Unimodal Sampling Research Articles

Detrital zircons in metasedimentary rocks of Mayuan and Mamianshan Group from Cathaysia Block in northwestern Fujian Province, South China: New constraints on their formation ages and paleogeographic implication

Pre-Palaeozoic metasedimentary rocks are widespread in the Cathaysia Block but their accurate depositional ages are poorly constrained. Here we report a detailed study on U–Pb dating for zircons from the metasedimentary rocks in both Mamianshan and Mayuan groups from NW Fujian Province. The data show two models of age spectrum, i.e. multimodal and unimodal. Multimodal samples include detrital zircons from Daling and Longbeixi Formations of Mamianshan Group, Dajinshan Formation of Mayuan Group and Dikou Formation. Their age spectra are characterized by two prominent age groups of 1.3–0.9 Ga and 0.9–0.7 Ga, and two minor age groups of 0.7–0.5 Ga and 2.7–2.4 Ga. They all have the youngest age group of Ediacaran-Cambrian (ca. 0.61–0.53 Ga). Their age spectra resemble those of early Cambrian strata in Nanling and Yunkai regions of the Cathaysia Block, indicating that their depositional age is most likely Cambrian rather than previously proposed mid-Neoproterozoic or Paleoproterozoic. Therefore it is suggested that the originally named Mamianshan Group, Mayuan Group and Dikou Formation metamorphic strata are probably not anymore a traditional lithostratigraphic unit but a “complex” with rocks of multiple ages. The unimodal samples are all from Nanshan Formation of Mayuan Group, which show age spectra characterized by the dominating age cluster of mid-Neoproterozoic (ca. 0.88–0.74 Ga). The age spectra are very similar to those of the Cryogenian strata in Nanhua rift basin of the South China Block. Therefore, we suggest that the depositional age of those unimodal samples from Nanshan Formation is likely Cryogenian. In addition, detrital zircons from our Cryogenian samples are mostly euhedral-subhedral and they could be derived mainly from the South China Block itself. In contrast those Cambrian samples may have exotic East Gondwana derived detrital zircon compositions. Comparing age spectra of detrital zircons from different terranes, our studied Cambrian strata in the Cathaysia Block show a similarity to those of western and central North India-Himalaya. It is suggested that the Cathaysia Block should be more close to west and central India-Himalaya during Cambrian.

Xergy analysis and multiobjective optimization of a biomass gasification-based multigeneration system

Biomass gasification is the process of converting biomass into a combustible gas suitable for use in boilers, engines, and turbines to produce combined cooling, heat, and power. This paper presents a detailed model of a biomass gasification system and designs a multigeneration energy system that uses the biomass gasification process for generating combined cooling, heat, and electricity. Energy and exergy analyses are first applied to evaluate the performance of the designed system. Next, the minimizing total cost rate and the maximizing exergy efficiency of the system are considered as two objective functions and a multiobjective optimization approach based on the differential evolution algorithm and the local unimodal sampling technique is developed to calculate the optimal values of the multigeneration system parameters. A parametric study is then carried out and the Pareto front curve is used to determine the trend of objective functions and assess the performance of the system. Furthermore, sensitivity analysis is employed to evaluate the effects of the design parameters on the objective functions. Simulation results are compared with two other multiobjective optimization algorithms and the effectiveness of the proposed method is verified by using various key performance indicators.

Exergy analysis and multiobjective optimization of a biomass gasification based multigeneration system

Biomass gasification is a process of converting biomass to a combustible gas suitable for use in boilers, engines and turbines to produce combined cooling, heat and power. This paper presents a detailed model of a biomass gasification system and designs a multigeneration energy system which uses the biomass gasification process for generating combined cooling, heat and electricity. Energy and exergy analyses are first applied to evaluate the performance of the designed system. Next, minimizing total cost rate and maximizing exergy efficiency of the system are considered as two objective functions and a multiobjective optimization approach based on differential evolution algorithm and local unimodal sampling technique is developed to calculate the optimal values of the multigeneration system parameters. A parametric study is then carried out and Pareto front curve is used to determine the trend of objective functions and assess the performance of the system. Furthermore, a sensitivity analysis is employed to evaluate effects of design parameters on the objective functions. Simulation results are compared with two other multiobjective optimization algorithms and effectiveness of the proposed method is verified using various performance indicators.

A hybrid stochastic fractal search and local unimodal sampling based multistage PDF plus (1 + PI) controller for automatic generation control of power systems

This paper proposes to use a hybrid Stochastic Fractal Search (SFS) and Local Unimodal Sampling (LUS) based multistage Proportional Integral Derivative (PID) controller consisting of Proportional Derivative controller with derivative Filter (PDF) plus (1+Proportional Integral) for Automatic Generation Control (AGC) of power systems. Initially, a single area multi-source power system consisting of thermal hydro and gas power plants is considered and parameters of Integral (I) controller is optimized by Stochastic Fractal Search (SFS) algorithm. The superiority of SFS algorithm over some recently proposed approaches such as optimal control, Differential Evolution (DE) and Teaching Learning Based Optimization (TLBO) is demonstrated. To improve the system performance further, LUS is subsequently employed. The study is further extended for different controllers like PID, and proposed multistage PID controller and the superiority of multistage PID controller over conventional PID controller structure is demonstrated. The study is further extended to a two-area six unit multi-source interconnected power system and the superiority of proposed approach over, TLBO and optimal control is demonstrated. Finally the study is extended to a three unequal area system power system with appropriate nonlinearities such as Generation Rate Constraint (GRC), Governor Dead Band (GDB) and time delay. From the analysis, it is found that hybrid SFS–LUS algorithm is superior to the original SFS algorithm and substantial improvement in system performance are realized with proposed multistage PID controller over conventional PID controller structure.

A novel SVM-kNN-PSO ensemble method for intrusion detection system

In machine learning, a combination of classifiers, known as an ensemble classifier, often outperforms individual ones. While many ensemble approaches exist, it remains, however, a difficult task to find a suitable ensemble configuration for a particular dataset. This paper proposes a novel ensemble construction method that uses PSO generated weights to create ensemble of classifiers with better accuracy for intrusion detection. Local unimodal sampling (LUS) method is used as a meta-optimizer to find better behavioral parameters for PSO. For our empirical study, we took five random subsets from the well-known KDD99 dataset. Ensemble classifiers are created using the new approaches as well as the weighted majority algorithm (WMA) approach. Our experimental results suggest that the new approach can generate ensembles that outperform WMA in terms of classification accuracy.

A novel hybrid LUS–TLBO optimized fuzzy-PID controller for load frequency control of multi-source power system

Abstract In this paper, a novel hybrid Local Unimodal Sampling (LUS) and Teaching Learning Based Optimization (TLBO) based fuzzy-PID controller is proposed for load frequency control (LFC) of a two-area interconnected multi-source power system with and without HVDC link. Each area of the multi-source power system consists of a reheat thermal, a hydro and a gas unit. Fuzzy-PID and conventional PID controllers are used to study the dynamic performance of the power system by applying a step load change of 0.01 pu in area1. The scaling factors of the fuzzy-PID controllers and the conventional PID controllers’ gains are optimized using the proposed hybrid LUS and TLBO (LUS–TLBO) algorithm. The supremacy of the proposed LUS–TLBO algorithm optimized fuzzy-PID controller is proved for both the power systems (with and without HVDC link) by comparing the results with that of recently published article based on Differential Evolution (DE) algorithm optimized conventional PID controller for the same power systems. Again the robustness of the proposed controller for power system with AC tie-line only is studied under parametric variation conditions by varying all the parameters from −50% to 50% of their nominal values in steps of 25%. Finally it is seen that LUS–TLBO optimized fuzzy-PID controller exhibit superior performance as compared to DE optimized fuzzy-PID controller and hybrid LUS–TLBO, TLBO, LUS & DE optimized conventional PID controller.

Tuning and Assessment of Proportional–Integral–Derivative Controller for an Automatic Voltage Regulator System Employing Local Unimodal Sampling Algorithm

—This article presents an approach for obtaining proportional–integral–derivative controller parameters for an automatic voltage regulator system based on a local unimodal sampling optimization algorithm. A conventional integral time of squared error objective function and modified objective functions in terms of integral time of absolute error, integral of absolute error, integral of squared error, peak overshoot, and settling time with appropriate weighting factors are employed to tune the controller parameters. Different objective functions are employed to obtain optimized proportional–integral–derivative controller gains. Superiority of proposed technique over some recently published modern heuristic optimization techniques, such as artificial bee colony algorithm, particle swarm optimization algorithm, and differential evolution algorithm, for the same automatic voltage regulator system is demonstrated. Simulation results reveal that the proposed proportional–integral–derivative controlled automatic voltage regulator system tuned by the local unimodal sampling algorithm with modified objective function exhibits better performance in terms of settling time, peak overshoot, and stability. The robustness of the system tuned by the proposed algorithm is also studied satisfactorily by varying the time constants of the automatic voltage regulator system in the range of –50% to +50% in steps of 25%.

Identification of multi-modal random variables through mixtures of polynomial chaos expansions

A methodology is introduced for the identification of a multi-modal real-valued random variable from a collection of samples. The random variable is seen as a finite mixture of uni-modal random variables. A functional representation of the random variable is used, which can be interpreted as a mixture of polynomial chaos expansions. After a suitable separation of samples into sets of uni-modal samples, the coefficients of the expansion are identified by using an empirical projection technique. This identification procedure allows for a generic representation of a large class of multi-modal random variables with low-order generalized polynomial chaos representations.

Measures of central tendency in rehabilitation research: what do they mean?

Measures of central tendency including the mean, median, and mode are commonly reported in rehabilitation research. It is believed that the relationship among the mean, median, and mode changes in a specific way when the distribution being analyzed is skewed. A number of widely used textbooks were reviewed to determine how the relationship among the mean, median, and mode is presented in the health sciences and rehabilitation literature. We report a potential misinterpretation of the relationship between measures of central tendency that was identified in several research and statistical textbooks on the subject of rehabilitation. The misinterpretation involves measures of central tendency derived from skewed unimodal sample distributions. The reviewed textbooks state or imply that in asymmetrical distributions, the median is always located between the mode and mean. An example is presented illustrating the fallacy of this assumption. The mean and median will always be to the right of the mode in a positively skewed unimodal distribution and to the left of the mode in a negatively skewed distribution; the order of the mean and median is impossible to predict or generalize. The assumption that the median always falls between the mode and mean in the calculation of coefficients of skewness has implications for the interpretation of exploratory and confirmatory data analysis in rehabilitation research.

Placement of observations for the efficient estimation of a psychometric function

Psychometric functions for different psychophysical tasks describe the relationship between physical stimuli and subjects' responses. Although a psychometric function is of considerable value, characterizing the function is time consuming and, hence, is not carried out routinely in psychophysical experiments. A principal reason for the lack of efficiency in characterizing the psychometric function is the use of unimodal (e.g., Gaussian and uniform) sampling methods. As an alternative, a multimodal four-point sampling method is proposed. A psychometric function is then fitted to the four data points (each with several trials) to estimate the threshold and slope parameters of the psychometric function. Results from three examples demonstrate that a 60% savings in data-collection time can be achieved.

The interpretation of averages in health professions research. An empirical examination.

A potential misinterpretation regarding measures of central tendency was identified in several health sciences textbooks presenting basic statistical procedures. The misinterpretation involves measures of central tendency derived from skewed unimodal sample distributions. The reviewed textbooks state or imply that in asymmetrical distributions the median is always located between the mode and mean. An example is presented illustrating the fallacy of this assumption. The mean and median will always be to the right of the mode in a positively skewed unimodal distribution and to the left of the mode in a negatively skewed distribution, but the order of the mean and median is impossible to predict or generalize. The assumption that the median always falls between the mode and mean in the calculation of coefficients of skewness has implications for the interpretation of health sciences research.

Fish Population Structure in Arctic Lakes

Existing theories attempting to account for the predominance of older, larger individuals and the often observed bimodal character of the length-frequency distribution of unexploited northern fish populations were evaluated and rejected. The error in interpretation appears to result from problems in age determination of northern lake trout (Salvelinus namaycush) and lake whitefish (Coregonus clupeaformis). An alternative explanation of the observed structure of arctic lake fish populations is proposed. Growth of fish in these populations is relatively rapid until first maturity, when it becomes slow through a life span that may exceed 50 yr. Mortality declines rapidly through early life and stabilizes at a very low level through much of the life span. The combination of these growth and mortality patterns produces a population containing many small, few intermediate, and many large fish. Selection by gill nets provides a unimodal sample of large fish or a bimodal sample of large and smaller fish from such populations. A model is developed to demonstrate this and compared with results obtained from several northern Quebec lakes. Key words: Salvelinus namaycush, Coregonus clupeaformis, age, population structure, arctic lakes

Verbal and extraverbal components of language as related to lateralized brain damage.

Twelve patients with left cerebral hemisphere lesions and 12 with right hemisphere lesions chose, from among four alternatives, the word that was identical in spelling to a sample word (verbal or extraverbal components sufficient to perform task at this level), and chose a synonym of the sample word from among four alternatives (verbal component necessary). The words were presented in unimodal and cross-modal conditions. In the unimodal conditions sample words and alternatives were presented in the same modality (aural or visual); in the cross-modal conditions the sample word was presented in one modality (A or V) and the alternatives in the opposite modality (V or A). The subject responded by pushing a button when he perceived the correct choice. Patients with right-sided lesions had significantly greater response times, and more errors, than patients with left-sided lesions on those items in which the extraverbal component was crucial to successful performance. The converse was true on those items that called for greater facility with the verbal component of language. There were no significant differences between unimodal and cross-modal tasks.