A Plant Disease Recognition Method Based on Fusion of Images and Graph Structure Text

The disease image recognition models based on deep learning have achieved relative success under limited and restricted conditions, but such models are generally subjected to the shortcoming of weak robustness. The model accuracy would decrease obviously when recognizing disease images with complex backgrounds under field conditions. Moreover, most of the models based on deep learning only involve characterization learning on visual information in the image form, while the expression of other modal information rather than the image form is often ignored. The present study targeted the main invasive diseases in tomato and cucumber as the research object. Firstly, in response to the problem of weak robustness, a feature decomposition and recombination method was proposed to allow the model to learn image features at different granularities so as to accurately recognize different test images. Secondly, by extracting the disease feature words from the disease text description information composed of continuous vectors and recombining them into the disease graph structure text, the graph convolutional neural network (GCN) was then applied for feature learning. Finally, a vegetable disease recognition model based on the fusion of images and graph structure text was constructed. The results show that the recognition accuracy, precision, sensitivity, and specificity of the proposed model were 97.62, 92.81, 98.54, and 93.57%, respectively. This study improved the model robustness to a certain extent, and provides ideas and references for the research on the fusion method of image information and graph structure information in disease recognition.

Controlling hallucinations at word level in data-to-text generation

Data-to-Text Generation (DTG) is a subfield of Natural Language Generation aiming at transcribing structured data in natural language descriptions. The field has been recently boosted by the use of neural-based generators which exhibit on one side great syntactic skills without the need of hand-crafted pipelines; on the other side, the quality of the generated text reflects the quality of the training data, which in realistic settings only offer imperfectly aligned structure-text pairs. Consequently, state-of-art neural models include misleading statements –usually called hallucinations—in their outputs. The control of this phenomenon is today a major challenge for DTG, and is the problem addressed in the paper. Previous work deal with this issue at the instance level: using an alignment score for each table-reference pair. In contrast, we propose a finer-grained approach, arguing that hallucinations should rather be treated at the word level. Specifically, we propose a Multi-Branch Decoder which is able to leverage word-level labels to learn the relevant parts of each training instance. These labels are obtained following a simple and efficient scoring procedure based on co-occurrence analysis and dependency parsing. Extensive evaluations, via automated metrics and human judgment on the standard WikiBio benchmark, show the accuracy of our alignment labels and the effectiveness of the proposed Multi-Branch Decoder. Our model is able to reduce and control hallucinations, while keeping fluency and coherence in generated texts. Further experiments on a degraded version of ToTTo show that our model could be successfully used on very noisy settings.

Students’ Writing Difficulties in Procedure Text: An Analysis Study

The function of writing skills is the most effective way to show someone’s English proficiency, including the ability and difficulties. The objective of this research was to know the factors and to the dominant factor of students’ writing difficulties in procedure text. The instruments of this research were interview and writing test as the support data. Therefore, the researcher conducted a descriptive qualitative study analysis. The technique in analysed the data of the interview was a descriptive analysis technique (percentage) and descriptive analysis technique without percentage to analyse the writing test. The researcher asked some aspects of students’ writing difficulties in writing procedure text based on the syllabus of class 9 K13 namely social function, structure text, language features, and topic. For the writing test, the students were asked to write a procedure text. So that the students had difficulties in social function, structure text, language features, and topic. This research showed the dominant factor students’ writing difficulties in procedure text was language features, like vocabulary and grammar which made the students difficult when writing the procedure text. Thus, the students still faced difficulties in writing skills like procedure text and the students have to improve their ability in writing skills. Keywords: Difficulty, Writing, Procedure Text

Content-Enhanced Network Embedding for Academic Collaborator Recommendation

It is meaningful for a researcher to find some proper collaborators in complex academic tasks. Academic collaborator recommendation models are always based on the network embedding of academic collaborator networks. Most of them focus on the network structure, text information, and the combination of them. The latent semantic relationships exist according to the text information of nodes in the academic collaborator network. However, these relationships are often ignored, which implies the similarity of the researchers. How to capture the latent semantic relationships among researchers in the academic collaborator network is a challenge. In this paper, we propose a content-enhanced network embedding model for academic collaborator recommendation, namely, CNEacR. We build a content-enhanced academic collaborator network based on the weighted text representation of each researcher. The content-enhanced academic collaborator network contains intrinsic collaboration relationships and latent semantic relationships. Firstly, the weighted text representation of each researcher is obtained according to its text information. Secondly, a content-enhanced academic collaborator network is built via the similarity of the weighted text representation of researchers and intrinsic collaboration relationships. Thirdly, each researcher is represented as a latent vector using network representation learning. Finally, top- k similar researchers are recommended for each target researcher. Experiment results on the real-world datasets show that CNEacR achieves better performance than academic collaborator recommendation baselines.

The Human Factor: Accounting for Texts and Contexts in the Analysis of Foreign Policy and International Relations

Acknowledging the role of discourses as the entry door to social reality, the article highlights the value that discourse analysis (DA) can add to the cognate fields of foreign policy analysis (FPA) and international relations (IR). It argues that DA offers researchers an analytical platform to focus in parallel on the interaction between levels of analysis traditionally considered as separate (domestic/international, agent/structure, text/context). The first section of the article discusses the framing, generative, performative, and coordinative functions of discourse and highlights how DA helps disciplinary cross-fertilization. The second section reviews the way in which various perspectives on DA have approached the cognate fields of FPA and IR and makes the case for moving across theoretical and disciplinary boundaries. The third section critically reviews the methods of analysis that allow scrutinizing the connections between texts and context and the performative power of a word. Resumen Este artículo señala que el análisis del discurso (AD) puede agregar mucho valor a los campos afines del análisis de la política exterior (APE) y las relaciones internacionales (RI). Al reconocer el papel de los discursos como puerta de entrada a la realidad social, el artículo sostiene que el AD ofrece a los investigadores una plataforma analítica para centrarse al mismo tiempo en la interacción entre los niveles de análisis tradicionalmente considerados por separado (nacional/internacional, agente/estructura, texto/contexto). El artículo continúa de la siguiente manera. En la primera sección se analiza las funciones de estructuración, generativas, performativas y de coordinación del discurso, y hace hincapié en cómo el análisis del discurso ayuda a la fertilización cruzada disciplinaria. En la segunda sección se examina cómo las diversas perspectivas sobre el DA se han enfocado en los campos afines del APE y las RI, y se demuestra la necesidad de traspasar los límites teóricos y disciplinarios. En la tercera sección se examina de manera crítica los métodos de análisis que permiten investigar las conexiones entre los textos y el contexto, y el poder performativo de la palabra. Extrait Cet article souligne le fait que l'Analyse des discours peut ajouter beaucoup de valeur aux domaines apparentés à l'Analyse des politiques étrangères et aux Relations internationales. Il admet le rôle des discours comme porte d'entrée vers la réalité sociale et soutient que l'Analyse des discours dote les chercheurs d'une plateforme analytique pour se concentrer en parallèle sur l'interaction entre les niveaux d'analyse traditionnellement considérés comme distincts (intérieur/international, agent/structure, texte/contexte). Cet article traite cette question de la manière suivante: La première section aborde les fonctions génératives, performatives, coordinatives et de cadrage du discours et souligne la manière dont l'Analyse des discours contribue à l'enrichissement croisé des disciplines. La deuxième section évalue la manière dont les diverses perspectives de l'Analyse des discours ont approché les domaines apparentés à l'Analyse de la politique étrangère et aux relations internationales et plaidé en faveur d'un dépassement des limites liées aux théories et disciplines. La troisième section évalue d'un œil critique les méthodes d'analyse qui permettent d'examiner minutieusement les liens entre textes et contexte et le pouvoir performatif des mots.

IMPROVEMENT OF DESCRIPTION TEXT WRITING SKILLS THROUGH THE APPLICATION OF THE CLUSTERING METHOD FOR STUDENTS

Writing skill is a competency that the student should accive in the end of teaching and learning process, in each genre they learned. Description text is a texs that, learned in grade ten (x) in the first semester. Description text is text that decribe place, thing and people in detail. The structure text of description text are identification and description the language features of description text are. Use-present tense, noun phrase and passive sentence. In fact there are many student who cannot write the description text well. Their paragraph is bad, they use the wrong tense, diction and noun phrase. Their creativity is still low there is few students who answer and ask to the teacher, if they have problem and they are afraid to share their ideas so the researcher try to do the class action researh using clustering method to increase the students, skill in writing description text : This class action researh is carried out in class X IPS 4 SMAN 1 Tengaran 2014/2015 academic year in first semester. Based on this class action research, using clustering method can increase students’ writing skill in writing description text

Revision Strategy and Self-Diagnosis in Italian L1 and L2 Argumentative Essays

The present study investigates the effects of Revision Strategy (RS) on Argumentative Essay (AE) writing. Specifically, the study provides an analysis of 58 short AEs written by L1 and L2 university students. Two different levels of errors are examined: linguistic (Spelling, (Morpho)syntax, Lexicon, Syntax, Punctuation) and structure (Text structure and Coherence) errors, in order to measure how RS influences the texts. The comparison between RS and non-RS samples shows a significant difference in favour of texts with RS. In fact, we can surmise that RS positively influences text production both in L1 and L2 writing. In the third section we provide a quantitative analysis of the errors and we find some common issues within the specific rhetorical and linguistic framework of AE.

Developing critical literacy in science through an SFL-informed pedagogical heuristic

Purpose This paper describes and exemplifies a pedagogical heuristic for promoting critical literacy in science. Design/methodology/approach One way to support critical literacy in science is through a linguistically informed pedagogical heuristic called 5Es – Enquire, Engage, Examine, Exercise and Extend. Findings This paper describes the implementation of 5Es in a four-week middle school science unit on climate change, showing how the heuristic can be used to develop students’ understanding of the varied ways authors use language to present information, structure text, infuse judgment and evaluation, engage with and position the reader and express epistemic commitment to knowledge claims. Originality/value 5Es offer teachers a new heuristic for text exploration that develops students’ critical language awareness, advanced literacy and disciplinary literacy at the same time.

TATA BAHASA SEBAGAI CERMINAN NILAI IDEOLOGIS WACANA POLITIK PEREMPUAN DALAM “KOLOM PEREMPUAN”: KAJIAN ANALISIS WACANA KRITIS ATAS TEKS DI HARIAN SUARA MERDEKA

Critical Discourse Analysis is one of the language studies to uncover certain ideology particularly gender ideology. This research aimed to find out the language choice from the text writer both lexically and grammatically based on the experiential meaning. In addition, it aims to figure out the ideological value contained in discourse text. The data used in this research are 23 clauses in which there are woman words. The data were analyzed by using Critical Discourse Analysis (description, interpretation, and explanation) and Systemic Functional Linguistics approach. The data collection method was used documentation method with non-participatory observation and note-taking techniques. The data were analized by using content analysis method with abductive inferential technique. The result of this research shows that the reflected ideology based on lexical is revealed through the classification pattern (reality depiction), struggled for-ideology words, rewording (showing equality), meaning relation, and metaphor (picturing reality using symbol). In addition, the reflected ideology based on the grammatical is indicated by transitivity namely material process (projecting agent without goal, and target of action and policies), exixtential process (patriarchy bound), nominalization and passivation (hiding agent to cover actors), and negative sentence (defense on woman nature and condition). Then The structure text is analytical exposition consisting of thesis, argumentation, elaboration, and reiteration. Key words: experiential meaning, SFL, CDA, ideology