scholarly journals Automatic Calibration Algorithm for English Text Translation Based on Semantic Features

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Fengzhen Liu
Keyword(s):  
English Text ◽  
Automatic Calibration ◽  
Semantic Features ◽  
Body Parts ◽  
Output Matrix ◽  
Calibration Algorithm ◽  
Feature Based ◽  
English Articles ◽  
Accuracy Rates ◽  
Automatic Text

At present, the existing methods of English article flip calibration neglect to extract English semantic features, which leads to errors in English flip results and has a great impact on the accuracy and time consumption of translation sentence calibration. Therefore, a semantic feature-based automatic text flipping calibration algorithm is proposed. According to the features of semantic information in machine translation, a semantic grammar tree is constructed to complete the machine turning of English articles. The CART decision tree attribute is obtained, and the random forest method is introduced to extract the input matrix and output matrix of the corpus feature as samples to determine the spatial attribute feature of the mistranslated sentences. Choose 10000 English sentences about human body parts as the experimental object and design the simulation experiment. The experimental results show that the minimum and maximum accuracy rates are 95.4% and 100.0%, respectively. The proposed algorithm is time-consuming, and the KSMR value is lower than that of the traditional method. It is proved that the error rate of English article flipping is significantly reduced.

scholarly journals Identification of Plant-Leaf Diseases Using CNN and Transfer-Learning Approach

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1388
Author(s):  
Sk Mahmudul Hassan ◽  
Arnab Kumar Maji ◽  
Michał Jasiński ◽  
Zbigniew Leonowicz ◽  
Elżbieta Jasińska
Keyword(s):  
Disease Classification ◽  
Batch Size ◽  
Healthy Plant ◽  
Plant Leaves ◽  
Early Prevention ◽  
Computation Cost ◽  
Training Time ◽  
Feature Based ◽  
Deep Cnn ◽  
Accuracy Rates

The timely identification and early prevention of crop diseases are essential for improving production. In this paper, deep convolutional-neural-network (CNN) models are implemented to identify and diagnose diseases in plants from their leaves, since CNNs have achieved impressive results in the field of machine vision. Standard CNN models require a large number of parameters and higher computation cost. In this paper, we replaced standard convolution with depth=separable convolution, which reduces the parameter number and computation cost. The implemented models were trained with an open dataset consisting of 14 different plant species, and 38 different categorical disease classes and healthy plant leaves. To evaluate the performance of the models, different parameters such as batch size, dropout, and different numbers of epochs were incorporated. The implemented models achieved a disease-classification accuracy rates of 98.42%, 99.11%, 97.02%, and 99.56% using InceptionV3, InceptionResNetV2, MobileNetV2, and EfficientNetB0, respectively, which were greater than that of traditional handcrafted-feature-based approaches. In comparison with other deep-learning models, the implemented model achieved better performance in terms of accuracy and it required less training time. Moreover, the MobileNetV2 architecture is compatible with mobile devices using the optimized parameter. The accuracy results in the identification of diseases showed that the deep CNN model is promising and can greatly impact the efficient identification of the diseases, and may have potential in the detection of diseases in real-time agricultural systems.

scholarly journals A Novel Calibration Algorithm for Cable-Driven Parallel Robots with Application to Rehabilitation

2019 ◽  
Vol 9 (11) ◽  
pp. 2182 ◽  
Author(s):  
Han Yuan ◽  
Xianghui You ◽  
Yongqing Zhang ◽  
Wenjing Zhang ◽  
Wenfu Xu
Keyword(s):  
Calibration Method ◽  
Parallel Robot ◽  
Parallel Robots ◽  
Human Robot Interaction ◽  
Automatic Calibration ◽  
Unknown Parameters ◽  
Robot Interaction ◽  
Geometric Calibration ◽  
Rehabilitation Robots ◽  
Calibration Algorithm

Cable-driven parallel robots are suitable candidates for rehabilitation due to their intrinsic flexibility and adaptability, especially considering the safety of human–robot interaction. However, there are still some challenges to apply cable-driven parallel robots to rehabilitation, one of which is the geometric calibration. This paper proposes a new automatic calibration method that is applicable for cable-driven parallel rehabilitation robots. The key point of this method is to establish the mapping between the unknown parameters to be calibrated and the parameters that could be measured by the inner sensors and then use least squares algorithm to find the solutions. Specifically, the unknown parameters herein are the coordinates of the attachment points, and the measured parameters are the lengths of the redundant cables. Simulations are performed on a 3-DOF parallel robot driven by four cables for validation. Results show that the proposed calibration method could precisely find the real coordinate values of the attachment points, with errors less than 10 − 12 mm. Trajectory simulations also indicate that the positioning accuracy of the cable-driven parallel robot (CDPR) could be greatly improved after calibration using the proposed method.

Delay in the acquisition of Differential Object Marking by Spanish monolingual and bilingual teenagers

2016 ◽  
Vol 21 (2) ◽  
pp. 159-177 ◽  
Author(s):  
Pedro Guijarro-Fuentes ◽  
Acrisio Pires ◽  
Will Nediger
Keyword(s):  
Repeated Measures ◽  
Full Range ◽  
Judgment Task ◽  
Semantic Features ◽  
Differential Object Marking ◽  
Test Items ◽  
Feature Reassembly ◽  
Feature Based ◽  
Vulnerability Hypothesis ◽  
Object Marking

Aims and Objectives/Purpose/Research Questions: This study investigated the acquisition of Spanish Differential Object Marking (DOM) by bilingual and monolingual Spanish teenagers, evaluating to which extent their knowledge of DOM can be explained by different theories of acquisition. Design/Methodology/Approach: Two experiments with bilingual and monolingual Spanish teenagers (ages 10 to 15) were conducted. The experiments included an Elicited Production Completion Task, in which a space was to either be filled with an object marker or left blank, and a Context-Matching Acceptability Judgment Task. Data and Analysis: 54 subjects (44 bilinguals and 10 monolinguals) were tested. For both tasks, there were 6 conditions testing different syntactic–semantic features that trigger DOM (test items n = 42 in each task). The data were analysed with linear regressions and repeated measures analyses of variance. Findings/Conclusions: This study’s results show that bilingual teenagers do not demonstrate significant differences from age-matched monolinguals in their competence regarding the syntactic–semantic properties of DOM. Both groups are below ceiling in showing evidence of knowledge about all the syntactic–semantic features involved in DOM, indicating the possibility of a significant delay beyond childhood in their acquisition. Originality: There are few previous studies on the acquisition of DOM, and none which consider the full range of features and specific population considered here. Work by Montrul focuses on the animacy feature, while Guijarro-Fuentes considers the full range of features, but for adult L2 learners of Spanish. Significance/Implications: This study shows that the Interface Vulnerability Hypothesis, the Feature Reassembly Hypothesis, the Full Access/Full Transfer Hypothesis and the Interpretability Hypothesis have limitations in explaining its results. Instead, a feature-based approach is proposed in which the specification of features beyond animacy raises difficulties for the acquisition of DOM until late childhood.

scholarly journals PERSONIFICATION IN THE EMOTIVE PROSE TEXT (IN THE NOVEL "LES VENTS NOIRS" ("THE BLACK WINDS") BY ARNAUD DE LA GRANGE)

2021 ◽  
pp. 115-124
Author(s):  
ALEXEY V. FEDORINOV ◽  
◽  
VALENTINA F. REMIZOVA ◽  
Keyword(s):  
Mental States ◽  
Time Of Day ◽  
Semantic Features ◽  
Body Parts ◽  
The Novel ◽  
Natural Phenomena ◽  
Abstract Concepts ◽  
Related Substances ◽  
Important Means ◽  
Physical Abilities

The paper examines the denotata of personification in the novel "Les vents noirs" ("The Black Winds") by Arnaud de La Grange. The quantitative and qualitative analysis of the material under study has resulted in the identification of the main groups of personifications in the emotive prose text: personification of objects, personification of abstract concepts, personification of physical (natural) phenomena. Within each group, subgroups have been identified based on semantic features. The group of physical (natural) phenomena includes denotata of meteorological phenomena, time of day, celestial bodies and the light they radiate. The group of abstract concepts covers a wide variety of denotata related to mental states, mental and physical abilities, moral experiences, military and political terms and the philosophical category of time. It has been figured out that the most frequent examples are personification of objects that include geographical objects, natural objects and related substances, human body parts, and objects related to the war. Those objects and phenomena that play a key role in the development of the novel have been personified. Personification as a part of the lexical system of the novel, serves as the most important means of constructing this emotive prose text.

scholarly journals Influence of native language and general English proficiency on the use of articles in English

2019 ◽  
Vol 9 (2) ◽  
pp. 110-121
Author(s):  
Selma Elyildirim
Keyword(s):  
Language Proficiency ◽  
Second Language Learners ◽  
English Proficiency ◽  
Native Language ◽  
Great Difficulty ◽  
Target Language ◽  
Supporting Evidence ◽  
Semantic Features ◽  
Article System ◽  
English Articles

Second language learners face a great difficulty in the use of English articles since their native language does not have an article system which is similar to the target language they learn. Turkish is one of the languages which have an article system marking the semantic features ‘definiteness’ or ‘specificity’ in different ways.  It encodes these features by using case morphology, word order, stress and tense-aspect modality.  Being aware of the fact that this difference and lack of an article system similar to English may cause problems to learners, this study investigates the acquisition of the English articles by Turkish learners.   The data used in the study came from a fill-in-the blank task and a cloze test.  The former included 20 test-sentences assessing the production of English articles in terms of definiteness and specificity whereas the latter had 20 blanks measuring the proficiency of learners. Thirty five English major students attending a university in Turkey participated in the study. Following the data collection, the data were analysed to find out the effect of the learners’ native language as well as their general English proficiency on the production of English articles.  The results provided supporting evidence that the participants had some difficulties in the production of the definite and indefinite articles in English. In view of this finding, this paper discusses both the results and pedagogical implications of the study. Keywords: English articles, definiteness, specificity, L1 influence, language proficiency

scholarly journals SPACE CALIBRATION OF THE ROBOT SYSTEM IN PUNCTURE SURGERY

2021 ◽  
Author(s):  
CHANGLE LI ◽  
ZEQUN LI ◽  
XUEHE ZHANG ◽  
GANGFENG LIU ◽  
JIE ZHAO
Keyword(s):  
Automatic Calibration ◽  
Robot System ◽  
System Noise ◽  
Digital Reference ◽  
Calibration Algorithm ◽  
Tomography Method ◽  
Improving Accuracy ◽  
Strong Radiation ◽  
Surgical System ◽  
Poor Stability

Traditional manual puncture surgery has low positioning accuracy and poor stability. Moreover, the computed tomography method can cause strong radiation damage. Therefore, this study intends to establish a robotic system in puncture surgery, which is based on optical registration to improve safety, accuracy, and efficiency. As the accuracy of surgical space calibration influences the accuracy of the surgical system, this study proposes an improved automatic calibration algorithm for linear rotation. The algorithm can reduce error caused by manual calibration and system noise. Recalibration is not required provided that the pose of the digital reference frame is unchanged, thereby improving accuracy and efficiency. The proposed algorithm is experimentally verified to prove its effectiveness. Results show that the average errors of position and posture are 0.25[Formula: see text]mm and 0.2∘, respectively. The accuracy of calibration fully meets the needs of surgery.

scholarly journals Holographic Micromirror Array with Diffuse Areas for Accurate Calibration of 3D Light-Field Display

2020 ◽  
Vol 10 (20) ◽  
pp. 7188
Author(s):  
Lode Jorissen ◽  
Ryutaro Oi ◽  
Koki Wakunami ◽  
Yasuyuki Ichihashi ◽  
Gauthier Lafruit ◽  
...  
Keyword(s):  
Light Field ◽  
3D Visualization ◽  
Calibration Method ◽  
Automatic Calibration ◽  
Display System ◽  
Extrinsic Parameters ◽  
Calibration Algorithm ◽  
Fully Automatic ◽  
Intrinsic And Extrinsic Parameters ◽  
Micromirror Array

Light field 3D displays require a precise alignment between the display source and the micromirror-array screen for error free 3D visualization. Hence, calibrating the system using an external camera becomes necessary, before displaying any 3D contents. The inter-dependency of the intrinsic and extrinsic parameters of display-source, calibration-camera, and micromirror-array screen, makes the calibration process very complex and error-prone. Thus, several assumptions are made with regard to the display setup, in order to simplify the calibration. A fully automatic calibration method based on several such assumptions was reported by us earlier. Here, in this paper, we report a method that uses no such assumptions, but yields a better calibration. The proposed method adapts an optical solution where the micromirror-array screen is fabricated as a computer generated hologram with a tiny diffuser engraved at one corner of each elemental micromirror in the array. The calibration algorithm uses these diffusing areas as markers to determine the relation between the pixels of display source and the mirrors in the micromirror-array screen. Calibration results show that virtually reconstructed 3D scenes align well with the real world contents, and are free from any distortion. This method also eliminates the position dependency of display source, calibration-camera, and mirror-array screen during calibration, which enables easy setup of the display system.

Understanding semantic accents in Japanese–English bilinguals: A feature-based approach

2020 ◽  
Vol 24 (1) ◽  
pp. 137-153
Author(s):  
Eriko Matsuki ◽  
Yasushi Hino ◽  
Debra Jared
Keyword(s):  
The Other ◽  
Cultural Immersion ◽  
Semantic Features ◽  
L2 Proficiency ◽  
Feature Based ◽  
L1 And L2 ◽  
Japanese English

AbstractA bilingual exhibits a “semantic accent” when they comprehend or use a word in one language in a way that is influenced by its translation. Semantic accents are well-captured by feature-based models: however, few studies have specifically examined the processing of features that contribute to a semantic accent. Japanese–English bilinguals and monolinguals of each language completed three feature-based tasks focusing on culture-specific semantic features. Bilinguals exhibited semantic accents in L1 and L2 in that they had stronger associations than monolinguals between the features specific to one culture and words in the other language. Within bilinguals, culture-specific features were more strongly associated with the congruent language than the incongruent language. Finally, changes in the strengths of associations between culture-specific features and words depended more on L2 cultural immersion than L2 proficiency. Semantic accents lessened in L2 and increased in L1 after many years of exposure to the L2 culture.

A Scalable Graph-Based Semi-Supervised Ranking System for Content-Based Image Retrieval

2013 ◽  
Vol 4 (4) ◽  
pp. 15-34
Author(s):  
Xiaojun Qi ◽  
Ran Chang
Keyword(s):  
Image Retrieval ◽  
Semantic Features ◽  
Dynamic Feedback ◽  
Ranking System ◽  
Retrieval Systems ◽  
Feature Based ◽  
Semantic Spaces ◽  
Supervised Ranking ◽  
High Level

The authors propose a scalable graph-based semi-supervised ranking system for image retrieval. This system exploits the synergism between relevance feedback based transductive short-term learning and semantic feature-based long-term learning to improve retrieval performance. Active learning is applied to build a dynamic feedback log to extract semantic features of images. Two-layer manifold graphs are then built in both low-level visual and high-level semantic spaces. One graph is constructed at the first layer using anchor images obtained from the feedback log. Several graphs are constructed at the second layer using images in their respective cluster formed around each anchor image. An asymmetric relevance vector is created for each second layer graph by propagating initial scores from the first layer. These vectors are fused to propagate relevance scores of labeled images to unlabeled images. The authors’ extensive experiments demonstrate the proposed system outperforms four manifold-based and five state-of-the-art long-term-based image retrieval systems.

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