Windowing applied to a given signal is a technique commonly used in signal processing in order to reduce spectral leakage in a signal with many data. Several windows are well known: hamming, hanning, beartlett, etc. T...Windowing applied to a given signal is a technique commonly used in signal processing in order to reduce spectral leakage in a signal with many data. Several windows are well known: hamming, hanning, beartlett, etc. The selection of a window is based on its spectral characteristics. Several papers that analyze the amplitude and width of the lobes that appear in the spectrum of various types of window have been published. This is very important because the lobes can hide information on the frequency components of the original signal, in particular when frequency components are very close to each other. In this paper it is shown that the size of the window can also have an impact in the spectral information. Until today, the size of a window has been chosen in a subjective way. As far as we know, there are no publications that show how to determine the minimum size of a window. In this work the frequency interval between two consecutive values of a Fourier Transform is considered. This interval determines if the sampling frequency and the number of samples are adequate to differentiate between two frequency components that are very close. From the analysis of this interval, a mathematical inequality is obtained, that determines in an objective way, the minimum size of a window. Two examples of the use of this criterion are presented. The results show that the hiding of information of a signal is due mainly to the wrong choice of the size of the window, but also to the relative amplitude of the frequency components and the type of window. Windowing is the main tool used in spectral analysis with nonparametric periodograms. Until now, optimization was based on the type of window. In this paper we show that the right choice of the size of a window assures on one hand that the number of data is enough to resolve the frequencies involved in the signal, and on the other, reduces the number of required data, and thus the processing time, when very long files are being analyzed.展开更多
The male gametogenic cycle, spawning season, first sexual maturity, and the biological minimum size in male Ruditapes philippinarum were investigated by qualitative and quantitative reproductive analyses. In the study...The male gametogenic cycle, spawning season, first sexual maturity, and the biological minimum size in male Ruditapes philippinarum were investigated by qualitative and quantitative reproductive analyses. In the study of the male gametogenic cycle by qualitative histological analysis, the gametogenic cycle in male individuals can be classified into five successive stages： （1） early active stage, （2） late active stage, （3） ripe stage, （4） partially spawned stage, and （5） spent and inactive stage. Monthly changes in the gonad index in males measured by qualitative analysis showed a similar pattern to the male gametogenic cycle. In the study of the male gametogenic cycle by quantitative statistical analysis, monthly changes in the portions （%） of areas occupied by the testis areas to total tissue areas showed a rapid increase in March, and reached the maximum in May-June. And also monthly changes in the portions （%） of areas occupied by the spermatogenic stages to the testis area showed a maximum in May and gradually decreased from June to October. Therefore, this species showed a unimodal gametogenic cycle during the year, and the number of spawning seasons occurred once per year, from June to October, with a peak spawning between July and August. The percentage at the first sexual maturity of male clams ranging from 15.1-20.0 mm in shell length was 64.7%, and that of all individuals ranging from over 25.1 mm in shell length was 100%. The biological minimum size （shell lengths at 50% of sexual maturity （RMs0）） of male mature clams that was fitted to an exponential equation was 17.16 mm （considered to be 1 year old）. Because harvesting clams less than 17.16 mm in shell length could potentially cause a drastic reduction in recruitment, a measure indicating a prohibitory fishing size should be enacted for adequate fisheries management.展开更多
Purpose： The main goal of this study is to provide reliable comparison of performance in higher education. In this respect, we use scientometric measures associated with faculties of medicine in the six health studie...Purpose： The main goal of this study is to provide reliable comparison of performance in higher education. In this respect, we use scientometric measures associated with faculties of medicine in the six health studies universities in Romania.Design/methodology/approach： The method to estimate the minimum necessary size, proposed in in Shen et al.（2017）, is applied in this article. We collected data from the Scopus data-base for the academics of the departments of medicine within the six health studies universities in Romania during the 2009 to 2014. And two kind of statistic treatments based on that method are implemented, pair-wise comparison and one-to-the-rest comparison. All the results of these comparisons are shown.Findings： According to the results： We deem that Cluj and Tg. Mure？ have the superior and inferior performance respectively, since their reasonably small value of the minimum representative size, in either of the kinds of comparison, whichever indexes of citations, h-index, or g-index is used. we can not reliably distinguish differences among the rest of the faculties, since the quite large value of their minimum representative size.Research limitations： There is only six faculties of medicine in health studies universities in Romania are analyzed.Practical implications： Our methods of comparison play an important role in ranking data sets associated with different collective units, such as faculties, universities, institutions, based on some aggregate scores like mean and totality. Originality/value： We applied the minimum representative size to a new emprical context- that of the departments of medicine in the health studies universities in Romania.展开更多
This article constructs statistical selection procedures for exponential populations that may differ in only the threshold parameters. The scale parameters of the populations are assumed common and known. The independ...This article constructs statistical selection procedures for exponential populations that may differ in only the threshold parameters. The scale parameters of the populations are assumed common and known. The independent samples drawn from the populations are taken to be of the same size. The best population is defined as the one associated with the largest threshold parameter. In case more than one population share the largest threshold, one of these is tagged at random and denoted the best. Two procedures are developed for choosing a subset of the populations having the property that the chosen subset contains the best population with a prescribed probability. One procedure is based on the sample minimum values drawn from the populations, and another is based on the sample means from the populations. An “Indifference Zone” (IZ) selection procedure is also developed based on the sample minimum values. The IZ procedure asserts that the population with the largest test statistic (e.g., the sample minimum) is the best population. With this approach, the sample size is chosen so as to guarantee that the probability of a correct selection is no less than a prescribed probability in the parameter region where the largest threshold is at least a prescribed amount larger than the remaining thresholds. Numerical examples are given, and the computer R-codes for all calculations are given in the Appendices.展开更多
文摘Windowing applied to a given signal is a technique commonly used in signal processing in order to reduce spectral leakage in a signal with many data. Several windows are well known: hamming, hanning, beartlett, etc. The selection of a window is based on its spectral characteristics. Several papers that analyze the amplitude and width of the lobes that appear in the spectrum of various types of window have been published. This is very important because the lobes can hide information on the frequency components of the original signal, in particular when frequency components are very close to each other. In this paper it is shown that the size of the window can also have an impact in the spectral information. Until today, the size of a window has been chosen in a subjective way. As far as we know, there are no publications that show how to determine the minimum size of a window. In this work the frequency interval between two consecutive values of a Fourier Transform is considered. This interval determines if the sampling frequency and the number of samples are adequate to differentiate between two frequency components that are very close. From the analysis of this interval, a mathematical inequality is obtained, that determines in an objective way, the minimum size of a window. Two examples of the use of this criterion are presented. The results show that the hiding of information of a signal is due mainly to the wrong choice of the size of the window, but also to the relative amplitude of the frequency components and the type of window. Windowing is the main tool used in spectral analysis with nonparametric periodograms. Until now, optimization was based on the type of window. In this paper we show that the right choice of the size of a window assures on one hand that the number of data is enough to resolve the frequencies involved in the signal, and on the other, reduces the number of required data, and thus the processing time, when very long files are being analyzed.
文摘The male gametogenic cycle, spawning season, first sexual maturity, and the biological minimum size in male Ruditapes philippinarum were investigated by qualitative and quantitative reproductive analyses. In the study of the male gametogenic cycle by qualitative histological analysis, the gametogenic cycle in male individuals can be classified into five successive stages： （1） early active stage, （2） late active stage, （3） ripe stage, （4） partially spawned stage, and （5） spent and inactive stage. Monthly changes in the gonad index in males measured by qualitative analysis showed a similar pattern to the male gametogenic cycle. In the study of the male gametogenic cycle by quantitative statistical analysis, monthly changes in the portions （%） of areas occupied by the testis areas to total tissue areas showed a rapid increase in March, and reached the maximum in May-June. And also monthly changes in the portions （%） of areas occupied by the spermatogenic stages to the testis area showed a maximum in May and gradually decreased from June to October. Therefore, this species showed a unimodal gametogenic cycle during the year, and the number of spawning seasons occurred once per year, from June to October, with a peak spawning between July and August. The percentage at the first sexual maturity of male clams ranging from 15.1-20.0 mm in shell length was 64.7%, and that of all individuals ranging from over 25.1 mm in shell length was 100%. The biological minimum size （shell lengths at 50% of sexual maturity （RMs0）） of male mature clams that was fitted to an exponential equation was 17.16 mm （considered to be 1 year old）. Because harvesting clams less than 17.16 mm in shell length could potentially cause a drastic reduction in recruitment, a measure indicating a prohibitory fishing size should be enacted for adequate fisheries management.
文摘Purpose： The main goal of this study is to provide reliable comparison of performance in higher education. In this respect, we use scientometric measures associated with faculties of medicine in the six health studies universities in Romania.Design/methodology/approach： The method to estimate the minimum necessary size, proposed in in Shen et al.（2017）, is applied in this article. We collected data from the Scopus data-base for the academics of the departments of medicine within the six health studies universities in Romania during the 2009 to 2014. And two kind of statistic treatments based on that method are implemented, pair-wise comparison and one-to-the-rest comparison. All the results of these comparisons are shown.Findings： According to the results： We deem that Cluj and Tg. Mure？ have the superior and inferior performance respectively, since their reasonably small value of the minimum representative size, in either of the kinds of comparison, whichever indexes of citations, h-index, or g-index is used. we can not reliably distinguish differences among the rest of the faculties, since the quite large value of their minimum representative size.Research limitations： There is only six faculties of medicine in health studies universities in Romania are analyzed.Practical implications： Our methods of comparison play an important role in ranking data sets associated with different collective units, such as faculties, universities, institutions, based on some aggregate scores like mean and totality. Originality/value： We applied the minimum representative size to a new emprical context- that of the departments of medicine in the health studies universities in Romania.
文摘This article constructs statistical selection procedures for exponential populations that may differ in only the threshold parameters. The scale parameters of the populations are assumed common and known. The independent samples drawn from the populations are taken to be of the same size. The best population is defined as the one associated with the largest threshold parameter. In case more than one population share the largest threshold, one of these is tagged at random and denoted the best. Two procedures are developed for choosing a subset of the populations having the property that the chosen subset contains the best population with a prescribed probability. One procedure is based on the sample minimum values drawn from the populations, and another is based on the sample means from the populations. An “Indifference Zone” (IZ) selection procedure is also developed based on the sample minimum values. The IZ procedure asserts that the population with the largest test statistic (e.g., the sample minimum) is the best population. With this approach, the sample size is chosen so as to guarantee that the probability of a correct selection is no less than a prescribed probability in the parameter region where the largest threshold is at least a prescribed amount larger than the remaining thresholds. Numerical examples are given, and the computer R-codes for all calculations are given in the Appendices.
