at full load. This source can also be considered as a source of general use dedicated commercial with a simple control circuit in analog form based on discrete components. The assembly of power circuit uses a methodology for higher power than the initially stipulated.

Keywords: DC-DC power converters, converters, power conversion, pulse width modulation converters

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Authors: Gete Umbrey, Saifur Rahman

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Graphs are found to be most capable in computing, and its abstract structures have been applied in some specific computations and algorithms like in phase encoding controller, processor microcontroller, and synthesis of a CMOS switching network, etc. Being motivated by these works, we develop an independent approach to study semiring structures and various properties by defining the binary operations which in fact, seems analogous to an existing definition in some sense but with a different approach. This work emphasizes specifically on the construction of semigroup and semiring structures on the set of undirected graphs, and their properties are investigated therein. It is expected that the investigation done here may have some interesting applications in theoretical computer science, networking and decision making, and also on joining of two network systems.

Keywords: graphs, join and union of graphs, semiring, weighted graphs

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Authors: Chih-Chiang Hua, Yi-Hsiung Fang, Cyuan-Jyun Wong

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An improved PV balancer for photovoltaic applications is proposed in this paper. The proposed PV balancer senses the voltage and current of PV module and adjusts the output voltage of converter. Thus, the PV system can implement maximum power point tracking (MPPT) independently for each module whether it is under shading, different irradiation or degradation of PV cell. In addition, the cost of PV balancer can be reduced due to the low power rating of converter. To assess the effectiveness of the proposed system, two PV balancers are designed and verified through simulation under different shading conditions. The proposed PV balancers can provide more energy than the traditional PV balancer.

Keywords: MPPT, partial shading, PV System, converter

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Authors: Dona Shaini Abhilasha Nanayakkara, Kurugamage Jude Pravinda Gregory Perera

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E-commerce platforms have revolutionized the shopping experience, offering convenient ways for consumers to make purchases. To improve interactions with customers and optimize marketing strategies, it is essential for businesses to understand user behavior, preferences, and needs on these platforms. This paper focuses on recommending businesses to customize interactions with users based on their behavioral patterns, leveraging data-driven analysis and machine learning techniques. Businesses can improve engagement and boost the adoption of e-commerce platforms by aligning behavioral patterns with user goals of usability and satisfaction. We propose TheAnalyzer, a clustering-based system designed to enhance business productivity by analyzing user-profiles and improving human-computer interaction. The Analyzer seamlessly integrates with business applications, collecting relevant data points based on users' natural interactions without additional burdens such as questionnaires or surveys. It defines five key user analytics as features for its dataset, which are easily captured through users' interactions with e-commerce platforms. This research presents a study demonstrating the successful distinction of users into specific groups based on the five key analytics considered by TheAnalyzer. With the assistance of domain experts, customized business rules can be attached to each group, enabling The Analyzer to influence business applications and provide an enhanced personalized user experience. The outcomes are evaluated quantitatively and qualitatively, demonstrating that utilizing TheAnalyzer’s capabilities can optimize business outcomes, enhance customer satisfaction, and drive sustainable growth. The findings of this research contribute to the advancement of personalized interactions in e-commerce platforms. By leveraging user behavioral patterns and analyzing both new and existing users, businesses can effectively tailor their interactions to improve customer satisfaction, loyalty and ultimately drive sales.

Keywords: data clustering, data standardization, dimensionality reduction, human computer interaction, user profiling

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Authors: Fatima Zahra Moussa, Yamina Belhadef, Souheyla Ferouani

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In this work, we present a new form of miniature circular patch antenna based on CSRR metamaterials with an extended bandwidth proposed for 5 GHz Wi-Fiapplications. A reflection coefficient of -35 dB and a radiation pattern of 7.47 dB are obtained when simulating the initial proposed antenna with the CST microwave studio simulation software. The notch insertion technique in the radiating element was used for matching the antenna to the desired frequency in the frequency band [5150-5875] MHz.An extension of the bandwidth from 332 MHz to 1423 MHz was done by the DGS (defected ground structure) technique to meet the user's requirement in the 5 GHz Wi-Fi frequency band.

Keywords: patch antenna, miniaturisation, CSRR, notches, wifi, DGS

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Authors: R. Latif, W. Jenkal, A. Toumanari, A. Hatim

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This paper presents an efficient method of electrocardiogram signal denoising based on a hybrid approach. Two techniques are brought together to create an efficient denoising process. The first is an Adaptive Dual Threshold Filter (ADTF) and the second is the Discrete Wavelet Transform (DWT). The presented approach is based on three steps of denoising, the DWT decomposition, the ADTF step and the highest peaks correction step. This paper presents some application of the approach on some electrocardiogram signals of the MIT-BIH database. The results of these applications are promising compared to other recently published techniques.

Keywords: hybrid technique, ADTF, DWT, thresholding, ECG signal

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Authors: Hamid Yazdani, Raheleh Akbar

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Infrared thermography is a modern non-destructive measuring method for the examination of redeveloped and non-renovated buildings. Infrared cameras provide a means for temperature measurement in building constructions from the inside, as well as from the outside. Thus, heat bridges can be detected. It has been shown that infrared thermography is applicable for insulation inspection, identifying air leakage and heat losses sources, finding the exact position of heating tubes or for discovering the reasons why mold, moisture is growing in a particular area, and it is also used in conservation field to detect hidden characteristics, degradations of building structures. The paper gives a brief description of the theoretical background of infrared thermography.

Keywords: infrared thermography, examination of buildings, emissivity, heat losses sources

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Authors: Mahmoud H. Abu Elella, Riham R. Mohamed, Magdy W. Sabaa

Abstract:

Firstly, synthesis of N-Quaternized Chitosan (NQC), then it was proven by FTIR and 1H-NMR analysis. The degree of quaternization(DQ 35% ) was determined by equation. Secondly, synthesis of cross-linked hydrogels composed of NQC and poly (vinyl alcohol) (PVA) in different weight ratios in presence of glutaraldehyde (GA) as cross-linking agent. Characterization of the prepared hydrogels was done using FTIR, SEM, XRD,and TGA. Swellability in simulated body fluid (SBF) solutions applied on NQC / PVA hydrogels and swelling rate(Wt%) and metal ions uptake was done on it.

Keywords: hydrogel, metal ions uptake, N-quaternized chitosan, poly (vinyl alcohol), swellability

Procedia PDF Downloads 430

Authors: Jeroen S. de Bruin, Karin Schindler, Christian Schuh

Abstract:

With increasingly more mobile health applications appearing due to the popularity of smartphones, the possibility arises that these data can be used to improve the medical diagnostic process, as well as the overall quality of healthcare, while at the same time lowering costs. However, as of yet there have been no reports of a successful combination of patient-generated data from smartphones with data from clinical routine. In this paper, we describe how these two types of data can be combined in a secure way without modification to hospital information systems, and how they can together be used in a medical expert system for automatic nutritional classification and triage.

Keywords: mobile health, data integration, expert systems, disease-related malnutrition

Procedia PDF Downloads 477

Authors: Ogunrinde Roseline Bosede

Abstract:

This paper presents the development, analysis and implementation of an inverse polynomial numerical method which is well suitable for solving initial value problems in first order ordinary differential equations with applications to sample problems. We also present some basic concepts and fundamental theories which are vital to the analysis of the scheme. We analyzed the consistency, convergence, and stability properties of the scheme. Numerical experiments were carried out and the results compared with the theoretical or exact solution and the algorithm was later coded using MATLAB programming language.

Keywords: differential equations, numerical, polynomial, initial value problem, differential equation

Procedia PDF Downloads 447

Authors: Ahlam Chennani, Nadia Anter, Abdelouahed Médaghri Alaoui, Abdellah Hannioui

Abstract:

Non-precious metals such as zinc, copper, iron, and nickel are promising hydrosilylation catalysts due to their abundance, affordability, and low toxicity. This study focuses on the preparation of zinc nanoparticles using a simple, scalable method. Advanced techniques such as X-ray diffraction (XRD) and transmission electron microscopy (TEM) are used to characterize these catalysts, revealing their crystal structure and morphology. ZnO nanoparticles demonstrate high efficiency and selectivity in hydrosilylation reactions, producing silylated products. These results highlight the potential of ZnO nanocatalysts for advanced chemical transformations and practical applications in various industrial fields.

Keywords: nanoparticles, hydrosilylation, catalysts, non-precious metal

Procedia PDF Downloads 27