Search results for: demonstration wildfire detection and action from space

Authors: B. Siva Kumar Reddy, B. Lakshmi

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Cognitive Radio is a turning out technology that empowers viable usage of the spectrum. Energy Detector-based Sensing is the most broadly utilized spectrum sensing strategy. Besides, it is a lot of generic as receivers does not like any information on the primary user's signals, channel data, of even the sort of modulation. This paper puts forth the execution of energy detection sensing for AM (Amplitude Modulated) signal at 710 KHz, FM (Frequency Modulated) signal at 103.45 MHz (local station frequency), Wi-Fi signal at 2.4 GHz and WiMAX signals at 6 GHz. The OFDM/OFDMA based WiMAX physical layer with convolutional channel coding is actualized utilizing USRP N210 (Universal Software Radio Peripheral) and GNU Radio based Software Defined Radio (SDR). Test outcomes demonstrated the BER (Bit Error Rate) augmentation with channel noise and BER execution is dissected for different Eb/N0 (the energy per bit to noise power spectral density ratio) values.

Keywords: BER, Cognitive Radio, GNU Radio, OFDM, SDR, WiMAX

Procedia PDF Downloads 487

Authors: Kenan Morani, Esra Kaya Ayana

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This study aimed to develop a novel pipeline for COVID-19 detection using a large and rigorously annotated database of computed tomography (CT) images. The pipeline consists of UNet-based segmentation, lung extraction, and a classification part, with the addition of optional slice removal techniques following the segmentation part. In this work, a batch normalization was added to the original UNet model to produce lighter and better localization, which is then utilized to build a full pipeline for COVID-19 diagnosis. To evaluate the effectiveness of the proposed pipeline, various segmentation methods were compared in terms of their performance and complexity. The proposed segmentation method with batch normalization outperformed traditional methods and other alternatives, resulting in a higher dice score on a publicly available dataset. Moreover, at the slice level, the proposed pipeline demonstrated high validation accuracy, indicating the efficiency of predicting 2D slices. At the patient level, the full approach exhibited higher validation accuracy and macro F1 score compared to other alternatives, surpassing the baseline. The classification component of the proposed pipeline utilizes a convolutional neural network (CNN) to make final diagnosis decisions. The COV19-CT-DB dataset, which contains a large number of CT scans with various types of slices and rigorously annotated for COVID-19 detection, was utilized for classification. The proposed pipeline outperformed many other alternatives on the dataset.

Keywords: classification, computed tomography, lung extraction, macro F1 score, UNet segmentation

Procedia PDF Downloads 117

Authors: John McDowall, Crysta Derham

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Broaden and build theory of emotion describes how experiencing positive emotions, such as happiness, broadens our ‘thought-action repertoire’ leading us to be more likely to go out and act on our positive emotions. This results in the building of new relationships, resources and skills, which we can draw on in times of need throughout life. In contrast, the experience of negative emotion is thought to narrow our ‘thought-action repertoire’, leading to specific actions to aid in survival. Three experiments aimed to explore the effect of briefly presented schematic faces (happy, sad, and neutral) on attentional scope using the flanker task. Based on the broaden and build theory it was hypothesised that there would be an increase in reaction time in trials primed with a happy face due to a broadening of attention, leading to increased flanker interference. A decrease in reaction time was predicted for trials primed with a sad face, due to a narrowing of attention leading to less flanker interference. Results lended partial support to the broaden and build hypothesis, with reaction times being slower following happy primes in incongruent flanker trials. Recent research is discussed in regards to potential mediators of the relationship between emotion and attention.

Keywords: emotion, attention, broaden and build, flanker task

Procedia PDF Downloads 465

Authors: Dmitry Yu. Korulkin, Raissa A. Muzychkina, Evgenii N. Kojaev

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In review the generalized data about biological activity of anthraquinone-containing plants and specimens on their basis is presented. Data of traditional medicine, results of bioscreening and clinical researches of specimens are analyzed.

Keywords: anthraquinones, physiologically active substances, phytopreparation, Ramon

Procedia PDF Downloads 362

Authors: Harsh Thakkar, Ganesh Iyer

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In this paper, we survey various user-centered or context-based biomedical health information retrieval systems. We present and discuss the performance of systems submitted in CLEF eHealth 2014 Task 3 for this purpose. We classify and focus on comparing the two most prevalent retrieval models in biomedical information retrieval namely: Language Model (LM) and Vector Space Model (VSM). We also report on the effectiveness of using external medical resources and ontologies like MeSH, Metamap, UMLS, etc. We observed that the LM based retrieval systems outperform VSM based systems on various fronts. From the results we conclude that the state-of-art system scores for MAP was 0.4146, P@10 was 0.7560 and NDCG@10 was 0.7445, respectively. All of these score were reported by systems built on language modeling approaches.

Keywords: clinical document retrieval, concept-based information retrieval, query expansion, language models, vector space models

Procedia PDF Downloads 306

Authors: Marut Phichetvit

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The research objective aims to search information about storytelling and fable associated with fireflies in Amphawa community, in order to design and create a story book which is appropriate for the interests of children in early childhood. This book should help building the development of learning about the natural environment, imagination, and creativity among children, which then, brings about the promotion of the development, conservation and dissemination of cultural values and uniqueness of the Amphawa community. The population used in this study were 30 students in early childhood aged between 6-8 years-old, grade 1-3 from the Demonstration School of Suan Sunandha Rajabhat University. The method used for this study was purposive sampling and the research conducted by the query and analysis of data from both the document and the narrative field tales and fable associated with the fireflies of Amphawa community. Then, using the results to synthesize and create a conceptual design in a form of 8 visual images which were later applied to 1 illustrated children’s book and presented to the experts to evaluate and test this media.

Keywords: children’s illustrated book, fireflies, Amphawa

Procedia PDF Downloads 187

Authors: Isah Mohammed Patizhiko

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This paper aimed at discussing the important role learning resources play in enhancing the teaching and learning of science and technology courses in post primary institution in Nigeria. The paper highlighted the importance learning resources contributed to the effective understanding of the learners. The use of learning resources in the teaching of these courses will encourage teachers to be more exploratory and the learners to have more understanding. In this paper, different range of learning resources particularly common learning resources (learning resources not design primarily for education purposes) to enrich their teaching. The paper also highlighted how ordinary resource can be turned into an educational resource. Recommendations were proffered in the sourcing of learning resources ie from the market, library, institutions, museums, and dump refuse and concluded that good demonstration on the use of resources will engage the learner’s interest and will develop higher level of conceptual understanding in the learning area.

Keywords: enhance, learning, resources, science and technology, teaching

Procedia PDF Downloads 383

Authors: Helga Heylen

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With dogs saving wildlife in New Zealand since 1890 and governments in Africa, Australia and Canada trusting them to give the best results, Conservation Dogs Ireland want to introduce more detection dogs to protect Europe's native wildlife. Conservation detection dogs are fast, portable and endlessly trainable. They are a cost-effective, highly sensitive and non-invasive way to detect protected and invasive species and wildlife disease. Conservation dogs find targets up to 40 times faster than any other method. They give results instantly, with near-perfect accuracy. They can search for multiple targets simultaneously, with no reduction in efficacy The European Red List indicates the decline in biodiversity has been most rapid in the past 50 years, and the risk of extinction never higher. Just two examples of major threats dogs are trained to tackle are: (I)Japanese Knotweed (Fallopia Japonica), not only a serious threat to ecosystems, crops, structures like bridges and roads - it can wipe out the entire value of a house. The property industry and homeowners are only just waking up to the full extent of the nightmare. When those working in construction on the roads move topsoil with a trace of Japanese Knotweed, it suffices to start a new colony. Japanese Knotweed grows up to 7cm a day. It can stay dormant and resprout after 20 years. In the UK, the cost of removing Japanese Knotweed from the London Olympic site in 2012 was around £70m (€83m). UK banks already no longer lend on a house that has Japanese Knotweed on-site. Legally, landowners are now obliged to excavate Japanese Knotweed and have it removed to a landfill. More and more, we see Japanese Knotweed grow where a new house has been constructed, and topsoil has been brought in. Conservation dogs are trained to detect small fragments of any part of the plant on sites and in topsoil. (II)Zebra mussels (Dreissena Polymorpha) are a threat to many waterways in the world. They colonize rivers, canals, docks, lakes, reservoirs, water pipes and cooling systems. They live up to 3 years and will release up to one million eggs each year. Zebra mussels attach to surfaces like rocks, anchors, boat hulls, intake pipes and boat engines. They cause changes in nutrient cycles, reduction of plankton and increased plant growth around lake edges, leading to the decline of Europe's native mussel and fish populations. There is no solution, only costly measures to keep it at bay. With many interconnected networks of waterways, they have spread uncontrollably. Conservation detection dogs detect the Zebra mussel from its early larvae stage, which is still invisible to the human eye. Detection dogs are more thorough and cost-effective than any other conservation method, and will greatly complement and speed up the work of biologists, surveyors, developers, ecologists and researchers.

Keywords: native biodiversity, conservation detection dogs, invasive species, Japanese Knotweed, zebra mussel

Procedia PDF Downloads 181

Authors: Francisco Vidal Vázquez, Pekka Simell, Christian Frilund, Matti Reinikainen, Ilkka Hiltunen, Tim Böltken, Benjamin Andris, Paolo Piermartini

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Carbon capture and utilization (CCU) are one of the key topics in mitigation of CO2 emissions. There are many different technologies that are applied for the production of diverse chemicals from CO2 such as synthetic natural gas, Fischer-Tropsch products, methanol and polymers. Power-to-Gas and Power-to-Liquids concepts arise as a synergetic solution for storing energy and producing value added products from the intermittent renewable energy sources and CCU. VTT is a research and technology development company having energy in transition as one of the key focus areas. VTT has extensive experience in piloting and upscaling of new energy and chemical processes. Recently, VTT has developed and commissioned a Mobile Synthesis Unit (MOBSU) in close collaboration with INERATEC, a spin-off company of Karlsruhe Institute of Technology (KIT, Germany). The MOBSU is a multipurpose synthesis unit for CO2 upgrading to energy carriers and chemicals, which can be transported on-site where CO2 emission and renewable energy are available. The MOBSU is initially used for production of fuel compounds and chemical intermediates by combination of two consecutive processes: reverse Water-Gas Shift (rWGS) and Fischer-Tropsch synthesis (FT). First, CO2 is converted to CO by high-pressure rWGS and then, the CO and H2 rich effluent is used as feed for FT using an intensified reactor technology developed and designed by INERATEC. Chemical equilibrium of rWGS reaction is not affected by pressure. Nevertheless, compression would be required in between rWGS and FT in the case when rWGS is operated at atmospheric pressure. This would also require cooling of rWGS effluent, water removal and reheating. For that reason, rWGS is operated using precious metal catalyst in the MOBSU at similar pressure as FT to simplify the process. However, operating rWGS at high pressures has also some disadvantages such as methane and carbon formation, and more demanding specifications for materials. The main parts of FT module are an intensified reactor, a hot trap to condense the FT wax products, and a cold trap to condense the FT liquid products. The FT synthesis is performed using cobalt catalyst in a novel compact reactor technology with integrated highly-efficient water evaporation cooling cycle. The MOBSU started operation in November 2016. First, the FT module is tested using as feedstock H2 and CO. Subsequently, rWGS and FT modules are operated together using CO2 and H2 as feedstock of ca. 5 Nm3/hr total flowrate. On spring 2017, The MOBSU unit will be integrated together with a direct air capture (DAC) of CO2 unit, and a PEM electrolyser unit at Lappeenranta University of Technology (LUT) premises for demonstration of the SoletAir concept. This would be the first time when synthetic fuels are produced by combination of DAC unit and electrolyser unit which uses solar power for H2 production.

Keywords: CO2 utilization, demonstration, Fischer-Tropsch synthesis, intensified reactors, reverse water-gas shift

Procedia PDF Downloads 278

Authors: O. B. Iskender, K. V. Ling, V. Dubanchet, L. Simonini

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This paper discusses the recent advances and future prospects of spacecraft position and attitude control using Model Predictive Control (MPC). First, the challenges of the space missions are summarized, in particular, taking into account the errors, uncertainties, and constraints imposed by the mission, spacecraft and, onboard processing capabilities. The summary of space mission errors and uncertainties provided in categories; initial condition errors, unmodeled disturbances, sensor, and actuator errors. These previous constraints are classified into two categories: physical and geometric constraints. Last, real-time implementation capability is discussed regarding the required computation time and the impact of sensor and actuator errors based on the Hardware-In-The-Loop (HIL) experiments. The rationales behind the scenarios’ are also presented in the scope of space applications as formation flying, attitude control, rendezvous and docking, rover steering, and precision landing. The objectives of these missions are explained, and the generic constrained MPC problem formulations are summarized. Three key design elements used in MPC design: the prediction model, the constraints formulation and the objective cost function are discussed. The prediction models can be linear time invariant or time varying depending on the geometry of the orbit, whether it is circular or elliptic. The constraints can be given as linear inequalities for input or output constraints, which can be written in the same form. Moreover, the recent convexification techniques for the non-convex geometrical constraints (i.e., plume impingement, Field-of-View (FOV)) are presented in detail. Next, different objectives are provided in a mathematical framework and explained accordingly. Thirdly, because MPC implementation relies on finding in real-time the solution to constrained optimization problems, computational aspects are also examined. In particular, high-speed implementation capabilities and HIL challenges are presented towards representative space avionics. This covers an analysis of future space processors as well as the requirements of sensors and actuators on the HIL experiments outputs. The HIL tests are investigated for kinematic and dynamic tests where robotic arms and floating robots are used respectively. Eventually, the proposed algorithms and experimental setups are introduced and compared with the authors' previous work and future plans. The paper concludes with a conjecture that MPC paradigm is a promising framework at the crossroads of space applications while could be further advanced based on the challenges mentioned throughout the paper and the unaddressed gap.

Keywords: convex optimization, model predictive control, rendezvous and docking, spacecraft autonomy

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Authors: Sergey Ermolin, Olga Ermolin

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A Deep Convolution Neural Network with Triplet Loss is used to identify duplicate images in real-estate advertisements in the presence of image artifacts such as watermarking, cropping, hue/brightness adjustment, and others. The effects of batch normalization, spatial dropout, and various convergence methodologies on the resulting detection accuracy are discussed. For comparative Return-on-Investment study (per industry request), end-2-end performance is benchmarked on both Nvidia Titan GPUs and Intel’s Xeon CPUs. A new real-estate dataset from San Francisco Bay Area is used for this work. Sufficient duplicate detection accuracy is achieved to supplement other database-grounded methods of duplicate removal. The implemented method is used in a Proof-of-Concept project in the real-estate industry.

Keywords: visual recognition, convolutional neural networks, triplet loss, spatial batch normalization with dropout, duplicate removal, advertisement technologies, performance benchmarking

Procedia PDF Downloads 323

Authors: Anwesha Pathak

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With the increasing number of satellites and space debris, space traffic management (STM) becomes crucial. AI can aid in STM by predicting and preventing potential collisions, optimizing satellite trajectories, and managing orbital slots. Governance frameworks need to address the integration of AI algorithms in STM to ensure safe and sustainable satellite activities. AI and governance play significant roles in the context of satellite activities in space. Artificial intelligence (AI) technologies, such as machine learning and computer vision, can be utilized to process vast amounts of data received from satellites. AI algorithms can analyse satellite imagery, detect patterns, and extract valuable information for applications like weather forecasting, urban planning, agriculture, disaster management, and environmental monitoring. AI can assist in automating and optimizing satellite operations. Autonomous decision-making systems can be developed using AI to handle routine tasks like orbit control, collision avoidance, and antenna pointing. These systems can improve efficiency, reduce human error, and enable real-time responsiveness in satellite operations. AI technologies can be leveraged to enhance the security of satellite systems. AI algorithms can analyze satellite telemetry data to detect anomalies, identify potential cyber threats, and mitigate vulnerabilities. Governance frameworks should encompass regulations and standards for securing satellite systems against cyberattacks and ensuring data privacy. AI can optimize resource allocation and utilization in satellite constellations. By analyzing user demands, traffic patterns, and satellite performance data, AI algorithms can dynamically adjust the deployment and routing of satellites to maximize coverage and minimize latency. Governance frameworks need to address fair and efficient resource allocation among satellite operators to avoid monopolistic practices. Satellite activities involve multiple countries and organizations. Governance frameworks should encourage international cooperation, information sharing, and standardization to address common challenges, ensure interoperability, and prevent conflicts. AI can facilitate cross-border collaborations by providing data analytics and decision support tools for shared satellite missions and data sharing initiatives. AI and governance are critical aspects of satellite activities in space. They enable efficient and secure operations, ensure responsible and ethical use of AI technologies, and promote international cooperation for the benefit of all stakeholders involved in the satellite industry.

Keywords: satellite, space debris, traffic, threats, cyber security.

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Authors: Xun Li, Haojie Wang

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Federated learning is a kind of distributed training and centralized training mode, which is of great value in the protection of user privacy. In order to solve the problem that the model is vulnerable to backdoor attacks in federated learning, a backdoor attack detection method based on a weighted k-medoids algorithm is proposed. First of all, this paper collates the update parameters of the client to construct a vector group, then uses the principal components analysis (PCA) algorithm to extract the corresponding feature information from the vector group, and finally uses the improved k-medoids clustering algorithm to identify the normal and backdoor update parameters. In this paper, the backdoor is implanted in the federation learning model through the model replacement attack method in the simulation experiment, and the update parameters from the attacker are effectively detected and removed by the defense method proposed in this paper.

Keywords: federated learning, backdoor attack, PCA, k-medoids, backdoor defense

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Authors: Elham Kiyani

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In this paper, we first introduce the concept of Q-efficient solutions in a real linear space not necessarily endowed with a topology, where Q is some nonempty (not necessarily convex) set. We also used the scalarization technique including the Gerstewitz function generated by a nonconvex set to characterize these Q-efficient solutions. The algebraic concepts of interior and closure are useful to study optimization problems without topology. Studying nonconvex vector optimization is valuable since topological interior is equal to algebraic interior for a convex cone. So, we use the algebraic concepts of interior and closure to define Q-weak efficient solutions and Q-Henig proper efficient solutions of set-valued optimization problems, where Q is not a convex cone. Optimization problems with set-valued maps have a wide range of applications, so it is expected that there will be a useful analytical tool in optimization theory for set-valued maps. These kind of optimization problems are closely related to stochastic programming, control theory, and economic theory. The paper focus on nonconvex problems, the results are obtained by assuming generalized non-convexity assumptions on the data of the problem. In convex problems, main mathematical tools are convex separation theorems, alternative theorems, and algebraic counterparts of some usual topological concepts, while in nonconvex problems, we need a nonconvex separation function. Thus, we consider the Gerstewitz function generated by a general set in a real linear space and re-examine its properties in the more general setting. A useful approach for solving a vector problem is to reduce it to a scalar problem. In general, scalarization means the replacement of a vector optimization problem by a suitable scalar problem which tends to be an optimization problem with a real valued objective function. The Gerstewitz function is well known and widely used in optimization as the basis of the scalarization. The essential properties of the Gerstewitz function, which are well known in the topological framework, are studied by using algebraic counterparts rather than the topological concepts of interior and closure. Therefore, properties of the Gerstewitz function, when it takes values just in a real linear space are studied, and we use it to characterize Q-efficient solutions of vector problems whose image space is not endowed with any particular topology. Therefore, we deal with a constrained vector optimization problem in a real linear space without assuming any topology, and also Q-weak efficient and Q-proper efficient solutions in the senses of Henig are defined. Moreover, by means of the Gerstewitz function, we provide some necessary and sufficient optimality conditions for set-valued vector optimization problems.

Keywords: algebraic interior, Gerstewitz function, vector closure, vector optimization

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Authors: Seham Alsaif, Susan Wray

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Obesity is a worldwide disorder influencing women’s health and childbearing. There is a close relation between obesity and pregnancy related complications. Dyslipidemia and adipokine dysregulation are core environmental changes that may mechanistically link these complications with obesity in pregnant women. We have previously found that visfatin has a relaxant effect on mouse, rat and human myometrial contractility. We hypothesised that visfatin inhibits mouse myometrial contractility through the NAD+ pathway. This study was designed to examine the mechanism of action of visfatin on myometrial contractility. To examine the NAD+ pathway, FK866 which is a potent inhibitor of NAD+ biosynthesis was used. Methods: Myometrial strips from term pregnant mice were dissected, superfused with physiological saline and the effects of visfatin (10nM) on oxytocin-induced contractions (0.5nM) alone and after the infusion of FK866 (10uM) were studied. After regular contractions were established, contractility was examined for control (100%) and test response at 37 °C for 10 min each. Results: FK866 was found to inhibit the effect of visfatin on myometrial contractility (the AUC increased from 89±2% of control, P=0.0009 for visfatin alone to 97±4% of control, P>0.05 for visfatin combined with FK866, n=8). In conclusion, NAD+ pathway appears to be involved in the mechanism of action of visfatin on mouse myometrium. This could have a role in making new targets to prevent obesity-related complications.

Keywords: myometrium, obesity, oxytocin, pregnancy, visfatin

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Authors: Jin Lin, Shouxiang Lu, Kim Meow Liew

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The requirement for the long-term mission of the submarine and spacecraft has made the removal of CO₂ and trace CO the critical technology to ensure the health and life of the crews. In this work, CuMnCe, a metal oxide catalyst, supporting K₂CO₃ sorbent was prepared by the wet-solid state impregnation method to realize the integrated CO and CO₂ removal, which might also reduce the volume/mass load of the purification units in the limited space. The as-prepared samples with different addition amount of K₂CO₃ were tested using the fixed bed reactor to reveal the CO oxidation and CO₂ absorption behavior. And the regeneration and stability experiments were also conducted. The results showed that the samples realized the catalyst and sorbent integration to capture CO and CO₂ at the same time. The addition amount of the sorbent had a weak influence on the CO oxidation performance. While the addition amount affected the CO₂ sorption efficiency and capacity significantly. Meanwhile, the presence of water vapor could reduce the CO oxidation activity of the samples similarly, whether with K2CO3 sorbent addition or not. Furtherly, regeneration and stability experiment results showed that the samples after 3-5 times regeneration exhibited almost the same performance of CO and CO₂ removal. Summarily, CuMnCe catalyst supporting K₂CO₃ sorbent could be a good attempt to control CO and CO₂ pollutants generated from the daily equipment running and staff breathing in the confined space such as submarine and spacecraft.

Keywords: CO oxidation, CO₂ absorptio, potassium carbonate, CuMnCe metal oxide, confined space

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Authors: Ling Liyun

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In the field of contemporary architecture, complex forms of architectural works continue to emerge in the world, along with some new terminology emerged: digital architecture, parametric design, algorithm generation, building information modeling, CNC construction and so on. Architects gradually mastered the new skills of mathematical logic in the form of exploration, virtual simulation, and the entire design and coordination in the construction process. Digital construction technology has a greater degree in controlling construction, and ensure its accuracy, creating a series of new construction techniques. As a result, the use of digital technology is an improvement and expansion of the practice of digital architecture design revolution. We worked by reading and analyzing information about the digital architecture development process, a large number of cases, as well as architectural design and construction as a whole process. Thus current developments were introduced and discussed in our paper, such as architectural discourse, design theory, digital design models and techniques, material selecting, as well as artificial intelligence space design. Our paper also pays attention to the representative three cases of digital design and construction experiment at great length in detail to expound high-informatization, high-reliability intelligence, and high-technique in constructing a humane space to cope with the rapid development of urbanization. We concluded that the opportunities and challenges of the shift existed in architectural paradigms, such as the cooperation methods, theories, models, technologies and techniques which were currently employed in digital design research and digital praxis. We also find out that the innovative use of space can gradually change the way people learn, talk, and control information. The past two decades, digital technology radically breaks the technology constraints of industrial technical products, digests the publicity on a particular architectural style (era doctrine). People should not adapt to the machine, but in turn, it’s better to make the machine work for users.

Keywords: artificial intelligence, collaboration, digital architecture, digital design theory, material selection, space construction

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Authors: Andra Yount

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The purpose of this research project is to understand how focusing on movement can help English language learners acquire better reading, writing, and speaking skills. More specifically, this case study tests how Laban movement analysis, a tool often used in dance and physical education classes, contributes to advanced-level high school students’ English language acquisition at an international Swiss boarding school. This article shares theoretical bases for and findings from a teaching experiment in which LMA categories (body, effort, space, and shape) were adapted and introduced to students to encourage basic language acquisition and also cultural awareness and sensitivity. As part of the participatory action research process, data collection included pseudonym-protected questionnaires and written/video-taped responses to LMA language and task prompts. Responses from 43 participants were evaluated to determine the efficacy of using this system. Participants (ages 16-19) were enrolled in advanced English as an Additional Language (EAL) courses at a private, co-educational Swiss international boarding school. Final data analysis revealed that drawing attention to movement using LMA language as a stimulus creates better self-awareness and understanding/retention of key literary concepts and vocabulary but does not necessarily contribute to greater cultural sensitivity or eliminate the use of problematic (sexist, racist, or classist) language. Possibilities for future exploration and development are also explored.

Keywords: dance, English, Laban, pedagogy

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Authors: A. Sreedevi, G. Anantaramu

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The present space research organizations are striving towards the development of lighter, smaller, more efficient, low cost, and highly reliable power supply. Switch mode power supplies (SMPS) overcome the demerits of linear power supplies such as low efficiency, difficulties in thermal management, and in boosting the output voltage. Space applications require a constant DC voltage to supply its load. As the load varies, the battery terminal voltage tends to vary accordingly. To avoid this variation in the load terminal voltage, a DC-DC regulator is required. The conventional regulator for space applications is isolated boost topology. The proposed topology uses an interleaved push-pull converter with a current doubler secondary to reduce the EMI issues and increase efficiency. The proposed topology uses a floating technique where the converter derives power from the battery and generates only the voltage that is required to fill the gap between the bus and the battery voltage. The direct voltage sense and current loop provide tight regulation of output and better stability. Converter is designed with 50 kHz switching frequency using UC 1825 PWM controller employing both voltage and peak current mode control. Experimental tests have been carried out on the converter under different input and load conditions to validate the design. The experimental results showed that the efficiency was greater than 91%. Stability analysis is done using venable stability analyzer.

Keywords: push pull converter, current doubler, converter, PWM control

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Authors: Faisal Alshammari, Abdulmajid Addali, Mosab Alrashed, Taihiret Alhashan

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The application of acoustic emission techniques is gaining popularity, as it can monitor the condition of gears and bearings and detect early symptoms of a defect in the form of pitting, wear, and flaking of surfaces. Early detection of these defects is essential as it helps to avoid major failures and the associated catastrophic consequences. Signal processing techniques are required for early defect detection – in this article, a time domain technique called the Energy Index (EI) is used. This article presents an investigation into the Energy Index’s effectiveness to detect early-stage defect initiation and deterioration, and compares it with the common r.m.s. index, Kurtosis, and the Kolmogorov-Smirnov statistical test. It is concluded that EI is a more effective technique for monitoring defect initiation and development than other statistical parameters.

Keywords: acoustic emission, signal processing, kurtosis, Kolmogorov-Smirnov test

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Authors: Chamika Chiran Perera, Dananjaya Perera, Chirath Dasanayake, Banuka Athuraliya

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Male infertility is a major problem in the world, and it is a neglected and sensitive health issue in Sri Lanka. It can be determined by analyzing human semen samples. Sperm motility is one of many factors that can evaluate male’s fertility potential. In Sri Lanka, this analysis is performed manually. Manual methods are time consuming and depend on the person, but they are reliable and it can depend on the expert. Machine learning and deep learning technologies are currently being investigated to automate the spermatozoa motility analysis, and these methods are unreliable. These automatic methods tend to produce false positive results and false detection. Current automatic methods support different techniques, and some of them are very expensive. Due to the geographical variance in spermatozoa characteristics, current automatic methods are not reliable for motility analysis in Sri Lanka. The suggested system, DeepMotile, is to explore a method to analyze motility of human spermatozoa automatically and present it to the andrology laboratories to overcome current issues. DeepMotile is a novel deep learning method for analyzing spermatozoa motility parameters in the Sri Lankan population. To implement the current approach, Sri Lanka patient data were collected anonymously as a dataset, and glass slides were used as a low-cost technique to analyze semen samples. Current problem was identified as microscopic object detection and tackling the problem. YOLOv5 was customized and used as the object detector, and it achieved 94 % mAP (mean average precision), 86% Precision, and 90% Recall with the gathered dataset. StrongSORT was used as the object tracker, and it was validated with andrology experts due to the unavailability of annotated ground truth data. Furthermore, this research has identified many potential ways for further investigation, and andrology experts can use this system to analyze motility parameters with realistic accuracy.

Keywords: computer vision, deep learning, convolutional neural networks, multi-target tracking, microscopic object detection and tracking, male infertility detection, motility analysis of human spermatozoa

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Authors: Suzanne Strauss, Leandi Steenkamp

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The Finnish symphonic metal band Nightwish is the brainchild of songwriter and lyricist TuomasHolopainen and the band recorded their first demonstration recording in 1996. The band has since produced nine full-length studio albums, the most recent being the 2020 album Human. :||: Nature., and has reached massive international success. The band is well known for songs about fantasy and escapism and employs many sonic, visual and branding tools and techniques to communicate these constructs to the audience. Among these, is the band’s creation of the so-called “Nightwish world and mythology” with a set of recurring characters and narratives which, in turn, creates a psychological anchor and safe space for Nightwish fans around the globe. Nature and the reverence of nature are central themes in Nightwish’s self-created mythology.Swiss psychologist Carl Jung’s theory of the collective unconscious identified a mysterious reservoir of psychological constructs common to all people, being derived from ancestral memory and experience, common to all humankind, and distinct from the individual’s personal unconscious. Furthermore, he defined archetypes as timeless collective patterns and images that springs forth from the collective unconscious. Archetypes can be actualized when they enter consciousness as images in interaction with the outside world. Archetypal patterns or images can manifest in different ways across world cultures, but follow common patterns, also known as archetypal themes and symbols. The Jungian approach to the psyche places great emphasis on nature, positing a direct link betweenthe concept of wholeness and responsible care for nature and the environment.In our proposed paper, we examine, by means of thematic content analysis, how Nightwish makes use of archetypal themes and symbols referring to nature and the environment in selected songs from their ninth full-length album Human. II Nature. Furthermore, we argue that the longing for and reverence of nature in selected Nightwish songs may serve as a type of “social intervention” and social critique on modern capitalist society. The type of social critique that the band offers is generally connoted intertextually and is not equally explicit in their songs. The band uses a unique combination of escapism, fantasy, and nature narratives to inspire a sense of wonder, enchantment, and magic in the listener. In this way, escapism, fantasy, and nature serve as postmodern frames of reference that aim to “re-enchant” the disenchanted and de-spiritualized. In this way, re-enchantment could also refer to spiritual and/or psychological healing and rebirth.

Keywords: archetypes, metal music, nature, Nightwish, social interventions

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Authors: Sabin Stoica

Abstract:

In this paper the theoretical challenges in the study of neutrinoless double beta decay are reviewed. Then, new upper limits of the neutrino mass parameters in the case of three isotopes are derived; 48Ca, 76Ge, and 82Se, assuming two possible mechanisms of occurrence of this nuclear process, namely the exchange of i) light left-handed neutrinos and ii) heavy right-handed neutrinos, between two nucleons inside the nucleus. The derivation is based on accurate calculations of the phase space factors and nuclear matrix elements performed with new high-performance computer codes, which are described in more detail in recent publications. These results are useful both for a better understanding of the scale of neutrino absolute mass and for the planning of future double beta decay experiments.

Keywords: double beta decay, neutrino properties, nuclear matrix elements, phase space factors

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Authors: Hossein Jafari, Xiangfang Li, Lijun Qian, Alexander Aved, Timothy Kroecker

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Traditionally in sensor networks and recently in the Internet of Things, numerous heterogeneous sensors are deployed in distributed manner to monitor a phenomenon that often can be model by an underlying stochastic process. The big time-series data collected by the sensors must be analyzed to detect change in the stochastic process as quickly as possible with tolerable false alarm rate. However, sensors may have different accuracy and sensitivity range, and they decay along time. As a result, the big time-series data collected by the sensors will contain uncertainties and sometimes they are conflicting. In this study, we present a framework to take advantage of Evidence Theory (a.k.a. Dempster-Shafer and Dezert-Smarandache Theories) capabilities of representing and managing uncertainty and conflict to fast change detection and effectively deal with complementary hypotheses. Specifically, Kullback-Leibler divergence is used as the similarity metric to calculate the distances between the estimated current distribution with the pre- and post-change distributions. Then mass functions are calculated and related combination rules are applied to combine the mass values among all sensors. Furthermore, we applied the method to estimate the minimum number of sensors needed to combine, so computational efficiency could be improved. Cumulative sum test is then applied on the ratio of pignistic probability to detect and declare the change for decision making purpose. Simulation results using both synthetic data and real data from experimental setup demonstrate the effectiveness of the presented schemes.

Keywords: CUSUM, evidence theory, kl divergence, quickest change detection, time series data

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Authors: A. Biran, P. Sobhe Bidari, A. Almazroe, V. Lakshminarayanan, K. Raahemifar

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Diabetic Retinopathy (DR) is a severe retinal disease which is caused by diabetes mellitus. It leads to blindness when it progress to proliferative level. Early indications of DR are the appearance of microaneurysms, hemorrhages and hard exudates. In this paper, an automatic algorithm for detection of DR has been proposed. The algorithm is based on combination of several image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Also, Support Vector Machine (SVM) Classifier is used to classify retinal images to normal or abnormal cases including non-proliferative or proliferative DR. The proposed method has been tested on images selected from Structured Analysis of the Retinal (STARE) database using MATLAB code. The method is perfectly able to detect DR. The sensitivity specificity and accuracy of this approach are 90%, 87.5%, and 91.4% respectively.

Keywords: diabetic retinopathy, fundus images, STARE, Gabor filter, support vector machine

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Authors: Carlos H. Cuadra, Nobuhiro Shimoi

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Application of piezoelectric sensors to detect structural damage due to seismic action on building structures is investigated. Plate-type piezoelectric sensor was developed and proposed for this task. A film-type piezoelectric sheet was attached on a steel plate and covered by a layer of glass. A special glue is used to fix the glass. This glue is a silicone that requires the application of ultraviolet rays for its hardening. Then, the steel plate was set up at a steel column-beam joint of a test specimen that was subjected to bending moment when test specimen is subjected to monotonic load and cyclic load. The structural behavior of test specimen during cyclic loading was verified using a finite element model, and it was found good agreement between both results on load-displacement characteristics. The cross section of steel elements (beam and column) is a box section of 100 mm×100 mm with a thin of 6 mm. This steel section is specified by the Japanese Industrial Standards as carbon steel square tube for general structure (STKR400). The column and beam elements are jointed perpendicularly using a fillet welding. The resulting test specimen has a T shape. When large deformation occurs the glass plate of the sensor device cracks and at that instant, the piezoelectric material emits a voltage signal which would be the indicator of a certain level of deformation or damage. Applicability of this piezoelectric sensor to detect structural damages was verified; however, additional analysis and experimental tests are required to establish standard parameters of the sensor system.

Keywords: piezoelectric sensor, static cyclic test, steel structure, seismic damages

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Authors: Laura Bickel

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This paper aims to investigate to what extent Merleau-Ponty’s philosophy of body memory serves as a viable resource for the enactive approach to cognitive science and its first-person experience-based research on ‘recurrent depressive disorder’ coded F33 in ICD-10. In pursuit of this goal, the analysis begins by revisiting the neuroreductive paradigm. This paradigm serves biological psychiatry to explain the condition of vital contact in terms of underlying neurophysiological mechanisms. It is demonstrated that the neuroreductive model cannot sufficiently account for the depressed person’s episodical withdrawal in causal terms. The analysis of the irregular loss of vital resonance requires integrating the body as the subject of experience and its phenomenological time. Then, it is shown that the enactive approach to depression as disordered sense-making is a promising alternative. The enactive model of perception implies that living beings do not register pre-existing meaning ‘out there’ but unfold ‘sense’ in their action-oriented response to the world. For the enactive approach, Husserl’s passive synthesis of inner time consciousness is fundamental for what becomes perceptually present for action. It seems intuitive to bring together the enactive approach to depression with the long-standing view in phenomenological psychopathology that explains the loss of vital contact by appealing to the disruption of the temporal structure of consciousness. However, this paper argues that the disruption of the temporal structure is not justified conceptually. Instead, one may integrate Merleau-Ponty’s concept of the past as the unconscious into the enactive approach to depression. From this perspective, the living being’s experiential and biological past inserts itself in the form of habit and bodily skills and ensures action-oriented responses to the environment. Finally, it is concluded that the depressed person’s withdrawal indicates the impairment of this application process. The person suffering from F33 cannot actualize sedimented meaning to respond to the valences and tasks of a given situation.

Keywords: depression, enactivism, neuroreductionsim, phenomenology, temporality

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Authors: Ugoh Kelechi Melford, Anene O.

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Introduction: Evidence has shown that there are increasing rates of new HIV and other STI infections occurring among Men who have Sex with Men (MSM) in Nigeria, with the prevalence 3 times higher than the general population as reported by the 2011 National Integrated Bio Behavioral Surveillance Survey. The poor state of health care and support services hinders our effort to control the high rates of these new infections among MSM. Methods: The Initiative for Improved Male Health (IMH-Initiative) works to provide a safe space for young MSM living with HIV to access comprehensive palliative care and support, as well as referrals for other services through drama and dance competitions. An STI assessment was conducted in IMH-Initiative’s Community Center in Calabar, for gay men and other MSM. An STI history was conducted for all clients who visited the community clinic specifically for HCT and STI counseling and referrals within a 5 month period, and their data were collated. Results: 61 MSM were diagnosed, and reported the following in the last 6 months. 49 where living with HIV. 46 had previous histories of untreated anal warts. 20 had previous histories of treated Gonorrhea by self-medication and herbs. 21 had untreated boils and rashes around the genitals. 10 clients where living with HIV, and reported untreated penile and rectal gonorrhea. All clients indicated that there were not comfortable discussing STI infections with staff of public hospitals. Conclusion: It is evident that a reasonable number of STI infections among MSM are not completely treated or ignored. This thereby increases the individual’s risk of HIV infection, and cripples HIV prevention programming in Nigeria. HIV programs targeting MSM must incorporate STI syndromic management, so as to increase access to non-stigmatized diagnosis and treatment of STIs. Also, access to STI drugs for clients cannot be overemphasized.

Keywords: MSM, IBBSS, STI, IMH

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Authors: Rajasekar Elangopandian, Anand Shanmugam

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In order to reduce the cost of launching satellite and payloads to the orbit this project envisages some immense combined technology. This new technology in space odyssey contains literally four concepts. The first mode in this innovation is flight mission characteristics which, says how the mission will induct. The conventional technique of magnetic levitation will help us to produce the initial thrust. The name states reusable launch vehicle shows its viability of reuseness. The flight consists miniature rocket which produces the required thrust and the two JATO (jet assisted takeoff) boosters which gives the initial boost for the vehicle. The vehicle ostensibly looks like an airplane design and will be located on the super conducting rail track. When the high power electric current given to the rail track, the vehicle starts floating as per the principle of magnetic levitation. If the flight reaches the particular takeoff distance the two boosters gets starts and will give the 48KN thrust each. Obviously it`ll follow the vertical path up to the atmosphere end/start to space. As soon as it gets its speed the two boosters will cutoff. Once it reaches the space the inbuilt spacecraft keep the satellite in the desired orbit. When the work finishes, the apogee motors gives the initial kick to the vehicle to come in to the earth’s atmosphere with 22N thrust and automatically comes to the ground by following the free fall, the help of gravitational force. After the flying region it makes the spiral flight mode then gets landing where the super conducting levitated rail track located. It will catch up the vehicle and keep it by changing the poles of magnets and varying the current. Initial cost for making this vehicle might be high but for the frequent usage this will reduce the launch cost exactly half than the now-a-days technology. The incorporation of such a mechanism gives `hybrid` and the reusability gives `reusable launch vehicle` and ultimately Hybrid reusable launch vehicle.

Keywords: the two JATO (jet assisted takeoff) boosters, magnetic levitation, 48KN thrust each, 22N thrust and automatically comes to the ground

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Authors: Manutchanok Jongprasithporn, Rawiphorn Srivilai, Paweena Pongsopha

Abstract:

Fall is the most serious accident leading to increased unintentional injuries and mortality. Falls are not only the cause of suffering and functional impairments to the individuals, but also the cause of increasing medical cost and days away from work. The early detection of falls could be an advantage to reduce fall-related injuries and consequences of falls. Smartphones, embedded accelerometer, have become a common device in everyday life due to decreasing technology cost. This paper explores a physical activity monitoring and fall detection application in smartphones which is a non-invasive biomedical device to determine physical activities and fall event. The combination of application and sensors could perform as a biomedical sensor to monitor physical activities and recognize a fall. We have chosen Android-based smartphone in this study since android operating system is an open-source and no cost. Moreover, android phone users become a majority of Thai’s smartphone users. We developed Thai 3 Axis (TH3AX) as a physical activities and fall detection application which included command, manual, results in Thai language. The smartphone was attached to right hip of 10 young, healthy adult subjects (5 males, 5 females; aged< 35y) to collect accelerometer and gyroscope data during performing physical activities (e.g., walking, running, sitting, and lying down) and falling to determine threshold for each activity. Dependent variables are including accelerometer data (acceleration, peak acceleration, average resultant acceleration, and time between peak acceleration). A repeated measures ANOVA was performed to test whether there are any differences between DVs’ means. Statistical analyses were considered significant at p<0.05. After finding threshold, the results were used as training data for a predictive model of activity recognition. In the future, accuracies of activity recognition will be performed to assess the overall performance of the classifier. Moreover, to help improve the quality of life, our system will be implemented with patients and elderly people who need intensive care in hospitals and nursing homes in Thailand.

Keywords: activity recognition, accelerometer, fall, gyroscope, smartphone

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