Low-frequency Terms Research Articles

Using Google Trends Data to Study High-Frequency Search Terms: Evidence for a Reliability-Frequency Continuum

Google Trends (GT) data are increasingly used in the social sciences and adjacent fields. However, previous research on the quality of GT data has raised concerns regarding their reliability. In the present study, we investigated whether reliability differs between low- and high-frequency search terms. In other words, we explored the existence of a reliability-frequency continuum in GT data. Our study adds to previous research by investigating a more comprehensive set of search terms and different aspects of reliability (e.g., differences in relative search volume distributions, correctly identified maxima). For this purpose, we collected samples of GT data for ten high- and two low-frequency search terms. We obtained one real-time sample and 62 non–realtime samples per search term (30 non–realtime samples for low-frequency search terms). Data collection was restricted to search data for Germany. Our data support the existence of a reliability-frequency continuum—low-frequency search terms are subject to greater reliability issues compared to high-frequency search terms. Based on our findings, we have derived practical recommendations for the use of GT data and have outlined future research opportunities.

Association rule mining with a special rule coding and dynamic genetic algorithm for air quality impact factors in Beijing, China.

Understanding air quality requires a comprehensive understanding of its various factors. Most of the association rule techniques focuses on high frequency terms, ignoring the potential importance of low- frequency terms and causing unnecessary storage space waste. Therefore, a dynamic genetic association rule mining algorithm is proposed in this paper, which combines the improved dynamic genetic algorithm with the association rule mining algorithm to realize the importance mining of low- frequency terms. Firstly, in the chromosome coding phase of genetic algorithm, an innovative multi-information coding strategy is proposed, which selectively stores similar values of different levels in one storage unit. It avoids storing all the values at once and facilitates efficient mining of valid rules later. Secondly, by weighting the evaluation indicators such as support, confidence and promotion in association rule mining, a new evaluation index is formed, avoiding the need to set a minimum threshold for high-interest rules. Finally, in order to improve the mining performance of the rules, the dynamic crossover rate and mutation rate are set to improve the search efficiency of the algorithm. In the experimental stage, this paper adopts the 2016 annual air quality data set of Beijing to verify the effectiveness of the unit point multi-information coding strategy in reducing the rule storage air, the effectiveness of mining the rules formed by the low frequency item set, and the effectiveness of combining the rule mining algorithm with the swarm intelligence optimization algorithm in terms of search time and convergence. In the experimental stage, this paper adopts the 2016 annual air quality data set of Beijing to verify the effectiveness of the above three aspects. The unit point multi-information coding strategy reduced the rule space storage consumption by 50%, the new evaluation index can mine more interesting rules whose interest level can be up to 90%, while mining the rules formed by the lower frequency terms, and in terms of search time, we reduced it about 20% compared with some meta-heuristic algorithms, while improving convergence.

Privacy-Preserving Image Retrieval with Multi-Modal Query

Abstract The ever-growing multi-modal images pose great challenges to local image storage and retrieval systems. Cloud computing provides a solution to large-scale image data storage but suffers from privacy issues and lacks the support for multi-modal image retrieval. To address these, a searchable encryption-empowered privacy-preserving multi-modal image retrieval method is proposed. First, we design a hybrid image retrieval framework that fuses visual features and textual features at a decision level and further supports similar image retrieval and multi-keyword image retrieval. Second, we construct a new hybrid inverted index structure to distinguish high-frequency terms from low-frequency terms and index them through hierarchical index trees and data blocks, respectively, which greatly improves query efficiency. Third, we design a prime encoding-based multi-keyword query method that converts mapping operations in bloom filters into inner product calculations, and further implements secure multi-keyword image query. Experiments against the Baseline schemes are conducted to verify the performance of the scheme in terms of high efficiency.

Nonuniform Dependence of a Two-Component NOVIKOV System in Besov Spaces

Considered herein is the Cauchy problem of the two-component Novikov system. In the periodic case, we first constructed an approximate solution sequence that possesses the nonuniform dependence property; then, by applying the energy methods, we managed to prove that the difference between the approximate and actual solution is negligible, thus succeeding in proving the nonuniform dependence result in both supercritical Besov spaces Bp,rs(T)×Bp,rs(T) with s>max{32,1+1p},1≤p≤∞,1≤r<∞ and critical Besov space B2,132(T)×B2,132(T). In the non-periodic case, we constructed two sequences of initial data with high and low-frequency terms by analyzing the inner structure of the system under investigation in detail, and we proved that the distance between the two corresponding solution sequences is lower-bounded by time t, but converges to zero at initial time. This implies that the solution map is not uniformly continuous both in supercritical Besov spaces Bp,rs(R)×Bp,rs(R) with s>max{32,1+1p},1≤p≤∞,1≤r<∞ and critical Besov spaces Bp,11+1p(R)×Bp,11+1p(R) with 1≤p≤2. The proof of nonuniform dependence is based on approximate solutions and Littlewood–Paley decomposition theory. These approaches are widely applicable in the study of continuous properties for shallow water equations.

Heart rate measurement method based on wavelet transform noise reduction for low power millimeter wave radar platform

In recent years, non-contact vital sign estimation using millimeter wave radar technology has gotten much attention. Most studies are based on radar platforms that were not built for home scenarios and had high transmitting power and colossal volume. This work employs a low-power millimeter wave radar system produced using Antenna in Package technology (AiP) with a transmit power of less than 6 dBm, significantly lower than that commonly utilized in related research. However, in application scenarios, the echo intensity cannot be maintained at an optimal level with these low-power devices, making accurate and reliable monitoring difficult to obtain. To further reduce the noise component and improve the signal-to-noise ratio, a heartbeat monitoring algorithm based on wavelet transform noise reduction is suggested in this study. The low-frequency terms of the wavelet transform of the chest wall micro-motion signal are interpreted as body random swinging and breathing, and the remaining terms are interpreted as the heartbeat signal. In a 20-minute monitoring experiment, 96.96% accuracy is reached by the method proposed in this study in the context of home scenario monitoring.

Evolutionary Characteristics of Runoff in a Changing Environment: A Case Study of Dawen River, China

Watershed water cycles undergo profound changes under changing environments. Analyses of runoff evolution characteristics are fundamental to our understanding of the evolution of water cycles under changing environments. In this study, linear regression, moving average, Mann–Kendall, Pettitt, accumulative anomaly, STARS, wavelet analysis, and CEEMDAN methods were used to analyze the trends, mutations, and periodic and intrinsic dynamic patterns of runoff evolution using long-term historical data. The intra-annual distribution of runoff in the Dawen River Basin was uneven, with an overall decreasing trend and mutations in 1975–1976. The main periods of runoff were 1.9 and 2.2 years, and the strongest oscillations in the study period occurred in 1978–1983. The runoff decomposition high-frequency term (intra-annual fluctuation term) had a stronger fluctuation frequency, with a period of 0.51–0.55 years, while the low-frequency term (interannual fluctuation term) had a period of 1.55–2.26 years. The trend term for the runoff decomposition tended to decrease throughout the monitoring period and gradually stabilized at the end of the monitoring period, while the period gradually decreased from upstream to downstream. In summary, we used multiple methods to analyze the evolutionary characteristics of runoff, which are of great relevance to the adaptive management of water resources under changing environments.

Approach to Predict Land Subsidence in Old Goafs considering the Influence of Engineering Noise

Considering that it is easily disturbed by various engineering factors such as weather, hydrology, and construction during engineering monitoring, the collected subsidence data contain various noises. In order to reduce the influence of engineering noise on the accuracy of subsidence prediction, it is proposed to use the Daubechies (DB) wavelet to decompose the original subsidence time series; the items with the low-frequency trend, after decomposition, are predicted using long short-term memory (LSTM) model, items with high-frequency noise used the autoregressive (AR) time series model to make predictions, and the prediction results of the low-frequency trend term and the high-frequency noise term are summed to obtain the total time series predicted value. Combining the actual engineering subsidence monitoring data of the old goaf, compared with the prediction results of the LSTM and RNN models without DB wavelet decomposition and the gray model GM (1,1), the results show that the DB wavelet has an obvious improvement effect in reducing the influence of measurement data noise on prediction error. Compared with the single prediction model LSTM, RNN, and GM (1,1), the proposed prediction model has higher prediction accuracy, smaller error, and better trend. It can be used as a calculation method to improve the prediction accuracy of surface subsidence in old goaf.

Diagnostic value of water-fat-separated images and CT-like susceptibility-weighted images extracted from a single ultrashort echo time sequence for the evaluation of vertebral fractures and degenerative changes of the spine

ObjectivesTo evaluate the performance of single-echo Dixon water-fat imaging and computed tomography (CT)–like imaging based on a single ultrashort echo time (sUTE) MR sequence for imaging of vertebral fractures as well as degenerative bone changes of the spine in comparison to conventional CT and MR sequences.MethodsThirty patients with suspected acute vertebral fractures were examined using a 3-T MRI, including an sUTE sequence as well as short-tau inversion recovery (STIR) and T1-weighted sequences. During postprocessing, water-fat separation was performed by solving the smoothness-constrained inverse water-fat problem based on a single-complex UTE image. By removing the unwanted low-frequency phase terms, additional MR-based susceptibility-weighted-like (SW-like) images with CT-like contrast were created. Two radiologists evaluated semi-quantitative and quantitative features of fractures and degenerative changes independently and separately on CT and MR images.ResultsIn total, all 58 fractures were accurately detected of whom 24 were correctly classified as acute fractures with an edema detected on the water-fat-separated UTE images, using STIR and T1w sequences as standard of reference. For the morphological assessment of fractures and degenerative changes, the overall agreement between SW-like images and CT was substantial to excellent (e.g., Genant: κ 0.90 (95% confidence interval 0.54–1.00); AO/Magerl: κ 0.75 (95% confidence interval 0.43–1.00)). Overall inter-reader agreement for water-fat-separated UTE images and SW-like images was substantial to almost perfect.ConclusionDetection and assessment of vertebral fractures and degenerative bone changes of the spine were feasible and accurate using water-fat-separated images as well as SW-like images, both derived from the same sUTE-Dixon sequence.Key Points• The detection of acute vertebral fractures was feasible using water-fat-separated images and CT-like images reconstructed from one sUTE sequence.• Assessment of the vertebral fractures using SW-like images with CT-like contrast was found to be comparable to conventional CT.• sUTE imaging of the spine can help reduce examination times and radiation exposure.

THE ROLE OF CONSUMER INVOLVEMENT ON INNOVATION AND NEW PRODUCT DEVELOPMENT PROCESS: META-ANALYSIS AND WORD CLOUD TEXT ANALYSIS

Today, businesses are trying to make the concept and process of innovation a collective phenomenon by collaborating in innovation activities and opening up, especially thanks to the cooperation and relationships they have established with consumers. In order for new economic paradigms to be superior, new paradigms must have factors that can be defined as a group of key inputs. From this point of view, there are many factors that affect the success and performance of innovation and new product development. Consumers have become the most important source of innovation. Studies show that the impact of consumer integration on innovative products and resource expenditure is enormous. In this study, the aforementioned paradigms were brought together and a literature review of the projects and researches in the field of innovation, consumer effects of new product development processes and innovation integration between the years 2005-2022 was conducted. Then, the text data of these studies were brought together and translated and a dataset was created. Then, word cloud text analysis, which is a powerful visualization tool, was applied on the Anaconda-Pycharm software with python programming language to provide a statistical view. It has been observed that the results obtained by this text analysis method, the most frequent terms settle in the center by increasing their density, and the lower frequency terms are located towards the borders by decreasing. According to the results of the observation, it was found that the terms with high frequency were “NPD (New Product Development), consumer participation and innovation” and were clearly concentrated in the center. As a result, in parallel with the results of meta-analysis and word cloud text analysis, it is concluded that the innovation and new product development strategy is "consumer participation", that is, staying close to the consumer, so that the right users can provide the company with ideas that promote new products.In future studies, considering that product innovations have different dimensions as "technology innovation" and "market innovation", the factors that demand different levels of information from the consumer depending on the innovation level should be evaluated. The contribution of the study to the literature is that at the stage of developing a new product idea, companies that have a high level of knowledge about consumers and consumer groups will be able to develop products that perform at a higher level when they gain more information.

Dynamic mechanical properties and constitutive model of shale with different bedding under triaxial impact test

With the gradual depletion of traditional energy sources such as oil and natural gas. As an unconventional energy that can replace traditional resources, shale gas has attracted the attention of the world energy department. The storage environment of shale gas (oil) is usually accompanied by in-situ stress, and the exploitation of shale gas is actually a dynamic process. Therefore, it is of great significance to study the dynamic mechanical characteristics of shale under in-situ stress. In this paper, the dynamic mechanical parameter and constitutive relationship of shales with different bedding (0°, 30°, 45°, 60°, 90°) was studied by the triaxial SHPB tests with the confining pressure from 0 to 15 MPa. The effects of confining pressure on the mechanical properties of shale with different bedding were discussed from the aspects of the dynamic compressive strength, elastic modulus, failure strain, energy characteristics as well as the dynamic failure mode. The experimental results showed that, the dynamic mechanical properties of shale mainly depended on the interaction of the bedding dip angle and various confining pressures. The failure modes of shale under confining pressure mainly present compression shear failure or only damage crack. In additional, a modified dynamic constitutive model of shales was based on the ZWT viscoelastic constitutive relationship, which simplified the low frequency term and took into account shale material damage characteristics. The modified constitutive model is simple in structure and can predict the strength characteristics of shale under confining pressure in a certain range when the basic mechanical parameters and empirical parameters are known.

Inner Dynamic Detection and Prediction of Water Quality Based on CEEMDAN and GA-SVM Models

Urban water quality is facing strongly adverse degradation in rapidly developing areas. However, there exists a huge challenge to estimating the inner features and predicting the variation of long-term water quality due to the lack of related monitoring data and the complexity of urban water systems. Fortunately, multi-remote sensing data, such as nighttime light and evapotranspiration (ET), provide scientific data support and reasonably reveal the variation mechanisms. Here, we develop an integrated decomposition-reclassification-prediction method for water quality by integrating the CEEMDN method, the RF method mothed, and the genetic algorithm-support vector machine model (GA-SVM). The degression of the long-term water quality was decomposed and reclassified into three different frequency terms, i.e., high-frequency, low-frequency, and trend terms, to reveal the inner mechanism and dynamics in the CEEMDAN method. The RF method was then used to identify the teleconnection and the significance of the selected driving factors. More importantly, the GA-SVM model was designed with two types of model schemes, which were the data-driven model (GA-SVMd) and the integrated CEEMDAN-GA-SVM model (defined as GA-SVMc model), in order to predict urban water quality. Results revealed that the high-frequency terms for NH3-N and TN had a major contribution to the water quality and were mainly dominated by hydrometeorological factors such as ET, rainfall, and the dynamics of the lake water table. The trend terms revealed that the water quality continuously deteriorated during the study period; the terms were mainly regulated by the land use and land cover (LULC), land metrics, population, and yearly rainfall. The predicting results confirmed that the integrated GA-SVMc model had better performance than single data-driven models (such as the GA-SVM model). Our study supports that the integrated method reveals variation rules in water quality and provides early warning and guidance for reducing the water pollutant concentration.

Correlation of term usage and term indexing frequencies

There have been several studies on the distributions of index terms, title terms, authors and other elements used in searching bibliographic databases. What is needed is to relate this information of the actual usage of terms in searching. This study uses data from monitoring the actual usage of terms in an online catalog at the School of Library and Information Science at the University of Western Ontario. Every time a term was used in a search expression, a count in the dictionary file was updated. If a word was not in the dictionary it was added. In this way we can see which words are in the catalog and not searched and also those which were searched but not in the dictionary. As a check on other studies the rank distribution of terms used in searching was checked and found to be of a general Zipf type.
 The main interest was to check if high frequency terms in the catalog were used frequently in searching. Several measures of this were tried. First the regular scatterplot of frequency of use in the catalog versus the frequency in searching was checked and Pearson’s correlation coefficient was calculated. The correlation was reasonably high at 0.74. Since the total number of terms and frequencies was much larger in the catalog, a plot of the rank of the terms in the catalog was plotted against the rank of the term in searching.
 This provided a very scattered plot with less clustering at the origin as in the original plot of frequencies. The Spearman rank correlation coefficient was moderate at 0.58. Some studies have suggested that removing high frequency and very low frequency terms from the search vocabulary will improve retrieval performance. This data shows that many general users actually use these terms in searching.
 Currently a sample of search words are being analyzed for factors which affect the correlation, such as errors in both the catalog and searching, the effect of truncations, and the effect of stemming (which was done on both the catalog vocabulary and the search terms).

Ionic contribution to van der Waals interaction of polar compounds

Ionic contributions to the van der Waals interactions of typical polar compounds have been investigated based on density-functional-theory-calculated dielectric functions. Derived from the Lifshitz theory, the contribution of ionic polarizabilities to the dispersion energy between parallel half-spaces can be up to 3.4%. Using the Clausius-Mossotti relationship with a Lorentz factor of 4\ensuremath{\pi}/3, it is found that the ionic effect on ${C}_{6}$ is consistent with that on energy. In parallel slabs separated distantly, the ionic polarizability plays a substantially enhanced role, contributing up to 25% of the energy. The significant ionic effect in the latter case is due to a reduction in the screening of low-frequency terms, and a zero Lorentz factor should be assumed to predict a consistent ionic effect on ${C}_{6}$.

An Adaptive Regularized Solution to Inverse Ill-Posed Models

The ill-posed models are widely encountered in various inversions of geodesy and remote sensing. The regularization approaches can significantly stabilize the solution to ill-posed models since the high-frequency noise is effectively suppressed. Although the famous Tikhonov regularization and truncated singular value decomposition (TSVD) regularization have been widely applied in various geodetic applications, there still remain theoretical drawbacks for either single regularization. For Tikhonov regularization, given a regularization parameter, the low-frequency terms are over regularized, and high-frequency terms are under regularized. For TSVD regularization, some medium-frequency terms will be mistaken for high-frequency terms to be truncated and the hidden signals will be lost. For this reason, we propose an adaptive regularized solution in spectral form, which adaptively divides the terms of different frequencies into three kinds: (i) the low-frequency terms are not regularized; (ii) the medium-frequency terms are regularized by the Tikhonov method; (iii) the high-frequency terms are regularized by TSVD method. The analytical conditions for determining the term sets are derived based on the criteria that the introduced biases should be smaller than the reduced errors, in other words, the mean squared error (MSE) should be reduced. The two examples are presented to demonstrate the performance of our adaptive regularization. The first numerical example is solving the Fredholm integral equation of the first kind, which is widely encountered in remote sensing inversions. The simulations clearly demonstrate that the adaptive regularized solution can improve the MSE of ordinary Tikhonov and TSVD regularized functions by 25.00% and 9.09%, respectively; In the second example, we apply the new method to investigate the mass variation of the Yangtze River Basin based on the Gravity Recovery and Climate Experiment (GRACE) time-variable gravity field model. The Tongji-Grace 2018 monthly gravity field solutions from April 2002 to December 2016 are used to construct the mascon observation equation. The results show that our method also outperforms the ordinary Tikhonov and TSVD regularized solutions, with mean MSE reductions of about 13.40% and 11.69%, respectively. Furthermore, the spatial resolution of secular trend derived by our method are improved and the signal-to-noise ratio (SNR) of mass variation series is higher than the other two regularizations.

Robust adaptive fuzzy sliding mode trajectory tracking control for serial robotic manipulators

The ever increasingly stringent performance requirements of industrial robotic applications highlight significant importance of advanced robust control designs for serial robots that are generally subject to various uncertainties and external disturbances. Therefore, this paper proposes and investigates the design and implementation of a robust adaptive fuzzy sliding mode controller in the task space for uncertain serial robotic manipulators. The sliding mode control is well known for its robustness to system parameter variations and external disturbances, and is thus a highly desirable and cost-effective approach to achieve high precision control task for serial robots. The proposed controller is designed based on a fuzzy logic approximation to accomplish trajectory tracking with high accuracy and simultaneously attenuate effects from uncertainties. In the controller, the high-frequency uncertain term is approximated by using a fuzzy logic system while the low-frequency term is adaptively updated in real time based on a parametric adaption law. The control efficacy and effectiveness of the proposed control algorithm are comparatively verified against a recently proposed conventional controller. The test results demonstrate that the proposed controller has better trajectory tracking performances and is more robust against large disturbances than the conventional controller under the same operating conditions.

Assessment of vertebral fractures and edema of the thoracolumbar spine based on water-fat and susceptibility-weighted images derived from a single ultra-short echo time scan.

To develop a methodology to simultaneously perform single echo Dixon water-fat imaging and susceptibility-weighted imaging (SWI) based on a single echo time (TE) ultra-short echo time (UTE) (sUTE) scan to assess vertebral fractures and degenerative bone changes in the thoracolumbar spine. A methodology was developed to solve the smoothness-constrained inverse water-fat problem to separate water and fat while removing unwanted low-frequency phase terms. Additionally, the corrected UTE phase was used for SWI. UTE imaging (TE: 0.14 ms, 3T MRI) was performed in the lumbar spine of nine patients with vertebral fractures and bone marrow edema (BME). All images were reviewed by two radiologists. Water- and fat-separated images were analyzed in comparison with short-tau inversion recovery (STIR) and with respect to BME visibility. The visibility of fracture lines and cortical outlining of the UTE magnitude images were analyzed in comparison with computed tomography. Unwanted phase components, dominated by the B1 phase, were removed from the UTE phase images. The rating of the diagnostic quality of BME visualization showed a high preference for the sUTE-Dixon water- and fat-separated images in comparison with STIR. The UTE magnitude images enabled better visualizing fracture lines compared with STIR and slightly better visibility of cortical outlining. With increasing SWI weighting osseous structures and fatty tissues were enhanced. The proposed sUTE-Dixon-SWI methodology allows the removal of unwanted low-frequency phases and enables water-fat separation and SWI processing from a single complex UTE image. The methodology can be used for the simultaneous assessment of vertebral fractures and BME of the thoracolumbar spine.

Surgical outcomes of tension-free vaginal tape (TVT)- abbrevo® and TVT-obturator® for the treatment of stress urinary incontinence: a retrospective study.

ObjectiveWe compared the efficacy and postoperative complications of tension-free vaginal tape (TVT)-abbrevo® (TVT-A) and TVT-obturator® (TVT-O) surgeries for the treatment of stress urinary incontinence (SUI).MethodsWe retrospectively analyzed the medical records of 143 female patients with SUI who underwent TVT-A or TVT-O surgery between January 2010 and December 2019 at the Asan Medical Center in Seoul. We evaluated intra- and postoperative complications such as bladder injury, groin pain, urinary retention, and mesh exposure. We also checked the success rate at 6 months after surgery.ResultsThere were no complications, including fever, hematuria, hematoma of the vulva, or bladder injury, immediately after surgery in either group. Postoperative complications 2 weeks post-surgery were groin pain (11.3%), urinary retention (4.9%), and mesh exposure (0.7%). Groin pain was not significantly different between the two groups at 2 weeks, 3 months, and 6 months after surgery (TVT-O vs. TVT-A after 2 weeks: 12.5% vs. 10.3%, P=0.791; 3 months: 0.0% vs. 1.4%, P=0.999; and 6 months: 0.0% vs. 0.0%, P=0.999). Over 90% of the patients reported cure or improved symptoms in both groups. In the univariate logistic analysis, the type of TVT (TVT-O or TVT-A) was not associated with the success rate (odds ratio, 3.21; 95% confidence interval, 0.59–17.40; P=0.175).ConclusionTVT-A surgery is comparable with TVT-O in terms of high success rate and low frequency of complications, including bladder injury and groin pain.

Shock Signal Trend Term Error Correction Method Based on Discrete Wavelet Transform and Low-Frequency Oscillator Combination

Shock response spectrum (SRS), calculated according to shock loading signal, is the primary metric for assessing the shock resistance ability of shipborne equipment. Nevertheless, the measured shock acceleration signal contains a trend term error that severely distorts the low frequency of the SRS. The accuracy of present correction methods cannot be assured due to a lack of reference. A discrete wavelet transform (DWT) and low-frequency oscillator combination method is proposed for correcting shock signals in this paper. The optimal wavelet parameters can be selected according to a low-frequency spectrum baseline fitted by the measured relative displacement to reject low-frequency trend term errors. Shock machine test results show that the average difference between the low-frequency spectrum baseline and uncorrected SRS is reduced from 89.8% to 3.2%, while the SRS slope rolled off to 5.8 dB/oct after imposing the proposed correction. The corrected SRS can faithfully show the actual shock loading characteristics of shipborne equipment in shock tests.

A COMPLEMENTAL ANALYSIS OF WAVE IRREGULARITY EFFECT ON THE HYDRODYNAMIC RESPONSES OF OFFSHORE WIND TURBINES WITH THE SEMI-SUBMERSIBLE PLATFORM

Changes in the spectral shape and the directional spreading are typical properties of irregular waves in nature. The effect of wave irregularity on the hydrodynamic responses of floating offshore wind turbines (FOWT) has been investigated in several studies. However, a complemental analysis of the effects of frequency spectrum shape and wave multi-directionality on the low-frequency (LF) and the wave-frequency (WF) responses due to the second order and the first order hydrodynamic loads, respectively and cable tensions of FOWT under a complete range of mean wave directions is missing. In this study, two hydrodynamic models are developed firstly using different calibration methods based on the free decay tests and wave loading tests. They are compared with the experimental data for validation. No wind loads were considered in this analysis. The validation results show that the model calibrated using wave loading has better agreement with the experimental data, especially in the LF region, and therefore used for further analysis. Then the hydrodynamic responses are investigated under irregular waves with different spectral shapes. As the spectral shape becomes narrower with pronounced wave grouping and the larger waves in the time series, the responses and tensions increase in the WF region. Furthermore, the narrower the spectrum, the more snap loads in the mooring cables occur. Hydrodynamic responses are also compared under a uni-directional and multi-directional wave excitation from all angles of attack in terms of LF and WF amplitudes. The condition that the responses under multi-directional waves are higher than the ones under uni-directional waves has appeared in multiple cases, especially in the WF region, although it does not lead to excessive responses like the uni-directional wave. Therefore, it is concluded that the wave irregularity in terms of the spectral shape and the directional spreading should be considered during the design stage for better comprehension of the actual motion of floating wind turbines.

Relaxation processes in silicon heterojunction solar cells probed via noise spectroscopy

We have employed state-of-the-art cross-correlation noise spectroscopy (CCNS) to study carrier dynamics in silicon heterojunction solar cells (SHJ SCs). These cells were composed of a light absorbing n-doped monocrystalline silicon wafer contacted by passivating layers of i-a-Si:H and doped a-Si:H selective contact layers. Using CCNS, we are able to resolve and characterize four separate noise contributions: (1) shot noise with Fano factor close to unity due to holes tunneling through the np-junction, (2) a 1/f term connected to local potential fluctuations of charges trapped in a-Si:H defects, (3) generation-recombination noise with a time constant between 30 and 50 μs and attributed to recombination of holes at the interface between the ITO and n-a-Si:H window layer, and (4) a low-frequency generation-recombination term observed below 100 K which we assign to thermal emission over the ITO/ni-a-Si:H interface barrier. These results not only indicate that CCNS is capable of reveling otherwise undetectable relaxation process in SHJ SCs and other multi-layer devices, but also that the technique has a spatial selectivity allowing for the identification of the layer or interface where these processes are taking place.