Search results for: responsive architecture

Authors: Bruk Gebregziabher

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

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

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Authors: Samina Khalid, Tehmina Khalil, Smeea Arshad

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Knowledge management is essential ingredient of successful coordination in globally distributed software engineering. Various frameworks, KMSs, and tools have been proposed to foster coordination and communication between virtual teams but practical implementation of these solutions has not been found. Organizations have to face challenges to implement knowledge management system. For this purpose at first, a literature review is arranged to investigate about challenges that restrict organizations to implement KMS and then by taking in account these challenges a problem of need of integrated solution in the form of standardized KMS that can easily store tacit and explicit knowledge, has traced down to facilitate coordination and collaboration among virtual teams. Literature review has been already shown that knowledge is a complex perception with profound meanings, and one of the most important resources that contributes to the competitive advantage of an organization. In order to meet the different challenges caused by not properly managing knowledge related to projects among virtual teams in GSE, we suggest making use of the cloud computing model. In this research a distributed architecture to support KM storage is proposed called conceptual framework of KM as a service in cloud. Framework presented is enhanced and conceptual framework of KM is embedded into that framework to store projects related knowledge for future use.

Keywords: management, Globsl software development, global software engineering

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Authors: Haile Berihulay, Chenglong Luo

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Avian influenza, commonly known as bird flu, is a highly contagious viral disease primarily affecting poultry and wild birds, with significant implications for both animal health and public safety. The influenza virus (IV) is notorious for its ability to mutate and infect multiple species, including humans, leading to severe consequences. Avian influenza poses considerable pandemic risks due to the potential evolution of low pathogenic avian influenza (LPAI) into highly pathogenic avian influenza (HPAI), which can cause rapid outbreaks in domestic flocks. While AVI viruses typically do not replicate well in humans, strains such as H5N1 and H7N9 have crossed the species barrier, raising alarm over human infections. The recent documentation of human transmission of the H5N8 strain from birds underscores the ongoing threat posed by avian influenza. This review necessitates a thorough discussion about the genetic foundation of viral pathogens, identifying key candidate genes linked to disease resilience, and discussing powerful tools. This review can help researchers to comprehensively overview the disease severity and combat related to AIV, which causes significant economic impact and set effective control strategies to mitigate the risks associated with avian influenza outbreaks.

Keywords: Avian, candidate genes, chicken, molecular, pathogen, virus

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Authors: Sofiane Bendoukha, Daniel Moldt, Hayat Bendoukha

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Workflow concepts are essential for the development of remote sensing applications. They can help users to manage and process satellite data and execute scientific experiments on distributed resources. The objective of this paper is to introduce an approach for the specification and the execution of complex scientific workflows in Cloud-like environments. The approach strives to support scientists during the modeling, the deployment and the monitoring of their workflows. This work takes advantage from Petri nets and more pointedly the so-called reference nets formalism, which provides a robust modeling/implementation technique. RENEWGRASS is a tool that we implemented and integrated into the Petri nets editor and simulator RENEW. It provides an easy way to support not experienced scientists during the specification of their workflows. It allows both modeling and enactment of image processing workflows from the remote sensing domain. Our case study is related to the implementation of vegetation indecies. We have implemented the Normalized Differences Vegetation Index (NDVI) workflow. Additionally, we explore the integration possibilities of the Cloud technology as a supplementary layer for the deployment of the current implementation. For this purpose, we discuss migration patterns of data and applications and propose an architecture.

Keywords: cloud computing, scientific workflows, petri nets, RENEWGRASS

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Authors: Pimploi Tirastittam, Phutthiwat Waiyawuththanapoom, Manop Tirastittam

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Traceability system is one of the tools which can ensure the product’s confident of the consumer as it can trace the product back to its origin and can reduce the operation cost of recall. Nowadays, there are so many technologies which can be applied to the traceability system and also able to increase the efficiency of the system such as QR Code, barcode, GS1 and GTIN. As the result, this research is aimed to study and design the information technology pattern that suits for the traceability of Thailand’s orchid because Thailand’s orchid is the popular export product for Japan, USA, China, Netherlands and Italy. This study will enhance the value of Thailand’s orchid and able to prevent the unexpected event of the defects or damaged product. The traceability pattern was received IOC test from 12 experts from 4 fields of study which are traceability field, information technology field, information communication technology field and orchid export field. The result of the in-depth interview and questionnaire showed that the technology which most compatibility with the traceability system is the QR code. The mean of the score was 4.25 and the standard deviation was 0.5 as the QR code is the new technology and user-friendly. The traceability system should start from the farm to the consumer in the consuming country as the traceability system will enhance the quality level of the product and increase the value of its as well. The other outcome from this research is the supply chain model of Thailand’s Orchid along with the system architecture and working system diagram.

Keywords: exporting, information technology pattern, orchid, traceability

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Authors: Mithil Pandey, Ragunathan Bala Subramanian

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One of the major conversion technologies in the oil refinery industry is Fluid catalytic cracking (FCC) which produces the majority of the world’s gasoline. Some useful products are generated from the vacuum gas oil, heavy gas oil and residue feedstocks by the FCC unit in an oil refinery. Moreover, Zeolite catalysts (zeo-catalysts) have found widespread applications and have proved to be substantial and paradigmatic in oil refining and petrochemical processes, such as FCC because of their porous features. Several famous zeo-catalysts have been fabricated and applied in industrial processes as milestones in history, and have brought on huge changes in petrochemicals. So far, more than twenty types of zeolites have been industrially applied, and their versatile porous architectures with their essential features have contributed to affect the catalytic efficiency. This poster depicts the evolution of pore models in zeolite catalysts which are accompanied by an increase in environmental and demands. The crucial roles of modulating pore models are outlined for zeo-catalysts for the enhancement of their catalytic performances in various industrial processes. The development of industrial processes for the FCC process, aromatic conversions and olefin production, makes it obvious that the pore architecture plays a very important role in zeo-catalysis processes. By looking at the different necessities of industrial processes, rational construction of the pore model is critically essential. Besides, the pore structure of the zeolite would have a substantial and direct effect on the utilization efficiency of the zeo-catalyst.

Keywords: catalysts, fluid catalytic cracking, industrial processes, zeolite

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Authors: Subhra Prosun Paul, Shruti Aggarwal

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Now a days Routing Protocol in Wireless Sensor Network has become a promising technique in the different fields of the latest computer technology. Routing in Wireless Sensor Network is a demanding task due to the different design issues of all sensor nodes. Network architecture, no of nodes, traffic of routing, the capacity of each sensor node, network consistency, service value are the important factor for the design and analysis of Routing Protocol in Wireless Sensor Network. Additionally, internal energy, the distance between nodes, the load of sensor nodes play a significant role in the efficient routing protocol. In this paper, our intention is to analyze the research trends in different routing protocols of Wireless Sensor Network in terms of different parameters. In order to explain the research trends on Routing Protocol in Wireless Sensor Network, different data related to this research topic are analyzed with the help of Web of Science and Scopus databases. The data analysis is performed from global perspective-taking different parameters like author, source, document, country, organization, keyword, year, and a number of the publication. Different types of experiments are also performed, which help us to evaluate the recent research tendency in the Routing Protocol of Wireless Sensor Network. In order to do this, we have used Web of Science and Scopus databases separately for data analysis. We have observed that there has been a tremendous development of research on this topic in the last few years as it has become a very popular topic day by day.

Keywords: analysis, routing protocol, research trends, wireless sensor network

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Authors: Husain S. Yawer, Vasim Raja Panwar, Nidhi Priya

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The objective of this study is to evaluate and compare the role of nano-gelatin and Bioengineered Scaffolds on the attachment, proliferation, and osteogenic differentiation of human dental pulp stem cells (DPSCs). Tooth decay and early fall have each been one of the most prevailing dental disorders which cause physical and emotional suffering and compromise the patient's quality of life. The design of novel scaffolding materials will be based on mimicking the architecture of natural dental extracellular matrix which may provide as in vivo environments for proper cell growth. This methodology will involve the combination of nano-fibred gelatin as well as biodegradable hydrogel based tooth scaffold. We have measured and optimized the Dental Pulp Stem Cells growth profile in cultures carried out on collagen-coated plastic surface, however, for tissue regeneration study, we aim to develop an enhanced microenvironment for stem cell growth and dental tissue regeneration. We believe biomimetic cell adhesion and scaffolds might provide a near in vivo growth environment for proper growth and differentiation of human DPSCs, which further help in dentin/pulp tissue regeneration.

Keywords: nano-gelatin, stem cells, dental pulp, scaffold

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Authors: Seungwoo Kim, Yeongcheol Cho

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In this paper, a holonomic mobile robot is designed in omnidirectional wheels and an adaptive fuzzy controller is presented for its precise trajectories. A kind of adaptive controller based on fuzzy multi-layered algorithm is used to solve the big parametric uncertainty of motor-controlled dynamic system of 3-wheels omnidirectional mobile robot. The system parameters such as a tracking force are so time-varying due to the kinematic structure of omnidirectional wheels. The fuzzy adaptive control method is able to solve the problems of classical adaptive controller and conventional fuzzy adaptive controllers. The basic idea of new adaptive control scheme is that an adaptive controller can be constructed with parallel combination of robust controllers. This new adaptive controller uses a fuzzy multi-layered architecture which has several independent fuzzy controllers in parallel, each with different robust stability area. Out of several independent fuzzy controllers, the most suited one is selected by a system identifier which observes variations in the controlled system parameter. This paper proposes a design procedure which can be carried out mathematically and systematically from the model of a controlled system. Finally, the good performance of a holonomic mobile robot is confirmed through live tests of the tracking control task.

Keywords: fuzzy adaptive control, fuzzy multi-layered controller, holonomic mobile robot, omnidirectional wheels, robustness and stability.

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Authors: Tareq AlNuaim, Mubashir Alam, Abdulrazaq Aldowesh

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The usage of micro-Unmanned Ariel Vehicles (UAVs) has witnessed an enormous increase recently. Detection of such drones became a necessity nowadays to prevent any harmful activities. Typically, such targets have low velocity and low Radar Cross Section (RCS), making them indistinguishable from clutter and phase noise. Multiple-Input Multiple-Output (MIMO) Radars have many potentials; it increases the degrees of freedom on both transmit and receive ends. Such architecture allows for flexibility in operation, through utilizing the direct access to every element in the transmit/ receive array. MIMO systems allow for several array processing techniques, permitting the system to stare at targets for longer times, which improves the Doppler resolution. In this paper, a 2×2 MIMO radar prototype is developed using Software Defined Radio (SDR) technology, and its performance is evaluated against a slow-moving low radar cross section micro-UAV used by hobbyists. Radar cross section simulations were carried out using FEKO simulator, achieving an average of -14.42 dBsm at S-band. The developed prototype was experimentally evaluated achieving more than 300 meters of detection range for a DJI Mavic pro-drone

Keywords: digital beamforming, drone detection, micro-UAV, MIMO, phased array

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Authors: Hang Yang, Jiahao Liu, Jichao Li, Kewei Yang, Minghao Li, Bingfeng Ge

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The system-of-systems (SoS) are utilized to characterize networks formed by integrating individual complex systems that demonstrate interdependence and interconnectedness. Research on the disintegration issue in SoS is significant in improving network survivability, maintaining network security, and optimizing SoS architecture. Accordingly, this study proposes an integrated framework called resilience-oriented disintegration in SoS (SoSRD), for modeling and solving the issue of SoS disintegration. Firstly, a SoS disintegration index (SoSDI) is presented to evaluate the disintegration effect of SoS. This index provides a practical description of the disintegration process and is the first integration of the network disintegration model and resilience models. Subsequently, we propose a resilience-oriented disintegration method based on reinforcement learning (RDRL) to enhance the efficiency of SoS disintegration. This method is not restricted by the problem scenario as well as considering the coexistence of disintegration (node/link removal) and recovery (node/link addition) during the process of SoS disintegration. Finally, the effectiveness and superiority of the proposed SoSRD are demonstrated through a case study. We demonstrate that our proposed framework outperforms existing indexes and methods in both node and link disintegration scenarios, providing a fresh perspective on network disintegration. The findings provide crucial insights into dismantling harmful SoS and designing a more resilient SoS.

Keywords: system-of-systems, disintegration index, resilience, reinforcement learning

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Authors: Pinhas Dannon, Aviv Weinstein

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Impulsivity is raising major interest clinically because it is associated with various clinical conditions such as delinquency, antisocial behavior, suicide attempts, aggression, and criminal activity. The evolutionary perspective argued that impulsivity relates to self-regulation and it has predicted that female individuals should have evolved a greater ability to inhibit pre-potent responses. There is supportive evidence showing that female individuals have better performance on cognitive tasks measuring impulsivity such as delay in gratification and delayed discounting mainly in childhood. During adolescence, brain imaging studies using diffusion tensor imaging on white matter architecture indicated contrary to the evolutionary perspective hypothesis, that young adolescent male individuals may be less vulnerable than age-matched female individuals to risk- and reward- related maladaptive behaviors. In adults, the results are mixed presumably owing to hormonal effects on neuro-biological mechanisms of reward. Consequently, female individuals were less impulsive than male individuals only during fertile stages of the menstrual cycle. Finally, there is evidence the serotonin (5-HT) system is more involved in the impulsivity of men than in that of women. Overall, there seem to be sex differences in impulsivity but these differences are more pronounced in childhood and they are later subject to maturational and hormonal changes during adolescence and adulthood and their effects on the brain, cognition, and behavior.

Keywords: impulse control, male population, female population, gender differences, reward, neurocognitive tests

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Authors: Jiaqi Dong, Qing-Hua Qin, Yi Xiao

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Some of the most fundamental challenges of elastic metamaterials (EMMs) optimization can be attributed to the high consumption of computational power resulted from finite element analysis (FEA) simulations that render the optimization process inefficient. Furthermore, due to the inherent mesh dependence of FEA, minuscule geometry features, which often emerge during the later stages of optimization, induce very fine elements, resulting in enormously high time consumption, particularly when repetitive solutions are needed for computing the objective function. In this study, a surrogate modelling algorithm is developed to reduce computational time in structural optimization of EMMs. The surrogate model is constructed based on a multilayer feedforward artificial neural network (ANN) architecture, trained with prepopulated eigenfrequency data prepopulated from FEA simulation and optimized through regime selection with genetic algorithm (GA) to improve its accuracy in predicting the location and width of the primary elastic band gap. With the optimized ANN surrogate at the core, a Nelder-Mead (NM) algorithm is established and its performance inspected in comparison to the FEA solution. The ANNNM model shows remarkable accuracy in predicting the band gap width and a reduction of time consumption by 47%.

Keywords: artificial neural network, machine learning, mechanical metamaterials, Nelder-Mead optimization

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Authors: Fatima Zohra Rahou, A.Guen Bouazza, B. Bouazza

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SOI TRI GATE FinFET transistors have emerged as novel devices due to its simple architecture and better performance: better control over short channel effects (SCEs) and reduced power dissipation due to reduced gate leakage currents. As the oxide thickness scales below 2 nm, leakage currents due to tunneling increase drastically, leading to high power consumption and reduced device reliability. Replacing the SiO2 gate oxide with a high-κ material allows increased gate capacitance without the associated leakage effects. In this paper, SOI TRI-GATE FinFET structure with use of high K dielectric materials (HfO2) and SiO2 dielectric are simulated using the 3-D device simulator Devedit and Atlas of TCAD Silvaco. The simulated results exhibits significant improvements in the performances of SOI TRI GATE FinFET with gate oxide HfO2 compared with conventional gate oxide SiO2 for the same structure. SOI TRI-GATE FinFET structure with the use of high K materials (HfO2) in gate oxide results into the increase in saturation current, threshold voltage, on-state current and Ion/Ioff ratio while off-state current, subthreshold slope and DIBL effect are decreased.

Keywords: technology SOI, short-channel effects (SCEs), multi-gate SOI MOSFET, SOI-TRI Gate FinFET, high-K dielectric, Silvaco software

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Authors: Alena Cejkova, Martina Paldrychova, Jana Michailidu, Olga Matatkova, Jan Masak

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Increasing the resistance of pathogenic microorganisms to many antibiotics is a serious threat to the treatment of infectious diseases and cleaning medical instruments. It should be added that the resistance of microbial populations growing in biofilms is often up to 1000 times higher compared to planktonic cells. Biofilm formation in a number of microorganisms is largely influenced by the quorum sensing regulatory mechanism. Finding external factors such as natural substances or physical processes that can interfere effectively with quorum sensing signal molecules should reduce the ability of the cell population to form biofilm and increase the effectiveness of antibiotics. The present work is devoted to the effect of chitosan as a representative of natural substances with anti-biofilm activity and non- thermal plasma (NTP) alone or in combination with polymyxin B on biofilm formation of Pseudomonas aeruginosa. Particular attention was paid to the influence of these agents on the level of quorum sensing signal molecules (acyl-homoserine lactones) during planktonic and biofilm cultivations. Opportunistic pathogenic strains of Pseudomonas aeruginosa (DBM 3081, DBM 3777, ATCC 10145, ATCC 15442) were used as model microorganisms. Cultivations of planktonic and biofilm populations in 96-well microtiter plates on horizontal shaker were used for determination of antibiotic and anti-biofilm activity of chitosan and polymyxin B. Biofilm-growing cells on titanium alloy, which is used for preparation of joint replacement, were exposed to non-thermal plasma generated by cometary corona with a metallic grid for 15 and 30 minutes. Cultivation followed in fresh LB medium with or without chitosan or polymyxin B for next 24 h. Biofilms were quantified by crystal violet assay. Metabolic activity of the cells in biofilm was measured using MTT (3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide) colorimetric test based on the reduction of MTT into formazan by the dehydrogenase system of living cells. Activity of N-acyl homoserine lactones (AHLs) compounds involved in the regulation of biofilm formation was determined using Agrobacterium tumefaciens strain harboring a traG::lacZ/traR reporter gene responsive to AHLs. The experiments showed that both chitosan and non-thermal plasma reduce the AHLs level and thus the biofilm formation and stability. The effectiveness of both agents was somewhat strain dependent. During the eradication of P. aeruginosa DBM 3081 biofilm on titanium alloy induced by chitosan (45 mg / l) there was an 80% decrease in AHLs. Applying chitosan or NTP on the P. aeruginosa DBM 3777 biofilm did not cause a significant decrease in AHLs, however, in combination with both (chitosan 55 mg / l and NTP 30 min), resulted in a 70% decrease in AHLs. Combined application of NTP and polymyxin B allowed reduce antibiotic concentration to achieve the same level of AHLs inhibition in P. aeruginosa ATCC 15442. The results shown that non-thermal plasma and chitosan have considerable potential for the eradication of highly resistant P. aeruginosa biofilms, for example on medical instruments or joint implants.

Keywords: anti-biofilm activity, chitosan, non-thermal plasma, opportunistic pathogens

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Authors: Abdel Rahman Altakhaineh

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This paper has analysed the conceptual relations between the elements of NN compounds in Arabic and compared them to those found in English based on the framework of Conceptual Semantics and a modified version of Parallel Architecture referred to as Relational Morphology. The analysis revealed that the repertoire of possible semantic relations between the two nouns in Arabic NN compounds reproduces that in English NN compounds and that, therefore, the main difference is in headedness (right-headed in English, left-headed in Arabic). Adopting RM allows productive and idiosyncratic elements to interweave with each other naturally. Semantically transparent compounds can be stored in memory or produced and understood online, while compounds with different degrees of semantic idiosyncrasy are stored in memory. Furthermore, the predictable parts of idiosyncratic compounds are captured by general schemas. In compounds, such schemas pick out the range of possible semantic relations between the two nouns. Finally, conducting a cross-linguistic study of the systematic patterns of possible conceptual relationships between compound elements is an area worthy of further exploration. In addition, comparing and contrasting compounding in Arabic and Hebrew, especially as they are both Semitic languages, is another area that needs to be investigated thoroughly. It will help morphologists understand the extent to which Jackendoff’s repertoire of semantic relations in compounds is universal. That is, if a language as distant from English as Arabic displays a similar range of cases, this is evidence for a (relatively) universal set of relations from which individual languages may pick and choose.

Keywords: conceptual semantics, morphology, compounds, arabic, english

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Authors: Ayman Hijazi, Witold Kwapinski, J. J. Leahy

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Finding a sustainable alternative energy to fossil fuel is an urgent need as various environmental challenges in the world arise. Therefore, formic acid (FA) decomposition has been an attractive field that lies at the center of biomass platform, comprising a potential pool of hydrogen energy that stands as a new energy vector. Liquid FA features considerable volumetric energy density of 6.4 MJ/L and a specific energy density of 5.3 MJ/Kg that qualifies it in the prime seat as an energy source for transportation infrastructure. Additionally, the increasing research interest in FA decomposition is driven by the need of in-situ H2 production, which plays a key role in the hydrogenation reactions of biomass into higher value components. It is reported elsewhere in literature that catalytic decomposition of FA is usually performed in poorly designed setup using simple glassware under magnetic stirring, thus demanding further energy investment to retain the used catalyst. it work suggests an approach that integrates designing a novel catalyst featuring magnetic property with a robust setup that minimizes experimental & measurement discrepancies. One of the most prominent active species for dehydrogenation/hydrogenation of biomass compounds is palladium. Accordingly, we investigate the potential of engrafting palladium metal onto functionalized magnetic nanoparticles as a heterogeneous catalyst to favor the production of CO-free H2 gas from FA. Using ordinary magnet to collect the spent catalyst renders core-shell magnetic nanoparticles as the backbone of the process. Catalytic experiments were performed in a jacketed batch reactor equipped with an overhead stirrer under inert medium. Through a novel approach, FA is charged into the reactor via high-pressure positive displacement pump at steady state conditions. The produced gas (H2+CO2) was measured by connecting the gas outlet to a measuring system based on the amount of the displaced water. The novelty of this work lies in designing a very responsive catalyst, pumping consistent amount of FA into a sealed reactor running at steady state mild temperatures, and continuous gas measurement, along with collecting the used catalyst without the need for centrifugation. Catalyst characterization using TEM, XRD, SEM, and CHN elemental analyzer provided us with details of catalyst preparation and facilitated new venues to alter the nanostructure of the catalyst framework. Consequently, the introduction of amine groups has led to appreciable improvements in terms of dispersion of the doped metals and eventually attaining nearly complete conversion (100%) of FA after 7 hours. The relative importance of the process parameters such as temperature (35-85°C), stirring speed (150-450rpm), catalyst loading (50-200mgr.), and Pd doping ratio (0.75-1.80wt.%) on gas yield was assessed by a Taguchi design-of-experiment based model. Experimental results showed that operating at lower temperature range (35-50°C) yielded more gas while the catalyst loading and Pd doping wt.% were found to be the most significant factors with a P-values 0.026 & 0.031, respectively.

Keywords: formic acid decomposition, green catalysis, hydrogen, mesoporous silica, process optimization, nanoparticles

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Authors: Mbambu K. Shaloom, Biba Kalengo, Pierre Echard, Olivier Gilson, Tshiswaka Ngalula, Léonard Kabeya Mukeba Yakasham

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In this 21st century, while design and eco-construction continue to be governed by considerations of functionality, safety, comfort and initial investment cost. Today, the principles of sustainable development lead us to think over longer time frames, to take into account new issues and the operating costs of green energy. DR Congo (sub-Saharan Africa) still suffers from the unusability of certain bio-sourced materials (such as bamboo, branches, etc.) and the lack of energy, i.e. 9% of the population has access to electricity and 21% of access to water. Ecoconstruction involves the energy performance of buildings which carry out a dynamic thermal simulation, which targets the different assumptions and conventional parameters (weather, occupancy, materials, thermal comfort, green energies, etc.). The objective of this article is to remedy the thermal, economic and technical artisanal problems in an aqueous environment in the city of Kinshasa. In order to establish a behavioral model to mitigate environmental impacts on architectural modifications and low-cost eco-construction through the approach of innovation and design thinking.

Keywords: thermal comfort, bio-sourced material, eco-architecture, eco-construction, squatting, design thinking

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Authors: Hamd Ahmed

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During the Persian Gulf War in 1991s, The confederation forces were surprised when they were being shot at by friendly forces in Iraqi desert. As obvious was the fact that they were mislead due to the lack of proper guidance and technology resulting in unnecessary loss of life and bloodshed. This unforeseen incident along with many others led the US department of defense to open the doors of GPS. In the very beginning, this technology was for military use, but now it is being widely used and increasingly popular among the public due to its high accuracy and immeasurable significance. The GPS system simply consists of three segments, the space segment (the satellite), the control segment (ground control) and the user segment (receiver). This project work is about designing a 1.57GHZ mixer for triple conversion GPS receiver .The GPS Front-End receiver based on super heterodyne receiver which improves selectivity and image frequency. However the main principle of the super heterodyne receiver depends on the mixer. Many different types of mixers (single balanced mixer, Single Ended mixer, Double balanced mixer) can be used with GPS receiver, it depends on the required specifications. This research project will provide an overview of the GPS system and details about the basic architecture of the GPS receiver. The basic emphasis of this report in on investigating general concept of the mixer circuit some terms related to the mixer along with their definitions and present the types of mixer, then gives some advantages of using singly balanced mixer and its application. The focus of this report is on how to design mixer for GPS receiver and discussing the simulation results.

Keywords: GPS , RF filter, heterodyne, mixer

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Authors: Anita Sadat Sadati Rostami, Reza Almasi Ghaleh

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Surface electromyography (sEMG) offers important insights into muscle activation and has applications in fields including rehabilitation and human-computer interaction. The purpose of this work is to predict the degree of activation of two joints in the index finger using an LSTM-Transformer architecture trained on sEMG data from the Ninapro DB8 dataset. We apply advanced preprocessing techniques, such as multi-band filtering and customizable rectification methods, to enhance the encoding of sEMG data into features that are beneficial for regression tasks. The processed data is converted into spike patterns and simulated using Leaky Integrate-and-Fire (LIF) neuron models, allowing for neuromorphic-inspired processing. Our findings demonstrate that adjusting filtering parameters and neuron dynamics and employing the LSTM-Transformer model improves joint angle prediction performance. This study contributes to the ongoing development of deep learning frameworks for sEMG analysis, which could lead to improvements in motor control systems.

Keywords: surface electromyography, LSTM-transformer, spiking neural networks, hand kinematics, leaky integrate-and-fire neuron, band-pass filtering, muscle activity decoding

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Authors: Eiman Kattan

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This study aims to evaluate the impact of classifying labelled remote sensing images conventional neural network (CNN) architecture, i.e., AlexNet on different land cover scenarios based on two remotely sensed datasets from different point of views such as the computational time and performance. Thus, a set of experiments were conducted to specify the effectiveness of the selected convolutional neural network using two implementing approaches, named fully trained and fine-tuned. For validation purposes, two remote sensing datasets, AID, and RSSCN7 which are publicly available and have different land covers features were used in the experiments. These datasets have a wide diversity of input data, number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in training, validation, and testing. As a result, the fully trained approach has achieved a trivial result for both of the two data sets, AID and RSSCN7 by 73.346% and 71.857% within 24 min, 1 sec and 8 min, 3 sec respectively. However, dramatic improvement of the classification performance using the fine-tuning approach has been recorded by 92.5% and 91% respectively within 24min, 44 secs and 8 min 41 sec respectively. The represented conclusion opens the opportunities for a better classification performance in various applications such as agriculture and crops remote sensing.

Keywords: conventional neural network, remote sensing, land cover, land use

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Authors: Arian Hosseini, Mahmudul Hasan

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To address the increasing need for efficient and accurate content moderation, we propose an efficient and lightweight deep classification ensemble structure. Our approach is based on a combination of simple visual features, designed for high-accuracy classification of violent content with low false positives. Our ensemble architecture utilizes a set of lightweight models with narrowed-down color features, and we apply it to both images and videos. We evaluated our approach using a large dataset of explosion and blast contents and compared its performance to popular deep learning models such as ResNet-50. Our evaluation results demonstrate significant improvements in prediction accuracy, while benefiting from 7.64x faster inference and lower computation cost. While our approach is tailored to explosion detection, it can be applied to other similar content moderation and violence detection use cases as well. Based on our experiments, we propose a "think small, think many" philosophy in classification scenarios. We argue that transforming a single, large, monolithic deep model into a verification-based step model ensemble of multiple small, simple, and lightweight models with narrowed-down visual features can possibly lead to predictions with higher accuracy.

Keywords: deep classification, content moderation, ensemble learning, explosion detection, video processing

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Authors: Adewale O. Ogunde, Olusegun Folorunso, Adesina S. Sodiya

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Most existing Distributed Association Rule Mining (DARM) systems are still facing several challenges. One of such challenges that have not received the attention of many researchers is the inability of existing systems to adapt to constantly changing databases and mining environments. In this work, an Adaptive Incremental Mining Algorithm (AIMA) is therefore proposed to address these problems. AIMA employed multiple mobile agents for the entire mining process. AIMA was designed to adapt to changes in the distributed databases by mining only the incremental database updates and using this to update the existing rules in order to improve the overall response time of the DARM system. In AIMA, global association rules were integrated incrementally from one data site to another through Results Integration Coordinating Agents. The mining agents in AIMA were made adaptive by defining mining goals with reasoning and behavioral capabilities and protocols that enabled them to either maintain or change their goals. AIMA employed Java Agent Development Environment Extension for designing the internal agents’ architecture. Results from experiments conducted on real datasets showed that the adaptive system, AIMA performed better than the non-adaptive systems with lower communication costs and higher task completion rates.

Keywords: adaptivity, data mining, distributed association rule mining, incremental mining, mobile agents

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Authors: YingWei Tan, XueFeng Ding

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Attention-based voice activity detection models have gained significant attention in recent years due to their fast training speed and ability to capture a wide contextual range. The inclusion of multi-head style and position embedding in the attention architecture are crucial. Having multiple attention heads allows for differential focus on different parts of the sequence, while position embedding provides guidance for modeling dependencies between elements at various positions in the input sequence. In this work, we propose an approach by considering each head as a node, enabling the application of graph neural networks (GNN) to identify correlations among the different nodes. In addition, we adopt an implementation named rotary position embedding (RoPE), which encodes absolute positional information into the input sequence by a rotation matrix, and naturally incorporates explicit relative position information into a self-attention module. We evaluate the effectiveness of our method on a synthetic dataset, and the results demonstrate its superiority over the baseline CRNN in scenarios with low signal-to-noise ratio and noise, while also exhibiting robustness across different noise types. In summary, our proposed framework effectively combines the strengths of CNN and RNN (LSTM), and further enhances detection performance through the integration of graph neural networks and rotary position embedding.

Keywords: voice activity detection, CRNN, graph neural networks, rotary position embedding

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Authors: Sahar Nasr, Lin Li, Edwin Wang

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Bladder cancer (BLCA) is known as the 13th cause of death among cancer patients worldwide, and ~575,000 new BLCA cases are diagnosed each year. Urothelial carcinoma (UC) is the most prevalent subtype among BLCA patients, which can be categorized into muscle-invasive bladder cancer (MIBC) and non-muscle-invasive bladder cancer (NMIBC). Currently, various therapeutic options are available for UC patients, including (1) transurethral resection followed by intravesical instillation of chemotherapeutics or Bacillus Calmette-Guérin for NMIBC patients, (2) neoadjuvant platinum-based chemotherapy (NAC) plus radical cystectomy is the standard of care for localized MIBC patients, and (3) systematic chemotherapy for metastatic UC. However, conventional treatments may lead to several challenges for treating patients. As an illustration, some patients may suffer from recurrence of the disease after the first line of treatment. Recently, immune checkpoint therapy (ICT) has been introduced as an alternative treatment strategy for the first or second line of treatment in advanced or metastatic BLCA patients. Although ICT showed lucrative results for a fraction of BLCA patients, ~80% of patients were not responsive to it. Therefore, novel treatment methods are required to augment the ICI response rate within BLCA patients. It has been shown that the infiltration of T-cells into the tumor microenvironment (TME) is positively correlated with the response to ICT within cancerous patients. Therefore, the goal of this study is to enhance the infiltration of cytotoxic T-cells into TME through the identification of target genes within the tumor that are responsible for the non-T-cell inflamed TME and their inhibition. BLCA bulk RNA-sequencing data from The Cancer Genome Atlas (TCGA) and immune score for TCGA samples were used to determine the Pearson correlation score between the expression of different genes and immune score for each sample. The genes with strong negative correlations were selected (r < -0.2). Thereafter, the correlation between the expression of each gene and survival in BLCA patients was calculated using the TCGA data and Cox regression method. The genes that are common in both selected gene lists were chosen for further analysis. Afterward, BLCA bulk and single-cell RNA-sequencing data were ranked based on the expression of each selected gene and the top and bottom 25% samples were used for pathway enrichment analysis. If the pathways related to the T-cell infiltration (e.g., antigen presentation, interferon, or chemokine pathways) were enriched within the low-expression group, the gene was included for downstream analysis. Finally, the selected genes will be used to calculate the correlation between their expression and the infiltration rate of the activated CD+8 T-cells, natural killer cells and the activated dendric cells. A list of potential target genes has been identified and ranked based on the above-mentioned analysis and criteria. SUN-1 got the highest score within the gene list and other identified genes in the literature as benchmarks. In conclusion, inhibition of SUN1 may increase the tumor-infiltrating lymphocytes and the efficacy of ICI in BLCA patients. BLCA tumor cells with and without SUN-1 CRISPR/Cas9 knockout will be injected into the syngeneic mouse model to validate the predicted SUN-1 effect on increasing tumor-infiltrating lymphocytes.

Keywords: data analysis, gene expression analysis, gene identification, immunoinformatic, functional genomics, transcriptomics

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Authors: Xiaolin Zeng, Lei Cheng, Zhirong Li, Xueping Liu

Abstract:

Aiming at the problem of low accuracy and susceptibility to cultural relic diseases in the generation of high-resolution archaeology drawings by current image generation algorithms, an archaeology drawings generation algorithm based on a conditional generative adversarial network is proposed. An attention mechanism is added into the high-resolution image generation network as the backbone network, which enhances the line feature extraction capability and improves the accuracy of line drawing generation. A dual-branch parallel architecture consisting of two backbone networks is implemented, where the semantic translation branch extracts semantic features from orthophotographs of cultural relics, and the gradient screening branch extracts effective gradient features. Finally, the fusion fine-tuning module combines these two types of features to achieve the generation of high-quality and high-resolution archaeology drawings. Experimental results on the self-constructed archaeology drawings dataset of grotto temple statues show that the proposed algorithm outperforms current mainstream image generation algorithms in terms of pixel accuracy (PA), structural similarity (SSIM), and peak signal-to-noise ratio (PSNR) and can be used to assist in drawing archaeology drawings.

Keywords: archaeology drawings, digital heritage, image generation, deep learning

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Authors: Alexandra Monteiro, K. Bousson, Fernando J. O. Moreira, Ricardo Reis

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Fixed-wing flying vehicles are usually controlled by means of control surfaces such as elevators, ailerons, and rudders. The failure of these systems may lead to severe or even fatal crashes. These failures resulted in increased popularity for research activities on propulsion control in the last decades. The present work deals with a hybrid control architecture in which the propulsion-controlled vehicle maintains its traditional control surfaces, addressing the issue of robust lateral-directional dynamics control. The challenges stem from the parameter uncertainties in the stability and control derivatives and some unknown terms in the flight dynamics model. Two approaches are implemented and tested: linear quadratic regulation with robustness characteristics and H∞ control. The problem is centered on roll-yaw controller design with full state-feedback, which is able to deal with a standalone propulsion control mode as well as a hybrid mode combining both propulsion control and conventional control surface concepts while maintaining the original flight maneuverability characteristics. The results for both controllers emphasized very good control performances; however, the H∞ controller showed higher stabilization rates and robustness albeit with a slightly higher control magnitude than using the linear quadratic regulator.

Keywords: robust propulsion control, h-infinity control, lateral-directional flight dynamics, parameter uncertainties

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Authors: Allison Tucker, Carolyn Clarke, Erin Keith

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Introduction: In education, the determination to uncover privileged practices requires critical reflection to be placed at the center of both pre-service and in-service teacher education. Confronting deficit thinking about children’s abilities and shifting to holding an image of the child as capable and competent is necessary for teachers to engage in responsive pedagogy that meets children where they are in their learning and builds on strengths. This paper explores the ways in which early elementary teachers' perceptions of the assets of children might shift through the pedagogical use of video clubs. Video club is a pedagogical practice whereby teachers record and view short videos with the intended purpose of deepening their practices. The use of video club as a learning tool has been an extensively documented practice. In this study, a video club is used to watch short recordings of playing children to identify the assets of their students. Methodology: The study on which this paper is based asks the question: What are the ways in which teachers’ image of the child and teaching practices evolve through the use of video club focused on the strengths of children demonstrated during play? Using critical reflection, it aims to identify and describe participants’ experiences of examining their personally held image of the child through the pedagogical tool video club, and how that image influences their practices, specifically in implementing play pedagogy. Teachers enrolled in a graduate-level play pedagogy course record and watch videos of their own students as a means to notice and reflect on the learning that happens during play. Using a co-constructed viewing protocol, teachers identify student strengths and consider their pedagogical responses. Video club provides a framework for teachers to critically reflect in action, return to the video to rewatch the children or themselves and discuss their noticings with colleagues. Critical reflection occurs when there is focused attention on identifying the ways in which actions perpetuate or challenge issues of inherent power in education. When the image of the child held by the teacher is from a deficit position and is influenced by hegemonic dimensions of practice, critical reflection is essential in naming and addressing power imbalances, biases, and practices that are harmful to children and become barriers to their thriving. The data is comprised of teacher reflections, analyzed using phenomenology. Phenomenology seeks to understand and appreciate how individuals make sense of their experiences. Teacher reflections are individually read, and researchers determine pools of meaning. Categories are identified by each researcher, after which commonalities are named through a recursive process of returning to the data until no more themes emerge or saturation is reached. Findings: The final analysis and interpretation of the data are forthcoming. However, emergent analysis of the data collected using teacher reflections reveals the ways in which the use of video club grew teachers’ awareness of their image of the child. It shows video club as a promising pedagogical tool when used with in-service teachers to prompt opportunities for play and to challenge deficit thinking about children and their abilities to thrive in learning.

Keywords: asset-based teaching, critical reflection, image of the child, video club

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Authors: Fitri Nugraheni, Adwitya Bhaskara, N. Faried Hanafi

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Coastal is one area that can be a place to live. Various buildings can be built in the area around the beach. Many Indonesians use beaches as housing and work, but we know that coastal areas are identical to tsunami and wind. Costs incurred due to permanent damage caused by tsunamis and wind disasters in Indonesia can be minimized by replacing permanent buildings into semi-permanent buildings. Semi-permanent buildings can be realized by using cold-formed steel as a building. Thus, the purpose of this research is to provide efficient semi-permanent building recommendations for residents around the coast. The research is done by first designing the building model by using sketch-up software, then the validation phase is done in consultation with the expert consultant of cold form steel structure. Based on the results of the interview there are several revisions on several sides of the building by adding some bracing rods on the roof, walls and floor frame. The result of this research is recommendation of semi-permanent building model, where the nature of the building; easy to disassemble and install (knockdown), tsunami-friendly (continue the tsunami load), cost and time efficient (using cold-formed-steel and prefabricated GRC), zero waste, does not require many workers (less labor). The recommended building design concept also keeps the architecture side in mind thus it remains a comfortable occupancy for the residents.

Keywords: construction method, cold-formed steel, efficiency, semi-permanent building, tsunami

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Authors: Ina Dajci

Abstract:

Biologic Materials presents groundbreaking transdisciplinary research aimed at fostering new collaborative models across the Built Environment, Forestry, and Agriculture sectors. This initiative seeks to establish innovative paradigms for local and global material flows by developing a biocompatible, regenerative material economy. The project focuses on creating materials derived from biowaste and silvicultural practices, ensuring the preservation of endangered indigenous and vernacular techniques through the integration of emerging biosciences. By utilizing biomaterials sourced from agricultural waste and forest byproducts, the initiative incorporates fabrication methods recognized by UNESCO as ‘intangible cultural heritage of humanity,’ which are currently at risk. The structural, mechanical, and environmental properties of these materials are enhanced through advanced CAD-CAM fabrication, along with energy-efficient biochemical and bacterial processes that promote healthy indigo coloration. Furthermore, the integration of AI technologies in species selection facilitates a novel partnership model, enabling designers to collaborate effectively with forest managers and silviculture practitioners. This collaborative approach not only optimizes the use of plant-based materials but also enhances biodiversity and climate resilience in regional ecosystems. Overall, this project embodies a holistic strategy for addressing environmental challenges while revitalizing traditional practices and fostering sustainable innovation.

Keywords: material, architecture, culture, heritage, ecology, environment

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