Search results for: fifth generation of bonding agent

Authors: Riad

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As present world needs more and more energy in a low cost way, it needs to find out the optimal way of power generation. In the sense of low cost, renewable energy is one of the greatest sources of power generation. Water vapour of sea/river/lake can be used for power generation by using the greenhouse effect in a large flat type water chamber floating on the water surface. The water chamber will always be kept half filled. When water evaporates by sunlight, the high pressured gaseous water will be stored in the chamber. By passing through a pipe and by using aerodynamics it can be used for power generation. The water level of the chamber is controlled by some means. As a large amount of water evaporates, an estimation can be highlighted, approximately 3 to 4 thousand gallons of water evaporates from per acre of surface (this amount will be more by greenhouse effect). This large amount of gaseous water can be utilized for power generation by passing through a pipe. This method can be a source of power generation.

Keywords: renewable energy, greenhouse effect, water chamber, water vapour

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Authors: Hiroyuki Aoki

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Molecular imaging has attracted much attention recently, which visualizes biological molecules, cells, tissue, and so on. Among various in vivo imaging techniques, the fluorescence imaging method has been widely employed as a useful modality for small animals in pre-clinical researches. However, the higher signal intensity is needed for highly sensitive in vivo imaging. The objective of the current study is the development of a fluorescent imaging agent with high brightness for the tumor imaging of a mouse. The strategy to enhance the fluorescence signal of a bio-imaging agent is the increase of the absorption of the excitation light and the fluorescence conversion efficiency. We developed a nano-particle fluorescence imaging agent consisting of a π-conjugated polymer emitting a fluorescence signal in a near infrared region. A large absorption coefficient and high emission intensity at a near infrared optical window for biological tissue enabled highly sensitive in vivo imaging with a tumor-targeting ability by an EPR (enhanced permeation and retention) effect. The signal intensity from the π-conjugated fluorescence imaging agent is larger by two orders of magnitude compared to a quantum dot, which has been known as the brightest imaging agent. The π-conjugated polymer nano-particle would be a promising candidate in the in vivo imaging of small animals.

Keywords: fluorescence, conjugated polymer, in vivo imaging, nano-particle, near-infrared

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Authors: Nadia Ezzat Al-Kirbasee, Ahlam Hussein Hassan, Shatha Raheem Helal Alhimidi, Doaa Ezzat Al-Kirbasee, Muhsen Abood Muhsen Al-Ibadi

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Through DFT/QTAIM calculations, we have provided new insights into the nature of the M-M, M-H, M-O, and M-C bonds of the (Cp*Ru)n(Cp*Os)3−n(μ3-O)2(μ-H)(Cp* = η5-C5Me5, n= 3,2,1,0). The topological analysis of the electron density reveals important details of the chemical bonding interactions in the clusters. Calculations confirm the absence of bond critical points (BCP) and the corresponding bond paths (BP) between Ru-Ru, Ru-Os, and Os-Os. The position of bridging hydrides and Oxo atoms coordinated to Ru-Ru, Ru-Os, and Os-Os determines the distribution of the electron densities and which strongly affects the formation of the bonds between these transition metal atoms. On the other hand, the results confirm that the four clusters contain a 6c–12e and 4c–2e bonding interaction delocalized over M3(μ-H)(μ-O)2 and M3(μ-H), respectively, as revealed by the non-negligible delocalization indexes calculations. The small values for electron density ρ(b) above zero, together with the small values, again above zero, for laplacian ∇2ρ(b) and the small negative values for total energy density H(b) are shown by the Ru-H, Os-H, Ru-O, and Os-O bonds in the four clusters are typical of open shell interactions. Also, the topological data for the bonds between Ru and Os atoms with the C atoms of the pentamethylcyclopentadienyl (Cp*) ring ligands are basically similar and show properties very consistent with open shell interactions in the QTAIM classification.

Keywords: metal-metal and metal-ligand interactions, organometallic complexes, topological analysis, DFT and QTAIM analyses

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Authors: M. Taheri Tehrani, H. Ajorloo

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In this paper, an intelligent multi-agent framework is developed for each router in which agents have two vital functionalities, traffic shaping and buffer allocation and are positioned in the ports of the routers. With traffic shaping functionality agents shape the traffic forward by dynamic and real time allocation of the rate of generation of tokens in a Token Bucket algorithm and with buffer allocation functionality agents share their buffer capacity between each other based on their need and the conditions of the network. This dynamic and intelligent framework gives this opportunity to some ports to work better under burst and more busy conditions. These agents work intelligently based on Reinforcement Learning (RL) algorithm and will consider effective parameters in their decision process. As RL have limitation considering much parameter in its decision process due to the volume of calculations, we utilize our novel method which invokes Principle Component Analysis (PCA) on the RL and gives a high dimensional ability to this algorithm to consider as much as needed parameters in its decision process. This implementation when is compared to our previous work where traffic shaping was done without any sharing and dynamic allocation of buffer size for each port, the lower packet drop in the whole network specifically in the source routers can be seen. These methods are implemented in our previous proposed intelligent simulation environment to be able to compare better the performance metrics. The results obtained from this simulation environment show an efficient and dynamic utilization of resources in terms of bandwidth and buffer capacities pre allocated to each port.

Keywords: principal component analysis, reinforcement learning, buffer allocation, multi- agent systems

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Authors: Hyeong-Jin Kim, Jong Kook Lee

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Zirconia has biological, mechanical and optical properties, so, it used as a dental implant material in human body. But, it is difficult to form directly bonding with living tissues after the procedure and induces the falling away from implanted parts of the body. To improve this phenomenon, it is essential to increase the surface roughness of zirconia implants and induce a forming-ability of strong bonds. In this study, we performed a room temperature spray coating on zirconia specimen to obtain a highly roughened zirconia surface. To get optimal surface roughness, we controlled the distance between the nozzle and the substrate, coating times and powder condition. Bonding microstructure, surface roughness, and chemical composition of the coating layer were observed by SEM, XRD and roughness tester.

Keywords: implant, aerosoldeposition, zirconia, dental

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Authors: Narsimhulu Sanke, D. N. Reddy

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The purpose of the paper is to discuss the biomass as a renewable source of energy for power generation. The setup is designed and fabricated in the Centre for Energy Technology (CET) and four different fuels are tested in the laboratory, but here the focus is on wood blocks (fuel) combustion with temperature, gas composition percentage by volume and the heating values.

Keywords: biomass, downdraft gasifier, power generation, renewable energy sources

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Authors: Muazzam Ali Khan Khattak

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Next Generation Network is combination of different networks having different technologies. Due to mobile nature of nodes the movement of nodes occurs from one network to another network. Multicasting in such networks is still a hot issue of research because the user in today's world wants reliable communication wherever it lies. Due to heterogeneity of NGN it is very difficult to handle reliable multicast communication. In this paper we proposed an improved scheme for reliable multicast communication in next generation networks. Because multicast communication is very important to deliver same data packets to multiple receivers and minimize the network traffic. This new scheme will make the multicast communication in NGN more reliable and efficient.

Keywords: next generation networks, route request, IPT, NACK, ARQ, DTN

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Authors: Rishi Prajapati

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3G is the abbreviation of third generation of wireless mobile telecommunication technologies. 3G is a mode that finds application in wireless voice telephony, mobile internet access, fixed wireless internet access, video calls and mobile TV. It also provides mobile broadband access to smartphones and mobile modems in laptops and computers. The first 3G networks were introduced in 1998, followed by 4G networks in 2008. 4G is the abbreviation of fourth generation of wireless mobile telecommunication technologies. 4G is termed to be the advanced form of 3G. 4G was firstly introduced in South Korea in 2007. Many abstracts have floated researches that depicted the diversity and similarity between the third and the fourth generation of wireless mobile telecommunications technology, whereas this abstract reflects the study that focuses on analyzing the preference between 3G versus 4G given by the elite group of the Indian society who are known as adolescents or the Millennial Generation aging from 18 years to 25 years. The Millennial Generation was chosen for this study as they have the easiest access to the latest technology. A sample size of 200 adolescents was selected and a structured survey was carried out which had several closed ended as well as open ended questions, to aggregate the result of this study. It was made sure that the effect of environmental factors on the subjects was as minimal as possible. The data analysis comprised of primary data collection reflecting it as quantitative research. The rationale behind this research is to give brief idea of how 3G and 4G are accepted by the Millennial Generation in India. The findings of this research would materialize a framework which depicts whether Millennial Generation would prefer 4G over 3G or vice versa.

Keywords: fourth generation, wireless telecommunication technology, Indian society, millennial generation, market research, third generation

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Authors: Yeliz Ekinci, Melis Koyuncu

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Successful planning of solid waste management systems requires successful prediction of the amount of solid waste generated in an area. Waste management planning can protect the environment and human health, hence it is tremendously important for countries. The lack of information in waste generation can cause many environmental and health problems. Turkey is a country that plans to join European Union, hence, solid waste management is one of the most significant criteria that should be handled in order to be a part of this community. Solid waste management system requires a good forecast of solid waste generation. Thus, this study aims to forecast solid waste generation in Turkey. Artificial Neural Network and Linear Regression models will be used for this aim. Many models will be run and the best one will be selected based on some predetermined performance measures.

Keywords: forecast, solid waste generation, solid waste management, Turkey

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Authors: Umarov Jamshid, Ju-Su Kim, Hak-Jun Lee, Man-Kyo Han, Ryum-Duck Oh

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Recently, it becomes convenient to identify the location information of cargos by using GPS and wireless communication technologies. The development of IoT technologies and tracking system allows us to confirm site situation on an ad hoc basis in all the industries and social environments. Moreover, it allows us to apply IT technologies to a manageable extent. However, there have been many limitations for using the system due to the difficulty of identifying location information in real time and also due to the simple features. To globalize the logistics related tracking system, it is required to conduct a study to resolve the aforementioned problem. On that account, this paper designed and developed the IoT and RTLS based intelligent multi tracking agent system for more secure, accurate and reliable transportation in relation to logistics.

Keywords: GPS, tracking agent system, IoT, RTLS, Logistics

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Authors: Monica Hoeldtke Pietruchinski, Andrey Ricardo Pimentel

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The teaching of computer programming for beginners has been presented to the community as a not simple or trivial task. Several methodologies and research tools have been developed; however, the problem still remains. This paper aims to present multi-agent system architecture to be incorporated to the educational collaborative game software for teaching programming that monitors, evaluates and encourages collaboration by the participants. A literature review has been made on the concepts of Collaborative Learning, Multi-agents systems, collaborative games and techniques to teach programming using these concepts simultaneously.

Keywords: architecture of multi-agent systems, collaborative evaluation, collaboration assessment, gamifying educational software

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Authors: Sagir M. Yusuf, Chris Baber

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We describe issues bedeviling the coordination of heterogeneous (different sensors carrying agents) multi-agent missions such as belief conflict, situation reasoning, etc. We applied Bayesian and agents' presumptions inferential reasoning to solve the outlined issues with the heterogeneous multi-agent belief variation and situational-base reasoning. Bayesian Belief Network (BBN) was used in modeling the agents' belief conflict due to sensor variations. Simulation experiments were designed, and cases from agents’ missions were used in training the BBN using gradient descent and expectation-maximization algorithms. The output network is a well-trained BBN for making inferences for both agents and human experts. We claim that the Bayesian learning algorithm prediction capacity improves by the number of training data and argue that it enhances multi-agents robustness and solve agents’ sensor conflicts.

Keywords: distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence

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Authors: Antonio A. M. Laudani, Igor O. Golosnoy, Ole T. Thomsen

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Rotor blades of large, modern wind turbines are highly susceptible to downward lightning strikes, as well as to triggering upward lightning; consequently, it is necessary to equip them with an effective lightning protection system (LPS) in order to avoid any damage. The performance of existing LPSs is affected by carbon fibre reinforced polymer (CFRP) structures, which lead to lightning-induced damage in the blades, e.g. via electrical sparks. A solution to prevent internal arcing would be to electrically bond the LPS and the composite structures such that to obtain the same electric potential. Nevertheless, elevated temperatures are achieved at the joint interfaces because of high contact resistance, which melts and vaporises some of the epoxy resin matrix around the bonding. The produced high-pressure gasses open up the bonding and can ignite thermal sparks. The objective of this paper is to predict the current density distribution and the temperature field in the adhesive joint cross-section, in order to check whether the resin pyrolysis temperature is achieved and any damage is expected. The finite element method has been employed to solve both the current and heat transfer problems, which are considered weakly coupled. The mathematical model for electric current includes Maxwell-Ampere equation for induced electric field solved together with current conservation, while the thermal field is found from heat diffusion equation. In this way, the current sub-model calculates Joule heat release for a chosen bonding configuration, whereas the thermal analysis allows to determining threshold values of voltage and current density not to be exceeded in order to maintain the temperature across the joint below the pyrolysis temperature, therefore preventing the occurrence of outgassing. In addition, it provides an indication of the minimal number of bonding points. It is worth to mention that the numerical procedures presented in this study can be tailored and applied to any type of joints other than adhesive ones for wind turbine blades. For instance, they can be applied for lightning protection of aerospace bolted joints. Furthermore, they can even be customized to predict the electromagnetic response under lightning strikes of other wind turbine systems, such as nacelle and hub components.

Keywords: carbon fibre reinforced polymer, equipotential bonding, finite element method, FEM, lightning protection system, LPS, wind turbine blades

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Authors: Rahul S. Raj

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Electro-mechanical impedance technique is a recently developed non-destructive method for structural health monitoring. This system comprises of piezo electric patch, bonded to the structure using an adhesive/epoxy and electrically excited to determine the health of the component. The subjected electric field actuates the PZT patch harmonically and imparts a force on the host structure. The structural response thus produced by the host component is in the form of peaks and valleys which further shows the admittance signatures of the structure for the given excitation frequency. Adhesives have the capability to change the structural signatures, in EMI technique, by transforming conductance and susceptance signatures. The static approximation provide a justifiable result where adhesive bond lines are thin and stiff. The epoxy adhesive bonds limits design flexibility due to poor bond strengths, hence to enhance the performance of the joints, a new technique is developed for joining PZT, i.e. the alloy bonding technique. It is a metallic joining compound which contains many active elements including Titanium, that reacts with the tenacious surface films of the ceramic and composites to create excellent bonds. This alloy-based bonding technique will be used for better strain interaction and rigorous stress transfer between PZT patch and the host structure.

Keywords: EMI technique, conductance, susceptance, admittance, alloy bonding

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Authors: Arslan Ellahi, Syed Amjad Hussain

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Software Testing is a vital process in software development life cycle. We can attain the quality of software after passing it through software testing phase. We have tried to find out automatic test data generation techniques that are a key research area of software testing to achieve test automation that can eventually decrease testing time. In this paper, we review some of the approaches presented in the literature which use evolutionary search based algorithms like Genetic Algorithm, Particle Swarm Optimization (PSO), etc. to validate the test data generation process. We also look into the quality of test data generation which increases or decreases the efficiency of testing. We have proposed test data generation techniques for model-based testing. We have worked on tuning and fitness function of PSO algorithm.

Keywords: search based, evolutionary algorithm, particle swarm optimization, genetic algorithm, test data generation

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Authors: G. B. Hong

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Liquid-Liquid Equilibrium (LLE) data are measured for the ternary mixtures of water + 1-butanol + butyl acetate and quaternary mixtures of water + 1-butanol + butyl acetate + glycerol at atmospheric pressure at 313.15 K. In addition, isothermal Vapor–Liquid–Liquid Equilibrium (VLLE) data are determined experimentally at 333.15 K. The region of heterogeneity is found to increase as the hydrophilic agent (glycerol) is introduced into the aqueous mixtures. The experimental data are correlated with the NRTL model. The predicted results from the solution model with the model parameters determined from the constituent binaries are also compared with the experimental values.

Keywords: LLE, VLLE, hydrophilic agent, NRTL

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Authors: Yufen Qin

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Topic-to-Essay generation is a challenging task in Natural language processing, which aims to generate novel, diverse, and topic-related text based on user input. Previous research has overlooked the generation of articles under the constraints of event elements, resulting in issues such as incomplete event elements and logical inconsistencies in the generated results. To fill this gap, this paper proposes an event-constrained approach for a topic-to-essay generation that enforces the completeness of event elements during the generation process. Additionally, a language model is employed to verify the logical consistency of the generated results. Experimental results demonstrate that the proposed model achieves a better BLEU-2 score and performs better than the baseline in terms of subjective evaluation on a real dataset, indicating its capability to generate higher-quality topic-related text.

Keywords: event element, language model, natural language processing, topic-to-essay generation.

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Authors: Rio Hirakawa, Christian Gundlach, Sven Hartwig

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In recent years, the use of aluminium has further expanded and is expected to replace steel in the future as vehicles become lighter and more recyclable in order to reduce greenhouse gas (GHG) emissions and improve fuel economy. In line with this, structures and components are becoming increasingly multi-material, with different materials, including aluminium, being used in combination to improve mechanical utility and performance. A common method of assembling dissimilar materials is mechanical fastening, but it has several drawbacks, such as increased manufacturing processes and the influence of substrate-specific mechanical properties. Adhesive bonding and fusion bonding are methods that overcome the above disadvantages. In these two joining methods, surface pre-treatment of the substrate is always necessary to ensure the strength and durability of the joint. Previous studies have shown that laser surface treatment improves the strength and durability of the joint. Yan et al. showed that laser surface treatment of aluminium alloys changes α-Al2O3 in the oxide layer to γ-Al2O3. As γ-Al2O3 has a large specific surface area, is very porous and chemically active, laser-treated aluminium surfaces are expected to undergo physico-chemical changes over time and adsorb moisture and organic substances from the air or storage atmosphere. The impurities accumulated on the laser-treated surface may be released at the adhesive and bonding interface by the heat input to the bonding system during the joining phase, affecting the strength and durability of the joint. However, only a few studies have discussed the effect of such storage periods on laser-treated surfaces. This paper, therefore, investigates the ageing of laser-treated aluminium alloy surfaces through thermal analysis, electrochemical analysis and microstructural observations.AlMg3 of 0.5 mm and 1.5 mm thickness was cut using a water-jet cutting machine, cleaned and degreased with isopropanol and surface pre-treated with a pulsed fibre laser at 1060 nm wavelength, 70 W maximum power and 55 kHz repetition frequency. The aluminium surface was then analysed using SEM, thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR) and cyclic voltammetry (CV) after storage in air for various periods ranging from one day to several months TGA and FTIR analysed impurities adsorbed on the aluminium surface, while CV revealed changes in the true electrochemically active surface area. SEM also revealed visual changes on the treated surface. In summary, the changes in the laser-treated aluminium surface with storage time were investigated, and the final results were used to determine the appropriate storage period.

Keywords: laser surface treatment, pre-treatment, adhesion, bonding, corrosion, durability, dissimilar material interface, automotive, aluminium alloys

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Authors: Edward W. Staley, Corban G. Rivera, Ashley J. Llorens

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Advances in reinforcement learning (RL) have resulted in recent breakthroughs in the application of artificial intelligence (AI) across many different domains. An emerging landscape of development environments is making powerful RL techniques more accessible for a growing community of researchers. However, most existing frameworks do not directly address the problem of learning in complex operating environments, such as dense urban settings or defense-related scenarios, that incorporate distributed, heterogeneous teams of agents. To help enable AI research for this important class of applications, we introduce the AI Arena: a scalable framework with flexible abstractions for distributed multi-agent reinforcement learning. The AI Arena extends the OpenAI Gym interface to allow greater flexibility in learning control policies across multiple agents with heterogeneous learning strategies and localized views of the environment. To illustrate the utility of our framework, we present experimental results that demonstrate performance gains due to a distributed multi-agent learning approach over commonly-used RL techniques in several different learning environments.

Keywords: reinforcement learning, multi-agent, deep learning, artificial intelligence

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Authors: Zubaidan Yushan, Hudayar Cıhan

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Turkiye and China are countries that have collective cultures, but they have different cultural backgrounds. They have different cultures, different religions, and different levels of economic development. The aim of this study is to test the moderation effect of caregiver bonding on the relationship between dating violence and coping strategies among unmarried emerging adults in China and Turkiye. Participants ages were 19 and 26 years (X=23.66, SD=3.66), unmarried emerging adults Turkish 171 participants (72.5% women, 24% men, 3.5% prefer not to say), Chinese 170 participants (71.8% women, 21.8% men, 6.5% prefer not to say). All participants had been in a relationship for more than six months. Participants completed The Conflict Tactics Scales—(CTS2), The Cope Inventory, and The Parental Bonding Instrument (PBI). Examining the dating violence and coping strategies of the participant's relationship through caregiver bonding moderation analysis was performed using the Jamovi. Significance was tested using the bootstrapping method with bias-corrected confidence estimates. The outcome variable for analysis was dating violence, and the predictor variable for the analysis was coping strategies. The moderator variable evaluated for the analysis was parent attachment. Before the analysis, the mean-centered scores of each variable and moderator were calculated. Furthermore, the moderation analysis was conducted separately for each outcome. The Moderation analysis results show that the sub-dimension of over-protection moderates psychological aggression perpetration and avoidance coping in China. The sub-dimension of care moderates injury victimization and avoidance management in Turkiye; also, over-protection moderates injury victimization and social support coping. Moreover, the sub-dimension of care moderates sexual coercion perpetration and avoidance coping. In the results, caregiver bonding moderates the relationship between coping strategies and dating violence, which may be explained by the fact that our ways of coping with problems are learned, and people are influenced by their parents when they face problems. Therefore, problem-solving is permanently fixed, and each person has his or her fixed solution, which leads to a habit of using solutions to problems. However, sometimes, these solutions become the justification for the injured or abusive person. The quality of the attachment between parents can regulate this state. The results are somewhat similar to and slightly different from those in the previous literature. These mixed results indicate the need for further exploration. Many other factors, such as alcohol, drug violence, and pathological problems, maybe the reasons for these differences. In addition, diverse factors such as the study environment and the applied measurement scales may also affect the results.

Keywords: caregiver bonding, coping strategies, dating violence, emerging adulthood, cross-cultural, comparison

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Authors: Jaleh Shoshtarian Malak, Niloofar Mohamadzadeh

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Managing pre-hospital emergency patients requires real-time practices and efficient resource utilization. Since we are facing a distributed Network of healthcare providers, services and applications choosing the right resources and treatment protocol considering patient situation is a critical task. Delivering care to emergency patients at right time and with the suitable treatment settings can save ones live and prevent further complication. In recent years Multi Agent Systems (MAS) introduced great solutions to deal with real-time, distributed and complicated problems. In this paper we propose a multi agent based pre-hospital emergency management architecture in order to manage coordination, collaboration, treatment protocol and healthcare provider selection between different parties in pre-hospital emergency in a self-organizing manner. We used AnyLogic Agent Based Modeling (ABM) tool in order to simulate our proposed architecture. We have analyzed and described the functionality of EMS center, Ambulance, Consultation Center, EHR Repository and Quality of Care Monitoring as main collaborating agents. Future work includes implementation of the proposed architecture and evaluation of its impact on patient quality of care improvement.

Keywords: multi agent systems, pre-hospital emergency, simulation, software architecture

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Authors: Ratchanon Boonachathong, Bordin Kaewnok, Suksun Amornraksa

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Rigid polyurethane foam (RPUF) used for imitation wood is typically prepared by using 1-Dichloro-1-fluoroethane (HCFC-141b) as a blowing agent. However, this chemical is a hydrofluorocarbon which severely causes ozone depletion to the atmosphere. In this work, a more environmental-friendly RPUF was prepared by using distilled water and cyclopentane (CP) as alternative blowing agent. Several properties of the prepared RPUF were investigated and measured such as density (kg/m³), surface hardness (shore D), and glass transition temperature (°C). It was found that when the amount of the blowing agents decreased, the foam density is increased as well as the surface hardness and glass transition temperature. The results showed that the proper amount of water and cylopentane blowing agent is around 0.3–1.2% and 0.5-1.3% respectively. And the new RPUF produced has a good potential to substitute for a conventional RPUF.

Keywords: blowing agent, cyclopentane co-blown, imitation wood, rigid polyurethane foam, surface hardness

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Authors: Francisco José Plácido da Cunha, Tassio Ferenzini Martins Sirqueira, Marx Leles Viana, Carlos José Pereira de Lucena

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Open Multiagent Systems (MASs) are societies in which heterogeneous and independently designed entities (agents) work towards similar, or different ends. Software agents are autonomous and the diversity of interests among different members living in the same society is a fact. In order to deal with this autonomy, these open systems use mechanisms of social control (norms) to ensure a desirable social order. This paper considers the following types of norms: (i) obligation — agents must accomplish a specific outcome; (ii) permission — agents may act in a particular way, and (iii) prohibition — agents must not act in a specific way. All of these characteristics mean to encourage the fulfillment of norms through rewards and to discourage norm violation by pointing out the punishments. Once the software agent decides that its priority is the satisfaction of its own desires and goals, each agent must evaluate the effects associated to the fulfillment of one or more norms before choosing which one should be fulfilled. The same applies when agents decide to violate a norm. This paper also introduces a framework for the development of MASs that provide support mechanisms to the agent’s decision-making, using norm-based reasoning. The applicability and validation of this approach is demonstrated applying a traffic intersection scenario.

Keywords: BDI agent, BDI4JADE framework, multiagent systems, normative agents

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Authors: Saadia Drissi

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The cloud computing is an innovative paradigm that introduces several changes in technology that have resulted a new ways for cloud providers to deliver their services to cloud consumers mainly in term of security risk assessment, thus, adapting a current risk assessment tools to cloud computing is a very difficult task due to its several characteristics that challenge the effectiveness of risk assessment approaches. As consequence, there is a need of risk assessment model adapted to cloud computing. This paper requires a new risk assessment model based on multi-agent system and AHP model as fundamental steps towards the development of flexible risk assessment approach regarding cloud consumers.

Keywords: cloud computing, risk assessment model, multi-agent system, AHP model, cloud consumer

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Authors: Mohamed Hassan, Rahul Gajbhiye

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The high mobility and gravity override of CO₂ gas can be minimized by generating the CO₂ foam with the aid of surfactant. However, CO₂ is unable to generate the foam/stable foam above its supercritical point (1100 psi, 31°C). These difficulties with CO₂ foam is overcome by adding N₂ in small fraction to enhance the foam generation of CO₂ at supercritical conditions. This study shows how the addition of small quantity of N₂ helps in generating the CO₂ foam and performance of the CO₂/N₂ mixture foam in enhanced oil recovery. To investigate the performance of CO₂/N₂ foam, core-flooding experiments were conducted at elevated pressure and temperature condition (higher than supercritical CO₂ - 50°C and 1500 psi) in sandstone cores. Fluorosurfactant (FS-51) was used as a foaming agent, and n-decane was used as model oil in all the experiments. The selection of foam quality and N₂ fraction was optimized based on foam generation and stability tests. Every gas or foam flooding was preceded by seawater injection to simulate the behavior in the reservoir. The results from the core-flood experiments showed that the CO₂ and CO₂/N₂ foam flooding recovered an additional 34-40% of Original Initial Oil in Place (OIIP) indicating that foam flooding succeeded in producing more oil than pure CO₂ gas injection processes. Additionally, the performance CO₂/N₂ foam injection was better than CO₂ foam injection.

Keywords: CO₂/N₂ foam, enhanced oil recovery (EOR), supercritical CO₂, sweep efficiency

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

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

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

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Authors: Vincent Murray

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The chromatin structure at the transcription start sites (TSSs) of genes is very important in the control of gene expression. In order for gene expression to occur, the chromatin structure at the TSS has to be altered so that the transcriptional machinery can be assembled and RNA transcripts can be produced. In particular, the nucleosome structure and positioning around the TSS has to be changed. Bleomycin is utilized as an anti-tumor agent to treat Hodgkin's lymphoma, squamous cell carcinoma, and testicular cancer. Bleomycin produces DNA damage in human cells and DNA strand breaks, especially double-strand breaks, are thought to be responsible for the cancer chemotherapeutic activity of bleomycin. Bleomycin is a large glycopeptide with molecular weight of approximately 1500 Daltons and hence its DNA strand cleavage activity can be utilized as a probe of chromatin structure. In this project, Illumina next-generation DNA sequencing technology was used to determine the position of DNA double-strand breaks at the TSSs of genes in intact cells. In this genome-wide study, it was found that bleomycin cleavage preferentially occurred at the TSSs of actively transcribed human genes in comparison with non-transcribed genes. There was a correlation between the level of enhanced bleomycin cleavage at TSSs and the degree of transcriptional activity. In addition, bleomycin was able to determine the position of nucleosomes at the TSSs of human genes. Bleomycin analogues were also utilized as probes of chromatin structure at the TSSs of human genes. In a similar manner to bleomycin, the bleomycin analogues 6′-deoxy-BLM Z and zorbamycin preferentially cleaved at the TSSs of human genes. Interestingly this degree of enhanced TSS cleavage inversely correlated with the cytotoxicity (IC50 values) of BLM analogues. This indicated that the degree of cleavage by bleomycin analogues at the TSSs of human genes was very important in the cytotoxicity of bleomycin and analogues. It also provided a deeper insight into the mechanism of action of this cancer chemotherapeutic agent since actively transcribed genes were preferentially targeted.

Keywords: anti-cancer activity, chromatin structure, cytotoxicity, gene expression, next-generation DNA sequencing

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Authors: Hyeongbok Kim, Lingling Zhao, Xiaohong Su

Abstract:

Deep reinforcement learning has been applied to address various problems in robotics, such as autonomous driving and unmanned aerial vehicle. However, because of the sparse reward penalty for a collision with obstacles during the navigation mission, the agent fails to learn the optimal policy or requires a long time for convergence. Therefore, using obstacles and enemy agents, in this paper, we present a curriculum-based boost learning method to effectively train compound skills during multi-agent reinforcement learning. First, to enable the agents to solve challenging tasks, we gradually increased learning difficulties by adjusting reward shaping instead of constructing different learning environments. Then, in a benchmark environment with static obstacles and moving enemy agents, the experimental results showed that the proposed curriculum learning strategy enhanced cooperative navigation and compound collision avoidance skills in uncertain environments while improving learning efficiency.

Keywords: curriculum learning, hard exploration, multi-agent reinforcement learning, robotic navigation, sparse reward

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Authors: Yeraldin Galindo, Soraida Mora

Abstract:

Solid urban waste represents one of the largest sources of global environmental pollution due to the large quantities of these that are produced every day; thus, the elimination of such waste is a major problem for the environmental authorities who must look for alternatives to reduce the volume of waste with the possibility of obtaining an energy recovery. At the Autónoma de Colombia University, approximately 423.27 kg/d of solid waste are generated mainly paper, cardboard, and plastic. A large amount of these solid wastes has as final disposition the sanitary landfill of the city, wasting the energy potential that these could have, this, added to the emissions generated by the collection and transport of the same, has as consequence the increase of atmospheric pollutants. One of the alternative process used in the last years to generate electrical energy from solid waste such as paper, cardboard, plastic and, mainly, organic waste or biomass to replace the use of fossil fuels is the gasification. This is a thermal conversion process of biomass. The objective of it is to generate a combustible gas as the result of a series of chemical reactions propitiated by the addition of heat and the reaction agents. This project was developed with the intention of giving an energetic use to the waste (paper, cardboard, and plastic) produced inside the university, using them to generate a synthesis gas with a gasifier prototype. The gas produced was evaluated to determine their benefits in terms of electricity generation or raw material for the chemical industry. In this process, air was used as gasifying agent. The characterization of the synthesis gas was carried out by a gas chromatography carried out by the Chemical Engineering Laboratory of the National University of Colombia. Taking into account the results obtained, it was concluded that the gas generated is of acceptable quality in terms of the concentration of its components, but it is a gas of low calorific value. For this reason, the syngas generated in this project is not viable for the production of electrical energy but for the production of methanol transformed by the Fischer-Tropsch cycle.

Keywords: alternative energies, gasification, gasifying agent, solid urban waste, syngas

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Authors: Filip Stojcevski, Tim Hilditch, Luke Henderson

Abstract:

Although carbon fibre composites are becoming ever more prominent in the engineering industry, interfacial failure still remains one of the most common limitations to material performance. Carbon fiber surface treatments have played a major role in advancing composite properties however research into the influence of manufacturing variables on a fiber manufacturing line is lacking. This project investigates the impact of altering carbon fiber manufacturing conditions on a production line (specifically electrochemical oxidization and sizing variables) to assess fiber-matrix adhesion. Pristine virgin fibers were manufactured and interfacial adhesion systematically assessed from a microscale (single fiber) to a mesoscale (12k tow), and ultimately a macroscale (laminate). Correlations between interfacial shear strength (IFSS) at each level is explored as a function of known interfacial bonding mechanisms; namely mechanical interlocking, chemical adhesion and fiber wetting. Impact of these bonding mechanisms is assessed through extensive mechanical, topological and chemical characterisation. They are correlated to performance as a function of IFSS. Ultimately this study provides a bottoms up approach to improving composite laminates. By understanding the scaling effects from a singular fiber to a composite laminate and linking this knowledge to specific bonding mechanisms, material scientists can make an informed decision on the manufacturing conditions most beneficial for interfacial adhesion.

Keywords: carbon fibers, interfacial adhesion, surface treatment, sizing

Procedia PDF Downloads 237