Towards an Early Software Estimation Using Log-Linear Regression and a Multilayer Perceptron Model

Software estimation is a tedious and daunting task in project management and software development. Software estimators are notorious in predicting software effort and they have been struggling in the past decades to provide new models to enhance software estimation. The most critical and crucial part of software estimation is when estimation is required in the early stages of the software life cycle where the problem to be solved has not yet been completely revealed. This paper presents a novel log-linear regression model based on the use case point model (UCP) to calculate the software effort based on use case diagrams. A fuzzy logic approach is used to calibrate the productivity factor in the regression model. Moreover, a multilayer perceptron (MLP) neural network model was developed to predict software effortbased on the software size and team productivity. Experiments show that the proposed approach outperforms the original UCP model. Furthermore, a comparison between the MLP and log-linear regression models was conducted based on the size of the projects. Results demonstrate that the MLP model can surpass the regression model when small projects are used, but the log-linear regression model gives better results when estimating larger projects

Estimation in high dimensions: a geometric perspective

This tutorial provides an exposition of a flexible geometric framework for high dimensional estimation problems with constraints. The tutorial develops geometric intuition about high dimensional sets, justifies it with some results of asymptotic convex geometry, and demonstrates connections between geometric results and estimation problems. The theory is illustrated with applications to sparse recovery, matrix completion, quantization, linear and logistic regression and generalized linear models.Comment: 56 pages, 9 figures. Multiple minor change

Enhancing Use Case Points Estimation Method Using Soft Computing Techniques

Software estimation is a crucial task in software engineering. Software estimation encompasses cost, effort, schedule, and size. The importance of software estimation becomes critical in the early stages of the software life cycle when the details of software have not been revealed yet. Several commercial and non-commercial tools exist to estimate software in the early stages. Most software effort estimation methods require software size as one of the important metric inputs and consequently, software size estimation in the early stages becomes essential. One of the approaches that has been used for about two decades in the early size and effort estimation is called use case points. Use case points method relies on the use case diagram to estimate the size and effort of software projects. Although the use case points method has been widely used, it has some limitations that might adversely affect the accuracy of estimation. This paper presents some techniques using fuzzy logic and neural networks to improve the accuracy of the use case points method. Results showed that an improvement up to 22% can be obtained using the proposed approach

Fast, non-monte-carlo estimation of transient performance variation due to device mismatch

This paper describes an efficient way of simulating the effects of device random mismatch on circuit transient characteristics, such as variations in delay or in frequency. The proposed method models DC random offsets as equivalent AC pseudo-noises and leverages the fast, linear periodically time-varying (LPTV) noise analysis available from RF circuit simulators. Therefore, the method can be considered as an extension to DC match analysis and offers a large speed-up compared to the traditional Monte-Carlo analysis. Although the assumed linear perturbation model is valid only for small variations, it enables easy ways to estimate correlations among variations and identify the most sensitive design parameters to mismatch, all at no additional simulation cost. Three benchmarks measuring the variations in the input offset voltage of a clocked comparator, the delay of a logic path, and the frequency of an oscillator demonstrate the speed improvement of about 100-1000x compared to a 1000-point Monte-Carlo method

a systematic analysis from the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury

Funding Information: Countries provided feedback on the estimates through WHO's consultation of its 194 Member States. We specially acknowledge the ILO for its strategic contributions, as well as its sharing of data and contributions to the production of the estimates. Eurostat produced and shared the transition probabilities for exposure to UVR assigned via proxy of occupation for 27 countries in the European Region. Dr Yuka Ujita (ILO) and then Dr Halim Hamzaoui (ILO) were the ILO focal point for the WHO/ILO Joint Estimates. Marion McFeedy (consultant to the ILO) contributed to initial database development, and Dr Bochen Cao (WHO) shared WHO Global Health Estimates. Dr Claudine Backes (WHO) and Dr Emilie van Deventer (WHO) contributed to the early development of the estimation approach. Jessica CY Ho (WHO), Wahyu R Mahanani (WHO), Dr Bálint Náfrádi (ILO), Dr Annette M Prüss (WHO) and Dr Yuka Ujita provided feedback on an earlier version of the manuscript. Dr Ivan D Ivanov (WHO), Nancy Leppink (ILO), Franklin Muchiri (ILO), Dr Maria P Neira (WHO), Vera L Isaac Paquete-Perdigão (ILO) and Joaquim P Pintado Nunes (ILO) contributed to the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury. Dr Maria P Neira and Vera L Isaac Paquete-Perdigão provided overall guidance. Funding Information: This modelling study was prepared with financial support to WHO from: the National Institute for Occupational Safety and Health of the Centers for Disease Control and Prevention of the United States of America (Grant 1E11OH0010676-02, Grant 6NE11OH010461-02-01 and Grant 5NE11OH010461-03-00); the German Federal Ministry of Health (BMG Germany) under the BMG-WHO Collaboration Programme 2020–2023 (WHO specified award ref. 70672); and the Spanish Agency for International Cooperation (AECID) (WHO specified award ref. 71208). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Publisher Copyright: © 2023 International Labour Organization, World Health OrganizationBackground: A World Health Organization (WHO) and International Labour Organization (ILO) systematic review reported sufficient evidence for higher risk of non-melanoma skin cancer (NMSC) amongst people occupationally exposed to solar ultraviolet radiation (UVR). This article presents WHO/ILO Joint Estimates of global, regional, national and subnational occupational exposures to UVR for 195 countries/areas and the global, regional and national attributable burdens of NMSC for 183 countries, by sex and age group, for the years 2000, 2010 and 2019. Methods: We calculated population-attributable fractions (PAFs) from estimates of the population occupationally exposed to UVR and the risk ratio for NMSC from the WHO/ILO systematic review. Occupational exposure to UVR was modelled via proxy of occupation with outdoor work, using 166 million observations from 763 cross-sectional surveys for 96 countries/areas. Attributable NMSC burden was estimated by applying the PAFs to WHO's estimates of the total NMSC burden. Measures of inequality were calculated. Results: Globally in 2019, 1.6 billion workers (95 % uncertainty range [UR] 1.6–1.6) were occupationally exposed to UVR, or 28.4 % (UR 27.9–28.8) of the working-age population. The PAFs were 29.0 % (UR 24.7–35.0) for NMSC deaths and 30.4 % (UR 29.0–31.7) for disability-adjusted life years (DALYs). Attributable NMSC burdens were 18,960 deaths (UR 18,180–19,740) and 0.5 million DALYs (UR 0.4–0.5). Men and older age groups carried larger burden. Over 2000–2019, attributable deaths and DALYs almost doubled. Conclusions: WHO and the ILO estimate that occupational exposure to UVR is common and causes substantial, inequitable and growing attributable burden of NMSC. Governments must protect outdoor workers from hazardous exposure to UVR and attributable NMSC burden and inequalities.publishersversionpublishe

Estimation of Percentage on Malnutrition Occurrences in East Java Using Geographically Weighted Regression Model

The Province of East Java has its own characteristics that differentiate it from any other regions. Dissimilarities in characteristics of a region may encompass issues such as social, economic, cultural, parenting, education, and the environment, so as to cause the difference in case of severe under nutrition between one region to another. Sufferers of malnutrition in one region may be linked and influenced by the surrounding regions. Therefore, we need a statistical modeling that is able to take into account the spatial factor. Statistical methods that can be used to analyze the data and also takes into account the spatial factor are the Geographically Weighted Regression (GWR). This study is aimed to determine the case of malnutrition models in East Java Province using GWR model with kernel adaptive bi-square weighting and comparing it to the conventional linear regression model.  The data used in the study are secondary data obtained from the National Socio-Economic Survey and Basic Health Research (2010) conducted in 38 districts in East Java. Estimation is done by using the Weighted Least Squares method that provides different weighting values to each region. The result showed that there are 38 models of the malnutrition case that is different for each district in East Java. The GWR model with bi-square kernel weighting function is better in modelling the case of malnutrition in East Java compared to the conventional linear regression models that are based on the criteria of goodness that is the R-square, Mean Square Error and the Akaike Information Criterion

Estimation of glottal closure instants in voiced speech using the DYPSA algorithm

Published versio

Impacts of latency on throughput of a corporate computer network

This paper addressed the impacts of latency on good throughputs of a computer network. The networks latency contributed largely on the performance of Covenant University network. Experiment using the University network were carried out with the channel capacity, the file sizes with the distance varies to suit the performed experiment. The Mathlab/Simulink and Netcracker Professional systems were used to simulate the model network, throughput and latency. The results from simulated hypothetical corporate computer network were validated and compared to those obtained from some websites traffic, which indicated the impact of latency on good throughput of a corporate computer network decreases the efficiency of data exchange with increase in the number of users. Thus, poor data exchange in a network with constant and good throughput was better resolved through detailed knowledge of the latency

Position estimation delays in signal injection-based sensorless PMSM drives

The causes of position estimation delays and their effects on the sensorless control of permanent magnet synchronous motor drives are investigated. The position of a permanent magnet synchronous machine is estimated via the injection of high frequency voltage signals. The delays under investigation are due to the digital implementation of the control algorithm and to the digital filters adopted for decoupling the inspection signals from the fundamental components of the stator current measures. If not correctly modeled and compensated, such delays can reduce the performance of the control scheme. Experimental results are provided, proving the accuracy of the modeling approach and the effectiveness of the related compensation strateg