Relevant bibliographies by topics / Data of variable size

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Data of variable size'

Author: Grafiati
Published: 25 May 2024

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Journal articles on the topic "Data of variable size"

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Fibriyanti, Yenni Vera. "THE INFLUENCE OF CORPORATE GOVERNANCE, LEVERAGE, COMPANY SIZE ON FINANCIAL PERFORMANCE." JHSS (Journal of Humanities and Social Studies) 6, no. 3 (2022): 345–48. http://dx.doi.org/10.33751/jhss.v6i3.6490.

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This study aims to determine the effect of corporate governance as proxied by independent commissioners, directors and audit committees as well as other variables, namely leverage and firm size on financial performance. The data used in this study is secondary data. While the sample in this study is the automotive and component sub-sector manufacturing companies during the 2017-2020 period. The method used is purposive sampling and there are 12 companies included in this research criteria. The results of this study indicate that the independent commissioner variable partially has no effect on financial performance. The directors variable partially has no effect on financial performance. The audit committee variable partially has no effect on financial performance. In the next variable, leverage partially affects financial performance. Firm size variable partially has no effect on financial performance. While the variables of independent commissioners, directors, audit committee leverage, firm size simultaneously affect financial performance.
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Axford, Danny, Robin Owen, and Gwyndaf Evans. "Diffraction data collection with a dynamically variable beam size." Acta Crystallographica Section A Foundations of Crystallography 69, a1 (2013): s409. http://dx.doi.org/10.1107/s0108767313096438.

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Nur Syamsiyah and Wulandari. "Factors Affecting Dividend Policy in Financial Sector Companies in Indonesia: Panel Data Analysis." JFBA: Journal of Financial and Behavioural Accounting 2, no. 1 (2022): 35–45. http://dx.doi.org/10.33830/jfba.v2i1.3642.2022.

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This study aims to analyze the factors that influence dividend policy in financial sector companies in Indonesia. The independent variables in this study are profitability, leverage, managerial ownership, and firm size. While the dependent variable used is dividend policy. Findings. The results showed that simultaneously all independent variables (leverage, firm size, profitability, and managerial ownership) affected dividend policy (the dependent variable). The percentage of influence of all variables used in this study on dividend policy is 72.52%. At the same time the rest is influenced by other variables equal to 27.48%. Partially, profitability and firm size have a positive relationship to dividend policy.
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Ma, Yung-Cheng, Jih-Ching Chiu, Tien-Fu Chen, and Chung-Ping Chung. "Variable-size data item placement for load and storage balancing." Journal of Systems and Software 66, no. 2 (2003): 157–66. http://dx.doi.org/10.1016/s0164-1212(02)00073-0.

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Mukherjee, Prasita, Sourasekhar Banerjee, and Asoke Nath. "Data Hiding Algorithm using Variable Block Size in Cover Image File." International Journal of Computer Applications 89, no. 13 (2014): 11–20. http://dx.doi.org/10.5120/15690-4559.

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Rizky, Zan Ana, and Anton Bawono. "THE EFFECT OF CAR, SIZE, CKPN, NPF ON FDR BUS WITH TPF AS INTERVENING VARIABLES IN 2016-2021." JOURNAL OF APPLIED MANAGERIAL ACCOUNTING 6, no. 2 (2022): 221–32. http://dx.doi.org/10.30871/jama.v6i2.4076.

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This study was conducted to know the effect of CAR, Size, CKPN, and NPF on Sharia Banking FDR with TPF as the intervening variable BUS in 2016-2021. This type of research uses quantitative with multiple regression analysis as data analysis sourced from secondary data. The model selected in this study uses panel data in the form of Fixed Effect Model annual data of CAR, Size, CKPN, NPF, TPF, and FDR recorded in BUS for the 2016-2021 period. The research data obtained were analyzed using the Eviews 10 application tool. The results of the research conducted by data processing showed that the TPF variable had a negative and significant effect on FDR. Variables CAR, Size, CKPN, and NPF have no significant effect on FDR. Then the Size variable has a positive and significant effect on TPF, while the CAR, CKPN, and NPF variables have no significant effect on TPF. After performing path analysis, the TPF variable can mediate the effect of Size on FDR. And the TPF variable cannot mediate the effect of CAR, CKPN, and NPF on FDR..
 
 Keywords: CAR, Size, CKPN, NPF, TPF, FDR
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Angraeni, Windy, Elvin Bastian, and Tri Lestari. "The Effect of Leverage, Firm Size, Profitability and Political Connections on Income Smoothing." Journal of Applied Business, Taxation and Economics Research 1, no. 6 (2022): 532–35. http://dx.doi.org/10.54408/jabter.v1i6.93.

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This study aims to determine the effect of leverage, firm size, profitability and political connections on income smoothing with firm value as a moderating variable. The approach used in this research is a quantitative approach. The data in this study are secondary data and data obtained from the site www.idx.go.id and company performance reports. The sampling technique used was purposive sampling technique with a total sample of 90 observation data from manufacturing companies in the consumer goods industry sector in 2016-2020. The data analysis technique uses multiple linear regression analysis using SPSS version 23 program. The results of this study indicate that the Leverage variable has no effect on income smoothing, while Company Size, Profitability and Political Connections affect income smoothing. For the moderating variable, firm value is proven to be able to moderate Leverage and Profitability, and not able to moderate the variables of Firm Size and Political Connections.
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Wicaksono, Dimas, and Ade Saputra. "10.84389 Pengaruh Managerial Ownership, Profitability, Firm Size dan Capital Structure." AKRUAL : Jurnal Akuntansi dan Keuangan 5, no. 1 (2023): 1–11. http://dx.doi.org/10.34005/akrual.v5i1.3061.

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This study aims to examine the effect of the variables Managerial Ownership, Profitability, and Company Size on Capital Structure in Food and Beverage Sector Companies Listed on the Indonesia Stock Exchange for the 2017-2021 period. In this study, capital structure is measured using the Debt to Equity Ratio (DER). Samples were taken by purposive sampling method with certain criteria, during the study period. Based on the predetermined sample criteria, the number of observational data that can be processed is 60 data. The analytical method used is Multiple Linear Regression processed using SPSS 25. The results of this study indicate that the independent variable Managerial Ownership has a negative and significant effect on the dependent variable Capital Structure. Profitability independent variable has a negative and significant effect on the dependent variable Capital Structure. While the independent variable Firm Size has a positive and significant effect on the dependent variable Capital Structure.
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Zhao, Naifei, Qingsong Xu, Man-lai Tang, and Hong Wang. "Variable Screening for Near Infrared (NIR) Spectroscopy Data Based on Ridge Partial Least Squares Regression." Combinatorial Chemistry & High Throughput Screening 23, no. 8 (2020): 740–56. http://dx.doi.org/10.2174/1386207323666200428114823.

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Aim and Objective: Near Infrared (NIR) spectroscopy data are featured by few dozen to many thousands of samples and highly correlated variables. Quantitative analysis of such data usually requires a combination of analytical methods with variable selection or screening methods. Commonly-used variable screening methods fail to recover the true model when (i) some of the variables are highly correlated, and (ii) the sample size is less than the number of relevant variables. In these cases, Partial Least Squares (PLS) regression based approaches can be useful alternatives. Materials and Methods : In this research, a fast variable screening strategy, namely the preconditioned screening for ridge partial least squares regression (PSRPLS), is proposed for modelling NIR spectroscopy data with high-dimensional and highly correlated covariates. Under rather mild assumptions, we prove that using Puffer transformation, the proposed approach successfully transforms the problem of variable screening with highly correlated predictor variables to that of weakly correlated covariates with less extra computational effort. Results: We show that our proposed method leads to theoretically consistent model selection results. Four simulation studies and two real examples are then analyzed to illustrate the effectiveness of the proposed approach. Conclusion: By introducing Puffer transformation, high correlation problem can be mitigated using the PSRPLS procedure we construct. By employing RPLS regression to our approach, it can be made more simple and computational efficient to cope with the situation where model size is larger than the sample size while maintaining a high precision prediction.
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Indrabudiman, Amir. "Model and Financial Performance: Panel Data in Causality and Cointegration Test." International Journal of Engineering & Technology 7, no. 3.27 (2018): 391. http://dx.doi.org/10.14419/ijet.v7i3.27.17979.

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This paper aims to analyze the interaction between financial performance variables and bankruptcy status of companies in the banking industry in Indonesia. This study used the test of causality and cointegration of panel data for variable bankruptcy status and variable of financial performance among others (variable of NPL, ROA, CAR, NIM, SIZE, GROWTH, LEVERAGE) at 43 banks listed on BEI during 2010-2016 financial reporting period. From the research conducted in the findings that between the status of bankruptcy and variable financial performance of banks in Indonesia are only a few variables that have a two-way relationship, this is seen in the test results of causality lags 1, using lags 5, 10 and 15 this causal relationship is getting smaller . However, cointegration has been confirmed by using lags 1-1 to 1-4 lags interval premises, there are 7 variables that in each cointegrated each other.
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Dissertations / Theses on the topic "Data of variable size"

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Chen, Haiying. "Ranked set sampling for binary and ordered categorical variables with applications in health survey data." Connect to this title online, 2004. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1092770729.

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Thesis (Ph. D.)--Ohio State University, 2004.<br>Title from first page of PDF file. Document formatted into pages; contains xiii, 109 p.; also includes graphics Includes bibliographical references (p. 99-102). Available online via OhioLINK's ETD Center
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Liv, Per. "Efficient strategies for collecting posture data using observation and direct measurement." Doctoral thesis, Umeå universitet, Yrkes- och miljömedicin, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-59132.

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Relationships between occupational physical exposures and risks of contracting musculoskeletal disorders are still not well understood; exposure-response relationships are scarce in the musculoskeletal epidemiology literature, and many epidemiological studies, including intervention studies, fail to reach conclusive results. Insufficient exposure assessment has been pointed out as a possible explanation for this deficiency. One important aspect of assessing exposure is the selected measurement strategy; this includes issues related to the necessary number of data required to give sufficient information, and to allocation of measurement efforts, both over time and between subjects in order to achieve precise and accurate exposure estimates. These issues have been discussed mainly in the occupational hygiene literature considering chemical exposures, while the corresponding literature on biomechanical exposure is sparse. The overall aim of the present thesis was to increase knowledge on the relationship between data collection design and the resulting precision and accuracy of biomechanical exposure assessments, represented in this thesis by upper arm postures during work, data which have been shown to be relevant to disorder risk. Four papers are included in the thesis. In papers I and II, non-parametric bootstrapping was used to investigate the statistical efficiency of different strategies for distributing upper arm elevation measurements between and within working days into different numbers of measurement periods of differing durations. Paper I compared the different measurement strategies with respect to the eventual precision of estimated mean exposure level. The results showed that it was more efficient to use a higher number of shorter measurement periods spread across a working day than to use a smaller number for longer uninterrupted measurement periods, in particular if the total sample covered only a small part of the working day. Paper II evaluated sampling strategies for the purpose of determining posture variance components with respect to the accuracy and precision of the eventual variance component estimators. The paper showed that variance component estimators may be both biased and imprecise when based on sampling from small parts of working days, and that errors were larger with continuous sampling periods. The results suggest that larger posture samples than are conventionally used in ergonomics research and practice may be needed to achieve trustworthy estimates of variance components. Papers III and IV focused on method development. Paper III examined procedures for estimating statistical power when testing for a group difference in postures assessed by observation. Power determination was based either on a traditional analytical power analysis or on parametric bootstrapping, both of which accounted for methodological variance introduced by the observers to the exposure data. The study showed that repeated observations of the same video recordings may be an efficient way of increasing the power in an observation-based study, and that observations can be distributed between several observers without loss in power, provided that all observers contribute data to both of the compared groups, and that the statistical analysis model acknowledges observer variability. Paper IV discussed calibration of an inferior exposure assessment method against a superior “golden standard” method, with a particular emphasis on calibration of observed posture data against postures determined by inclinometry. The paper developed equations for bias correction of results obtained using the inferior instrument through calibration, as well as for determining the additional uncertainty of the eventual exposure value introduced through calibration. In conclusion, the results of the present thesis emphasize the importance of carefully selecting a measurement strategy on the basis of statistically well informed decisions. It is common in the literature that postural exposure is assessed from one continuous measurement collected over only a small part of a working day. In paper I, this was shown to be highly inefficient compared to spreading out the corresponding sample time across the entire working day, and the inefficiency was also obvious when assessing variance components, as shown in paper II. The thesis also shows how a well thought-out strategy for observation-based exposure assessment can reduce the effects of measurement error, both for random methodological variance (paper III) and systematic observation errors (bias) (paper IV).
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Högberg, Hans. "Some properties of measures of disagreement and disorder in paired ordinal data." Doctoral thesis, Örebro universitet, Handelshögskolan vid Örebro universitet, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-12350.

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The measures studied in this thesis were a measure of disorder, D, and a measure of the individual part of the disagreement, the measure of relative rank variance, RV, proposed by Svensson in 1993. The measure of disorder is a useful measure of order consistency in paired assessments of scales with a different number of possible values. The measure of relative rank variance is a useful measure in evaluating reliability and for evaluating change in qualitative outcome variables. In Paper I an overview of methods used in the analysis of dependent ordinal data and a comparison of the methods regarding the assumptions, specifications, applicability, and implications for use were made. In Paper II an application, and a comparison of the results of some standard models, tests, and measures to two different research problems were made. The sampling distribution of the measure of disorder was studied both analytically and by a simulation experiment in Paper III. The asymptotic normal distribution was shown by the theory of U-statistics and the simulation experiments for finite sample sizes and various amount of disorder showed that the sampling distribution was approximately normal for sample sizes of about 40 to 60 for moderate sizes of D and for smaller sample sizes for substantial sizes of D. The sampling distribution of the relative rank variance was studied in a simulation experiment in Paper IV. The simulation experiment showed that the sampling distribution was approximately normal for sample sizes of 60-100 for moderate size of RV, and for smaller sample sizes for substantial size of RV. In Paper V a procedure for inference regarding relative rank variances from two or more samples was proposed. Pair-wise comparison by jackknife technique for variance estimation and the use of normal distribution as approximation in inference for parameters in independent samples based on the results in Paper IV were demonstrated. Moreover, an application of Kruskal-Wallis test for independent samples and Friedman’s test for dependent samples were conducted.<br>Statistical methods for ordinal data
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Fakhouri, Elie Michel. "Variable block-size motion estimation." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ37260.pdf.

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Ruengvirayudh, Pornchanok. "A Monte Carlo Study of Parallel Analysis, Minimum Average Partial, Indicator Function, and Modified Average Roots for Determining the Number of Dimensions with Binary Variables in Test Data: Impact of Sample Size and Factor Structure." Ohio University / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou151516919677091.

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Nataša, Krklec Jerinkić. "Line search methods with variable sample size." Phd thesis, Univerzitet u Novom Sadu, Prirodno-matematički fakultet u Novom Sadu, 2014. http://dx.doi.org/10.2298/NS20140117KRKLEC.

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The problem under consideration is an unconstrained optimization&nbsp;problem with the objective function in the form of mathematical ex-pectation. The expectation is with respect to the random variable that represents the uncertainty. Therefore, the objective &nbsp;function is in fact deterministic. However, nding the analytical form of that objective function can be very dicult or even impossible. This is the reason why the sample average approximation is often used. In order to obtain reasonable good approximation of the objective function, we have to use relatively large sample size. We assume that the sample is generated at the beginning of the optimization process and therefore we can consider this sample average objective function as the deterministic one. However, applying some deterministic method on that sample average function from the start can be very costly. The number of evaluations of the function under expectation is a common way of measuring the cost of an algorithm. Therefore, methods that vary the sample size throughout the optimization process are developed. Most of them are trying to determine the optimal dynamics of increasing the sample size.The main goal of this thesis is to develop the clas of methods that&nbsp;can decrease the cost of an algorithm by decreasing the number of&nbsp;function evaluations. The idea is to decrease the sample size whenever&nbsp;it seems to be reasonable - roughly speaking, we do not want to impose&nbsp;a large precision, i.e. a large sample size when we are far away from the&nbsp;solution we search for. The detailed description of the new methods&nbsp;is presented in Chapter 4 together with the convergence analysis. It&nbsp;is shown that the approximate solution is of the same quality as the&nbsp;one obtained by dealing with the full sample from the start.Another important characteristic of the methods that are proposed&nbsp;here is the line search technique which is used for obtaining the sub-sequent iterates. The idea is to nd a suitable direction and to search&nbsp;along it until we obtain a sucient decrease in the &nbsp;function value. The&nbsp;sucient decrease is determined throughout the line search rule. In&nbsp;Chapter 4, that rule is supposed to be monotone, i.e. we are imposing&nbsp;strict decrease of the function value. In order to decrease the cost of&nbsp;the algorithm even more and to enlarge the set of suitable search directions, we use nonmonotone line search rules in Chapter 5. Within that chapter, these rules are modied to t the variable sample size framework. Moreover, the conditions for the global convergence and the R-linear rate are presented.&nbsp;In Chapter 6, numerical results are presented. The test problems&nbsp;are various - some of them are academic and some of them are real&nbsp;world problems. The academic problems are here to give us more&nbsp;insight into the behavior of the algorithms. On the other hand, data&nbsp;that comes from the real world problems are here to test the real&nbsp;applicability of the proposed algorithms. In the rst part of that&nbsp;chapter, the focus is on the variable sample size techniques. Different&nbsp;implementations of the proposed algorithm are compared to each other&nbsp;and to the other sample schemes as well. The second part is mostly&nbsp;devoted to the comparison of the various line search rules combined&nbsp;with dierent search directions in the variable sample size framework.&nbsp;The overall numerical results show that using the variable sample size&nbsp;can improve the performance of the algorithms signicantly, especially&nbsp;when the nonmonotone line search rules are used.The rst chapter of this thesis provides the background material&nbsp;for the subsequent chapters. In Chapter 2, basics of the nonlinear&nbsp;optimization are presented and the focus is on the line search, while&nbsp;Chapter 3 deals with the stochastic framework. These chapters are&nbsp;here to provide the review of the relevant known results, while the&nbsp;rest of the thesis represents the original contribution.&nbsp;<br>U okviru ove teze posmatra se problem optimizacije bez ograničenja pri čcemu je funkcija cilja u formi matematičkog očekivanja. Očekivanje se odnosi na slučajnu promenljivu koja predstavlja neizvesnost. Zbog toga je funkcija cilja, u stvari, deterministička veličina. Ipak, odredjivanje analitičkog oblika te funkcije cilja može biti vrlo komplikovano pa čak i nemoguće. Zbog toga se za aproksimaciju često koristi uzoračko očcekivanje. Da bi se postigla dobra aproksimacija, obično je neophodan obiman uzorak. Ako pretpostavimo da se uzorak realizuje pre početka procesa optimizacije, možemo posmatrati uzoračko očekivanje kao determinističku funkciju. Medjutim, primena nekog od determinističkih metoda direktno na tu funkciju&nbsp; moze biti veoma skupa jer evaluacija funkcije pod ocekivanjem često predstavlja veliki tro&scaron;ak i uobičajeno je da se ukupan tro&scaron;ak optimizacije meri po broju izračcunavanja funkcije pod očekivanjem. Zbog toga su razvijeni metodi sa promenljivom veličinom uzorka. Većcina njih je bazirana na odredjivanju optimalne dinamike uvećanja uzorka.Glavni cilj ove teze je razvoj algoritma koji, kroz smanjenje broja izračcunavanja funkcije, smanjuje ukupne tro&scaron;skove optimizacije. Ideja je da se veličina uzorka smanji kad god je to moguće. Grubo rečeno, izbegava se koriscenje velike preciznosti&nbsp; (velikog uzorka) kada smo daleko od re&scaron;senja. U čcetvrtom poglavlju ove teze opisana je nova klasa metoda i predstavljena je analiza konvergencije. Dokazano je da je aproksimacija re&scaron;enja koju dobijamo bar toliko dobra koliko i za metod koji radi sa celim uzorkom sve vreme.Jo&scaron; jedna bitna karakteristika metoda koji su ovde razmatrani je primena linijskog pretražzivanja u cilju odredjivanja naredne iteracije. Osnovna ideja je da se nadje odgovarajući pravac i da se duž njega vr&scaron;si pretraga za dužzinom koraka koja će dovoljno smanjiti vrednost funkcije. Dovoljno smanjenje je odredjeno pravilom linijskog pretraživanja. U čcetvrtom poglavlju to pravilo je monotono &scaron;to znači da zahtevamo striktno smanjenje vrednosti funkcije. U cilju jos većeg smanjenja tro&scaron;kova optimizacije kao i pro&scaron;irenja skupa pogodnih pravaca, u petom poglavlju koristimo nemonotona pravila linijskog pretraživanja koja su modifikovana zbog promenljive velicine uzorka. Takodje, razmatrani su uslovi za globalnu konvergenciju i R-linearnu brzinu konvergencije.Numerički rezultati su predstavljeni u &scaron;estom poglavlju. Test problemi su razliciti - neki od njih su akademski, a neki su realni. Akademski problemi su tu da nam daju bolji uvid u pona&scaron;anje algoritama. Sa druge strane, podaci koji poticu od stvarnih problema služe kao pravi test za primenljivost pomenutih algoritama. U prvom delu tog poglavlja akcenat je na načinu ažuriranja veličine uzorka. Različite varijante metoda koji su ovde predloženi porede se medjusobno kao i sa drugim &scaron;emama za ažuriranje veličine uzorka. Drugi deo poglavlja pretežno je posvećen poredjenju različitih pravila linijskog pretraživanja sa različitim pravcima pretraživanja u okviru promenljive veličine uzorka. Uzimajuci sve postignute rezultate u obzir dolazi se do zaključcka da variranje veličine uzorka može značajno popraviti učinak algoritma, posebno ako se koriste nemonotone metode linijskog pretraživanja.U prvom poglavlju ove teze opisana je motivacija kao i osnovni pojmovi potrebni za praćenje preostalih poglavlja. U drugom poglavlju je iznet pregled osnova nelinearne optimizacije sa akcentom na metode linijskog pretraživanja, dok su u trećem poglavlju predstavljene osnove stohastičke optimizacije. Pomenuta poglavlja su tu radi pregleda dosada&scaron;njih relevantnih rezultata dok je originalni doprinos ove teze predstavljen u poglavljima 4-6.
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Hintze, Christopher Jerry. "Modeling correlation in binary count data with application to fragile site identification." Texas A&M University, 2005. http://hdl.handle.net/1969.1/4278.

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Available fragile site identification software packages (FSM and FSM3) assume that all chromosomal breaks occur independently. However, under a Mendelian model of inheritance, homozygosity at fragile loci implies pairwise correlation between homologous sites. We construct correlation models for chromosomal breakage data in situations where either partitioned break count totals (per-site single-break and doublebreak totals) are known or only overall break count totals are known. We derive a likelihood ratio test and Neyman’s C( α) test for correlation between homologs when partitioned break count totals are known and outline a likelihood ratio test for correlation using only break count totals. Our simulation studies indicate that the C( α) test using partitioned break count totals outperforms the other two tests for correlation in terms of both power and level. These studies further suggest that the power for detecting correlation is low when only break count totals are reported. Results of the C( α) test for correlation applied to chromosomal breakage data from 14 human subjects indicate that detection of correlation between homologous fragile sites is problematic due to sparseness of breakage data. Simulation studies of the FSM and FSM3 algorithms using parameter values typical for fragile site data demonstrate that neither algorithm is significantly affected by fragile site correlation. Comparison of simulated fragile site misclassification rates in the presence of zero-breakage data supports previous studies (Olmsted 1999) that suggested FSM has lower false-negative rates and FSM3 has lower false-positive rates.
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Sodagari, Shabnam. "Variable block-size disparity estimation in stereo imagery." Thesis, University of Ottawa (Canada), 2003. http://hdl.handle.net/10393/26399.

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This thesis addresses the problem of developing and implementing in software a variable block size (quadtree splitting) disparity estimation algorithm that is optimized for use in compression of stereo image pairs and studying its performance over a range of rate/distortion values for a variety of images. First the constrained optimization problem is converted to an unconstrained one using the Lagrange multiplier approach. Then by solving the optimization problem using dynamic programming, the optimal variables representing the optimal quadtree structure and the quantizer for each node are determined. The experimental results show the improvements of this method over simple intraframe JPEG coding and over fixed block-size disparity estimation.
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Dziminski, Martin A. "The evolution of variable offspring provisioning." University of Western Australia, 2005. http://theses.library.uwa.edu.au/adt-WU2005.0134.

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Most theoretical models predict an optimal offspring size that maximises parental fitness. Variation in the quality of the offspring environment can result in multiple offspring size optima and therefore variation of offspring provisioning can evolve. Variation in offspring provisioning is common and found across a variety of taxa. It can be defined as between populations, explained by optimality models, or between and within individuals, neither so easily explained by optimality models. My research focused on the evolution of variable offspring provisioning by testing theoretical models relating to variation in offspring provisioning between and within individuals. Using comparative methods, I found a positive relationship between intraclutch variation in offspring provisioning and variation in the quality of the offspring environment in a suite of pond breeding frogs. This positive relationship provided evidence that patterns of variable offspring provisioning are related to the offspring environment. This study also identified a species (Crinia georgiana) with high variation in offspring provisioning on which to focus further investigations. High variation in offspring provisioning occured between and within individuals of this species independent of female phenotype and a trade-off in offspring size and number existed. In laboratory studies, increased yolk per offspring led to increased fitness per offspring. Parental fitness calculations revealed that in high quality conditions production of small more numerous offspring resulted in higher parental fitness, but in lower quality conditions the production of large offspring resulted in the highest parental fitness. This was confirmed in field experiments under natural conditions using molecular markers to trace offspring to clutches of known provisioning, allowing me to measure exact parental fitness. The strategy of high variation in offspring size within clutches can be of benefit when the future of the offspring environment is not known to the parents: as a form of bet-hedging. Further study of the offspring environment revealed that conditions such as density dependent fitness loss, spatial variation in habitat quality, and non-random offspring dispersal, can combine to create the conditions predicted by theoretical models to maintain a strategy of variable offspring provisioning in the population. My research provides a comprehensive empirical test of the theory of variable offspring provisioning
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Acuna, Stamp Annabelen. "Design Study for Variable Data Printing." University of Cincinnati / OhioLINK, 2000. http://rave.ohiolink.edu/etdc/view?acc_num=ucin962378632.

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Books on the topic "Data of variable size"

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Tritton, Kelvin. Variable data printing. PIRA, 2003.

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Components, Philips. Variable capacitors: Data handbook. Philips Components, 1993.

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Christine, Bachrach, National Survey of Family Growth (U.S.), and National Center for Health Statistics (U.S.), eds. National survey of family growth, cycle III: Sample design, weighting, and variance estimation : this report describes the procedures used to select the sample. U.S. Dept. of Health and Human Services, Public Health Service, National Center for Health Statistics, 1985.

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Salomon, David. Variable-length Codes for Data Compression. Springer London, 2007. http://dx.doi.org/10.1007/978-1-84628-959-0.

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Albert, Boggess, and Stewart James 1941-, eds. Single variable CalcLabs with Derive: For Stewart's fourth edition, Calculus, Single variable calculus, Calculus--early transcendentals, Single variable calculus--early transcendentals. Brooks/Cole Pub., 1999.

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Thomas' calculus: Single variable. Addison-Wesley, 2009.

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Center, Goddard Space Flight, ed. Nickel-cadmium cell design variable program data analysis. National Aeronautics and Space Administration, Goddard Space Flight Center, 1985.

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Hirsch and Coxford. Predicting from Data: An alternative unit for representing and analyzing two-variable data. McGraw-Hill/Glencoe, 1995.

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Bizon, Thomas P. Real-time transmission of digital video using variable-lengthbcoding. National Aeronautics and Space Administration, 1993.

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Bizon, Thomas P. Real-time transmission of digital video using variable-lengthbcoding. National Aeronautics and Space Administration, 1993.

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Book chapters on the topic "Data of variable size"

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Quicke, Donald L. J., Buntika A. Butcher, and Rachel A. Kruft Welton. "Count data as response variable." In Practical R for biologists: an introduction. CABI, 2021. http://dx.doi.org/10.1079/9781789245349.0012.

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Abstract This chapter is devoted specifically to count data for three reasons: (i) they are common in ecological studies (e.g. clutch sizes, numbers of fledglings from a nest, numbers of seeds per pod...); (ii) they are simple to collect and are therefore often the data collected by students (e.g. numbers of beetles in a pitfall trap, number of pollinator visits to flowers...); and (iii) they pose numerous issues that linear models with their normal error structure cannot deal with. Two studies will be examined with the response variable being counts, starting with one that nearly fits the ideals of a Poisson distribution well, the other less so. Example 1 deals with fledgling numbers in relation to clutch initiation date. The data are on the northern cardinal bird, Cardinalis cardinalis, and were collected to test the hypothesis that birds that start their clutches later may suffer higher pre-fledging offspring mortality. Example 2 focuses on pollinator flower visits in Passiflora speciosa in relation to flower size.
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Quicke, Donald L. J., Buntika A. Butcher, and Rachel A. Kruft Welton. "Count data as response variable." In Practical R for biologists: an introduction. CABI, 2021. http://dx.doi.org/10.1079/9781789245349.0147.

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Abstract This chapter is devoted specifically to count data for three reasons: (i) they are common in ecological studies (e.g. clutch sizes, numbers of fledglings from a nest, numbers of seeds per pod...); (ii) they are simple to collect and are therefore often the data collected by students (e.g. numbers of beetles in a pitfall trap, number of pollinator visits to flowers...); and (iii) they pose numerous issues that linear models with their normal error structure cannot deal with. Two studies will be examined with the response variable being counts, starting with one that nearly fits the ideals of a Poisson distribution well, the other less so. Example 1 deals with fledgling numbers in relation to clutch initiation date. The data are on the northern cardinal bird, Cardinalis cardinalis, and were collected to test the hypothesis that birds that start their clutches later may suffer higher pre-fledging offspring mortality. Example 2 focuses on pollinator flower visits in Passiflora speciosa in relation to flower size.
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Djebour, Lamia, Reza Akbarinia, and Florent Masseglia. "Variable-Size Segmentation for Time Series Representation." In Transactions on Large-Scale Data- and Knowledge-Centered Systems LIII. Springer Berlin Heidelberg, 2023. http://dx.doi.org/10.1007/978-3-662-66863-4_2.

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Putluri, Srinivasareddy, and Md Zia Ur Rahman. "Novel Exon Predictors Using Variable Step Size Adaptive Algorithms." In Innovative Data Communication Technologies and Application. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38040-3_86.

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Behera, Mandakini Priyadarshani, Archana Sarangi, Debahuti Mishra, and Srikanta Kumar Mohapatra. "Variable Step Size Firefly Algorithm for Automatic Data Clustering." In Smart Innovation, Systems and Technologies. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9873-6_22.

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Li, Yuxiong, Yujuan Tan, Congcong Xu, et al. "AIR Cache: A Variable-Size Block Cache Based on Fine-Grained Management Method." In Web and Big Data. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-85899-5_12.

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Dröge, Gisbert, and Hans-Jörg Schek. "Query- adaptive data space partitioning using variable-size storage clusters." In Advances in Spatial Databases. Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/3-540-56869-7_19.

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Leirens, Sylvain, Christophe Villien, and Bruno Flament. "Feasibility of WiFi Site-Surveying Using Crowdsourced Data." In Latent Variable Analysis and Signal Separation. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53547-0_45.

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Quicke, Donald L. J., Buntika A. Butcher, and Rachel A. Kruft Welton. "Analysis of covariance (ANCOVA)." In Practical R for biologists: an introduction. CABI, 2021. http://dx.doi.org/10.1079/9781789245349.0014.

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Abstract This chapter deals with analysis of covariance or ANCOVA, a combination of ANOVA and regression. It tests the effects of a mix of continuous and categorical variables on a continuous response variable. Two examples are presented. Example 1 is based on a study investigating the effects of two types of tagging (acrylic paint and subcutaneous microtags) on the growth of the coral reef goby, Coryphopterus glaucofraenum, in the British Virgin Islands and included initial size as a continuous explanatory variable. Example 2 analyses data from a study on the number of pollinaria removed by pollinators from inflorescences of two Sirindhornia orchid species (S. monophylla and S. mirabillis) in relation to the number of flowers in the inflorescence (also count data) and the orchid species (categorical).
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Quicke, Donald L. J., Buntika A. Butcher, and Rachel A. Kruft Welton. "Analysis of covariance (ANCOVA)." In Practical R for biologists: an introduction. CABI, 2021. http://dx.doi.org/10.1079/9781789245349.0166.

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Abstract This chapter deals with analysis of covariance or ANCOVA, a combination of ANOVA and regression. It tests the effects of a mix of continuous and categorical variables on a continuous response variable. Two examples are presented. Example 1 is based on a study investigating the effects of two types of tagging (acrylic paint and subcutaneous microtags) on the growth of the coral reef goby, Coryphopterus glaucofraenum, in the British Virgin Islands and included initial size as a continuous explanatory variable. Example 2 analyses data from a study on the number of pollinaria removed by pollinators from inflorescences of two Sirindhornia orchid species (S. monophylla and S. mirabillis) in relation to the number of flowers in the inflorescence (also count data) and the orchid species (categorical).
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Conference papers on the topic "Data of variable size"

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Wang, Su, and Chein-I. Chang. "Variable-size variable-band selection for spectral feature characterization in hyperspectral data." In Optics East 2006, edited by Steven D. Christesen, Arthur J. Sedlacek III, James B. Gillespie, and Kenneth J. Ewing. SPIE, 2006. http://dx.doi.org/10.1117/12.684911.

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Katsipoulakis, Nikos R., Alexandros Labrinidis, and Panos K. Chrysanthis. "Concept-Driven Load Shedding: Reducing Size and Error of Voluminous and Variable Data Streams." In 2018 IEEE International Conference on Big Data (Big Data). IEEE, 2018. http://dx.doi.org/10.1109/bigdata.2018.8622265.

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Voigt, Michael. "Watermarking geographic vector-data using a variable strip-size scheme." In Electronic Imaging 2007. SPIE, 2007. http://dx.doi.org/10.1117/12.704557.

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Emlek, Alper, Murat Peker, and Kamil Fatih Dilaver. "Variable window size for stereo image matching based on edge information." In 2017 International Artificial Intelligence and Data Processing Symposium (IDAP). IEEE, 2017. http://dx.doi.org/10.1109/idap.2017.8090229.

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Do, Jaeyoung, Chen Luo, and David Lomet. "Programming an SSD Controller to Support Batched Writes for Variable-Size Pages." In 2021 IEEE 37th International Conference on Data Engineering (ICDE). IEEE, 2021. http://dx.doi.org/10.1109/icde51399.2021.00071.

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Rusu, Alexandru-George, Laura-Maria Dogariu, Ruxandra-Liana Costea, Constantin Paleologu, Jacob Benesty, and Silviu Ciochina. "A Variable Step-Size Affine Projection Algorithm Based on Data Reuse." In 2022 45th International Conference on Telecommunications and Signal Processing (TSP). IEEE, 2022. http://dx.doi.org/10.1109/tsp55681.2022.9851279.

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Wu, Cen, Wei Zhang, Yao Wang, and Chao Gao. "Study on the Performance of the Variable Step-Size LMS Algorithms." In 2020 IEEE International Conference on Information Technology,Big Data and Artificial Intelligence (ICIBA). IEEE, 2020. http://dx.doi.org/10.1109/iciba50161.2020.9276956.

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Azad, A. K. M., and J. Kamruzzaman. "Asynchronous Variable Hop Size Transmission with Stochastic Data Model for Sensor Networks." In 2008 IEEE International Conference on Communications. IEEE, 2008. http://dx.doi.org/10.1109/icc.2008.801.

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Szadkowski, Zbigniew. "Variable Step-Size Least Mean Square Filter Supressing Radio Frequency Interferentions in Cosmic Rays Radio Detection." In 2018 International Conference on Advances in Big Data, Computing and Data Communication Systems (icABCD). IEEE, 2018. http://dx.doi.org/10.1109/icabcd.2018.8465415.

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Li, Haiqing, and Lang Wang. "A variable size sliding window based frequent itemsets mining algorithm in data stream." In MATERIALS SCIENCE, ENERGY TECHNOLOGY, AND POWER ENGINEERING I: 1st International Conference on Materials Science, Energy Technology, Power Engineering (MEP 2017). Author(s), 2017. http://dx.doi.org/10.1063/1.4982511.

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Reports on the topic "Data of variable size"

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Skone, Timothy J. Variable Size Wind Farm, Operation. Office of Scientific and Technical Information (OSTI), 2010. http://dx.doi.org/10.2172/1509463.

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Kim, Changmo, Ghazan Khan, Brent Nguyen, and Emily L. Hoang. Development of a Statistical Model to Predict Materials’ Unit Prices for Future Maintenance and Rehabilitation in Highway Life Cycle Cost Analysis. Mineta Transportation Institute, 2020. http://dx.doi.org/10.31979/mti.2020.1806.

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The main objectives of this study are to investigate the trends in primary pavement materials’ unit price over time and to develop statistical models and guidelines for using predictive unit prices of pavement materials instead of uniform unit prices in life cycle cost analysis (LCCA) for future maintenance and rehabilitation (M&amp;R) projects. Various socio-economic data were collected for the past 20 years (1997–2018) in California, including oil price, population, government expenditure in transportation, vehicle registration, and other key variables, in order to identify factors affecting pavement materials’ unit price. Additionally, the unit price records of the popular pavement materials were categorized by project size (small, medium, large, and extra-large). The critical variables were chosen after identifying their correlations, and the future values of each variable were predicted through time-series analysis. Multiple regression models using selected socio-economic variables were developed to predict the future values of pavement materials’ unit price. A case study was used to compare the results between the uniform unit prices in the current LCCA procedures and the unit prices predicted in this study. In LCCA, long-term prediction involves uncertainties due to unexpected economic trends and industrial demand and supply conditions. Economic recessions and a global pandemic are examples of unexpected events which can have a significant influence on variations in material unit prices and project costs. Nevertheless, the data-driven scientific approach as described in this research reduces risk caused by such uncertainties and enables reasonable predictions for the future. The statistical models developed to predict the future unit prices of the pavement materials through this research can be implemented to enhance the current LCCA procedure and predict more realistic unit prices and project costs for the future M&amp;R activities, thus promoting the most cost-effective alternative in LCCA.
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Uechi, Luis, and José A. Barbero. Assessment of Transport Data Availability and Quality in Latin America. Inter-American Development Bank, 2012. http://dx.doi.org/10.18235/0010453.

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The report is part of an initiative to map the transport data currently available within selected developing countries, looking to evaluate availability and quality of transport-related data in general, and particularly for information gaps affecting estimation of Greenhouse Gas emissions. The assessment of transport data availability and quality is performed by comparing the input information needed to run a transport model that identifies the major drivers for transport activity and emissions. The database requested includes typical transport information like fleet size and composition, passenger and freight activity, and fuel consumption, as well as other types of data related to demographic, macroeconomic, trade or other variables specified by the model. The assessment was carried out in eight Latin American countries, checking the data that has been collected and reviewing gathering procedures. The results show the major data availability and quality gaps, and expose implications beyond the modeling of transport emissions: such data will provide a basis for the implementation of important transport sector policies and planning processes, affecting both the public and private sectors. The analysis has demonstrated that transportation systems in the region are relatively sophisticated, including a great diversity of modes, flows, vehicle types, fuel types, and so forth. Therefore, estimation of sector emissions is expected to be considerably data-intensive.
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Kimhi, Ayal, Barry Goodwin, Ashok Mishra, Avner Ahituv, and Yoav Kislev. The dynamics of off-farm employment, farm size, and farm structure. United States Department of Agriculture, 2006. http://dx.doi.org/10.32747/2006.7695877.bard.

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Objectives: (1) Preparing panel data sets for both the United States and Israel that contain a rich set of farm attributes, such as size, specialization, and output composition, and farmers’ characteristics such as off-farm employment status, education, and family composition. (2) Developing an empirical framework for the joint analysis of all the endogenous variables of interest in a dynamic setting. (3) Estimating simultaneous equations of the endogenous variables using the panel data sets from both countries. (4) Analyzing, using the empirical results, the possible effects of economic policies and institutional changes on the dynamics of the farm sector. An added objective is analyzing structural changes in farm sectors in additional countries. Background: Farm sectors in developed countries, including the U.S. and Israel, have experienced a sharp decline in their size and importance during the second half of the 20th century. The overall trend is towards fewer and larger farms that rely less on family labor. These structural changes have been a reaction to changes in technology, in government policies, and in market conditions: decreasing terms of trade, increasing alternative opportunities, and urbanization pressures. As these factors continue to change, so does the structure of the agricultural sector. Conclusions: We have shown that all major dimensions of structural changes in agriculture are closely interlinked. These include farm efficiency, farm scale, farm scope (diversification), and off-farm labor. We have also shown that these conclusions hold and perhaps even become stronger whenever dynamic aspects of structural adjustments are explicitly modeled using longitudinal data. While the results vary somewhat in the different applications, several common features are observed for both the U.S. and Israel. First, the trend towards the concentration of farm production in a smaller number of larger farm enterprises is likely to continue. Second, at the micro level, increased farm size is negatively associated with increased off-farm labor, with the causality going both ways. Third, the increase in farm size is mostly achieved by diversifying farm production into additional activities (crops or livestock). All these imply that the farm sector converges towards a bi-modal farm distribution, with some farms becoming commercial while the remaining farm households either exit farming altogether or continue producing but rely heavily on off-farm income. Implications: The primary scientific implication of this project is that one should not analyze a specific farm attribute in isolation. We have shown that controlling for the joint determination of the various farm and household attributes is crucial for obtaining meaningful empirical results. The policy implications are to some extent general but could be different in the two countries. The general implication is that farm policy is an important determinant of structural changes in the farm sector. For the U.S., we have shown the different effects of coupled and decoupled (direct) farm payments on the various farm attributes, and also shown that it is important to take into account the joint farm-household decisions in order to conduct a meaningful policy analysis. Only this kind of analysis explains the indirect effect of direct farm payments on farm production decisions. For Israel, we concluded that farm policy (or lack of farm policy) has contributed to the fast structural changes we observed over the last 25 years. The sharp change of direction in farm policy that started in the early 1980s has accelerated structural changes that could have been smoother otherwise. These accelerated structural changes most likely lead to welfare losses in rural areas.
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Axenrot, Thomas, Erik Degerman, and Anders Asp. Seasonal variation in thermal habitat volume for cold-water fish populations : implications for hydroacoustic survey design and stock assessment. Department of Aquatic Resources, Swedish University of Agricultural Sciences, 2023. http://dx.doi.org/10.54612/a.5i05rb1iu1.

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For accurate stock assessment, survey design must consider fish behavior and ecology. Yearlings and older individuals of the commercially exploited cold-water species vendace (Coregonus albula) are found below the metalimnion through periods of thermal stratification. These stratification periods generally last for 3-4 months, from the middle of summer to early autumn. In lakes with heterogeneous distribution of depths, the habitat volume for vendace vary drastically within and across years, which affects the distribution and population densities. Variable thermal habitat volumes, with food and oxygen depletion in the hypolimnion through the period of stratification, may act as a population size-regulating factor. Using hydroacoustics in combination with trawl data and temperature profiles, we examined the distribution of vendace through annual periods of thermal stratification. We found that yearling and older vendace these periods were confined to cold-water habitat volumes representing less than 10 % of the total water volume of Lake Mälaren, the third largest lake in Sweden. By introducing stratification to the design of hydroacoustic surveys supported by midwater trawling, seasonal aggregations of fish in temporally restricted thermal habitat volumes can be used to lower survey effort and improve the precision in estimates of population size. Temporally restricted habitat volumes may induce risks for the populations to over-fishing and sensitivity to environmental changes that potentially may call for directed management.
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Nelson, Gena, Hannah Carter, and Peter Boedeker. Early Math Interventions in Informal Learning Settings Coding Protocol. Boise State University, Albertsons Library, 2021. http://dx.doi.org/10.18122/sped141.boisestate.

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The purpose of document is to provide readers with the coding protocol that authors used to code experimental and quasi-experimental early mathematics intervention studies conducted in informal learning environments. The studies were conducted in homes and in museums with caregivers as intervention agents and included children between the ages of 3,0 and 8,11 years. The coding protocol includes more than 200 variables related to basic study information, participant sample size and demographics, methodological information, intervention information, mathematics content information, the control/comparison condition, outcome measures, and results and effect sizes. The coding protocol was developed for the purpose of conducting a meta-analysis; results of the meta-analysis is pending. The data set associated with this coding protocol will be available to the public at the conclusion of the grant (early 2024).
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Aboal, Diego, and Paula Garda. Technological and Nontechnological Innovation and Productivity in Services vis a vis Manufacturing in Uruguay. Inter-American Development Bank, 2012. http://dx.doi.org/10.18235/0006944.

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In this paper, the links between the investment in innovation activities, innovation outputs (technological and non-technological innovation), and productivity in services and manufacturing are explored using innovation survey data from Uruguay. This is the first attempt to study these links for a developing country. The size of firms, their cooperation on R&amp;D activities, the use of public financial support, patent protection, and the use of market sources of information, are the variables that are more consistently associated with the decision to invest in innovation activities across sectors. The main determinants of technological and non-technological innovations are the level of investment in innovation activities and the size of firms. The results indicate that both technological (i.e., product and process) and non-technological (i.e., marketing an organizational) innovations are positively associated to productivity gains in services, but nontechnological innovations have a more important role. The reverse happens for manufacturing; technological innovations are the relevant ones for productivity.
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Bernard, David Rhys, Gharad Bryan, Sylvain Chabé-Ferret, Jon de Quidt, Jasmin Claire Fliegner, and Roland Rathelot. How Biased are Observational Methods in Practice? Accumulating Evidence Using Randomised Controlled Trials with Imperfect Compliance. Centre for Excellence and Development Impact and Learning (CEDIL), 2023. http://dx.doi.org/10.51744/crpp9.

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Consider a policy maker choosing between programs of unknown impact. She can inform her decision using observational methods, or by running a randomised controlled trial (RCT). The proponents of RCTs would argue that observational approaches suffer from bias of an unknown size and direction, and so are uninformative. Our study treats this as an empirical claim that can be studied. By doing so we hope to increase the value of observational data and studies, as well as better inform the choice to undertake RCTs. We propose a large-scale, standardised, hands-off approach to assessing the performance of observational methods. First, we collect and categorise data from a large number of RCTs in the past 20 years. Second, we implement new methods to understand the size and direction of expected bias in observational studies, and how bias depends on measurable characteristics of programmes and settings. We find that the difference between observational estimators and the experimental benchmark is on average zero, but the resulting observational bias distribution has high variance.
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Campi, Mercedes, Marco Dueñas, and Tommaso Ciarli. Open configuration options Do Creative Industries Enhance Employment Growth? Regional Evidence from Colombia. Inter-American Development Bank, 2022. http://dx.doi.org/10.18235/0003993.

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Creative industries are considered highly innovative and productive, constituting an important driver of economic change. For high-income countries, several studies discuss the positive spillovers of creative industries for the local economy, for instance by attracting creative workers, which can benet entrepreneurs and workers in other industries. Like many other activities, creative industries are likely to dier in low- and middle-income countries compared to high-income countries. Moreover, the existing evidence is based on correlations between variables likely to be endogenous. This paper contributes to the literature on the role of creative industries in driving economic change in two main ways. First, we make a rst attempt to control for endogeneity and identify the impact of creative industries on local economies. Second, we report evidence for a middle-income country. Using granular employment data, we study the agglomeration patterns of creative industries across Colombian cities between 2008 and 2017. Exploiting the co-location of creative industries with other industries, we estimate the relation between employment growth in creative and non-creative industries in the same city. Using a shift-share instrumental variable approach, we estimate the multiplier eect of employment growth in creative industries on the employment growth in the rest of the economy. Creative industries represented between 2.7 and 3.3 percent of Colombian employment in 2008 and 2017. We nd that creative industries agglomerate mainly in three large cities (Bogota, Medelln, and Cartagena) and in a few smaller cities. Such agglomeration is positively related to an increase in the employment of non-creative services industries. For a positive causal relation to materialize, creative industries should have a larger size or be more connected to other economic sectors. However, after controlling for endogeneity, we nd no signicant impact of an increase of creative industries employment on employment growth in other industries.
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Scholz, Florian. Sedimentary fluxes of trace metals, radioisotopes and greenhouse gases in the southwestern Baltic Sea Cruise No. AL543, 23.08.2020 – 28.08.2020, Kiel – Kiel - SEDITRACE. GEOMAR Helmholtz Centre for Ocean Research Kiel, 2020. http://dx.doi.org/10.3289/cr_al543.

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R/V Alkor Cruise AL543 was planned as a six-day cruise with a program of water column and sediment sampling in Kiel Bight and the western Baltic Sea. Due to restrictions related to the Covid-19 pandemic, the original plan had to be changed and the cruise was realized as six oneday cruises with sampling in Kiel Bight exclusively. The first day was dedicated to water column and sediment sampling for radionuclide analyses at Boknis Eck and Mittelgrund in Eckernförde Bay. On the remaining five days, water column, bottom water, sediment and pore water samples were collected at eleven stations covering different types of seafloor environment (grain size, redox conditions) in western Kiel Bight. The data and samples obtained on cruise AL543 will be used to investigate (i) the sedimentary cycling of bio-essential metals (e.g., nickel, zinc, and their isotopes) as a function of variable redox conditions, (ii) the impact of submarine groundwater discharge and diffusive benthic fluxes on the distribution of radium and radon as well as greenhouse gases (methane and nitrous oxide) in the water column, and (iii) to characterize and quantify the impact of coastal erosion on sedimentary iron, phosphorus and rare earth element cycling in Kiel Bight.
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