Search results for: digital applications

Authors: Babak Sadeghi, Parisa Ghayomipour

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ZnO/Ag nanocomposites coated with polyvinyl chloride (PVC) were prepared by chemical reduction method, for anti-infection biomaterial application. There is a growing interest in attempts in using biomolecular as the templates to grow inorganic nanocomposites in controlled morphology and structure. By optimizing the experiment conditions, we successfully fabricated high yield of ZnO/Ag nanocomposite with full coverage of high-density polyvinyl chloride (PVC) coating. More importantly, ZnO/Ag nanocomposites were shown to significantly inhibit the growth of S. aureus in solution. It was further shown that ZnO/Ag nanocomposites induced thiol depletion that caused death of S. aureus. The coatings were fully characterized using techniques such as scanning electron microscopy (SEM), transmission electron microscopy (TEM) and X-ray diffraction (XRD). Most importantly, compared to uncoated metals, the coatings on PVC promoted healthy antibacterial activity. Importantly, compared to ZnO-Ag -uncoated PVC, the ZnO/Ag nanocomposites coated was approximately triplet more effective in preventing bacteria attachment. The result of Thermal Gravimetric Analysis (TGA) indicates that, the ZnO/Ag nanocomposites are chemically stable in the temperature range from 50 to 900 ºC. This result, for the first time, demonstrates the potential of using ZnO/Ag nanocomposites as a coating material for numerous anti-bacterial applications.

Keywords: nanocomposites, antibacterial activity, scanning electron microscopy (SEM), x-ray diffraction (XRD)

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Authors: Mohamad Mahdi Namdari

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In today's rapidly changing and evolving business competition, companies and organizations require advanced and efficient tools to manage their markets and sales networks. Big data analysis, quick response in competitive markets, process and operations optimization, and forecasting customer behavior are among the concerns of executive managers. Artificial intelligence, as one of the emerging technologies, has provided extensive capabilities in this regard. The use of artificial intelligence in market and sales network management can lead to improved efficiency, increased decision-making accuracy, and enhanced customer satisfaction. Specifically, AI algorithms can analyze vast amounts of data, identify complex patterns, and offer strategic suggestions to improve sales performance. However, many companies are still distant from effectively leveraging this technology, and those that do face challenges in fully exploiting AI's potential in market and sales network management. It appears that the general public's and even the managerial and academic communities' lack of knowledge of this technology has caused the managerial structure to lag behind the progress and development of artificial intelligence. Additionally, high costs, fear of change and employee resistance, lack of quality data production processes, the need for updating structures and processes, implementation issues, the need for specialized skills and technical equipment, and ethical and privacy concerns are among the factors preventing widespread use of this technology in organizations. Clarifying and explaining this technology, especially to the academic, managerial, and elite communities, can pave the way for a transformative beginning. The aim of this research is to elucidate the capacities of artificial intelligence in market and sales network management, identify its opportunities and benefits, and examine the existing challenges and obstacles. This research aims to leverage AI capabilities to provide a framework for enhancing market and sales network performance for managers. The results of this research can help managers and decision-makers adopt more effective strategies for business growth and development by better understanding the capabilities and limitations of artificial intelligence.

Keywords: artificial intelligence, market management, sales network, big data analysis, decision-making, digital marketing

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Authors: T. Ewetumo, K. D. Adedayo, Festus Ben

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Knowledge of the thermal properties of foods is of fundamental importance in the food industry to establish the design of processing equipment. However, for tropical fruit juice, there is very little information in literature, seriously hampering processing procedures. This research work describes the development of an instrument for automated thermal conductivity and thermal diffusivity measurement of tropical fruit juice using a transient thermal probe technique based on line heat principle. The system consists of two thermocouple sensors, constant current source, heater, thermocouple amplifier, microcontroller, microSD card shield and intelligent liquid crystal. A fixed distance of 6.50mm was maintained between the two probes. When heat is applied, the temperature rise at the heater probe measured with time at time interval of 4s for 240s. The measuring element conforms as closely as possible to an infinite line source of heat in an infinite fluid. Under these conditions, thermal conductivity and thermal diffusivity are simultaneously measured, with thermal conductivity determined from the slope of a plot of the temperature rise of the heating element against the logarithm of time while thermal diffusivity was determined from the time it took the sample to attain a peak temperature and the time duration over a fixed diffusivity distance. A constant current source was designed to apply a power input of 16.33W/m to the probe throughout the experiment. The thermal probe was interfaced with a digital display and data logger by using an application program written in C++. Calibration of the instrument was done by determining the thermal properties of distilled water. Error due to convection was avoided by adding 1.5% agar to the water. The instrument has been used for measurement of thermal properties of banana, orange and watermelon. Thermal conductivity values of 0.593, 0.598, 0.586 W/m^o C and thermal diffusivity values of 1.053 ×〖10〗^(-7), 1.086 ×〖10〗^(-7), and 0.959 ×〖10〗^(-7) 〖m/s〗^2 were obtained for banana, orange and water melon respectively. Measured values were stored in a microSD card. The instrument performed very well as it measured the thermal conductivity and thermal diffusivity of the tropical fruit juice samples with statistical analysis (ANOVA) showing no significant difference (p>0.05) between the literature standards and estimated averages of each sample investigated with the developed instrument.

Keywords: thermal conductivity, thermal diffusivity, tropical fruit juice, diffusion equation

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Authors: Shriya Shukla, Lachin Fernando

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

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

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Authors: Jihane Mossalim

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This study proposes a methodological framework that combines Participatory Action Research (PAR) with Arts-Based Research (ABR) to explore the potential of generative AI in elementary art education. By integrating PAR, this framework emphasizes elementary school students’ active participation as co-researchers, engaging with AI technologies and reflecting on their creative journeys. PAR’s iterative cycles of planning, action, observation, and reflection provide a solid structure for involving children in the research process, ensuring that the study is inclusive and reflective of the children’s perspectives. Arts-Based Research, on the other hand, allows for the exploration of AI not just as a tool but as a medium of creative expression. ABR’s emphasis on visual, performative, and creative outputs complements PAR’s inclusive approach, offering a dynamic and flexible way of studying the intersection of technology and art in educational contexts. This combination is particularly valuable as it encourages students to express their ideas and emotions through art, making the learning process more engaging and personally meaningful. Despite the recognized benefits of both PAR and ABR, there remains a notable gap in research that applies these methodologies in combination with elementary school students, particularly in the context of emerging technologies like generative AI. Addressing this gap is crucial, as integrating these approaches can lead to more inclusive and innovative educational practices that cater to the diverse needs of young learners. This chapter seeks to demonstrate how integrating PAR and ABR can empower young learners, giving them a voice in the research process while enriching their creative and critical thinking skills. This chapter will develop a methodology that integrates both theoretical and practical aspects of PAR and ABR, highlighting the challenges and opportunities that emerge when these approaches are integrated. It will also discuss how to adapt these methods for research in the elementary art education, providing a foundation for future inquiry. Further, the chapter will focus on situating these methodological developments in relation to a study that seeks to understand the potential of generative AI in fostering creativity, collaboration, and critical thinking among young learners. Ultimately, this work aims to provide a pioneering example that inspires further exploration and development of educational practices in the digital age.

Keywords: participatory action research, arts-based research, generative AI, elementary art education

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Authors: Usama Zahid, Fasiha Kashif

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The tailoring and controlled fabrication of metal-organic framework (MOF) with diverse conductive materials have garnered significant academic attention, owing to their potential applications in next-generation energy storage devices. Herein, we synthesized the rGO@Cd-MOF composite by a facile solvothermal method and utilized as an electrode in hybrid supercapacitor. FESEM and TEM images verify composite material formation as Cd-MOF crystals are dispersed on the rGO nanosheet. The rGO@Cd-MOF composite electrode showcases outstanding electrochemical performance in a 3-electrode system by achieving the high specific capacity of 634 Cg⁻¹ at a current density of 2 Ag⁻¹ within the potential range of 0 to 0.6 V. Furthermore, the composite was utilized as an electrode in symmetric and asymmetric supercapacitor devices, however, ASC device achieved impressive energy density of 78.69 Whkg⁻¹ at a power density of 1282 Wkg⁻¹, compared to SSC device, which achieved 21.15 Whkg⁻¹ at 721 Wkg⁻¹. The ASC device maintained 90 % coulombic efficiency and 94 % capacity after 10k charge-discharge cycles. Thus, for the first time, this study presents the use of rGO@Cd-MOF composite to develop an effective supercapacitor electrode. This proposed layout is also versatile for a flexible symmetric and asymmetric supercapacitor device, providing high energy density and specific capacity values.

Keywords: metal-organic framework, rGO nanosheets, symmetric supercapacitor, asymmetric supercapacitor, energy density, power density

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Authors: Simon Bambey, Edward Lim, Kai Corley-Jory, Pooya Taheri

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The main goal of this paper is to propose a simple and low-cost microcontroller-based laser communication link. To demonstrate that laser communication is a viable and efficient means for transmitting data, a transceiver capable of transfer rates of approximately 0.7 kB/s is prototyped. The hardware used for the transceiver consists of Commercial Off-The-Shelf (COTS) lasers, photodiodes, and the Arduino Mega 2560 which is an open-source and easy-to-use microcontroller-based platform intended for making interactive projects. A graphic user interface utilizing the Meteor framework is developed to facilitate the communication between the user and transceiver. The developed transceiver prototype is capable of receiving and transmitting data at significant ranges with no loss of information. Furthermore, stable and secure communication is achieved through several mechanisms developed to manage simultaneous sending and receiving, in addition to detecting physical interruptions during transmission. The design setup is scalable and with further development can be transformed into a fiber-optic transmission system. Due to its nature, laser communication is very secure and can provide a safe and private communication link. Overall, this paper demonstrates how laser communication can be an economical, durable, and effective means of information transfer.

Keywords: Arduino microcontrollers, laser applications, user interfaces, wireless communication

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Authors: Sijo S. Thomas, S. Hridya, Manoj Mohan, Bibin Jacob, Hysen Thomas

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Ferrites are iron based oxides with technologically significant magnetic properties and have widespread applications in medicine, technology, and industry. There has been a growing interest in the study of magnetic, electrical and structural properties of mixed ferrites. In the present work, structural and magnetic properties of Nickel and Calcium substituted Fe₃O₄ nanoparticles were investigated. NiₓCa₁₋ₓFe₂O₄ nanoparticles (x = 0, 0.1, 0.3, 0.5, 0.7, 0.9) were synthesized by chemical co-precipitation method and the samples were subsequently sintered at 900°C. The magnetic and structural properties of NiₓCa₁₋ₓFe₂O₄ were investigated using Vibrating Sample Magnetometer and X-Ray diffraction. The XRD results revealed that the synthesized particles have nanometer size and it varies from 46-72 nm as the calcium concentration diminishes. The variation is explained based on the increase in the reaction rate with Ni concentration which favors the formation of ultrafine particles of mixed ferrites. VSM results show pure CaFe₂O₄ exhibit paramagnetic behavior with low saturation value. As the concentration of Ca decreases, a transition occurs from paramagnetic state to ferromagnetic state. When the concentration of Ni becomes dominant, magnetic saturation, coercivity, and retentivity become high, indicating near ferromagnetic behavior of the compound.

Keywords: co-precipitation, ferrites, magnetic behavior, structure

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Authors: Kwangwon Seo, Haksoo Han

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Al-Si was synthesized and introduced in poly 2,2’-m-(phenylene)-5,5’-bibenzimidazole (PBI). As a result, a series of five Al-Si/PBI composite (ASPBI) membranes (0, 3, 6, 9, and 12 wt.%) were developed and characterized for application in high temperature polymer electrolyte membrane fuel cells (HT-PEMFCs). The chemical and morphological structure of ASPBI membranes were analyzed by Fourier transform infrared spectroscopy, X-ray diffractometer and scanning electron microscopy. According to the doping level test and thermogravimetric analysis, as the concentration of Al-Si increased, the doping level increased up to 475%. Moreover, the proton conductivity, current density at 0.6V, and maximum power density of ASPBI membranes increased up to 0.31 Scm-1, 0.320 Acm-2, and 0.370 Wcm-2, respectively, because the increased concentration of Al-Si allows the membranes to hold more PA. Alternatively, as the amount of Al-Si increased, the tensile strength of PA-doped and -undoped membranes decreased. This was resulted by both excess PA and aggregation, which can cause serious degradation of the membrane and induce cracks. Moreover, the PA-doped and -undoped ASPBI12 had the lowest tensile strength. The improved performances of ASPBI membranes imply that ASPBI membranes are possible candidates for HT-PEMFC applications. However, further studies searching to improve the compatibility between PBI matrix and inorganic and optimize the loading of Al-Si should be performed.

Keywords: composite membrane, high temperature polymer electrolyte membrane fuel cell, membrane electrode assembly, polybenzimidazole, polymer electrolyte membrane, proton conductivity

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Authors: Felix Boehnisch, Alexander Lutz

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Based on the number of users and the amount of content posted daily, Facebook is considered the largest social network in the world. This content includes images or text posts from companies but also private persons, which are also commented on by other users. However, it can sometimes be difficult for companies to keep track of all the posts and the reactions to them, especially when there are several posts a day that contain hundreds to thousands of comments. To facilitate this, the following paper deals with the possible applications of sentiment analysis to social media comments in order to be able to support the work in social media marketing. In a first step, post comments were divided into positive and negative by a subjective rating, then the same comments were checked for their polarity value by the two german python libraries TextBlobDE and SentiWS and also grouped into positive, negative, or even neutral. As a control, the subjective classifications were compared with the machine-generated ones by a confusion matrix, and relevant quality criteria were determined. The accuracy of both libraries was not really meaningful, with 60% to 66%. However, many words or sentences were not evaluated at all, so there seems to be room for optimization to possibly get more accurate results. In future studies, the use of these specific German libraries can be optimized to gain better insights by either applying them to stricter cleaned data or by adding a sentiment value to emojis, which have been removed from the comments in advance, as they are not contained in the libraries.

Keywords: Facebook, German libraries, polarity, sentiment analysis, social media comments

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Authors: Sena Su, Burak Ozbek, Yesim M. Sahin, Sevil Yucel, Dilek Kazan, Faik N. Oktar, Nazmi Ekren, Oguzhan Gunduz

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In recent years, protein, lipid or polysaccharide-based polymers have been used in order to develop biodegradable materials and their chemical nature determines the physical properties of the resulting films. Among these polymers, proteins from different sources have been extensively employed because of their relative abundance, film forming ability, and nutritional qualities. In this study, the biodegradable composite nanofiber films based on fish sarcoplasmic protein (FSP) were prepared via electrospinning technique. Biodegradable polycaprolactone (PCL) was blended with the FSP to obtain hybrid FSP/PCL nanofiber mats with desirable physical properties. Mixture solutions of FSP and PCL were produced at different concentrations and their density, viscosity, electrical conductivity and surface tension were measured. Mechanical properties of electrospun nanofibers were evaluated. Morphology of composite nanofibers was observed using scanning electron microscopy (SEM). Moreover, Fourier transform infrared spectrometer (FTIR) studies were used for analysis chemical composition of composite nanofibers. This study revealed that the FSP based nanofibers have the potential to be used for different applications such as biodegradable packaging, drug delivery, and wound dressing, etc.

Keywords: edible film, electrospinning, fish sarcoplasmic protein, nanofiber

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Authors: Jeng-Shin Sheu, Qi-Xun Zheng

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This paper mainly discusses a method of separating speech when using a microphone array without knowing the number and direction of sound sources. In recent years, there have been many studies on the method of separating signals by using masking, but most of the separation methods must be operated under the condition of a known number of sound sources. Such methods cannot be used for real-time applications. In our method, this paper uses Circular-Integrated-Cross-Spectrum to estimate the statistical histogram distribution of the direction of arrival (DOA) to obtain the number of sound sources and sound in the mixed-signal Source direction. In calculating the relevant parameters of the ring integrated cross-spectrum, the phase (Phase of the Cross-Power Spectrum) and phase rotation factors (Phase Rotation Factors) calculated by the cross power spectrum of each microphone pair are used. In the part of separating speech, it uses the DOA weighting and shielding separation method to calculate the sound source direction (DOA) according to each T-F unit (time-frequency point). The weight corresponding to each T-F unit can be used to strengthen the intensity of each sound source from the T-F unit and reduce the influence of the remaining sound sources, thereby achieving voice separation.

Keywords: real-time, spectrum analysis, sound source localization, sound source separation

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Authors: Sherif Keddis, Rafik Mitry, Norbert Schwesinger

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

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

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Authors: Shrikant Randhavane, Anjali Khambete

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Use of Pesticides is vital in attaining food security and protection from harmful pests and insects in living environment. Chlorpyrifos, an organophosphate pesticide is widely used worldwide for various purposes. Due to its wide use and applications, its residues are found in environmental matrices and persist in nature for long duration of time. This has an adverse effect on human, aquatic and living bodies. Use of different methodologies is need of an hour to treat such type of recalcitrant compound. The paper focuses on Hydrodynamic Cavitation (HC), a hybrid Advanced Oxidation Potential (AOP) method to degrade Chlorpyrifos in aqueous water. Obtained results show that optimum inlet pressure of 5 bars gave maximum degradation of 99.25% for lower concentration and 87.14% for higher concentration Chlorpyrifos solution in 1 hour treatment time. Also, with known initial concentrations, comparing treatment time with optimum pressure of 5 bars, degradation efficiency increases with Hydrodynamic Cavitation. The potential application of HC in removal of Chemical Oxygen Demand (COD) from real effluent with venturi as cavitating device reveals around 40% COD removal with 1 hour of treatment time.

Keywords: advanced oxidation potential, cavitation, chlorpyrifos, COD

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Authors: Peter Akayuure, Michael Johnson Nabie

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Similar to many colonized nations in the world, one indelible mark left by colonial masters after Ghana’s independence in 1957 has been the fact that many contexts used to teach statistics and probability concepts are often alien and do not resonate with the social domain of our indigenous Ghanaian child. This has seriously limited the understanding, discoveries, and applications of mathematics for national developments. With the recent curriculum demands of making the Ghanaian child mathematically literate, this qualitative study involved video recordings and mathematical analysis of play sessions of an indigenous girl game called Ampe with the aim to demystify the concepts in probability theorem, which is applied in mathematics related fields of study. The mathematical analysis shows that the game of Ampe, which is widely played by school girls in Ghana, is suitable for learning concepts of the probability theorems. It was also revealed that as a girl game, the use of Ampe provides good lessons to educators, textbook writers, and teachers to rethink about the selection of mathematics tasks and learning contexts that are sensitive to gender. As we undertake to transform teacher education and student learning, the use of indigenous games should be critically revisited.

Keywords: Ampe, mathematical analysis, probability theorem, Ghanaian girl game

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Authors: I. Stacher, B. Schrank, K. Stiehl, K. A. Woodcock

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Background: The need and desire for connectedness and belonging to a peer group is a major concern in middle childhood. This is particularly true for the period of school transition when making and maintaining friendships is put to the test. Social relations are important for enhancing self-esteem, confidence, and mental health. Conflicts with peers and victimization mark challenges in the complex social environment of early adolescents. Thus, the promotion of supportive peer relationships is an important social goal. The current literature lacks an in-depth analysis of young people’s experiences connected to making and maintaining friendships. Aim: This qualitative study aims to understand the factors that facilitate and hinder friendship and peer relations within the complex context of school transition. Methods: Youth engagement workshops at primary and secondary schools were conducted with 53 classes (N = 906 pupils; M age = 10.44; SD = .912) in 29 different schools across lower Austria. A big poster was created with the entire class, collecting early adolescents’ ideas on ways they can support each other in the school environment. Then, students were divided into smaller groups and encouraged to share their personal experiences of friendship. Verbatim quotes from students were collected on observation sheets and sticky notes during the activities. A thematic analysis was conducted. Results: Early adolescents describe facilitating factors that allow them to connect with peers. These descriptions are mainly on a behavioral level and are relevant for face-to-face and digital contact, e.g., practical and emotional support, spending time together, pleasure and fun. Specific challenges such as offensive actions, betrayal, and lack of emotion regulation exist and need to be addressed if aiming to reduce barriers between peers. Conclusion: Knowing first-hand experiences, desires, and barriers for making and maintaining friends at the time of school transition will help researchers to develop preventive health programs that adequately address the needs and preferences of today’s youth.

Keywords: youth voice, experts by experience, friendship, peer relations, primary-secondary school, transition

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Authors: Bandar Alahmadi, Lethia Jackson

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Machine Learning model is used today in many real-life applications. The safety and security of such model is important, so the results of the model are as accurate as possible. One challenge of machine learning model security is the adversarial examples attack. Adversarial examples are designed by the attacker to cause the machine learning model to misclassify the input. We propose a method to generate adversarial examples to attack image classifiers. We are modifying the successfully classified images, so a classifier misclassifies them after the modification. In our method, we do not update the whole image, but instead we detect the important region, modify it, place it back to the original image, and then run it through a classifier. The algorithm modifies the detected region using two methods. First, it will add abstract image matrix on back of the detected image matrix. Then, it will perform a rotation attack to rotate the detected region around its axes, and embed the trace of image in image background. Finally, the attacked region is placed in its original position, from where it was removed, and a smoothing filter is applied to smooth the background with foreground. We test our method in cascade classifier, and the algorithm is efficient, the classifier confident has dropped to almost zero. We also try it in CNN (Convolutional neural network) with higher setting and the algorithm was successfully worked.

Keywords: adversarial examples, attack, computer vision, image processing

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Authors: Magdalena Hałupka-Bryl, Magdalena Bednarowicz, Ryszard Krzyminiewski, Yukio Nagasaki

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Due to their unique physical properties, superparamagnetic iron oxide nanoparticles are increasingly used in medical applications. They are very useful carriers for delivering antitumor drugs in targeted cancer treatment. Magnetic nanoparticles (PEG-PIONs/DOX) with chemotherapeutic were synthesized by coprecipitation method followed by coating with biocompatible polymer PEG-derivative (poly(ethylene glycol)-block-poly(4-vinylbenzylphosphonate). Complete physicochemical characterization was carried out (ESR, HRTEM, X-ray diffraction, SQUID analysis) to evaluate the magnetic properties of obtained PEG-PIONs/DOX. Nanoparticles were investigated also in terms of their stability, drug loading efficiency, drug release and antiproliferative effect on cancer cells. PEG-PIONs/DOX have been successfully used for the efficient delivery of an anticancer drug into the tumor region. Fluorescent imaging showed the internalization of PEG-PIONs/DOX in the cytoplasm. Biodistribution studies demonstrated that PEG-PIONs/DOX preferentially accumulate in tumor region via the enhanced permeability and retention effect. The present findings show that synthesized nanosystem is promising tool for potential magnetic drug delivery.

Keywords: targeted drug delivery, magnetic properties, iron oxide nanoparticles, biodistribution

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

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

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

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Authors: Coline Bretz, Andrea Vaccaro, Dario Leumann

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The food, personal care, and cosmetic industries are seeing increased consumer demand for more sustainable and innovative ingredients. When developing new formulations incorporating such ingredients, stability is one of the first criteria that must be assessed, and it is thus of great importance to have a method that can detect instabilities early and quickly. Diffusing Wave Spectroscopy (DWS) is a light scattering technique that probes the motion,i.e., the mean square displacement (MSD), of colloids, such as nanoparticles in a suspension or droplets in emulsions. From the MSD, the rheological properties of the surrounding medium can be determined via the so-called microrheology approach. In the case of purely viscous media, it is also possible to obtain information about particle size. DWS can thus be used to monitor the size evolution of particles, droplets, or bubbles in aging dispersions, emulsions, or foams. In the context of early instability detection in emulsions, DWS offers considerable advantages, as the samples are measured in a contact-free manner, using only small quantities of samples loaded in a sealable cuvette. The sensitivity and rapidity of the technique are key to detecting and following the ageing of emulsions reliably. We present applications of DWS focused on the characterization of emulsions. In particular, we demonstrate the ability to record very subtle changes in the structural properties early on. We also discuss the various mechanisms at play in the destabilization of emulsions, such as coalescence or Ostwald ripening, and how to identify them through this technique.

Keywords: instrumentation, emulsions, stability, DWS

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Authors: Sheelagh Heugh, Michael Upton, Kriya Kalidas, Stephen Breen

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This article aims to create awareness of the opportunities and issues the artificial intelligence (AI) tool GPT-3 (Generative Pre-trained Transformer-3) brings to higher education. Technological disruptors have featured in higher education (HE) since Konrad Klaus developed the first functional programmable automatic digital computer. The flurry of technological advances, such as personal computers, smartphones, the world wide web, search engines, and artificial intelligence (AI), have regularly caused disruption and discourse across the educational landscape around harnessing the change for the good. Accepting AI influences are inevitable; we took mixed methods through participatory action research and evaluation approach. Joining HE communities, reviewing the literature, and conducting our own research around Chat GPT-3, we reviewed our institutional approach to changing our current practices and developing policy linked to assessments and the use of Chat GPT-3. We review the impact of GPT-3, a high-powered natural language processing (NLP) system first seen in 2020 on HE. Historically HE has flexed and adapted with each technological advancement, and the latest debates for educationalists are focusing on the issues around this version of AI which creates natural human language text from prompts and other forms that can generate code and images. This paper explores how Chat GPT-3 affects the current educational landscape: we debate current views around plagiarism, research misconduct, and the credibility of assessment and determine the tool's value in developing skills for the workplace and enhancing critical analysis skills. These questions led us to review our institutional policy and explore the effects on our current assessments and the development of new assessments. Conclusions: After exploring the pros and cons of Chat GTP-3, it is evident that this form of AI cannot be un-invented. Technology needs to be harnessed for positive outcomes in higher education. We have observed that materials developed through AI and potential effects on our development of future assessments and teaching methods. Materials developed through Chat GPT-3 can still aid student learning but lead to redeveloping our institutional policy around plagiarism and academic integrity.

Keywords: artificial intelligence, Chat GPT-3, intellectual property, plagiarism, research misconduct

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Authors: Islam Elsayed Hussein Ali, Stefan M. Wagner

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Smartphone and tablet computers, as well as other ultra portable devices, have already gained enough critical mass to be considered mainstream devices, being present in the daily lives of millions of higher education students. Many universities throughout the world have already adopted or are planning to adopt mobile technologies in many of their courses as a better way to connect students with the subjects they are studying. These new mobile platforms allow students to access content anywhere/anytime to immerse himself/herself into that content (alone or interacting with teachers or colleagues via web communication forms) and to interact with that content in ways that were not previously possible. This paper plans to provide a thorough overview of the possibilities and consequences of m-learning in higher education environments as a gateway to ubiquitous learning – perhaps the ultimate form of learner engagement, since it allows the student to learn, access and interact with important content in any way or at any time or place he might want so the objective of the study is to examine how the usage of mobile phones for m-learning differs between heavy and light mobile phone users at TU Braunschweig. Heavy mobile phone users are hypothesized to have access to/subscribe to one type of mobile content than light mobile phone users, to have less frequent access to, subscribe to or purchase mobile content within the last year than light mobile phone users, and to pay less money for mobile learning, its content and mobile games than light mobile phone users.

Keywords: mobile learning, technologies, applications, higher education

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Authors: Khadija Oumghar, Adil Eddiai, Omar Cherkaoui

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Using flexible piezoelectric nanocomposite films in autonomous nano-systems, sensors, and portable electronics has garnered significant attention within the scientific community. This paper investigates the impact of Lead zirconate titanate (PZT) nanoparticles on the crystal structure of polyvinylidene fluoride hexafluoro propylene (PVDF-HFP)/polylactic acid (PLA), its distinctive crystallization behavior, mechanical properties, and the ensuing enhancement in piezoelectricity. In this study, PVDF-HFP/PLA/PZT nanocomposite films were fabricated utilizing the solvent casting technique, incorporating varying concentrations of PZT. Subsequent characterization of the films involved comprehensive analyses employing polarized optical microscopy (POM), Fourier-transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD). POM observations revealed a homogeneous dispersion of PZT nanofillers within the PVDF-HFP/PLA matrix. FTIR and XRD analyses confirmed the presence of the β-phase in the nanocomposites, signifying improvements in their piezoelectric properties. The substantial augmentation in piezoelectricity witnessed emphasizes the potential of electroactive nanocomposites for energy harvesting applications. This research contributes to advancing sustainable energy technologies by elucidating the efficacy of PZT-enhanced PVDFHFP-PLA nanocomposites as proficient materials for piezoelectric energy conversion.

Keywords: piezoelectric films, energy harvesting, dielectric polymers, nanocomposite

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Authors: Linhang Zhu, Hongyu Zhu, Jiahe Liu

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This paper investigated a method of indoor real-time positioning and mapping based on the Manhattan world assumption. In indoor environments, relying solely on feature matching techniques or other geometric algorithms for sensor pose estimation inevitably resulted in cumulative errors, posing a significant challenge to indoor positioning. To address this issue, we adopt the Manhattan world hypothesis to optimize the camera pose algorithm based on feature matching, which improves the accuracy of camera pose estimation. A special processing method was applied to image data frames that conformed to the Manhattan world assumption. When similar data frames appeared subsequently, this could be used to eliminate drift in sensor pose estimation, thereby reducing cumulative errors in estimation and optimizing mapping and positioning. Through experimental verification, it is found that our method achieves high-precision real-time positioning in indoor environments and successfully generates maps of indoor environments. This provides effective technical support for applications such as indoor navigation and robot control.

Keywords: Manhattan world hypothesis, real-time positioning and mapping, feature matching, loopback detection

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Authors: Wajdi Mohamed Ratemi

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The very well-known stacked sets of numbers referred to as Pascal’s triangle present the coefficients of the binomial expansion of the form (x+y)n. This paper presents an approach (the Staircase Horizontal Vertical, SHV-method) to the generalization of planar Pascal’s triangle for polynomial expansion of the form (x+y+z+w+r+⋯)n. The presented generalization of Pascal’s triangle is different from other generalizations of Pascal’s triangles given in the literature. The coefficients of the generalized Pascal’s triangles, presented in this work, are generated by inspection, using embedded Pascal’s triangles. The coefficients of I-variables expansion are generated by horizontally laying out the Pascal’s elements of (I-1) variables expansion, in a staircase manner, and multiplying them with the relevant columns of vertically laid out classical Pascal’s elements, hence avoiding factorial calculations for generating the coefficients of the polynomial expansion. Furthermore, the classical Pascal’s triangle has some pattern built into it regarding its odd and even numbers. Such pattern is known as the Sierpinski’s triangle. In this study, a presentation of Sierpinski-like patterns of the generalized Pascal’s triangles is given. Applications related to those coefficients of the binomial expansion (Pascal’s triangle), or polynomial expansion (generalized Pascal’s triangles) can be in areas of combinatorics, and probabilities.

Keywords: pascal’s triangle, generalized pascal’s triangle, polynomial expansion, sierpinski’s triangle, combinatorics, probabilities

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Authors: Hamid Merzouk, Djahida Touati-Talantikite, Amina Zaabar

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New nanosized materials are in huge expansion worldwide. They play a fundamental role in various industrial applications thanks their unique and functional properties. Moreover, in recent years, a great effort has been made to the design and control fabrication of nanostructured semiconductors such zinc sulphide. In recent years, much attention has been accorded in doped and co-doped ZnS to improve the ZnS films quality. We present in this work the preparation and characterization of ZnS and Al doped ZnS thin films. Nanoparticles ZnS and Al doped ZnS films are prepared by chemical bath deposition method (CBD), for various dopant concentrations. Thin films are deposed onto commercial microscope glass slides substrates. Thiourea is used as sulfide ion source, zinc acetate as zinc ion source and manganese acetate as manganese ion source in alkaline bath at 90 °C. X-ray diffraction (XRD) analyses are carried out at room temperature on films and powders with a powder diffractometer, using CuKα radiation. The average grain size obtained from the Debye–Scherrer’s formula is around 10 nm. Films morphology is examined by scanning electron microscopy. IR spectra of representative sample are recorded with the FTIR between 400 and 4000 cm-1.The transmittance (70 %) is performed with the UV–VIS spectrometer in the wavelength range 200–800 nm. This value is enhanced by Al doping.

Keywords: ZnS, nanostructured semiconductors, thin films, chemical bath deposition

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Authors: Kwame Amoah

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Artificial intelligence (AI) has the prospect of transforming project management, significantly improving efficiency and accuracy. By automating specific tasks with defined guidelines, AI can assist project managers in making better decisions and allocating resources efficiently, with possible risk mitigation. This study explores how AI is already impacting project management and likely future AI's impact on the field. The AI's reaction has been a divided opinion; while others picture it as a destroyer of jobs, some welcome it as an innovation advocate. Both sides agree that AI will be disruptive and revolutionize PM's functions. If current research is to go by, AI or some form will replace one-third of all learning graduate PM jobs by as early as 2030. A recent survey indicates AI spending will reach $97.9 billion by the end of 2023. Considering such a profound impact, the project management profession will also see a paradigm shift driven by AI. The study examines what the project management profession will look like in the next 5-10 years after this technological disruption. The research methods incorporate existing literature, develop trend analysis, and conduct structured interviews with project management stakeholders from North America to gauge the trend. PM professionals can harness the power of AI, ensuring a smooth transition and positive outcomes. AI adoption will maximize benefits, minimize adverse consequences, and uphold ethical standards, leading to improved project performance.

Keywords: project management, disruptive teacnologies, project management function, AL applications, artificial intelligence

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Authors: Tian Zhang

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Unsupervised object segmentation aims at segmenting objects in sequential images and obtaining the mask of each object without any manual intervention. Unsupervised segmentation remains a challenging task due to the lack of prior knowledge about these objects. Previous methods often require manually specifying the action of each object, which is often difficult to obtain. Instead, this paper does not need action information of objects and automatically learns the actions and relations among objects from the structured environment. To obtain the object segmentation of sequential images, the relationships between objects and images are extracted to infer the action and interaction of objects based on the multi-head attention mechanism. Three types of objects’ relationships in the object segmentation task are proposed: the relationship between objects in the same frame, the relationship between objects in two frames, and the relationship between objects and historical information. Based on these relationships, the proposed model (1) is effective in multiple objects segmentation tasks, (2) just needs images as input, and (3) produces better segmentation results as more relationships are considered. The experimental results on multiple datasets show that this paper’s method achieves state-of-art performance. The quantitative and qualitative analyses of the result are conducted. The proposed method could be easily extended to other similar applications.

Keywords: unsupervised object segmentation, attention mechanism, contrastive learning, structured environment

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Authors: Su Chul Han, Seungwoo Park

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As the increasing incidence of cancer, the technology and modality of radiotherapy have advanced and the importance of preclinical model is increasing in the cancer research. Furthermore, the small animal dosimetry is an essential part of the evaluation of the relationship between the absorbed dose in preclinical small animal and biological effect in preclinical study. In this study, we carried out realistic modeling of the preclinical small animal phantom possible to verify irradiated dose using commercial software. The small animal phantom was modeling from 4D Digital Mouse whole body phantom. To manipulate Moby phantom in commercial software (Mimics, Materialise, Leuven, Belgium), we converted Moby phantom to DICOM image file of CT by Matlab and two- dimensional of CT images were converted to the three-dimensional image and it is possible to segment and crop CT image in Sagittal, Coronal and axial view). The CT images of small animals were modeling following process. Based on the profile line value, the thresholding was carried out to make a mask that was connection of all the regions of the equal threshold range. Using thresholding method, we segmented into three part (bone, body (tissue). lung), to separate neighboring pixels between lung and body (tissue), we used region growing function of Mimics software. We acquired 3D object by 3D calculation in the segmented images. The generated 3D object was smoothing by remeshing operation and smoothing operation factor was 0.4, iteration value was 5. The edge mode was selected to perform triangle reduction. The parameters were that tolerance (0.1mm), edge angle (15 degrees) and the number of iteration (5). The image processing 3D object file was converted to an STL file to output with 3D printer. We modified 3D small animal file using 3- Matic research (Materialise, Leuven, Belgium) to make space for radiation dosimetry chips. We acquired 3D object of realistic small animal phantom. The width of small animal phantom was 2.631 cm, thickness was 2.361 cm, and length was 10.817. Mimics software supported efficiency about 3D object generation and usability of conversion to STL file for user. The development of small preclinical animal phantom would increase reliability of verification of absorbed dose in small animal for preclinical study.

Keywords: mimics, preclinical small animal, segmentation, 3D printer

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Authors: Kwang Chun, John Kemeny

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Light detection and ranging (LiDAR) has been a prevalent remote-sensing technology applied in the geological fields due to its high precision and ease of use. One of the major applications is to use the detailed geometrical information of underground structures as a basis for the generation of a three-dimensional numerical model that can be used in a geotechnical stability analysis such as FEM or DEM. To date, however, straightforward techniques in reconstructing the numerical model from the scanned data of the underground structures have not been well established or tested. In this paper, we propose a comprehensive approach integrating all the various processes, from LiDAR scanning to finite element numerical analysis. The study focuses on converting LiDAR 3D point clouds of geologic structures containing complex surface geometries into a finite element model. This methodology has been applied to Kartchner Caverns in Arizona, where detailed underground and surface point clouds can be used for the analysis of underground stability. Numerical simulations were performed using the finite element code Abaqus and presented by 3D computing visualization solution, ParaView. The results are useful in studying the stability of all types of underground excavations including underground mining and tunneling.

Keywords: finite element analysis, LiDAR, remote-sensing, scientific visualization, underground stability

Procedia PDF Downloads 181