Search results for: real time digital simulator

Authors: Jaroslava Sucha, Martin Dolejs, Helena Pipova, Panajotis Cakirpaloglu

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The paper introduces the research project which is focused on evaluating the level of pathological relation towards computer or video games playing (including any games played by using a screen such as a mobile or a tablet). The study involves representative sample of the Czech adolescents between ages 11 and 19. This poster presents the psychometric indicators of the new psychologic assessment method (mean, standard deviation, reliability, validity) which will be able to detect an acceptable level of games’ playing and at the same time will detect and describe the level of gaming which might be potentially risky. The prevalence of risky computer game playing at Czech adolescents in age 11 to 19 will be mentioned. The research study also aims to describe the personality profile of the problematic players with respect to the digital games. The research area will encompass risky behaviour, aggression, the level of self-esteem, impulsivity, anxiety and depression. The contribution will introduce a new test method for the assessment of pathological playing computer games. The research will give the first screening information of playing computer games in the Czech Republic by adolescents between 11-19 years. The results clarify what relationship exists between playing computer games and selected personality characteristics (it will describe personality of the gamer, who is in the category of ‘pathological playing computer games’).

Keywords: adolescence, computer games, personality traits, risk behaviour

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Authors: P. Jost, L. Muckova, M. Matula, J. Pejchal, D. Jun, R. Stetina

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Sulfur mustard (bis(2-chlorethyl) sulfide) is highly toxic, chemical warfare agent that has been used in the past in several armed conflicts. Except for the skin, respiratory tract is one of the important routes of exposure. The elucidation and understanding of the mechanism of toxicity of SM have been effort intensive research. The multiple targets character of SM caused cellular damage resulted in activation of many different mechanisms which contribute to cellular response and participate in the final cytopathology effect. In our present work, we compared time-dependent changes in sulfur mustard exposed adult human lung fibroblasts NHLF and lung epithelial alveolar cell line A-549. Cell viability (MTT assay, Calcein-AM assay, and xCELLigence - real-time cell analysis), apoptosis (flow cytometry), mitochondrial membrane potential (Δψm, flow cytometry), reactive oxygen species induction (DC and cell cycle distribution (flow cytometry) were studied. We observed significantly decreased mitochondrial membrane potential and subsequent induction of apoptosis correlating with decreased cellular viability in the sulfur mustard exposed cells. In low concentrations, sulfur mustard-induced S-phase cell cycle arrest, on the other hand, high concentrations, cell cycle phase distribution of sulfur mustard exposed cells resembled cell cycle phase distribution of control group, which implies nonspecific cell cycle inhibition. Epithelial cells A-549 was found as more sensible to sulfur mustard toxicity. Acknowledgements: This work was supported by a long-term organization development plan Medical Aspects of Weapons of Mass Destruction of the Faculty of Military Health Sciences, University of Defence.

Keywords: apoptosis, cell cycle, cytotoxicity, sulfur mustard

Procedia PDF Downloads 187

Authors: Judith Hanke

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Due to the rise of students with reading difficulties, a digital reading support was developed. The digital reading support focuses on reading comprehension of elementary school students. It consists of literary texts and reading exercises with diagnostics. To analyze the use of the reading packages an intervention study took place in 2023. For the methodology, an ABA-design was selected for the intervention study to examine the reading packages. The study was expedited from April 2023 until July 2023 and collected quantitative data of individuals, groups, and classes. It consisted of a survey group (N = 58) and a control group (N = 53). The pretest was conducted before the reading support intervention. The students of the survey group received reading support on their ability level to aid the individual student’s needs. At the beginning of the study characteristics of the students were collected. The characteristics included gender, age, repetition of a class, spoken language at home, German as a second language, and special support needs such as dyslexia; right after the intervention, the posttest was examined. At least three weeks after the intervention, the follow-up testing was administered. A standardized reading comprehension test was used for the three test times. The test consists of three subtests: word comprehension, sentence comprehension, and text comprehension. The focus of this paper is to determine which characteristics have an impact on reading comprehension of elementary school students. The students’ characteristics were correlated with the three test times through a Pearson correlation. The main findings are that age, repetition of a class, spoken language at home, German as a second language have an effect on reading comprehension. Interestingly gender and special support needs did not have a significant effect on the reading comprehension of the students. The significance of the study is to determine which characteristics have an impact on reading comprehension and then to assess how reading support can be modified to support the diverse students.

Keywords: class repetition, reading comprehension, reading support, second language, spoken language at home

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Authors: Benjaporn Buranrat, Nootchanat Mairuae

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Cratoxylum formosum (Jack) Dyer (CF) has been used for the traditional medicines in South East Asian and Thailand. Normally, northeast Thai vegetables have proven cytotoxic to many cancer cells. Therefore, the present study aims to explore the molecular mechanisms underlying CF-induced cancer cell death and apoptosis on breast and liver cancer cells. The cytotoxicity and antiproliferative effects of CF on the human breast MCF-7 and liver HepG2 cancer cell lines were evaluated using sulforhodamine B assay and colony formation assay. Cell migration assay was measured using wound healing assay. The apoptosis induction mechanisms were investigated through reactive oxygen species formation, caspase 3 activity, and JC-1 activity. Gene expression by real-time PCR and apoptosis related protein levels by Western blot analysis. CF induced MCF-7 and HepG2 cell death by time- and dose-dependent manner. Furthermore, CF had the greater cytotoxic potency on MCF-7 more than HepG2 cells with IC50 values of 85.70+4.52 μM and 219.03±9.96 μM respectively, at 24 h. Treatment with CF also caused a dose-dependent decrease in colony forming ability and cell migration, especially on MCF-7 cells. CF induced ROS formation, increased caspase 3 activities, and decreased the mitochondrial membrane potential, and causing apoptotic body production and DNA fragmentation. CF significantly decreased expression of the cell cycle regulatory protein RAC1 and downstream proteins, cdk6. Additionally, CF enhanced p21 and reduced cyclin D1 protein levels. CF leaf extract induced cell death, apoptosis, antimigration in both of MCF-7 and HepG2 cells. CF could be useful for developing to anticancer drug candidate for breast and liver cancer therapy.

Keywords: cratoxylum formosum (jack) dyer, breast cancer, liver cancer, cell death

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Authors: Duhania O. Mahara, Santi W. Purnami, Aulia N. Fitria, Merissa N. Z. Wirontono, Revina Musfiroh, Shofi Andari, Sagiran Sagiran, Estiana Khoirunnisa, Wahyudi Widada

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For assessing interventions in numerous disease areas, the use of multiple time-to-event outcomes is common. An individual might experience two different events called bivariate time-to-event data, the events may be correlated because it come from the same subject and also influenced by individual characteristics. The bivariate time-to-event case can be applied by copula-based bivariate Cox survival model, using the Clayton and Frank copulas to analyze the dependence structure of each event and also the covariates effect. By applying this method to modeling the recurrent event infection of hemodialysis insertion on chronic kidney disease (CKD) patients, from the AIC and BIC values we find that the Clayton copula model was the best model with Kendall’s Tau is (τ=0,02).

Keywords: bivariate cox, bivariate event, copula function, survival copula

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Authors: Amit Kumar, Himanshu Singal, Arnav Bhavsar

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In this modern era of automation, most of the academic exams and competitive exams are Multiple Choice Questions (MCQ). The responses of these MCQ based exams are recorded in the Optical Mark Reader (OMR) sheet. Evaluation of the OMR sheet requires separate specialized machines for scanning and marking. The sheets used by these machines are special and costs more than a normal sheet. Available process is non-economical and dependent on paper thickness, scanning quality, paper orientation, special hardware and customized software. This study tries to tackle the problem of evaluating the OMR sheet without any special hardware and making the whole process economical. We propose an image processing based algorithm which can be used to read and evaluate the scanned OMR sheets with no special hardware required. It will eliminate the use of special OMR sheet. Responses recorded in normal sheet is enough for evaluation. The proposed system takes care of color, brightness, rotation, little imperfections in the OMR sheet images.

Keywords: OMR, image processing, hough circle trans-form, interpolation, detection, binary thresholding

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Authors: Marcin Sowa

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The paper discusses the subinterval-based numerical method for fractional derivative computations. It is now referred to by its acronym – SubIval. The basis of the method is briefly recalled. The ability of the method to be applied in time stepping solvers is discussed. The possibility of implementing a time step size adaptive solver is also mentioned. The solver is tested on a transient circuit example. In order to display the accuracy of the solver – the results have been compared with those obtained by means of a semi-analytical method called gcdAlpha. The time step size adaptive solver applying SubIval has been proven to be very accurate as the results are very close to the referential solution. The solver is currently able to solve FDE (fractional differential equations) with various derivative orders for each equation and any type of source time functions.

Keywords: numerical method, SubIval, fractional calculus, numerical solver, circuit analysis

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Authors: V. Esteves

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As products of participatory culture, internet memes represent a global form of interaction with online culture. These digital objects draw upon a rich historical engagement with remix practices that dates back decades: from the copy and paste practices of Dadaism and punk to the re-appropriation techniques of the Situationist International; memes echo a long established form of cultural creativity that pivots on the art of the remix. Online culture has eagerly embraced the changes that the Web 2.0 afforded in terms of making use of remixing as an accessible form of societal expression, bridging these remix practices of the past into a more widely available and accessible platform. Memes embody the idea of 'intercreativity', allowing global creative collaboration to take place through networked digital media; they reflect the core values of participation and interaction that are present throughout much internet discourse whilst also existing in a historical remix continuum. Memes hold the power of cultural symbolism manipulated by global audiences through which societies make meaning, as these remixed digital objects have an elasticity and low literacy level that allows for a democratic form of cultural engagement and meaning-making by and for users around the world. However, because memes are so elastic, their ability to be re-appropriated by other powers for reasons beyond their original intention has become evident. Recently, corporations have made use of internet memes for advertising purposes, engaging in the circulation and re-appropriation of internet memes in commercial spaces – which has, in turn, complicated this relation between online users and memes' democratic possibilities further. By engaging in a widespread online ethnography supplemented by in-depth interviews with meme makers, this research was able to not only track different online meme use through commercial contexts, but it also allowed the possibility to engage in qualitative discussions with meme makers and users regarding their perception and experience of these varying commercial uses of memes. These can be broadly put within two categories: internet memes that are turned into physical merchandise and the use of memes in advertising to sell other (non-meme related) products. Whilst there has been considerable acceptance of the former type of commercial meme use, the use of memes in adverts in order to sell unrelated products has been met with resistance. The changes in reception regarding commercial meme use is dependent on ideas of cultural ownership and perceptions of authorship, ultimately uncovering underlying socio-cultural ideologies that come to the fore within these overlapping contexts. Additionally, this adoption of memes by corporate powers echoes the recuperation process that the Situationist International endured, creating a further link with older remix cultures and their lifecycles.

Keywords: commodification, internet culture, memes, recuperation, remix

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Authors: Matthias Haenisch, Katharina Hermann, Marc Godau, Verena Weidner

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Over the past two decades, international music education has been characterized by a growing interest in informal learning for formal contexts and a "compositional turn" that has moved from closed to open forms of composing. This change occurs under social and technological conditions that permeate 21st-century musical practices. This forms the background of Musical Communities in the (Post)Digital Age (MusCoDA), a four-year joint research project of the University of Erfurt (UE) and the University of Education Karlsruhe (PHK), funded by the German Federal Ministry of Education and Research (BMBF). Both explore songwriting processes as an example of collective creativity in (post)digital communities, one in formal and the other in informal learning contexts. Collective songwriting will be studied from a network perspective, that will allow us to view boundaries between both online and offline as well as formal and informal or hybrid contexts as permeable and to reconstruct musical learning practices. By comparing these songwriting processes, possibilities for a pedagogical-didactic interweaving of different educational worlds are highlighted. Therefore, the subproject of the University of Erfurt investigates school music lessons with the help of interviews, videography, and network maps by analyzing new digital pedagogical and didactic possibilities. In the first step, the international literature on songwriting in the music classroom was examined for design development. The analysis focused on the question of which methods and practices are circulating in the current literature. Results from this stage of the project form the basis for the first instructional design that will help teachers in planning regular music classes and subsequently reconstruct musical learning practices under these conditions. In analyzing the literature, we noticed certain structural methods and concepts that recur, such as the Building Blocks method and the pre-structuring of the songwriting process. From these findings, we developed a deck of cards that both captures the current state of research and serves as a method for design development. With this deck of cards, both teachers and students themselves can plan their individual songwriting lessons by independently selecting and arranging topic, structure, and action cards. In terms of science communication, music educators' interactions with the card game provide us with essential insights for developing the first design. The overall goal of MusCoDA is to develop an empirical model of collective musical creativity and learning and an instructional design for teaching music in the postdigital age.

Keywords: card game, collective songwriting, community of practice, network, postdigital

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Authors: Le Xuan Cau

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Flash flood is occurred in short time rainfall interval: from 1 hour to 12 hours in small and medium basins. Flash floods typically have two characteristics: large water flow and big flow velocity. Flash flood is occurred at hill valley site (strip of lowland of terrain) in a catchment with large enough distribution area, steep basin slope, and heavy rainfall. The risk of flash floods is determined through Gridded Basin Flash Flood Potential Index (GBFFPI). Flash Flood Potential Index (FFPI) is determined through terrain slope flash flood index, soil erosion flash flood index, land cover flash floods index, land use flash flood index, rainfall flash flood index. Determining GBFFPI, each cell in a map can be considered as outlet of a water accumulation basin. GBFFPI of the cell is determined as basin average value of FFPI of the corresponding water accumulation basin. Based on GIS, a tool is developed to compute GBFFPI using ArcObjects SDK for .NET. The maps of GBFFPI are built in two types: GBFFPI including rainfall flash flood index (real time flash flood warning) or GBFFPI excluding rainfall flash flood index. GBFFPI Tool can be used to determine a high flash flood potential site in a large region as quick as possible. The GBFFPI is improved from conventional FFPI. The advantage of GBFFPI is that GBFFPI is taking into account the basin response (interaction of cells) and determines more true flash flood site (strip of lowland of terrain) while conventional FFPI is taking into account single cell and does not consider the interaction between cells. The GBFFPI Map of QuangNam, QuangNgai, DaNang, Hue is built and exported to Google Earth. The obtained map proves scientific basis of GBFFPI.

Keywords: ArcObjects SDK for NET, basin average value of FFPI, gridded basin flash flood potential index, GBFFPI map

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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: Yunwei Zhang, Qiaochu Tang, Yao Zhang, Jiabin Wang, Ulrich Stimming, Alpha Lee

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Forecasting the state of health and remaining useful life of Li-ion batteries is an unsolved challenge that limits technologies such as consumer electronics and electric vehicles. Here we build an accurate battery forecasting system by combining electrochemical impedance spectroscopy (EIS) -- a real-time, non-invasive and information-rich measurement that is hitherto underused in battery diagnosis -- with Gaussian process machine learning. We collect over 20,000 EIS spectra of commercial Li-ion batteries at different states of health, states of charge and temperatures -- the largest dataset to our knowledge of its kind. Our Gaussian process model takes the entire spectrum as input, without further feature engineering, and automatically determines which spectral features predict degradation. Our model accurately predicts the remaining useful life, even without complete knowledge of past operating conditions of the battery. Our results demonstrate the value of EIS signals in battery management systems.

Keywords: battery degradation, machine learning method, electrochemical impedance spectroscopy, battery diagnosis

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Authors: Shathya Duobiene, Gediminas Račiukaitis

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Solar-powered wireless sensor nodes work best when they operate continuously with minimal energy consumption. Wireless Sensor Networks (WSNs) are a new technology opens up wide studies, and advancements are expanding the prevalence of numerous monitoring applications and real-time aid for environments. The Selective Surface Activation Induced by Laser (SSAIL) technology is an exciting development that gives the design of WSNs more flexibility in terms of their shape, dimensions, and materials. This research work proposes a methodology for using SSAIL technology for forest ecosystem monitoring by wireless sensor networks. WSN monitoring the temperature and humidity were deployed, and their architectures are discussed. The paper presents the experimental outcomes of deploying newly built sensor nodes in forested areas. Finally, a practical method is offered to extend the WSN's lifespan and ensure its continued operation. When operational, the node is independent of the base station's power supply and uses only as much energy as necessary to sense and transmit data.

Keywords: internet of things (IoT), wireless sensor network, sensor nodes, SSAIL technology, forest ecosystem

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Authors: Amaladhithyan Krishnamoorthy, Ruvaitha Banu

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Vision is considered as the most important sense in humans, without which leading a normal can be often difficult. There are many existing smart canes for visually impaired with obstacle detection using ultrasonic transducer to help them navigate. Though the basic smart cane increases the safety of the users, it does not help in filling the void of visual loss. This paper introduces the concept of Digi-Buddy which is an evolved smart cane for visually impaired. The cane consists for several modules, apart from the basic obstacle detection features; the Digi-Buddy assists the user by capturing video/images and streams them to the server using a wide-angled camera, which then detects the objects using Deep Convolutional Neural Network. In addition to determining what the particular image/object is, the distance of the object is assessed by the ultrasonic transducer. The sound generation application, modelled with the help of Natural Language Processing is used to convert the processed images/object into audio. The object detected is signified by its name which is transmitted to the user with the help of Bluetooth hear phones. The object detection is extended to facial recognition which maps the faces of the person the user meets in the database of face images and alerts the user about the person. One of other crucial function consists of an automatic-intimation-alarm which is triggered when the user is in an emergency. If the user recovers within a set time, a button is provisioned in the cane to stop the alarm. Else an automatic intimation is sent to friends and family about the whereabouts of the user using GPS. In addition to safety and security by the existing smart canes, the proposed concept devices to be implemented as a prototype helping visually-impaired visualize their surroundings through audio more in an amicable way.

Keywords: artificial intelligence, facial recognition, natural language processing, internet of things

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Authors: Emily Hamilton, Adiel Kahana, Ron Hauser, Shimi Barda

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BACKGROUND: In the male fertility and sperm bank unit of Tel Aviv Sourasky medical center, women are treated with intrauterine insemination (IUI) using washed sperm from their partner or thawed sperm from a selected donor. In most cases, the women perform the IUI treatment in Sourasky, but sometimes they ask to undergo the insemination procedure in another clinic with their own fertility doctor. In these cases, the sperm sample is prepared at the Sourasky lab and the patient is inseminated after arriving to her doctor. Our laboratory has previously found that time negatively affects several parameters of thawed sperm, and we estimate that it has more severe and significant effect than on washed sperm. AIM: To examine the effect of time on the quality of washed sperm versus thawed sperm. METHODS: Sperm samples were collected from men referred for semen analysis. Each ejaculate was allowed to liquefy for at least 20 min at 37°C and analyzed for sperm motility and vitality percentage and DNA fragmentation index (Time 0). Subsequently, 1ml of the sample was divided into two parts, 1st part was washed only and the 2nd part was washed, frozen and thawed. Time 1 analysis occurred immediately after sperm washing or thawing. Time 2 analysis occurred 75 minutes after time 1. Statistical analysis was performed using Student t-test. P values<0.05 were considered significant. RESULTS: Preliminary data showed that time had a greater impact on the average percentages of sperm motility and vitality in thawed compared to washed sperm samples (26%±10% vs. 21%±10% and 21%±9% vs. 9%±10%, respectively). An additional trend towards increased average DNA fragmentation percentage in thawed samples compared to washed samples was observed (46%±18% vs. 25%±24%). CONCLUSION: Time negatively effects sperm quality. The effect is greater in thawed samples compared to fresh samples.

Keywords: ART, male fertility, sperm cryopreservation, sperm quality

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Authors: Paul Dankers, Juliet Stoltenkamp, Carolynne Kies

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In May 2005, the University of the Western Cape (UWC) established an eLearning Division (ED) that, over the past 18 years, accelerated into the institutionalization of an efficient eLearning Centre. The initial objective of the ED was to incessantly align itself with emerging technologies caused by digital transformation, which progressively impacted Higher Education Institutions (HEIs) globally. In this paper, we present how the UWC eLearning Division (ED) first evolved into the eLearning Development and Support Unit (EDUS), currently called the ‘Centre for Innovative Education and Communication Technologies (CIECT). CIECT was strategically separated from the Department of Information and Communication Services (ICS) in 2009 and repositioned as an independent structure at UWC. Using a comparative research method, we highlight the transformative eLearning landscape at UWC by doing a detailed account of the shift in practices. Our research method will determine the initial vision and outcomes of institutionalizing an eLearning division. The study aims to compare across space or time the eLearning division’s rate of growth. By comparing the progressive growth of the UWCs eLearning division over the years, we will be able to document the successes and achievements of the eLearning division precisely. This study’s outcomes will act as a reference for novel research subjects on formalising eLearning. More research that delves into the effectiveness of having an eLearning division at HEIs in support of students’ teaching and learning is needed.

Keywords: eLearning, institutionalization, teaching and learning, transformation

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Authors: Linxin Liu

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As system complexity increases, log parsing and anomaly detection become more and more important in ensuring system stability. However, traditional methods often face the problems of insufficient adaptability and decreasing accuracy when dealing with rapidly changing log contents and unknown domains. To this end, this paper proposes a distinct approach, LogRAG, which combines RAG (Retrieval Augmented Generation) technology with Prompt Engineering for Large Language Models, applied to log analysis tasks to achieve dynamic parsing of logs and intelligent anomaly detection. By combining real-time information retrieval and prompt optimization, this study significantly improves the adaptive capability of log analysis and the interpretability of results. Experimental results show that the method performs well on several public datasets, especially in the absence of training data, and significantly outperforms traditional methods. This paper provides a different technical path for log parsing and anomaly detection, demonstrating significant theoretical value and application potential.

Keywords: log parsing, anomaly detection, RAG (Retrieval-Augmented Generation), prompt engineering, LLMs

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Authors: Ece A. Irmak, Amdulla O. Mekhrabov, M. Vedat Akdeniz

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There is a growing interest in the modeling and simulation of magnetic nanoalloys by various computational methods. Magnetic crystalline/amorphous nanoparticles (NP) are interesting materials from both the applied and fundamental points of view, as their properties differ from those of bulk materials and are essential for advanced applications such as high-performance permanent magnets, high-density magnetic recording media, drug carriers, sensors in biomedical technology, etc. As an important magnetic material, Fe-Ni based nanoalloys have promising applications in the chemical industry (catalysis, battery), aerospace and stealth industry (radar absorbing material, jet engine alloys), magnetic biomedical applications (drug delivery, magnetic resonance imaging, biosensor) and computer hardware industry (data storage). The physical and chemical properties of the nanoalloys depend not only on the particle or crystallite size but also on composition and atomic ordering. Therefore, computer modeling is an essential tool to predict structural, electronic, magnetic and optical behavior at atomistic levels and consequently reduce the time for designing and development of new materials with novel/enhanced properties. Although first-principles quantum mechanical methods provide the most accurate results, they require huge computational effort to solve the Schrodinger equation for only a few tens of atoms. On the other hand, molecular dynamics method with appropriate empirical or semi-empirical inter-atomic potentials can give accurate results for the static and dynamic properties of larger systems in a short span of time. In this study, structural evolutions, magnetic and electronic properties of Fe-Ni based nanoalloys have been studied by using molecular dynamics (MD) method in Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) and Density Functional Theory (DFT) in the Vienna Ab initio Simulation Package (VASP). The effects of particle size (in 2-10 nm particle size range) and temperature (300-1500 K) on stability and structural evolutions of amorphous and crystalline Fe-Ni bulk/nanoalloys have been investigated by combining molecular dynamic (MD) simulation method with Embedded Atom Model (EAM). EAM is applicable for the Fe-Ni based bimetallic systems because it considers both the pairwise interatomic interaction potentials and electron densities. Structural evolution of Fe-Ni bulk and nanoparticles (NPs) have been studied by calculation of radial distribution functions (RDF), interatomic distances, coordination number, core-to-surface concentration profiles as well as Voronoi analysis and surface energy dependences on temperature and particle size. Moreover, spin-polarized DFT calculations were performed by using a plane-wave basis set with generalized gradient approximation (GGA) exchange and correlation effects in the VASP-MedeA package to predict magnetic and electronic properties of the Fe-Ni based alloys in bulk and nanostructured phases. The result of theoretical modeling and simulations for the structural evolutions, magnetic and electronic properties of Fe-Ni based nanostructured alloys were compared with experimental and other theoretical results published in the literature.

Keywords: density functional theory, embedded atom model, Fe-Ni systems, molecular dynamics, nanoalloys

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Authors: Asmir Gogic, Aljo Mujcic, Sandra Ibric, Nermin Suljanovic

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Ubiquity of natural disasters during last few decades have risen serious questions towards the prediction of such events and human safety. Every disaster regardless its proportion has a precursor which is manifested as a disruption of some environmental parameter such as temperature, humidity, pressure, vibrations and etc. In order to anticipate and monitor those changes, in this paper we propose an overall system for disaster prediction and monitoring, based on wireless sensor network (WSN). Furthermore, we introduce a modified and simplified WSN routing protocol built on the top of the trickle routing algorithm. Routing algorithm was deployed using the bluetooth low energy protocol in order to achieve low power consumption. Performance of the WSN network was analyzed using a real life system implementation. Estimates of the WSN parameters such as battery life time, network size and packet delay are determined. Based on the performance of the WSN network, proposed system can be utilized for disaster monitoring and prediction due to its low power profile and mesh routing feature.

Keywords: bluetooth low energy, disaster prediction, mesh routing protocols, wireless sensor networks

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Authors: Maik Kschischo, Dominik Kahl, Philipp Wendland, Andreas Weber

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Understanding and modelling of real-world complex dynamic systems in biology, engineering and other fields is often made difficult by incomplete knowledge about the interactions between systems states and by unknown disturbances to the system. In fact, most real-world dynamic networks are open systems receiving unknown inputs from their environment. To understand a system and to estimate the state dynamics, these inputs need to be reconstructed from output measurements. Reconstructing the input of a dynamic system from its measured outputs is an ill-posed problem if only a limited number of states is directly measurable. A first requirement for solving this problem is the invertibility of the input-output map. In our work, we exploit the fact that invertibility of a dynamic system is a structural property, which depends only on the network topology. Therefore, it is possible to check for invertibility using a structural invertibility algorithm which counts the number of node disjoint paths linking inputs and outputs. The algorithm is efficient enough, even for large networks up to a million nodes. To understand structural features influencing the invertibility of a complex dynamic network, we analyze synthetic and real networks using the structural invertibility algorithm. We find that invertibility largely depends on the degree distribution and that dense random networks are easier to invert than sparse inhomogeneous networks. We show that real networks are often very difficult to invert unless the sensor nodes are carefully chosen. To overcome this problem, we present a sensor node placement algorithm to achieve invertibility with a minimum set of measured states. This greedy algorithm is very fast and also guaranteed to find an optimal sensor node-set if it exists. Our results provide a practical approach to experimental design for open, dynamic systems. Since invertibility is a necessary condition for unknown input observers and data assimilation filters to work, it can be used as a preprocessing step to check, whether these input reconstruction algorithms can be successful. If not, we can suggest additional measurements providing sufficient information for input reconstruction. Invertibility is also important for systems design and model building. Dynamic models are always incomplete, and synthetic systems act in an environment, where they receive inputs or even attack signals from their exterior. Being able to monitor these inputs is an important design requirement, which can be achieved by our algorithms for invertibility analysis and sensor node placement.

Keywords: data-driven dynamic systems, inversion of dynamic systems, observability, experimental design, sensor node placement

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Authors: Xizhen Zhou, Yanjie Ji

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The charging behavior of drivers provides a reference for the planning and management of charging facilities. Based on the real trajectory data of electric vehicles, this study explored the influence of the surrounding environments of the parking spot on charging decisions. The built environment, the condition of vehicles, and the nearest charging station were all considered. And the mixed binary logit model was used to capture the impact of unobserved heterogeneity. The results show that the number of fast chargers in the charging station, parking price, dwell time, and shopping services all significantly impact the charging decision, while the leisure services, scenic spots, and mileage since the last charging are opposite. Besides, factors related to unobserved heterogeneity include the number of fast chargers, parking and charging prices, residential areas, etc. The interaction effects of random parameters further illustrate the complexity of charging choice behavior. The results provide insights for planning and managing charging facilities.

Keywords: charging decision, trajectory, electric vehicle, infrastructure, mixed logit

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Authors: Amir Mukhtar, Dr. Likun Xia

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An improved, robust and efficient visual target tracking algorithm using particle filtering is proposed. Particle filtering has been proven very successful in estimating non-Gaussian and non-linear problems. In this paper, the particle filter is used with color feature to estimate the target state with time. Color distributions are applied as this feature is scale and rotational invariant, shows robustness to partial occlusion and computationally efficient. The performance is made more robust by choosing the different (YIQ) color scheme. Tracking is performed by comparison of chrominance histograms of target and candidate positions (particles). Color based particle filter tracking often leads to inaccurate results when light intensity changes during a video stream. Furthermore, background subtraction technique is used for size estimation of the target. The qualitative evaluation of proposed algorithm is performed on several real-world videos. The experimental results demonstrate that the improved algorithm can track the moving objects very well under illumination changes, occlusion and moving background.

Keywords: tracking, particle filter, histogram, corner points, occlusion, illumination

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Authors: Sergei Aleinik, Yuri Matveev

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In this paper a novel method for the detection of clipping in speech signals is described. It is shown that the new method has better performance than known clipping detection methods, is easy to implement, and is robust to changes in signal amplitude, size of data, etc. Statistical simulation results are presented.

Keywords: clipping, clipped signal, speech signal processing, digital signal processing

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Authors: Michael Okeke, Andrew Blyth

Abstract:

Supervisory Control And Data Acquisition (SCADA) as the state of the art Industrial Control Systems (ICS) are used in many different critical infrastructures, from smart home to energy systems and from locomotives train system to planes. Security of SCADA systems is vital since many lives depend on it for daily activities and deviation from normal operation could be disastrous to the environment as well as lives. This paper describes how No-Trust-Zone (NTZ) architecture could be incorporated into SCADA Systems in order to reduce the chances of malicious intent. The architecture is made up of two distinctive parts which are; the field devices such as; sensors, PLCs pumps, and actuators. The second part of the architecture is designed following lambda architecture, which is made up of a detection algorithm based on Particle Swarm Optimization (PSO) and Hadoop framework for data processing and storage. Apache Spark will be a part of the lambda architecture for real-time analysis of packets for anomalies detection.

Keywords: industrial control system (ics, no-trust-zone (ntz), particle swarm optimisation (pso), supervisory control and data acquisition (scada), swarm intelligence (SI)

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Authors: Dimitri Golenko-Ginzburg

Abstract:

A CPM network project with deterministic activity durations, in which activities require homogenous resources with fixed capacities, is considered. The problem is to determine the optimal schedule of starting times for all network activities within their maximal allowable limits (in order not to exceed the network's critical time) to minimize the maximum required resources for the project at any point in time. In case when a non-critical activity may start only at discrete moments with the pregiven time span, the problem becomes NP-complete and an optimal solution may be obtained via a look-over algorithm. For the case when a look-over requires much computational time an approximate algorithm is suggested. The algorithm's performance ratio, i.e., the relative accuracy error, is determined. Experimentation has been undertaken to verify the suggested algorithm.

Keywords: resource smoothing problem, CPM network, lookover algorithm, lexicographical order, approximate algorithm, accuracy estimate

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Authors: Zongjie Wang, Zhizhong Guo

Abstract:

While the regular optimal power flow model focuses on a single time scan, the optimization of power systems is typically intended for a time duration with respect to a desired objective function. In this paper, a temporal optimal power flow model for a time period is proposed. To reduce the computation burden needed for calculating temporal optimal power flow, a characteristic optimal power flow model is proposed, which employs different characteristic load patterns to represent the objective function and security constraints. A numerical method based on the interior point method is also proposed for solving the characteristic optimal power flow model. Both the temporal optimal power flow model and characteristic optimal power flow model can improve the systems’ desired objective function for the entire time period. Numerical studies are conducted on the IEEE 14 and 118-bus test systems to demonstrate the effectiveness of the proposed characteristic optimal power flow model.

Keywords: optimal power flow, time period, security, economy

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Authors: Khaing Yadana Swe, Lillie Dewan

Abstract:

At present, the cascade PID control is widely used to control the super-heating temperature (main steam temperature). As the main steam temperature has the characteristics of large inertia, large time-delay, and time varying, etc., conventional PID control strategy can not achieve good control performance. In order to overcome the bad performance and deficiencies of main steam temperature control system, Model Free Adaptive Control (MFAC) P cascade control system is proposed in this paper. By substituting MFAC in PID of the main control loop of the main steam temperature control, it can overcome time delays, non-linearity, disturbance and time variation.

Keywords: model-free adaptive control, cascade control, adaptive control, PID

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Authors: Jadwiga Klukow, Anna Ksykiewicz-Dorota

Abstract:

An analysis of the distribution of nurses’ working time constitutes vital information for the management in planning employment. The objective of the study was to analyze the distribution of nurses’ working time in an emergency department. The study was conducted in an emergency department of a teaching hospital in Lublin, in Southeast Poland. The catalogue of activities performed by nurses was compiled by means of continuous observation. Identified activities were classified into four groups: Direct care, indirect care, coordination of work in the department and personal activities. Distribution of nurses’ working time was determined by work sampling observation (Tippett) at random intervals. The research project was approved by the Research Ethics Committee by the Medical University of Lublin (Protocol 0254/113/2010). On average, nurses spent 31% of their working time on direct care, 47% on indirect care, 12% on coordinating work in the department and 10% on personal activities. The most frequently performed direct care tasks were diagnostic activities – 29.23% and treatment-related activities – 27.69%. The study has provided information on the complexity of performed activities and utilization of nurses’ working time. Enhancing the effectiveness of nursing actions requires working out a strategy for improved management of the time nurses spent at work. Increasing the involvement of auxiliary staff and optimizing communication processes within the team may lead to reduction of the time devoted to indirect care for the benefit of direct care.

Keywords: emergency nurses, nursing care, workload, work sampling

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Authors: Harriet Jane R. Caleja, Joel I. Ballesteros, Florian R. Del Mundo

Abstract:

The dengue fever belongs to the world’s major cause of death, especially in the tropical areas. In the Philippines, the number of dengue cases during the first half of 2015 amounted to more than 50,000. In 2012, the total number of cases of dengue infection reached 132,046 of which 701 patients died. Dengue Nonstructural 1 virus (Dengue NS1 virus) is a recently discovered biomarker for the early detection of dengue virus. It is present in the serum of the dengue virus infected patients even during the earliest stages prior to the formation of dengue virus antibodies. A biosensor for the dengue detection using NS1 virus was developed for faster and accurate diagnostic tool. Biotinylated anti-dengue virus NS1 was used as the receptor for dengue virus NS1. Using the Diffractive Optics Technology (dotTM) technique, real time binding of the NS1 virus to the biotinylated anti-NS1 antibody is observed. The dot®-Avidin sensor recognizes the biotinylated anti-NS1 and this served as the capture molecule to the analyte, NS1 virus. The increase in the signal of the diffractive intensity signifies the binding of the capture and the analyte. The LOD was found to be 3.87 ng/mL while the LOQ is 12.9 ng/mL. The developed biosensor was also found to be specific for the NS1 virus.

Keywords: avidin-biotin, diffractive optics technology, immunosensor, NS1

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Authors: S. Abdulkadir, I. Y. Moh’d, S. U. Kunya, U. Nuruddeen

Abstract:

The basis of any contract formation between the client and contractor is the budgeted cost and the estimated duration of projects. These variables are paramount important to project's sponsor in a construction projects and in assessing the success or viability of construction projects. Despite the availability of various techniques of cost and time control, many projects failed to achieve their initial estimated cost and time. The paper evaluate the inhibiting factors of cost and time control in Nigerian construction practice and comparing the result with the United Kingdom practice as identified by one researcher. The populations of the study are construction professionals within Bauchi and Gombe state, Nigeria, a judgmental sampling employed in determining the size of respondents. Descriptive statistics used in analyzing the data in SPSS. Design change, project fraud and corruption, financing and payment of completed work found to be common among the top five inhibiting factors of cost and time control in the study area. Furthermore, the result had shown some comprising with slight contrast as in the case of United Kingdom practice. Study recommend the adaptation of mitigation measures developed in the UK prior to assessing its effectiveness and so also developing a mitigating measure for other top factors that are not within the one developed in United Kingdom practice. Also, it recommends a wider assessing comparison on the modify inhibiting factors of cost and time control as revealed by the study to cover almost all part of Nigeria.

Keywords: comparison, cost, inhibiting factor, United Kingdom, time

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