Search results for: error metrics
2324 An Extensible Software Infrastructure for Computer Aided Custom Monitoring of Patients in Smart Homes
Authors: Ritwik Dutta, Marylin Wolf
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This paper describes the trade-offs and the design from scratch of a self-contained, easy-to-use health dashboard software system that provides customizable data tracking for patients in smart homes. The system is made up of different software modules and comprises a front-end and a back-end component. Built with HTML, CSS, and JavaScript, the front-end allows adding users, logging into the system, selecting metrics, and specifying health goals. The back-end consists of a NoSQL Mongo database, a Python script, and a SimpleHTTPServer written in Python. The database stores user profiles and health data in JSON format. The Python script makes use of the PyMongo driver library to query the database and displays formatted data as a daily snapshot of user health metrics against target goals. Any number of standard and custom metrics can be added to the system, and corresponding health data can be fed automatically, via sensor APIs or manually, as text or picture data files. A real-time METAR request API permits correlating weather data with patient health, and an advanced query system is implemented to allow trend analysis of selected health metrics over custom time intervals. Available on the GitHub repository system, the project is free to use for academic purposes of learning and experimenting, or practical purposes by building on it.Keywords: flask, Java, JavaScript, health monitoring, long-term care, Mongo, Python, smart home, software engineering, webserver
Procedia PDF Downloads 3832323 Design for Error-Proofing Assembly: A Systematic Approach to Prevent Assembly Issues since Early Design Stages, an Industrial Case Study
Authors: Gabriela Estrada, Joaquim Lloveras
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Design for error-proofing assembly is a new DFX approach to prevent assembly issues since early design stages. Assembly issues that can happen during the life phases of a system such as: production, installation, operation, and replacement phases. This prevention is possible by designing the product with poka-yoke or error-proofing characteristics. This approach guide designers to make decisions based on poka-yoke assembly design requirements. As a result of applying these requirements designers are able to create solutions to prevent assembly issues for the product in development stage. This paper integrates the needs to design products in an error proofing way into the systematic approach of design process by Pahl and Beitz. A case study is presented applying this approach.Keywords: poka-yoke, error-proofing, assembly issues, design process, life phases of a system
Procedia PDF Downloads 3692322 Design for Error-Proofing Assembly: A Systematic Approach to Prevent Assembly Issues since Early Design Stages. An Industry Case Study
Authors: Gabriela Estrada, Joaquim Lloveras
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Design for error-proofing assembly is a new DFX approach to prevent assembly issues since early design stages. Assembly issues that can happen during the life phases of a system such as: production, installation, operation and replacement phases. This prevention is possible by designing the product with poka-yoke or error-proofing characteristics. This approach guide designers to make decisions based on poka-yoke assembly design requirements. As a result of applying these requirements designers are able to create solutions to prevent assembly issues for the product in development stage. This paper integrates the needs to design products in an error proofing way into the systematic approach of design process by Pahl and Beitz. A case study is presented applying this approach.Keywords: poka-yoke, error-proofing, assembly issues, design process, life phases of a system
Procedia PDF Downloads 3172321 Correction of Frequent English Writing Errors by Using Coded Indirect Corrective Feedback and Error Treatment: The Case of Reading and Writing English for Academic Purposes II
Authors: Chaiwat Tantarangsee
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The purposes of this study are 1) to study the frequent English writing errors of students registering the course: Reading and Writing English for Academic Purposes II, and 2) to find out the results of writing error correction by using coded indirect corrective feedback and writing error treatments. Samples include 28 2nd year English Major students, Faculty of Education, Suan Sunandha Rajabhat University. Tool for experimental study includes the lesson plan of the course; Reading and Writing English for Academic Purposes II, and tool for data collection includes 4 writing tests of short texts. The research findings disclose that frequent English writing errors found in this course comprise 7 types of grammatical errors, namely Fragment sentence, Subject-verb agreement, Wrong form of verb tense, Singular or plural noun endings, Run-ons sentence, Wrong form of verb pattern and Lack of parallel structure. Moreover, it is found that the results of writing error correction by using coded indirect corrective feedback and error treatment reveal the overall reduction of the frequent English writing errors and the increase of students’ achievement in the writing of short texts with the significance at .05.Keywords: coded indirect corrective feedback, error correction, error treatment, English writing
Procedia PDF Downloads 2982320 User-Perceived Quality Factors for Certification Model of Web-Based System
Authors: Jamaiah H. Yahaya, Aziz Deraman, Abdul Razak Hamdan, Yusmadi Yah Jusoh
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One of the most essential issues in software products is to maintain it relevancy to the dynamics of the user’s requirements and expectation. Many studies have been carried out in quality aspect of software products to overcome these problems. Previous software quality assessment models and metrics have been introduced with strengths and limitations. In order to enhance the assurance and buoyancy of the software products, certification models have been introduced and developed. From our previous experiences in certification exercises and case studies collaborating with several agencies in Malaysia, the requirements for user based software certification approach is identified and demanded. The emergence of social network applications, the new development approach such as agile method and other varieties of software in the market have led to the domination of users over the software. As software become more accessible to the public through internet applications, users are becoming more critical in the quality of the services provided by the software. There are several categories of users in web-based systems with different interests and perspectives. The classifications and metrics are identified through brain storming approach with includes researchers, users and experts in this area. The new paradigm in software quality assessment is the main focus in our research. This paper discusses the classifications of users in web-based software system assessment and their associated factors and metrics for quality measurement. The quality model is derived based on IEEE structure and FCM model. The developments are beneficial and valuable to overcome the constraints and improve the application of software certification model in future.Keywords: software certification model, user centric approach, software quality factors, metrics and measurements, web-based system
Procedia PDF Downloads 3962319 The Omani Learner of English Corpus: Source and Tools
Authors: Anood Al-Shibli
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Designing a learner corpus is not an easy task to accomplish because dealing with learners’ language has many variables which might affect the results of any study based on learners’ language production (spoken and written). Also, it is very essential to systematically design a learner corpus especially when it is aimed to be a reference to language research. Therefore, designing the Omani Learner Corpus (OLEC) has undergone many explicit and systematic considerations. These criteria can be regarded as the foundation to design any learner corpus to be exploited effectively in language use and language learning studies. Added to that, OLEC is manually error-annotated corpus. Error-annotation in learner corpora is very essential; however, it is time-consuming and prone to errors. Consequently, a navigating tool is designed to help the annotators to insert errors’ codes in order to make the error-annotation process more efficient and consistent. To assure accuracy, error annotation procedure is followed to annotate OLEC and some preliminary findings are noted. One of the main results of this procedure is creating an error-annotation system based on the Omani learners of English language production. Because OLEC is still in the first stages, the primary findings are related to only one level of proficiency and one error type which is verb related errors. It is found that Omani learners in OLEC has the tendency to have more errors in forming the verb and followed by problems in agreement of verb. Comparing the results to other error-based studies indicate that the Omani learners tend to have basic verb errors which can found in lower-level of proficiency. To this end, it is essential to admit that examining learners’ errors can give insights to language acquisition and language learning and most errors do not happen randomly but they occur systematically among language learners.Keywords: error-annotation system, error-annotation manual, learner corpora, verbs related errors
Procedia PDF Downloads 1342318 A Multi-Objective Methodology for Selecting Lean Initiatives in Modular Construction Companies
Authors: Saba Shams Bidhendi, Steven Goh, Andrew Wandel
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The implementation of lean manufacturing initiatives has produced significant impacts in improving operational performance and reducing manufacturing wastes in the production process. However, selecting an appropriate set of lean strategies is critical to avoid misapplication of the lean manufacturing techniques and consequential increase in non-value-adding activities. To the author’s best knowledge, there is currently no methodology to select lean strategies that considers their impacts on manufacturing wastes and performance metrics simultaneously. In this research, a multi-objective methodology is proposed that suggests an appropriate set of lean initiatives based on their impacts on performance metrics and manufacturing wastes and within manufacturers’ resource limitation. The proposed methodology in this research suggests the best set of lean initiatives for implementation that have highest impacts on identified critical performance metrics and manufacturing wastes. Therefore, manufacturers can assure that implementing suggested lean tools improves their production performance and reduces manufacturing wastes at the same time. A case study was conducted to show the effectiveness and validate the proposed model and methodologies.Keywords: lean manufacturing, lean strategies, manufacturing wastes, manufacturing performance, optimisation, decision making
Procedia PDF Downloads 1872317 Reduced Complexity of ML Detection Combined with DFE
Authors: Jae-Hyun Ro, Yong-Jun Kim, Chang-Bin Ha, Hyoung-Kyu Song
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In multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems, many detection schemes have been developed to improve the error performance and to reduce the complexity. Maximum likelihood (ML) detection has optimal error performance but it has very high complexity. Thus, this paper proposes reduced complexity of ML detection combined with decision feedback equalizer (DFE). The error performance of the proposed detection scheme is higher than the conventional DFE. But the complexity of the proposed scheme is lower than the conventional ML detection.Keywords: detection, DFE, MIMO-OFDM, ML
Procedia PDF Downloads 6052316 Examining the Performance of Three Multiobjective Evolutionary Algorithms Based on Benchmarking Problems
Authors: Konstantinos Metaxiotis, Konstantinos Liagkouras
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The objective of this study is to examine the performance of three well-known multiobjective evolutionary algorithms for solving optimization problems. The first algorithm is the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), the second one is the Strength Pareto Evolutionary Algorithm 2 (SPEA-2), and the third one is the Multiobjective Evolutionary Algorithms based on decomposition (MOEA/D). The examined multiobjective algorithms are analyzed and tested on the ZDT set of test functions by three performance metrics. The results indicate that the NSGA-II performs better than the other two algorithms based on three performance metrics.Keywords: MOEAs, multiobjective optimization, ZDT test functions, evolutionary algorithms
Procedia PDF Downloads 4622315 Task Space Synchronization Control of Multi-Robot Arms with Position Synchronous Method
Authors: Zijian Zhang, Yangyang Dong
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Synchronization is of great importance to ensure the multi-arm robot to complete the task. Therefore, a synchronous controller is designed to coordinate task space motion of the multi-arm in the paper. The position error, the synchronous position error, and the coupling position error are all considered in the controller. Besides, an adaptive control method is used to adjust parameters of the controller to improve the effectiveness of coordinated control performance. Simulation in the Matlab shows the effectiveness of the method. At last, a robot experiment platform with two 7-DOF (Degree of Freedom) robot arms has been established and the synchronous controller simplified to control dual-arm robot has been validated on the experimental set-up. Experiment results show the position error decreased 10% and the corresponding frequency is also greatly improved.Keywords: synchronous control, space robot, task space control, multi-arm robot
Procedia PDF Downloads 1562314 An Evaluation and Guidance for mHealth Apps
Authors: Tareq Aljaber
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The number of mobile health apps is growing at a fast frequency as it's nearly doubled in a year between 2015 and 2016. Though, there is a lack of an effective evaluation framework to verify the usability and reliability of mobile phone health education applications which would help saving time and effort for the numerous user groups. This abstract describing a framework for evaluating mobile applications in specifically mobile health education applications, along with a guidance select tool to assist different users to select the most suitable mobile health education apps. The effective framework outcome is intended to meet the requirements and needs of the different stakeholder groups additionally to enhancing the development of mobile health education applications with software engineering approaches, by producing new and more effective techniques to evaluate such software. This abstract highlights the significance and consequences of mobile health education apps, before focusing the light on the required to create an effective evaluation framework for these apps. An explanation of the effective evaluation framework is going to be delivered in the abstract, beside with some specific evaluation metrics: an efficient hybrid of selected heuristic evaluation (HE) and usability evaluation (UE) metrics to enable the determination of the usefulness and usability of health education mobile apps. Moreover, an explanation of the qualitative and quantitative outcomes for the effective evaluation framework was accomplished using Epocrates mobile phone app in addition to some other mobile phone apps. This proposed framework-An Evaluation Framework for Mobile Health Education Apps-consists of a hybrid of 5 metrics designated from a larger set in usability evaluation and heuristic evaluation, illuminated grounded on 15 unstructured interviews from software developers (SD), health professionals (HP) and patients (P). These five metrics corresponding to explicit facets of usability recognised through a requirements analysis of typical stakeholders of mobile health apps. These five hybrid selected metrics were scattered across 24 specific questionnaire questions, which are available on request from first author. This questionnaire has been sent to 81 participants distributed in three sets of stakeholders from software developers (SD), health professionals (HP) and patients/general users (P/GU) on the purpose of ranking three sets of mobile health education applications. Finally, the outcomes from the questionnaire data helped us to approach our aims which are finding the profile for different stakeholders, finding the profile for different mobile health educations application packages, ranking different mobile health education application and guide us to build the select guidance too which is apart from the Evaluation Framework for Mobile Health Education Apps.Keywords: evaluation framework, heuristic evaluation, usability evaluation, metrics
Procedia PDF Downloads 3972313 A Combined Error Control with Forward Euler Method for Dynamical Systems
Authors: R. Vigneswaran, S. Thilakanathan
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Variable time-stepping algorithms for solving dynamical systems performed poorly for long time computations which pass close to a fixed point. To overcome this difficulty, several authors considered phase space error controls for numerical simulation of dynamical systems. In one generalized phase space error control, a step-size selection scheme was proposed, which allows this error control to be incorporated into the standard adaptive algorithm as an extra constraint at negligible extra computational cost. For this generalized error control, it was already analyzed the forward Euler method applied to the linear system whose coefficient matrix has real and negative eigenvalues. In this paper, this result was extended to the linear system whose coefficient matrix has complex eigenvalues with negative real parts. Some theoretical results were obtained and numerical experiments were carried out to support the theoretical results.Keywords: adaptivity, fixed point, long time simulations, stability, linear system
Procedia PDF Downloads 3072312 Parameter Estimation of False Dynamic EIV Model with Additive Uncertainty
Authors: Dalvinder Kaur Mangal
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For the past decade, noise corrupted output measurements have been a fundamental research problem to be investigated. On the other hand, the estimation of the parameters for linear dynamic systems when also the input is affected by noise is recognized as more difficult problem which only recently has received increasing attention. Representations where errors or measurement noises/disturbances are present on both the inputs and outputs are usually called errors-in-variables (EIV) models. These disturbances may also have additive effects which are also considered in this paper. Parameter estimation of false EIV problem using equation error, output error and iterative prefiltering identification schemes with and without additive uncertainty, when only the output observation is corrupted by noise has been dealt in this paper. The comparative study of these three schemes has also been carried out.Keywords: errors-in-variable (EIV), false EIV, equation error, output error, iterative prefiltering, Gaussian noise
Procedia PDF Downloads 4812311 Error Analysis: Examining Written Errors of English as a Second Language (ESL) Spanish Speaking Learners
Authors: Maria Torres
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After the acknowledgment of contrastive analysis, Pit Coder’s establishment of error analysis revolutionized the way instructors analyze and examine students’ writing errors. One question that relates to error analysis with speakers of a first language, in this case, Spanish, who are learning a second language (English), is the type of errors that these learners make along with the causes of these errors. Many studies have looked at the way the native tongue influences second language acquisition, but this method does not take into account other possible sources of students’ errors. This paper examines writing samples from an advanced ESL class whose first language is Spanish at non-profit organization, Learning Quest Stanislaus Literacy Center. Through error analysis, errors in the students’ writing were identified, described, and classified. The purpose of this paper was to discover the type and origin of their errors which generated appropriate treatments. The results in this paper show that the most frequent errors in the advanced ESL students’ writing pertain to interlanguage and a small percentage from an intralanguage source. Lastly, the least type of errors were ones that originate from negative transfer. The results further solidify the idea that there are other errors and sources of errors to account for rather than solely focusing on the difference between the students’ mother and target language. This presentation will bring to light some strategies and techniques that address the issues found in this research. Taking into account the amount of error pertaining to interlanguage, an ESL teacher should provide metalinguistic awareness of the students’ errors.Keywords: error analysis, ESL, interlanguage, intralangauge
Procedia PDF Downloads 2942310 A Soft Error Rates (SER) Evaluation Method of Combinational Logic Circuit Based on Linear Energy Transfers
Authors: Man Li, Wanting Zhou, Lei Li
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Communication stability is the primary concern of communication satellites. Communication satellites are easily affected by particle radiation to generate single event effects (SEE), which leads to soft errors (SE) of the combinational logic circuit. The existing research on soft error rates (SER) of the combined logic circuit is mostly based on the assumption that the logic gates being bombarded have the same pulse width. However, in the actual radiation environment, the pulse widths of the logic gates being bombarded are different due to different linear energy transfers (LET). In order to improve the accuracy of SER evaluation model, this paper proposes a soft error rate evaluation method based on LET. In this paper, the authors analyze the influence of LET on the pulse width of combinational logic and establish the pulse width model based on the LET. Based on this model, the error rate of test circuit ISCAS'85 is calculated. The effectiveness of the model is proved by comparing it with previous experiments.Keywords: communication satellite, pulse width, soft error rates, LET
Procedia PDF Downloads 1642309 Gender Effects in EEG-Based Functional Brain Networks
Authors: Mahdi Jalili
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Functional connectivity in the human brain can be represented as a network using electroencephalography (EEG) signals. Network representation of EEG time series can be an efficient vehicle to understand the underlying mechanisms of brain function. Brain functional networks – whose nodes are brain regions and edges correspond to functional links between them – are characterized by neurobiologically meaningful graph theory metrics. This study investigates the degree to which graph theory metrics are sex dependent. To this end, EEGs from 24 healthy female subjects and 21 healthy male subjects were recorded in eyes-closed resting state conditions. The connectivity matrices were extracted using correlation analysis and were further binarized to obtain binary functional networks. Global and local efficiency measures – as graph theory metrics– were computed for the extracted networks. We found that male brains have a significantly greater global efficiency (i.e., global communicability of the network) across all frequency bands for a wide range of cost values in both hemispheres. Furthermore, for a range of cost values, female brains showed significantly greater right-hemispheric local efficiency (i.e., local connectivity) than male brains.Keywords: EEG, brain, functional networks, network science, graph theory
Procedia PDF Downloads 4372308 Influence of Error Correction Codes on the Quality of Optical Broadband Connections
Authors: Mouna Hemdi, Jamel bel Hadj Tahar
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The increasing development of multimedia applications requiring the simultaneous transport of several different services contributes to the evolution of the need for very high-speed network. In this paper, we propose an effective solution to achieve the very high speed while retaining elements of the optical transmission channel. So our study focuses on error correcting codes that aim for quality improvement on duty. We present a comparison of the quality of service for single channels and integrating the code BCH, RS and LDPC in order to find the best code in the different conditions of the transmission.Keywords: code error correction, high speed broadband, optical transmission, information systems security
Procedia PDF Downloads 3842307 A Short-Baseline Dual-Antenna BDS/MEMS-IMU Integrated Navigation System
Authors: Tijing Cai, Qimeng Xu, Daijin Zhou
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This paper puts forward a short-baseline dual-antenna BDS/MEMS-IMU integrated navigation, constructs the carrier phase double difference model of BDS (BeiDou Navigation Satellite System), and presents a 2-position initial orientation method on BDS. The Extended Kalman-filter has been introduced for the integrated navigation system. The differences between MEMS-IMU and BDS position, velocity and carrier phase indications are used as measurements. To show the performance of the short-baseline dual-antenna BDS/MEMS-IMU integrated navigation system, the experiment results show that the position error is less than 1m, the pitch angle error and roll angle error are less than 0.1°, and the heading angle error is about 1°.Keywords: MEMS-IMU (Micro-Electro-Mechanical System Inertial Measurement Unit), BDS (BeiDou Navigation Satellite System), dual-antenna, integrated navigation
Procedia PDF Downloads 1852306 Weighted G2 Multi-Degree Reduction of Bezier Curves
Authors: Salisu ibrahim, Abdalla Rababah
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In this research, we use Weighted G2-Multi-degree reduction of Bezier curve of degree n to a Bezier curve of degree m, m < n. The degree reduction of Bezier curves is used to represent a given Bezier curve of n by a Bezier curve of degree m, m < n. Exact degree reduction is not possible, and degree reduction is approximate process in nature. We derive a weighted degree reducing method that is geometrically continuous at the end points. Different norms will be considered, several error minimizations will be given. The proposed methods produce error function that are less than the errors of existing methods.Keywords: Bezier curves, multiple degree reduction, geometric continuity, error function
Procedia PDF Downloads 4752305 Does sustainability disclosure improve analysts’ forecast accuracy Evidence from European banks
Authors: Albert Acheampong, Tamer Elshandidy
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We investigate the extent to which sustainability disclosure from the narrative section of European banks’ annual reports improves analyst forecast accuracy. We capture sustainability disclosure using a machine learning approach and use forecast error to proxy analyst forecast accuracy. Our results suggest that sustainability disclosure significantly improves analyst forecast accuracy by reducing the forecast error. In a further analysis, we also find that the induction of Directive 2014/95/European Union (EU) is associated with increased disclosure content, which then reduces forecast error. Collectively, our results suggest that sustainability disclosure improves forecast accuracy, and the induction of the new EU directive strengthens this improvement. These results hold after several further and robustness analyses. Our findings have implications for market participants and policymakers.Keywords: sustainability disclosure, machine learning, analyst forecast accuracy, forecast error, European banks, EU directive
Procedia PDF Downloads 642304 A Use Case-Oriented Performance Measurement Framework for AI and Big Data Solutions in the Banking Sector
Authors: Yassine Bouzouita, Oumaima Belghith, Cyrine Zitoun, Charles Bonneau
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Performance measurement framework (PMF) is an essential tool in any organization to assess the performance of its processes. It guides businesses to stay on track with their objectives and benchmark themselves from the market. With the growing trend of the digital transformation of business processes, led by innovations in artificial intelligence (AI) & Big Data applications, developing a mature system capable of capturing the impact of digital solutions across different industries became a necessity. Based on the conducted research, no such system has been developed in academia nor the industry. In this context, this paper covers a variety of methodologies on performance measurement, overviews the major AI and big data applications in the banking sector, and covers an exhaustive list of relevant metrics. Consequently, this paper is of interest to both researchers and practitioners. From an academic perspective, it offers a comparative analysis of the reviewed performance measurement frameworks. From an industry perspective, it offers exhaustive research, from market leaders, of the major applications of AI and Big Data technologies, across the different departments of an organization. Moreover, it suggests a standardized classification model with a well-defined structure of intelligent digital solutions. The aforementioned classification is mapped to a centralized library that contains an indexed collection of potential metrics for each application. This library is arranged in a manner that facilitates the rapid search and retrieval of relevant metrics. This proposed framework is meant to guide professionals in identifying the most appropriate AI and big data applications that should be adopted. Furthermore, it will help them meet their business objectives through understanding the potential impact of such solutions on the entire organization.Keywords: AI and Big Data applications, impact assessment, metrics, performance measurement
Procedia PDF Downloads 1942303 Performance Analysis of Artificial Neural Network with Decision Tree in Prediction of Diabetes Mellitus
Authors: J. K. Alhassan, B. Attah, S. Misra
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Human beings have the ability to make logical decisions. Although human decision - making is often optimal, it is insufficient when huge amount of data is to be classified. medical dataset is a vital ingredient used in predicting patients health condition. In other to have the best prediction, there calls for most suitable machine learning algorithms. This work compared the performance of Artificial Neural Network (ANN) and Decision Tree Algorithms (DTA) as regards to some performance metrics using diabetes data. The evaluations was done using weka software and found out that DTA performed better than ANN. Multilayer Perceptron (MLP) and Radial Basis Function (RBF) were the two algorithms used for ANN, while RegTree and LADTree algorithms were the DTA models used. The Root Mean Squared Error (RMSE) of MLP is 0.3913,that of RBF is 0.3625, that of RepTree is 0.3174 and that of LADTree is 0.3206 respectively.Keywords: artificial neural network, classification, decision tree algorithms, diabetes mellitus
Procedia PDF Downloads 4042302 Quantifying Firm-Level Environmental Innovation Performance: Determining the Sustainability Value of Patent Portfolios
Authors: Maximilian Elsen, Frank Tietze
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The development and diffusion of green technologies are crucial for achieving our ambitious climate targets. The Paris Agreement commits its members to develop strategies for achieving net zero greenhouse gas emissions by the second half of the century. Governments, executives, and academics are working on net-zero strategies and the business of rating organisations on their environmental, social and governance (ESG) performance has grown tremendously in its public interest. ESG data is now commonly integrated into traditional investment analysis and an important factor in investment decisions. Creating these metrics, however, is inherently challenging as environmental and social impacts are hard to measure and uniform requirements on ESG reporting are lacking. ESG metrics are often incomplete and inconsistent as they lack fully accepted reporting standards and are often of qualitative nature. This study explores the use of patent data for assessing the environmental performance of companies by focusing on their patented inventions in the space of climate change mitigation and adaptation technologies (CCMAT). The present study builds on the successful identification of CCMAT patents. In this context, the study adopts the Y02 patent classification, a fully cross-sectional tagging scheme that is fully incorporated in the Cooperative Patent Classification (CPC), to identify Climate Change Adaptation Technologies. The Y02 classification was jointly developed by the European Patent Office (EPO) and the United States Patent and Trademark Office (USPTO) and provides means to examine technologies in the field of mitigation and adaptation to climate change across relevant technologies. This paper develops sustainability-related metrics for firm-level patent portfolios. We do so by adopting a three-step approach. First, we identify relevant CCMAT patents based on their classification as Y02 CPC patents. Second, we examine the technological strength of the identified CCMAT patents by including more traditional metrics from the field of patent analytics while considering their relevance in the space of CCMAT. Such metrics include, among others, the number of forward citations a patent receives, as well as the backward citations and the size of the focal patent family. Third, we conduct our analysis on a firm level by sector for a sample of companies from different industries and compare the derived sustainability performance metrics with the firms’ environmental and financial performance based on carbon emissions and revenue data. The main outcome of this research is the development of sustainability-related metrics for firm-level environmental performance based on patent data. This research has the potential to complement existing ESG metrics from an innovation perspective by focusing on the environmental performance of companies and putting them into perspective to conventional financial performance metrics. We further provide insights into the environmental performance of companies on a sector level. This study has implications of both academic and practical nature. Academically, it contributes to the research on eco-innovation and the literature on innovation and intellectual property (IP). Practically, the study has implications for policymakers by deriving meaningful insights into the environmental performance from an innovation and IP perspective. Such metrics are further relevant for investors and potentially complement existing ESG data.Keywords: climate change mitigation, innovation, patent portfolios, sustainability
Procedia PDF Downloads 792301 A Variant of Newton's Method with Free Second-Order Derivative
Authors: Young Hee Geum
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In this paper, we present the iterative method and determine the control parameters to converge cubically for solving nonlinear equations. In addition, we derive the asymptotic error constant.Keywords: asymptotic error constant, iterative method, multiple root, root-finding, order of convergent
Procedia PDF Downloads 2862300 Impact Analysis Based on Change Requirement Traceability in Object Oriented Software Systems
Authors: Sunil Tumkur Dakshinamurthy, Mamootil Zachariah Kurian
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Change requirement traceability in object oriented software systems is one of the challenging areas in research. We know that the traces between links of different artifacts are to be automated or semi-automated in the software development life cycle (SDLC). The aim of this paper is discussing and implementing aspects of dynamically linking the artifacts such as requirements, high level design, code and test cases through the Extensible Markup Language (XML) or by dynamically generating Object Oriented (OO) metrics. Also, non-functional requirements (NFR) aspects such as stability, completeness, clarity, validity, feasibility and precision are discussed. We discuss this as a Fifth Taxonomy, which is a system vulnerability concern.Keywords: artifacts, NFRs, OO metrics, SDLC, XML
Procedia PDF Downloads 3322299 Developing a Machine Learning-based Cost Prediction Model for Construction Projects using Particle Swarm Optimization
Authors: Soheila Sadeghi
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Accurate cost prediction is essential for effective project management and decision-making in the construction industry. This study aims to develop a cost prediction model for construction projects using Machine Learning techniques and Particle Swarm Optimization (PSO). The research utilizes a comprehensive dataset containing project cost estimates, actual costs, resource details, and project performance metrics from a road reconstruction project. The methodology involves data preprocessing, feature selection, and the development of an Artificial Neural Network (ANN) model optimized using PSO. The study investigates the impact of various input features, including cost estimates, resource allocation, and project progress, on the accuracy of cost predictions. The performance of the optimized ANN model is evaluated using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared. The results demonstrate the effectiveness of the proposed approach in predicting project costs, outperforming traditional benchmark models. The feature selection process identifies the most influential variables contributing to cost variations, providing valuable insights for project managers. However, this study has several limitations. Firstly, the model's performance may be influenced by the quality and quantity of the dataset used. A larger and more diverse dataset covering different types of construction projects would enhance the model's generalizability. Secondly, the study focuses on a specific optimization technique (PSO) and a single Machine Learning algorithm (ANN). Exploring other optimization methods and comparing the performance of various ML algorithms could provide a more comprehensive understanding of the cost prediction problem. Future research should focus on several key areas. Firstly, expanding the dataset to include a wider range of construction projects, such as residential buildings, commercial complexes, and infrastructure projects, would improve the model's applicability. Secondly, investigating the integration of additional data sources, such as economic indicators, weather data, and supplier information, could enhance the predictive power of the model. Thirdly, exploring the potential of ensemble learning techniques, which combine multiple ML algorithms, may further improve cost prediction accuracy. Additionally, developing user-friendly interfaces and tools to facilitate the adoption of the proposed cost prediction model in real-world construction projects would be a valuable contribution to the industry. The findings of this study have significant implications for construction project management, enabling proactive cost estimation, resource allocation, budget planning, and risk assessment, ultimately leading to improved project performance and cost control. This research contributes to the advancement of cost prediction techniques in the construction industry and highlights the potential of Machine Learning and PSO in addressing this critical challenge. However, further research is needed to address the limitations and explore the identified future research directions to fully realize the potential of ML-based cost prediction models in the construction domain.Keywords: cost prediction, construction projects, machine learning, artificial neural networks, particle swarm optimization, project management, feature selection, road reconstruction
Procedia PDF Downloads 422298 Channel Estimation/Equalization with Adaptive Modulation and Coding over Multipath Faded Channels for WiMAX
Authors: B. Siva Kumar Reddy, B. Lakshmi
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WiMAX has adopted an Adaptive Modulation and Coding (AMC) in OFDM to endure higher data rates and error free transmission. AMC schemes employ the Channel State Information (CSI) to efficiently utilize the channel and maximize the throughput and for better spectral efficiency. This CSI has given to the transmitter by the channel estimators. In this paper, LSE (Least Square Error) and MMSE (Minimum Mean square Error) estimators are suggested and BER (Bit Error Rate) performance has been analyzed. Channel equalization is also integrated with with AMC-OFDM system and presented with Constant Modulus Algorithm (CMA) and Least Mean Square (LMS) algorithms with convergence rates analysis. Simulation results proved that increment in modulation scheme size causes to improvement in throughput along with BER value. There is a trade-off among modulation size, throughput, BER value and spectral efficiency. Results also reported the requirement of channel estimation and equalization in high data rate systems.Keywords: AMC, CSI, CMA, OFDM, OFDMA, WiMAX
Procedia PDF Downloads 3892297 Analytical Performance of Cobas C 8000 Analyzer Based on Sigma Metrics
Authors: Sairi Satari
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Introduction: Six-sigma is a metric that quantifies the performance of processes as a rate of Defects-Per-Million Opportunities. Sigma methodology can be applied in chemical pathology laboratory for evaluating process performance with evidence for process improvement in quality assurance program. In the laboratory, these methods have been used to improve the timeliness of troubleshooting, reduce the cost and frequency of quality control and minimize pre and post-analytical errors. Aim: The aim of this study is to evaluate the sigma values of the Cobas 8000 analyzer based on the minimum requirement of the specification. Methodology: Twenty-one analytes were chosen in this study. The analytes were alanine aminotransferase (ALT), albumin, alkaline phosphatase (ALP), Amylase, aspartate transaminase (AST), total bilirubin, calcium, chloride, cholesterol, HDL-cholesterol, creatinine, creatinine kinase, glucose, lactate dehydrogenase (LDH), magnesium, potassium, protein, sodium, triglyceride, uric acid and urea. Total error was obtained from Clinical Laboratory Improvement Amendments (CLIA). The Bias was calculated from end cycle report of Royal College of Pathologists of Australasia (RCPA) cycle from July to December 2016 and coefficient variation (CV) from six-month internal quality control (IQC). The sigma was calculated based on the formula :Sigma = (Total Error - Bias) / CV. The analytical performance was evaluated based on the sigma, sigma > 6 is world class, sigma > 5 is excellent, sigma > 4 is good and sigma < 4 is satisfactory and sigma < 3 is poor performance. Results: Based on the calculation, we found that, 96% are world class (ALT, albumin, ALP, amylase, AST, total bilirubin, cholesterol, HDL-cholesterol, creatinine, creatinine kinase, glucose, LDH, magnesium, potassium, triglyceride and uric acid. 14% are excellent (calcium, protein and urea), and 10% ( chloride and sodium) require more frequent IQC performed per day. Conclusion: Based on this study, we found that IQC should be performed frequently for only Chloride and Sodium to ensure accurate and reliable analysis for patient management.Keywords: sigma matrics, analytical performance, total error, bias
Procedia PDF Downloads 1642296 Urban Landscape Composition and Configuration Dynamics and Expansion of Hawassa City Analysis, Ethiopia Using Satellite Images and Spatial Metrics Approach
Authors: Berhanu Keno Terfa
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To understand the consequences of urbanization, accurate, and long-term representation of urban dynamics is essential. Remote sensing data from various multi-temporal satellite images viz., TM (1987), TM (1995), ETM+ (2005) and OLI (2017) were used. An integrated method, landscape metrics, built-up density, and urban growth type analysis were employed to analyze the pattern, process, and overall growth status in the city. The result showed that the built-up area had increased by 541.3% between 1987 and 2017, at an average annual increment of 8.9%. The area of urban expansion in a city has tripled during the 2005-2017 period as compared to 187- 1995. The major growth took place in the east and southeast directions during 1987–1995 period, whereas predominant built-up development was observed in south and southeast direction during 1995–2017 period. The analysis using landscape metrics and urban typologies showed that Hawassa experienced a fragmented and irregular spatiotemporal urban growth patterns, mostly by extension, suggesting a strong tendency towards sprawl in the past three decades.Keywords: Hawassa, spatial patterns, remote sensing, multi-temporal, urban sprawl
Procedia PDF Downloads 1402295 A Sectional Control Method to Decrease the Accumulated Survey Error of Tunnel Installation Control Network
Authors: Yinggang Guo, Zongchun Li
Abstract:
In order to decrease the accumulated survey error of tunnel installation control network of particle accelerator, a sectional control method is proposed. Firstly, the accumulation rule of positional error with the length of the control network is obtained by simulation calculation according to the shape of the tunnel installation-control-network. Then, the RMS of horizontal positional precision of tunnel backbone control network is taken as the threshold. When the accumulated error is bigger than the threshold, the tunnel installation control network should be divided into subsections reasonably. On each segment, the middle survey station is taken as the datum for independent adjustment calculation. Finally, by taking the backbone control points as faint datums, the weighted partial parameters adjustment is performed with the adjustment results of each segment and the coordinates of backbone control points. The subsections are jointed and unified into the global coordinate system in the adjustment process. An installation control network of the linac with a length of 1.6 km is simulated. The RMS of positional deviation of the proposed method is 2.583 mm, and the RMS of the difference of positional deviation between adjacent points reaches 0.035 mm. Experimental results show that the proposed sectional control method can not only effectively decrease the accumulated survey error but also guarantee the relative positional precision of the installation control network. So it can be applied in the data processing of tunnel installation control networks, especially for large particle accelerators.Keywords: alignment, tunnel installation control network, accumulated survey error, sectional control method, datum
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