Search results for: time series data

Authors: Daniil Karzanov

Abstract:

This paper studies the effect of quarterly earnings reports on the stock price. The profitability of the stock is modeled by geometric Brownian diffusion and the Constant Elasticity of Variance model. We fit several variations of stochastic differential equations to the pre-and after-report period using the Maximum Likelihood Estimation and Grid Search of parameters method. By examining the change in the model parameters after reports’ publication, the study reveals that the reports have enough evidence to be a structural breakpoint, meaning that all the forecast models exploited are not applicable for forecasting and should be refitted shortly.

Keywords: stock market, earnings reports, financial time series, structural breaks, stochastic differential equations

Procedia PDF Downloads 204

Authors: Luis Andrey Fajardo Fajardo

Abstract:

We are immersed in complex systems. The human brain, the galaxies, the snowflakes are examples of complex systems. An area of interest in Complex systems is the chaos theory. This revolutionary field of science presents different ways of study than determinism and reductionism. Here is where in junction with the Nonlinear DSP, chaos theory offer valuable techniques that establish a link between time series and complex theory in terms of complex networks, so that, the study of signals can be explored from the graph theory. Recently, some people had purposed a method to transform time series in graphs, but no one had developed a suitable implementation in Python with signals extracted from Chaotic Systems or Complex systems. That’s why the implementation in Python of an existing method to transform one dimensional chaotic signals from time domain to graph domain and some measures that may reveal information not extracted in the time domain is proposed.

Keywords: Python, complex systems, graph theory, dynamical systems

Procedia PDF Downloads 508

Authors: A. Djahbar, E. Bounadja, A. Zegaoui, H. Allouache

Abstract:

In this paper, vector control of a series-connected two-machine drive system fed by a single inverter (CSI/VSI) is presented. The two stator windings of both machines are connected in series while the rotors may be connected to different loads, are called series-connected two-machine drive. Appropriate phase transposition is introduced while connecting the series stator winding to obtain decoupled control the two-machines. The dynamic decoupling of each machine from the group is obtained using the vector control algorithm. The independent control is demonstrated by analyzing the characteristics of torque and speed of each machine obtained via simulation under vector control scheme. The viability of the control techniques is proved using analytically and simulation approach.

Keywords: drives, inverter, multi-phase induction machine, vector control

Procedia PDF Downloads 478

Authors: André Rafael Ferreira, Laurentina Vareiro, Raquel Mendes

Abstract:

This study’s main objective is to explore residents’ perceptions of film-induced tourism and the impacts of filmmaking on the development of a destination. Specifically, the research examines resident´s perceptions of the social, economic, and environmental impacts on a Portuguese municipality (Arcos de Valdevez) given its feature in a popular Portuguese television series. Data is collected by means of an Internet survey, in which resident´s perceptions of the impacts of filmmaking are solicited. Residents generally agree that the recording and exhibition of the television series is important to the municipality, and contributes to the increased number of tourists. Given that residents consider that the positive impacts are more significant than the negative impacts, they supported the recording of another television series in the same municipality. Considering that destination managers and tourism development authorities aim to plan for optimal tourism development, and at the same time wish to minimize the negative impacts of this development on the local communities, monitoring residents’ opinions of perceived impacts is a good way of incorporating their reaction into tourism planning and development. The results of this research may provide useful information in this sense.

Keywords: film-induced tourism, residents’ perceptions, tourism development, tourism impacts

Procedia PDF Downloads 452

Authors: Vinay C. Doranalu, Amba Shetty

Abstract:

In recent days due to climate change, there is a large variation in spatial distribution of daily rainfall within a small region. Rainfall is one of the main end climatic variables which affect spatio-temporal patterns of water availability. The real task postured by the change in climate is identification, estimation and understanding the uncertainty of rainfall. This study intended to analyze the spatial variations and temporal trends of daily precipitation using high resolution (0.25º x 0.25º) gridded data of Indian Meteorological Department (IMD). For the study, 38 grid points were selected in the study area and analyzed for daily precipitation time series (113 years) over the period 1901-2013. Grid points were divided into two zones based on the elevation and situated location of grid points: Low Land (exposed to sea and low elevated area/ coastal region) and High Land (Interior from sea and high elevated area/western Ghats). Time series were applied to examine the spatial analysis and temporal trends in each grid points by non-parametric Mann-Kendall test and Theil-Sen estimator to perceive the nature of trend and magnitude of slope in trend of rainfall. Pettit-Mann-Whitney test is applied to detect the most probable change point in trends of the time period. Results have revealed remarkable monotonic trend in each grid for daily precipitation of the time series. In general, by the regional cluster analysis found that increasing precipitation trend in shoreline region and decreasing trend in Western Ghats from recent years. Spatial distribution of rainfall can be partly explained by heterogeneity in temporal trends of rainfall by change point analysis. The Mann-Kendall test shows significant variation as weaker rainfall towards the rainfall distribution over eastern parts of the Western Ghats region of Karnataka.

Keywords: change point analysis, coastal region India, gridded rainfall data, non-parametric

Procedia PDF Downloads 291

Authors: L. Mallesha, P. Mallu, B. Veeresh

Abstract:

In the present study, 2, 6-diflurobenzohydrazide and 4-fluorophenylisothiocyanate were used as the starting materials to synthesize 5-phenyl-N3-(4-fluorophenyl)-4H-1, 2, 4-triazole-3, 4-diamine. Further, compound 5-phenyl-N3-(4-fluorophenyl)-4H-1, 2, 4-triazole-3,4-diamine reacted with fluoro substituted benzaldehydes to yield a series of Schiff bases. All the final compounds were characterized using IR, 1H NMR, 13C NMR, MS and elemental analyses. New compounds were evaluated for their antiproliferative effect using the MTT assay method against four human cancer cell lines (K562, COLO-205, MDA-MB231, and IMR-32) for the time period of 24 h. Among the series, few compounds showed good activity on all cell lines, whereas the other compounds in the series exhibited moderate activity.

Keywords: Schiff bases, MTT assay, antiproliferative activity, human cancer cell lines, 1, 2, 4-triazoles

Procedia PDF Downloads 371

Authors: Shunsuke Aoki, Taku Ri, Tatsuya Yamazaki

Abstract:

These days, along with the development of e-sports, video games as a competitive sport is attracting attention. But, in many cases, action in the screen does not match the real motion of operation. Inclusiveness of player motion is needed to increase reality and excitement for sports games. Therefore, in this study, the authors propose a method to recognize player motion by using the motion capture technology and develop a virtual basketball game. The virtual basketball game consists of a screen with nine targets, players, depth sensors, and no ball. The players pretend a two-handed basketball shot without a ball aiming at one of the nine targets on the screen. Time-series data of three-dimensional coordinates of player joints are captured by the depth sensor. 20 joints data are measured for each player to estimate the shooting motion in real-time. The trajectory of the thrown virtual ball is calculated based on the time-series data and hitting on the target is judged as success or failure. The virtual basketball game can be played by 2 to 4 players as a competitive game among the players. The developed game was exhibited to the public for evaluation on the authors' university open campus days. 339 visitors participated in the exhibition and enjoyed the virtual basketball game over the two days. A questionnaire survey on the developed game was conducted for the visitors who experienced the game. As a result of the survey, about 97.3% of the players found the game interesting regardless of whether they had experienced actual basketball before or not. In addition, it is found that women are easy to comfort for shooting motion. The virtual game with motion capture technology has the potential to become a universal entertainment between e-sports and actual sports.

Keywords: basketball, motion capture, questionnaire survey, video ga

Procedia PDF Downloads 126

Authors: Gaurav Kumar Sinha

Abstract:

The volatility of the oil market, influenced by geopolitical, economic, and environmental factors, presents significant challenges for stakeholders in predicting trends and demand. This article explores the application of artificial intelligence (AI) in developing robust forecasting models to anticipate changes in the oil market more accurately. We delve into various AI techniques, including machine learning, deep learning, and time series analysis, that have been adapted to analyze historical data and current market conditions to forecast future trends. The study evaluates the effectiveness of these models in capturing complex patterns and dependencies in market data, which traditional forecasting methods often miss. Additionally, the paper discusses the integration of external variables such as political events, economic policies, and technological advancements that influence oil prices and demand. By leveraging AI, stakeholders can achieve a more nuanced understanding of market dynamics, enabling better strategic planning and risk management. The article concludes with a discussion on the potential of AI-driven models in enhancing the predictive accuracy of oil market forecasts and their implications for global economic planning and strategic resource allocation.

Keywords: AI forecasting, oil market trends, machine learning, deep learning, time series analysis, predictive analytics, economic factors, geopolitical influence, technological advancements, strategic planning

Procedia PDF Downloads 33

Authors: Hare Krishna Nigam

Abstract:

In this paper, for the first time, (E,q)(C,2) product summability method is introduced and two quite new results on degree of approximation of the function f belonging to Lip (alpha,r)class and W(L(r), xi(t)) class by (E,q)(C,2) product means of Fourier series, has been obtained.

Keywords: Degree of approximation, (E, q)(C, 2) means, Fourier series, Lebesgue integral, Lip (alpha, r)class, W(L(r), xi(t))class of functions

Procedia PDF Downloads 516

Authors: M. T. Islam, S. H. Shakif, R. Hasan, S. H. Kobi

Abstract:

Investigation of rainfall trends is crucial considering climate change, food security, and the economy of a particular region. This research aims to study seasonal and annual precipitation trends and their abrupt changes over time in the south-central climatic zone of Bangladesh using monthly time series data of 50 years (1970-2019). A trend-free pre-whitening method has been employed to make necessary adjustments for autocorrelations in the rainfall data. Trends in rainfall and their intensity have been observed using the non-parametric Mann-Kendall test and Theil-Sen estimator. Significant changes and fluctuation points in the data series have been detected using the sequential Mann-Kendall test at the 95% confidence limit. The study findings show that most of the rainfall stations in the study area have a decreasing precipitation pattern throughout all seasons. The maximum decline in the rainfall intensity has been found for the Tangail station (-8.24 mm/year) during monsoon. Madaripur and Chandpur stations have shown slight positive trends in post-monsoon rainfall. In terms of annual precipitation, a negative rainfall pattern has been identified in each station, with a maximum decrement (-) of 14.48 mm/year at Chandpur. However, all the trends are statistically non-significant within the 95% confidence interval, and their monotonic association with time ranges from very weak to weak. From the sequential Mann-Kendall test, the year of changing points for annual and seasonal downward precipitation trends occur mostly after the 90s for Dhaka and Barishal stations. For Chandpur, the fluctuation points arrive after the mid-70s in most cases.

Keywords: trend analysis, Mann-Kendall test, Theil-Sen estimator, sequential Mann-Kendall test, rainfall trend

Procedia PDF Downloads 77

Authors: Carla Palencia-Aguilar

Abstract:

Calculations of Net Carbon Balance can be obtained by means of Net Biome Productivity (NBP), Net Ecosystem Productivity (NEP), and Net Primary Production (NPP). The latter is an important component of the biosphere carbon cycle and is easily obtained data from MODIS MOD17A3HGF; however, the results are only available yearly. To overcome data availability, bands 33 to 36 from MODIS MYD021KM (obtained on a daily basis) were analyzed and compared with NPP data from the years 2000 to 2021 in 7 sites where surface mining takes place in the Colombian territory. Coal, Gold, Iron, and Limestone were the minerals of interest. Scales and Units as well as thermal anomalies, were considered for net carbon balance per location. The NPP time series from the satellite images were filtered by using two Matlab filters: First order and Discrete Transfer. After filtering the NPP time series, comparing the graph results from the satellite’s image value, and running a linear regression, the results showed R2 from 0,72 to 0,85. To establish comparable units among NPP and bands 33 to 36, the Greenhouse Gas Equivalencies Calculator by EPA was used. The comparison was established in two ways: one by the sum of all the data per point per year and the other by the average of 46 weeks and finding the percentage that the value represented with respect to NPP. The former underestimated the total CO2 emissions. The results also showed that coal and gold mining in the last 22 years had less CO2 emissions than limestone, with an average per year of 143 kton CO2 eq for gold, 152 kton CO2 eq for coal, and 287 kton CO2 eq for iron. Limestone emissions varied from 206 to 441 kton CO2 eq. The maximum emission values from unfiltered data correspond to 165 kton CO2 eq. for gold, 188 kton CO2 eq. for coal, and 310 kton CO2 eq. for iron and limestone, varying from 231 to 490 kton CO2 eq. If the most pollutant limestone site improves its production technology, limestone could count with a maximum of 318 kton CO2 eq emissions per year, a value very similar respect to iron. The importance of gathering data is to establish benchmarks in order to attain 2050’s zero emissions goal.

Keywords: carbon dioxide, NPP, MODIS, MINING

Procedia PDF Downloads 103

Authors: Seyyd Hossein Jafari-Petroudi, Maryam Pirouz

Abstract:

This note is devoted to (k; h)-Jacobsthal sequence as a general term of particular series. More formulas for nth term and sum of the first n terms of series that their general terms are (k; h)-Jacobsthal sequence and (k; h)-Jacobsthal-Petroudi sequence are derived. Finally other properties of these sequences are represented.

Keywords: (k, h)-Jacobsthal sequence, (k, h)-Jacobsthal Petroudisequence, recursive relation, sum

Procedia PDF Downloads 391

Authors: Lia Matchavariani

Abstract:

Water reservoir construction on the rivers flowing into the sea complicates the coast protection, seashore starts to degrade causing coast erosion and disaster on the backdrop of current climate change. The instruments of the impact of a water reservoir on the climate and coastal areas are its contact surface with the atmosphere and the area irrigated with its water or humidified with infiltrated waters. The Black Sea coastline is characterized by the highest ecological vulnerability. The type and intensity of the water reservoir impact are determined by its morphometry, type of regulation, level regime, and geomorphological and geological characteristics of the adjoining area. Studies showed the impact of the water reservoir on the climate, on its comfort parameters is positive if it is located in the zone of insufficient humidity and vice versa, is negative if the water reservoir is found in the zone with abundant humidity. There are many natural and anthropogenic factors determining the peculiarities of the impact of the water reservoir on the climate, which can be assessed with maximum accuracy by the so-called “long series” method, which operates on the meteorological elements (temperature, wind, precipitations, etc.) with the long series formed with the stationary observation data. This is the time series, which consists of two periods with statistically sufficient duration. The first period covers the observations up to the formation of the water reservoir and another period covers the observations accomplished during its operation. If no such data are available, or their series is statistically short, “an analog” method is used. Such an analog water reservoir is selected based on the similarity of the environmental conditions. It must be located within the zone of the designed water reservoir, under similar environmental conditions, and besides, a sufficient number of observations accomplished in its coastal zone.

Keywords: coast-constituent sediment, eustasy, meteorological parameters, seashore degradation, water reservoirs impact

Procedia PDF Downloads 43

Authors: Hajar Hajmohammadi, Paul Pfeffer, Anna De Simoni, Jim Cole, Chris Griffiths, Sally Hull, Benjamin Heydecker

Abstract:

Background: There is strong interest in the relationship between short-term air pollution exposure and human health. Most studies in this field focus on serious health effects such as death or hospital admission, but air pollution exposure affects many people with less severe impacts, such as exacerbations of respiratory conditions. A lack of quantitative analysis and inconsistent findings suggest improved methodology is needed to understand these effectsmore fully. Method: We developed a time series regression model to quantify the relationship between daily NOₓ concentration and Asthma exacerbations requiring oral steroids from primary care settings. Explanatory variables include daily NOₓ concentration measurements extracted from 8 available background and roadside monitoring stations in east London and daily ambient temperature extracted for London City Airport, located in east London. Lags of NOx concentrations up to 21 days (3 weeks) were used in the model. The dependent variable was the daily number of oral steroid courses prescribed for GP registered patients with asthma in east London. A mixed distribution model was then fitted to the significant lags of the regression model. Result: Results of the time series modelling showed a significant relationship between NOₓconcentrations on each day and the number of oral steroid courses prescribed in the following three weeks. In addition, the model using only roadside stations performs better than the model with a mixture of roadside and background stations.

Keywords: air pollution, time series modeling, public health, road transport

Procedia PDF Downloads 142

Authors: Rita U. Onolemhemhen, Saheed L. Bello, Akin P. Iwayemi

Abstract:

The effectiveness of energy demand policy depends on identifying the key drivers of energy demand both in the short-run and the long-run. This paper examines the influence of regional differences on the link between energy demand and other explanatory variables for Nigeria, China and USA using the Vector Error Correction Model (VECM) approach. This study employed annual time series data on energy consumption (ED), real gross domestic product (GDP) per capita (RGDP), real energy prices (P) and urbanization (N) for a thirty-six-year sample period. The utilized time-series data are sourced from World Bank’s World Development Indicators (WDI, 2016) and US Energy Information Administration (EIA). Results from the study, shows that all the independent variables (income, urbanization, and price) substantially affect the long-run energy consumption in Nigeria, USA and China, whereas, income has no significant effect on short-run energy demand in USA and Nigeria. In addition, the long-run effect of urbanization is relatively stronger in China. Urbanization is a key factor in energy demand, it therefore recommended that more attention should be given to the development of rural communities to reduce the inflow of migrants into urban communities which causes the increase in energy demand and energy excesses should be penalized while energy management should be incentivized.

Keywords: economic growth, energy demand, income, real GDP, urbanization, VECM

Procedia PDF Downloads 311

Authors: Tatiana Tunon, Gottfried Pestal

Abstract:

Government agencies responsible for the management of fisheries resources publish many types of grey literature, and these materials are increasingly accessible to the public on agency websites. However, scope and quality vary considerably, and end-users need meta-data about the report series when deciding whether to use the information (e.g. apply the methods, include the results in a systematic review), or when prioritizing materials for archiving (e.g. library holdings, reference databases). A proposed taxonomy for these report series was developed based on a review of 41 report series from 6 government agencies in 4 countries (Canada, New Zealand, Scotland, and United States). Each report series was categorized according to multiple criteria describing peer-review process, content, and purpose. A robust classification tree was then fitted to these descriptions, and the resulting taxonomic groups were used to compare agency output from 4 countries using reports available in their online repositories.

Keywords: classification tree, fisheries, government, grey literature

Procedia PDF Downloads 280

Authors: Atish Bagchi, Siva Chandrasekaran

Abstract:

Background: According to World Bank national accounts data, the estimated global manufacturing value-added output in 2020 was 13.74 trillion USD. These manufacturing processes are monitored, modelled, and controlled by advanced, real-time, computer-based systems, e.g., Industrial IoT, PLC, SCADA, etc. These systems measure and manipulate a set of physical variables, e.g., temperature, pressure, etc. Despite the use of IoT, SCADA etc., in manufacturing, studies suggest that unplanned downtime leads to economic losses of approximately 864 billion USD each year. Therefore, real-time, accurate detection, classification and prediction of machine behaviour are needed to minimise financial losses. Although vast literature exists on time-series data processing using machine learning, the challenges faced by the industries that lead to unplanned downtimes are: The current algorithms do not efficiently handle the high-volume streaming data from industrial IoTsensors and were tested on static and simulated datasets. While the existing algorithms can detect significant 'point' outliers, most do not handle contextual outliers (e.g., values within normal range but happening at an unexpected time of day) or subtle changes in machine behaviour. Machines are revamped periodically as part of planned maintenance programmes, which change the assumptions on which original AI models were created and trained. Aim: This research study aims to deliver a Graph Neural Network(GNN)based hybrid forecasting model that interfaces with the real-time machine control systemand can detect, predict machine behaviour and behavioural changes (anomalies) in real-time. This research will help manufacturing industries and utilities, e.g., water, electricity etc., reduce unplanned downtimes and consequential financial losses. Method: The data stored within a process control system, e.g., Industrial-IoT, Data Historian, is generally sampled during data acquisition from the sensor (source) and whenpersistingin the Data Historian to optimise storage and query performance. The sampling may inadvertently discard values that might contain subtle aspects of behavioural changes in machines. This research proposed a hybrid forecasting and classification model which combines the expressive and extrapolation capability of GNN enhanced with the estimates of entropy and spectral changes in the sampled data and additional temporal contexts to reconstruct the likely temporal trajectory of machine behavioural changes. The proposed real-time model belongs to the Deep Learning category of machine learning and interfaces with the sensors directly or through 'Process Data Historian', SCADA etc., to perform forecasting and classification tasks. Results: The model was interfaced with a Data Historianholding time-series data from 4flow sensors within a water treatment plantfor45 days. The recorded sampling interval for a sensor varied from 10 sec to 30 min. Approximately 65% of the available data was used for training the model, 20% for validation, and the rest for testing. The model identified the anomalies within the water treatment plant and predicted the plant's performance. These results were compared with the data reported by the plant SCADA-Historian system and the official data reported by the plant authorities. The model's accuracy was much higher (20%) than that reported by the SCADA-Historian system and matched the validated results declared by the plant auditors. Conclusions: The research demonstrates that a hybrid GNN based approach enhanced with entropy calculation and spectral information can effectively detect and predict a machine's behavioural changes. The model can interface with a plant's 'process control system' in real-time to perform forecasting and classification tasks to aid the asset management engineers to operate their machines more efficiently and reduce unplanned downtimes. A series of trialsare planned for this model in the future in other manufacturing industries.

Keywords: GNN, Entropy, anomaly detection, industrial time-series, AI, IoT, Industry 4.0, Machine Learning

Procedia PDF Downloads 149

Authors: Iyad Ismail, Fathilatul Abdul Hamid

Abstract:

This research was mainly investigated to recognize the extent of big data analysis by external auditors. This paper adopts grounded theory as a framework for conducting a series of semi-structured interviews with eighteen external auditors. The research findings comprised the availability extent of big data and big data analysis usage by the external auditors in Palestine, Gaza Strip. Considering the study's outcomes leads to a series of auditing procedures in order to improve the external auditing techniques, which leads to high-quality audit process. Also, this research is crucial for auditing firms by giving an insight into the mechanisms of auditing firms to identify the most important strategies that help in achieving competitive audit quality. These results are aims to instruct the auditing academic and professional institutions in developing techniques for external auditors in order to the big data analysis. This paper provides appropriate information for the decision-making process and a source of future information which affects technological auditing.

Keywords: big data analysis, external auditors, audit reliance, internal audit function

Procedia PDF Downloads 68

Authors: Jonardan Koner

Abstract:

The study attempts to find out the impact of infrastructural investment on state economic growth in India. It further tries to determine the magnitude of the impact of infrastructural investment on economic indicator, i.e., per-capita income (PCI) in Indian States. The study uses panel regression technique to measure the impact of infrastructural investment on per-capita income (PCI) in Indian States. Panel regression technique helps incorporate both the cross-section and time-series aspects of the dataset. In order to analyze the difference in impact of the explanatory variables on the explained variables across states, the study uses Fixed Effect Panel Regression Model. The conclusions of the study are that infrastructural investment has a desirable impact on economic development and that the impact is different for different states in India. We analyze time series data (annual frequency) ranging from 1991 to 2010. The study reveals that the infrastructural investment significantly explains the variation of economic indicators.

Keywords: infrastructural investment, multiple regression, panel regression techniques, economic development, fixed effect dummy variable model

Procedia PDF Downloads 370

Authors: Bodhayan Nandi, Shubhajit Roy Chowdhury

Abstract:

This paper presents the development of a portable blood glucose monitoring device based on Near-Infrared Spectroscopy. The system supports Internet connectivity through WiFi and uploads the time series data of glucose concentration of patients to a server. In addition, the server is given sufficient intelligence to predict the future pathophysiological state of a patient given the current and past pathophysiological data. This will enable to prognosticate the approaching critical condition of the patient much before the critical condition actually occurs.The server hosts web applications to allow authorized users to monitor the data remotely.

Keywords: non invasive, blood glucose concentration, microcontroller, IoT, application server, database server

Procedia PDF Downloads 215

Authors: N. Sopipan

Abstract:

In this paper, we study of rainfall time series of weather stations in Nakhon Ratchasima province in Thailand using various statistical methods enabled to analyse the behaviour of rainfall in the study areas. Time-series analysis is an important tool in modelling and forecasting rainfall. ARIMA and Holt-Winter models based on exponential smoothing were built. All the models proved to be adequate. Therefore, could give information that can help decision makers establish strategies for proper planning of agriculture, drainage system and other water resource applications in Nakhon Ratchasima province. We found the best perform for forecasting is ARIMA(1,0,1)(1,0,1)12.

Keywords: ARIMA Models, exponential smoothing, Holt-Winter model

Procedia PDF Downloads 298

Authors: Gebreegziabher Hailu Gebrecherkos

Abstract:

This study explores the derivatives of functions defined by I-functions of two variables and their connections to generalized M-series. We begin by defining I-functions, which are generalized functions that encompass various special functions, and analyze their properties. By employing advanced calculus techniques, we derive new formulas for the first and higher-order derivatives of I-functions with respect to their variables; we establish some derivative formulae of the I-function of two variables involving generalized M-series. The special cases of our derivatives yield interesting results.

Keywords: I-function, Mellin-Barners control integral, generalized M-series, higher order derivative

Procedia PDF Downloads 14

Authors: N. Ravikumar, S. Krishnan, B. Yokeshkumar

Abstract:

In present days, the power quality issues are increases due to non-linear loads like fridge, AC, washing machines, induction motor, etc. This power quality issues will affects the output voltages, output current, and output power of the total performance of the generator. This paper explains how to test the generator using the Fluke 435 II series power quality analyser. This Fluke 435 II series power quality analyser is used to measure the voltage, current, power, energy, total harmonic distortion (THD), current harmonics, voltage harmonics, power factor, and frequency. The Fluke 435 II series power quality analyser have several advantages. They are i) it will records output in analog and digital format. ii) the fluke analyzer will records at every 0.25 sec. iii) it will also measure all the electrical parameter at a time.

Keywords: THD, harmonics, power quality, TNEB, Fluke 435

Procedia PDF Downloads 175

Authors: James Newman

Abstract:

Process mining is an emerging technology that looks to serialize enterprise data in time series data. It has been used by many companies and has been the subject of a variety of research papers. However, the majority of current efforts have looked at how to best create process mining from standard relational databases. This paper is the first pass at outlining a database custom-built for the minimal viable product of process mining. We present Block Miner, a blockchain protocol to store process mining data across a distributed network. We demonstrate the feasibility of storing process mining data on the blockchain. We present a proof of concept and show how the intersection of these two technologies helps to solve a variety of issues, including but not limited to ransomware attacks, tax documentation, and conflict resolution.

Keywords: blockchain, process mining, memory optimization, protocol

Procedia PDF Downloads 101

Authors: Wei-Na Li, Mei-Lan Piao, Nam Kim

Abstract:

We proposed a novel computer-generated hologram (CGH) achieved scheme, wherein the CGH is generated from a point cloud which is transformed by a mapping relationship of a series of elemental images captured from a real three-dimensional (3D) object by using a lens array. This scheme is composed of three procedures: mapping from elemental images to point cloud, hologram generation, and hologram display. A mapping method is figured out to achieve a virtual volume date (point cloud) from a series of elemental images. This mapping method consists of two steps. Firstly, the coordinate (x, y) pairs and its appearing number are calculated from the series of sub-images, which are generated from the elemental images. Secondly, a series of corresponding coordinates (x, y, z) are calculated from the elemental images. Then a hologram is generated from the volume data that is calculated by the previous two steps. Eventually, a spatial light modulator (SLM) and a green laser beam are utilized to display this hologram and reconstruct the original 3D object. In this paper, in order to show a more auto stereoscopic display of a real 3D object, we successfully obtained the actual depth data of every discrete point of the real 3D object, and overcame the inherent drawbacks of the depth camera by obtaining point cloud from the elemental images.

Keywords: elemental image, point cloud, computer-generated hologram (CGH), autostereoscopic display

Procedia PDF Downloads 582

Authors: Jacky Liu

Abstract:

This paper develops a team sports outcome prediction system with potential for wide-ranging applications across various disciplines. Despite significant advancements in predictive analytics, existing studies in sports outcome predictions possess considerable limitations, including insufficient feature engineering and underutilization of advanced machine learning techniques, among others. To address these issues, we extend the Sports Cross Industry Standard Process for Data Mining (SRP-CRISP-DM) framework and propose a unique, comprehensive predictive system, using National Basketball Association (NBA) data as an example to test this extended framework. Our approach follows a holistic methodology in feature engineering, employing both Time Series and Non-Time Series Data, as well as conducting Explanatory Data Analysis and Feature Selection. Furthermore, we contribute to the discourse on target variable choice in team sports outcome prediction, asserting that point spread prediction yields higher profits as opposed to game-winner predictions. Using machine learning algorithms, particularly XGBoost, results in a significant improvement in predictive accuracy of team sports outcomes. Applied to point spread betting strategies, it offers an astounding annual return of approximately 900% on an initial investment of $100. Our findings not only contribute to academic literature, but have critical practical implications for sports betting. Our study advances the understanding of team sports outcome prediction a burgeoning are in complex system predictions and pave the way for potential profitability and more informed decision making in sports betting markets.

Keywords: machine learning, team sports, game outcome prediction, sports betting, profits simulation

Procedia PDF Downloads 101

Authors: Eric Kumar, Erica Cochran, Zhiang Zhang, Wei Liang, Ronak Mody

Abstract:

The objective of this article was to create a modelling framework that exposes the marginal costs of shifting workloads across geographically distributed data-centers. Geographical distribution of internet services helps to optimize their performance for localized end users with lowered communications times and increased availability. However, due to the geographical and temporal effects, the physical embodiments of a service's data center infrastructure can vary greatly. In this work, we first identify that the sources of variances in the physical infrastructure primarily stem from local weather conditions, specific user traffic profiles, energy sources, and the types of IT hardware available at the time of deployment. Second, we create a traffic simulator that indicates the IT load at each data-center in the set as an approximator for user traffic profiles. Third, we implement a framework that quantifies the global level energy demands using building energy models and the traffic profiles. The results of the model provide a time series of energy demands that can be used for further life cycle analysis of internet services.

Keywords: data-centers, energy, life cycle, network simulation

Procedia PDF Downloads 147

Authors: Harold Vásquez, Cesar Hernández, Ingrid Páez

Abstract:

This paper approach cognitive radio technic and applied pure proactive handoff Model to decrease interference between PU and SU and comparing it with reactive handoff model. Through the study and analysis of multivariate models SAW and TOPSIS join to 3 dynamic prediction techniques AR, MA ,and ARMA. To evaluate the best model is taken four metrics: number failed handoff, number handoff, number predictions, and number interference. The result presented the advantages using this type of pure proactive models to predict changes in the PU according to the selected channel and reduce interference. The model showed better performance was TOPSIS-MA, although TOPSIS-AR had a higher predictive ability this was not reflected in the interference reduction.

Keywords: cognitive radio, spectrum handoff, decision making, time series, wireless networks

Procedia PDF Downloads 486

Authors: K. S. Sreejith, C. Shaji

Abstract:

Though both Arabian Sea and its counterpart Bay of Bengal is forced primarily by the semi-annually reversing monsoons, the spatio-temporal variations of surface waters is very strong in the Arabian Sea as compared to the Bay of Bengal. This study focuses on the inter-annual variability of Sea Surface Temperature (SST) in the Arabian Sea by analysing ERSST dataset which covers 152 years of SST (January 1854 to December 2002) based on the ICOADS in situ observations. To capture the dominant SST oscillations and to understand the inter-annual SST variations at various local regions of the Arabian Sea, wavelet analysis was performed on this long time-series SST dataset. This tool is advantageous over other signal analysing tools like Fourier analysis, based on the fact that it unfolds a time-series data (signal) both in frequency and time domain. This technique makes it easier to determine dominant modes of variability and explain how those modes vary in time. The analysis revealed that pentadal SST oscillations predominate at most of the analysed local regions in the Arabian Sea. From the time information of wavelet analysis, it was interpreted that these cold and warm events of large amplitude occurred during the periods 1870-1890, 1890-1910, 1930-1950, 1980-1990 and 1990-2005. SST oscillations with peaks having period of ~ 2-4 years was found to be significant in the central and eastern regions of Arabian Sea. This indicates that the inter-annual SST variation in the Indian Ocean is affected by the El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) events.

Keywords: Arabian Sea, ICOADS, inter-annual variation, pentadal oscillation, SST, wavelet analysis

Procedia PDF Downloads 274

Authors: Soheila Sadeghi

Abstract:

Accurate forecasting of project performance metrics is crucial for successfully managing and delivering urban road reconstruction projects. Traditional methods often rely on static baseline plans and fail to consider the dynamic nature of project progress and external factors. This research proposes a machine learning-based approach to forecast project performance metrics, such as cost variance and earned value, for each Work Breakdown Structure (WBS) category in an urban road reconstruction project. The proposed model utilizes time series forecasting techniques, including Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) networks, to predict future performance based on historical data and project progress. The model also incorporates external factors, such as weather patterns and resource availability, as features to enhance the accuracy of forecasts. By applying the predictive power of machine learning, the performance forecasting model enables proactive identification of potential deviations from the baseline plan, which allows project managers to take timely corrective actions. The research aims to validate the effectiveness of the proposed approach using a case study of an urban road reconstruction project, comparing the model's forecasts with actual project performance data. The findings of this research contribute to the advancement of project management practices in the construction industry, offering a data-driven solution for improving project performance monitoring and control.

Keywords: project performance forecasting, machine learning, time series forecasting, cost variance, earned value management

Procedia PDF Downloads 46