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In the present paper, we study the information generating (IG) function and relative information generating (RIG) function measures associated with maximum and minimum ranked set sampling (RSS) schemes with unequal sizes. We also examine the IG measures for simple random sampling (SRS) and provide some comparison results between SRS and RSS procedures in terms of dispersive stochastic ordering. Finally, we discuss the RIG divergence measure between SRS and RSS frameworks.

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We study fault detection and isolation of multi-agent systems existing fault signals. Based upon the designing idea of unknown input observer, we proposed an innovative fault detection and isolation strategy. When the existence conditions are satisfied, the observer can be constructed using only relative information. A threshold logic and the corresponding algorithm are presented to detect and isolate the agent suffering from fault. Furthermore, a distributed implementation of our method is provided which helps to reduce the observer dimensions and simplify the design procedure. Practical simulations are given to demonstrate the validity of the theoretic results.

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Objective: Speech tests assess the ability of people with hearing loss to comprehend speech with a hearing aid or cochlear implant. The tests are usually at the word or sentence level. However, few tests analyze errors at the phoneme level. So, there is a need for an automated program to visualize in real time the accuracy of phonemes in these tests. Method: The program reads in stimulus-response pairs and obtains their phonemic representations from an open-source digital pronouncing dictionary. The stimulus phonemes are aligned with the response phonemes via a modification of the Levenshtein Minimum Edit Distance algorithm. Alignment is achieved via dynamic programming with modified costs based on phonological features for insertion, deletions and substitutions. The accuracy for each phoneme is based on the F1-score. Accuracy is visualized with respect to place and manner (consonants) or height (vowels). Confusion matrices for the phonemes are used in an information transfer analysis of ten phonological features. A histogram of the information transfer for the features over a frequency-like range is presented as a phonemegram. Results: The program was applied to two datasets. One consisted of test data at the sentence and word levels. Stimulus-response sentence pairs from six volunteers with different degrees of hearing loss and modes of amplification were analyzed. Four volunteers listened to sentences from a mobile auditory training app while two listened to sentences from a clinical speech test. Stimulus-response word pairs from three lists were also analyzed. The other dataset consisted of published stimulus-response pairs from experiments of 31 participants with cochlear implants listening to 400 Basic English Lexicon sentences via different talkers at four different SNR levels. In all cases, visualization was obtained in real time. Analysis of 12,400 actual and random pairs showed that the program was robust to the nature of the pairs. Conclusion: It is possible to automate the alignment of phonemes extracted from stimulus-response pairs from speech tests in real time. The alignment then makes it possible to visualize the accuracy of responses via phonological features in two ways. Such visualization of phoneme alignment and accuracy could aid clinicians and scientists.

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Nonlinear mixed-effects (NLME) modeling is one of the most powerful tools for analyzing longitudinal data especially under the sparse sampling design. The determinant of the Fisher information matrix is a commonly used global metric of the information that can be provided by the data under a given model. However, in clinical studies, it is also important to measure how much information the data provide for a certain parameter of interest under the assumed model, for example, the clearance in population pharmacokinetic models. This paper proposes a new, easy-to-interpret information metric, the "relative information" (RI), which is designed for specific parameters of a model and takes a value between 0% and 100%. We establish the relationship between interindividual variability for a specific parameter and the variance of the associated parameter estimator, demonstrating that, under a "perfect" experiment (eg, infinite samples or/and minimum experimental error), the RI and the variance of the model parameter estimator converge, respectively, to 100% and the ratio of the interindividual variability for that parameter and the number of subjects. Extensive simulation experiments and analyses of three real datasets show that our proposed RI metric can accurately characterize the information for parameters of interest for NLME models. The new information metric can be readily used to facilitate study designs and model diagnosis.

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This paper is focused on f-divergences, consisting of three main contributions. The first one introduces integral representations of a general f-divergence by means of the relative information spectrum. The second part provides a new approach for the derivation of f-divergence inequalities, and it exemplifies their utility in the setup of Bayesian binary hypothesis testing. The last part of this paper further studies the local behavior of f-divergences.

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Work over the past 20 years has demonstrated a gravity bias in toddlers; when an object is dropped into a curved tube, they will frequently search at a point immediately beneath the entry of the tube rather than in the object's actual location. The current study tested 2- to 3½-year-olds' (N = 88) gravity bias under consideration of object weight. They were tested with either a heavy or light ball, and they had information about either one of the balls only or both balls. Evaluating their first search behavior showed that participants generally displayed the same age trends as other studies had demonstrated, with older toddlers passing more advanced task levels by being able to locate objects in the correct location. Object weight appeared to have no particular impact on the direction of these trends. However, where weight was accessible as relative information, toddlers were younger at passing levels and older at failing levels, although significantly so only from around 3 years of age onward. When they failed levels, toddlers made significantly more gravity errors with the heavy ball when they had information about both balls and made more correct choices with the light ball. As a whole, the findings suggest that nonvisual object variables, such as weight, affect young children's search behaviors in the gravity task, but only if these variables are presented in relation to other objects. This relational information has the potential to enhance or diminish the gravity bias.

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Neural responses in visual cortex are governed by a topographic mapping from retinal locations to cortical responses. Moreover, at the voxel population level early visual cortex (EVC) activity enables accurate decoding of stimuli locations. However, in many cases information enabling one to discriminate between locations (i.e., discriminative information) may be less relevant than information regarding the relative location of two objects (i.e., relative information). For example, when planning to grab a cup, determining whether the cup is located at the same retinal location as the hand is hardly relevant, whereas the location of the cup relative to the hand is crucial for performing the action. We have previously used multivariate pattern analysis techniques to measure discriminative location information, and found the highest levels in EVC, in line with other studies. Here we show, using representational similarity analysis, that availability of discriminative information in fMRI activation patterns does not entail availability of relative information. Specifically, we find that relative location information can be reliably extracted from activity patterns in posterior intraparietal sulcus (pIPS), but not from EVC, where we find the spatial representation to be warped. We further show that this variability in relative information levels between regions can be explained by a computational model based on an array of receptive fields. Moreover, when the model's receptive fields are extended to include inhibitory surround regions, the model can account for the spatial warping in EVC. These results demonstrate how size and shape properties of receptive fields in human visual cortex contribute to the transformation of discriminative spatial representations into relative spatial representations along the visual stream.

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AIM: A capillary electrophoresis fingerprints(CEFP) method of Fructus Gardeniae was established to evaluate its quality. METHODS: The background electrolyte(BGE) was 25 mmol/L sodium borate solution containing 10% acetonitrile.The detection wavelength was 228 nm and 24 kV was applied.Fructus Gardeniae was extracted by water and injectded for 15 s(9 cm).Some parameters were used to evaluate the similarities.(RESULTS): 24 co-possessing peaks were selected as the fingerprint peaks of Fructus Gardeniae taking chlorogenic acid peak as the reference peak.The similarities between each of the ten places and the standard CEFP of Fructus Gardeniae were evaluated both qualitatively and quantitatively.The CEFP was also evaluated by the information index(I) and the relative information index(I_r). CONCLUSIONS: The CEFP has acceptable precision,reproducibility and can be used to control the quality of Fructus Gardeniae.