Search results for: system model

Authors: E. Faizan, Wahab Abdul Ghafar, Tao Zhong

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Steel plate shear walls (SPSWs) are a robust lateral load resistance structure because of their high flexibility and efficient energy dissipation when subjected to seismic loads. This research investigates the seismic performance of an innovative infill web strip (IWS-SPSW) and a typical unstiffened steel plate shear wall (USPSW). As a result, two 1:3 scale specimens of an IWS-SPSW and USPSW with a single story and a single bay were built and subjected to a cyclic lateral loading methodology. In the prototype, the beam-to-column connections were accomplished with the assistance of semi-rigid end-plate connectors. IWS-SPSW demonstrated exceptional ductility and shear load-bearing capacity during the testing process, with no cracks or other damage occurring. In addition, the IWS-SPSW could effectively dissipate energy without causing a significant amount of beam-column connection distortion. The shear load-bearing capacity of the USPSW was exceptional. However, it exhibited low ductility, severe infill plate corner ripping, and huge infill web plate cracks. The FE models were created and then confirmed using the experimental data. It has been demonstrated that the infill web strips of an SPSW system can affect the system's high performance and total energy dissipation. In addition, a parametric analysis was carried out to evaluate the material qualities of the IWS, which can considerably improve the system's seismic performances. These properties include the steel's strength as well as its thickness.

Keywords: steel shear walls, seismic performance, failure mode, hysteresis response, nonlinear finite element analysis, parametric study

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Authors: Amirhossein Mohajerzadeh, Abolghasem Mohajerzadeh

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In this paper, target parameter is estimated with desirable precision in hierarchical wireless sensor networks (WSN) while the proposed algorithm also tries to prolong network lifetime as much as possible, using efficient data collecting algorithm. Target parameter distribution function is considered unknown. Sensor nodes sense the environment and send the data to the base station called fusion center (FC) using hierarchical data collecting algorithm. FC builds underlying phenomena based on collected data. Considering the aggregation level, x, the goal is providing the essential infrastructure to find the best value for aggregation level in order to prolong network lifetime as much as possible, while desirable accuracy is guaranteed (required sample size is fully depended on desirable precision). First, the sample size calculation algorithm is discussed, second, the average queue length based on M/M[x]/1/K queue model is determined and it is used for energy consumption calculation. Nodes can decrease transmission cost by aggregating incoming data. Furthermore, the performance of the new algorithm is evaluated in terms of lifetime and estimation accuracy.

Keywords: aggregation, estimation, queuing, wireless sensor network

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Authors: Evar C. Umeozor, Experience I. Nduagu, Ian D. Gates

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The energy requirements of carbon dioxide utilization (CDU) technologies/processes are diverse, so also are their environmental footprints. This paper explores the energy and environmental impacts of systems for CO₂ conversion to fuels, chemicals, and materials. Energy needs of the technologies and processes deployable in CO₂ conversion systems are met by one or combinations of hydrogen (chemical), electricity, heat, and light. Likewise, the environmental footprint of any CO₂ utilization pathway depends on the systems involved. So far, evaluation of CDU systems has been constrained to particular energy source/type or a subset of the overall system needed to make CDU possible. This introduces limitations to the general understanding of the energy and environmental implications of CDU, which has led to various pitfalls in past studies. A CDU system has an energy source, CO₂ supply, and conversion units. We apply a holistic approach to consider the impacts of all components in the process, including various sources of energy, CO₂ feedstock, and conversion technologies. The electricity sources include nuclear power, renewables (wind and solar PV), gas turbine, and coal. Heat is supplied from either electricity or natural gas, and hydrogen is produced from either steam methane reforming or electrolysis. The CO₂ capture unit uses either direct air capture or post-combustion capture via amine scrubbing, where applicable, integrated configurations of the CDU system are explored. We demonstrate how the overall energy and environmental impacts of each utilization pathway are obtained by aggregating the values for all components involved. Proper accounting of the energy and emission intensities of CDU must incorporate total balances for the utilization process and differences in timescales between alternative conversion pathways. Our results highlight opportunities for the use of clean energy sources, direct air capture, and a number of promising CO₂ conversion pathways for producing methanol, ethanol, synfuel, urea, and polymer materials.

Keywords: carbon dioxide utilization, processes, energy options, environmental impacts

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Authors: Arthur D. Wiedemann, Christopher Fuller, Kyle A. Pascioni

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With the introduction of electric motors, small unmanned aerial vehicle designers have to consider trade-offs between acoustic noise and thrust generated. Currently, there are few low-computational tools available for predicting acoustic noise emitted by a propeller into the far-field. Artificial neural networks offer a highly non-linear and adaptive model for predicting isolated and interactive tonal noise. But neural networks require large data sets, exceeding practical considerations in modeling experimental results. A methodology known as physics guided machine learning has been applied in this study to reduce the required data set to train the network. After building and evaluating several neural networks, the best model is investigated to determine how the network successfully predicts the acoustic waveform. Lastly, a post-network transfer function is developed to remove discontinuity from the predicted waveform. Overall, methodologies from physics guided machine learning show a notable improvement in prediction performance, but additional loss functions are necessary for constructing predictive networks on small datasets.

Keywords: aeroacoustics, machine learning, propeller, rotor, neural network, physics guided machine learning

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Authors: Rendani Mercy Makhwathana

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This paper intends to explore teachers' encounters when teaching English First Additional Language in rural public schools. Teachers are pillars of any education system around the globe. Educational transformations hinge on them as critical role players in the education system. Thus, teachers' encounters are worth consideration, for they impact learners' learning and the well-being of education in general. An exploratory qualitative approach was used in this paper. The population for this paper comprised all Foundation Phase teachers in the district. A purposive sample of 15 Foundation Phase teachers from five rural-based schools was used. Data were collected through classroom observation and individual face-to-face interviews. Data were categorized, analyzed, and interpreted. Amongst the revealed teachers' encounters are learners' inability to read and write and learners' lack of English language background and learners' lack of the vocabulary to express themselves. This paper recommends the provision of relevant resources and support to effectively teach English First Additional Language to enable learners' engagement and effective use of the English language.

Keywords: first additional language, english second language, medium of instruction, teacher professional development

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Authors: Gulyas Erzsebet

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The multimerisation of proteins is a common feature of many cellular processes; however, it could also impair protein functions and/or be associated with the occurrence of diseases. Thus, development of a research tool monitoring the appearance/presence of multimeric protein forms has great importance for a variety of research fields. Such a tool is potentially applicable in the ante-mortem diagnosis of certain conformational diseases, such as transmissible spongiform encephalopathies (TSE) and Alzheimer’s disease. These conditions are accompanied by the appearance of aggregated protein multimers, present in low concentrations in various tissues. This detection is particularly relevant for TSE where the handling of tissues derived from affected individuals and of meat products of infected animals have become an enormous health concern. Here we demonstrate the potential of such a multimer detection approach in TSE by developing a facile approach. The Biospiral-Detect system resembles a traditional sandwich ELISA, except that the capturing antibody that is attached to a solid surface and the detecting antibody is directed against the same or overlapping epitopes. As a consequence, the capturing antibody shields the epitope on the captured monomer from reacting with the detecting antibody, therefore monomers are not detected. Thus, MDS is capable of detecting only protein multimers with high specificity. We developed an alternative system as well, where RNA aptamers were employed instead of monoclonal antibodies. In order to minimize degradation, the 3' and 5' ends of the aptamer contained deoxyribonucleotides and phosphorothioate linkages. When compared the monoclonal antibodies-based system with the aptamers-based one, the former proved to be superior. Thus all subsequent experiments were conducted by employing the Biospiral -Detect modified sandwich ELISA kit. Our approach showed an order of magnitude higher sensitivity toward mulimers than monomers suggesting that this approach may become a valuable diagnostic tool for conformational diseases that are accompanied by multimerization.

Keywords: diagnosis, ELISA, Prion, TSE

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Authors: Nanadcha Sinjindawong

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This article discusses the design process of a community mall called Castle of The Mall-dern. The concept behind this mall is to combine elements of a medieval castle with modern architecture. The author aims to create a building that fits into the surroundings while also providing users with the vibes of the ancient era. The total area used for the mall is 4,000 square meters, with three floors. The first floor is 1,500 square meters, the second floor is 1,750 square meters, and the third floor is 750 square meters. Research Aim: The aim of this research is to design a community mall that sells ancient clothes and accessories, and to combine sustainable architectural design with the ideas of ancient architecture in an urban area with convenient transportation. Methodology: The research utilizes qualitative research methods in architectural design. The process begins with calculating the given area and dividing it into different zones. The author then sketches and draws the plan of each floor, adding the necessary rooms based on the floor areas mentioned earlier. The program "SketchUp" is used to create an online 3D model of the community mall, and a physical model is built for presentation purposes on A1 paper, explaining all the details. Findings: The result of this research is a community mall with various amenities. The first floor includes retail shops, clothing stores, a food center, and a service zone. Additionally, there is an indoor garden with a fountain and a tree for relaxation. The second and third floors feature a void in the middle, with a few stores, cafes, restaurants, and studios on the second floor. The third floor is home to the administration and security control room, as well as a community gathering area designed as a public library with a café inside. Theoretical Importance: This research contributes to the field of sustainable architectural design by combining ancient architectural ideas with modern elements. It showcases the potential for creating buildings that blend historical aesthetics with contemporary functionality. Data Collection and Analysis Procedures: The data for this research is collected through a combination of area calculation, sketching, and building a 3D model. The analysis involves evaluating the design based on the allocated area, zoning, and functional requirements for a community mall. Question Addressed: The research addresses the question of how to design a community mall with a theme of ancient Medieval and Victorian eras. It explores how to combine sustainable architectural design principles with historical aesthetics to create a functional and visually appealing space. Conclusion: In conclusion, this research successfully designs a community mall called “Castle of The Mall-dern” that incorporates elements of Medieval and Victorian architecture. The building encompasses various zones, including retail shops, restaurants, community gathering areas, and service zones. It also features an interior garden and a public library within the mall. The research contributes to the field of sustainable architectural design by showcasing the potential for combining ancient architectural ideas with modern elements in an urban setting.

Keywords: 3D model, community mall, modern architecture, medieval architecture

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Authors: Chi Zhang, Hua-Peng Chen

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With the increasingly demanding resources in the word, renewable and clean energy has been considered as an alternative way to replace traditional ones. Thus, one of practical examples for using wind energy is wind turbine, which has gained more attentions in recent research. Like most offshore structures, the blades, which is the most critical components of the wind turbine, will be subjected to millions of loading cycles during service life. To operate safely in marine environments, the blades are typically made from fibre reinforced composite materials to resist fatigue delamination and harsh environment. The fatigue crack development of blades is uncertain because of indeterminate mechanical properties for composite and uncertainties under offshore environment like wave loads, wind loads, and humid environments. There are three main delamination failure modes for composite blades, and the most common failure type in practices is subjected to mixed mode loading, typically a range of opening (mode 1) and shear (mode 2). However, the fatigue crack development for mixed mode cannot be predicted as deterministic values because of various uncertainties in realistic practical situation. Therefore, selecting an effective stochastic model to evaluate the mixed mode behaviour of wind turbine blades is a critical issue. In previous studies, gamma process has been considered as an appropriate stochastic approach, which simulates the stochastic deterioration process to proceed in one direction such as realistic situation for fatigue damage failure of wind turbine blades. On the basis of existing studies, various Paris Law equations are discussed to simulate the propagation of the fatigue crack growth. This paper develops a Paris model with the stochastic deterioration modelling according to gamma process for predicting fatigue crack performance in design service life. A numerical example of wind turbine composite materials is investigated to predict the mixed mode crack depth by Paris law and the probability of fatigue failure by gamma process. The probability of failure curves under different situations are obtained from the stochastic deterioration model for comparisons. Compared with the results from experiments, the gamma process can take the uncertain values into consideration for crack propagation of mixed mode, and the stochastic deterioration process shows a better agree well with realistic crack process for composite blades. Finally, according to the predicted results from gamma stochastic model, assessment strategies for composite blades are developed to reduce total lifecycle costs and increase resistance for fatigue crack growth.

Keywords: Reinforced fibre composite, Wind turbine blades, Fatigue delamination, Mixed failure mode, Stochastic process.

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Authors: Kai-Yi Cho, Fa-Shian Chang, Lih-Tyng Hwang, Chih-Feng Liu, Jeng-Nan Lee, Shun-Min Wang, Jhu-Wei Ji

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This paper presents a ground robot which has the tracked transformative structures of the motion mechanism. The robot has a good ability to adapt to the terrain, due to the front end of the track can be deformed, it can more easily pass the more complex area, such as to climb stairs and ramp areas. Usually in the disaster area, where the terrain is generally broken and complicated, there will be many slopes, broken walls, rubble, and obstacles, then if you want the robot through this area, you need to have a good off-road performance for possible complex terrain, this robot with the transformative tracked mechanism has a strong adaptability, it can overcome the limitation of the terrains to be a good rescue robot. Also, the robot has a good flexibility in the shape of contact with the ground; that can adapt the varied terrain by the deformable track, thus able to pass the different terrains, that was verified through the experiments on a test-platform and a field test. The prototype of the robot system has been developed, and experiments are carried out to verify the validity of the proposed design.

Keywords: tracked robot, rescue robot, transformation mechanism, deformable track, hull design

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Authors: Mohammad Saberian, Reza Porhoseini, Mohammad Ali Rahgozar

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Peat is a partially carbonized vegetable tissue which is formed in wet conditions by decomposition of various plants, mosses and animal remains. This restricted definition, including only materials which are entirely of vegetative origin, conflicts with several established soil classification systems. Peat soils are usually defined as soils having more than 75 percent organic matter. Due to this composition, the structure of peat soil is highly different from the mineral soils such as silt, clay and sand. Peat has high compressibility, high moisture content, low shear strength and low bearing capacity, so it is considered to be in the category of problematic. Since this kind of soil is generally found in many countries and various zones, except for desert and polar zones, recognizing this soil is inevitably significant. The objective of this paper is to review the classification of peats based on various properties of peat soils such as organic contents, water content, color, odor, and decomposition, scholars offer various classification systems which Von Post classification system is one of the most well-known and efficient system.

Keywords: peat soil, degree of decomposition, organic content, water content, Von Post classification

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Authors: Sina Mahdavi

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Background and Objective: Multiple sclerosis (MS) is an inflammatory autoimmune disease of the CNS that affects the myelination process in the central nervous system (CNS). Complex interactions of various "environmental or infectious" factors may act as triggers in autoimmunity and disease progression. The association between viral infections, especially human endogenous retrovirus (HERV) and MS is one potential cause that is not well understood. This study aims to summarize the available data on HERV infection in MS disease progression. Materials and Methods: For this study, the keywords "Multiple sclerosis", "Human endogenous retrovirus", and "central nervous system" in the databases PubMed, Google Scholar, Sid, and MagIran between 2016 and 2022 were searched and 14 articles chosen, studied, and analyzed. Results: In the leptomeningeal cells of MS patients, a retrovirus-like element associated with reverse transcriptase (RT) activity called multiple sclerosis-associated retroviruses (MSRV) has been identified. HERVs are expressed in the human CNS despite mechanisms to suppress their expression. External factors, especially viral infections such as influenza virus, Epstein-Barr virus, and herpes simplex virus type 1, can activate HERV gene expression. The MSRV coat protein is activated by activating TLR4 at the brain surface, particularly in oligodendroglial progenitor cells and macrophages, leading to immune cascades followed by the downregulation of myelin protein expression. The HERV-K18 envelope gene (env) acts as a superantigen and induces inflammatory responses in patients with MS. Conclusion: There is a high expression of endogenous retroviruses during the course of MS, which indicates the relationship between HERV and MS, that this virus can play a role in the development of MS by creating an inflammatory state. Therefore, measures to modulate the expression of endogenous retroviruses may be effective in reducing inflammatory processes in demyelinated areas of MS patients.

Keywords: multiple sclerosis, human endogenous retrovirus, central nervous system, MSRV

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Authors: Mohammad Ahmad, Sander Gersen, Erwin Wilbers

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Carbon capture, transport and underground storage have become a major solution to reduce CO2 emissions from power plants and other large CO2 sources. A big part of this captured CO2 stream is transported at high pressure dense phase conditions and stored in offshore underground depleted oil and gas fields. CO2 is also transported in offshore pipelines to be used for enhanced oil and gas recovery. The captured CO2 stream with impurities may contain water that causes severe corrosion problems, flow assurance failure and might damage valves and instrumentations. Thus, free water formation should be strictly prevented. The purpose of this work is to study the solubility of water in pure CO2 and in CO2 mixtures under real pipeline pressure (90-150 bar) and temperature operation conditions (5-35°C). A set up was constructed to generate experimental data. The results show the solubility of water in CO2 mixtures increasing with the increase of the temperature or/and with the increase in pressure. A drop in water solubility in CO2 is observed in the presence of impurities. The data generated were then used to assess the capabilities of two mixture models: the GERG-2008 model and the EOS-CG model. By generating the solubility data, this study contributes to determine the maximum allowable water content in CO2 pipelines.

Keywords: carbon capture and storage, water solubility, equation of states, fluids engineering

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Authors: Michael Okeke, Andrew Blyth

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

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

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Authors: Yujie Zhou, Hee-Seong Byun, Sang-In Bak, Eui-Joon Kil, Kyung Joo Min, Vivek Chavan, Won Kyong Cho, Sukchan Lee, Seung-Woo Hong, Tae-Sun Park

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Fast neutron irradiation (FNI) can cause mutations on plant genome but, in the most of cases, these irradiated plants have not shown significant characteristics phenotypically. In this study, we utilized RNA-Seq to generate a high-resolution transcriptome map of the tomato (Solanum lycopersicum) genome effected by FNI. To quantify the different transcription levels in tomato irradiated by FNI, tomato seeds were irradiated by using MC-50 cyclotron (KIRAMS, Korea) for 0, 30 and 90 minutes, respectively. To investigate the effects on the pre-soaking condition, experimental groups were divided into dry and soaked seeds, which were soaked for 8 hours before irradiation. There was no noticeable difference in the percentage germination (PG) among dry seeds, while irradiated soaked seeds have about 10 % lower PG compared to the unirradiated control group. Using whole transcriptome sequencing by HiSeq 2000, we analyzed the differential gene expression in response to different time of FNI in dry and soaked seeds. More than 1.4 million base pair reads were mapped onto the tomato reference genome and the expression pattern differences between irradiated and unirradiated seeds were assessed. In 0, 30 and 90 minutes irradiation, 12,135, 28,495 and 28,675 transcripts were generated, respectively. Gene ontology analysis suggested the different enrichment of transcripts involved in response to different FNI. The present study showed that FNI effects on plant gene expression, which can become a new parameters for evaluating the responses against FNI on plants. In addition, the comparative analysis of differentially expressed genes in D and S seeds by FNI will also give us a chance to deep explore novel candidate genes for FNI, which could be a good model system to understand the mechanisms behind the adaption of plant to space biology research.

Keywords: tomato (solanum lycopersicum), fast neutron irradiation, RNA-sequence, transcriptome expression

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Authors: Yasser Elhenaw, A. Farag, Mohamed El-Ghandour, M. Shatat, G. H. Moustafa

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This study investigates the performance of two spiral-wound Air Gap Membrane Distillation (AGMD) units. These units are connected in two different configurations in order to be tested and compared experimentally. In AGMD, the coolant water is used to condensate water vapor leaving membrane via condensing plate. The rejected cooling water has a relativity high temperature which can be used, depending on operation parameters, to increase the thermal efficiency and water productivity. In the first configuration, the seawater feed flows parallel and equally through both units then rejected. The coolant water is divided into the two units, and the heat source is divided into the two heat exchangers. In the second one, only the feed of the first unit is heated while the cooling rejected from the unit is used in heating the feed to the second. The performance of the system, estimated by the water productivity as well as the Gain Output Ratio (GOR), is measured for the two configurations at different feed flow rates, temperatures and salinities. The results show that at steady state condition, the heat recovery configurations lead to an increase in water productivity by 25%.

Keywords: membrane distillation, heat transfer, heat recovery, desalination

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Authors: Thomas Monahan, Nicolas Gorius, Thanh Nguyen

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Exoplanet atmospheric parameters retrieval is a complex, computationally intensive, inverse modeling problem in which an exoplanet’s atmospheric composition is extracted from an observed spectrum. Traditional Bayesian sampling methods require extensive time and computation, involving algorithms that compare large numbers of known atmospheric models to the input spectral data. Runtimes are directly proportional to the number of parameters under consideration. These increased power and runtime requirements are difficult to accommodate in space missions where model size, speed, and power consumption are of particular importance. The use of traditional Bayesian sampling methods, therefore, compromise model complexity or sampling accuracy. The Atmospheric Retrievals conditional Generative Adversarial Network (ARcGAN) is a deep convolutional generative adversarial network that improves on the previous model’s speed and accuracy. We demonstrate the efficacy of artificial intelligence to quickly and reliably predict atmospheric parameters and present it as a viable alternative to slow and computationally heavy Bayesian methods. In addition to its broad applicability across instruments and planetary types, ARcGAN has been designed to function on low power application-specific integrated circuits. The application of edge computing to atmospheric retrievals allows for real or near-real-time quantification of atmospheric constituents at the instrument level. Additionally, edge computing provides both high-performance and power-efficient computing for AI applications, both of which are critical for space missions. With the edge computing chip implementation, ArcGAN serves as a strong basis for the development of a similar machine-learning algorithm to reduce the downlinked data volume from the Compact Ultraviolet to Visible Imaging Spectrometer (CUVIS) onboard the DAVINCI mission to Venus.

Keywords: deep learning, generative adversarial network, edge computing, atmospheric parameters retrieval

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Authors: Zhenzhen Xu, Chunfu Shao, Shengyou Wang, Chunjiao Dong

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To improve the satisfaction of residents' travel, this paper analyzes the characteristics and influencing factors of urban residents' travel behavior. First, a Multinominal Logit Model (MNL) model is built to analyze the characteristics of residents' travel behavior, reveal the influence of individual attributes, family attributes and travel characteristics on the choice of travel mode, and identify the significant factors. Then put forward suggestions for policy improvement. Finally, Support Vector Machine (SVM) and Multi-Layer Perceptron (MLP) models are introduced to evaluate the policy effect. This paper selects Futian Street in Futian District, Shenzhen City for investigation and research. The results show that gender, age, education, income, number of cars owned, travel purpose, departure time, journey time, travel distance and times all have a significant influence on residents' choice of travel mode. Based on the above results, two policy improvement suggestions are put forward from reducing public transportation and non-motor vehicle travel time, and the policy effect is evaluated. Before the evaluation, the prediction effect of MNL, SVM and MLP models was evaluated. After parameter optimization, it was found that the prediction accuracy of the three models was 72.80%, 71.42%, and 76.42%, respectively. The MLP model with the highest prediction accuracy was selected to evaluate the effect of policy improvement. The results showed that after the implementation of the policy, the proportion of public transportation in plan 1 and plan 2 increased by 14.04% and 9.86%, respectively, while the proportion of private cars decreased by 3.47% and 2.54%, respectively. The proportion of car trips decreased obviously, while the proportion of public transport trips increased. It can be considered that the measures have a positive effect on promoting green trips and improving the satisfaction of urban residents, and can provide a reference for relevant departments to formulate transportation policies.

Keywords: neural network, travel characteristics analysis, transportation choice, travel sharing rate, traffic resource allocation

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Authors: Fouzi Aboura

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The fractional order proportional-integral-derivative (FOPID) controller or fractional order (PIλDµ) is a proportional-integral-derivative (PID) controller where integral order (λ) and derivative order (µ) are fractional, one of the important application of classical PID is the Automatic Voltage Regulator (AVR).The FOPID controller needs five parameters optimization while the design of conventional PID controller needs only three parameters to be optimized. In our paper we have proposed a comparison between algorithms Differential Evolution (DE) and Hybrid Genetic Algorithm Particle Swarm Optimization (HGAPSO) ,we have studied theirs characteristics and performance analysis to find an optimum parameters of the FOPID controller, a new objective function is also proposed to take into account the relation between the performance criteria’s.

Keywords: FOPID controller, fractional order, AVR system, objective function, optimization, GA, PSO, HGAPSO

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Authors: Morteza Raminnia

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In this study, dynamic analysis of functionally graded nano-composite pipe reinforced by single-walled carbon nano-tubes (SWCNTs) with simply supported boundary condition subjected to moving mechanical loads is investigated. The material properties of functionally graded carbon nano tube-reinforced composites (FG-CNTRCs) are assumed to be graded in the thickness direction and are estimated through a micro-mechanical model. In this paper polymeric matrix considered as isotropic material and for the CNTRC, uniform distribution (UD) and three types of FG distribution patterns of SWCNT reinforcements are considered. The system equation of motion is derived by using Hamilton's principle under the assumptions of first order shear deformation theory (FSDT).The thin piezoelectric layers embedded on inner and outer surfaces of FG-CNTRC layer are acted as distributed sensor and actuator to control dynamic characteristics of the FG-CNTRC laminated pipe. The modal analysis technique and Newmark's integration method are used to calculate the displacement and dynamic stress of the pipe subjected to moving loads. The effects of various material distribution and velocity of moving loads on dynamic behavior of the pipe is presented. This present approach is validated by comparing the numerical results with the published numerical results in literature. The results show that the above-mentioned effects play very important role on dynamic behavior of the pipe .This present work shows that some meaningful results that which are interest to scientific and engineering community in the field of FGM nano-structures.

Keywords: nano-composite, functionally garded material, moving load, active control, PZT layers

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Authors: Jamshaid Ul Rahman, Faiza Makhdoom, Dianchen Lu

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Activation functions play a decisive role in determining the capacity of Deep Neural Networks (DNNs) as they enable neural networks to capture inherent nonlinearities present in data fed to them. The prior research on activation functions primarily focused on the utility of monotonic or non-oscillatory functions, until Growing Cosine Unit (GCU) broke the taboo for a number of applications. In this paper, a Convolutional Neural Network (CNN) model named as ASU-CNN is proposed which utilizes recently designed activation function ASU across its layers. The effect of this non-monotonic and oscillatory function is inspected through feature map visualizations from different convolutional layers. The optimization of proposed network is offered by Adam with a fine-tuned adjustment of learning rate. The network achieved promising results on both training and testing data for the classification of CIFAR-10. The experimental results affirm the computational feasibility and efficacy of the proposed model for performing tasks related to the field of computer vision.

Keywords: amplifying sine unit, activation function, convolutional neural networks, oscillatory activation, image classification, CIFAR-10

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Authors: Choi Younshick, Lee Wonseok, Lee Jaemeun, Park Sun-Hyun, Kim Sunwoung, Park Sua, Kim Eun Ho, Kim Jong-Ki

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Iron accumulation in the brain accelerates Alzheimer’s disease progression. To cure iron toxicity, we assessed the therapeutic effects of noncontact transcranial electric field stimulation to the brain on toxic iron deposits in either the Aβ-fibril structure or the Aβ plaque in a mouse model of Alzheimer’s disease (AD). A capacitive electrode-based alternating electric field (AEF) was applied to a suspension of magnetite (Fe₃O₄) to measure the field-sensitized electro-Fenton effect and resultant reactive oxygen species (ROS) generation. The increase in ROS generation compared to the untreated control was both exposure-time and AEF-frequency dependent. The frequency-specific exposure of AEF to 0.7–1.4 V/cm on a magnetite-bound Aβ-fibril or a transgenic Alzheimer’s disease (AD) mouse model revealed the removal of intraplaque ferrous magnetite iron deposit and Aβ-plaque burden together at the same time compared to the untreated control. The results of the behavioral tests show an improvement in impaired cognitive function following AEF treatment on the AD mouse model. Western blot assay found some disease-modifying biological responses, including down-regulating ferroptosis, neuroinflammation and reactive astrocytes that eventually made cognitive improvement feasible. Tissue clearing and 3D-imaging analysis revealed no induced damage to the neuronal structures of normal brain tissue following AEF treatment. In conclusion, our results suggest that the effective degradation of magnetite-bound amyloid fibrils or plaques in the AD brain by the electro-Fenton effect from electric field-sensitized magnetite offers a potential electroceutical treatment option for AD.

Keywords: electroceutical, intraplaque magnetite, alzheimer’s disease, transcranial electric field, electro-fenton effect

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Authors: Augustine Okolie, Johannes Müller, Mirjam Kretzchmar

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We adopt a maximum-likelihood framework to estimate parameters of a stochastic susceptible-infected-recovered (SIR) model with contact tracing on a rooted random tree. Given the number of detectees per index case, our estimator allows to determine the degree distribution of the random tree as well as the tracing probability. Since we do not discover all infectees via contact tracing, this estimation is non-trivial. To keep things simple and stable, we develop an approximation suited for realistic situations (contract tracing probability small, or the probability for the detection of index cases small). In this approximation, the only epidemiological parameter entering the estimator is the basic reproduction number R0. The estimator is tested in a simulation study and applied to covid-19 contact tracing data from India. The simulation study underlines the efficiency of the method. For the empirical covid-19 data, we are able to compare different degree distributions and perform a sensitivity analysis. We find that particularly a power-law and a negative binomial degree distribution meet the data well and that the tracing probability is rather large. The sensitivity analysis shows no strong dependency on the reproduction number.

Keywords: stochastic SIR model on graph, contact tracing, branching process, parameter inference

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Authors: Hsiang-Yu Yuan, Marc Baguelin, Kin O. Kwok, Nimalan Arinaminpathy, Edwin Leeuwen, Steven Riley

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Traditional syndromic surveillance for influenza has substantial public health value in characterizing epidemics. Because the relationship between syndromic incidence and the true infection events can vary from one population to another and from one year to another, recent studies rely on combining serological test results with syndromic data from traditional surveillance into epidemic models to make inference on epidemiological processes of influenza. However, despite the widespread availability of serological data, epidemic models have thus far not explicitly represented antibody titre levels and their correspondence with immunity. Most studies use dichotomized data with a threshold (Typically, a titre of 1:40 was used) to define individuals as likely recently infected and likely immune and further estimate the cumulative incidence. Underestimation of Influenza attack rate could be resulted from the dichotomized data. In order to improve the use of serosurveillance data, here, a refinement of the concept of the stratified immunity within an epidemic model for influenza transmission was proposed, such that all individual antibody titre levels were enumerated explicitly and mapped onto a variable scale of susceptibility in different age groups. Haemagglutination inhibition titres from 523 individuals and 465 individuals during pre- and post-pandemic phase of the 2009 pandemic in Hong Kong were collected. The model was fitted to serological data in age-structured population using Bayesian framework and was able to reproduce key features of the epidemics. The effects of age-specific antibody boosting and protection were explored in greater detail. RB was defined to be the effective reproductive number in the presence of stratified immunity and its temporal dynamics was compared to the traditional epidemic model using use dichotomized seropositivity data. Deviance Information Criterion (DIC) was used to measure the fitness of the model to serological data with different mechanisms of the serological response. The results demonstrated that the differential antibody response with age was present (ΔDIC = -7.0). The age-specific mixing patterns with children specific transmissibility, rather than pre-existing immunity, was most likely to explain the high serological attack rates in children and low serological attack rates in elderly (ΔDIC = -38.5). Our results suggested that the disease dynamics and herd immunity of a population could be described more accurately for influenza when the distribution of immunity was explicitly represented, rather than relying only on the dichotomous states 'susceptible' and 'immune' defined by the threshold titre (1:40) (ΔDIC = -11.5). During the outbreak, RB declined slowly from 1.22[1.16-1.28] in the first four months after 1st May. RB dropped rapidly below to 1 during September and October, which was consistent to the observed epidemic peak time in the late September. One of the most important challenges for infectious disease control is to monitor disease transmissibility in real time with statistics such as the effective reproduction number. Once early estimates of antibody boosting and protection are obtained, disease dynamics can be reconstructed, which are valuable for infectious disease prevention and control.

Keywords: effective reproductive number, epidemic model, influenza epidemic dynamics, stratified immunity

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Authors: Michael Kenomore, Mohamed Hassan, Amjad Shah, Hom Dhakal

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Shale gas reservoirs have been of greater importance compared to shale oil reservoirs since 2009 and with the current nature of the oil market, understanding the technical and economic performance of shale gas reservoirs is of importance. Using the Barnett shale as a case study, an economic model was developed to quantify the effect of finding and development costs and gas prices on the basins in the Barnett shale using net present value as an evaluation parameter. A rate of return of 20% and a payback period of 60 months or less was used as the investment hurdle in the model. The Barnett was split into four basins (Strawn Basin, Ouachita Folded Belt, Forth-worth Syncline and Bend-arch Basin) with analysis conducted on each of the basin to provide a holistic outlook. The dataset consisted of only horizontal wells that started production from 2008 to at most 2015 with 1835 wells coming from the strawn basin, 137 wells from the Ouachita folded belt, 55 wells from the bend-arch basin and 724 wells from the forth-worth syncline. The data was analyzed initially on Microsoft Excel to determine the estimated ultimate recoverable (EUR). The range of EUR from each basin were loaded in the Palisade Risk software and a log normal distribution typical of Barnett shale wells was fitted to the dataset. Monte Carlo simulation was then carried out over a 1000 iterations to obtain a cumulative distribution plot showing the probabilistic distribution of EUR for each basin. From the cumulative distribution plot, the P10, P50 and P90 EUR values for each basin were used in the economic model. Gas production from an individual well with a EUR similar to the calculated EUR was chosen and rescaled to fit the calculated EUR values for each basin at the respective percentiles i.e. P10, P50 and P90. The rescaled production was entered into the economic model to determine the effect of the finding and development cost and gas price on the net present value (10% discount rate/year) as well as also determine the scenario that satisfied the proposed investment hurdle. The finding and development costs used in this paper (assumed to consist only of the drilling and completion costs) were £1 million, £2 million and £4 million while the gas price was varied from $2/MCF-$13/MCF based on Henry Hub spot prices from 2008-2015. One of the major findings in this study was that wells in the bend-arch basin were least economic, higher gas prices are needed in basins containing non-core counties and 90% of the Barnet shale wells were not economic at all finding and development costs irrespective of the gas price in all the basins. This study helps to determine the percentage of wells that are economic at different range of costs and gas prices, determine the basins that are most economic and the wells that satisfy the investment hurdle.

Keywords: shale gas, Barnett shale, unconventional gas, estimated ultimate recoverable

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Authors: Priyadarsini Samal, Rajesh Singla

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Many mobile games come with the benefits of entertainment by introducing stress to the human brain. In recognizing this mental stress, the brain-computer interface (BCI) plays an important role. It has various neuroimaging approaches which help in analyzing the brain signals. Electroencephalogram (EEG) is the most commonly used method among them as it is non-invasive, portable, and economical. Here, this paper investigates the pattern in brain signals when introduced with mental stress. Two healthy volunteers played a game whose aim was to search hidden words from the grid, and the levels were chosen randomly. The EEG signals during gameplay were recorded to investigate the impacts of stress with the changing levels from easy to medium to hard. A total of 16 features of EEG were analyzed for this experiment which includes power band features with relative powers, event-related desynchronization, along statistical features. Support vector machine was used as the classifier, which resulted in an accuracy of 93.9% for three-level stress analysis; for two levels, the accuracy of 92% and 98% are achieved. In addition to that, another game that was similar in nature was played by the volunteers. A suitable regression model was designed for prediction where the feature sets of the first and second game were used for testing and training purposes, respectively, and an accuracy of 73% was found.

Keywords: brain computer interface, electroencephalogram, regression model, stress, word search

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Authors: Manam Hanfi

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Pakistan is a victim of terrorism since 9/11 attacks. Since then it is a home for violence and extremism. One of the major reasons behind rising violence and extremism in Pakistan is radicalization. Pakistan has seen and suffered from the modification of terrorism from old to new. In new terrorism, the terrorist organizations incorporated internet to disseminate propaganda, to recruit and train people. The study focuses on the relationship between Pakistan and new terrorism and examines how the internet is being used by terrorist organizations. The study investigates radicalization through social media by terrorist organizations in Pakistan with the help of case studies. The study suggests five ways to counter radicalization, including, counter narrative on social media, content analysis of the data on the internet, curriculum and madrassa reforms, teaching peace education in the educational institutions and use of technical software such as eGLYPH to quickly remove violent data from social media. Lastly, the research attempted to contribute in counter-radicalization by combining the media dependency model and ideas for counter-radicalization. The dependency model elaborates the impact of mass media content on the audience. If media dependency is high, it will cause cognitive, affective and behavioral changes. In order to counter radicalization through social media, it is important to make cognitive, affective and behavioral changes with the help of counter-radicalization suggestions.

Keywords: counter radicalization, extremism, social media, terrorism

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Authors: Dong Nyoung Heo, Il Keun Kwon

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Three-dimensional (3D) technology is a promising method for bone tissue engineering. In order to enhance bone tissue regeneration, it is important to have ideal 3D constructs with biomimetic mechanical strength, structure interconnectivity, roughened surface, and the presence of chemical functionality. In this respect, a 3D printing system combined with cold atmospheric plasma (CAP) was developed to fabricate a 3D construct that has a rough surface with polar functional chemical groups. The CAP-etching process leads to oxidation of chemical groups existing on the polycaprolactone (PCL) surface without conformational change. The surface morphology, chemical composition, mean roughness of the CAP-treated PCL surfaces were evaluated. 3D printed constructs composed of CAP-treated PCL showed an effective increment in the hydrophilicity and roughness of the PCL surface. Also, an in vitro study revealed that CAP-treated 3D PCL constructs had higher cellular behaviors such as cell adhesion, cell proliferation, and osteogenic differentiation. Therefore, a 3D printing system with CAP can be a highly useful fabrication method for bone tissue regeneration.

Keywords: bone tissue engineering, cold atmospheric plasma, PCL, 3D printing

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Authors: Abdulrahman S. Alqahtani

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The revolution of computing and networks could revolutionise terrorism in the same way that it has brought about changes in other aspects of life. The modern technological era has faced countries with a new set of security challenges. There are many states and potential adversaries who have the potential and capacity in cyberspace, which makes them able to carry out cyber-attacks in the future. Some of them are currently conducting surveillance, gathering and analysis of technical information, and mapping of networks and nodes and infrastructure of opponents, which may be exploited in future conflicts. This poster presents the results of the quantitative study (survey) to test the validity of the proposed theoretical framework for the cyber terrorist threats. This theoretical framework will help to in-depth understand these new digital terrorist threats. It may also be a practical guide for managers and technicians in critical infrastructure, to understand and assess the threats they face. It might also be the foundation for building a national strategy to counter cyberterrorism. In the beginning, it provides basic information about the data. To purify the data, reliability and exploratory factor analysis, as well as confirmatory factor analysis (CFA) were performed. Then, Structural Equation Modelling (SEM) was utilised to test the final model of the theory and to assess the overall goodness-of-fit between the proposed model and the collected data set.

Keywords: cyberterrorism, critical infrastructure, , national security, theoretical framework, terrorism

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Authors: C. Puangsawat, C. Limotai, P. Srikhachin

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Bio-psycho-social caring was required for promoting the quality of life of the patients with epilepsy (PWE), despite controlled seizures. Multifaceted issues emerge at the epilepsy clinic. Unpredicted seizures, antiepileptic drug compliance problems/adverse effects, psychiatric, and social problems are all needed to be explored and managed. The Nursing Service System (NSS) at the tertiary epilepsy clinic (TEC) was consequently developed for improving the clinical care for PWE. Case manager concept was integrated as the framework guiding the processes and strategies used for developing the NSS as well as the roles of the multidisciplinary team at the clinic. This study aimed to report the outcomes of the developed NSS integrated case manager concept. The processes of our developed NSS program included 1) screening for patient’s problems using questionnaire prior to seeing epileptologists i.e., assessing the patient’s risk to develop acute seizures at the clinic, issues related to medication use, and uncovered psychiatric and social problems; and 2) assigning the patients at risk to be evaluated and managed by appropriate team. Nurses specializing in epilepsy in coordination with the multidisciplinary team implemented the NSS to promote coordinated work among the team which consists of epileptologists, nurses, pharmacists, psychologists, and social workers. Determination of the role of each person and their responsibilities along with joint care plan were clearly established. One year after implementation, the rate of acute seizure occurrence at the clinic was decreased, and satisfactory feedback from the patients was received. In order to achieve an optimal goal to promote self-management behaviors in PWE, continuing the NSS and systematic assessment of its effectiveness is required.

Keywords: case manager concept, nursing service system, patients with epilepsy, quality of life

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Authors: Shierwin Agagen Cabunilas

Abstract:

The unitary form of Philippine government has built a tradition of bureaucracy that strengthened oligarch and clientele politics. Consequently, the Philippines is lagged behind development. There is so much poverty, unemployment, and inadequate social services. In addition, it seems that the rights of national ethnic minority groups like the Igorots to develop their political and economic interests, linguistic and cultural heritage are neglected. Given these circumstances, a paradigm shift is inevitable. The author advocates a transition from a unitary to a federal system of government. Contrary to the notion that a unitary system facilitates better governance, it actually stifles it. As a unitary government, the Philippines seems (a) to exhibit incompetence in delivering efficient, necessary services to the people and (b) to exclude the minority from political participation and policy making. This shows that Philippine unitary system is highly centralized and operates from a top-bottom scheme. However, a federal system encourages decentralization, plurality and political participation. In my view, federalism is beneficial to the Philippine society and congenial to the Igorot indigenous peoples insofar as participative decision-making and development goals are concerned. This research employs critical and constructive analyses. The former interprets some complex practices of Philippine politics while the latter investigates how theories of federalism can be appropriated to deal with political deficits, ethnic diversity, and indigenous peoples’ rights to self-determination. The topic is developed accordingly: First, the author briefly examines the unitary structure of the Philippines and its impact on inter-governmental affairs and processes, asserting that bureaucracy and corruption, for example, are counterproductive to a participative political life, to economic development and to the recognition of national ethnic minorities. Second, he scrutinizes why federalism might transform this. Here, he assesses various opposing philosophical contentions on federal system in managing ethnically diverse society, like the Philippines, and argue that decentralization of political power, economic and cultural developments are reasons to exit from unitary government. Third, he suggests that federalism can be instrumental to Igorots self-determination. Self-determination is neither opposed to national development nor to the ideals of democracy – liberty, justice, solidarity. For example, as others have already noted, a politics in the vernacular facilitates greater participation among the people. Hence, there is a greater chance to arrive at policies that serve the interest of the people. Some may wary that decentralization disintegrates a nation. According to the author, however, the recognition of minority rights which includes self-determination may promote filial devotion to the state. If Igorot indigenous peoples have access to suitable institutions to determine their political life, economic goals, social needs, i.e., education, culture, language, chances are it moves the country forward to development fostering national unity. Remarkably, federal system thus best responds to the Philippines’s democratic and development deficits. Federalism can also significantly rectify the practices that oppress and dislocate national ethnic minorities as it ensures the creation of localized institutions for optimum political, economic, cultural determination and maximizes representation in the public sphere.

Keywords: federalism, Igorot, indigenous peoples, self-determination

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