Search results for: laser applications

Authors: Richard, Iyan Subiyanto, Chairul Hudaya

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Activated carbon has been playing a significant role for many applications, especially in energy storage devices. However, commercially activated carbons generally require complicated processes and high production costs. Therefore, in this study, an activated carbon originating from green coke waste, that is economically affordable will be used as a carbon source. To synthesize activated carbon, KOH as an activator was employed with variation of C:KOH in ratio of 1:2, 1:3, 1:4, and 1:5, respectively, with an activation temperature of 700°C. The characterizations of activated carbon are obtained from Scanning Electron Microscopy, Energy Dispersive X-Ray, Raman Spectroscopy, and Brunauer-Emmett-Teller. The optimal activated carbon sample with specific surface area of 2,024 m²/g with high carbon content ( > 80%) supported by the high porosity carbon image obtained by SEM was prepared at C:KOH ratio of 1:4. The result shows that the synthesized activated carbon would be an ideal choice for energy storage device applications. Therefore, this study is expected to reduce the costs of activated carbon production by expanding the utilization of petroleum waste.

Keywords: activated carbon, energy storage material, green coke, specific surface area

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Authors: Roghaye Behroozi

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Traditional chemical synthesis methods for nanoparticles (NPs) often involve environmental hazards, complex procedures, and low yields. Green synthesis has emerged as a safer, cost-effective, and eco-friendly alternative. Citrus peel, an agricultural byproduct, provides a sustainable source of bioactive compounds capable of reducing and stabilizing metal ions, enabling the production of biocompatible NPs with valuable biomedical, photovoltaic, and environmental applications. This study aims to develop a green synthesis approach for producing metal oxide and silver nanoparticles (AgNPs) using citrus peel extracts, evaluating their antibacterial, antidiabetic, and photovoltaic properties. Nanoparticles were synthesized via aqueous citrus peel extracts, which served as natural reducing and capping agents. The synthesized NPs were characterized using techniques such as X-ray diffraction (XRD), scanning electron microscopy (SEM), and UV-Vis spectroscopy to confirm their crystalline structure, morphology, and stability. Antibacterial efficacy was tested against common pathogenic bacteria, while antidiabetic activity was assessed through in vitro α-amylase inhibition. Photovoltaic properties were evaluated by incorporating the NPs into dye-sensitized solar cells (DSSCs). The synthesized NPs demonstrated distinct crystalline phases and spherical morphology, with notable stability and size uniformity. AgNPs showed significant antibacterial activity against tested pathogens, with enhanced inhibition at higher concentrations. In α-amylase inhibition assays, both metal oxide and AgNPs displayed dose-dependent antidiabetic potential. The DSSCs exhibited promising photovoltaic efficiency, confirming the feasibility of these NPs in light energy applications. Citrus peel-mediated synthesis of metal oxide and AgNPs provides a green, scalable method for producing nanoparticles with multifaceted applications. The findings highlight the potential of these NPs as eco-friendly agents in antibacterial and antidiabetic therapies and as components in renewable energy devices. This approach not only utilizes agricultural waste but also aligns with sustainable development goals by reducing synthetic chemical usage and environmental impact.

Keywords: antibacterial activity, citrus peel extract, green synthesis, metal oxide nanoparticles, silver nanoparticles

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Authors: Bashar Mudhaffar Abdullah, Hasniza Zaman Huri, Nany Hairunisa

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This study was carried out to determine the thermal properties and spectroscopy study of Malaysian Jatropha curcas seed oil. The J. curcas seed oil physicochemical properties such as free fatty acid (FFA %), acid value, saponification value, iodine value, unsaponifiable matter, and viscosity (cp) gave values of 1.89±0.10%, 3.76±0.07, 203.36±0.36 mg/g, 4.90±0.25, 1.76±0.03%, and 32, respectively. Gas chromatography (GC) was used to determine the fatty acids (FAs) composition. J. curcas seed oil is consisting of saturated FAs (19.55%) such as palmitic (13.19%), palmitoleic (0.40%), and stearic (6.36%) acids and unsaturated FAs (80.42%) such as oleic (43.32%) and linoleic (36.70%) acids. The thermal properties using differential scanning calorimetry (DSC) showed that crystallized TAG was observed at -6.79°C. The melting curves displayed three major exothermic regions of J. curcas seed oil, monounsaturated (lower-temperature peak) at -31.69°C, di-unsaturated (medium temperature peak) at -20.23°C and tri-unsaturated (higher temperature peak) at -12.72°C. The results of this study showed that the J. curcas seed oil is a plausible source of polyunsaturated fatty acid (PUFA) to be developed in the future for pharmaceutical applications.

Keywords: Jatropha curcas seed oil, thermal properties, crystallization, melting, spectroscopy

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Authors: Jinan Fiaidhi, Sabah Mohammed

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Cross-domain learning in the medical field is a research challenge as many conditions, like in oncology imaging, use different imaging modalities. Moreover, in most of the medical learning applications, the sample training size is relatively small. Although few-shot learning (FSL) through the use of a Siamese neural network was able to be trained on a small sample with remarkable accuracy, FSL fails to be effective for use in multiple domains as their convolution weights are set for task-specific applications. In this paper, we are addressing this problem by enabling FSL to possess the ability to shift across domains by designing a two-layer FSL network that can learn individually from each domain and produce a shared features map with extra modulation to be used at the second layer that can recognize important targets from mix domains. Our initial experimentations based on mixed medical datasets like the Medical-MNIST reveal promising results. We aim to continue this research to perform full-scale analytics for testing our cross-domain FSL learning.

Keywords: Siamese neural network, few-shot learning, meta-learning, metric-based learning, thick data transformation and analytics

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Authors: Mikhail Zarechnev, Bora I. Kumova

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A syllogism is a deductive inference scheme used to derive a conclusion from a set of premises. In a categorical syllogisms, there are only two premises and every premise and conclusion is given in form of a quantified relationship between two objects. The different order of objects in premises give classification known as figures. We have shown that the ordered combinations of 3 generalized quantifiers with certain figure provide in total of 108 syllogistic moods which can be considered as different inference rules. The classical syllogistic system allows to model human thought and reasoning with syllogistic structures always attracted the attention of cognitive scientists. Since automated reasoning is considered as part of learning subsystem of AI agents, syllogistic system can be applied for this approach. Another application of syllogistic system is related to inference mechanisms on the Semantic Web applications. In this paper we proposed the mathematical model and algorithm for syllogistic reasoning. Also the model of iterative syllogistic reasoning in case of continuous flows of incoming data based on case–based reasoning and possible applications of proposed system were discussed.

Keywords: categorical syllogism, case-based reasoning, cognitive architecture, inference on the semantic web, syllogistic reasoning

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Authors: Feixiang Zhao, Shuangcheng Jia, Qian Li

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High-precision measurement of the target’s position and size is one of the hotspots in the field of vision inspection. This paper proposes a three-dimensional object positioning and measurement method using a monocular camera and GPS, namely the Distance Area Number-New Minimize Projection Error (DAN-NMPE). Our algorithm contains two parts: DAN and NMPE; specifically, DAN is a picture sequence algorithm, NMPE is a relatively positive optimization algorithm, which greatly improves the measurement accuracy of the target’s position and size. Comprehensive experiments validate the effectiveness of our proposed method on a self-made traffic sign dataset. The results show that with the laser point cloud as the ground truth, the size and position errors of the traffic sign measured by this method are ± 5% and 0.48 ± 0.3m, respectively. In addition, we also compared it with the current mainstream method, which uses a monocular camera to locate and measure traffic signs. DAN-NMPE attains significant improvements compared to existing state-of-the-art methods, which improves the measurement accuracy of size and position by 50% and 15.8%, respectively.

Keywords: monocular camera, GPS, positioning, measurement

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Authors: Virender Ranga, Mayank Dave, Anil Kumar Verma

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Recently wireless sensor networks (WSNs) are used in many real life applications like environmental monitoring, habitat monitoring, health monitoring etc. Due to power constraint cheaper devices used in these applications, the energy consumption of each device should be kept as low as possible such that network operates for longer period of time. One of the techniques to prolong the network lifetime is an intelligent grouping of sensor nodes such that they can perform their operation in cooperative and energy efficient manner. With this motivation, we propose a novel approach by organize the sensor nodes in cooperative multihop mini-groups so that the total global energy consumption of the network can be reduced and network lifetime can be improved. Our proposed approach also reduces the number of transmitted messages inside the WSNs, which further minimizes the energy consumption of the whole network. The experimental simulations show that our proposed approach outperforms over the state-of-the-art approach in terms of stability period and aggregated data.

Keywords: clustering, cluster-head, mini-group, stability period

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Authors: Rohaya Abdul Wahab, Raja Mohd Fuad Tengku Aziz, Nazaliza Othman, Sharifah Saleh, Nabihah Razali, Rozaimah Baharim, M. Hanif M. Nasir

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This paper will discuss how EDA tools are integrated and automated in an Integrated Circuit Design Environment. Some of the problems face in our current environment is that users need to configure manually on the library paths, start-up files and project directories. Certain manual processes that happen between the users and applications can be automated but they must be transparent to the users. For example, the users can run the applications directly after login without knowing the library paths and start-up files locations. The solution to these problems is to automate the processes using standard configuration files which will benefit the users and EDA support. This paper will discuss how the implementation is done to automate the process using scripting languages such as Perl, Tcl, Scheme and Shell Script. These scripting tools are great assets for design engineers to build a robust and powerful design flow and this technique is widely used to integrate all the tools together.

Keywords: EDA tools, Integrated Circuits, scripting, integration, automation

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Authors: Georgeta Voicu, Cristina Daniela Ghitulica, Andreia Cucuruz, Cristina Busuioc

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In the field of tissue engineering, the compositional and microstructural features of the employed materials play an important role, with implications on the mechanical and biological behaviour of the medical devices. In this context, the development of apatite - natural biopolymer composites represents a choice of many scientific groups. Thus, hydroxyapatite powders were synthesized by a wet method, namely co-precipitation, starting from high purity reagents (CaO, MgO, and H3PO4). Moreover, the substitution of calcium with magnesium have been approached, in the 5 - 10 wt.% range. Afterward, the phosphate powders were integrated in two types of composites with chitosan, different from morphological point of view. First, 3D porous scaffolds were obtained by a freeze-drying procedure. Second, uniform, compact films were achieved by film casting. The influence of chitosan molecular weight (low, medium and high), as well as apatite powder to polymer ratio (1:1 and 1:2) on the morphological properties, were analysed in detail. In conclusion, the reported biocomposites, prepared by a straightforward route are suitable for bone substitution or repairing applications.

Keywords: bone reconstruction, chitosan, composite scaffolds, hydroxyapatite

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Authors: Jiří Kubásek, Peter Minárik, Klára Hosová, Stanislav Šašek, Jozef Veselý, Jitka Stráská, Drahomír Dvorský, Dalibor Vojtěch, Miloš Janeček

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Mg-2Y-2Gd-1Ca and Mg-4Y-4Gd-2Ca alloys were processed by extrusion or equal channel angular pressing (ECAP) to analyse the effect of the microstructure on ignition temperature, mechanical properties and corrosion resistance. The alloys are characterized by good mechanical properties and exceptionally high ignition temperature, which is a critical safety measure. The effect of extrusion and ECAP on the microstructure, mechanical properties and ignition temperature was studied. The obtained results indicated a substantial effect of the processing conditions on the average grain size, the recrystallized fraction and texture formation. Both alloys featured a high strength, depending on the composition and processing condition, and a high ignition temperature of ≈1100 °C (Mg-4Y-4Gd-2Ca) and ≈950 °C (Mg-2Y-2Gd-1Ca), which was attributed to the synergic effect of Y, Gd and Ca oxides, with the dominant effect of Y₂O₃. The achieved combination of enhanced mechanical properties and the ignition temperature makes these alloys a prominent candidate for aircraft applications.

Keywords: magnesium alloys, enhanced ignition temperature, mechanical properties, ECAP

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Authors: Karim Sobh, Khaled El-Ayat, Fady Morcos, Amr El-Kadi

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Distributed applications deployed on LEO satellites and ground stations require substantial communication between different members in a constellation to overcome the earth coverage barriers imposed by GEOs. Applications running on LEO constellations suffer the earth line-of-sight blockage effect. They need adequate lab testing before launching to space. We propose a scalable cloud-based net-work simulation framework to simulate problems created by the earth line-of-sight blockage. The framework utilized cloud IaaS virtual machines to simulate LEO satellites and ground stations distributed software. A factorial ANOVA statistical analysis is conducted to measure simulator overhead on overall communication performance. The results showed a very low simulator communication overhead. Consequently, the simulation framework is proposed as a candidate for testing LEO constellations with distributed software in the lab before space launch.

Keywords: LEO, cloud computing, constellation, satellite, network simulation, netfilter

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Authors: Hamed Ouattara, Pierre Duthon, Frédéric Bernardin, Omar Ait Aider, Pascal Salmane

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In this article, we present three neural network architectures for real-time classification of weather conditions (sunny, rainy, snowy, foggy) from images. Inspired by recent advances in style transfer, two of these architectures -Truncated ResNet50 and Truncated ResNet50 with Gram Matrix and Attention- surpass the state of the art and demonstrate re-markable generalization capability on several public databases, including Kaggle (2000 images), Kaggle 850 images, MWI (1996 images) [1], and Image2Weather [2]. Although developed for weather detection, these architectures are also suitable for other appearance-based classification tasks, such as animal species recognition, texture classification, disease detection in medical images, and industrial defect identification. We illustrate these applications in the section “Applications of Our Models to Other Tasks” with the “SIIM-ISIC Melanoma Classification Challenge 2020” [3].

Keywords: weather simulation, weather measurement, weather classification, weather detection, style transfer, Pix2Pix, CycleGAN, CUT, neural style transfer

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Authors: Neeta Kumari, Gopal Pathak

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Artificial neural network has been proved to be an efficient tool for non-parametric modeling of data in various applications where output is non-linearly associated with input. It is a preferred tool for many predictive data mining applications because of its power , flexibility, and ease of use. A standard feed forward networks (FFN) is used to predict the groundwater fluoride content. The ANN model is trained using back propagated algorithm, Tansig and Logsig activation function having varying number of neurons. The models are evaluated on the basis of statistical performance criteria like Root Mean Squarred Error (RMSE) and Regression coefficient (R2), bias (mean error), Coefficient of variation (CV), Nash-Sutcliffe efficiency (NSE), and the index of agreement (IOA). The results of the study indicate that Artificial neural network (ANN) can be used for groundwater fluoride prediction in the limited data situation in the hard rock region like western parts of Jharkhand with sufficiently good accuracy.

Keywords: Artificial neural network (ANN), FFN (Feed-forward network), backpropagation algorithm, Levenberg-Marquardt algorithm, groundwater fluoride contamination

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Authors: Maram Shahad Dana Anfal

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This research paper presents the design of a surveillance drone with computer-aided durability and model analyses that provides a cost-effective and efficient solution for various applications. The quadcopter's design is based on a lightweight and strong structure made of materials such as aluminum and titanium, which provide a durable structure for the quadcopter. The structure of this product and the computer-aided durability system are both designed to ensure frequent repairs or replacements, which will save time and money in the long run. Moreover, the study discusses the drone's ability to track, investigate, and deliver objects more quickly than traditional methods, makes it a highly efficient and cost-effective technology. In this paper, a comprehensive analysis of the quadcopter's operation dynamics and limitations is presented. In both simulation and experimental data, the computer-aided durability system and the drone's design demonstrate their effectiveness, highlighting the potential for a variety of applications, such as search and rescue missions, infrastructure monitoring, and agricultural operations. Also, the findings provide insights into possible areas for improvement in the design and operation of the drone. Ultimately, this paper presents a reliable and cost-effective solution for surveillance applications by designing a drone with computer-aided durability and modeling. With its potential to save time and money, increase reliability, and enhance safety, it is a promising technology for the future of surveillance drones. operation dynamic equations have been evaluated successfully for different flight conditions of a quadcopter. Also, CAE modeling techniques have been applied for the modal risk assessment at operating conditions.Stress analysis have been performed under the loadings of the worst-case combined motion flight conditions.

Keywords: drone, material, solidwork, hypermesh

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Authors: Hanaa M. Abdelgawad, Mona Safar, Ayman M. Wahba

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Real-time image and video processing is a demand in many computer vision applications, e.g. video surveillance, traffic management and medical imaging. The processing of those video applications requires high computational power. Therefore, the optimal solution is the collaboration of CPU and hardware accelerators. In this paper, a Canny edge detection hardware accelerator is proposed. Canny edge detection is one of the common blocks in the pre-processing phase of image and video processing pipeline. Our presented approach targets offloading the Canny edge detection algorithm from processing system (PS) to programmable logic (PL) taking the advantage of High Level Synthesis (HLS) tool flow to accelerate the implementation on Zynq platform. The resulting implementation enables up to a 100x performance improvement through hardware acceleration. The CPU utilization drops down and the frame rate jumps to 60 fps of 1080p full HD input video stream.

Keywords: high level synthesis, canny edge detection, hardware accelerators, computer vision

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Authors: V. K. Banga

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Robots are now playing a very promising role in industries. Robots are commonly used in applications in repeated operations or where operation by human is either risky or not feasible. In most of the industrial applications, robotic arm manipulators are widely used. Robotic arm manipulator with two link or three link structures is commonly used due to their low degrees-of-freedom (DOF) movement. As the DOF of robotic arm increased, complexity increases. Instrumentation involved with robotics plays very important role in order to interact with outer environment. In this work, optimal control for movement of various DOFs of robotic arm using various soft computing techniques has been presented. We have discussed about different robotic structures having various DOF robotics arm movement. Further stress is on kinematics of the arm structures i.e. forward kinematics and inverse kinematics. Trajectory planning of robotic arms using soft computing techniques is demonstrating the flexibility of this technique. The performance is optimized for all possible input values and results in optimized movement as resultant output. In conclusion, soft computing has been playing very important role for achieving optimized movement of robotic arm. It also requires very limited knowledge of the system to implement soft computing techniques.

Keywords: artificial intelligence, kinematics, robotic arm, neural networks, fuzzy logic

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Authors: O. Mauroner, L. Le, S. Best

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Digital technologies offer many opportunities in the design and implementation of brand communication and advertising. Augmented reality (AR) is an innovative technology in marketing communication that focuses on the fact that virtual interaction with a product ad offers additional value to consumers. AR enables consumers to obtain (almost) real product experiences by the way of virtual information even before the purchase of a certain product. Aim of AR applications in relation with advertising is in-depth examination of product characteristics to enhance product knowledge as well as brand knowledge. Interactive design of advertising provides observers with an intense examination of a specific advertising message and therefore leads to better brand knowledge. The elaboration likelihood model and the central route to persuasion strongly support this argumentation. Nevertheless, AR in brand communication is still in an initial stage and therefore scientific findings about the impact of AR on information processing and brand attitude are rare. The aim of this paper is to empirically investigate the potential of AR applications in combination with traditional print advertising. To that effect an experimental design with different levels of interactivity is built to measure the impact of interactivity of an ad on different variables o advertising effectiveness.

Keywords: advertising effectiveness, augmented reality, brand communication, brand recall

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Authors: Sandesh Achar

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Artificial intelligence is being increasingly incorporated into many applications across various sectors such as health, education, security, and agriculture. Recently, there has been rapid development in cloud computing technology, resulting in AI’s implementation into cloud computing to enhance and optimize the technology service rendered. The deployment of AI in cloud-based applications has brought about autonomous computing, whereby systems achieve stated results without human intervention. Despite the amount of research into autonomous computing, work incorporating AI/ML into cloud computing to enhance its performance and resource allocation remain a fundamental challenge. This paper highlights different manifestations, roles, trends, and challenges related to AI-based cloud computing models. This work reviews and highlights excellent investigations and progress in the domain. Future directions are suggested for leveraging AI/ML in next-generation computing for emerging computing paradigms such as cloud environments. Adopting AI-based algorithms and techniques to increase operational efficiency, cost savings, automation, reducing energy consumption and solving complex cloud computing issues are the major findings outlined in this paper.

Keywords: artificial intelligence, cloud computing, deep learning, machine learning, internet of things

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Authors: Asteria Nsamba

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Social networking applications and tools have become compelling platforms for generating and sharing knowledge across the world. Social networking applications and tools refer to a variety of social media platforms which include Facebook, Twitter WhatsApp, blogs and Wikis. The most popular of these platforms are Facebook, with 2.41 billion active users on a monthly basis, followed by WhatsApp with 1.6 billion users and Twitter with 330 million users. These communication platforms have not only impacted social lives but have also impacted students’ learning, across different delivery modes in higher education: distance, conventional and blended learning modes. With this amount of interest in these platforms, knowledge sharing has gained importance within the context in which it is required. In open distance learning (ODL) contexts, social networking platforms can offer students and teachers the platform on which to create and share knowledge, and form learning collaborations. Thus, they can serve as support mechanisms to increase interactions and reduce isolation and loneliness inherent in ODL. Despite this potential and opportunity, research indicates that many ODL teachers are not inclined to using social media tools in learning. Although it is unclear why these tools are uncommon in these environments, concerns raised in the literature have indicated that many teachers have not mastered the art of teaching with technology. Using technological, pedagogical content knowledge (TPCK) and product quality theory, and Bloom’s Taxonomy as lenses, this paper is aimed at; firstly, assessing the quality of three social media applications: Facebook, Twitter and WhatsApp, in order to determine the extent to which they are suitable platforms for teaching and learning, in terms of content generation, information sharing and learning collaborations. Secondly, the paper demonstrates the application of teaching, learning and assessment using Bloom’s Taxonomy.

Keywords: distance education, quality, social networking tools, TPACK

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Authors: Alireza Rafieerad, Bushroa Abd Razak, Bahman Nasiri Tabrizi, Jamunarani Vadivelu

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Recently, reports on the fabrication of nanotubular arrays have generated considerable scientific interest, owing to the broad range of applications of the oxide nanotubes in solar cells, orthopedic and dental implants, photocatalytic devices as well as lithium-ion batteries. A more attractive approach for the fabrication of oxide nanotubes with controllable morphology is the electrochemical anodization of substrate in a fluoride-containing electrolyte. Consequently, titanium dioxide nanotubes (TiO2 NTs) have been highly considered as an applicable material particularly in the district of artificial implants. In addition, regarding long-term efficacy and reasons of failing and infection after surgery of currently used dental implants required to enhance the cytocompatibility properties of Ti-based bone-like tissue. As well, graphene oxide (GO) with relevant biocompatibility features in tissue sites, osseointegration and drug delivery functionalization was fully understood. Besides, the boasting antibacterial ability of silver (Ag) remarkably provided for implantable devices without infection symptoms. Here, surface modification of Ti–6Al–7Nb implants (Ti67IMP) by the development of Ag/GO co-decorated TiO2 NTs was examined. Initially, the anodic TiO2 nanotubes obtained at a constant potential of 60 V were annealed at 600 degree centigrade for 2 h to improve the adhesion of the coating. Afterward, the Ag/GO co-decorated TiO2 NTs were developed by spin coating on Ti67IM. The microstructural features, phase composition and wettability behavior of the nanostructured coating were characterized comparably. In a nutshell, the results of the present study may contribute to the development of the nanostructured Ti67IMP with improved surface properties.

Keywords: anodic tio2 nanotube, biomedical applications, graphene oxide, silver, spin coating

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Authors: Kadir Özsoy

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Creating a moderately competitive learning environment is believed to have positive effects on student interest and motivation. The best way today to attract young learners to get involved in a fun, competitive learning experience is possible through mobile applications as these learners mostly rely on games and applications on their phones and tablets to have fun, communicate, look for information and study. In this study, a mobile application called ‘QuizUp’ is used to create a specific game topic for elementary level students at Anadolu University Preparatory School. The topic is specially designed with weekly-added questions in accordance with the course syllabus. Students challenge their classmates or randomly chosen opponents to answer questions related to their course subjects. They also chat and post on the topic’s wall in English. The study aims at finding out students’ perceptions towards the use of the application as a classroom and extra-curricular activity through a survey. The study concludes that educational games boost students’ motivation, lead to increased effort, and positively change their studying habits.

Keywords: competitive learning, educational application, effort, motivation 'QuizUp', study habits

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Authors: Sourav Sarkar, Manashjit Gogoi

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In the evolving landscape of cancer diagnostics, optical biosensing has emerged as a promising tool due to its sensitivity and specificity. This study explores the potential of CdS/ZnS core-shell quantum dots (QDs) capped with 3-Mercaptopropionic acid (3-MPA), which aids in the linking chemistry of QDs to various cancer antibodies. The QDs, with their unique optical and electronic properties, have been integrated into the biosensor design. Their high quantum yield and size-dependent emission spectra have been exploited to improve the sensor’s detection capabilities. The study presents the design of this QD-enhanced optical biosensor. The use of these QDs can also aid multiplexed detection, enabling simultaneous monitoring of different cancer biomarkers. This innovative approach holds significant potential for advancing cancer diagnostics, contributing to timely and accurate detection. Future work will focus on optimizing the biosensor design for clinical applications and exploring the potential of QDs in other biosensing applications. This study underscores the potential of integrating nanotechnology and biosensing for cancer research, paving the way for next-generation diagnostic tools. It is a step forward in our quest for achieving precision oncology.

Keywords: quantum dots, biosensing, cancer, device

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Authors: Marek Maruszczak

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Gamified applications have been used successfully in education for years. The rapid development of technologies such as augmented reality and image recognition increases their availability and reduces their prices. Thus, there is an increasing possibility and need for a wide use of such applications in education. The main purpose of this article is to present the effects of work on a mobile application with augmented reality, the aim of which is to motivate tourists to pay more attention to the attractions and increase the likelihood of moving from one attraction to the next while visiting the Palácio Nacional de Sintra in Portugal. Work on the application was carried out together with the employees of Parques de Sintra from 2019 to 2021. Their effect was the preparation of a mobile application using augmented reality and image recognition. The application was tested on the palace premises by both Parques de Sintra employees and tourists visiting Palácio Nacional de Sintra. The collected conclusions allowed for the formulation of good practices and guidelines that can be used when designing gamified apps for the purpose of cultural education.

Keywords: augmented reality, cultural education, gamification, image recognition, mobile games

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Authors: Abdullah Eqal Al Mazrooei

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In this paper, a nonlinear dynamical system is presented. This system is a bilinear class. The bilinear systems are very important kind of nonlinear systems because they have many applications in real life. They are used in biology, chemistry, manufacturing, engineering, and economics where linear models are ineffective or inadequate. They have also been recently used to analyze and forecast weather conditions. Bilinear systems have three advantages: First, they define many problems which have a great applied importance. Second, they give us approximations to nonlinear systems. Thirdly, they have a rich geometric and algebraic structures, which promises to be a fruitful field of research for scientists and applications. The type of nonlinearity that is treated and analyzed consists of bilinear interaction between the states vectors and the system input. By using some properties of the tensor product, these systems can be transformed to linear systems. But, here we discuss the nonlinearity when the state vector is multiplied by itself. So, this model will be able to handle evolutions according to the Lotka-Volterra models or the Lorenz weather models, thus enabling a wider and more flexible application of such models. Here we apply by using an estimator to estimate temperatures. The results prove the efficiency of the proposed system.

Keywords: Lorenz models, nonlinear systems, nonlinear estimator, state-space model

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Authors: M. G. Ghanem, A. M. M. A. Allam, Diaa E. Fawzy, Mehmet Faruk Cengiz

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This paper is devoted to the design and implementation of a smartwatch textile antenna for Wi-Fi bio-medical applications in millimetric wave bands. The antenna is implemented on a leather textile-based substrate to be embedded in a smartwatch. It enables the watch to pick Wi-Fi signals without the need to be connected to a mobile through Bluetooth. It operates at 60 GHz or WiGig (Wireless Gigabit Alliance) band with a wide band for higher rate applications. It also could be implemented over many stratified layers of the body organisms to be used in the diagnosis of many diseases like diabetes and cancer. The structure is designed and simulated using CST (Studio Suite) program. The wearable patch antenna has an octagon shape, and it is implemented on leather material that acts as a flexible substrate with a size of 5.632 x 6.4 x 2 mm3, a relative permittivity of 2.95, and a loss tangent of 0.006. The feeding is carried out using differential feed (discrete port in CST). The work provides five antenna implementations; antenna without ground, a ground is added at the back of the antenna in order to increase the antenna gain, the substrate dimensions are increased to 15 x 30 mm2 to resemble the real hand watch size, layers of skin and fat are added under the ground of the antenna to study the effect of human body tissues human on the antenna performance. Finally, the whole structure is bent. It is found that the antenna can achieve a simulated peak realized gain in dB of 5.68, 7.28, 6.15, 3.03, and 4.37 for antenna without ground, antenna with the ground, antenna with larger substrate dimensions, antenna with skin and fat, and bent structure, respectively. The antenna with ground exhibits high gain; while adding the human organisms absorption, the gain is degraded because of human absorption. The bent structure contributes to higher gain.

Keywords: bio medical engineering, millimetric wave, smart watch, textile antennas, Wi-Fi

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Authors: B. Kahouadji, L. Guerbous, L. Lamiri, A. Mendoud

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Recently, nanomaterials are developed in the form of nano-films, nano-crystals and nano-pores. Lanthanide phosphates as a material find extensive application as laser, ceramic, sensor, phosphor, and also in optoelectronics, medical and biological labels, solar cells and light sources. Among the different kinds of rare-earth orthophosphates, yttrium orthophosphate has been shown to be an efficient host lattice for rare earth activator ions, which have become a research focus because of their important role in the field of light display systems, lasers, and optoelectronic devices. It is in this context that the 4fn- « 4fn-1 5d transitions of rare earth in insulating materials, lying in the UV and VUV, are the aim of large number of studies .Though there has been a few reports on Eu3+, Nd3+, Pr3+,Er3+, Ce3+, Tm3+ doped YPO4. The 4fn- « 4fn-1 5d transitions of the rare earth dependent to the host-matrix, several matrices ions were used to study these transitions, in this work we are suggesting to study on a very specific class of inorganic material that are orthophosphate doped with rare earth ions. This study focused on the effect of Ce3+ concentration on the structural and optical properties of Ce3+ doped YPO4 yttrium orthophosphate with powder form prepared by the Sol Gel method.

Keywords: YPO4, Ce3+, 4fn- <->4fn-1 5d transitions, scintillator

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Authors: Ebere Ellison Obisike, Justina N. Adalikwu-Obisike

Abstract:

Artificial intelligence (AI) is progressively transforming health and social care. With the rapid invention of various electronic devices, machine learning, and computing systems, the use of AI istraversing many health and social care practices. In this systematic review of journal and grey literature, this study explores how the applications of AI might promote the prevention of micro and macrovascular complications in type 1 diabetic patients. This review focuses on the use of a digitized blood glucose meter and the application of insulin pumps for the effective management of type 1 diabetes in low and middle-income countries. It is projected that the applications of AI may assist individuals with type 1 diabetes to monitor and control their blood glucose level and prevent the early onset of micro and macrovascular complications.

Keywords: artificial intelligence, blood glucose meter, insulin pump, low and middle-income countries, micro and macrovascular complications, type 1 diabetes

Procedia PDF Downloads 200

Authors: Yaowei Hu, Yongkai Wu, Lu Zhang, Xintao Wu

Abstract:

Causal inference from observational data is receiving wide applications in many fields. However, unidentifiable situations, where causal effects cannot be uniquely computed from observational data, pose critical barriers to applying causal inference to complicated real applications. In this paper, we develop a bounding method for estimating the average causal effect (ACE) under unidentifiable situations due to hidden confounders. We propose to parameterize the unknown exogenous random variables and structural equations of a causal model using neural networks and implicit generative models. Then, with an adversarial learning framework, we search the parameter space to explicitly traverse causal models that agree with the given observational distribution and find those that minimize or maximize the ACE to obtain its lower and upper bounds. The proposed method does not make any assumption about the data generating process and the type of the variables. Experiments using both synthetic and real-world datasets show the effectiveness of the method.

Keywords: average causal effect, hidden confounding, bound estimation, generative adversarial learning

Procedia PDF Downloads 194

Authors: Fethi Soltani, Adel Almarashi, Idir Mechai

Abstract:

Tikhonov regularization and reproducing kernels are the most popular approaches to solve ill-posed problems in computational mathematics and applications. And the Fourier multiplier operators are an essential tool to extend some known linear transforms in Euclidean Fourier analysis, as: Weierstrass transform, Poisson integral, Hilbert transform, Riesz transforms, Bochner-Riesz mean operators, partial Fourier integral, Riesz potential, Bessel potential, etc. Using the theory of reproducing kernels, we construct a simple and efficient representations for some class of Fourier multiplier operators Tm on the Paley-Wiener space Hh. In addition, we give an error estimate formula for the approximation and obtain some convergence results as the parameters and the independent variables approaches zero. Furthermore, using numerical quadrature integration rules to compute single and multiple integrals, we give numerical examples and we write explicitly the extremal function and the corresponding Fourier multiplier operators.

Keywords: fourier multiplier operators, Gauss-Kronrod method of integration, Paley-Wiener space, Tikhonov regularization

Procedia PDF Downloads 319

Authors: Ashwani Kumar Aggarwal

Abstract:

NIR Light is non-ionizing and can pass easily through living tissues such as breast without any harmful effects. Therefore, use of NIR light for imaging the biological tissue and to quantify its optical properties is a good choice over other invasive methods. Optical tomography involves two steps. One is the forward problem and the other is the reconstruction problem. The forward problem consists of finding the measurements of transmitted light through the tissue from source to detector, given the spatial distribution of absorption and scattering properties. The second step is the reconstruction problem. In X-ray tomography, there is standard method for reconstruction called filtered back projection method or the algebraic reconstruction methods. But this method cannot be applied as such, in optical tomography due to highly scattering nature of biological tissue. A hybrid algorithm for reconstruction has been implemented in this work which takes into account the highly scattered path taken by photons while back projecting the forward data obtained during Monte Carlo simulation. The reconstructed image suffers from blurring due to point spread function. This blurred reconstructed image has been enhanced using a digital filter which is optimal in mean square sense.

Keywords: least-squares optimization, filtering, tomography, laser interaction, light scattering

Procedia PDF Downloads 316