Search results for: PES (power electronics systems) synchronous machine
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 16508

Search results for: PES (power electronics systems) synchronous machine

14738 Pinch Analysis of Triple Pressure Reheat Supercritical Combined Cycle Power Plant

Authors: Sui Yan Wong, Keat Ping Yeoh, Chi Wai Hui

Abstract:

In this study, supercritical steam is introduced to Combined Cycle Power Plant (CCPP) in an attempt to further optimize energy recovery. Subcritical steam is commonly used in the CCPP, operating at maximum pressures around 150-160 bar. Supercritical steam is an alternative to increase heat recovery during vaporization period of water. The idea of improvement using supercritical steam is further examined with the use of exergy, pinch analysis and Aspen Plus simulation.

Keywords: exergy, pinch, combined cycle power plant, supercritical steam

Procedia PDF Downloads 135
14737 Iraqi Short Term Electrical Load Forecasting Based on Interval Type-2 Fuzzy Logic

Authors: Firas M. Tuaimah, Huda M. Abdul Abbas

Abstract:

Accurate Short Term Load Forecasting (STLF) is essential for a variety of decision making processes. However, forecasting accuracy can drop due to the presence of uncertainty in the operation of energy systems or unexpected behavior of exogenous variables. Interval Type 2 Fuzzy Logic System (IT2 FLS), with additional degrees of freedom, gives an excellent tool for handling uncertainties and it improved the prediction accuracy. The training data used in this study covers the period from January 1, 2012 to February 1, 2012 for winter season and the period from July 1, 2012 to August 1, 2012 for summer season. The actual load forecasting period starts from January 22, till 28, 2012 for winter model and from July 22 till 28, 2012 for summer model. The real data for Iraqi power system which belongs to the Ministry of Electricity.

Keywords: short term load forecasting, prediction interval, type 2 fuzzy logic systems, electric, computer systems engineering

Procedia PDF Downloads 391
14736 Evaluation of Machine Learning Algorithms and Ensemble Methods for Prediction of Students’ Graduation

Authors: Soha A. Bahanshal, Vaibhav Verdhan, Bayong Kim

Abstract:

Graduation rates at six-year colleges are becoming a more essential indicator for incoming fresh students and for university rankings. Predicting student graduation is extremely beneficial to schools and has a huge potential for targeted intervention. It is important for educational institutions since it enables the development of strategic plans that will assist or improve students' performance in achieving their degrees on time (GOT). A first step and a helping hand in extracting useful information from these data and gaining insights into the prediction of students' progress and performance is offered by machine learning techniques. Data analysis and visualization techniques are applied to understand and interpret the data. The data used for the analysis contains students who have graduated in 6 years in the academic year 2017-2018 for science majors. This analysis can be used to predict the graduation of students in the next academic year. Different Predictive modelings such as logistic regression, decision trees, support vector machines, Random Forest, Naïve Bayes, and KNeighborsClassifier are applied to predict whether a student will graduate. These classifiers were evaluated with k folds of 5. The performance of these classifiers was compared based on accuracy measurement. The results indicated that Ensemble Classifier achieves better accuracy, about 91.12%. This GOT prediction model would hopefully be useful to university administration and academics in developing measures for assisting and boosting students' academic performance and ensuring they graduate on time.

Keywords: prediction, decision trees, machine learning, support vector machine, ensemble model, student graduation, GOT graduate on time

Procedia PDF Downloads 68
14735 State of Emergency in Turkey (July 2016-July 2018): A Case of Utilization of Law as a Political Instrument

Authors: Neslihan Cetin

Abstract:

In this study, we will aim to analyze how the period of the state of emergency in Turkey lead to gaps in law and the formation of areas in which there was a complete lack of supervision. The state of emergency that was proclaimed following the coup attempt of July 15, 2016, continued until July 18, 2018, that is to say, 2 years, without taking into account whether the initial circumstances persisted. As part of this work, we claim that the state of emergency provided the executive power with important tools for governing, which it took constant use. We can highlight how the concern for security at the center of the basic considerations of the people in a city was exploited as a foundation by the military power in Turkey to interfere in the political, legal, and social spheres. The constitutions of 1924, 1961, and 1982 entrusted the army with the role of protector of the integrity of the state. This became an instrument at the hands of the military to legitimize their interventions in the name of public security. Its interventions in the political field are indeed politically motivated. The constitution, the legislative, and regulatory systems are modified and monopolized by the military power that dominates the legislative, regulatory, and judicial power, leading to a state of exception. With the political convulsions over a decade, the government was able to usurp the instrument called the state of exception. In particular, the decree-laws of the state of emergency, which the executive makes frequent and generally abusive use, became instruments in the hands of the government to take measures that it wishes to escape from the rules and the pre-established control mechanisms. Thus the struggle against the political opposition becomes more unbalanced and destructive. To this must also be added the ineffectiveness of ex-post controls and domestic remedies. This research allows us to stress how a legal concept, such as ‘the state of emergency’ can be politically exploited to make it a legal weapon that continues to produce victims.

Keywords: constitutional law, state of emergency, rule of law, instrumentalization of law

Procedia PDF Downloads 136
14734 Language as an Instrument of Manipulation and Political Control in Nigeria: The 2015 Presidential Election in Perspective

Authors: Abdulmalik Adamu

Abstract:

This study is premised on the assumption that language, particularly, English plays a significant role in the acquisition of power in Nigeria. This is against the backdrop of the fact that for the first time in the political history of Nigeria, an opposition party succeeded in dethroning an incumbent President and ruling political party in an election. Therefore the main objective was to investigate the role of language, particularly English in the acquisition of political power in Nigeria. The corpus generated for this study consisted of excerpts from the media exchange between the spokespersons of the two dominant political parties at the time of the elections in 2015; Olisa Metuh of the Peoples Democratic Party (PDP) and Lai Mohammed of the All Progressive Party (APC). The excerpts were analysed using Critical Discourse Analysis (CDA) as a research tool. The findings revealed the acceptance of the first proposition that English facilitates the acquisition of political power in Nigeria and the rejection of the second proposition that English is an instrument for the exclusion of the populist from political events in Nigeria. The study, therefore, concluded that language, particularly English played a significant role in the acquisition of political power in Nigeria.

Keywords: language, power, politics, Critical Discourse Analysis (CDA)

Procedia PDF Downloads 391
14733 Automatic Teller Machine System Security by Using Mobile SMS Code

Authors: Husnain Mushtaq, Mary Anjum, Muhammad Aleem

Abstract:

The main objective of this paper is used to develop a high security in Automatic Teller Machine (ATM). In these system bankers will collect the mobile numbers from the customers and then provide a code on their mobile number. In most country existing ATM machine use the magnetic card reader. The customer is identifying by inserting an ATM card with magnetic card that hold unique information such as card number and some security limitations. By entering a personal identification number, first the customer is authenticated then will access bank account in order to make cash withdraw or other services provided by the bank. Cases of card fraud are another problem once the user’s bank card is missing and the password is stolen, or simply steal a customer’s card & PIN the criminal will draw all cash in very short time, which will being great financial losses in customer, this type of fraud has increase worldwide. So to resolve this problem we are going to provide the solution using “Mobile SMS code” and ATM “PIN code” in order to improve the verify the security of customers using ATM system and confidence in the banking area.

Keywords: PIN, inquiry, biometric, magnetic strip, iris recognition, face recognition

Procedia PDF Downloads 359
14732 Modern Information Security Management and Digital Technologies: A Comprehensive Approach to Data Protection

Authors: Mahshid Arabi

Abstract:

With the rapid expansion of digital technologies and the internet, information security has become a critical priority for organizations and individuals. The widespread use of digital tools such as smartphones and internet networks facilitates the storage of vast amounts of data, but simultaneously, vulnerabilities and security threats have significantly increased. The aim of this study is to examine and analyze modern methods of information security management and to develop a comprehensive model to counteract threats and information misuse. This study employs a mixed-methods approach, including both qualitative and quantitative analyses. Initially, a systematic review of previous articles and research in the field of information security was conducted. Then, using the Delphi method, interviews with 30 information security experts were conducted to gather their insights on security challenges and solutions. Based on the results of these interviews, a comprehensive model for information security management was developed. The proposed model includes advanced encryption techniques, machine learning-based intrusion detection systems, and network security protocols. AES and RSA encryption algorithms were used for data protection, and machine learning models such as Random Forest and Neural Networks were utilized for intrusion detection. Statistical analyses were performed using SPSS software. To evaluate the effectiveness of the proposed model, T-Test and ANOVA statistical tests were employed, and results were measured using accuracy, sensitivity, and specificity indicators of the models. Additionally, multiple regression analysis was conducted to examine the impact of various variables on information security. The findings of this study indicate that the comprehensive proposed model reduced cyber-attacks by an average of 85%. Statistical analysis showed that the combined use of encryption techniques and intrusion detection systems significantly improves information security. Based on the obtained results, it is recommended that organizations continuously update their information security systems and use a combination of multiple security methods to protect their data. Additionally, educating employees and raising public awareness about information security can serve as an effective tool in reducing security risks. This research demonstrates that effective and up-to-date information security management requires a comprehensive and coordinated approach, including the development and implementation of advanced techniques and continuous training of human resources.

Keywords: data protection, digital technologies, information security, modern management

Procedia PDF Downloads 22
14731 Optimizing the Scanning Time with Radiation Prediction Using a Machine Learning Technique

Authors: Saeed Eskandari, Seyed Rasoul Mehdikhani

Abstract:

Radiation sources have been used in many industries, such as gamma sources in medical imaging. These waves have destructive effects on humans and the environment. It is very important to detect and find the source of these waves because these sources cannot be seen by the eye. A portable robot has been designed and built with the purpose of revealing radiation sources that are able to scan the place from 5 to 20 meters away and shows the location of the sources according to the intensity of the waves on a two-dimensional digital image. The operation of the robot is done by measuring the pixels separately. By increasing the image measurement resolution, we will have a more accurate scan of the environment, and more points will be detected. But this causes a lot of time to be spent on scanning. In this paper, to overcome this challenge, we designed a method that can optimize this time. In this method, a small number of important points of the environment are measured. Hence the remaining pixels are predicted and estimated by regression algorithms in machine learning. The research method is based on comparing the actual values of all pixels. These steps have been repeated with several other radiation sources. The obtained results of the study show that the values estimated by the regression method are very close to the real values.

Keywords: regression, machine learning, scan radiation, robot

Procedia PDF Downloads 72
14730 Early Prediction of Disposable Addresses in Ethereum Blockchain

Authors: Ahmad Saleem

Abstract:

Ethereum is the second largest crypto currency in blockchain ecosystem. Along with standard transactions, it supports smart contracts and NFT’s. Current research trends are focused on analyzing the overall structure of the network its growth and behavior. Ethereum addresses are anonymous and can be created on fly. The nature of Ethereum network and addresses make it hard to predict their behavior. The activity period of an ethereum address is not much analyzed. Using machine learning we can make early prediction about the disposability of the address. In this paper we analyzed the lifetime of the addresses. We also identified and predicted the disposable addresses using machine learning models and compared the results.

Keywords: blockchain, Ethereum, cryptocurrency, prediction

Procedia PDF Downloads 92
14729 Hybrid Control Strategy for Nine-Level Asymmetrical Cascaded H-Bridge Inverter

Authors: Bachir Belmadani, Rachid Taleb, M’hamed Helaimi

Abstract:

Multilevel inverters are well used in high power electronic applications because of their ability to generate a very good quality of waveforms, reducing switching frequency, and their low voltage stress across the power devices. This paper presents the hybrid pulse-width modulation (HPWM) strategy of a uniform step asymmetrical cascaded H-bridge nine-level Inverter (USACHB9LI). The HPWM approach is compared to the well-known sinusoidal pulse-width modulation (SPWM) strategy. Simulation results demonstrate the better performances and technical advantages of the HPWM controller in feeding a high power induction motor.

Keywords: uniform step asymmetrical cascaded h-bridge high-level inverter, hybrid pwm, sinusoidal pwm, high power induction motor

Procedia PDF Downloads 567
14728 The Role of Synthetic Data in Aerial Object Detection

Authors: Ava Dodd, Jonathan Adams

Abstract:

The purpose of this study is to explore the characteristics of developing a machine learning application using synthetic data. The study is structured to develop the application for the purpose of deploying the computer vision model. The findings discuss the realities of attempting to develop a computer vision model for practical purpose, and detail the processes, tools, and techniques that were used to meet accuracy requirements. The research reveals that synthetic data represents another variable that can be adjusted to improve the performance of a computer vision model. Further, a suite of tools and tuning recommendations are provided.

Keywords: computer vision, machine learning, synthetic data, YOLOv4

Procedia PDF Downloads 218
14727 Intelligent Drug Delivery Systems

Authors: Shideh Mohseni Movahed, Mansoureh Safari

Abstract:

Intelligent drug delivery systems (IDDS) are innovative technological innovations and clinical way to advance current treatments. These systems differ in technique of therapeutic administration, intricacy, materials and patient compliance to address numerous clinical conditions that require different pharmacological therapies. IDDS capable of releasing an active molecule at the proper site and at a amount that adjusts in response to the progression of the disease or to certain functions/biorhythms of the organism is particularly appealing. In this paper, we describe the most recent advances in the development of intelligent drug delivery systems.

Keywords: drug delivery systems, IDDS, medicine, health

Procedia PDF Downloads 219
14726 Fault Ride Through Management in Renewable Power Park

Authors: Mohd Zamri Che Wanik

Abstract:

This paper presents the management of the Fault Ride Through event within a Solar Farm during a grid fault. The modeling and simulation of a photovoltaic (PV) with battery energy storage connected to the power network will be described. The modeling approach and the study analysis performed are described. The model and operation scenarios are simulated using a digital simulator for different scenarios. The dynamic response of the system when subjected to sudden self-clearance temporary fault is presented. The capability of the PV system and battery storage riding through the power system fault and, at the same time, supporting the local grid by injecting fault current is demonstrated. For each case, the different control methods to achieve the objective of supporting the grid according to grid code requirements are presented and explained. The inverter modeling approach is presented and described.

Keywords: faut ride through, solar farm, grid code, power network

Procedia PDF Downloads 46
14725 The Convergence of IoT and Machine Learning: A Survey of Real-time Stress Detection System

Authors: Shreyas Gambhirrao, Aditya Vichare, Aniket Tembhurne, Shahuraj Bhosale

Abstract:

In today's rapidly evolving environment, stress has emerged as a significant health concern across different age groups. Stress that isn't controlled, whether it comes from job responsibilities, health issues, or the never-ending news cycle, can have a negative effect on our well-being. The problem is further aggravated by the ongoing connection to technology. In this high-tech age, identifying and controlling stress is vital. In order to solve this health issue, the study focuses on three key metrics for stress detection: body temperature, heart rate, and galvanic skin response (GSR). These parameters along with the Support Vector Machine classifier assist the system to categorize stress into three groups: 1) Stressed, 2) Not stressed, and 3) Moderate stress. Proposed training model, a NodeMCU combined with particular sensors collects data in real-time and rapidly categorizes individuals based on their stress levels. Real-time stress detection is made possible by this creative combination of hardware and software.

Keywords: real time stress detection, NodeMCU, sensors, heart-rate, body temperature, galvanic skin response (GSR), support vector machine

Procedia PDF Downloads 68
14724 Indian Premier League (IPL) Score Prediction: Comparative Analysis of Machine Learning Models

Authors: Rohini Hariharan, Yazhini R, Bhamidipati Naga Shrikarti

Abstract:

In the realm of cricket, particularly within the context of the Indian Premier League (IPL), the ability to predict team scores accurately holds significant importance for both cricket enthusiasts and stakeholders alike. This paper presents a comprehensive study on IPL score prediction utilizing various machine learning algorithms, including Support Vector Machines (SVM), XGBoost, Multiple Regression, Linear Regression, K-nearest neighbors (KNN), and Random Forest. Through meticulous data preprocessing, feature engineering, and model selection, we aimed to develop a robust predictive framework capable of forecasting team scores with high precision. Our experimentation involved the analysis of historical IPL match data encompassing diverse match and player statistics. Leveraging this data, we employed state-of-the-art machine learning techniques to train and evaluate the performance of each model. Notably, Multiple Regression emerged as the top-performing algorithm, achieving an impressive accuracy of 77.19% and a precision of 54.05% (within a threshold of +/- 10 runs). This research contributes to the advancement of sports analytics by demonstrating the efficacy of machine learning in predicting IPL team scores. The findings underscore the potential of advanced predictive modeling techniques to provide valuable insights for cricket enthusiasts, team management, and betting agencies. Additionally, this study serves as a benchmark for future research endeavors aimed at enhancing the accuracy and interpretability of IPL score prediction models.

Keywords: indian premier league (IPL), cricket, score prediction, machine learning, support vector machines (SVM), xgboost, multiple regression, linear regression, k-nearest neighbors (KNN), random forest, sports analytics

Procedia PDF Downloads 39
14723 Design an Expert System to Assess the Hydraulic System in Thermal and Hydrodynamic Aspect

Authors: Ahmad Abdul-Razzak Aboudi Al-Issa

Abstract:

Thermal and Hydrodynamic are basic aspects in any hydraulic system and therefore, they must be assessed with regard to this aspect before constructing the system. This assessment needs a good expertise in this aspect to obtain an efficient hydraulic system. Therefore, this study aims to build an expert system called Hydraulic System Calculations (HSC) to ensure a smooth operation for the hydraulic system. The expert system (HSC) had been designed and coded in an user-friendly interactive program called Microsoft Visual Basic 2010. The suggested code provides the designer with a number of choices to resolve the problem of hydraulic oil overheating which may arise during the continuous operation of the hydraulic unit. As a result, the HSC can minimize the human errors, effort, time and cost of hydraulic machine design.

Keywords: fluid power, hydraulic system, thermal and hydrodynamic, expert system

Procedia PDF Downloads 442
14722 Improving Activity Recognition Classification of Repetitious Beginner Swimming Using a 2-Step Peak/Valley Segmentation Method with Smoothing and Resampling for Machine Learning

Authors: Larry Powell, Seth Polsley, Drew Casey, Tracy Hammond

Abstract:

Human activity recognition (HAR) systems have shown positive performance when recognizing repetitive activities like walking, running, and sleeping. Water-based activities are a reasonably new area for activity recognition. However, water-based activity recognition has largely focused on supporting the elite and competitive swimming population, which already has amazing coordination and proper form. Beginner swimmers are not perfect, and activity recognition needs to support the individual motions to help beginners. Activity recognition algorithms are traditionally built around short segments of timed sensor data. Using a time window input can cause performance issues in the machine learning model. The window’s size can be too small or large, requiring careful tuning and precise data segmentation. In this work, we present a method that uses a time window as the initial segmentation, then separates the data based on the change in the sensor value. Our system uses a multi-phase segmentation method that pulls all peaks and valleys for each axis of an accelerometer placed on the swimmer’s lower back. This results in high recognition performance using leave-one-subject-out validation on our study with 20 beginner swimmers, with our model optimized from our final dataset resulting in an F-Score of 0.95.

Keywords: time window, peak/valley segmentation, feature extraction, beginner swimming, activity recognition

Procedia PDF Downloads 111
14721 Crystallization of the US Supreme Court’s Role as an Arbiter of Constitutionality of Laws

Authors: Fethia Braik

Abstract:

This paper summarizes the history of the US Supreme Court. It did not enjoy today’s status. It did neither control legislation nor the executive power. It was until 1803, during Marshall’s term, that it gained the pride of ruling over the constitutionality of acts be they federal or local, congressional or presidential. The Chief Justice, whether intended or not, vested such power in the supreme judicial institution via the case of Marbury v. Madison. Such power, nevertheless, had not been exercised for many years, till the Dred Scott case.

Keywords: Judiciary Acts 1789, 1801, chief justice, associate justice, justice of peace, review of constitutionality of acts, Jay court, Ellsworth court, Marshall court

Procedia PDF Downloads 300
14720 Reliability and Cost Focused Optimization Approach for a Communication Satellite Payload Redundancy Allocation Problem

Authors: Mehmet Nefes, Selman Demirel, Hasan H. Ertok, Cenk Sen

Abstract:

A typical reliability engineering problem regarding communication satellites has been considered to determine redundancy allocation scheme of power amplifiers within payload transponder module, whose dominant function is to amplify power levels of the received signals from the Earth, through maximizing reliability against mass, power, and other technical limitations. Adding each redundant power amplifier component increases not only reliability but also hardware, testing, and launch cost of a satellite. This study investigates a multi-objective approach used in order to solve Redundancy Allocation Problem (RAP) for a communication satellite payload transponder, focusing on design cost due to redundancy and reliability factors. The main purpose is to find the optimum power amplifier redundancy configuration satisfying reliability and capacity thresholds simultaneously instead of analyzing respectively or independently. A mathematical model and calculation approach are instituted including objective function definitions, and then, the problem is solved analytically with different input parameters in MATLAB environment. Example results showed that payload capacity and failure rate of power amplifiers have remarkable effects on the solution and also processing time.

Keywords: communication satellite payload, multi-objective optimization, redundancy allocation problem, reliability, transponder

Procedia PDF Downloads 259
14719 Optimization of Water Desalination System Powered by High Concentrated Photovoltaic Panels in Kuwait Climate Conditions

Authors: Adel A. Ghoneim

Abstract:

Desalination using solar energy is an interesting option specifically at regions with abundant solar radiation since such areas normally have scarcity of clean water resources. Desalination is the procedure of eliminating dissolved minerals from seawater or brackish water to generate fresh water. In this work, a simulation program is developed to determine the performance of reverse osmosis (RO) water desalination plant powered by high concentrated photovoltaic (HCPV) panels in Kuwait climate conditions. The objective of such a photovoltaic thermal system is to accomplish a double output, i.e., co-generation of both electricity and fresh water that is applicable for rural regions with high solar irradiation. The suggested plan enables to design an RO plant that does not depend on costly batteries or additional land and significantly reduce the government costs to subsidize the water generation cost. Typical weather conditions for Kuwait is employed as input to the simulation program. The simulation program is utilized to optimize the system efficiency as well as the distillate water production. The areas and slopes of HCPV modules are varied to attain maximum yearly power production. Maximum yearly distillate production and HCPV energy generation are found to correspond to HCPV facing south with tilt of 27° (Kuwait latitude-3°). The power needed to produce 1 l of clean drinking water ranged from 2 to 8 kW h/m³, based on the salinity of the feed water and the system operating conditions. Moreover, adapting HCPV systems achieve an avoided greenhouse gases emission by about 1128 ton CO₂ annually. Present outcomes certainly illustrate environmental advantages of water desalination system powered by high concentrated photovoltaic systems in Kuwait climate conditions.

Keywords: desalination, high concentrated photovoltaic systems, reverse osmosis, solar radiation

Procedia PDF Downloads 139
14718 Predicting Provider Service Time in Outpatient Clinics Using Artificial Intelligence-Based Models

Authors: Haya Salah, Srinivas Sharan

Abstract:

Healthcare facilities use appointment systems to schedule their appointments and to manage access to their medical services. With the growing demand for outpatient care, it is now imperative to manage physician's time effectively. However, high variation in consultation duration affects the clinical scheduler's ability to estimate the appointment duration and allocate provider time appropriately. Underestimating consultation times can lead to physician's burnout, misdiagnosis, and patient dissatisfaction. On the other hand, appointment durations that are longer than required lead to doctor idle time and fewer patient visits. Therefore, a good estimation of consultation duration has the potential to improve timely access to care, resource utilization, quality of care, and patient satisfaction. Although the literature on factors influencing consultation length abound, little work has done to predict it using based data-driven approaches. Therefore, this study aims to predict consultation duration using supervised machine learning algorithms (ML), which predicts an outcome variable (e.g., consultation) based on potential features that influence the outcome. In particular, ML algorithms learn from a historical dataset without explicitly being programmed and uncover the relationship between the features and outcome variable. A subset of the data used in this study has been obtained from the electronic medical records (EMR) of four different outpatient clinics located in central Pennsylvania, USA. Also, publicly available information on doctor's characteristics such as gender and experience has been extracted from online sources. This research develops three popular ML algorithms (deep learning, random forest, gradient boosting machine) to predict the treatment time required for a patient and conducts a comparative analysis of these algorithms with respect to predictive performance. The findings of this study indicate that ML algorithms have the potential to predict the provider service time with superior accuracy. While the current approach of experience-based appointment duration estimation adopted by the clinic resulted in a mean absolute percentage error of 25.8%, the Deep learning algorithm developed in this study yielded the best performance with a MAPE of 12.24%, followed by gradient boosting machine (13.26%) and random forests (14.71%). Besides, this research also identified the critical variables affecting consultation duration to be patient type (new vs. established), doctor's experience, zip code, appointment day, and doctor's specialty. Moreover, several practical insights are obtained based on the comparative analysis of the ML algorithms. The machine learning approach presented in this study can serve as a decision support tool and could be integrated into the appointment system for effectively managing patient scheduling.

Keywords: clinical decision support system, machine learning algorithms, patient scheduling, prediction models, provider service time

Procedia PDF Downloads 119
14717 A Comparative Analysis of Various Companding Techniques Used to Reduce PAPR in VLC Systems

Authors: Arushi Singh, Anjana Jain, Prakash Vyavahare

Abstract:

Recently, Li-Fi(light-fiedelity) has been launched based on VLC(visible light communication) technique, 100 times faster than WiFi. Now 5G mobile communication system is proposed to use VLC-OFDM as the transmission technique. The VLC system focused on visible rays, is considered for efficient spectrum use and easy intensity modulation through LEDs. The reason of high speed in VLC is LED, as they flicker incredibly fast(order of MHz). Another advantage of employing LED is-it acts as low pass filter results no out-of-band emission. The VLC system falls under the category of ‘green technology’ for utilizing LEDs. In present scenario, OFDM is used for high data-rates, interference immunity and high spectral efficiency. Inspite of the advantages OFDM suffers from large PAPR, ICI among carriers and frequency offset errors. Since, the data transmission technique used in VLC system is OFDM, the system suffers the drawbacks of OFDM as well as VLC, the non-linearity dues to non-linear characteristics of LED and PAPR of OFDM due to which the high power amplifier enters in non-linear region. The proposed paper focuses on reduction of PAPR in VLC-OFDM systems. Many techniques are applied to reduce PAPR such as-clipping-introduces distortion in the carrier; selective mapping technique-suffers wastage of bandwidth; partial transmit sequence-very complex due to exponentially increased number of sub-blocks. The paper discusses three companding techniques namely- µ-law, A-law and advance A-law companding technique. The analysis shows that the advance A-law companding techniques reduces the PAPR of the signal by adjusting the companding parameter within the range. VLC-OFDM systems are the future of the wireless communication but non-linearity in VLC-OFDM is a severe issue. The proposed paper discusses the techniques to reduce PAPR, one of the non-linearities of the system. The companding techniques mentioned in this paper provides better results without increasing the complexity of the system.

Keywords: non-linear companding techniques, peak to average power ratio (PAPR), visible light communication (VLC), VLC-OFDM

Procedia PDF Downloads 280
14716 MSIpred: A Python 2 Package for the Classification of Tumor Microsatellite Instability from Tumor Mutation Annotation Data Using a Support Vector Machine

Authors: Chen Wang, Chun Liang

Abstract:

Microsatellite instability (MSI) is characterized by high degree of polymorphism in microsatellite (MS) length due to a deficiency in mismatch repair (MMR) system. MSI is associated with several tumor types and its status can be considered as an important indicator for tumor prognostic. Conventional clinical diagnosis of MSI examines PCR products of a panel of MS markers using electrophoresis (MSI-PCR) which is laborious, time consuming, and less reliable. MSIpred, a python 2 package for automatic classification of MSI was released by this study. It computes important somatic mutation features from files in mutation annotation format (MAF) generated from paired tumor-normal exome sequencing data, subsequently using these to predict tumor MSI status with a support vector machine (SVM) classifier trained by MAF files of 1074 tumors belonging to four types. Evaluation of MSIpred on an independent 358-tumor test set achieved overall accuracy of over 98% and area under receiver operating characteristic (ROC) curve of 0.967. These results indicated that MSIpred is a robust pan-cancer MSI classification tool and can serve as a complementary diagnostic to MSI-PCR in MSI diagnosis.

Keywords: microsatellite instability, pan-cancer classification, somatic mutation, support vector machine

Procedia PDF Downloads 166
14715 Structural Stress of Hegemon’s Power Loss: A Pestle Analysis for Pacification and Security Policy Plan

Authors: Sehrish Qayyum

Abstract:

Active military power contention is shifting to economic and cyberwar to retain hegemony. Attuned Pestle analysis confirms that structural stress of hegemon’s power loss drives a containment approach towards caging actions. Ongoing diplomatic, asymmetric, proxy and direct wars are increasing stress hegemon’s power retention due to tangled military and economic alliances. It creates the condition of catalepsy with defective reflexive control which affects the core warfare operations. When one’s own power is doubted it gives power to one’s own doubt to ruin all planning either done with superlative cost-benefit analysis. Strategically calculated estimation of Hegemon’s power game since the early WWI to WWII, WWII-to Cold War and then to the current era in three chronological periods exposits that Thucydides’s trap became the reason for war broke out. Thirst for power is the demise of imagination and cooperation for better sense to prevail instead it drives ashes to dust. Pestle analysis is a wide array of evaluation from political and economic to legal dimensions of the state matters. It helps to develop the Pacification and Security Policy Plan (PSPP) to avoid hegemon’s structural stress of power loss in fact, in turn, creates an alliance with maximum amicable outputs. PSPP may serve to regulate and pause the hurricane of power clashes. PSPP along with a strategic work plan is based on Pestle analysis to deal with any conceivable war condition and approach for saving international peace. Getting tangled into self-imposed epistemic dilemmas results in regret that becomes the only option of performance. It is a generic application of probability tests to find the best possible options and conditions to develop PSPP for any adversity possible so far. Innovation in expertise begets innovation in planning and action-plan to serve as a rheostat approach to deal with any plausible power clash.

Keywords: alliance, hegemon, pestle analysis, pacification and security policy plan, security

Procedia PDF Downloads 102
14714 Virtual Routing Function Allocation Method for Minimizing Total Network Power Consumption

Authors: Kenichiro Hida, Shin-Ichi Kuribayashi

Abstract:

In a conventional network, most network devices, such as routers, are dedicated devices that do not have much variation in capacity. In recent years, a new concept of network functions virtualisation (NFV) has come into use. The intention is to implement a variety of network functions with software on general-purpose servers and this allows the network operator to select their capacities and locations without any constraints. This paper focuses on the allocation of NFV-based routing functions which are one of critical network functions, and presents the virtual routing function allocation algorithm that minimizes the total power consumption. In addition, this study presents the useful allocation policy of virtual routing functions, based on an evaluation with a ladder-shaped network model. This policy takes the ratio of the power consumption of a routing function to that of a circuit and traffic distribution between areas into consideration. Furthermore, the present paper shows that there are cases where the use of NFV-based routing functions makes it possible to reduce the total power consumption dramatically, in comparison to a conventional network, in which it is not economically viable to distribute small-capacity routing functions.

Keywords: NFV, resource allocation, virtual routing function, minimum power consumption

Procedia PDF Downloads 338
14713 Multi-Wavelength Q-Switched Erbium-Doped Fiber Laser with Photonic Crystal Fiber and Multi-Walled Carbon Nanotubes

Authors: Zian Cheak Tiu, Harith Ahmad, Sulaiman Wadi Harun

Abstract:

A simple multi-wavelength passively Q-switched Erbium-doped fiber laser (EDFL) is demonstrated using low cost multi-walled carbon nanotubes (MWCNTs) based saturable absorber (SA), which is prepared using polyvinyl alcohol (PVA) as a host polymer. The multi-wavelength operation is achieved based on nonlinear polarization rotation (NPR) effect by incorporating 50 m long photonic crystal fiber (PCF) in the ring cavity. The EDFL produces a stable multi-wavelength comb spectrum for more than 14 lines with a fixed spacing of 0.48 nm. The laser also demonstrates a stable pulse train with the repetition rate increases from 14.9 kHz to 25.4 kHz as the pump power increases from the threshold power of 69.0 mW to the maximum pump power of 133.8 mW. The minimum pulse width of 4.4 µs was obtained at the maximum pump power of 133.8 mW while the highest energy of 0.74 nJ was obtained at pump power of 69.0 mW.

Keywords: multi-wavelength Q-switched, multi-walled carbon nanotube, photonic crystal fiber

Procedia PDF Downloads 530
14712 A Spectral Decomposition Method for Ordinary Differential Equation Systems with Constant or Linear Right Hand Sides

Authors: R. B. Ogunrinde, C. C. Jibunoh

Abstract:

In this paper, a spectral decomposition method is developed for the direct integration of stiff and nonstiff homogeneous linear (ODE) systems with linear, constant, or zero right hand sides (RHSs). The method does not require iteration but obtains solutions at any random points of t, by direct evaluation, in the interval of integration. All the numerical solutions obtained for the class of systems coincide with the exact theoretical solutions. In particular, solutions of homogeneous linear systems, i.e. with zero RHS, conform to the exact analytical solutions of the systems in terms of t.

Keywords: spectral decomposition, linear RHS, homogeneous linear systems, eigenvalues of the Jacobian

Procedia PDF Downloads 326
14711 Uses for Closed Coal Mines: Construction of Underground Pumped Storage Hydropower Plants

Authors: Javier Menéndez, Jorge Loredo

Abstract:

Large scale energy storage systems (LSESS) such as pumped-storage hydro-power (PSH) are required in the current energy transition towards a low carbon economy by using green energies that produce low levels of greenhouse gas (GHG) emissions. Coal mines are currently being closed in the European Union and their underground facilities may be used to build PSH plants. However, the development of this projects requires the excavation of a network of tunnels and a large cavern that would be used as a powerhouse to install the Francis turbine and motor-generator. The technical feasibility to excavate the powerhouse cavern has been analyzed in the North of Spain. Three-dimensional numerical models have been conducted to analyze the stability considering shale and sandstone rock mass. Total displacements and thickness of plastic zones were examined considering different support systems. Systematic grouted rock bolts and fibre reinforced shotcrete were applied at the cavern walls and roof. The results obtained show that the construction of the powerhouse is feasible applying proper support systems.

Keywords: closed mines, mine water, numerical model, pumped-storage, renewable energies

Procedia PDF Downloads 89
14710 The Effect on Rolling Mill of Waviness in Hot Rolled Steel

Authors: Sunthorn Sittisakuljaroen

Abstract:

The edge waviness in hot rolled steel is a common defect. Variables that effect for such defect include as raw material and machine. These variables are necessary to consider. This research studied the defect of edge waviness for SS 400 of metal sheet manufacture. Defect of metal sheets divided into two groups. The specimens were investigated on chemical composition and mechanical properties to find the difference. The results of investigate showed that not different to a standard significantly. Therefore the roll milled machine for sample need to adjustable rollers for press on metal sheet which was more appropriate to adjustable at both ends.

Keywords: edge waviness, hot rolling steel, metal sheet defect, SS 400, roll leveller

Procedia PDF Downloads 411
14709 Comparison Analysis of Fuzzy Logic Controler Based PV-Pumped Hydro and PV-Battery Storage Systems

Authors: Seada Hussen, Frie Ayalew

Abstract:

Integrating different energy resources, like solar PV and hydro, is used to ensure reliable power to rural communities like Hara village in Ethiopia. Hybrid power system offers power supply for rural villages by providing an alternative supply for the intermittent nature of renewable energy resources. The intermittent nature of renewable energy resources is a challenge to electrifying rural communities in a sustainable manner with solar resources. Major rural villages in Ethiopia are suffering from a lack of electrification, that cause our people to suffer deforestation, travel for long distance to fetch water, and lack good services like clinic and school sufficiently. The main objective of this project is to provide a balanced, stable, reliable supply for Hara village, Ethiopia using solar power with a pumped hydro energy storage system. The design of this project starts by collecting data from villages and taking solar irradiance data from NASA. In addition to this, geographical arrangement and location are also taken into consideration. After collecting this, all data analysis and cost estimation or optimal sizing of the system and comparison of solar with pumped hydro and solar with battery storage system is done using Homer Software. And since solar power only works in the daytime and pumped hydro works at night time and also at night and morning, both load will share to cover the load demand; this need controller designed to control multiple switch and scheduling in this project fuzzy logic controller is used to control this scenario. The result of the simulation shows that solar with pumped hydro energy storage system achieves good results than with a battery storage system since the comparison is done considering storage reliability, cost, storage capacity, life span, and efficiency.

Keywords: pumped hydro storage, solar energy, solar PV, battery energy storage, fuzzy logic controller

Procedia PDF Downloads 71