Effect Of Sample Length Research Articles

Effect of sample length on MLU in Mandarin-speaking hard-of-hearing children.

This study investigated the impact of language sample length on mean length of utterance (MLU) and aimed to determine the minimum number of utterances required for a reliable MLU. Conversations were collected from Mandarin-speaking, hard-of-hearing and typical-hearing children aged 16-81months. The MLUs were calculated using sample sizes ranging from 25 to 200 utterances. The results showed that for an MLU between 1.0 and 2.5, 25 and 50 utterances were sufficient for reliable MLU calculations for hard-of-hearing and typical-hearing children, respectively. For an MLU between 2.5 and 3.75, 125 utterances were required for both groups. For an MLU greater than 3.75, 150 and 125 utterances were required for hard-of-hearing and typical-hearing children, respectively. These findings suggest that a greater number of utterances are required for a reliable MLU as language complexity increases. Professionals working with hard-of-hearing children should consider collecting different numbers of utterances based on the children's language complexity levels.

Wavelet characterizing the non-stationary features of mountain valley winds both in frequency and time domain

This study aimed to quantify and evaluate the non-stationary characteristics of wind speed in mountain canyon terrain. A non-stationarity index was proposed based on continuous wavelet transform to quantitatively evaluate the non-stationarity of measured wind speed samples in both time and frequency domains. Subsequently, the effect of sample length and observation time interval of wind speed samples on the non-stationarity index was investigated. In addition, the non-stationarity of mountain canyon winds was compared with that of normal climate winds under the same sample length and observation time interval. The results indicate that the non-stationarity index based on wavelet transform can quantitatively evaluate the non-stationary characteristics of wind speed. With an increase in the sample length of wind speed series, the non-stationarity of wind speed increase gradually, and its probability distribution becomes more positively skewed. When the sample length of wind speed does not exceed 10 min, the probability distribution of non-stationarity index for mountain valley terrain and normal climate winds is not significantly different, which implies that it is reasonable for most countries to use a 10-min statistical length to calculate average wind speed. However, the difference in the probability distribution of non-stationarity index between mountain and normal climate winds significantly increases when the sample length exceeds 10 min. Besides, the non-stationarity index can reflect the non-stationary characteristics of wind speed series at different frequency components. Higher frequency components in wind speed exhibit stronger non-stationary characteristics. Moreover, mountain winds exhibit stronger non-stationary characteristics than normal climate winds in amplitude and frequency, especially the high-frequency components in wind speed series with long sample lengths.

Reducing cost with MEMS sensor and improving performance of classifier using probabilistic voting method

When developing a solution for fault diagnosis, cost is a critical factor that must be considered to ensure a practical and feasible final product. To reduce expenses, the authors conducted a feasibility study using a low-cost MEMS accelerometer in conjunction with an Arduino Uno. This study aimed to determine the effect of sample length on fault classification by varying it from 50 to 5000 to identify the optimal value for this particular application. After finalizing the parameters, the vibration signal was acquired using the MEMS sensor and Arduino Uno. The resulting classification accuracy using the decision tree was 90.2%, a satisfactory result that can be further improved for industrial applications. To enhance the accuracy of decision tree classifiers, the authors proposed a novel approach known as the probabilistic voting method. By implementing this method and utilizing an Arduino Uno and MEMS sensor (ADXL335), they were able to drastically cut down costs while achieving remarkable classification accuracy. The implementation of the probabilistic voting method further elevated the accuracy to an astounding 98.5%, setting a new benchmark in the field.

Microwave-assisted puffing of Dendrobium officinale for higher extraction rate of polysaccharides

In order to increase the extraction rate of Dendrobium officinale polysaccharides, microwave puffing was used to process its fresh stems and the processing parameters were optimized. Response surface methodology was used to analyze the effects of sample length (1–5cm), moisture content (15%–25%), microwave power (550–790 W), and microwave processing time (20–40 s) on the expansion ratio. The results showed that the optimized expansion ratio of 371.7% was achieved at the following conditions, i.e., sample length of 3.5 cm, moisture content of 23%, microwave power of 706 W, and processing time of 35 s. It was found that polysaccharides were extracted more readily from puffed D. officinale than from non-puffed D. officinale by 41.8%. Moreover, the bioactivities of polysaccharides from puffing D. officinale and non-puffing D. officinale were evaluated and compared in lipid peroxidation inhibition and anti-hyperglycemic assays.
 Keywords: Dendrobium officinale; Microwave puffing; Polysaccharides; Lipid peroxidation; Anti-hyperglycemic activity

Embedding-Assisted Attentional Deep Learning for Real-World RF Fingerprinting of Bluetooth

A scalable and computationally efficient framework is designed to fingerprint real-world Bluetooth devices. We propose an embedding-assisted attentional framework (Mbed-ATN) suitable for fingerprinting actual Bluetooth devices. Its generalization capability is analyzed in different settings and the effect of sample length and anti-aliasing decimation is demonstrated. The embedding module serves as a dimensionality reduction unit that maps the high dimensional 3D input tensor to a 1D feature vector for further processing by the ATN module. Furthermore, unlike the prior research in this field, we closely evaluate the complexity of the model and test its fingerprinting capability with real-world Bluetooth dataset collected under a different time frame and experimental setting while being trained on another. Our study reveals a 9.17× and 65.2× lesser memory usage at a sample length of 100 kS when compared to the benchmark -GRU and Oracle models respectively. Further, the proposed Mbed-ATN showcases a 16.9× fewer FLOPs and 7.5× lesser trainable parameters when compared to Oracle. Finally, we show that when subject to anti-aliasing decimation and at greater input sample lengths of 1 MS, the proposed Mbed-ATN framework results in a 5.32× higher TPR, 37.9% fewer false alarms, and 6.74× higher accuracy under the challenging real-world setting.

In Vitro Thrombogenicity Testing of Biomaterials in a Dynamic Flow Loop: Effects of Length and Quantity of Test Samples.

The results of in vitro dynamic thrombogenicity testing of biomaterials and medical devices can be significantly impacted by test conditions. To develop and standardize a robust dynamic in vitro thrombogenicity tool, the key test parameters need to be appropriately evaluated and optimized. We used a flow loop test system previously developed in our laboratory to investigate the effects of sample length and the number of samples per test loop on the thrombogenicity results. Porcine blood heparinized to a donor-specific target concentration was recirculated at room temperature through polyvinyl chloride (PVC) tubing loops containing test materials for 1 h at 200 mL/min. Four test materials (polytetrafluoroethylene (PTFE), latex, PVC, and silicone) with various thrombotic potentials in two sample lengths (12 and 18 cm) were examined. For the 12-cm long materials, two different test configurations (one and two samples per loop) were compared. Thrombogenicity was assessed through percent thrombus surface coverage, thrombus weight, and platelet count reduction in the blood. The test system was able to effectively differentiate the thrombogenicity profile of the materials (latex > silicone > PVC ≥ PTFE) at all test configurations. Increasing test sample length by 50% did not significantly impact the test results as both 12 and 18 cm sample lengths were shown to equally differentiate thrombotic potentials between the materials. The addition of a second test sample to each loop did not increase the test sensitivity and may produce confounding results, and thus a single test sample per loop is recommended.

Effect of Samples Length on the Characteristics of Moisture Transfer and Shrinkage of Eucalyptus urophylla Wood during Conventional Drying

Moisture transfer influences wood deformation and moisture content (MC) distribution during conventional drying of Eucalyptus urophylla wood. This study aims to investigate the effect of sample length (30, 100, and 200 mm) on moisture distribution and transfer in different directions and locations and on deformation of wood. The results showed that when the MC was above the fiber saturated point (FSP), the drying rate decreases exponentially with an increase of sample length; however, below the FSP, there was no obvious relationship between the drying rate and sample length and above the FSP, the moisture distribution was non-uniform along tangential, radial, and longitudinal directions and became even below the FSP, which was more significant in the middle location of wood. The greatest MC differences occurred between the surface and sub-central layers along the tangential and radial direction, which were between the end and sub-middle locations along the longitudinal direction. The effect of sample length on the MC distribution and MC differences along wood in the three directions depended on locations and the MC stage of wood; most of the free water and bound water transferred from the wood central to the ends along the longitudinal direction for three sets of samples. Bound water diffusion significantly slowed as the sample length exceeded 200 mm; sample length affects wood collapse and its recovery, but the drying rate has a lesser effect on collapse for samples with a length below 200 mm.

Investigation the Effect of Sample Length in Different Currents and Frequencies of Measurement on the Magneto Impedance, Sensitivity and Extinction Field of Amorphous Cobalt Based Ribbons

In this paper, the effect of sample length on different currents and frequencies of measurement on magneto impedance (MI) of amorphous cobalt based ribbons was investigated. Firstly, we cut the ribbon to 4 cm length and then measurements of MI were carried out in constant current of 8 mA and frequency ranges between 1 to 15 MHz. The maximum sensitivity (9.16 Oe-1) at a frequency of 11 MHz was obtained. Also, the maximum extinction field was obtain 41.6 Oe. In the next step, the currents of 6 to 14 mA and the frequencies from 1 to 6 MHz were examined and in the optima conditions the maximum MI reached to 195%. In the next step, the length of ribbon was reduced to 2 cm and the MI was measured at previous currents and frequencies that results showed the reduction of MI in the most of conditions. In addition, at frequency ranges between 1 to 15 MHz, the maximum sensitivity was 10.2 Oe-1 and the maximum extinction field was 52.3 Oe. As a result, by decreasing the length of the ribbon, the MI reduce, but the sensitivity and excitation field increases, which is suitable for sensing applications. This behavior can be explained due to the demagnetization field, which is strongly dependent on the sample length.

An examination of sample length and reliability of the Interactional Network Tool, a new measure of group interactions in acquired brain injury

ABSTRACT Background Conversation is challenging to measure. Quantitative and qualitative measures need to be sensitive to the conversation context, the purpose and the variable contributions of participants in order to capture meaningful change. Measurements also need to be consistent across independent raters. The reliability of global observational rating scales across differing sample lengths has previously been investigated. An investigation into the effects of sample length on inter-rater reliability using a behavioural frequency measure is a new field of research. Aims This study reports on the inter-rater reliability of the Interactional Network Tool (INT), a behavioural coding system for use with group interaction data. It examines the effects of sample length on reliability using a refined coding system designed to improve the speed and efficiency of use in clinical settings. Methods Fourteen video samples of group interactions for people with acquired brain injury were prepared for analysis. Two raters independently coded the films using the INT coding system. Individual code reliability was calculated using intra-class correlations (ICCs). Codes were combined to form a new coding structure. Reliability of the new codes was calculated using intra-class correlations across four sample lengths (5,10,15 and 20 minutes). A one-way analysis of variance was used to compare the means of the four sample lengths. Outcomes and Results Acceptable inter-rater reliability was achieved using the refined INT coding system. There was no difference between the four sample lengths. Conclusions These findings indicate that trained clinicians using the INT in clinical practice can achieve a reliable measure of participation in a group interaction from short samples. Validation with other clinical groups is now indicated.

Hygroexpansion behaviors of bamboo in response to moisture absorption and desorption

As a natural cellulosic material, bamboo is hygroscopic. Its dimension changes in response to moisture variations. The purpose of this study aimed to investigate the variations of hygro-expansion, moisture absorption and desorption behaviors of bamboo’s internodes and nodes, as well as the effect of sample length on the moisture absorption and desorption. The results showed that the rate of moisture absorption and desorption of the nodes was relatively higher than that of internodes at initial stage, and then tends to converge the same, which follow a two-stage exponential model and experience rapid and slow stage for both internodes and nodes. An anisotropic hygro-expansion existed during absorption and desorption, with significantly larger deformations in transverse direction than in longitudinal direction. It was observed that swelling in radial direction were relatively larger than in tangential direction, while shrinkage was just opposite. The longitudinal deformations were less than 0.6% and can be ignored in many situations. A second-order effect of moisture absorption on dimensional changes and anisotropic behavior was confirmed by the facts that transverse dimensional changes were more during desorption compared to adsorption. The swelling and shrinkage behaviors of the external, middle and internal layers in radial direction of samples are different, but no significant difference was detected. The dimensional changes in radical and tangential directions were significantly different between the nodes and internodes. The sample length has no effect on the rate of moisture absorption and desorption. The moisture absorption capacity of the oven-dried samples is much lower than that of green samples. The results can provide knowledge and ideas for the improvement of drying technique in new-typed bamboo structural products, as well as for the evaluation of deformation and structural stability of modern bamboo constructions.

Effect of sample deformation in longitudinal axis on material parameter extraction by waveguides

An analysis was performed for examining the consequences of sample deformation in longitudinal axis in the sample-loaded non-resonant waveguide techniques. Vertical and horizontal deformations were first simulated to understand the change in field distributions and corresponding scattering parameters. Then, effects of sample length, dielectric constant, and loss factor for these deformations on extracted electromagnetic properties were analyzed using simulated results. Finally, S-parameter measurements were carried out to understand the effect of vertical deformation on permittivity results and to examine any improper sample preparation by hand-made and machine-made samples by applying a statistical model based on mean, standard deviation, coefficient of variation, and confidence interval. It was noted that extracted dielectric constants of each tested dielectric sample (polyethylene, polypropylene, polyvinyl-chloride) were within the confidence interval range of 90% while their retrieved loss factors were within the confidence interval range of 90%, 95%, or 98%.

An Integrative Framework for Combining Sequence and Epigenomic Data to Predict Transcription Factor Binding Sites Using Deep Learning

Knowing the transcription factor binding sites (TFBSs) is essential for modeling the underlying binding mechanisms and follow-up cellular functions. Convolutional neural networks (CNNs) have outperformed methods in predicting TFBSs from the primary DNA sequence. In addition to DNA sequences, histone modifications and chromatin accessibility are also important factors influencing their activity. They have been explored to predict TFBSs recently. However, current methods rarely take into account histone modifications and chromatin accessibility using CNN in an integrative framework. To this end, we developed a general CNN model to integrate these data for predicting TFBSs. We systematically benchmarked a series of architecture variants by changing network structure in terms of width and depth, and explored the effects of sample length at flanking regions. We evaluated the performance of the three types of data and their combinations using 256 ChIP-seq experiments and also compared it with competing machine learning methods. We find that contributions from these three types of data are complementary to each other. Moreover, the integrative CNN framework is superior to traditional machine learning methods with significant improvements.

Quantifying vulnerability to embolism in tropical trees and lianas using five methods: can discrepancies be explained by xylem structural traits?

Vulnerability curves (VCs) describe the loss of hydraulic conductance against increasing xylem tension, providing valuable insights about the response of plant water transport to water stress. Techniques to construct VCs have been developed and modified continuously, but controversies continue. We compared VCs constructed using the bench-top dehydration (BD), air-injection-flow (AI), pneumatic-air-discharge (PAD), optical (OP) and X-ray-computed microtomography (MicroCT) methods for tropical trees and lianas with contrasting vessel lengths. The PAD method generated highly vulnerable VCs, the AI method intermediate VCs, whereas the BD, OP and MicroCT methods produced comparable and more resistant VCs. Vessel-length and diameter accounted for the overestimation ratio of vulnerability estimated using the AI but not the PAD method. Compared with directly measured midday embolism levels, the PAD and AI methods substantially overestimated embolism, whereas the BD, MicroCT and OP methods provided more reasonable estimations. Cut-open vessels, uncertainties in maximum air volume estimations, sample-length effects, tissue cracks and shrinkage together may impede the reliability of the PAD method. In conclusion, we validate the BD, OP and MicroCT methods for tropical plants, whereas the PAD and AI need further mechanistic testing. Therefore, applications of VCs in estimating plant responses to drought need to be cautious.

Evaluating the effect of sample length on forecasting validity of FGM(1,1)

Three indicators (GDP, PCDIIP-rh and Total Population) are selected in this paper to study the effect of sample length on forecasting validity of FGM(1,1). It has passed the test, such as development coefficient, mean relative error within the sample, and ratio of mean square error. The above three sets of indicators are proved to be suitable for FGM(1,1) to make predictions. The results of the study indicate that the forecasting of 4–6 sample lengths is the most appropriate. The MAPE of 5 sample length is better than sample lengths 4 or 6. The conclusion of this study is verified by taking the oil production of India and Canada as examples. On this basis, the sample length 5 is selected to predict the average annual concentration of PM2.5 from 2019 to 2021 in Xingtai. The forecasting results show that the PM2.5 in Xingtai will decline in the next three years, but it will not reach the national level 2 concentration limit.

Effect of Sample Length on the Time Needed to Reach the Steady State Case

In this study, ANSYS-14 was used to study the effect of the length of the sample on the time needed to reach steady state (S.S.t) for the transient heat transfer. Three samples were studied in different lengths (15, 30 and 45 cm), 2 cm high, in addition to the selection of three materials with different thermal properties and applied to different lengths. One side of the three samples was exposed to a temperature at 100 ° C, while the other side was exposed to thermal load at 25 ° C and the sample was isolated from the top and bottom surfaces. The objective of this study is to determine the effect of the time reach to the steady state when changing the length of the sample exposed to constant thermal load and materials, depending on the distance from the hot face of all lengths at a number of points (3, 6, 9 and 12) cm. From the results of the time obtained numerically from the ANSYS-14 program, the time to reach the steady state was determined when the difference between the sample temperature reached with the previous grade of 0.001.The results indicated that the time required to reach the steady state (S.S.t) increases by increasing the length of the sample in the selected points when constant thermal diffusivity (α) ,where the time needed to reach the steady state of the copper material ranged between (879-1085) seconds at a length of 15 cm and (2112- 3005) seconds at length 30 cm and (2871-4937) seconds at a length of 45 cm as well as the results showed that the time required to reach the steady state increased with the thermal diffusivity decrease where the time required to reach the steady state of the copper of the highest thermal diffusivity ranged between (879-4937) seconds for all lengths while the time required to reach the steady state of the material of the lowest thermal diffusivity (hardboard) is between (168400-1078000) seconds.

Effects of sample length on the transient measurement results of water vapor diffusion coefficient of porous building materials: A case study of autoclave aerated concrete (AAC) with various porosities

The effects of sample length on the transient measurement results of the water vapor diffusion coefficient of autoclave aerated concrete (AAC) were studied based on the transient technique that solves an inverse problem of one-dimensional mass transfer in a semi-infinite domain. Tests were performed on square-rod-shaped AAC samples having various porosities. The axial sample length was varied from 120 mm to 250 mm while maintaining a constant cross-sectional area of 50 mm × 50 mm. Humidity sensors having two sizes of 6 mm and 12 mm were also adopted, and the transient measurement results were compared with reference values obtained using standardized steady-state method. Results showed that smaller humidity sensors are always preferred and that the appropriate sample length varies with the type of materials. For the specific types of AAC samples studied, the appropriate sample length was found to lie between 150 mm and 200 mm. The use of a shorter (or longer) sample was shown to cause overestimation (or underestimation) of the transient results. It was suggested that the appropriate sample length should be kept short as long as the semi-infinite domain assumption is valid, which could guide the sample length selection for other porous building materials.

Mode confinement, interface mass-smudging, and sample length effects on phonon transport in thin nanocomposite superlattices

We employ a semi-ab initio theoretical method to investigate mode confinement, interface mass-smudging, and sample length effects on phonon transport in thin nanocomposite superlattices. We present a detailed comparative study of numerical results showing the reduction in thermal conductivity due to each of these three effects for Si/Ge nanocomposite structures with planar superlattice (SL), embedded nanowire superlattice (NWSL), and embedded nanodot superlattice (NDSL) geometries. Importantly, it is found that any of these three types of thin period systems, with small amounts of interface mass smudging, can exhibit a room-temperature conductivity significantly lower than the SiGe alloy conductivity, providing strong evidence that they could be used as efficient thermoelectric materials. It is also found that the room-temperature conductivity of each of the nanocomposite superlattices shows a weaker sample size dependence than do the component bulk conductivities.

Microwave puffing assisted extraction of polysaccharides from Dendrobium devonianum

In this study, microwave assisted puffing technology was developed to increase the extraction efficiency of polysaccharides from D. devonianum. Fresh stems of Dendrobium devonianum were processed using microwave puffing technology and the processing conditions were explored and optimized to increase the extraction yield of polysaccharides. The effects of sample length (SL), initial moisture content (IMC), microwave power (MP), and processing time (PT) on quality attributes of the products, in terms of expansion ratio and sensory evaluation, were analyzed using response surface methodology. The optimal SL, IMC, MP, and PT were 3.5 cm, 22%, 702 W, and 31 s, respectively, which resulted in optimal expansion ratio and sensory score of 326.1% and 8.63, respectively. Furthermore, the extraction yield of polysaccharides from the microwave-puffed products was increased by 18.9% compared with that from nonpuffed samples. Antioxidant and anti-hyperglycemic activities of polysaccharides from puffed and nonpuffed D. devonianum were also evaluated and compared. Practical applications We developed a novel microwave assisted puffing technology to increase the extraction efficiency of polysaccharides from D. devonianum. Polysaccharides, the major active components of Dendrobium species, exhibit the potential as an inhibitor, including immunomodulator, antioxidant, anti-tumor and anti-hyperglycemic agent.

Efeito do comprimento do corpo de prova nas propriedades mecânicas do carvão de Eucalyptus

As propriedades mecânicas do carvão são indicadoras de qualidade e influenciam no processo siderúrgico. Os ensaios de avaliação (queda e tamboramento), em geral, apresentam resultados variáveis, comprometendo sua confiabilidade. Por isso, é importante desenvolver metodologias que produzam resultados comparáveis. Esse trabalho objetivou analisar a influência do comprimento do corpo de prova na determinação da rigidez e resistência da madeira e do carvão. Foram utilizados clones de Eucalyptus urophylla, dos quais foram produzidos corpos de prova de seção transversal de 25 mm x 25 mm e comprimentos de 50 mm, 75 mm, 100 mm e 125 mm. Dez amostras de cada comprimento foram selecionadas para a realização do ensaio com madeira, e outras dez para os ensaios com carvão. O módulo de elasticidade e a resistência à compressão foram determinados em ensaio de compressão paralela às fibras. Houve efeito significativo do comprimento do corpo de prova sobre a rigidez e resistência da madeira e do carvão, sendo que os melhores resultados foram encontrados para as dimensões 25 mm x 25 mm x 75 mm. Apenas a dimensão de 25 mm x 25 mm x 50 mm se mostrou inadequada, apresentando resultados inferiores aos relatados em literatura.

MouseIdentity: Modeling Mouse-Interaction Behavior for a User Verification System

Analysis of mouse-interaction behaviors for identifying individual computer users has experienced growing interest from information security and biometric researchers. This paper presents a simple and efficient user verification system by modeling mouse-interaction behavior, which is accurate and competent for future deployment. For each mouse-operation sample, holistic attributes of mouse trajectories are first analyzed using a power transformation method, to derive a schematic representation of behavior eigenspace. Then, a propagation-based segmentation method is developed to model the detailed dynamic process of mouse movements by performing adaptive behavior segmentation and then characterizing each obtained segment using fine-grained procedural motion metrics. Both schematic and procedural cues from mouse-interaction behaviors may be used independently for verification, being fused at the decision level using combination rules. Analyses are conducted using data from 106 subjects with 21 200 mouse-operation samples. The verification system achieves a 1.96% false-rejection rate and a 1.18% false-acceptance rate with a short verification time (about 6 s) and lightweight system overload. Additional experiments on the effect of sample length and subject pool further examine the applicability of our verification system. We also compare the proposed approach with the state-of-the-art approaches for the data collected. Our findings suggest that mouse-interaction behaviors can enhance traditional authentication systems.