Search results for: estimation algorithm

Authors: Muhammad M. A. S. Mahmoud

Abstract:

Natural gas sweetening process is a controlled process that must be done at maximum efficiency and with the highest quality. In this work, due to complexity and non-linearity of the process, the H₂S gas separation and the intelligent fuzzy controller, which is used to enhance the process, are simulated in MATLAB – Simulink. The new design of fuzzy control for Gas Separator is discussed in this paper. The design is based on the utilization of linear state-estimation to generate the internal knowledge-base that stores input-output pairs. The obtained input/output pairs are then used to design a feedback fuzzy controller. The proposed closed-loop fuzzy control system maintains the system asymptotically-stability while it enhances the system time response to achieve better control of the concentration of the output gas from the tower. Simulation studies are carried out to illustrate the Gas Separator system performance.

Keywords: gas separator, gas sweetening, intelligent controller, fuzzy control

Procedia PDF Downloads 454

Authors: T. Kobayashi, K. Shiba, T. Kaburagi, Y. Kurihara

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For the elderly living alone, falls can be a serious problem encountered in daily life. Some elderly people are unable to stand up without the assistance of a caregiver. They may become unconscious after a fall, which can lead to serious aftereffects such as hypothermia, dehydration, and sometimes even death. We treat the subject as an inverted pendulum and model its angle from the equilibrium position and its angular velocity. As the model is non-linear, we implement the filtering method with a particle filter which can estimate true states of the non-linear model. In order to evaluate the accuracy of the particle filter estimation results, we calculate the root mean square error (RMSE) between the estimated angle/angular velocity and the true values generated by the simulation. The experimental results give the highest accuracy RMSE of 0.0141 rad and 0.1311 rad/s for the angle and angular velocity, respectively.

Keywords: fall, microwave Doppler sensor, non-linear dynamics model, particle filter

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Authors: Daphne Ashley Sze, Kenneth Santos, Ariane Gabrielle Lim

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As women are now given more freedom and choice to pursue employment, the world’s over-all fertility has been decreasing mainly due to the shift in time allocation between working and child rearing. As such, we study the case of the Philippines, where there exists a decreasing fertility rate and increasing openness for women labor participation. We focused on the distinction between fertility and fecundity, the former being the manifestation of the latter and aim to trace and compare the effects of both fecundity and fertility to women’s employment status through the estimation of the reproduction function and multinomial logistic function. Findings suggest that the perception of women regarding employment opportunities in the Philippines links the negative relationship observed between fertility, fecundity and women’s employment status. Today, there has been a convergence in the traditional family roles of men and women, as both genders now have identical employment opportunities that continue to shape their preferences.

Keywords: multinomial logistic function, tobit, fertility, women employment status, fecundity

Procedia PDF Downloads 589

Authors: Khalid Sekkat, Fredj Fhima, Ridha Nouira

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This paper focuses on three main limitations of the literature regarding the impact of corruption on democracy. These limitations relate to the distinction between causality and correlation, the components of democracy underlying the impact and the shape of the relationship between corruption and democracy. The study uses recent developments in panel data causality econometrics, breaks democracy down into different components, and examines the types of the relationship. The results show that Control of Corruption leads to a higher quality of democracy. Regarding the estimated coefficients of the components of democracy, they are significant at the 1% level, and their signs and levels are in accordance with expectations except in a few cases. Overall, the results add to the literature in three respects: i). corruption has a causal effect on democracy and, hence, single equation estimation may pose a problem, ii) the assumption of the linearity of the relationships between control of corruption and democracy is also possibly problematic, and iii) the channels of transmission of the effects of corruption on democracy can be diverse. Disentangling them is useful from a policy perspective.

Keywords: corruption, governance, causality, threshold models

Procedia PDF Downloads 30

Authors: J. D. Martínez-Vargas, C. Castro-Hoyos, G. Castellanos-Dominguez

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In this work, we propose a novel approach for measuring the stationarity level of a multichannel time-series. This measure is based on a stationarity definition over time-varying spectrum, and it is aimed to quantify the relation between local stationarity (single-channel) and global dynamic behavior (multichannel dynamics). To assess the proposed approach validity, we use a well known EEG-BCI database, that was constructed for separate between motor/imagery tasks. Thus, based on the statement that imagination of movements implies an increase on the EEG dynamics, we use as discriminant features the proposed measure computed over an estimation of the non-stationary components of input time-series. As measure of separability we use a t-student test, and the obtained results evidence that such measure is able to accurately detect the brain areas projected on the scalp where motor tasks are realized.

Keywords: stationary measure, entropy, sub-space projection, multichannel dynamics

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Authors: Willian C. De Brito, Hernan D. C. Munoz, Erlan V. C. Carvalho, Helder L. C. De Oliveira

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In order to improve commute time for small distance trips and relieve large cities traffic, a new transport category has been the subject of research and new designs worldwide. The air taxi travel market promises to change the way people live and commute by using the concept of vehicles with the ability to take-off and land vertically and to provide passenger’s transport equivalent to a car, with mobility within large cities and between cities. Today’s civil air transport remains costly and accounts for 2% of the man-made CO₂ emissions. Taking advantage of this scenario, many companies have developed their own Vertical Take Off and Landing (VTOL) design, seeking to meet comfort, safety, low cost and flight time requirements in a sustainable way. Thus, the use of green power supplies, especially batteries, and fully electric power plants is the most common choice for these arising aircrafts. However, it is still a challenge finding a feasible way to handle with the use of batteries rather than conventional petroleum-based fuels. The batteries are heavy and have an energy density still below from those of gasoline, diesel or kerosene. Therefore, despite all the clear advantages, all electric aircrafts (AEA) still have low flight autonomy and high operational cost, since the batteries must be recharged or replaced. In this sense, this paper addresses a way to optimize the energy consumption in a typical mission of an aerial taxi aircraft. The approach and landing procedure was chosen to be the subject of an optimization genetic algorithm, while final programming can be adapted for take-off and flight level changes as well. A real tilt rotor aircraft with fully electric power plant data was used to fit the derived dynamic equations of motion. Although a tilt rotor design is used as a proof of concept, it is possible to change the optimization to be applied for other design concepts, even those with independent motors for hover and cruise flight phases. For a given trajectory, the best set of control variables are calculated to provide the time history response for aircraft´s attitude, rotors RPM and thrust direction (or vertical and horizontal thrust, for independent motors designs) that, if followed, results in the minimum electric power consumption through that landing path. Safety, comfort and design constraints are assumed to give representativeness to the solution. Results are highly dependent on these constraints. For the tested cases, performance improvement ranged from 5 to 10% changing initial airspeed, altitude, flight path angle, and attitude.

Keywords: air taxi travel, all electric aircraft, batteries, energy consumption, genetic algorithm, landing performance, optimization, performance improvement, tilt rotor, VTOL design

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Authors: Han-Taw Chen, Chung-Hou Lai, Tzu-Hsiang Lin, Ge-Jang He

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This study applies the inverse method and three-dimensional CFD commercial software in conjunction with the experimental temperature data to investigate the heat transfer and fluid flow characteristics of the plate-fin heat sink in a closed rectangular enclosure for various values of fin height. The inverse method with the finite difference method and the experimental temperature data is applied to determine the heat transfer coefficient. The k-ε turbulence model is used to obtain the heat transfer and fluid flow characteristics within the fins. To validate the accuracy of the results obtained, the comparison of the average heat transfer coefficient is made. The calculated temperature at selected measurement locations on the plate-fin is also compared with experimental data.

Keywords: inverse method, FLUENT, k-ε model, heat transfer characteristics, plate-fin heat sink

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Authors: Minho Kwak, Suhwan Yun, Choonsoo Park

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Nose shape optimizations of high-speed train are performed for the improvement of aerodynamic characteristics. Based on the commercial train, KTX-Sancheon, multi-objective optimizations are conducted for the improvement of the side wind stability and the micro-pressure wave following the optimization for the reduction of aerodynamic drag. 3D nose shapes are modelled by the Vehicle Modeling Function. Aerodynamic drag and side wind stability are calculated by three-dimensional compressible Navier-Stokes solver, and micro pressure wave is done by axi-symmetric compressible Navier-Stokes solver. The Maxi-min Latin Hypercube Sampling method is used to extract sampling points to construct the approximation model. The kriging model is constructed for the approximation model and the NSGA-II algorithm was used as the multi-objective optimization algorithm. Nose length, nose tip height, and lower surface curvature are design variables. Because nose length is a dominant variable for aerodynamic characteristics of train nose, two optimization processes are progressed respectively with and without the design variable, nose length. Each pareto set was obtained and each optimized nose shape is selected respectively considering Honam high-speed rail line infrastructure in South Korea. Through the optimization process with the nose length, when compared to KTX Sancheon, aerodynamic drag was reduced by 9.0%, side wind stability was improved by 4.5%, micro-pressure wave was reduced by 5.4% whereas aerodynamic drag by 7.3%, side wind stability by 3.9%, micro-pressure wave by 3.9%, without the nose length. As a result of comparison between two optimized shapes, similar shapes are extracted other than the effect of nose length.

Keywords: aerodynamic characteristics, design variable, multi-objective optimization, train nose shape

Procedia PDF Downloads 341

Authors: Ambali Alade Odebowale, Andargachew Mekonnen Berhe, Haroldo T. Hattori, Andrey E. Miroshnichenko

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Solar thermophotovoltaic systems (STPV) have emerged as a promising solution to overcome the Shockley-Queisser limit, a significant impediment in the direct conversion of solar radiation into electricity using conventional solar cells. The STPV system comprises essential components such as an optical concentrator, selective emitter, and a thermophotovoltaic (TPV) cell. The pivotal element in achieving high efficiency in an STPV system lies in the design of a spectrally selective emitter or absorber. Traditional methods for designing and optimizing selective emitters are often time-consuming and may not yield highly selective emitters, posing a challenge to the overall system performance. In recent years, the application of machine learning techniques in various scientific disciplines has demonstrated significant advantages. This paper proposes a novel nanostructure composed of four-layered materials (SiC/W/SiO2/W) to function as a selective emitter in the energy conversion process of an STPV system. Unlike conventional approaches widely adopted by researchers, this study employs a machine learning-based approach for the design and optimization of the selective emitter. Specifically, a random forest algorithm (RFA) is employed for the design of the selective emitter, while the optimization process is executed using genetic algorithms. This innovative methodology holds promise in addressing the challenges posed by traditional methods, offering a more efficient and streamlined approach to selective emitter design. The utilization of a machine learning approach brings several advantages to the design and optimization of a selective emitter within the STPV system. Machine learning algorithms, such as the random forest algorithm, have the capability to analyze complex datasets and identify intricate patterns that may not be apparent through traditional methods. This allows for a more comprehensive exploration of the design space, potentially leading to highly efficient emitter configurations. Moreover, the application of genetic algorithms in the optimization process enhances the adaptability and efficiency of the overall system. Genetic algorithms mimic the principles of natural selection, enabling the exploration of a diverse range of emitter configurations and facilitating the identification of optimal solutions. This not only accelerates the design and optimization process but also increases the likelihood of discovering configurations that exhibit superior performance compared to traditional methods. In conclusion, the integration of machine learning techniques in the design and optimization of a selective emitter for solar thermophotovoltaic systems represents a groundbreaking approach. This innovative methodology not only addresses the limitations of traditional methods but also holds the potential to significantly improve the overall performance of STPV systems, paving the way for enhanced solar energy conversion efficiency.

Keywords: emitter, genetic algorithm, radiation, random forest, thermophotovoltaic

Procedia PDF Downloads 52

Authors: Ariane C. Lim, Daphne Ashley L. Sze, Kenneth S. Santos

Abstract:

As women are now given more freedom and choice to pursue employment, the world’s over-all fertility has been decreasing mainly due to the shift in time allocation between working and child-rearing. As such, we study the case of the Philippines, where there exists a decreasing fertility rate and increasing openness for women labor participation. We focused on the distinction between fertility and fecundity, the former being the manifestation of the latter and aim to trace and compare the effects of both fecundity and fertility to women’s employment status through the estimation of the reproduction function and multinomial logistic function. Findings suggest that the perception of women regarding employment opportunities in the Philippines links the negative relationship observed between fertility, fecundity and women’s employment status. Today, there has been a convergence in the traditional family roles of men and women, as both genders now have identical employment opportunities that continue to shape their preferences.

Keywords: multinomial logistic function, tobit, fertility, women employment status, fecundity

Procedia PDF Downloads 610

Authors: Pragyan Paramita Das, Vishwas N. Khatri

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By using the lower- and upper- bound finite elements to limit analysis in conjunction with second-order conic programming (SOCP), the effect of seismic forces on the bearing capacity of surface strip footing resting on dense sand underlain by loose sand deposit is explored. The soil is assumed to obey the Mohr-Coulomb’s yield criterion and an associated flow rule. The angle of internal friction (ϕ) of the top and the bottom layer is varied from 42° to 44° and 32° to 34° respectively. The coefficient of seismic acceleration is varied from 0 to 0.3. The variation of bearing capacity with different thickness of top layer for various seismic acceleration coefficients is generated. A comparison will be made with the available solutions from literature wherever applicable.

Keywords: bearing capacity, conic programming, finite elements, seismic forces

Procedia PDF Downloads 161

Authors: Zakir Husain, Deepak Kumar

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The harmonics are very harmful within an electrical system and can have serious consequences such as reducing the life of apparatus, stress on cable and equipment etc. This paper cites extensive analytical study of harmonic characteristics of multiphase (six-phase) and three-phase system equipped with two and three level inverters for non-linear loads. Multilevel inverter has elevated voltage capability with voltage limited devices, low harmonic distortion, abridged switching losses. Multiphase technology also pays a promising role in harmonic reduction. Matlab simulation is carried out to compare the advantage of multi-phase over three phase systems equipped with two or three level inverters for non-linear load harmonic reduction. The extensive simulation results are presented based on case studies.

Keywords: fast Fourier transform (FFT), harmonics, inverter, ripples, total harmonic distortion (THD)

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Authors: Tengku Nilam Baizura, Noor Zalina Mahmood

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In Malaysia, landfilling is the most preferred method and most of it does not have the proper leachate treatment system which can cause environmental problems. Leachate is the major factor to river water pollution since most landfills are located near the river which is the main water resource for the country. The study aimed to estimate leachate production from landfills in Selangor. A simple mathematical modelling was used for the calculation of annual leachate volume. The estimate of identified landfill area (A) using Google Earth was multiplied by the annual rainfall (R). The product is expressed as volume (V). The data indicate that the leachate production is high even it is fully closed. It is important to design the efficient landfill and proper leachate treatment processes especially for the old/closed landfill. Extensive monitoring will be required to predict future impact.

Keywords: landfill, leachate, municipal solid waste management, waste disposal

Procedia PDF Downloads 360

Authors: M. Jathaveda, Joben Leons, G. Vidya

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Reentry from orbit is a critical phase in the entry trajectory. For a non-propulsive ballistic entry, static and dynamic stability play an important role in the trajectory, especially for the safe deployment of parachutes, typically at subsonic Mach numbers. Static stability of flight vehicles are being estimated through CFD techniques routinely. Advances in CFD software as well as computational facilities have enabled the estimation of the dynamic stability derivatives also through CFD techniques. Longitudinal static and dynamic stability of a typical reentry body for subsonic Mach number of 0.6 is predicted using commercial software CFD++ and presented here. Steady state simulations are carried out for α = 2° on an unstructured grid using SST k-ω model. Transient simulation using forced oscillation method is used to compute pitch damping derivatives.

Keywords: stability, typical reentry body, subsonic, static and dynamic

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Authors: O. Bendermel, C. Seladji, M. Khaouani

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In this work, we made a numerical study of the thermal and dynamic behaviour of air in a horizontal channel with electronic components. The influence to use baffles on the profiles of velocity and temperature is discussed. The finite volume method and the algorithm Simple are used for solving the equations of conservation of mass, momentum and energy. The results found show that baffles improve heat transfer between the cooling air and electronic components. The velocity will increase from 3 times per rapport of the initial velocity.

Keywords: electronic components, baffles, cooling, fluids engineering

Procedia PDF Downloads 284

Authors: Y. Zhang, J. Perez, S. Marnier

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To date, no study on goaltending butterfly motion has been completed in real conditions, during an ice hockey game or training practice, to the author's best knowledge. This motion, performed to save score, is unnatural, intense, and repeated. The target of this research activity is to identify representative biomechanical criteria for this goaltender-specific movement pattern. Determining specific physical parameters may allow to will identify the risk of hip and groin injuries sustained by goaltenders. Four professional or academic goalies were instrumented during ice hockey training practices with five inertial measurement units. These devices were inserted in dedicated pockets located on each thigh and shank, and the fifth on the lumbar spine. A camera was also installed close to the ice to observe and record the goaltenders' activities, especially the butterfly motions, in order to synchronize the captured data and the behavior of the goaltender. Each data recorded began with a calibration of the inertial units and a calibration of the fully equipped goaltender on the ice. Three butterfly motions were recorded out of the training practice to define referential individual butterfly motions. Then, a data processing algorithm based on the Madgwick filter computed hip and knee joints joint range of motion as well as angular specific angular velocities. The developed algorithm software automatically identified and analyzed all the butterfly motions executed by the four different goaltenders. To date, it is still too early to show that the analyzed criteria are representative of the trauma generated by the butterfly motion as the research is only at its beginning. However, this descriptive research activity is promising in its ecological assessment, and once the criteria are found, the tools and protocols defined will allow the prevention of as many injuries as possible. It will thus be possible to build a specific training program for each goalie.

Keywords: biomechanics, butterfly motion, human motion analysis, ice hockey, inertial measurement unit

Procedia PDF Downloads 119

Authors: I. Kade Wiratama

Abstract:

As a result of the significant growth of wind turbines in size, blade load control has become the main challenge for large wind turbines. Many advanced techniques have been investigated aiming at developing control devices to ease blade loading. Amongst them, trailing edge flaps have been proven as effective devices for load alleviation. The present study aims at investigating the potential benefits of flaps in enhancing the energy capture capabilities rather than blade load alleviation. A software tool is especially developed for the aerodynamic simulation of wind turbines utilising blades equipped with flaps. As part of the aerodynamic simulation of these wind turbines, the control system must be also simulated. The simulation of the control system is carried out via solving an optimisation problem which gives the best value for the controlling parameter at each wind turbine run condition. Developing a genetic algorithm optimisation tool which is especially designed for wind turbine blades and integrating it with the aerodynamic performance evaluator, a design optimisation tool for blades equipped with flaps is constructed. The design optimisation tool is employed to carry out design case studies. The results of design case studies on wind turbine AWT 27 reveal that, as expected, the location of flap is a key parameter influencing the amount of improvement in the power extraction. The best location for placing a flap is at about 70% of the blade span from the root of the blade. The size of the flap has also significant effect on the amount of enhancement in the average power. This effect, however, reduces dramatically as the size increases. For constant speed rotors, adding flaps without re-designing the topology of the blade can improve the power extraction capability as high as of about 5%. However, with re-designing the blade pretwist the overall improvement can be reached as high as 12%.

Keywords: flaps, design blade, optimisation, simulation, genetic algorithm, WTAero

Procedia PDF Downloads 328

Authors: Amit Kumar Happy

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This paper is motivated by the importance of multi-sensor image fusion with a specific focus on infrared (IR) and visual image (VI) fusion for various applications, including military reconnaissance. Image fusion can be defined as the process of combining two or more source images into a single composite image with extended information content that improves visual perception or feature extraction. These images can be from different modalities like visible camera & IR thermal imager. While visible images are captured by reflected radiations in the visible spectrum, the thermal images are formed from thermal radiation (infrared) that may be reflected or self-emitted. A digital color camera captures the visible source image, and a thermal infrared camera acquires the thermal source image. In this paper, some image fusion algorithms based upon multi-scale transform (MST) and region-based selection rule with consistency verification have been proposed and presented. This research includes the implementation of the proposed image fusion algorithm in MATLAB along with a comparative analysis to decide the optimum number of levels for MST and the coefficient fusion rule. The results are presented, and several commonly used evaluation metrics are used to assess the suggested method's validity. Experiments show that the proposed approach is capable of producing good fusion results. While deploying our image fusion algorithm approaches, we observe several challenges from the popular image fusion methods. While high computational cost and complex processing steps of image fusion algorithms provide accurate fused results, they also make it hard to become deployed in systems and applications that require a real-time operation, high flexibility, and low computation ability. So, the methods presented in this paper offer good results with minimum time complexity.

Keywords: image fusion, IR thermal imager, multi-sensor, multi-scale transform

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Authors: Mohammedi Ferhate

Abstract:

This work presents details of the study of the entire flow inside the facility where the exothermic chemical reaction process in the chemical laser cavity is analyzed. In our paper we will describe the principles of chemical lasers where flow reversal is produced by chemical reactions. We explain the device for converting chemical potential energy laser energy. We see that the phenomenon thus has an explosive trend. Finally, the feasibility and effectiveness of the proposed method is demonstrated by computer simulation

Keywords: genetic, lasers, nozzle, programming

Procedia PDF Downloads 83

Authors: Sreto Boljevic

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In the absence of considerable investment in electricity generation, transmission and distribution network (DN) capacity, the demand for electrical energy will quickly strain the capacity of the existing electrical power network. With anticipated growth and proliferation of Electric vehicles (EVs) and Heat pump (HPs) identified the likelihood that the additional load from EV changing and the HPs operation will require capital investment in the DN. While an area-wide implementation of EVs and HPs will contribute to the decarbonization of the energy system, they represent new challenges for the existing low-voltage (LV) network. Distributed energy resources (DER), operating both as part of the DN and in the off-network mode, have been offered as a means to meet growing electricity demand while maintaining and ever-improving DN reliability, resiliency and power quality. DN planning has traditionally been done by forecasting future growth in demand and estimating peak load that the network should meet. However, new problems are arising. These problems are associated with a high degree of proliferation of EVs and HPs as load imposes on DN. In addition to that, the promotion of electricity generation from renewable energy sources (RES). High distributed generation (DG) penetration and a large increase in load proliferation at low-voltage DNs may have numerous impacts on DNs that create issues that include energy losses, voltage control, fault levels, reliability, resiliency and power quality. To mitigate negative impacts and at a same time enhance positive impacts regarding the new operational state of DN, CHP system integration can be seen as best action to postpone/reduce capital investment needed to facilitate promotion and maximize benefits of EVs, HPs and RES integration in low-voltage DN. The aim of this paper is to generate an algorithm by using an analytical approach. Algorithm implementation will provide a way for optimal placement of the CHP system in the DN in order to maximize the integration of RES and increase in proliferation of EVs and HPs.

Keywords: combined heat & power (CHP), distribution networks, EVs, HPs, RES

Procedia PDF Downloads 190

Authors: Burcu Kaya, Jan-Martin Kaiser, Karl-Friedrich Becker, Tanja Braun, Klaus-Dieter Lang

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Quality of the molded packages is strongly influenced by the process parameters of the transfer molding. To achieve a better package quality and a stable transfer molding process, it is necessary to understand the influence of the process parameters on the package quality. This work aims to comprehend the relationship between the process parameters, and to identify the optimum process parameters for the transfer molding process in order to achieve less voids and wire sweep. To achieve this, a DoE is executed for process optimization and a regression analysis is carried out. A systematic approach is represented to generate models which enable an estimation of the number of voids and wire sweep. Validation experiments are conducted to verify the model and the results are presented.

Keywords: dielectric analysis, electronic packages, epoxy molding compounds, transfer molding process

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Authors: Borhan Marzougui

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Road and Transport Authority (RTA) is moving ahead with the implementation of the leader’s vision in exploring all avenues that may bring better security and safety services to the community. Smart transport means using smart technologies such as IoT (Internet of Things). This technology continues to affirm its important role in the context of Information and Transportation Systems. In fact, IoT is a network of Internet-connected objects able to collect and exchange different data using embedded sensors. With the growth of IoT, Distributed Denial of Service (DDoS) attacks is also growing exponentially. DDoS attacks are the major and a real threat to various transportation services. Currently, the defense mechanisms are mainly passive in nature, and there is a need to develop a smart technique to handle them. In fact, new IoT devices are being used into a botnet for DDoS attackers to accumulate for attacker purposes. The aim of this paper is to provide a relevant understanding of dangerous types of DDoS attack related to IoT and to provide valuable guidance for the future IoT security method. Our methodology is based on development of the distributed algorithm. This algorithm manipulates dedicated intelligent and cooperative agents to prevent and to mitigate DDOS attacks. The proposed technique ensure a preventive action when a malicious packets start to be distributed through the connected node (Network of IoT devices). In addition, the devices such as camera and radio frequency identification (RFID) are connected within the secured network, and the data generated by it are analyzed in real time by intelligent and cooperative agents. The proposed security system is based on a multi-agent system. The obtained result has shown a significant reduction of a number of infected devices and enhanced the capabilities of different security dispositives.

Keywords: IoT, DDoS, attacks, botnet, security, agents

Procedia PDF Downloads 133

Authors: Aditya Verma

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E-voting using blockchain provides us with a distributed system where data is present on each node present in the network and is reliable and secure too due to its immutability property. This work compares various blockchain consensus algorithms used for e-voting applications in the past, based on performance and node scalability, and chooses the optimal one and improves on one such previous implementation by proposing solutions for the loopholes of the optimally working blockchain consensus algorithm, in our chosen application, e-voting.

Keywords: blockchain, parallel bft, consensus algorithms, performance

Procedia PDF Downloads 158

Authors: Hadi Farhadian, Homayoon Katibeh

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In this paper, groundwater seepage into Amirkabir tunnel has been estimated using analytical and numerical methods for 14 different sections of the tunnel. Site Groundwater Rating (SGR) method also has been performed for qualitative and quantitative classification of the tunnel sections. The obtained results of above-mentioned methods were compared together. The study shows reasonable accordance with results of the all methods unless for two sections of tunnel. In these two sections there are some significant discrepancies between numerical and analytical results mainly originated from model geometry and high overburden. SGR and the analytical and numerical calculations, confirm the high concentration of seepage inflow in fault zones. Maximum seepage flow into tunnel has been estimated 0.425 lit/sec/m using analytical method and 0.628 lit/sec/m using numerical method occurred in crashed zone. Based on SGR method, six sections of 14 sections in Amirkabir tunnel axis are found to be in "No Risk" class that is supported by the analytical and numerical seepage value of less than 0.04 lit/sec/m.

Keywords: water Seepage, Amirkabir Tunnel, analytical method, DEM, SGR

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Authors: Yanto Santosa, Dede Aulia Rahman, Cory Wulan, Abdul Haris Mustari

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The global demand for long-tailed macaques for medical experimentation has continued to increase. Fulfillment of Indonesian export demands has been mostly from natural habitats, based on a harvesting quota. This quota has been determined according to the total catch for a given year, and not based on consideration of any demographic parameters or physical environmental factors with regard to the animal; hence threatening the sustainability of the various populations. It is therefore necessary to formulate a method for calculating a sustainable harvesting quota, based on population parameters in natural habitats. Considering the possibility of variations in habitat characteristics and population parameters, a time series observation of demographic and physical/biotic parameters, in various habitats, was performed on 13 groups of long-tailed macaques, distributed throughout the West Java, Lampung and Yogyakarta areas of Indonesia. These provinces were selected for comparison of the influence of human/tourism activities. Data on population parameters that was collected included data on life expectancy according to age class, numbers of individuals by sex and age class, and ‘ratio of infants to reproductive females’. The estimation of population growth was based on a population dynamic growth model: the Leslie matrix. The harvesting quota was calculated as being the difference between the actual population size and the MVP (minimum viable population) for each sex and age class. Observation indicated that there were variations within group size (24 – 106 individuals), gender (sex) ratio (1:1 to 1:1.3), life expectancy value (0.30 to 0.93), and ‘ratio of infants to reproductive females’ (0.23 to 1.56). Results of subsequent calculations showed that sustainable harvesting quotas for each studied group of long-tailed macaques, ranged from 29 to 110 individuals. An estimation model of the MVP for each age class was formulated as Log Y = 0.315 + 0.884 Log Ni (number of individual on ith age class). This study also found that life expectancy for the juvenile age class was affected by the humidity under tree stands, and dietary plants’ density at sapling, pole and tree stages (equation: Y= 2.296 – 1.535 RH + 0.002 Kpcg – 0.002 Ktg – 0.001 Kphn, R2 = 89.6% with a significance value of 0.001). By contrast, for the sub-adult-adult age class, life expectancy was significantly affected by slope (equation: Y=0.377 = 0.012 Kml, R2 = 50.4%, with significance level of 0.007). The infant to reproductive female ratio was affected by humidity under tree stands, and dietary plant density at sapling and pole stages (equation: Y = -1.432 + 2.172 RH – 0.004 Kpcg + 0.003 Ktg, R2 = 82.0% with significance level of 0.001). This research confirmed the importance of population parameters in determining the minimum viable population, and that MVP varied according to habitat characteristics (especially food availability). It would be difficult therefore, to formulate a general mathematical equation model for determining a harvesting quota for the species as a whole.

Keywords: harvesting, long-tailed macaque, population, quota

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Authors: Neta Kela Madar, Tali Teeni-Harari, Tamar Icekson, Yaron Sela

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This paper proposes and empirically tests a theoretical model positing relationships between dispositional optimism, emotional intelligence, and entrepreneurial intention. To author's best knowledge, this study examined for the first time the role of dispositional optimism together with emotional intelligence as predictors of entrepreneurial intentions. The study findings suggest that optimism may increase entrepreneurial intentions indirectly by enhancing emotional intelligence/ model formulation is based on a random survey of students (N= 227). Model parameter estimation was supported by Structural Equation Modeling (SEM). Results indicate that students’ optimism and emotional intelligence are associated with increased levels of entrepreneurial intention. Additionally, the present study argues that emotional intelligence mediates the positive relationship between optimism and entrepreneurial intention. Theoretical and practical implications of this model are discussed.

Keywords: entrepreneurial intentions, emotional intelligence, optimism, dispositional optimism

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Authors: Jazim Sohail, Filipe Teixeira-Dias

Abstract:

Mild traumatic brain injury (mTBI) within non-helmeted contact sports is a growing concern due to the serious risk of potential injury. Extensive research is being conducted looking into head kinematics in non-helmeted contact sports utilizing instrumented mouthguards that allow researchers to record accelerations and velocities of the head during and after an impact. This does not, however, allow the location of the impact on the head, and its magnitude and orientation, to be determined. This research proposes and validates two methods to quantify impact locations from instrumented mouthguard kinematic data, one using rigid body dynamics, the other utilizing machine learning. The rigid body dynamics technique focuses on establishing and matching moments from Euler’s and torque equations in order to find the impact location on the head. The methodology is validated with impact data collected from a lab test with the dummy head fitted with an instrumented mouthguard. Additionally, a Hybrid III Dummy head finite element model was utilized to create synthetic kinematic data sets for impacts from varying locations to validate the impact location algorithm. The algorithm calculates accurate impact locations; however, it will require preprocessing of live data, which is currently being done by cross-referencing data timestamps to video footage. The machine learning technique focuses on eliminating the preprocessing aspect by establishing trends within time-series signals from instrumented mouthguards to determine the impact location on the head. An unsupervised learning technique is used to cluster together impacts within similar regions from an entire time-series signal. The kinematic signals established from mouthguards are converted to the frequency domain before using a clustering algorithm to cluster together similar signals within a time series that may span the length of a game. Impacts are clustered within predetermined location bins. The same Hybrid III Dummy finite element model is used to create impacts that closely replicate on-field impacts in order to create synthetic time-series datasets consisting of impacts in varying locations. These time-series data sets are used to validate the machine learning technique. The rigid body dynamics technique provides a good method to establish accurate impact location of impact signals that have already been labeled as true impacts and filtered out of the entire time series. However, the machine learning technique provides a method that can be implemented with long time series signal data but will provide impact location within predetermined regions on the head. Additionally, the machine learning technique can be used to eliminate false impacts captured by sensors saving additional time for data scientists using instrumented mouthguard kinematic data as validating true impacts with video footage would not be required.

Keywords: head impacts, impact location, instrumented mouthguard, machine learning, mTBI

Procedia PDF Downloads 205

Authors: Ali Kazemi

Abstract:

Those within the volatile and interconnected international economic markets, appropriately predicting market trends, hold substantial fees for traders and financial establishments. Traditional device mastering strategies have made full-size strides in forecasting marketplace movements; however, monetary data's complicated and networked nature calls for extra sophisticated processes. This observation offers a groundbreaking method for monetary marketplace prediction that leverages the synergistic capability of Graph Convolutional Networks (GCNs) and Long Short-Term Memory (LSTM) networks. Our suggested algorithm is meticulously designed to forecast the traits of inventory market indices and cryptocurrency costs, utilizing a comprehensive dataset spanning from January 1, 2015, to December 31, 2023. This era, marked by sizable volatility and transformation in financial markets, affords a solid basis for schooling and checking out our predictive version. Our algorithm integrates diverse facts to construct a dynamic economic graph that correctly reflects market intricacies. We meticulously collect opening, closing, and high and low costs daily for key inventory marketplace indices (e.g., S&P 500, NASDAQ) and widespread cryptocurrencies (e.g., Bitcoin, Ethereum), ensuring a holistic view of marketplace traits. Daily trading volumes are also incorporated to seize marketplace pastime and liquidity, providing critical insights into the market's shopping for and selling dynamics. Furthermore, recognizing the profound influence of the monetary surroundings on financial markets, we integrate critical macroeconomic signs with hobby fees, inflation rates, GDP increase, and unemployment costs into our model. Our GCN algorithm is adept at learning the relational patterns amongst specific financial devices represented as nodes in a comprehensive market graph. Edges in this graph encapsulate the relationships based totally on co-movement styles and sentiment correlations, enabling our version to grasp the complicated community of influences governing marketplace moves. Complementing this, our LSTM algorithm is trained on sequences of the spatial-temporal illustration discovered through the GCN, enriched with historic fee and extent records. This lets the LSTM seize and expect temporal marketplace developments accurately. Inside the complete assessment of our GCN-LSTM algorithm across the inventory marketplace and cryptocurrency datasets, the version confirmed advanced predictive accuracy and profitability compared to conventional and opportunity machine learning to know benchmarks. Specifically, the model performed a Mean Absolute Error (MAE) of 0.85%, indicating high precision in predicting day-by-day charge movements. The RMSE was recorded at 1.2%, underscoring the model's effectiveness in minimizing tremendous prediction mistakes, which is vital in volatile markets. Furthermore, when assessing the model's predictive performance on directional market movements, it achieved an accuracy rate of 78%, significantly outperforming the benchmark models, averaging an accuracy of 65%. This high degree of accuracy is instrumental for techniques that predict the course of price moves. This study showcases the efficacy of mixing graph-based totally and sequential deep learning knowledge in economic marketplace prediction and highlights the fee of a comprehensive, records-pushed evaluation framework. Our findings promise to revolutionize investment techniques and hazard management practices, offering investors and economic analysts a powerful device to navigate the complexities of cutting-edge economic markets.

Keywords: financial market prediction, graph convolutional networks (GCNs), long short-term memory (LSTM), cryptocurrency forecasting

Procedia PDF Downloads 43

Authors: Dong-Bo Hsu

Abstract:

Universal Grammar (UG) claims that the constraints that are derived from this should operate in language users’ L2 grammars. This study investigated this hypothesis on knowledge of Subjacency and resumptive pronoun usage among Chinese learners of English. Chinese fulfills two requirements to examine the existence of UG, i.e., Subjacency does not operate in Chinese and resumptive pronouns in English are very different from those in Chinese and second L2 input undermines the knowledge of Subjacency. The results indicated that Chinese learners of English demonstrated a nearly identical pattern as English native speakers do but the resumptive pronoun in the embedding clauses. This may be explained in terms of the case that Chinese speakers’ usage of pronouns is not influenced by the number of embedding clauses. Chinese learners of English have full access to knowledge endowed by UG but their processing of English sentences may be different from native speakers as a general slow rate for processing in their L2 English.

Keywords: universal grammar, Chinese, English, wh-questions, resumption

Procedia PDF Downloads 460

Authors: Franziska Kaiser, Alexander Cuntz

Abstract:

When copyrighted comic characters are also protected under trademark laws, intellectual property (IP) rights can overlap. Arguably, registering a trademark can increase transaction costs for cross-media uses of characters, or it can favor advertise across a number of sales channels. In an application to book, movie, and video game publishing industries, we thus ask how creative reuse is affected in situations of overlapping rights and whether ‘fuzzy boundaries’ of right frameworks are, in fact, enhancing or decreasing content sales. We use a major U.S. Supreme Court decision as a quasi-natural experiment to apply an IV estimation in our analysis. We find that overlapping rights frameworks negatively affect creative reuses. At large, when copyright-protected comic characters are additionally registered as U.S. trademarks, they are less often reprinted and enter fewer video game productions while generating less revenue from game sales.

Keywords: copyright, fictional characters, trademark, reuse

Procedia PDF Downloads 199