Low Redundancy Research Articles

Исследование двухмодульных взвешенных кодов с суммированием с произвольными разбиениями множества информационных символов

A method has been proposed for constructing two-modulus sum codes that are suitable for solving the synthesis problems of self-checking digital computing devices and systems, as well as the technical means of their diagnostics. In the process of constructing a code, a set of data symbols is divided into two subsets, forming separate vectors for which the total weight is calculated according to a predetermined modulus. Beforehand, in each of the selected vectors, one of the data symbols is weighted with a coefficient from a natural series. Codes obtained with different values of weight coefficients and modulus for determining the total weight form a separate family of uniform binary codes with a fixed number of check symbols. The article provides an example of constructing a sum codes in the ring of residues modulus M = 4. Using this modulus enables the construction of a two-modulus code with k = 4 check symbols for any value of the m number of data symbols. As the value of m increases, the relationship between the number of data symbols and check symbols will change significantly, and the resulting code will have low redundancy. This is important when using the considered class of codes in the construction of digital devices. Previously unknown properties of the discussed class of sum codes have been identified, and taking these into account is beneficial when addressing problems related to the synthesis and technical diagnostics of digital devices.

The Restructuring of Ecological Networks by the Pleistocene Extinction

Most terrestrial large mammals went extinct on different continents at the end of the Pleistocene, between 50,000 and 10,000 years ago. Besides the loss in species diversity and the truncation of body mass distributions, those extinctions were even more impactful to interaction diversity. Along with each extinction, dozens of ecological interactions were lost, reorganizing species interaction networks, which attained species-poor configurations with low functional redundancy. Extinctions of most large herbivores impacted energy flow and the rates of nutrient cycling, reconfiguring ecosystem-level networks. Because large mammals have high mobility, their loss also shortened seed-dispersal distance and reduced nutrient diffusivity, disrupting spatial networks. This review examines the recent advances in understanding how different types of ecological networks have been restructured by megafaunal extinctions and how this reorganization affected ecosystem functions. ▪Megafaunal extinctions resulted in the loss of multiple ecological interactions in terrestrial systems.▪Interaction loss reshaped different types of ecological networks including food webs and spatial networks.▪The reorganization of ecological networks changed how terrestrial ecosystems are structured and function.

Odorant detection in a locust exhibits unusually low redundancy

Olfactory coding, from insects to humans, is canonically considered to involve considerable across-fiber coding already at the peripheral level, thereby allowing recognition of vast numbers of odor compounds. We show that the migratory locust has evolved an alternative strategy built on highly specific odorant receptors feeding into a complex primary processing center in the brain. By collecting odors from food and different life stages of the locust, we identified 205 ecologically relevant odorants, which we used to deorphanize 48 locust olfactory receptors via ectopic expression in Drosophila. Contrary to the often broadly tuned olfactory receptors of other insects, almost all locust receptors were found to be narrowly tuned to one or very few ligands. Knocking out a single receptor using CRISPR abolished physiological and behavioral responses to the corresponding ligand. We conclude that the locust olfactory system, with most olfactory receptors being narrowly tuned, differs from the so-far described olfactory systems.

Design of equalizers for frequency selective MIMO systems with low redundancy

Design of equalizers for frequency selective MIMO systems with low redundancy

A KRR-UKF robust state estimation method for distribution networks

State estimation is an integral component of energy management systems. Employing a state estimation methodology that is both accurate and resilient is essential for facilitating informed decision-making processes. However, the complex scenarios (unknown noise, low data redundancy, and reconfiguration) of the distribution network pose new challenges for state estimation. In the context of this study, we introduce a state estimation technique known as the kernel ridge regression and unscented Kalman filter. In normal conditions, the non-linear correlation among data and unknown noise increases the difficulty of modeling the distribution network. Thence, kernel ridge regression is developed to map the data into high-dimensional space that transforms the non-linear problem into linear formulations base on the data rather the complicate grid model, which improves model generalization performance and filters out unknown noises. In addition, with the unique prediction correction mechanism of the Kalman method, the kernel ridge regression-mapped state value can be revised by the measurement, which further enhances model accuracy and robustness. During abnormal operating conditions and taking into account the presence of faulty data within the measurement system, we initiate the use of a long short-term memory network and combined convolutional neural network (CNN) model, referred to as the ATT-CNN-GRU. This model is utilized for the prediction of pseudo-measurements. Subsequently, we use an outlier detection method known as ordering points to identify the clustering structure to effectively identify and substitute erroneous data points. Cases on the IEEE-33 bus system and 109-bus system from a city in China show that the method has superior accuracy and robustness.

A spanning tree algorithm with adaptive pruning with low redundancy coverage rate

In reality, when UAV is used in region reconnaissance, the shape of region is usually irregular. Selecting an algorithm to find a complete coverage path with smaller coverage redundancy rate, lower path motion complexity and theoretical energy consumption has certain research significance for the complete coverage path planning (CCPP). In existing algorithms, there is always a high redundant coverage rate under irregularly shaped regions. The motion complexity and the theoretical energy consumption of the path also increase. In this paper, a kind of spanning tree with adaptive pruning (STAP) algorithm based on the grid map is proposed to solve the above problems: on the one hand, it uses a greedy growth strategy to determine the branching growth direction, and proposes an adaptive pruning method for self-optimization of the initial path; on the other hand, a kind of nearest neighbor sub-region connection rule of adjacent paths is proposed to reduce the complexity and the coverage redundancy rate. The STAP algorithm searches for all grid centers, grows, and optimizes the spanning tree by creating paths between the centers. At the end of the optimization, it creates a complete coverage path based on the distribution of the spanning tree. Experiments show that when the STAP algorithm is applied to unobstructed regions, it plans the path with the lowest redundant coverage rate, which reaches 2.6296% and 4.9402%; when it is applied to the regions include obstacles, the advantages of the algorithm are more significant: On the one hand, the path planned by STAP has the least total length, the lowest number of turning and turning back. On the other hand, the redundant coverage rate of the path is still the lowest, reaching 4.1362% and 2.7765%, respectively. The STAP is primarily suitable for situations about CCPP under grid maps formed by irregularly shaped regions, and it holds certain significance for ground reconnaissance of UAVs.

Data reliability and fault diagnostic for air quality monitoring station based on low cost sensors and active redundancy

Air pollution is both an environmental and societal issue. Conventional air quality monitoring involves costly measuring stations that demand specialized personnel. A more affordable and accessible alternative approach consists in the use of low-cost sensor networks (LCS). However, LCS have drawbacks such as variable component quality, unreliable measurements, and short lifespan. Previous research has addressed these problems through redundant LCS and expand measurement capabilities. Nevertheless, challenges remain regarding reliability. Specifically, the use of median aggregations tends to hide errors and failures, especially when most sensors are faulty. This paper proposes a new method to make data reliable and generate diagnostic through three indicators: Synthesis, Detection, and Indexes. These indicators enable the prediction of the station’s health status, identify faulty sensors, and assess the quality of the Synthesis with a confidence index. This approach ensures consistent data collection despite disturbances and malfunctions in the LCS and can be used for informed decisions and actions to mitigate air pollution. The initial implementation of this approach involves deploying the first station in the Communauté de Communes Pyrénées Vallée des Gaves (CCPVG) territory. The obtained results showed the adaptability of the proposed approach for future LCS implementations and long-term air quality monitoring.

Translation and psychometrics of the Bengali adaptation of Coronavirus Anxiety Scale.

The Coronavirus Anxiety Scale (CAS) was developed in April 2020 as an instrument to gauge the symptoms of stress and anxiety occurring secondary to the COVID-19 pandemic. It was constructed using the English language due to which its application to a multi-linguistic country like India became a hindrance. To establish psychometric validity and reliability of the Bengali translation of CAS. Experts well-versed in the English and Bengali languages translated CAS from English to Bengali. This was followed by further correction by forward and backward translation processes until a version with high accuracy and low redundancy was procured. The original scale was applied to 91 volunteers, and the translated version was applied to the same group after 14 days. The mean scores of the original version and the translated version showed a significant correlation. The Bengali version of CAS had high internal consistency, significant concurrent validity, and acceptable split-half reliability. It was hence deemed easily understandable and capable of measuring anxiety due to COVID-19 similar to the original scale. The Bengali translation of the CAS can be accurately used to assess symptoms of anxiety and stress with high reliability and validity in those who are able to read the Bengali language.

High-resolution optical remote sensing geomorphological mapping of coral reef: Supporting conservation and management of marine protected áreas

Brazilian corals are unique ecosystems with high endemism and low functional redundancy. Hence, mapping its geomorphology is an important step to inferring analyzes on benthic habitats. We observe several difficulties during this mapping of coastal areas by remote sensing and a lack of fine-scale depth data for reef areas in Brazil. The present study aims to present the bathymetry extracted by satellite imagery in murky waters using a mosaic of Sentinel-2 images in Google Earth Engine (GEE) calibrated with field samples. We used the satellite extracted DBM to map the bottom geomorphology through BTM (Benthic Terrain Modeler). We then present the first detailed geomorphological map for the largest marine coastal protected area in Brazil- MPA Costa dos Corais. The geomorphological raster was differentiated into seven classes: Flat Plains, Depressions, Gentle Slopes, Slopes, Terrestrial Reef Flat, Reef Flat, and Crest. Altogether, we estimate >275 km2 of area representing reef structures (coral reef or beachrocks), or about 48% of the total MPA area. Mapping coral reefs can contribute to conservation, particularly in selecting areas for in situ monitoring activities and in prioritizing the application of remedial actions in the event of environmental disasters or threats to coral health, such as oil spills and bleaching episodes. Our findings encourage the applicability of these methodologies in other reef areas and collaborate for the management and monitoring of marine protected areas. In addition, all mapping is available online for any user.

Low redundancy among caddisflies sharing a mid‐mountain stream

AbstractIn fast‐flowing streams, caddisfly larvae are responsible for processes that collectively determine the efficiency with which the detritivore community is able to decompose autochthonous and allochthonous detritus. This ecosystem function ensures high water quality and represents a precious service for resident rural communities. The analysis of δ13C and δ15N in eight caddisfly taxa from a mid‐mountain stream evidenced a remarkable complementarity in their feeding preferences. An aquatic moth mimicking the caddis mode of life was also included in the survey and its feeding niche appeared to be in between the one of caddis taxa. Moderate niche overlap was interpreted in terms of low functional redundancy, implying that in case of a reduction in diversity, no taxon could be a perfect substitute for another, with a loss of functional efficiency. Low redundancy could be caused by niche segregation due to avoidance of competition/interference between taxa. The broad range of δ13C and δ15N described in this study warns against attributing single δ13C and δ15N to Trichoptera as a group, or even to single families. These results contribute to the still poorly known distribution of East African caddisflies and to the characterisation of feeding preferences of Afrotropical trichopteran larvae.

Plant parentage influences the type of timber use by traditional peoples of the Brazilian Caatinga.

Local populations select different plants to meet their demands, so that morphologically similar species can be more used for a given use. Herein, we seek to understand whether plant species that are phylogenetically closer together are used more similarly than distant species in the phylogeny. Ethnobotanical data were collected in five rural communities in a semi-arid region of Brazil. A total of 120 local experts were selected and interviewed using semi-structured questionnaires. The people's knowledge of plants was organized into usage subcategories. We estimated the redundancy values for the mentioned species, and we compiled data from the literature on the wood density values of the cited species. We constructed our phylogenetic hypothesis of useful plants and used comparative phylogenetic methods to estimate the signal. Our results showed a strong phylogenetic grouping for both tool handle and craft uses. We observed a moderate phylogenetic grouping in which related cited plants exhibit similar redundancy and a weak grouping in which cited plants present similar wood density values. Our results revealed the importance of using phylogeny for useful plants. We conclude the phylogenetic proximity of useful plants and the lower redundancy for some species in our study may suggest greater use pressure, given that few species fulfill the same function.

Multi-sensor and multi-level information fusion model for compressor blade crack detection

In order to complete the early crack detection of compressor blades under complex working conditions, a multi-sensor and multi-level information fusion model is proposed. Firstly, based on the designed correlated degree of cyclostationarity (CDCS) fusion rule, data-level fusion of multi-sensor signals is performed. The fused signal has more obvious fault features and lower redundancy. Then, based on the proposed multi-scale attention module (MSAM), a dual-branch one-dimensional convolutional neural network (1D-CNN) is designed to extract the features from the fused signal, and the dynamic feature fusion module is used to complete the feature fusion of the two branches, so as to obtain more rich and complete features. Finally, the fused features are input into the softmax classifier to complete the blade crack detection. The effectiveness and superiority of the proposed method are verified by a series of ablation experiments and comparison experiments under cross-speed conditions.

An Online Unsupervised Streaming Features Selection Through Dynamic Feature Clustering

Streaming feature selection (SFS) is emerging as a key research direction which addresses the non-stationary property of feature streams when the sample size is fixed. Most existing SFS techniques are supervised methods, and ignore the label scarcity. Real-world datasets are typically unlabeled and the labeling costs are expensive. Although some unsupervised SFS approaches are proposed, these approaches are either limited to the homogeneous feature types or require substantial computational complexity. To address these problems, we propose an online unsupervised feature selection framework using dynamic feature clustering in this paper. We derived a recursive density lower bound to estimate the density distribution of feature streams and developed a density-based dynamic clustering method to perform the online feature stream clustering for exploring feature redundancy. An unsupervised online feature relevance maximization and redundancy minimization strategy is introduced to extract a subset of important features with low redundancy from the feature stream. Experimental results on thirteen well-known benchmark datasets and comparison studies with seven state-of-the-art supervised SFS methods demonstrate that the proposed unsupervised method provides statistically comparable performance with the supervised SFS techniques while the label information is unknown.

Performance of polar codes with low complexity cyclic redundancy check aided bit‐flipping for successive cancellation list decoding over power line channels

SummaryPower lines have complex transmission characteristics and noise interference when used as information transmission channel, thus limiting their data‐carrying rate and reliability. Impulsive noise is the most dominant factor degrading the performance of communication systems over power lines. To combat the impulsive noise, polar codes are introduced into the orthogonal frequency division multiplexing (OFDM)‐based power line communication (PLC) system. Because the successive cancelation list bit‐flip (SCLF) decoding algorithm of polar codes has high decoding complexity, a low complexity segmented cyclic redundancy check (CRC)‐aided SCLF decoding is proposed to improve the decoding performance. The decoding process can be terminated early with segmented CRC, which can reduce the bit‐flip decoding complexity significantly with short and medium block lengths. Experimental results demonstrate that for various configurations, the proposed decoder outperforms the traditional CRC‐aided SCL decoder in terms of decoding performance and complexity, and the suggested polar codes‐based OFDM‐based PLC system can reduce the bit error rate of the system in the presence of impulsive noise.

The Coral Triangle and Strait of Malacca are two distinct hotspots of mangrove biodiversity

Knowledge of the biogeography of marine taxa has lagged significantly behind terrestrial ecosystems. A hotspot of marine biodiversity associated with coral reefs is known in the Coral Triangle of the Indo-West Pacific, but until now there was little data with which to evaluate broad patterns of species richness in the coastal fauna of ecosystems other than coral reefs. This data is critically needed for fauna with low functional redundancy like that of mangroves, that are vulnerable to habitat loss and rising sea levels. Here we show that the diversity of mangrove fauna is characterized by two distinct hotspots in the Indo-West Pacific, associated with two habitat types: fringe mangroves in the Coral Triangle, and riverine mangroves in the Strait of Malacca, between the west coast of Peninsular Malaysia and Sumatra. This finding, based on a family of slugs of which the systematics has been completely revised, illustrates an unexpected biogeographic pattern that emerged only after this taxon was studied intensively. Most organisms that live in the mangrove forests of Southeast Asia remain poorly known both taxonomically and ecologically, and the hotspot of diversity of onchidiid slugs in the riverine mangroves of the Strait of Malacca indicates that further biodiversity studies are needed to support effective conservation of mangrove biodiversity.

Research on the importance and structural vulnerability assessment of RC frame components and robustness improvement methods

ABSTRACT To reasonably evaluate the robustness of RC frame structures, the ability to resist continuous collapse is improved. In this paper, the members’ contribution to the bearing capacity of the structure and the impact of the member’s failure are comprehensively considered, and the calculation method of the importance coefficient of the member is improved. At the same time, the structural vulnerability coefficient based on the change of the strain energy of the structure is combined with the reasonable assessment of the structural robustness through the two aspects of the member and the structure finishing. The redundancy analysis of the peripheral components of the failed components is carried out, and the low redundancy components are strengthened to improve the robustness of the structure to achieve the purpose of “strengthening the part and improving the whole”. On this basis, this paper evaluates the robustness of a four-story RC frame structure. It strengthens the low redundancy components under the influence of failure components to meet the requirements of improving the robustness of the structure, which verifies the rationality of the robustness evaluation method of the RC frame structure in this paper and the feasibility of improving the robustness of the structure.

Species trait diversity sustains multiple dietary nutrients supplied by freshwater fisheries.

Species, through their traits, influence how ecosystems simultaneously sustain multiple functions. However, it is unclear how trait diversity sustains the multiple contributions biodiversity makes to people. Freshwater fisheries nourish hundreds of millions of people globally, but overharvesting and river fragmentation are increasingly affecting catches. We analyse how loss of nutritional trait diversity in consumed fish portfolios affects the simultaneous provisioning of six essential dietary nutrients using household data from the Amazon and Tonlé Sap, two of Earth's most productive and diverse freshwater fisheries. We find that fish portfolios with high trait diversity meet higher thresholds of required daily intakes for a greater variety of nutrients with less fish biomass. This beneficial biodiversity effect is driven by low redundancy in species nutrient content profiles. Our findings imply that sustaining the dietary contributions fish make to people given declining biodiversity could require more biomass and ultimately exacerbate fishing pressure in already-stressed ecosystems.

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A description of the algorithm for optimal symbol-by-symbol reception of signal structures based on block noise-resistant codes in non-binary Galois fields is given. It is shown that the basis of this algorithm is the fast spectral transformation algorithm in the Walsh–Hadamard basis with the dimension of the Galois field. It is shown that the resulting complexity of the analyzed character-by-character reception algorithm is determined by the dimension of the dual code, which determines the prospects of its application for block noise-resistant codes with a high code rate (with low redundancy). The results of modeling a character-by-symbol reception algorithm are presented in order to study noise immunity for a number of frequency-efficient digital signals with quadrature-amplitude and amplitude-phase manipulations (with frequency coefficient efficiencies of 3, 4 and 6 bps/Hz) in combination with a parity check code. It is shown that the use of a symbol-by-symbol reception algorithm provides an energy gain of up to 1.5...3.0 dB in relation to the transmission and reception of the considered series of signals without coding.

A Secure Lossless Redundancy Elimination Scheme With Semantic Awareness for Cloud-Assisted Health Systems

Due to the limited scalability and reliability of traditional storage systems, more and more medical data are stored in cloud. However, the cost of cloud-assisted health systems is skyrocketing. How to improve storage utilization and save resource cost for health systems has become urgent problems. Therefore, this study proposes a secure lossless redundancy elimination scheme with semantic awareness, called SLRE, to decrease storage overhead and improve the overall system performance. Compared with existing studies, when the locality of data is almost nonexistent or poor, SLRE can eliminate redundant data well by exploiting semantic properties of similarity and entropy rather than relying on the locality. Then, fine-grained post-deduplication delta compression based on proxy similarity discovers more similar blocks and improves storage efficiency. In addition, filtered Lempel–Ziv compression based on proxy entropy filters data with low redundancy to improve the overall performance. Importantly, in order to ensure the security of medical data after deredundancy, different auditing strategies for medical data with diverse characteristics are proposed to guarantee security and improve the auditing efficiency. The experimental results show that compared with the state-of-the-art methods, the overall compression ratio of SLRE is improved, and the system throughput and auditing efficiency are also improved.

Development and Validation of the Low Vision Severely Constricted Peripheral Eyesight (LV-SCOPE) Questionnaire

To develop and validate a novel patient-reported outcome (PRO) measure to assess vision-related functioning in individuals with severe peripheral field loss (PFL). Prospective outcome measure development/validation study. A 127-item questionnaire was developed based on a prior qualitative interview study. A total of 116 participants with severe PFL due to retinitis pigmentosa (RP) or glaucoma were recruited at the Kellogg Eye Center and completed the Likert-scaled telephone-administered questionnaire. Included participants had a horizontal extent of their visual field <20 degrees (RP) or a mixed or generalized stage 4 to 5 defect using the Enhanced Glaucoma Staging System (glaucoma) in the better seeing eye (or in 1 eye if the fellow eye visual acuity was <20/200). Response data were analyzed using exploratory factor analysis and Rasch modeling. Poorly functioning items were eliminated, confirmatory factor analysis was used to ensure scale unidimensionality, and the model was refit to produce the final instrument. The final Low Vision Severely Constricted Peripheral Eyesight (LV-SCOPE) Questionnaire contains 53 items across 6 domains: mobility, object localization, object recognition, reading, social functioning, and technology. There were 74 items removed because of high missingness, poor factor loadings, low internal consistency, high local dependency, low item information, item redundancy, or differential item functioning. Using Rasch item calibrations, person ability scores could be calculated for each of the 6 unidimensional LV-SCOPE domains with good test-retest stability. The LV-SCOPE Questionnaire provides a valid and reliable measure of vision-related functioning across 6 key domains relevant to individuals with severe PFL. Findings support the clinical utility of this psychometrically valid instrument.