Search results for: neural network models

Authors: Darren Zou

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Forecasting the stock market is a very challenging task. Various economic indicators such as GDP, exchange rates, interest rates, and unemployment have a substantial impact on the stock market. Time series models are the traditional methods used to predict stock market changes. In this paper, a machine learning method, Bayesian Additive Regression Tree (BART) is used in predicting stock market indexes based on multiple economic indicators. BART can be used to model heterogeneous treatment effects, and thereby works well when models are misspecified. It also has the capability to handle non-linear main effects and multi-way interactions without much input from financial analysts. In this research, BART is proposed to provide a reliable prediction on day-to-day stock market activities. By comparing the analysis results from BART and with time series method, BART can perform well and has better prediction capability than the traditional methods.

Keywords: BART, Bayesian, predict, stock

Procedia PDF Downloads 136

Authors: Hamed Mohamed Haggag

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Prior to 12 November 1955, no earthquakes have been reported from the Abu Dabbab area in the International Seismological Center catalogue (ISC). The largest earthquake in Abu Dabbab area occurred on November 12, 1955 with magnitude Mb 6.0. The closest station from the epicenter was at Helwan (about 700 km to the north), so the depth of this event is not constrained and no foreshocks or aftershocks were recorded. Two other earthquakes of magnitude Mb 4.5 and 5.2 took place in the same area on March 02, 1982 and July 02, 1984, respectively. Since the installation of Aswan Seismic Network stations in 1982, (250-300 km to the south-west of Abu Dabbab area) then the Egyptian Natoinal Seismic Network stations, it was possible to record some activity from Abu Dabbab area. The recorded earthquakes at Abu Dabbab area as recorded from 1982 to 2014 shows that the earthquake epicenters are distributed in the same direction of the main trends of the faults in the area, which is parallel to the Red Sea coast. The spectral analysis was made for some earthquakes. The source parameters, seismic moment (Mo), source dimension (r), stress drop (Δδ), and apparent stress (δ) are determined for these events. The spectral analysis technique was completed using MAG software program.

Keywords: Abu Dabbab, seismicity, seismic moment, source parameter

Procedia PDF Downloads 464

Authors: Dong-Hyun Ha, Young-Min Ko, Chang-Bin Ha, Hyoung-Kyu Song

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In Heterogeneous network (HetNet) can provide high quality of a service in a wireless communication system by composition of small cell networks. The composition of small cell networks improves cell coverage and capacity to the mobile users.Recently, various techniques using small cell networks have been researched in the wireless communication system. In this paper, the cooperative scheme obtaining high reliability is proposed in the small cell networks. The proposed scheme suggests a cooperative small cell system and the new signal transmission technique in the proposed system model. The new signal transmission technique applies a cyclic delay diversity (CDD) scheme based on the multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) system to obtain improved performance. The improved performance of the proposed scheme is confirmed by the simulation results.

Keywords: adaptive transmission, cooperative communication, diversity gain, OFDM

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Authors: I. Grigoratos, R. Monteiro

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Regions with a significant percentage of non-seismically designed buildings and reduced urban planning are particularly vulnerable to natural hazards. In this context, the project ‘Improved Tools for Disaster Risk Mitigation in Algeria’ (ITERATE) aims at seismic risk mitigation in Algeria. Past earthquakes in North Algeria caused extensive damages, e.g. the El Asnam 1980 moment magnitude (Mw) 7.1 and Boumerdes 2003 Mw 6.8 earthquakes. This paper will address a number of proposed developments and considerations made towards a further improvement of the component of seismic hazard. In specific, an updated earthquake catalog (until year 2018) is compiled, and new conversion equations to moment magnitude are introduced. Furthermore, a network-based method for the estimation of the spatial and temporal distribution of the minimum magnitude of completeness is applied. We found relatively large values for M_c, due to the sparse network, and a nonlinear trend between M_w and body wave (m_b) or local magnitude (M_L), which are the most common scales reported in the region. Lastly, the resulting b-value of the Gutenberg-Richter distribution is sensitive to the declustering method.

Keywords: conversion equation, magnitude of completeness, seismic events, seismic hazard

Procedia PDF Downloads 169

Authors: Puneet Katyal, Punit Kumar

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A great deal of efforts has been done in the field of thermal effects in electrohydrodynamic lubrication (TEHL) during the last five decades. The focus was primarily on the development of an efficient numerical scheme to deal with the computational challenges involved in the solution of TEHL model; however, some important aspects related to the accurate description of lubricant properties such as viscosity, rheology and thermal conductivity in EHL point contact analysis remain largely neglected. A few studies available in this regard are based upon highly complex mathematical models difficult to formulate and execute. Using a simplified thermal EHL model for point contacts, this work sheds some light on the importance of accurate characterization of the lubricant properties and demonstrates that the computed TEHL characteristics are highly sensitive to lubricant properties. It also emphasizes the use of appropriate mathematical models with experimentally determined parameters to account for correct lubricant behaviour.

Keywords: TEHL, shear thinning, rheology, conductivity

Procedia PDF Downloads 204

Authors: Seyed Hamed Hashemi Sohi, Gerald Jo Denoga

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Machining or metal cutting is one of the most widely used production processes in industry. The quality of the process and the resulting machined product depends on parameters like tool geometry, material, and cutting conditions. However, the relationships of these parameters to the cutting process are often based mostly on empirical knowledge. In this study, computer modeling and simulation using LS-DYNA software and a Smoothed Particle Hydrodynamic (SPH) methodology, was performed on the orthogonal metal cutting process to analyze three-dimensional deformation of AISI 1045 medium carbon steel during machining. The simulation was performed using the following constitutive models: the Power Law model, the Johnson-Cook model, and the Zerilli-Armstrong models (Z-A). The outcomes were compared against the simulated results obtained by Cenk Kiliçaslan using the Finite Element Method (FEM) and the empirical results of Jaspers and Filice. The analysis shows that the SPH method combined with the Zerilli-Armstrong constitutive model is a viable alternative to simulating the metal cutting process. The tangential force was overestimated by 7%, and the normal force was underestimated by 16% when compared with empirical values. The simulation values for flow stress versus strain at various temperatures were also validated against empirical values. The SPH method using the Z-A model has also proven to be robust against issues of time-scaling. Experimental work was also done to investigate the effects of friction, rake angle and tool tip radius on the simulation.

Keywords: metal cutting, smoothed particle hydrodynamics, constitutive models, experimental, cutting forces analyses

Procedia PDF Downloads 264

Authors: Hafida Ferfera-Harrar, Nacera Aiouaz, Nassima Dairi

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Super absorbents polymers received much attention and are used in many fields because of their superior characters to traditional absorbents, e.g., sponge and cotton. So, it is very important but challenging to prepare highly and fast-swelling super absorbents. A reliable, efficient and low-cost technique for removing heavy metal ions from waste water is the adsorption using bio-adsorbents obtained from biological materials, such as polysaccharides-based hydrogels super absorbents. In this study, novel multi-functional super absorbent composites type semi-interpenetrating polymer networks (Semi-IPNs) were prepared via graft polymerization of acrylamide onto chitosan backbone in presence of gelatin, CTS-g-PAAm/Ge, using potassium persulfate and N,N’ -methylenebisacrylamide as initiator and cross linker, respectively. These hydrogels were also partially hydrolyzed to achieve superabsorbents with ampholytic properties and uppermost swelling capacity. The formation of the grafted network was evidenced by Fourier Transform Infrared Spectroscopy (ATR-FTIR) and thermo gravimetric Analysis (TGA). The porous structures were observed by Scanning Electron Microscope (SEM). From TGA analysis, it was concluded that the incorporation of the Ge in the CTS-g-PAAm network has marginally affected its thermal stability. The effect of gelatin content on the swelling capacities of these super absorbent composites was examined in various media (distilled water, saline and pH-solutions).The water absorbency was enhanced by adding Ge in the network, where the optimum value was reached at 2 wt. % of Ge. Their hydrolysis has not only greatly optimized their absorption capacity but also improved the swelling kinetic. These materials have also showed reswelling ability. We believe that these super-absorbing materials would be very effective for the adsorption of harmful metal ions from waste water.

Keywords: chitosan, gelatin, superabsorbent, water absorbency

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Authors: Xiaogang Li, Jieqiong Miao

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As for the problem of the grey forecasting model prediction accuracy is low, an improved grey prediction model is put forward. Firstly, use trigonometric function transform the original data sequence in order to improve the smoothness of data , this model called SGM( smoothness of grey prediction model), then combine the improved grey model with support vector machine , and put forward the grey support vector machine model (SGM - SVM).Before the establishment of the model, we use trigonometric functions and accumulation generation operation preprocessing data in order to enhance the smoothness of the data and weaken the randomness of the data, then use support vector machine (SVM) to establish a prediction model for pre-processed data and select model parameters using genetic algorithms to obtain the optimum value of the global search. Finally, restore data through the "regressive generate" operation to get forecasting data. In order to prove that the SGM-SVM model is superior to other models, we select the battery life data from calce. The presented model is used to predict life of battery and the predicted result was compared with that of grey model and support vector machines．For a more intuitive comparison of the three models, this paper presents root mean square error of this three different models .The results show that the effect of grey support vector machine (SGM-SVM) to predict life is optimal, and the root mean square error is only 3.18%. Keywords: grey forecasting model, trigonometric function, support vector machine, genetic algorithms, root mean square error

Keywords: Grey prediction model, trigonometric functions, support vector machines, genetic algorithms, root mean square error

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Authors: Won Il Jung, Gene Lee, Luis Rabelo

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Since many weapon systems are getting more complex and diverse, various problems occur in terms of the acquisition cost, time, and performance limitation. As a matter of fact, the experiment execution in real world is costly, dangerous, and time-consuming to obtain Required Operational Characteristics (ROC) for a new weapon acquisition although enhancing the fidelity of experiment results. Also, until presently most of the research contained a large amount of assumptions so therefore a bias is present in the experiment results. At this moment, the new methodology is proposed to solve these problems without a variety of assumptions. ROC of the new weapon system is developed through the new methodology, which is a way to analyze big data generated by simulating various scenarios based on virtual and constructive models which are involving 6 Degrees of Freedom (6DoF). The new methodology enables us to identify unbiased ROC on new weapons by reducing assumptions and provide support in terms of the optimal weapon systems acquisition.

Keywords: big data, required operational characteristics (ROC), virtual and constructive models, weapon acquisition

Procedia PDF Downloads 292

Authors: Umm E. Aimen Minhas, Sameen Tahira, Haneen Kamran, Syed Saad Ul Hassan, Haris Bin Khalid, Hadia Nadeem, Ahmed Sanan

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In coronary artery bypass grafting (CABG) patients, vasodilators play a key role in optimizing graft patency by preventing vasospasm and enhancing blood flow. Limited literature is available comparing the effectiveness of various vasodilators on IMA flow in CABG patients. Thus, the rationale for conducting this Network-meta-analysis is to identify the most efficacious vasodilator for increasing IMA flow in CABG patients. A systematic search of 3 databases yielded 357 studies, with 19 meeting inclusion criteria (18 RCTs, 1 observational study). The primary outcome was IMA flow, with secondary outcomes including central venous pressure (CVP) and mean arterial pressure (MAP). Analyses were conducted on an intention-to-treat basis using the net meta package in R. A frequentist random-effects model was employed, with consistency assessed via node-splitting and heterogeneity evaluated. The risk of bias was assessed using RoB 2 and ROBINS-I tools. Out of 92 possible pairwise comparisons, 11 were direct, and 3 included both direct and indirect evidence. Network ranking identified milrinone as the most effective vasodilator for improving IMA flow (SMD: 1.12; 95% CI: 0.36–1.87), followed by nitroglycerin (SMD: 0.51; 95% CI: 0.01–1.00). On the contrary, CO₂ insufflation significantly reduced IMA flow (SMD: -1.17; 95% CI: -2.28 to -0.06). Dobutamine significantly increased CVP, favoring placebo, with no notable differences in MAP across interventions. This analysis positions milrinone as a potentially superior agent for enhancing IMA flow in CABG, warranting its consideration as a first-line therapy. However, moderate to high heterogeneity and limited direct evidence highlight the need for more head-to-head trials.

Keywords: IMA flow, vasodilators, CABG, milrinone, cardiac outcomes

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Authors: Abdulah Fajar

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Electronic Procurement System has been implemented at government institution in Indonesia. This system has been developed centrally at Institution of National Procurement Policy (LKPP) and implemented autonomously at either local or national government institution. The lack of competency at many institution on Information Technology Management arise several major problems. The main concern of LKPP to local administrator is assured that the system is running normally and always be able to serve the needs of its users. Monitoring system has been identified as the one of solution to prevent the problems appeared. Monitoring system is developed using Simple Network Management Protocol (SNMP) and implemented at LKPP. There are two modules; Main Dashboard and Local Agent. Main Dashboard is intended for LKPP and Local Agent is intended to implement at local autonomous e-procurement system (LPSE). There are several resources that must be monitored such as computation, memory and network traffic. Agile paradigm is applied to this project to assure user and system requirement is met. The length of project is the one of reason why agile paradigm has been chosen. The system has been successfully delivered to LKPP.

Keywords: procurement system, SNMP, LKPP, LPSE

Procedia PDF Downloads 429

Authors: R. Rajabpour, N. Talebbeydokhti, M. H. Ahmadi

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Carefully scheduling the operations of pumps can be resulted to significant energy savings. Schedules can be defined either implicit, in terms of other elements of the network such as tank levels, or explicit by specifying the time during which each pump is on/off. In this study, two new explicit representations based on time-controlled triggers were analyzed, where the maximum number of pump switches was established beforehand, and the schedule may contain fewer switches than the maximum. The optimal operation of pumping stations was determined using a Jumping Particle Swarm Optimization (JPSO) algorithm to achieve the minimum energy cost. The model integrates JPSO optimizer and EPANET hydraulic network solver. The optimal pump operation schedule of VanZyl water distribution system was determined using the proposed model and compared with those from Genetic and Ant Colony algorithms. The results indicate that the proposed model utilizing the JPSP algorithm outperformed the others and is a versatile management model for the operation of real-world water distribution system.

Keywords: JPSO, operation, optimization, water distribution system

Procedia PDF Downloads 251

Authors: Sofia Dokuka, Liz Lockhart, Alex Furman

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Organizational hierarchy, traditionally composed of individual contributors, middle management, and executives, is enhanced by the understanding of informal social roles. These roles, identified with organizational network analysis (ONA), might have an important effect on organizational functioning. In this paper, we identify three social roles – influencers, bridges, and soloists, and provide empirical analysis based on real-world organizational networks. Influencers are employees with broad networks and whose contacts also have rich networks. Influence is calculated using PageRank, initially proposed for measuring website importance, but now applied in various network settings, including social networks. Influencers, having high PageRank, become key players in shaping opinions and behaviors within an organization. Bridges serve as links between loosely connected groups within the organization. Bridges are identified using betweenness and Burt’s constraint. Betweenness quantifies a node's control over information flows by evaluating its role in the control over the shortest paths within the network. Burt's constraint measures the extent of interconnection among an individual's contacts. A high constraint value suggests fewer structural holes and lesser control over information flows, whereas a low value suggests the contrary. Soloists are individuals with fewer than 5 stable social contacts, potentially facing challenges due to reduced social interaction and hypothetical lack of feedback and communication. We considered social roles in the analysis of real-world organizations (N=1,060). Based on data from digital traces (Slack, corporate email and calendar) we reconstructed an organizational communication network and identified influencers, bridges and soloists. We also collected employee engagement data through an online survey. Among the top-5% of influencers, 10% are members of the Executive Team. 56% of the Executive Team members are part of the top influencers group. The same proportion of top influencers (10%) is individual contributors, accounting for just 0.6% of all individual contributors in the company. The majority of influencers (80%) are at the middle management level. Out of all middle managers, 19% hold the role of influencers. However, individual contributors represent a small proportion of influencers, and having information about these individuals who hold influential roles can be crucial for management in identifying high-potential talents. Among the bridges, 4% are members of the Executive Team, 16% are individual contributors, and 80% are middle management. Predominantly middle management acts as a bridge. Bridge positions of some members of the executive team might indicate potential micromanagement on the leader's part. Recognizing the individuals serving as bridges in an organization uncovers potential communication problems. The majority of soloists are individual contributors (96%), and 4% of soloists are from middle management. These managers might face communication difficulties. We found an association between being an influencer and attitude toward a company's direction. There is a statistically significant 20% higher perception that the company is headed in the right direction among influencers compared to non-influencers (p < 0.05, Mann-Whitney test). Taken together, we demonstrate that considering social roles in the company might indicate both positive and negative aspects of organizational functioning that should be considered in data-driven decision-making.

Keywords: organizational network analysis, social roles, influencer, bridge, soloist

Procedia PDF Downloads 111

Authors: Jing-Gang Xie

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The research, in this case, considers the integration of the Quantum Field Theory and the General Relativity Theory. As two successful models in explaining behaviors of particles, they are incompatible since they work at different masses and scales of energy, with the evidence that regards the description of black holes and universe formation. It is so considering previous efforts in merging the two theories, including the likes of the String Theory, Quantum Gravity models, and others. In a bid to prove an actionable experiment, the paper’s approach starts with the derivations of the existing theories at present. It goes on to test the derivations by applying the same initial assumptions, coupled with several deviations. The resulting equations get similar results to those of classical Newton model, quantum mechanics, and general relativity as long as conditions are normal. However, outcomes are different when conditions are extreme, specifically with no breakdowns even for less than Schwarzschild radius, or at Planck length cases. Even so, it proves the possibilities of integrating the two theories.

Keywords: general relativity theory, particles, photons, Quantum Gravity Model, gravitational frequency shift

Procedia PDF Downloads 360

Authors: Lyamine Guezouli, Kamel Barka, Zineb Seghir

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Wireless sensor and actor networks (WSANs) present a research challenge for different practice areas. Researchers are trying to optimize the use of such networks through their research work. This optimization is done on certain criteria, such as improving energy efficiency, exploiting node heterogeneity, self-adaptability and self-configuration. In this article, we present our proposal for BIFSA (Biologically-Inspired Framework for Wireless Sensor and Actor networks). Indeed, BIFSA is a middleware that addresses the key issues of wireless sensor and actor networks. BIFSA consists of two types of agents: sensor agents (SA) that operate at the sensor level to collect and transport data to actors and actor agents (AA) that operate at the actor level to transport data to base stations. Once the sensor agent arrives at the actor, it becomes an actor agent, which can exploit the resources of the actors and vice versa. BIFSA allows agents to evolve their genetic structures and adapt to the current network conditions. The simulation results show that BIFSA allows the agents to make better use of all the resources available in each type of node, which improves the performance of the network.

Keywords: wireless sensor and actor networks, self-management, genetic algorithm, agent.

Procedia PDF Downloads 96

Authors: Long Cheng, Tong He, Iraj Mantegh, Wen-Fang Xie

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Path planning is essential for UAVs (Unmanned Aerial Vehicle) with autonomous navigation in unknown environments. In this paper, an adaptive probabilistic sampling algorithm is proposed for the GPS-denied environment, which can be utilized for autonomous navigation system of multiple UAVs in a dynamically-changing structured environment. This method can be used for Unmanned Aircraft Systems Traffic Management (UTM) solutions and in autonomous urban aerial mobility, where a number of platforms are expected to share the airspace. A path network is initially built off line based on available environment map, and on-board sensors systems on the flying UAVs are used for continuous situational awareness and to inform the changes in the path network. Simulation results based on MATLAB and Gazebo in different scenarios and algorithms performance measurement show the high efficiency and accuracy of the proposed technique in unknown environments.

Keywords: path planning, adaptive probabilistic sampling, obstacle avoidance, multiple unmanned aerial vehicles, unknown environments

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Authors: Y. Bhatt, N. Ghosh, N. Tiwari

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Acreage response function are modeled taking account of expected harvest prices, weather related variables and other non-price variables allowing for partial adjustment possibility. At the outset, based on the literature on price expectation formation, we explored suitable formulations for estimating the farmer’s expected prices. Assuming that farmers form expectations rationally, the prices of food and biofuel crops are modeled using time-series methods for possible ARCH/GARCH effects to account for volatility. The prices projected on the basis of the models are then inserted to proxy for the expected prices in the acreage response functions. Food crop acreages in different growing states are found sensitive to their prices relative to those of one or more of the biofuel crops considered. The required percentage improvement in food crop yields is worked to offset the acreage loss.

Keywords: acreage response function, biofuel, food security, sustainable development

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Authors: Kidist Mesfin Nguse

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Ethiopia is the second most densely populated nation in Africa, and about 121 million people as the 2022 Ethiopia population live report recorded. In recent years, the Ethiopian government (GOE) has been gradually growing its road network. With 138,127 kilometers (85,825 miles) of all-weather roads as of the end of 2018–19, Ethiopia possessed just 39% of the nation's necessary road network and lacked a well-organized system. The Ethiopian urban population report recorded that about 21% of the population lives in urban areas, and the high population, coupled with growth in various infrastructures, has led to the migration of the workforce from rural areas to cities across the country. In main roads, the heterogeneous traffic flow with various operational features makes it more unfavorable, causing frequent congestion in the stretch of road. The Level of Service (LOS), a qualitative measure of traffic, is categorized based on the operating conditions in the traffic stream. Determining the capacity and LOS for this city is very crucial as this affects the planning and design of traffic systems and their operation, and the allocation of route selection for infrastructure building projects to provide for a considerably good level of service.

Keywords: capacity, level of service, traffic volume, free flow speed

Procedia PDF Downloads 54

Authors: Medha Basu, Kumardeb Banerjee, Dipak Ghosh

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After the massive blow of the COVID-19 pandemic, several health hazards have been reported all over the world. Serious cases of Major Depressive Disorder (MDD) are seen to be common in about 15% of the global population, making depression one of the leading mental health diseases, as reported by the World Health Organization. Various psychological and pharmacological treatment techniques are regularly being reported. Music, a globally accepted mode of entertainment, is often used as a therapeutic measure to treat various health conditions. We have tried to understand how Indian Classical Music can affect the overall well-being of the human brain. A case study has been reported here, where a Flute-rendition has been chosen from a detailed audience response survey, and the effects of that clip on human brain conditions have been studied from both psychological and neural perspectives. Taking help from internationally-accepted depression-rating scales, two questionnaires have been designed to understand both the prolonged and immediate effect of music on various emotional states of human lives. Thereafter, from EEG experiments on 5 participants using the same clip, the parameter ‘ALAY’, alpha frontal asymmetry (alpha power difference of right and left frontal hemispheres), has been calculated. Works of Richard Davidson show that an increase in the ‘ALAY’ value indicates a decrease in depressive symptoms. Using the non-linear technique of MFDFA on EEG analysis, we have also calculated frontal asymmetry using the complexity values of alpha-waves in both hemispheres. The results show a positive correlation between both the psychological survey and the EEG findings, revealing the prominent role of music on the human brain, leading to a decrease in mental unrest and an increase in overall well-being. In this study, we plan to propose the scientific foundation of music therapy, especially from a neurocognition perspective, with appropriate neural bio-markers to understand the positive and remedial effects of music on the human brain.

Keywords: music therapy, EEG, psychological survey, frontal alpha asymmetry, wellbeing

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Authors: Meshal M. Abdullah, Rusty A. Feagin, Layla Musawi

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When humans mismanage arid landscapes, soil erosion can become a primary mechanism that leads to desertification. This study focuses on applying soil erosion models to a disturbed landscape in Umm Nigga, Kuwait, and identifying its predicted change under restoration plans, The northern portion of Umm Nigga, containing both coastal and desert ecosystems, falls within the boundaries of the Demilitarized Zone (DMZ) adjacent to Iraq, and has been fenced off to restrict public access since 1994. The central objective of this project was to utilize GIS and remote sensing to compare the MPSIAC (Modified Pacific South West Inter Agency Committee), EMP (Erosion Potential Method), and USLE (Universal Soil Loss Equation) soil erosion models and determine their applicability for arid regions such as Kuwait. Spatial analysis was used to develop the necessary datasets for factors such as soil characteristics, vegetation cover, runoff, climate, and topography. Results showed that the MPSIAC and EMP models produced a similar spatial distribution of erosion, though the MPSIAC had more variability. For the MPSIAC model, approximately 45% of the land surface ranged from moderate to high soil loss, while 35% ranged from moderate to high for the EMP model. The USLE model had contrasting results and a different spatial distribution of the soil loss, with 25% of area ranging from moderate to high erosion, and 75% ranging from low to very low. We concluded that MPSIAC and EMP were the most suitable models for arid regions in general, with the MPSIAC model best. We then applied the MPSIAC model to identify the amount of soil loss between coastal and desert areas, and fenced and unfenced sites. In the desert area, soil loss was different between fenced and unfenced sites. In these desert fenced sites, 88% of the surface was covered with vegetation and soil loss was very low, while at the desert unfenced sites it was 3% and correspondingly higher. In the coastal areas, the amount of soil loss was nearly similar between fenced and unfenced sites. These results implied that vegetation cover played an important role in reducing soil erosion, and that fencing is much more important in the desert ecosystems to protect against overgrazing. When applying the MPSIAC model predictively, we found that vegetation cover could be increased from 3% to 37% in unfenced areas, and soil erosion could then decrease by 39%. We conclude that the MPSIAC model is best to predict soil erosion for arid regions such as Kuwait.

Keywords: soil erosion, GIS, modified pacific South west inter agency committee model (MPSIAC), erosion potential method (EMP), Universal soil loss equation (USLE)

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Authors: Rakesh Namdeti

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The liquid waste-wastewater- is essentially the water supply of the community after it has been used in a variety of applications. In recent years, heavy metal concentrations, besides other pollutants, have increased to reach dangerous levels for the living environment in many regions. Among the heavy metals, Lead has the most damaging effects on human health. It can enter the human body through the uptake of food (65%), water (20%), and air (15%). In this background, certain low-cost and easily available biosorbent was used and reported in this study. The scope of the present study is to remove Lead from its aqueous solution using Olea EuropaeaResin as biosorbent. The results showed that the biosorption capacity of Olea EuropaeaResin biosorbent was more for Lead removal. The Langmuir, Freundlich, Tempkin, and Dubinin-Radushkevich (D-R) models were used to describe the biosorption equilibrium of Lead Olea EuropaeaResin biosorbent, and the biosorption followed the Langmuir isotherm. The kinetic models showed that the pseudo-second-order rate expression was found to represent well the biosorption data for the biosorbent.

Keywords: novel biosorbent, central composite design, Lead, isotherms, kinetics

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Authors: L. J. de Bessa Neto, M. R. B. Guerra Vale, F. K. O. M. Varella Guerra

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In recent years, solar energy has established itself as one of the main sources of renewable energy, gaining a large space in electricity generation around the world. However, due to the low performance of photovoltaic panels, technologies need to be sought to maximize the production of electricity. In this regard, the present study aims to develop a prototype of solar tracker for didactics applications, controlled with the Arduino® platform, that enables the movement of photovoltaic plates in relation to the sun positions throughout the day through an electromechanical system, optimizing, thus, the efficiency of solar photovoltaic generation and improvements for the photovoltaic effect. The solar tracking technology developed in this work was presented of the shape oral and practical in two middle schools in the municipality of Mossoró/RN, being one of the public network and other of the private network, always keeping the average age of the students, in the case, around 16 years, contemplating an average of 60 students in each of the visits. Thus, it is concluded that the present study contributed substantially to the dissemination of knowledge concerning the photovoltaic solar generation, as well as the study of solar trackers, thus arousing the interest and curiosity of the students regarding the thematic approached.

Keywords: alternative energy, solar tracker, energy efficiency, photovoltaic panels

Procedia PDF Downloads 153

Authors: Navneet Kaur, Amarpreet Singh

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In Vehicular Adhoc Networks, Data Dissemination is a challenging task. There are number of techniques, types and protocols available for disseminating the data but in order to preserve limited bandwidth and to disseminate maximum data over networks makes it more challenging. There are broadcasting, multicasting and geocasting based protocols. Multicasting based protocols are found to be best for conserving the bandwidth. One such protocol named BEAM exists that improves the performance of Vehicular Adhoc Networks by reducing the number of in-network message transactions and thereby efficiently utilizing the bandwidth during an emergency situation. But this protocol may result in multicar chain collision as there was no V2V communication. So, this paper proposes a new protocol named Enhanced Bandwidth Efficient Cluster Based Multicasting Protocol (EBECM) that will overcome the limitations of existing BEAM protocol. And Simulation results will show the improved performance of EBECM in terms of Routing overhead, throughput and PDR when compared with BEAM protocol.

Keywords: BEAM, data dissemination, emergency situation, vehicular adhoc network

Procedia PDF Downloads 354

Authors: Matevž Breška, Iztok Peruš, Vlado Stankovski

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Systematic overview of existing Ground Motion Prediction Equations (GMPEs) has been published by Douglas. The number of earthquake recordings that have been used for fitting these equations has increased in the past decades. The current PF-L database contains 3550 recordings. Since the GMPEs frequently model the peak ground acceleration (PGA) the goal of the present study was to refit a selection of 44 of the existing equation models for PGA in light of the latest data. The algorithm Levenberg-Marquardt was used for fitting the coefficients of the equations and the results are evaluated both quantitatively by presenting the root mean squared error (RMSE) and qualitatively by drawing graphs of the five best fitted equations. The RMSE was found to be as low as 0.08 for the best equation models. The newly estimated coefficients vary from the values published in the original works.

Keywords: Ground Motion Prediction Equations, Levenberg-Marquardt algorithm, refitting PF-L database, peak ground acceleration

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Authors: J. Bartus, J. Odrobinak

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The paper presents a nonlinear analysis 3D model of composite steel and concrete beams with web openings using the Finite Element Method (FEM). The core of the study is the introduction of basic modeling techniques comprehending the description of material behavior, appropriate elements selection, and recommendations for overcoming problems with convergence. Results from various finite element models are compared in the study. The main objective is to observe the concrete failure mechanism and its influence on the structural performance of numerical models of the beams at particular load stages. The bearing capacity of beams, corresponding deformations, stresses, strains, and fracture patterns were determined. The results show how load-bearing elements consisting of concrete parts can be analyzed using FEM software with various options to create the most suitable numerical model. The paper demonstrates the versatility of Ansys software usage for structural simulations.

Keywords: Ansys, concrete, modeling, steel

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Authors: Yu Lu

Abstract:

Fixed point theory is a basic tool for the study of the existence of Nash equilibria in game theory. This paper presents a significant generalization of the Veinott-Zhou fixed point theorem for increasing correspondences, which serves as an essential framework for investigating the existence of Nash equilibria in supermodular and quasisupermodular games. To establish our proofs, we explore different conceptions of multivalued increasingness and provide comprehensive results concerning the existence of the largest/least fixed point. We provide two distinct approaches to the proof, each offering unique insights and advantages. These advancements not only extend the applicability of the Veinott-Zhou theorem to a broader range of economic scenarios but also enhance the theoretical framework for analyzing equilibrium behavior in complex game-theoretic models. Our findings pave the way for future research in the development of more sophisticated models of economic behavior and strategic interaction.

Keywords: fixed-point, Tarski’s fixed-point theorem, Nash equilibrium, supermodular game

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Authors: Jihad S. Daba, J. P. Dubois

Abstract:

Understanding the statistics of non-isotropic scattering multipath channels that fade randomly with respect to time, frequency, and space in a mobile environment is very crucial for the accurate detection of received signals in wireless and cellular communication systems. In this paper, we derive stochastic models for the probability density function (PDF) of the shift in the carrier frequency caused by the Doppler Effect on the received illuminating signal in the presence of a dominant line of sight. Our derivation is based on a generalized Clarke’s and a two-wave partially developed scattering models, where the statistical distribution of the frequency shift is shown to be consistent with the power spectral density of the Doppler shifted signal.

Keywords: Doppler shift, filtered Poisson process, generalized Clark’s model, non-isotropic scattering, partially developed scattering, Rician distribution

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Authors: Abdolghani Ebrahimi, Diego Klabjan, Chenxi Ge, Daniela Ladner, Parker Stride

Abstract:

In this work, we use machine learning and novel data analysis techniques to predict the one-year mortality of cirrhotic patients. Data from 2,322 patients with liver cirrhosis are collected at a single medical center. Different machine learning models are applied to predict one-year mortality. A comprehensive feature space including demographic information, comorbidity, clinical procedure and laboratory tests is being analyzed. A temporal pattern mining technic called Frequent Subgraph Mining (FSM) is being used. Model for End-stage liver disease (MELD) prediction of mortality is used as a comparator. All of our models statistically significantly outperform the MELD-score model and show an average 10% improvement of the area under the curve (AUC). The FSM technic itself does not improve the model significantly, but FSM, together with a machine learning technique called an ensemble, further improves the model performance. With the abundance of data available in healthcare through electronic health records (EHR), existing predictive models can be refined to identify and treat patients at risk for higher mortality. However, due to the sparsity of the temporal information needed by FSM, the FSM model does not yield significant improvements. To the best of our knowledge, this is the first work to apply modern machine learning algorithms and data analysis methods on predicting one-year mortality of cirrhotic patients and builds a model that predicts one-year mortality significantly more accurate than the MELD score. We have also tested the potential of FSM and provided a new perspective of the importance of clinical features.

Keywords: machine learning, liver cirrhosis, subgraph mining, supervised learning

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Authors: Breanna Macumber, Victor A. Huayamave, Emir A. Vela, Wangdo Kim, Tamara T. Chamber, Esteban Centeno

Abstract:

Spina bifida is a type of neural tube defect that affects the nervous system and can lead to problems such as total leg paralysis. Treatment requires physical therapy and rehabilitation. Robotic exoskeletons have been used for rehabilitation to train muscle movement and assist in injury recovery; however, current models focus on the adult populations and not on the infant population. The proposed framework aims to couple a musculoskeletal infant model with a robotic exoskeleton using vacuum-powered artificial muscles to provide rehabilitation to infants affected by spina bifida. The study that drove the input values for the robotic exoskeleton used motion capture technology to collect data from the spontaneous kicking movement of a 2.4-month-old infant lying supine. OpenSim was used to develop the musculoskeletal model, and Inverse kinematics was used to estimate hip joint angles. A total of 4 kicks (A, B, C, D) were selected, and the selection was based on range, transient response, and stable response. Kicks had at least 5° of range of motion with a smooth transient response and a stable period. The robotic exoskeleton used a Vacuum-Powered Artificial Muscle (VPAM) the structure comprised of cells that were clipped in a collapsed state and unclipped when desired to simulate infant’s age. The artificial muscle works with vacuum pressure. When air is removed, the muscle contracts and when air is added, the muscle relaxes. Bench testing was performed using a 6-month-old infant mannequin. The previously developed exoskeleton worked really well with controlled ranges of motion and frequencies, which are typical of rehabilitation protocols for infants suffering with spina bifida. However, the random kicking motion in this study contained high frequency kicks and was not able to accurately replicate all the investigated kicks. Kick 'A' had a greater error when compared to the other kicks. This study has the potential to advance the infant rehabilitation field.

Keywords: musculoskeletal modeling, soft robotics, rehabilitation, pediatrics

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Authors: Analise Borg, Paul Micallef

Abstract:

Over the past few years, the online multimedia collection has grown at a fast pace. Several companies showed interest to study the different ways to organize the amount of audio information without the need of human intervention to generate metadata. In the past few years, many applications have emerged on the market which are capable of identifying a piece of music in a short time. Different audio effects and degradation make it much harder to identify the unknown piece. In this paper, an audio fingerprinting system which makes use of a non-parametric based algorithm is presented. Parametric analysis is also performed using Gaussian Mixture Models (GMMs). The feature extraction methods employed are the Mel Spectrum Coefficients and the MPEG-7 basic descriptors. Bin numbers replaced the extracted feature coefficients during the non-parametric modelling. The results show that non-parametric analysis offer potential results as the ones mentioned in the literature.

Keywords: audio fingerprinting, mapping algorithm, Gaussian Mixture Models, MFCC, MPEG-7

Procedia PDF Downloads 425