Search results for: dynamic Bayesian networks

Authors: M. Dehghan, R. Al-Mahaidi, I. Sbarski

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An industrial epoxy adhesive used in Carbon Fiber Reinforced Polymer (CFRP)-strengthening systems was modified by dispersing multi-walled carbon nanotubes (MWCNTs). Nanocomposites were fabricated using solvent-assisted dispersion method and ultrasonic mixing. Thermogravimetric analysis (TGA), dynamic mechanical analysis (DMA) and tensile tests were conducted to study the effect of nanotubes dispersion on the thermal and mechanical properties of the epoxy composite. Experimental results showed a substantial enhancement in the decomposition temperature and tensile properties of epoxy composite, while, the glass transition temperature (Tg) was slightly reduced due to the solvent effect. The morphology of the epoxy nanocomposites was investigated by SEM. It was proved that using solvent improves the nanotubes dispersion. However, at contents higher than 2 wt. %, nanotubes started to re-bundle in the epoxy matrix which negatively affected the final properties of epoxy composite.

Keywords: carbon fiber reinforced polymer, epoxy, multi-walled carbon nanotube, DMA, glass transition temperature

Procedia PDF Downloads 322

Authors: Tao Feng, Xiaomei Ma, Xian Guo, Jing Wang

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Named Data Network (NDN) is one of the future Internet architecture, all nodes (i.e., hosts, routers) are allowed to have a local cache, used to satisfy incoming requests for content. However, depending on caching allows an adversary to perform attacks that are very effective and relatively easy to implement, such as content pollution attack. In this paper, we use a method of secure network coding based on homomorphic signature system to solve this problem. Firstly ,we use a dynamic public key technique, our scheme for each generation authentication without updating the initial secret key used. Secondly, employing the homomorphism of hash function, intermediate node and destination node verify the signature of the received message. In addition, when the network topology of NDN is simple and fixed, the code coefficients in our scheme are generated in a pseudorandom number generator in each node, so the distribution of the coefficients is also avoided. In short, our scheme not only can efficiently prevent against Intra/Inter-GPAs, but also can against the content poisoning attack in NDN.

Keywords: named data networking, content polloution attack, network coding signature, internet architecture

Procedia PDF Downloads 319

Authors: Chia-Hao Chang, Geng-Gui Wang, Jee-Cheng Wu

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The prediction of a landslide is a difficult task because it requires a detailed study of past activities using a complete range of investigative methods to determine the changing condition. In this research, first step, LiDAR 1-meter by 1-meter resolution of digital elevation model (DEM) was used to generate six environmental factors of landslide. Then, back-propagation neural networks (BPNN) was adopted to identify scarp, landslide areas and non-landslide areas. The BPNN uses 6 environmental factors in input layer and 1 output layer. Moreover, 6 landslide areas are used as training areas and 4 landslide areas as test areas in the BPNN. The hidden layer is set to be 1 and 2; the hidden layer neurons are set to be 4, 5, 6, 7 and 8; the learning rates are set to be 0.01, 0.1 and 0.5. When using 1 hidden layer with 7 neurons and the learning rate sets to be 0.5, the result of Network training root mean square error is 0.001388. Finally, evaluation of BPNN classification accuracy by the confusion matrix shows that the overall accuracy can reach 94.4%, and the Kappa value is 0.7464.

Keywords: digital elevation model, DEM, environmental factors, back-propagation neural network, BPNN, LiDAR

Procedia PDF Downloads 121

Authors: Ali Raheli, Rahim Habibifar, Behzad Mohammadi-Alasti, Mahdi Abbasgholipour

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This paper presents vibration behavior of a FGM micro-beam and its pull-in instability under a nonlinear electrostatic pressure. An exponential function has been applied to show the continuous gradation of the properties along thickness. Nonlinear integro-differential-electro-mechanical equation based on Euler–Bernoulli beam theory has been derived. The governing equation in the static analysis has been solved using Step-by-Step Linearization Method and Finite Difference Method. Fixed points or equilibrium positions and singular points have been shown in the state control space. In order to find the response to a step DC voltage, the nonlinear equation of motion has been solved using Galerkin-based reduced-order model and time histories and phase portrait for different applied voltages have been shown. The effects of electrostatic pressure on stability of FGM micro-beams having various amounts of the ceramic constituent have been investigated.

Keywords: FGM, MEMS, nonlinear vibration, electrical, dynamic pull-in voltage

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Authors: Saurabh Chanana, Monika Arora

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Demand response is getting increased attention these days due to the increase in electricity demand and introduction of renewable resources in the existing power grid. Traditionally demand response programs involve large industrial consumers but with technological advancement, demand response is being implemented for small residential and commercial consumers also. In this paper, demand response program aims to reduce the peak demand as well as overall energy consumption of the residential customers. Air conditioners are the major reason of peak load in residential sector in summer, so a dynamic model of air conditioning load with thermostat action has been considered for applying demand response programs. A programmable communicating thermostat (PCT) is a device that uses real time pricing (RTP) signals to control the thermostat setting. A new model incorporating PCT in air conditioning load has been proposed in this paper. Results show that introduction of PCT in air conditioner is useful in reducing the electricity payments of customers as well as reducing the peak demand.

Keywords: demand response, home energy management, programmable communicating thermostat, thermostatically controlled appliances

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Authors: Rupu Yang, Cong Toan Tran, Assaad Zoughaib

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The work provides an iterative nonlinear programming method to synthesize a heat exchanger network by manipulating the trade-offs between the heat load of process heat exchangers (HEs) and utilities. We consider for the synthesis problem two cases, the first one without fixed cost for HEs, and the second one with fixed cost. For the no fixed cost problem, the nonlinear programming (NLP) model with all the potential HEs is optimized to obtain the global optimum. For the case with fixed cost, the NLP model is iterated through adding/removing HEs. The method was applied in five case studies and illustrated quite well effectiveness. Among which, the approach reaches the lowest TAC (2,904,026$/year) compared with the best record for the famous Aromatic plants problem. It also locates a slightly better design than records in literature for a 10 streams case without fixed cost with only 1/9 computational time. Moreover, compared to the traditional mixed-integer nonlinear programming approach, the iterative NLP method opens a possibility to consider constraints (such as controllability or dynamic performances) that require knowing the structure of the network to be calculated.

Keywords: heat exchanger network, synthesis, NLP, optimization

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Authors: Ali Borhani Manesh, Sirus Mohammadi

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Harmonic distortion is caused by nonlinear devices in the power system. A nonlinear device is one in which the current is not proportional to the applied voltage. Harmonic distortion is present to some degree on all power systems. Proactive monitoring of power quality disturbance levels by electricity utilities is vital to allow cost-effective mitigation when disturbances are perceived to be approaching planning levels and also to protect the security of customer installations. Ensuring that disturbance levels are within limits at the HV and EHV points of supply of the network is essential if satisfactory levels downstream are to be maintained. This paper presents discussion on a power quality monitoring campaign performed at the sub-transmission point of supply of a distribution network with the objective of benchmarking background disturbance levels prior to modifications to the substation and to ensure emissions from HV customers and the downstream MV networks are within acceptable levels. Some discussion on the difficulties involved in such a study is presented. This paper presents a survey of voltage and current harmonic distortion levels at transmission system in Kohgiloye and Boyrahmad. The effects of harmonics on capacitors and power transformers are discussed.

Keywords: power quality, harmonics, flicker, measurement, substation

Procedia PDF Downloads 681

Authors: Chechen Liao, Sheng Yi Lin

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With the popularity of smartphone usage and the flourish of social networks, many people began to use the 'check-in' functions to share their location information and days of live and self-disclosure. In order to increase exposure and awareness, some stores provide discounts and other benefits to attract consumers to 'check-in' in their stores. The purpose of this study was to investigate whether personality traits, intrinsic motivations, extrinsic motivations, and privacy concerns would affect self-disclosure of location for consumers. Research data were collected from 407 individuals that have used Facebook check-in in Taiwan. This study used SmartPLS 2.0 structural equation modeling to validate the model. The results show that information sharing, information storage, enjoyment, self-presentation, get a feedback, economic reward, and keep up with trends had significant positive effects on self-disclosure. While extroversion and openness to use have significant positive effects on self-disclosure, conscientiousness and privacy concerns have significant negative effects on self-disclosure. The results of the study provide academic and practical implications for the future growth of location-based self-disclosure.

Keywords: check-in, extrinsic motivation, intrinsic motivation, personality trait, self-disclosure

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Authors: Heba M. Wagih, Hoda M. O. Mokhtar

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Social Network has recently played a significant role in both scientific and social communities. The growing adoption of social network applications has been a relevant source of information nowadays. Due to its popularity, several research trends are emerged to service the huge volume of users including, Location-Based Social Networks (LBSN), Recommendation Systems, Sentiment Analysis Applications, and many others. LBSNs applications are among the highly demanded applications that do not focus only on analyzing the spatiotemporal positions in a given raw trajectory but also on understanding the semantics behind the dynamics of the moving object. LBSNs are possible means of predicting human mobility based on users social ties as well as their spatial preferences. LBSNs rely on the efficient representation of users’ trajectories. Hence, traditional raw trajectory information is no longer convenient. In our research, we focus on studying human behavior trajectory which is the major pillar in location recommendation systems. In this paper, we propose an ontology design patterns with their underlying description logics to efficiently annotate human behavior trajectories.

Keywords: human behavior trajectory, location-based social network, ontology, social network

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Authors: Dzmitry Misiulia, Sergiy Antonyuk

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Small-scale cyclone separators are widely used in aerosol sampling. The flow field in a cyclone sampler is very complex, especially the vortex behavior. Most of the existing models for calculating cyclone efficiency use the same stable vortex structure while the vortex demonstrates dynamic variations rather than the steady-state picture. It can spontaneously ‘end’ at some point within the body of the separator. Natural vortex length is one of the most critical issues when designing and operating gas cyclones and is crucial to proper cyclone performance. The particle transport along the wall to the grid pot is not effective beyond this point. The flow field and vortex behavior inside the aerosol sampler have been investigated for a wide range of Reynolds numbers using Large Eddy Simulations. Two characteristics types of vortex behavior have been found with simulations. At low flow rates the vortex created in the cyclone dissipates in free space (without attaching to a surface) while at higher flow rates it attaches to the cyclone wall. The effects of the Reynolds number on the natural vortex length and the rotation frequency of the end of the vortex have been revealed.

Keywords: cyclone, flow field, natural vortex length, pressure drop

Procedia PDF Downloads 143

Authors: Nguyen J. M., Lucas G., Brunner M., Ruan S., Antonioli D.

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Deep learning based on convolutional neural networks (CNN) is a very powerful technique for classifying information from an image. We propose a new method, DeepNic, to transform each variable of a tabular dataset into an image where each pixel represents a set of conditions that allow the variable to make an error-free prediction. The contrast of each pixel is proportional to its prediction performance and the color of each pixel corresponds to a sub-family of NICs. NICs are probabilities that depend on the number of inputs to each neuron and the range of coefficients of the inputs. Each variable can therefore be expressed as a function of a matrix of 2 vectors corresponding to an image whose pixels express predictive capabilities. Our objective is to transform each variable of tabular data into images into an image that can be analysed by CNNs, unlike other methods which use all the variables to construct an image. We analyse the NIC information of each variable and express it as a function of the number of neurons and the range of coefficients used. The predictive value and the category of the NIC are expressed by the contrast and the color of the pixel. We have developed a pipeline to implement this technology and have successfully applied it to genomic expressions on an Affymetrix chip.

Keywords: tabular data, deep learning, perfect trees, NICS

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Authors: Sancho-Esper Franco, Rodríguez Sánchez Carla, Sánchez Carolina, Orús-Sanclemente Carlos

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Water scarcity is a reality that affects many regions of the world and is aggravated by climate change and population growth. Saving water has become an urgent need to ensure the sustainability of the planet and the survival of many communities, where youth and social networks play a key role in promoting responsible practices and adopting habits that contribute to environmental preservation. This study analyzes the persuasion capacity of messages designed to promote pro-environmental behaviors among youth. Specifically, it studies how the efficacy (effectiveness) of the response (personal response efficacy/effectiveness) and the perception of distance from the source of the message influence the water-saving behavior of the audience. To do so, two communication frameworks are combined. First, the Construal Level Theory, which is based on the concept of "psychological distance", that is, people, objects or events can be perceived as psychologically near or far, and this subjective distance (i.e., social, temporal, or spatial) determines their attitudes, emotions, and actions. This perceived distance can be social, temporal, or spatial. This research focuses on studying the spatial distance and social distance generated by cultural differences between influencers and their audience to understand how cultural distance can influence the persuasiveness of a message. Research on the effects of psychological distance between influencers-followers in the pro-environmental field is very limited, being relevant because people could learn specific behaviors suggested by opinion leaders such as influencers in social networks. Second, different approaches to behavioral change suggest that the perceived efficacy of a behavior can explain individual pro-environmental actions. People will be more likely to adopt a new behavior if they perceive that they are capable of performing it (efficacy belief) and that their behavior will effectively contribute to solving that problem (personal response efficacy). It is also important to study the different actors (social and individual) that are perceived as responsible for addressing environmental problems. Specifically, we analyze to what extent the belief individual’s water-saving actions are effective in solving the problem can influence water-saving behavior since this individual effectiveness increases people's sense of obligation and responsibility with the problem. However, in this regard, empirical evidence presents mixed results. Our study addresses the call for experimental studies manipulating different subtypes of response effectiveness to generate robust causal evidence. Based on all the above, this research analyzes whether cultural distance (local vs. international influencer) and the perception of effectiveness of behavior (personal response efficacy) (personal/individual vs. collective) affect the actual behavior and the intention to conserve water of social network users. An experiment of 2 (local influencer vs. international influencer) x 2 (effectiveness of individual vs. collective response) is designed and estimated. The results show that a message from a local influencer appealing to individual responsibility exerts greater influence on intention and actual water-saving behavior, given the cultural closeness between influencer-follower, and the appeal to individual responsibility increases the feeling of obligation to participate in pro-environmental actions. These results offer important implications for social marketing campaigns that seek to promote water conservation.

Keywords: social marketing, influencer, message framing, experiment, personal response efficacy, water saving

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Authors: Dana Madalina Pohrib, Elena Irina Ciobanu

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In compaction works, the most often used codes and standards are those for road embankments and refer to a maximum filling height of 3.00m. When filling a height greater than 3.00m, such codes are no longer valid and thus their application may lead to technical difficulties in the process of compaction and to the achievement of a sufficient degree of compaction. For this reason, in the case of controlled fillings with heights greater than 3.00m it is necessary to formulate and apply a number of special techniques, which can be determined by performing a full scale test. This paper presents the results of the studies and full scale tests conducted for the stabilization of a ravine with vertical banks and a depth of about 12.00m. The fillings will support a heavy traffic road connecting the two parts of a village in Vaslui County, Romania. After analyzing two comparative intervention solutions, the variant of a controlled filling bordered by a monolith concrete retaining wall was chosen. The results obtained by the authors highlighted the need to insert a geogrid reinforcement at every 2.00m for creating a 12.00m thick compacted fill.

Keywords: compaction, dynamic probing, stability, soil stratification

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Authors: Venkata Narayana Chejarla, Nafisa Parvez Shaik, Gopi Vara Prasad Marabathula, Deva Kumar Bejjam

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Yoga is an advanced, well-recognized method with roots in Indian philosophy. Yoga benefits both the body and the psyche. Yoga is a regular exercise that helps people relax and sleep better while also enhancing their balance, endurance, and concentration. Yoga can be learned in a variety of settings, including at home with the aid of books and the internet as well as in yoga studios with the guidance of an instructor. Self-learning does not teach the proper yoga poses, and doing them without the right instruction could result in significant injuries. We developed "Online Yoga Asana Trainer using Deep Learning" so that people could practice yoga without a teacher. Our project is developed using Tensorflow, Movenet, and Keras models. The system makes use of data from Kaggle that includes 25 different yoga poses. The first part of the process involves applying the movement model for extracting the 17 key points of the body from the dataset, and the next part involves preprocessing, which includes building a pose classification model using neural networks. The system scores a 98.3% accuracy rate. The system is developed to work with live videos.

Keywords: yoga, deep learning, movenet, tensorflow, keras, CNN

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Authors: Saul Ngarava, Leocadia Zhou, Nomakhaya Monde

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Water crises have the fourth most significant societal impact after weapons of mass destruction, climate change, and extreme weather conditions, ahead of natural disasters. Intricacies between women and water are central to achieving the 2030 Sustainable Development Goals (SDGs). The majority of the 1.2 billion poor people worldwide, with two-thirds being women, and mostly located in Sub Sahara Africa (SSA) and South Asia, do not have access to safe and reliable sources of water. There exist gendered differences in water security based on the division of labour associating women with water. Globally, women and girls are responsible for water collection in 80% of the households which have no water on their premises. Women spend 16 million hours a day collecting water, while men and children spend 6 million and 4 million per day, respectively, which is time foregone in the pursuit of other livelihood activities. Due to their proximity and activities concerning water, women are vulnerable to water insecurity through exposures to water-borne diseases, fatigue from physically carrying water, and exposure to sexual and physical harassment, amongst others. Proximity to treated water and their wellbeing also has an effect on their sensitivity and adaptive capacity to water insecurity. The great distances, difficult terrain and heavy lifting expose women to vulnerabilities of water insecurity. However, few studies have quantified the vulnerabilities and burdens on women, with a few taking a phenomenological qualitative approach. Vulnerability studies have also been scanty in the water security realm, with most studies taking linear forms of either quantifying exposures, sensitivities or adaptive capacities in climate change studies. The current study argues for the need for a water insecurity vulnerability assessment, especially for women into research agendas as well as policy interventions, monitoring, and evaluation. The study sought to identify and provide pathways through which female-headed households were water insecure in South Africa, the 30th driest country in the world. This was through linking the drinking water decision as well as the vulnerability frameworks. Secondary data collected during the 2016 General Household Survey (GHS) was utilised, with a sample of 5928 female-headed households. Principal Component Analysis and Structural Equation Modelling were used to analyse the data. The results show dynamic relationships between water characteristics and water treatment. There were also associations between water access and wealth status of the female-headed households. Association was also found between water access and water treatment as well as between wealth status and water treatment. The study concludes that there are dynamic relationships in water insecurity (exposure, sensitivity, and adaptive capacity) for female-headed households in South Africa. The study recommends that a multi-prong approach is required in tackling exposures, sensitivities, and adaptive capacities to water insecurity. This should include capacitating and empowering women for wealth generation, improve access to water treatment equipment as well as prioritising the improvement of infrastructure that brings piped and safe water to female-headed households.

Keywords: gender, principal component analysis, structural equation modelling, vulnerability, water insecurity

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Authors: Sharifa Alshahrani

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Comics is a multimodal text wherein meaning is created by taking in all modes of expression at once. It uses two different semiotic modes, the verbal and the visual modes, together to make meaning and these different semiotic modes can be socially and culturally shaped to give meaning. Therefore, comics translation cannot treat comics as a monomodal text by translating only the verbal mode inside or outside the speech balloons as the cultural differences are encoded in the visual mode as well. Due to the development of the internet and editing software, comics translation is not anymore confined to the publishing houses and official translation as scanlation, or the fan translation took the initiative in translating comics for being emotionally attracted to the culture and genre. Scanlation is carried out by volunteering fans who translate out of passion. However, quality is one of the debatable issues relating to scanlation and fan translation. This study will investigate how the dynamic multimodal relationship in comics is exploited and interpreted in the translation by exploring the translation strategies and procedures adopted by the publishing houses and scanlation in interpreting comics into Arabic using three analytical frameworks; cultural references model, multimodal relation model and translation strategies and procedures models.

Keywords: comics, multimodality, translation, scanlation

Procedia PDF Downloads 196

Authors: Amir Reza Radmanesh, Sina Farajzadeh Khosroshahi, Hani Sadr

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The transient catalytic converter performance is governed by complex interactions between exhaust gas flow and the monolithic structure of the catalytic converter. Stringent emission regulations around the world necessitate the use of highly-efficient catalytic converters in vehicle exhaust systems. Computational fluid dynamics (CFD) is a powerful tool for calculating the flow field inside the catalytic converter. Radial velocity profiles, obtained by a commercial CFD code, present very good agreement with respective experimental results published in the literature. However the applicability of CFD for transient simulations is limited by the high CPU demands. In the present work, Geometric modeling ceramic monolith substrate is done with square shaped channel type of Catalytic converter and it is coated platinum and palladium. This example illustrates the effect of flow distribution on thermal response of a catalytic converter and different gas flow velocities, during the critical phase of catalytic converter warm up.

Keywords: catalytic converter, computational fluid dynamic, porous media, velocity distribution

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Authors: Arafat A. A. Shabaneh

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Harsh environments demand a developed detection of an optical communication system to ensure a high level of security and safety. Fiber Bragg gratings (FBG) are emerging sensing instruments that respond to variations in strain and temperature via varying wavelengths. In this paper, cascaded uniform FBG as a strain sensor for 6 km length at 1550 nm wavelength with 30 oC is designed with analyzing of dynamic strain and wavelength shifts. FBG is placed in a small segment of optical fiber, which reflects light of a specific wavelength and passes the remaining wavelengths. This makes a periodic alteration in the refractive index within the fiber core. The alteration in the modal index of fiber produced due to strain consequences in a Bragg wavelength. When the developed sensor exposure to a strain of cascaded uniform FBG by 0.01, the wavelength is shifted to 0.0000144383 μm. The sensing accuracy of the developed sensor is 0.0012. Simulation results show reliable and effective strain monitoring sensors for remote sensing applications.

Keywords: Cascaded fiber Bragg gratings, Strain sensor, Remote sensing, Wavelength shift

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Authors: Benoit Rougier, Alexandre Lefrancois, Herve Aubert

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Microwave interrogation in the range 10-100 GHz is identified as an advanced technique to investigate simultaneously shock and particle velocity measurements. However, it requires the understanding of electromagnetic wave propagation in a multi-layered moving media. The existing models limit their approach to wave guides or evaluate the velocities with a fitting method, restricting therefore the domain of validity and the precision of the results. Moreover, few data of permittivity on high explosives at these frequencies under dynamic compression have been reported. In this paper, shock and particle velocities are computed concurrently for steady and unsteady shocks for various inert and reactive materials, via a propagation model based on Doppler shifts and signal amplitude. Refractive index of the material under compression is also calculated. From experimental data processing, it is demonstrated that Hugoniot curve can be evaluated. The comparison with published results proves the accuracy of the proposed method. This microwave interrogation technique seems promising for shock and detonation waves studies.

Keywords: electromagnetic propagation, experimental setup, Hugoniot measurement, shock propagation

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Authors: Madhan Vinu, Yue-Chun Jiang, Yi-Feng Lin, Chia-Her Lin

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An effective approach to enhance the ethanol/water pervaporation of mixed matrix membranes prepared from three microporous aluminium based metal-organic frameworks (MOFs), [Al(OH)(BPDC)] (DUT-5), [Al(OH)(NDC)] (DUT-4) and [Al(OH)(BzPDC)] (CAU-8) have been synthesized by employing solvothermal reactions. Interestingly, all Al-MOFs showed attractive surface area with microporous 12.3, 10.2 and 8.0 Å for DUT-5, DUT-4 and CAU-8 MOFs which are confirmed through N₂ gas sorption measurements. All the microporous compounds are highly stable as confirmed by thermogravimetric analysis and temperature-dependent powder X-ray diffraction measurements. Furthermore, the synthesized microporous MOF particles of DUT-5, DUT-4, and CAU-8 were successfully incorporated into biological chitosan (CS) membranes to form DUT-5@CS, DUT-4@CS, and CAU-8@CS membranes. The different MOF loadings such as 0.1, 0.15, and 0.2 wt% in CS networks have been prepared, and the same were used to separate mixtures of water and ethanol at 25ºC in the pervaporation process. In particular, when 0.15 wt% of DUT-5 was loaded, MOF@CS membrane displayed excellent permeability and selectivity in ethanol/water separation than that of the previous literature. These CS based membranes separation through functionalized microporous MOFs reveals the key governing factors that are essential for designing novel MOF membranes for bioethanol purification.

Keywords: metal-organic framework, microporous materials, separation, chitosan membranes

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Authors: M. Saadi, S. E. H. Abaidia, M. Y. Mokeddem.

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We present the results of a systematic and comparative study of the bulk, the structural properties, and phonon calculations of aluminum alloys using several exchange–correlations functional theory (DFT) with different plane-wave basis pseudo potential techniques. Density functional theory implemented by the Vienna Ab Initio Simulation Package (VASP) technique is applied to calculate the bulk and the structural properties of several structures. The calculations were performed for within several exchange–correlation functional and pseudo pententials available in this code (local density approximation (LDA), generalized gradient approximation (GGA), projector augmented wave (PAW)). The lattice dynamic code “PHON” developed by Dario Alfè was used to calculate some thermodynamics properties and phonon dispersion relation frequency distribution of Aluminium alloys using the VASP LDA PAW and GGA PAW results. The bulk and structural properties of the calculated structures were compared to different experimental and calculated works.

Keywords: DFT, exchange-correlation functional, LDA, GGA, pseudopotential, PAW, VASP, PHON, phonon dispersion

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Authors: Shiksha Jain, Ramesh Mishra

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One of the most widely used complex signals processing operation is filtering. The most important FIR digital filter are widely used in DSP for filtering to alter the spectrum according to some given specifications. Power consumption and Area complexity in the algorithm of Finite Impulse Response (FIR) filter is mainly caused by multipliers. So we present a multiplier less technique (DA technique). In this technique, precomputed value of inner product is stored in LUT. Which are further added and shifted with number of iterations equal to the precision of input sample. But the exponential growth of LUT with the order of FIR filter, in this basic structure, makes it prohibitive for many applications. The significant area and power reduction over traditional Distributed Arithmetic (DA) structure is presented in this paper, by the use of slicing of LUT to the desired length. An architecture of 16 tap FIR filter is presented, with different length of slice of LUT. The result of FIR Filter implementation on Xilinx ISE synthesis tool (XST) vertex-4 FPGA Tool by using proposed method shows the increase of the maximum frequency, the decrease of the resources as usage saving in area with more number of slices and the reduction dynamic power.

Keywords: multiplier less technique, linear phase symmetric FIR filter, FPGA tool, look up table

Procedia PDF Downloads 377

Authors: Getaneh Berie Tarekegn

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Wireless communication via unmanned aerial vehicles (UAVs) has drawn a great deal of attention due to its flexibility in establishing line-of-sight (LoS) communications. However, in complex urban and dynamic environments, the movement of UAVs can be blocked by trees and high-rise buildings that obstruct directional paths. With reconfigurable intelligent surfaces (RIS), this problem can be effectively addressed. To achieve this goal, accurate channel estimation in RIS-assisted UAV-enabled wireless communications is crucial. This paper proposes an accurate channel estimation model using long short-term memory (LSTM) for a multi-user RIS-assisted UAV-enabled wireless communication system. According to simulation results, LSTM can improve the channel estimation performance of RIS-assisted UAV-enabled wireless communication.

Keywords: channel estimation, reconfigurable intelligent surfaces, long short-term memory, unmanned aerial vehicles

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Authors: Neşe Taşci, Soner Çubuk, Ece Kök Yetimoğlu, M. Vezir Kahraman

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Bisphenol-A (BPA), 2,2-bis(4-hydroxyphenly)propane, is one of the highest usage volume chemicals in the world. Studies showed that BPA maybe has negative effects on the central nervous system, immune and endocrine systems. Several of analytical methods for the analysis of BPA have been reported including electrochemical processes, chemical oxidation, ozonization, spectrophotometric, chromatographic techniques. Compared with other conventional analytical techniques, optic sensors are reliable, providing quick results, low cost, easy to use, stands out as a much more advantageous method because of the high precision and sensitivity. In this work, a new photocured polymeric fluorescence sensor was prepared and characterized for Bisphenol-A (BPA) analysis. Characterization of the membrane was carried out by Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy (ATR-FTIR) and Scanning Electron Microscope (SEM) techniques. The response characteristics of the sensor including dynamic range, pH effect and response time were systematically investigated. Acknowledgment: This work was supported by the Scientific and Technological Research Council of Turkey (TUBITAK) under Grant 115Y469.

Keywords: bisphenol-a, fluorescence, photopolymerization, polymeric sensor

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Authors: Ater Amogpai

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Hydropower and solar photovoltaic (PV) generation are crucial in sustainability and transitioning from fossil fuel to clean energy. Integrating renewable energy sources such as hydropower and solar photovoltaic (PV) into the distributed networks contributes to achieving energy balance, pollution mitigation, and cost reduction. Frequent power outages and a lack of load reliability characterize the current South Sudan electricity distribution system. The country’s electricity demand is 300MW; however, the installed capacity is around 212.4M. Insufficient funds to build new electricity facilities and expand generation are the reasons for the gap in installed capacity. The South Sudan Ministry of Energy and Dams gave a contract to an Egyptian Elsewedy Electric Company that completed the construction of a solar PV plant in 2023. The plant has a 35 MWh battery storage and 20 MW solar PV system capacity. The construction of Juba Solar PV Park started in 2022 to increase the current installed capacity in Juba City to 53 MW. The plant will begin serving 59000 residents in Juba and save 10,886.2t of carbon dioxide (CO2) annually.

Keywords: renewable energy, hydropower, solar energy, photovoltaic, South Sudan

Procedia PDF Downloads 87

Authors: Seul-Ki Park, Jong-Chun Park, Gyu-Mok Jeon, Dae-Kyung Ock, Seung-Gyu Jeong

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Rogue waves cause frequent accidents of ships and offshore structures, which can result in severe damage to the structures. The Rogue waves, which are also known as big waves, freak waves, extreme waves, monster waves, focused waves, giant waves and abnormal waves, are unexpected and suddenly appearing, and can have a breaking force to destroy the structure even though modern structures are designed to tolerate a breaking wave. In the present study, a series of focused waves are numerically reproduced by concentrating nonlinear multi-directional waves into a target point using a commercial CFD software, Star-CCM+. A flow analysis for investigating the physical characteristics of the focused waves is performed using the Star-CCM+, while it has several difficulties to examine the inner properties of the waves in existing potential theory and experiments. Additionally, the 6-DOF (Degree of Freedom) motion of a floating body interacting with the focused waves are simulated, and the dynamic response of the body are discussed.

Keywords: multidirectional waves, focused waves, rogue waves, wave-structure interaction, numerical wave tank, computational fluid dynamics

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Authors: Saba Ebrahimi, Saeed Ahmadian, Hedie Ashrafi

Abstract:

Selecting appropriate patients for surgery is one of the main issues in thoracic surgery (TS). Both short-term and long-term risks and benefits of surgery must be considered in the patient selection criteria. There are some limitations in the existing datasets of TS patients because of missing values of attributes and imbalanced distribution of survival classes. In this study, a novel ensemble architecture of deep learning networks is proposed based on stacking different linear and non-linear layers to deal with imbalance datasets. The categorical and numerical features are split using different layers with ability to shrink the unnecessary features. Then, after extracting the insight from the raw features, a novel biased-kernel layer is applied to reinforce the gradient of the minority class and cause the network to be trained better comparing the current methods. Finally, the performance and advantages of our proposed model over the existing models are examined for predicting patient survival after thoracic surgery using a real-life clinical data for lung cancer patients.

Keywords: deep learning, ensemble models, imbalanced classification, lung cancer, TS patient selection

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Authors: Sarah Mueller-Saegebrecht, André Brendler

Abstract:

Business model innovation (BMI) as an intentional change of an existing business model (BM) or the design of a new BM is essential to a firm's development in dynamic markets. The relevance of BMI is also evident in the ongoing COVID-19 pandemic, in which start-ups, in particular, are affected by limited access to resources. However, first studies also show that they react faster to the pandemic than established firms. A strategy to successfully handle such threatening dynamic changes represents BMI. Entrepreneurship literature shows how and when firms should utilize BMI in times of crisis and which barriers one can expect during the BMI process. Nevertheless, research merging BMI barriers and crises is still underexplored. Specifically, further knowledge about antecedents and the effect of moderators on the BMI process is necessary for advancing BMI research. The addressed research gap of this study is two-folded: First, foundations to the subject on how different crises impact BM change intention exist, yet their analysis lacks the inclusion of barriers. Especially, entrepreneurship literature lacks knowledge about the individual perception of BMI barriers, which is essential to predict managerial reactions. Moreover, internal BMI barriers have been the focal point of current research, while external BMI barriers remain virtually understudied. Second, to date, BMI research is based on qualitative methodologies. Thus, a lack of quantitative work can specify and confirm these qualitative findings. By focusing on the crisis context, this study contributes to BMI literature by offering a first quantitative attempt to embed BMI barriers into a structural equation model. It measures managers' perception of BMI development and implementation barriers in the BMI process, asking the following research question: How does a manager's perception of BMI barriers influence BMI development and implementation in times of crisis? Two distinct research streams in economic literature explain how individuals react when perceiving a threat. "Prospect Theory" claims that managers demonstrate risk-seeking tendencies when facing a potential loss, and opposing "Threat-Rigidity Theory" suggests that managers demonstrate risk-averse behavior when facing a potential loss. This study quantitively tests which theory can best predict managers' BM reaction to a perceived crisis. Out of three in-depth interviews in the German chemical industry, 60 past BMIs were identified. The participating start-up managers gave insights into their start-up's strategic and operational functioning. After, each interviewee described crises that had already affected their BM. The participants explained how they conducted BMI to overcome these crises, which development and implementation barriers they faced, and how severe they perceived them, assessed on a 5-point Likert scale. In contrast to current research, results reveal that a higher perceived threat level of a crisis harms BM experimentation. Managers seem to conduct less BMI in times of crisis, whereby BMI development barriers dampen this relation. The structural equation model unveils a mediating role of BMI implementation barriers on the link between the intention to change a BM and the concrete BMI implementation. In conclusion, this study confirms the threat-rigidity theory.

Keywords: barrier perception, business model innovation, business model innovation barriers, crises, prospect theory, start-ups, structural equation model, threat-rigidity theory

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Authors: Anzor Abralava, Ketevan Kokrashvili, Rusudan Kutateladze, Nino Pailodze, Ketevan Kutateladze, Giorgi Sulashvili

Abstract:

Nowadays when the integration of states is growing fast, it is urgent to study the rules of behavior which they resort to in case of conflicts and disagreements. The reason of disagreement in many ways is the Foreign policy carried out by separate countries, as the market participants define production and export capacity and structure as well as level of international division of labor due to the competition among them. We can say over and over again that outbreak of conflicts in Georgia displays the serious controversy between political and economic powerhouses. However, to tell the truth existence of the unsolved conflicts in Georgia is the result of weakness and inadequacy of Georgian politics. Today the main task of political quarters in Georgia should be a direction to Caucasus, as to the region burdened with the most complicated problems which blockade the settlement of conflicts and farther development of our country (or vice versa). In this situation rehabilitation of our authority, leading role and hegemony; expansion and consolidation of peacekeeping and other missions are considered as the exact activities for accomplishing all Georgian economic and political goals.

Keywords: Awara Group, political centers, administrative services, dynamic process

Procedia PDF Downloads 260

Authors: Ankur Mundhra, Shubhadeep Chakraborty, Y. R. Singh, Vishal Das

Abstract:

Seismic data scaling affects the dynamic range of a data and with present day lower costs of storage and higher reliability of Hard Disk data, scaling is not suggested. However, in dealing with data of different vintages, which perhaps were processed in 16 bits or even 8 bits and are need to be processed with 32 bit available data, scaling is performed. Also, scaling amplifies low amplitude events in deeper region which disappear due to high amplitude shallow events that saturate amplitude scale. We have focused on significance of scaling data to aid interpretation. This study elucidates a proper seismic loading procedure in workstations without using default preset parameters as available in most software suites. Differences and distribution of amplitude values at different depth for seismic data are probed in this exercise. Proper loading parameters are identified and associated steps are explained that needs to be taken care of while loading data. Finally, the exercise interprets the un-certainties which might arise when correlating scaled and unscaled versions of seismic data with synthetics. As, seismic well tie correlates the seismic reflection events with well markers, for our study it is used to identify regions which are enhanced and/or affected by scaling parameter(s).

Keywords: clipping, compression, resolution, seismic scaling

Procedia PDF Downloads 457