algorithms are the essence of computational thinking, which refers to a set of problem-solving processes that help children become logical thinkers in this increasingly digital society. It is important for teachers of...
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algorithms are the essence of computational thinking, which refers to a set of problem-solving processes that help children become logical thinkers in this increasingly digital society. It is important for teachers of young children to carefully plan and implement algorithm design tasks that involve repeated step-by-step procedures to build strong foundational computational thinking skills. In this article, the authors present algorithm tasks, including following a recipe, creating a treasure map, modeling how to perform a task, and sharing a routine, which can be easily integrated in the daily activities in early childhood classrooms. Fostering young children's aptitude for algorithm-specific thinking-and-doing processes creates a foundation for logical thinking.
An improved successive cancellation list bit-flip based on assigned set(AS-SCLF) decoding algorithm is proposed to solve the problems that the successive decoding of the successive cancellation(SC) decoder has error p...
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An improved successive cancellation list bit-flip based on assigned set(AS-SCLF) decoding algorithm is proposed to solve the problems that the successive decoding of the successive cancellation(SC) decoder has error propagation and the path extension of the successive cancellation list(SCL) decoder has the decision errors in the traditional cyclic redundancy check aided successive cancellation list(CA-SCL) decoding algorithm. The proposed algorithm constructs the AS firstly. The construction criterion is to use the Gaussian approximation principle to estimate the reliabilities of the polar subchannel and the error probabilities of the bits under SC decoding, and the normalized beliefs of the bits in actual decoding are obtained through the path metric under CA-SCL decoding, thus the error bits containing the SC state are identified and sorted in ascending order of the reliability. Then the SCLF decoding is performed. When the CA-SCL decoding fails for the first time, the decision results on the path of the SC state in the AS are exchanged. The simulation results show that compared with the CA-SCL decoding algorithm, the SCLF decoding algorithm based on the critical set and the decision post-processing decoding algorithm, the improved AS-SCLF decoding algorithm can improve the gain of about 0.29 dB, 0.22 dB and 0.1 dB respectively at the block error rate(BLER) of 10-4 and reduce the number of decoding at the low signal-to-noise ratio(SNR), thus the computational complexity is also reduced.
An 80-year-old woman received a dual chamber pacemaker (Boston Scientific Accolade MRI DR) for pre-syncopal episodes associated with transient II-degree atrioventricular block type 1 and 2:1, recorded in 24-h Holter m...
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An 80-year-old woman received a dual chamber pacemaker (Boston Scientific Accolade MRI DR) for pre-syncopal episodes associated with transient II-degree atrioventricular block type 1 and 2:1, recorded in 24-h Holter monitoring. Due to residual AV conduction with I-degree AV block, the pacemaker was set with the RYTHMIQ (R) algorithm, in order to reduce inappropriate ventricular pacing. A month later the patient started to complain of severe asthenia and bradycardia (46-48 bpm). Telemetry-supported pacemaker control revealed III-degree AV block with junctional escape rhythm, unmasking missed switch of RYTHMIQ (R) algorithm.
The objective evaluation of speech quality can replace expensive manual scoring,but current objective indicators usually need pure reference speech,which is difficult to obtain in many practical acoustic systems.A non...
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The objective evaluation of speech quality can replace expensive manual scoring,but current objective indicators usually need pure reference speech,which is difficult to obtain in many practical acoustic systems.A non-intrusive speech quality evaluation algorithm combining auxiliary target learning and a convolutional recurrent network(CRN)is *** frequency cepstral coefficients(BFCCs),which are based on human-like auditory filters,are used as the input of the CRN network to effectively reduce the network ***,frame-level features are extracted by a convolutional neural network(CNN)from ***,long-term time dependence and sequence features are modeled by the bidirectional long shortterm memory(BiLSTM)networks in frame-level ***,a self-attention mechanism is introduced into the CRN,thereby adaptively extracting useful information from frame-level features,which is then integrated into the characteristics of the sentence level and mapped into the final objective *** addition,a multi-task training strategy is adopted,and voice activity detection(VAD)is introduced as an auxiliary learning target to improve the performance of the *** in public databases show that compared with other non-intrusive algorithms,the proposed algorithm has a better correlation with the mean opinion score(MOS).Moreover,it has a small parameter size and good generalization ability for the distorted speech database with MOS released by ITU-T P.808,which is close to the accuracy of the perceptual evaluation of speech quality(PESQ).
In order to solve the problem of low audio fingerprint retrieval recognition rate under background sound and noise conditions,a novel algorithm based on mute masking and frequency segmentation is *** the fingerprint e...
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In order to solve the problem of low audio fingerprint retrieval recognition rate under background sound and noise conditions,a novel algorithm based on mute masking and frequency segmentation is *** the fingerprint extraction stage,voice activity detection technology is used to remove the non-valid speech frames,and then the valid speech frames are recombined and features are extracted according to the difference of the adjacent sub-band energy,which can effectively solve the problem that silence frame fingerprint characteristics are not *** the matching stage,according to the distribution characteristics of different audio signals in the frequency domain,the audio fingerprints are segmented and weighted in different frequencies to calculate the similarity between the template and the test audio more *** show that the proposed algorithm doubles the retrieval speed compared with the classic Philips *** the meantime,it yields a large definite improvement over Philips by 17.94%on mean average precision and 4.66%on recall respectively for the data set disturbed by background *** with the latest Philips algorithm,the mean average precision and recall have been increased by 13.68%and 2.45%respectively.
Harvesting robots had difficulty extracting filament phenotypes for small,numerous filaments,heavy cross-obscuration,and similar phenotypic characteristics with *** experience difficulty in localizing under near-color...
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Harvesting robots had difficulty extracting filament phenotypes for small,numerous filaments,heavy cross-obscuration,and similar phenotypic characteristics with *** experience difficulty in localizing under near-colored backgrounds and fuzzy contour *** cannot accurately harvest filaments for ***,a method for detecting and locating filament picking points based on an improved DeepLabv3+algorithm is proposed in this study.A lightweight network structure,ShuffIetNetV2,was used to replace the backbone network Xception of the traditional DeepLabv3+.Convolutional branches for 3 different sampling rates were added to extract information on the safflower features under the receptive *** block attention was incorporated into feature extraction at the coding and decoding layers to solve the interference problem of the near-color background in the feature-fusion ***,using the region of interest of the safflower branch obtained by the improved DeepLabv3+,an algorithm for filament picking-point localization was designed based on barycenter *** tests demonstrated that this method was capable of accurately localizing the *** mean pixel accuracy and mean intersection over union of the improved DeepLabv3+were 95.84%and 96.87%,*** detection rate and weights file size required were superior to those of other *** the localization test,the depth-measurement distance between the depth camera and target safflower filament was 450 to 510 mm,which minimized the visual-localization *** average localization and picking success rates were 92.50%and 90.83%,*** results show that the proposed localization method offers a viable approach for accurate harvesting localization.
Three-dimensional(3D)phenotyping is important for studying plant structure and *** detection and ranging(LiDAR)has gained prominence in 3D plant phenotyping due to its ability to collect 3D point ***,organ-level branc...
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Three-dimensional(3D)phenotyping is important for studying plant structure and *** detection and ranging(LiDAR)has gained prominence in 3D plant phenotyping due to its ability to collect 3D point ***,organ-level branch detection remains challenging due to small targets,sparse points,and low signal-to-noise *** addition,extracting biologically relevant angle traits is *** this study,we developed a stratified,clustered,and growing-based algorithm(SCAG)for soybean branch detection and branch angle calculation from LiDAR data,which is heuristic,open-source,and *** achieved high branch detection accuracy(F-score=0.77)and branch angle calculation accuracy(r=0.84)when evaluated on 152 diverse soybean ***,the SCAG outperformed 2 other classic algorithms,the support vector machine(F-score=0.53)and density-based methods(F-score=0.55).Moreover,after applying the SCAG to 405 soybean varieties over 2 consecutive years,we quantified various 3D traits,including canopy width,height,stem length,and average *** data filtering,we identified novel heritable and repeatable traits for evaluating soybean density tolerance potential,such as the ratio of average angle to height and the ratio of average angle to stem length,which showed greater potential than the well-known ratio of canopy width to height *** work demonstrates remarkable advances in 3D phenotyping and plant architecture *** algorithm can be applied to other crops,such as maize and *** dataset,scripts,and software are public,which can further benefit the plant science community by enhancing plant architecture characterization and ideal variety selection.
This paper examines the overall performance of the Daffier-Hellman key trade algorithm for the relaxed transmission of data in cryptography networks. Two types of Daffier-Hellman key exchanges are considered: the trad...
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The A∗ algorithm is a well-known graph search technique widely used in various domains like robotics, games, and logistics. A∗ combines breadth-first search and heuristics to find optimal paths by evaluating cost and ...
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In response to the practical problems faced by manual defect detection in the textile industry, this paper studies an automatic fabric defect detection algorithm based on machine vision. Starting from the research bac...
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