Search results for: evidence based practice

Authors: Marco Frieslaar, Bing Chu, Eric Rogers

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Stroke is a devastating illness that is the second biggest cause of death in the world (after heart disease). Where it does not kill, it leaves survivors with debilitating sensory and physical impairments that not only seriously harm their quality of life, but also cause a high incidence of severe depression. It is widely accepted that early intervention is essential for recovery, but current rehabilitation techniques largely favor hospital-based therapies which have restricted access, expensive and specialist equipment and tend to side-step the emotional challenges. In addition, there is insufficient funding available to provide the long-term assistance that is required. As a consequence, recovery rates are poor. The relatively unexplored solution is to develop therapies that can be harnessed in the home and are formulated from technologies that already exist in everyday life. This would empower individuals to take control of their own improvement and provide choice in terms of when and where they feel best able to undertake their own healing. This research seeks to identify how effective post-stroke, rehabilitation therapy can be applied to upper limb mobility, within the physical context of a home rather than a hospital. This is being achieved through the design and construction of an automation scheme, based on iterative learning control and the Riener muscle model, that has the ability to adapt to the user and react to their level of fatigue and provide tangible physical recovery. It utilizes a SMART Phone and laptop to construct an iterative learning control (ILC) system, that monitors upper arm movement in three dimensions, as a series of exercises are undertaken. The equipment generates functional electrical stimulation to assist in muscle activation and thus improve directional accuracy. In addition, it monitors speed, accuracy, areas of motion weakness and similar parameters to create a performance index that can be compared over time and extrapolated to establish an independent and objective assessment scheme, plus an approximate estimation of predicted final outcome. To further extend its assessment capabilities, nerve conduction velocity readings are taken by the software, between the shoulder and hand muscles. This is utilized to measure the speed of response of neuron signal transfer along the arm and over time, an online indication of regeneration levels can be obtained. This will prove whether or not sufficient training intensity is being achieved even before perceivable movement dexterity is observed. The device also provides the option to connect to other users, via the internet, so that the patient can avoid feelings of isolation and can undertake movement exercises together with others in a similar position. This should create benefits not only for the encouragement of rehabilitation participation, but also an emotional support network potential. It is intended that this approach will extend the availability of stroke recovery options, enable ease of access at a low cost, reduce susceptibility to depression and through these endeavors, enhance the overall recovery success rate.

Keywords: home-based therapy, iterative learning control, Riener muscle model, SMART phone, stroke rehabilitation

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Authors: Hussain Sajid, Jung-Hun Shin, Kum-Won Cho

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Image super-resolution is the most common computer vision problem with many important applications. Generative adversarial networks (GANs) have promoted remarkable advances in single-image super-resolution (SR) by recovering photo-realistic images. However, high memory requirements of GAN-based SR (mainly generators) lead to performance degradation and increased energy consumption, making it difficult to implement it onto resource-constricted devices. To relieve such a problem, In this paper, we introduce an optimized and highly efficient architecture for SR-GAN (generator) model by utilizing model compression techniques such as Knowledge Distillation and pruning, which work together to reduce the storage requirement of the model also increase in their performance. Our method begins with distilling the knowledge from a large pre-trained model to a lightweight model using different loss functions. Then, iterative weight pruning is applied to the distilled model to remove less significant weights based on their magnitude, resulting in a sparser network. Knowledge Distillation reduces the model size by 40%; pruning then reduces it further by 18%. To accelerate the learning process, we employ the Horovod framework for distributed training on a cluster of 2 nodes, each with 8 GPUs, resulting in improved training performance and faster convergence. Experimental results on various benchmarks demonstrate that the proposed compressed model significantly outperforms state-of-the-art methods in terms of peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and image quality for x4 super-resolution tasks.

Keywords: single-image super-resolution, generative adversarial networks, knowledge distillation, pruning

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Authors: Despoina Chochtoula, Aristidis Ilias, Yannis Stamatiou

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Modbus is a protocol that enables the communication among devices which are connected to the same network. This protocol is, often, deployed in connecting sensor and monitoring units to central supervisory servers in Supervisory Control and Data Acquisition, or SCADA, systems. These systems monitor critical infrastructures, such as factories, power generation stations, nuclear power reactors etc. in order to detect malfunctions and ignite alerts and corrective actions. However, due to their criticality, SCADA systems are vulnerable to attacks that range from simple eavesdropping on operation parameters, exchanged messages, and valuable infrastructure information to malicious modification of vital infrastructure data towards infliction of damage. Thus, the SCADA research community has been active over strengthening SCADA systems with suitable data protection mechanisms based, to a large extend, on cryptographic methods for data encryption, device authentication, and message integrity protection. However, due to the limited computation power of many SCADA sensor and embedded devices, the usual public key cryptographic methods are not appropriate due to their high computational requirements. As an alternative, Elliptic Curve Cryptography has been proposed, which requires smaller key sizes and, thus, less demanding cryptographic operations. Until now, however, no such implementation has been proposed in the SCADA literature, to the best of our knowledge. In order to fill this gap, our methodology was focused on integrating Modbus, a frequently used SCADA communication protocol, with Elliptic Curve based cryptography and develop a server/client application to demonstrate the proof of concept. For the implementation we deployed two C language libraries, which were suitably modify in order to be successfully integrated: libmodbus (https://github.com/stephane/libmodbus) and ecc-lib https://www.ceid.upatras.gr/webpages/faculty/zaro/software/ecc-lib/). The first library provides a C implementation of the Modbus/TCP protocol while the second one offers the functionality to develop cryptographic protocols based on Elliptic Curve Cryptography. These two libraries were combined, after suitable modifications and enhancements, in order to give a modified version of the Modbus/TCP protocol focusing on the security of the data exchanged among the devices and the supervisory servers. The mechanisms we implemented include key generation, key exchange/sharing, message authentication, data integrity check, and encryption/decryption of data. The key generation and key exchange protocols were implemented with the use of Elliptic Curve Cryptography primitives. The keys established by each device are saved in their local memory and are retained during the whole communication session and are used in encrypting and decrypting exchanged messages as well as certifying entities and the integrity of the messages. Finally, the modified library was compiled for the Android environment in order to run the server application as an Android app. The client program runs on a regular computer. The communication between these two entities is an example of the successful establishment of an Elliptic Curve Cryptography based, secure Modbus wireless communication session between a portable device acting as a supervisor station and a monitoring computer. Our first performance measurements are, also, very promising and demonstrate the feasibility of embedding Elliptic Curve Cryptography into SCADA systems, filling in a gap in the relevant scientific literature.

Keywords: elliptic curve cryptography, ICT security, modbus protocol, SCADA, TCP/IP protocol

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Authors: Minghui Zhang, Sirine Fkaier, Sabri Fernana, Svetlana Kiseleva, Denis Kiselev

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The real-time identification of bacteria and fungi is difficult because they emit much weaker signals than pollen. In 2020, Plair developed Rapid-E+, which extends abilities of Rapid-E to detect smaller bioaerosols such as bacteria and fungal spores with diameters down to 0.3 µm, while keeping the similar or even better capability for measurements of large bioaerosols like pollen. Rapid-E+ enables simultaneous measurements of (1) time-resolved, polarization and angle dependent Mie scattering patterns, (2) fluorescence spectra resolved in 16 channels, and (3) fluorescence lifetime of individual particles. Moreover, (4) it provides 2D Mie scattering images which give the full information on particle morphology. The parameters of every single bioaerosol aspired into the instrument are subsequently analysed by machine learning. Firstly, pure species of microbes, e.g., Bacillus subtilis (a species of bacteria), and Penicillium chrysogenum (a species of fungal spores), were aerosolized in a bioaerosol chamber for Rapid-E+ training. Afterwards, we tested microbes under different concentrations. We used several steps of data analysis to classify and identify microbes. All single particles were analysed by the parameters of light scattering and fluorescence in the following steps. (1) They were treated with a smart filter block to get rid of non-microbes. (2) By classification algorithm, we verified the filtered particles were microbes based on the calibration data. (3) The probability threshold (defined by the user) step provides the probability of being microbes ranging from 0 to 100%. We demonstrate how Rapid-E+ identified simultaneously microbes based on the results of Bacillus subtilis (bacteria) and Penicillium chrysogenum (fungal spores). By using machine learning, Rapid-E+ achieved identification precision of 99% against the background. The further classification suggests the precision of 87% and 89% for Bacillus subtilis and Penicillium chrysogenum, respectively. The developed algorithm was subsequently used to evaluate the performance of microbe classification and quantification in real-time. The bacteria and fungi were aerosolized again in the chamber with different concentrations. Rapid-E+ can classify different types of microbes and then quantify them in real-time. Rapid-E+ enables classifying different types of microbes and quantifying them in real-time. Rapid-E+ can identify pollen down to species with similar or even better performance than the previous version (Rapid-E). Therefore, Rapid-E+ is an all-in-one instrument which classifies and quantifies not only pollen, but also bacteria and fungi. Based on the machine learning platform, the user can further develop proprietary algorithms for specific microbes (e.g., virus aerosols) and other aerosols (e.g., combustion-related particles that contain polycyclic aromatic hydrocarbons).

Keywords: bioaerosols, laser-induced fluorescence, Mie-scattering, microorganisms

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Authors: Enayatollah Yazdani

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Globalization is the most significant change in today’s world. It has caused remarkable growth in different aspects of human life. Such a strong contribution to the development would not have occurred without the role that each country and particularly great powers play in the globalization process. Among those powers is China, whose role in the globalization trend is growing fast. With its rapid economic and technological development, China has moved from a regional economic power to a global powerhouse. Accordingly, China has been supporting the development of global infrastructure through new initiatives and institutions such as the Asia Infrastructure Investment Bank and the New Development Bank, among them, the most ambitious manifestation of these efforts is China Belt and Road Initiative (BRI). BRI is seen as an important vehicle that helps China to play a more proactive role in the globalization process. China started Belt and Road initiative as a global drive in more than 65 (now more than 140) countries in Asia, the Middle East, Central Asia, Latin America, Africa, and Europe, offering the world a unique state of bigger openness, integration, and interdependence with a comprehensive approach to shared development, shared future, and shared opportunities. As a result, one can say that BRI is an attempt by China to promote international cooperation and enhance globalization. However, in this regard, China may face some challenges as well. This paper aims to address: how China is playing a role in globalization through BRI and how BRI will support the Chinese role in the globalization process. And what are the major challenges that China might be faced? Based on the analytical methodology, the paper argues that BRI is a cornucopia of international projects that offer mammoth opportunities for more economic cooperation and deeper regional and global integration, primarily among emerging economies. The paper discusses that at a time when globalization from the West appears to be in retreat, the BRI is a potent symbol of the rise of China-based globalization.

Keywords: globalization, China, belt, and road initiative

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Authors: D. Kakulia, L. Shoshiashvili, G. Sapharishvili

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The results of the study are related to the direction of plastic mine detection research using electromagnetic induction, the development of appropriate equipment, and the evaluation of expected results. Electromagnetic induction sensing is effectively used in the detection of metal objects in the soil and in the discrimination of unexploded ordnances. Metal objects interact well with a low-frequency alternating magnetic field. Their electromagnetic response can be detected at the low-frequency range even when they are placed in the ground. Detection of plastic things such as plastic mines by electromagnetic induction is associated with difficulties. The interaction of non-conducting bodies or low-conductive objects with a low-frequency alternating magnetic field is very weak. At the high-frequency range where already wave processes take place, the interaction increases. Interactions with other distant objects also increase. A complex interference picture is formed, and extraction of useful information also meets difficulties. Sensing by electromagnetic induction at the intermediate MHz frequency range is the subject of research. The concept of detecting plastic mines in this range can be based on the study of the electromagnetic response of non-conductive cavity in a low-conductivity environment or the detection of small metal components in plastic mines, taking into account constructive features. The detector node based on the amplitude and phase detector 'Analog Devices ad8302' has been developed for experimental studies. The node has two inputs. At one of the inputs, the node receives a sinusoidal signal from the generator, to which a transmitting coil is also connected. The receiver coil is attached to the second input of the node. The additional circuit provides an option to amplify the signal output from the receiver coil by 20 dB. The node has two outputs. The voltages obtained at the output reflect the ratio of the amplitudes and the phase difference of the input harmonic signals. Experimental measurements were performed in different positions of the transmitter and receiver coils at the frequency range 1-20 MHz. Arbitrary/Function Generator Tektronix AFG3052C and the eight-channel high-resolution oscilloscope PICOSCOPE 4824 were used in the experiments. Experimental measurements were also performed with a low-conductive test object. The results of the measurements and comparative analysis show the capabilities of the simple detector node and the prospects for its further development in this direction. The results of the experimental measurements are compared and analyzed with the results of appropriate computer modeling based on the method of auxiliary sources (MAS). The experimental measurements are driven using the MATLAB environment. Acknowledgment -This work was supported by Shota Rustaveli National Science Foundation (SRNSF) (Grant number: NFR 17_523).

Keywords: EM induction sensing, detector, plastic mines, remote sensing

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Authors: Xia Luo, Cheng Zeng

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Under the promotion of the Central Committee of the Communist Party of China and the State Council in 2017, Xiong'an New Area is the third crucial new area in China established after Shenzhen and Shanghai. Its constructions' significance lies in mitigating Beijing's non-capital functions and exploring a new mode of optimizing development in densely populated and economically intensive areas. For this purpose, developing underground logistics can assume the role of goods distribution in the capital, relieve the road transport pressure in Beijing-Tianjin-Hebei Urban Agglomeration, adjust and optimize the urban layout and spatial structure of it. Firstly, the construction planning of Xiong'an New Area and underground logistics development are summarized, especially the development status abroad, the development trend, and bottlenecks of underground logistics in China. This paper explores the technicality, feasibility, and necessity of four modes of transportation. There are pneumatic capsule pipeline (PCP) technology, the CargoCap technology, cable hauled mule, and automatic guided vehicle (AGV). The above technical parameters and characteristics are introduced to relevant experts or scholars. Through establishing an indicator system, carrying out a questionnaire survey with the Delphi method, the final suggestion is obtained: China should develop logistics vehicles similar to CargoCap, adopting rail mode and driverless mode. Based on China's temporal and spatial logistics demand and the geographical pattern of Xiong'an New Area, the construction scale, technical parameters, node location, and other vital parameters of underground logistics are planned. In this way, we hope to speed up the new area's construction and the logistics industry's innovation.

Keywords: the Xiong'an new area, underground logistics, contrastive analysis, CargoCap, logistics planning

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Authors: Matthias Stange

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Building Information Modelling (BIM) is one of the most promising methods in the building design process and plays an important role in the digitalization of the Architectural, Engineering, and Construction (AEC) Industry. The application of BIM is seen as the key enabler for increasing productivity in the construction industry. The model-based collaboration using the BIM method is intended to significantly reduce cost increases, schedule delays, and quality problems in the planning and construction of buildings. Numerous qualitative studies based on expert interviews support this theory and report perceived benefits from the use of BIM in terms of achieving project objectives related to cost, schedule, and quality. However, there is a large research gap in analysing quantitative data collected from real construction projects regarding the actual benefits of applying BIM based on representative sample size and different application regions as well as different project typologies. In particular, the influence of the project-related BIM maturity level is completely unexplored. This research project examines primary data from 105 construction projects worldwide using quantitative research methods. Projects from the areas of residential, commercial, and industrial construction as well as infrastructure and hydraulic engineering were examined in application regions North America, Australia, Europe, Asia, MENA region, and South America. First, a descriptive data analysis of 6 independent project variables (BIM maturity level, application region, project category, project type, project size, and BIM level) were carried out using statistical methods. With the help of statisticaldata analyses, the influence of the project-related BIM maturity level on 6 dependent project variables (deviation in planning time, deviation in construction time, number of planning collisions, frequency of rework, number of RFIand number of changes) was investigated. The study revealed that most of the benefits of using BIM perceived through numerous qualitative studies have not been confirmed. The results of the examined sample show that the application of BIM did not have an improving influence on the dependent project variables, especially regarding the quality of the planning itself and the adherence to the schedule targets. The quantitative research suggests the conclusion that the BIM planning method in its current application has not (yet) become a recognizable increase in productivity within the planning and construction process. The empirical findings indicate that this is due to the overall low level of BIM maturity in the projects of the examined sample. As a quintessence, the author suggests that the further implementation of BIM should primarily focus on an application-oriented and consistent development of the project-related BIM maturity level instead of implementing BIM for its own sake. Apparently, there are still significant difficulties in the interweaving of people, processes, and technology.

Keywords: AEC-process, building information modeling, BIM maturity level, project results, productivity of the construction industry

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Authors: Mari Carmen Reyes Angeles, Dalia Michel Reyes Villeda, Ana María Herrera González

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This work reports the design and synthesis of two composite materials based on physically activated carbon and basic polyelectrolytes useful in the adsorption of textile dyes present in aqueous solutions and wastewater. The synthesis of basic polyelectrolytes poly(2-vinylpyridine) (P2VP) and poly(4-vinylpyridine) (P4VP) was made by means of free radical polymerization. The carbon made from prickly pear peel (CarTunaF) was thermally activated in the presence of combustion gases. Composite materials CarTunaF2VP and CarTunaF4VP were obtained from CarTunaF and polybasic polyelectrolytes P2VP and P4VP with a ratio of 67:33 wt. The structure of each polyelectrolyte, P2VP, and P4VP, was elucidated by means of the FTIR and 1H NMR spectrophotometric techniques. Their thermal stability was evaluated using TGA. The characterization of CarTunaF and composite materials CarTunaF2VP and CarTunaF4VP was made by means of FTIR, TGA, SEM, and N2 adsorption. The adsorptive capacities of the polyelectrolytes and the composite materials were evaluated by adsorption of direct dyes present in aqueous solutions. The polyelectrolytes removed between 90 and 100% of the dyes, and the composite materials removed between 68 and 93% of the dyes. Using the four adsorbents P2VP, P4VP, CarTuna2VP, and CarTuna4VP, it was observed that the dyes studied, Direct Blue 80, Direct Turquoise 86, and Direct Orange 26, were adsorbed in the range between 46.1 and 188.7mg∙g-1 by means of electrostatic interactions between the anionic groups in the dyes with the cationic groups in the adsorbents. By using adsorbent materials in the treatment of wastewater from the textile industry, an improvement in the quality of the water was observed by decreasing its pH, COD, conductivity, and color considerably

Keywords: adsorption, anionic dyes, composite, polyelectrolytes

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Authors: Abdulrahman Alajlan

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While the sun serves as a robust energy source, the frigid conditions of outer space present promising prospects for nocturnal power generation due to its continuous accessibility during nighttime hours. This investigation illustrates a proficient methodology facilitating uninterrupted energy capture throughout the day. This method involves the utilization of water-based heat storage systems and radiative thermal emitters implemented across thermometric devices. Remarkably, this approach permits an enhancement of nighttime power generation that exceeds the level of 1 Wm-2, which is unattainable by alternative methodologies. Outdoor experiments conducted at the King Abdulaziz City for Science and Technology (KACST) have demonstrated unparalleled performance, surpassing prior experimental benchmarks by nearly an order of magnitude. Furthermore, the developed device exhibits the capacity to concurrently supply power to multiple light-emitting diodes, thereby showcasing practical applications for nighttime power generation. This research unveils opportunities for the creation of scalable and efficient 24-hour power generation systems based on thermoelectric devices. Central findings from this study encompass the realization of continuous 24-hour power generation from clean and sustainable energy sources. Theoretical analyses indicate the potential for nighttime power generation reaching up to 1 Wm-2, while experimental results have reached nighttime power generation at a density of 0.5 Wm-2. Additionally, the efficiency of multiple light-emitting diodes (LEDs) has been evaluated when powered by the nighttime output of the integrated thermoelectric generator (TEG). Therefore, this methodology exhibits promise for practical applications, particularly in lighting, marking a pivotal advancement in the utilization of renewable energy for both on-grid and off-grid scenarios.

Keywords: nighttime power generation, thermoelectric devices, radiative cooling, thermal management

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Authors: Lucas Bublitz, Michael Herdrich

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By achieving the first commercialization approval in San Francisco the Autonomous Driving (AD) industry proves the technology maturity of the SAE L4 AD systems and the corresponding software and hardware stack. This milestone reflects the upcoming phase in the industry, where the focus is now about scaling and supervising larger autonomous vehicle (AV) fleets in different operation areas. This requires an operation framework, which organizes and assigns responsibilities to the relevant AV technology and operation stakeholders from the AV system provider, the Remote Intervention Operator, the MaaS provider and regulatory & approval authority. This holistic operation framework consists of technological, processual, and organizational activities to ensure safe operation for fully automated vehicles. Regarding the supervision of large autonomous vehicle fleets, a major focus is on the continuous field monitoring. The field monitoring approach must reflect the safety and security criticality of incidents in the field during driving operation. This includes an automatic containment approach, with the overall goal to avoid safety critical incidents and reduce downtime by a malfunction of the AD software stack. An End-to-end (E2E) field monitoring approach detects critical faults in the field, uses a knowledge-based approach for evaluating the safety criticality and supports the automatic containment of these E/E faults. Applying such an approach will ensure the scalability of AV fleets, which is determined by the handling of incidents in the field and the continuous regulatory compliance of the technology after enhancing the Operational Design Domain (ODD) or the function scope by Functions on Demand (FoD) over the entire digital product lifecycle.

Keywords: field monitoring, incident management, multicompliance management for AI in AD, root cause analysis, database approach

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Authors: Bassem Nassar, Wessam Hussein, Medhat Mokhtar

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The crucial concern of satellite operations is to ensure the health and safety of satellites. The worst case in this perspective is probably the loss of a mission but the more common interruption of satellite functionality can result in compromised mission objectives. All the data acquiring from the spacecraft are known as Telemetry (TM), which contains the wealth information related to the health of all its subsystems. Each single item of information is contained in a telemetry parameter, which represents a time-variant property (i.e. a status or a measurement) to be checked. As a consequence, there is a continuous improvement of TM monitoring systems in order to reduce the time required to respond to changes in a satellite's state of health. A fast conception of the current state of the satellite is thus very important in order to respond to occurring failures. Statistical multivariate latent techniques are one of the vital learning tools that are used to tackle the aforementioned problem coherently. Information extraction from such rich data sources using advanced statistical methodologies is a challenging task due to the massive volume of data. To solve this problem, in this paper, we present a proposed unsupervised learning algorithm based on Principle Component Analysis (PCA) technique. The algorithm is particularly applied on an actual remote sensing spacecraft. Data from the Attitude Determination and Control System (ADCS) was acquired under two operation conditions: normal and faulty states. The models were built and tested under these conditions and the results shows that the algorithm could successfully differentiate between these operations conditions. Furthermore, the algorithm provides competent information in prediction as well as adding more insight and physical interpretation to the ADCS operation.

Keywords: space telemetry monitoring, multivariate analysis, PCA algorithm, space operations

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Authors: Sushma Yadav, Anil K. Saroha

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Complex industrial effluent generated from chemical industry is contaminated with toxic and hazardous organic compounds and not amenable to direct biological treatment. To effectively remove many toxic organic pollutants has made it evident that new, compact and more efficient systems are needed. Catalytic Wet Air Oxidation (CWAO) is a promising treatment technology for the abatement of organic pollutants in wastewater. A lot of information is available on using CWAO for the treatment of synthetic solution containing single organic pollutant. But the real industrial effluents containing multi-component mixture of organic compounds were less studied. The main objective of this study is to use the CWAO process for converting the organics into compounds more amenable to biological treatment; complete oxidation may be too expensive. Therefore efforts were made in the present study to explore the potential of alumina based Platinum (Pt) catalyst for the treatment of industrial organic raffinate containing toxic constituents like ammoniacal nitrogen, pyridine etc. The catalysts were prepared by incipient wetness impregnation method and characterized by scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX) and BET (Brunauer, Emmett, and Teller) surface area. CWAO experiments were performed at atmospheric pressure and (30 °C - 70 °C) temperature conditions and the results were evaluated in terms of COD removal efficiency. The biodegradability test was performed by BOD/COD ratio for checking the toxicity of the industrial wastewater as well as for the treated water. The BOD/COD ratio of treated water was significantly increased and signified that the toxicity of the organics was decreased while the biodegradability was increased, indicating the more amenability towards biological treatment.

Keywords: alumina based pt catalyst, BOD/COD ratio, catalytic wet air oxidation, COD removal efficiency, industrial organic raffinate

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Authors: Cheng Fang Wang, Fu Li Gao, Jian Ying Zhou

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The '1+4' integration pilot area in the border area of Guangzhou-Foshan is an important platform for Guangzhou-Foshan strategic cooperation, as well as a typical semi-urbanized area with mixed urban and rural landscapes, of which the Baiyun-Nanhai pilot area is one of them. Baiyun district and Nanhai district are only separated by the Pearl River. In this paper, the three dimensions, which include production, living, and ecology, have been put forward, as well as cross-regional multi-agency negotiation mechanism has been discussed. Taking 'Baiyun-Nanhai' pilot area as a case study, POI (Point of Interest) data to analyze the distribution characteristics of 'production-living-ecological space' from the spatial dimension has been introduced in this paper, as well as the land-use change of 'production-living-ecological space' in western region of Baiyun district in 2007 and 2017 from the temporal dimension has been analyzed. Based on the above analysis, the integration development strategy and rethinking of cross-administrative region based on 'production-living-ecological integration' mechanism have been discussed later. It will explore the mechanism of industrial collaborative innovation, infrastructure co-construction, and ecological co-protection in semi-urban areas across borders. And it is expected to provide a reference for the integrated construction of the Guangdong-Hong Kong-Macao Greater Bay Area.

Keywords: semi-urbanization, production-living-ecological integration, multi-agency negotiation, Guangzhou-Foshan integration, synergetic development

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Authors: Ciaran Friel, Jerry Suls, Patrick Robles, Frank Vicari, Joan Duer-Hefele, Karina W. Davidson

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Physical activity guidelines focus on increasing moderate intensity activity for older adults, but adherence to recommendations remains low. This is despite the fact that scientific evidence supports that any increase in physical activity is positively correlated with health benefits. Behavior change techniques (BCTs) have demonstrated effectiveness in reducing sedentary behavior and promoting physical activity. This pilot study uses a Personalized Trials (N-of-1) design to evaluate the efficacy of using four BCTs to promote an increase in low-intensity physical activity (2,000 steps of walking per day) in adults aged 45-75 years old. The 4 BCTs tested were goal setting, action planning, feedback, and self-monitoring. BCTs were tested in random order and delivered by text message prompts requiring participant response. The study recruited health system employees in the target age range, without mobility restrictions and demonstrating interest in increasing their daily activity by a minimum of 2,000 steps per day for a minimum of five days per week. Participants were sent a Fitbit Charge 4 fitness tracker with an established study account and password. Participants were recommended to wear the Fitbit device 24/7, but were required to wear it for a minimum of ten hours per day. Baseline physical activity was measured by the Fitbit for two weeks. Participants then engaged with a clinical research coordinator to review comprehension of the text message content and required actions for each of the BCTs to be tested. Participants then selected a consistent daily time in which they would receive their text message prompt. In the 8 week intervention phase of the study, participants received each of the four BCTs, in random order, for a two week period. Text message prompts were delivered daily at a time selected by the participant. All prompts required an interactive response from participants and may have included recording their detailed plan for walking or daily step goal (action planning, goal setting). Additionally, participants may have been directed to a study dashboard to view their step counts or compare themselves with peers (self-monitoring, feedback). At the end of each two week testing interval, participants were asked to complete the Self-Efficacy for Walking Scale (SEW_Dur), a validated measure that assesses the participant’s confidence in walking incremental distances and a survey measuring their satisfaction with the individual BCT that they tested. At the end of their trial, participants received a personalized summary of their step data in response to each individual BCT. Analysis will examine the novel individual-level heterogeneity of treatment effect made possible by N-of-1 design, and pool results across participants to efficiently estimate the overall efficacy of the selected behavioral change techniques in increasing low-intensity walking by 2,000 steps, 5 days per week. Self-efficacy will be explored as the likely mechanism of action prompting behavior change. This study will inform the providers and demonstrate the feasibility of N-of-1 study design to effectively promote physical activity as a component of healthy aging.

Keywords: aging, exercise, habit, walking

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Authors: Pál Iván Szontagh

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We suppose that today, the motivation for the career of a pedagogue (including its existential, organizational and infrastructural conditions) is different from the level of commitment to the profession of an educator (which can be experienced informally, or outside of the public education system). In our research, we made efforts to address the widest possible range of student elementary teachers, and to interpret their responses using different filters. In the first phase of our study, we analyzed first-year kindergarten teacher students’ career motivation and commitment to the profession, and in the second phase, that of final-year kindergarten teacher candidates. In the third phase, we conducted surveys to explore students’ motivation for the profession and the career path of a pedagogue in four countries of the Carpathian Basin (Hungary, Slovakia, Romania and Serbia). The surveys were conducted in 17 campuses of 11 Hungarian teacher’s training colleges and universities. Finally, we extended the survey to practicing graduates preparing for their on-the-job rating examination. Based on our results, in all breakdowns, regardless of age group, training institute or - in part - geographical location and nationality, it is proven that lack of social- and financial esteem of the profession poses serious risks for recruitment and retention of teachers. As a summary, we searched for significant differences between the professional- and career motivations of the three respondent groups (kindergarten teacher students, elementary teacher students and practicing teachers), i.e. the motivation factors that change the most with education and/or with the time spent on the job. Based on our results, in all breakdowns, regardless of age group, training institute or - in part - geographical location and nationality, it is proven that lack of social- and financial esteem of the profession poses serious risks for recruitment and retention of teachers.

Keywords: career motivation, career socialization, professional motivation, teacher training

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Authors: Yafit Gabay

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Attention deficit hyperactivity disorder (ADHD) has been associated with both suboptimal functioning in the striatum and prefrontal cortex. Such abnormalities may impede the acquisition of perceptual categories, which are important for fundamental abilities such as object recognition and speech perception. Indeed, prior research has supported this possibility, demonstrating that children with ADHD have similar visual category learning performance as their neurotypical peers but use suboptimal learning strategies. However, much less is known about category learning processes in the auditory domain or among adults with ADHD in which prefrontal functions are more mature compared to children. Here, we investigated auditory and visual perceptual category learning in adults with ADHD and neurotypical individuals. Specifically, we examined learning of rule-based categories – presumed to be optimally learned by a frontal cortex-mediated hypothesis testing – and information-integration categories – hypothesized to be optimally learned by a striatally-mediated reinforcement learning system. Consistent with striatal and prefrontal cortical impairments observed in ADHD, our results show that across sensory modalities, both rule-based and information-integration category learning is impaired in adults with ADHD. Computational modeling analyses revealed that individuals with ADHD were slower to shift to optimal strategies than neurotypicals, regardless of category type or modality. Taken together, these results suggest that both explicit, frontally mediated and implicit, striatally mediated category learning are impaired in ADHD. These results suggest impairments across multiple learning systems in young adults with ADHD that extend across sensory modalities and likely arise from domain-general mechanisms.

Keywords: ADHD, category learning, modality, computational modeling

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Authors: Usama Mohamed, Sam Booth, Aliysn J. Nedoma

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As part of the transition to electric vehicles, there has been a recent increase in demand for battery manufacturing. Cathodes typically account for approximately 50% of the total lithium-ion battery cell cost and are a pivotal factor in determining the viability of new industrial infrastructure. Cathodes which offer lower costs whilst maintaining or increasing performance, such as nickel-rich layered cathodes, have a significant competitive advantage when scaling up the manufacturing process. This project evaluates the techno-economic value proposition of an integrated industrial scale cathode active material (CAM) production process, closing the mass and energy balances, and optimizing the operation conditions using a sensitivity analysis. This is done by developing a process model of a co-precipitation synthesis route using Aspen Plus software and validated based on experimental data. The mechanism chemistry and equilibrium conditions were established based on previous literature and HSC-Chemistry software. This is then followed by integrating the energy streams, adding waste recovery and treatment processes, as well as testing the effect of key parameters (temperature, pH, reaction time, etc.) on CAM production yield and emissions. Finally, an economic analysis estimating the fixed and variable costs (including capital expenditure, labor costs, raw materials, etc.) to calculate the cost of CAM ($/kg and $/kWh), total plant cost ($) and net present value (NPV). This work sets the foundational blueprint for future research into sustainable industrial scale processes for CAM manufacturing.

Keywords: cathodes, industrial production, nickel-rich layered cathodes, process modelling, techno-economic analysis

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Authors: Amir Reza Heydari, Yaser Jenab

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Coronary artery disease, a common cardiovascular disease, is attributed to the accumulation of cholesterol-based plaques in the coronary arteries, leading to atherosclerosis. This disease is associated with risk factors such as smoking, hypertension, diabetes, and elevated cholesterol levels, contributing to severe clinical consequences, including acute coronary syndromes and myocardial infarction. Treatment approaches such as from lifestyle interventions to surgical procedures like percutaneous coronary intervention and coronary artery bypass surgery. These interventions often employ stents, including bare-metal stents (BMS), drug-eluting stents (DES), and bioresorbable vascular scaffolds (BVS), each with its advantages and limitations. Computational tools have emerged as critical in optimizing stent designs and assessing their performance. The aim of this study is to provide an overview of the computational methods of studies based on the finite element (FE) method in the field of coronary stenting and discuss the potential for development and clinical application of stent devices. Additionally, the importance of assessing the ability of computational models is emphasized to represent real-world phenomena, supported by recent guidelines from the American Society of Mechanical Engineers (ASME). Validation processes proposed include comparing model performance with in vivo, ex-vivo, or in vitro data, alongside uncertainty quantification and sensitivity analysis. These methods can enhance the credibility and reliability of in silico simulations, ultimately aiding in the assessment of coronary stent designs in various clinical contexts.

Keywords: atherosclerosis, materials, restenosis, review, validation

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Authors: Siddharatha Sharma

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With the advent of technology and machines, the role of biometrics in society is taking an important place for secured living. Security issues are the major concern in today’s world and continue to grow in intensity and complexity. Biometrics based recognition, which involves precise measurement of the characteristics of living beings, is not a new method. Fingerprints are being used for several years by law enforcement and forensic agencies to identify the culprits and apprehend them. Biometrics is based on four basic principles i.e. (i) uniqueness, (ii) accuracy, (iii) permanency and (iv) peculiarity. In today’s world fingerprints are the most popular and unique biometrics method claiming a social benefit in the government sponsored programs. A remarkable example of the same is UIDAI (Unique Identification Authority of India) in India. In case of fingerprint biometrics the matching accuracy is very high. It has been observed empirically that even the identical twins also do not have similar prints. With the passage of time there has been an immense progress in the techniques of sensing computational speed, operating environment and the storage capabilities and it has become more user convenient. Only a small fraction of the population may be unsuitable for automatic identification because of genetic factors, aging, environmental or occupational reasons for example workers who have cuts and bruises on their hands which keep fingerprints changing. Fingerprints are limited to human beings only because of the presence of volar skin with corrugated ridges which are unique to this species. Fingerprint biometrics has proved to be a high level authentication system for identification of the human beings. Though it has limitations, for example it may be inefficient and ineffective if ridges of finger(s) or palm are moist authentication becomes difficult. This paper would focus on uniqueness of fingerprints to the human beings in comparison to other living beings and review the advancement in emerging technologies and their limitations.

Keywords: fingerprinting, biometrics, human beings, authentication

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Authors: Simone F. Medeiros, Isabela F. Santos, Rodolfo M. Moraes, Jaspreet K. Kular, Marcus A. Johns, Ram Sharma, Amilton M. Santos

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Tissue engineering aims to develop alternatives to treat damaged tissues by promoting their regeneration. Its basic principle is to place cells on a scaffold capable of promoting cell functions, and for this purpose, polymeric nanoparticles have been successfully used due to the ability of some macro chains to mimic the extracellular matrix and influence cell functions. In general, nanoparticles require surface chemical modification to achieve cell adhesion, and recent advances in their synthesis include methods for modifying the ligand density and distribution onto nanoparticles surface. However, this work reports the development of biodegradable polymeric nanoparticles capable of promoting cellular adhesion without any surface chemical modification by ligands. Biocompatible and biodegradable nanoparticles based on poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBHV) were synthesized by solvent evaporation method. The produced nanoparticles were small in size (85 and 125 nm) and colloidally stable against time in aqueous solution. Morphology evaluation showed their spherical shape with small polydispersity. Human osteoblast-like cells (MG63) were cultured in the presence of PHBHV nanoparticles, and growth kinetics were compared to those grown on tissue culture polystyrene (TCPS). Cell attachment on non-tissue culture polystyrene (non-TCPS) pre-coated with nanoparticles was assessed and compared to attachment on TCPS. These findings reveal the potential of PHBHV nanoparticles for cell adhesion and growth, without requiring a matrix ligand to support cells, to be used as scaffolds, in tissue engineering applications.

Keywords: tissue engineering, PHBHV, stem cells, cellular attachment

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Authors: Wanying Xie

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Under the background of the increasing Sino-US trade friction, the two nations pay more attention to the medias’ words. This paper mainly studies the causality, effectiveness, and influence of discourse construction between traditional media and social media. Based on the Network Agenda Setting theory, a kind of associative memory pattern in Psychology, who focuses on how media affect audiences’ cognition of issues and attributes, as well as the significance of the relation between people and matters. The date of the sample chosen in this paper ranges from March 23, 2018, to April 30, 2019. A total of 395 Tweets of Donald Trump are obtained, and 731 related reports are collected from the mainstream American newspapers including New York Times, the Washington Post and the Washington Street, by using Factiva and other databases. The sample data are processed by MAXQDA while the media discourses are analyzed by SPSS and Cite Space, with an aim to study: 1) whether the inter-media discourse construction exists; 2) which media (traditional media V.S. social media) is dominant; 3) the causality between two media. The results show: 1) the discourse construction between three American mainstream newspapers and Donald Trump's Twitter is proved in some periods; 2) the dominant position is extremely depended on the events; 3) the causality between two media is decided by many reasons. New media technology shortens the time of agenda-setting effect to one day or less. By comparing the specific relation between the three major American newspapers and Donald Trump’s Twitter, whose popularity and influence could be reflected. Hopefully, this paper could enable readers to have a more comprehensive understanding of the international media language and political environment.

Keywords: discourse construction, media language, network agenda-setting theory, sino-us trade friction

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Authors: Priyoth Kittiteerasack, Alana Steffen, Alicia K. Matthews

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Depression is a leading cause of the worldwide burden of disability and disease burden. Notably, lesbian, gay, bisexual, and transgender (LGBT) populations are more likely to be a high-risk group for depression compared to their heterosexual and cisgender counterparts. To date, little is known about the rates and predictors of depression among Thai LGBT populations. As such, the purpose of this study was to: 1) measure the prevalence of depression among a diverse sample of Thai LGBT adults and 2) determine the influence of minority stress variables (discrimination, victimization, internalized homophobia, and identity concealment), general stress (stress and loneliness), and coping strategies (problem-focused, avoidance, and seeking social support) on depression outcomes. This study was guided by the Minority Stress Model (MSM). The MSM posits that elevated rates of mental health problems among LGBT populations stem from increased exposures to social stigma due to their membership in a stigmatized minority group. Social stigma, including discrimination and violence, represents unique sources of stress for LGBT individuals and have a direct impact on mental health. This study was conducted as part of a larger descriptive study of mental health among Thai LGBT adults. Standardized measures consistent with the MSM were selected and translated into the Thai language by a panel of LGBT experts using the forward and backward translation technique. The psychometric properties of translated instruments were tested and acceptable (Cronbach’s alpha > .8 and Content Validity Index = 1). Study participants were recruited using convenience and snowball sampling methods. Self-administered survey data were collected via an online survey and via in-person data collection conducted at a leading Thai LGBT organization. Descriptive statistics and multivariate analyses using multiple linear regression models were conducted to analyze study data. The mean age of participants (n = 411) was 29.5 years (S.D. = 7.4). Participants were primarily male (90.5%), homosexual (79.3%), and cisgender (76.6%). The mean score for depression of study participant was 9.46 (SD = 8.43). Forty-three percent of LGBT participants reported clinically significant levels of depression as measured by the Beck Depression Inventory. In multivariate models, the combined influence of demographic, stress, coping, and minority stressors explained 47.2% of the variance in depression scores (F(16,367) = 20.48, p < .001). Minority stressors independently associated with depression included discrimination (β = .43, p < .01) victimization (β = 1.53, p < .05), and identity concealment (β = -.54, p < .05). In addition, stress (β = .81, p < .001), history of a chronic disease (β = 1.20, p < .05), and coping strategies (problem-focused coping β = -1.88, p < .01, seeking social support β = -1.12, p < .05, and avoidance coping β = 2.85, p < .001) predicted depression scores. The study outcomes emphasized that minority stressors uniquely contributed to depression levels among Thai LGBT participants over and above typical non-minority stressors. Study findings have important implications for nursing practice and the development of intervention research.

Keywords: depression, LGBT, minority stress, sexual and gender minority, Thailand

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Authors: Mohamed Ayeldeen, Abdelazim Negm

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Nowadays, strength characteristics of soils have more importance due to increasing building loads. In some projects, geotechnical properties of the soils are be improved using man-made materials varying from cement-based to chemical-based. These materials have proven successful in improving the engineering properties of the soil such as shear strength, compressibility, permeability, bearing capacity etc.. However, the use of these artificial injection formulas often modifies the pH level of soil, contaminates soil and groundwater. This is attributed to their toxic and hazardous characteristics. Recently, an environmentally friendly soil treatment method or Biological Treatment Method (BTM) was to bond particles of loose sandy soils. This research paper presents the preliminary results of using biopolymers for strengthening cohesionless soil. Xanthan gum was identified for further study over a range of concentrations varying from 0.25% to 2.00%. Xanthan gum is a polysaccharide secreted by the bacterium Xanthomonas campestris, used as a food additive and it is a nontoxic material. A series of direct shear, unconfined compressive strength, and permeability tests were carried out to investigate the behavior of sandy soil treated with Xanthan gum with different concentration ratios and at different curing times. Laser microscopy imaging was also conducted to study the microstructure of the treated sand. Experimental results demonstrated the compatibility of Xanthan gum to improve the geotechnical properties of sandy soil. Depending on the biopolymer concentration, it was observed that the biopolymers effectively increased the cohesion intercept and stiffness of the treated sand and reduced the permeability of sand. The microscopy imaging indicates that the cross-links of the biopolymers through and over the soil particles increase with the increase of the biopolymer concentration.

Keywords: biopolymer, direct shear, permeability, sand, shear strength, Xanthan gum

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Authors: Sergo Tsiramua, Sulkhan Sulkhanishvili, Elisabed Asabashvili, Lazare Kvirtia

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The paper presents logical-probabilistic methods, models, and algorithms for reliability assessment of complex systems, based on which a web application for structural analysis and reliability assessment of systems was created. It is important to design systems based on structural analysis, research, and evaluation of efficiency indicators. One of the important efficiency criteria is the reliability of the system, which depends on the components of the structure. Quantifying the reliability of large-scale systems is a computationally complex process, and it is advisable to perform it with the help of a computer. Logical-probabilistic modeling is one of the effective means of describing the structure of a complex system and quantitatively evaluating its reliability, which was the basis of our application. The reliability assessment process included the following stages, which were reflected in the application: 1) Construction of a graphical scheme of the structural reliability of the system; 2) Transformation of the graphic scheme into a logical representation and modeling of the shortest ways of successful functioning of the system; 3) Description of system operability condition with logical function in the form of disjunctive normal form (DNF); 4) Transformation of DNF into orthogonal disjunction normal form (ODNF) using the orthogonalization algorithm; 5) Replacing logical elements with probabilistic elements in ODNF, obtaining a reliability estimation polynomial and quantifying reliability; 6) Calculation of “weights” of elements of system. Using the logical-probabilistic methods, models and algorithms discussed in the paper, a special software was created, by means of which a quantitative assessment of the reliability of systems of a complex structure is produced. As a result, structural analysis of systems, research, and designing of optimal structure systems are carried out.

Keywords: complex systems, logical-probabilistic methods, orthogonalization algorithm, reliability of systems, “weights” of elements

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Authors: Hyunsun Lee, Yi Zhu

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Wireless ad-hoc network is a decentralized type of temporary machine-to-machine connection that is spontaneous or impromptu so that it does not rely on any fixed infrastructure and centralized administration. As unmanned aerial vehicles (UAVs), also called drones, have recently become more accessible and widely utilized in military and civilian domains such as surveillance, search and detection missions, traffic monitoring, remote filming, product delivery, to name a few. The communication between these UAVs become possible and materialized through Flying Ad-hoc Networks (FANETs). However, due to the high mobility of UAVs that may cause different types of transmission interference, it is vital to design robust routing protocols for FANETs. In this talk, the multicast routing method based on a modified stochastic branching process is proposed. The stochastic branching process is often used to describe an early stage of an infectious disease outbreak, and the reproductive number in the process is used to classify the outbreak into a major or minor outbreak. The reproductive number to regulate the local transmission rate is adapted and modified for flying ad-hoc network communication. The performance of the proposed routing method is compared with other well-known methods such as flooding method and gossip method based on three measures; average reachability, average node usage and average branching factor. The proposed routing method achieves average reachability very closer to flooding method, average node usage closer to gossip method, and outstanding average branching factor among methods. It can be concluded that the proposed multicast routing scheme is more efficient than well-known routing schemes such as flooding and gossip while it maintains high performance.

Keywords: Flying Ad-hoc Networks, Multicast Routing, Stochastic Branching Process, Unmanned Aerial Vehicles

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Authors: Soheila Sadeghi

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In construction projects, predicting project performance metrics accurately is essential for effective management and successful delivery. However, conventional methods often depend on fixed baseline plans, disregarding the evolving nature of project progress and external influences. To address this issue, we introduce a distinct approach based on machine learning to forecast key performance indicators, such as cost variance and earned value, for each Work Breakdown Structure (WBS) category within an urban road reconstruction project. Our proposed model leverages time series forecasting techniques, namely Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) networks, to predict future performance by analyzing historical data and project progress. Additionally, the model incorporates external factors, including weather patterns and resource availability, as features to improve forecast accuracy. By harnessing the predictive capabilities of machine learning, our performance forecasting model enables project managers to proactively identify potential deviations from the baseline plan and take timely corrective measures. To validate the effectiveness of the proposed approach, we conduct a case study on an urban road reconstruction project, comparing the model's predictions with actual project performance data. The outcomes of this research contribute to the advancement of project management practices in the construction industry by providing a data-driven solution for enhancing project performance monitoring and control.

Keywords: project performance forecasting, machine learning, time series forecasting, cost variance, schedule variance, earned value management

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Authors: H. Duggal, G. Singh, G. Singh, A. Bhalla, S. Kumar, J. S. Shahi, D. Mehta

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The total differential cross section for scattering of the 5.895 keV photons by various polymers has been measured at scattering angle of 135o. The experimental measurements were carried out using the energy dispersive setup involving annular source of the 55Fe radioisotope and a low energy germanium (LEGe) detector. The cross section values are measured for 20 polymer targets namely, Paraffin Wax, Polytetrafluoro ethylene (PTFE), Cellulose, Silicone oil, Polyvinyl alcohol (PVA), Polyvinyl purrolidone (PVP), Polymethyl methacrylate (PMMA), Kapton, Mylar, Chitosan, Polyvinyl chloride (PVC), Bakelite, Carbopol, Chlorobutyl rubber (CBR), Polyetylene glycol (PEG), Polysorbate-20, Nylon-6, Cetyl alcohol, Carboxyl methyl sodium cellulose and Sodium starch glucolate. The measurements were performed in vacuum so as to avoid scattering contribution due to air and strong absorption of low energy photons in the air column. In the present investigations, the geometrical factor and efficiency of the detector were determined by measuring the K x-rays emitted from the 22Ti and 23V targets excited by the Mn K x-rays in the same experimental set up. The measured scattering cross sections have been compared with the sum of theoretically calculated elastic and inelastic scattering cross sections. The theoretical elastic (Rayleigh) scattering cross sections based on the various form factor approximations, namely, non-relativistic form factor (NF), relativistic form factor (RF), modified form factor (MF), and MF with anomalous scattering factor (ASF) as well as the second order S-matrix formalisms, and the inelastic scattering differential cross sections based on the Klein-Nishina formula after including the inelastic scattering function (KN+ISF) have been calculated. The experimental results show fairly good agreement with theoretical cross sections.

Keywords: photon, polymers, elastic and inelastic, scattering cross sections

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Authors: Masoud Ghaemi, Mohammadjafar Hedayati, Faezeh Yousefzadeh, Hoseinali Heydarzadeh

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Careful monitoring in the earth dams to measure deformation caused by settlement and movement has always been a concern for engineers in the field. In order to measure settlement and deformation of earth dams, usually, the precision instruments of settlement set and combined Inclinometer that is commonly referred to IS instrument will be used. In some dams, because the thickness of alluvium is high and there is no possibility of alluvium removal (technically and economically and in terms of performance), there is no possibility of placing the end of IS instrument (precision instruments of Inclinometer-settlement set) in the rock foundation. Inevitably, have to accept installing pipes in the weak and deformable alluvial foundation that leads to errors in the calculation of the actual settlement (absolute settlement) in different parts of the dam body. The purpose of this paper is to present new and refine criteria for predicting settlement and deformation in earth dams. The study is based on conditions in three dams with a deformation quite alluvial (Agh Chai, Narmashir and Gilan-e Gharb) to provide settlement criteria affected by the alluvial foundation. To achieve this goal, the settlement of dams was simulated by using the finite difference method with FLAC3D software, and then the modeling results were compared with the reading IS instrument. In the end, the caliber of the model and validate the results, by using regression analysis techniques and scrutinized modeling parameters with real situations and then by using MATLAB software and CURVE FITTING toolbox, new criteria for the settlement based on elasticity modulus, cohesion, friction angle, the density of earth dam and the alluvial foundation was obtained. The results of these studies show that, by using the new criteria measures, the amount of settlement and deformation for the dams with alluvial foundation can be corrected after instrument readings, and the error rate in reading IS instrument can be greatly reduced.

Keywords: earth-fill dam, foundation, settlement, finite difference, MATLAB, curve fitting

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Authors: Ding He, Ping Hu

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This article presents a “networking approach” as an alternative to the “layering model” in the issue of the historic urban landscape [HUL], based on research conducted in the historic city of Jingdezhen, the center of the porcelain industry in China. This study points out that the existing HUL concept, which can be traced back to the fundamental conceptual divisions set forth by western science, tends to analyze the various elements of urban heritage (composed of hybrid natural-cultural elements) by layers and ignore the nuanced connections and interweaving structure of various elements. Instead, the networking analysis approach can respond to the challenges of complex heritage networks and to the difficulties that are often faced when modern schemes of looking and thinking of landscape in the Eurocentric heritage model encounters local knowledge of Chinese settlement. The fieldwork in this paper examines the local language regarding place names and everyday uses of urban spaces, thereby highlighting heritage systems grounded in local life and indigenous knowledge. In the context of Chinese “Fengshui”, this paper demonstrates the local knowledge of nature and local intelligence of settlement location and design. This paper suggests that industrial elements (kilns, molding rooms, piers, etc.) and spiritual elements (temples for ceramic saints or water gods) are located in their intimate natural networks. Furthermore, the functional, spiritual, and natural elements are perceived as a whole and evolve as an interactive system. This paper proposes a local and cognitive approach in heritage, which was initially developed in European Landscape Convention and historic landscape characterization projects, and yet seeks a more tentative and nuanced model based on urban ethnography in a Chinese city.

Keywords: Chinese city, historic urban landscape, heritage conservation, network

Procedia PDF Downloads 131