Schematic Network Research Articles

Multi-scale feature fusion segmentation and lightweight ensemble deep learning approach for urban slum classification using satellite images

ABSTRACT Although there are some drawbacks to satellite imaging, such as the difficulty in identifying slums in highly populated metropolitan areas, it is nonetheless a useful tool for preliminary screening and can support on-the-ground and other data sources. Hence, we proposed the MSFF-Seg (Multi-Scale Feature Fusion-based Segmentation) model for urban slum classification using satellite images. Hence we proposed the MSFF-Seg model for urban slum classification using satellite images. Initially, three types of corrections are performed in preprocessing such as geometric correction which is corrected by Enhanced Scale Invariant Feature Transform (ESIFT), radiometric correction which is corrected by Ground-based Relative Radiometric Calibration (GRRC), and atmospheric correction which is corrected by homomorphic filter. After completion of preprocessing phase, segmentation is initiated by Tweak Mask RCNN which extracts the features in multilevel for segmentation that increases the segmentation accuracy. The segmented images are fed into an ensemble classifier for urban slum identification. Here, three types of deep learning are used for ensemble learning namely Schematic Convolutional Neural Network (SCNN), Shallow MobileNet, and Lite ShuffleNet. They extract multiple features from the segmented region, based on the extracted features. LGBM performed urban slum classification which classifies the images into two classes such as slums and non-slums. Finally, the performance of this research is evaluated based on several performance metrics like accuracy (98%), precision (96%), recall (94%), and F1 score (97%), which proved that the proposed work achieved superior performance in urban slum classification.

Assessing the Suitability of Fractal Dimension for Measuring Graphic Complexity Change in Schematic Metro Networks

Schematization is a process of generating schematic network maps (e.g., metro network maps), where the graphic complexity of networks is usually reduced. In the past two decades, various automated schematization methods have been developed. A quantitative and accurate description of the complexity variation in the schematization is critical to evaluate the usability of schematization methods. It is noticed that fractal dimension (F) has been widely used to analyze the complexity of geographic objects, and this indicator may be appropriate for this purpose. In some existing studies, although F has been employed to describe the complexity variation, the theoretical and experimental basis for adopting this approach is inadequate. In this study, experiments based on 26 Chinese cities’ metro networks showed that the F of all these metro networks have decreased in schematization, and a significant positive correlation exists between the F of original networks and the reduction of F after schematization. The above results were verified to have similar trends with the subjective opinions of participants in a psychological questionnaire. Therefore, it can be concluded that F can quantitatively measure the complexity change of networks in schematization. These discoveries provide the basis for using F to evaluate the usability of schematization methods.

Action-rule-based cognitive control enables efficient execution of stimulus-response conflict tasks: a model validation of Simon task performance.

The human brain can flexibly modify behavioral rules to optimize task performance (speed and accuracy) by minimizing cognitive load. To show this flexibility, we propose an action-rule-based cognitive control (ARC) model. The ARC model was based on a stochastic framework consistent with an active inference of the free energy principle, combined with schematic brain network systems regulated by the dorsal anterior cingulate cortex (dACC), to develop several hypotheses for demonstrating the validity of the ARC model. A step-motion Simon task was developed involving congruence or incongruence between important symbolic information (illustration of a foot labeled "L" or "R," where "L" requests left and "R" requests right foot movement) and irrelevant spatial information (whether the illustration is actually of a left or right foot). We made predictions for behavioral and brain responses to testify to the theoretical predictions. Task responses combined with event-related deep-brain activity (ER-DBA) measures demonstrated a key contribution of the dACC in this process and provided evidence for the main prediction that the dACC could reduce the Shannon surprise term in the free energy formula by internally reversing the irrelevant rapid anticipatory postural adaptation. We also found sequential effects with modulated dip depths of ER-DBA waveforms that support the prediction that repeated stimuli with the same congruency can promote remodeling of the internal model through the information gain term while counterbalancing the surprise term. Overall, our results were consistent with experimental predictions, which may support the validity of the ARC model. The sequential effect accompanied by dip modulation of ER-DBA waveforms suggests that cognitive cost is saved while maintaining cognitive performance in accordance with the framework of the ARC based on 1-bit congruency-dependent selective control.

A replication and extension of the Personal Social Media Ecosystem Framework

Abstract The recently forwarded Personal Social Media Ecosystem Framework (PSMEF) allows researchers to study social media in terms of generalized types of user interfaces. This study formally extended the PSMEF via the Digital User Interface Model and replicated previous work by evidencing the existence of new (e.g., Overtly Algorithmic Content Pages) and validating previously identified types of user interfaces (e.g., Home Pages and Chats/Messages) that make up individuals’ personal social media environments. Using topic modeling (i.e., Latent Dirichlet Allocation) and a novel mixed methods approach (i.e., schematic semantic network analysis), we quantitatively evidenced four distinct classes of user interfaces based on open-ended descriptions that participants provided for six popular social media platforms (i.e., Instagram, Snapchat, Facebook, Twitter, TikTok, and YouTube). Results inform on the qualitative differences between distinct user interface classes that underwrite users’ experiences over social media, with implications for conceptualization and operationalization related to social media use.

Revealing Schematic Map Designs with Preservation of Relativity in Node Position and Segment Length in Existing Official Maps

Schematic maps have widely been used for representing transport networks. In the schematization process, preserving the relative position of nodes and the relative length of segments are considered highly important for constructing spatial cognition. Some researchers have regarded these as general principles of automated schematization. However, in-depth investigations into the conversion of these general principles into specific schematic network map designs are still lacking. This study aimed to empirically investigate how the two relative relations are preserved in existing manually produced schematic maps to better understand and interpret designer thinking. Official underground network maps of 32 cities were used in this study. The results revealed that (1) relative relations were largely preserved with a preservation ratio of approximately 80%, and the global preservation ratios of two relative relations were significantly higher than those of local preservation; (2) the preservation of relative position took priority over the preservation of relative length for the schematic maps with significant enlargement of dense regions; and (3) a reference object may be used for preserving relative relations, for example, the center region or major axis. The findings of this study will assist in developing and/or optimizing design rules for automated schematization while preserving relative relations.

The development of the Chinese VdeO cleft construction

AbstractThis paper addresses the development of the Chinese VdeO cleft construction, and how the cleft constructional network was developed in the history of Chinese. It is argued that VdeO clefts emerged in the 13th century which was about 300 years later than VPdeclefts. A key factor in their development is the use in Middle Chinese of relative clause in post-copula position. We argue that the emergence of VdeO clefts also involved analogization to the extant VPdeclefts as well as deferred equatives. Once VdeO clefts occurred, they were recruited into the cleft network as a subschema, resulting in the schematic network being augmented and expanded. This study is a contribution to the developing field of constructionalization by making more explicit the way how nodes are created in a constructional network and how the network is reorganized and expanded.

Automated generation of labelled schematic network maps

Automated generation of labelled schematic network maps

Schema Theory and Language Acquisition: Justification for the Implementation of a Spiral Syllabus

In the realm of foreign language education, most educational institutions’ syllabi and textbooks organize content in a linear fashion, moving from topic to topic. By nature of having disparate topics, the vocabulary and grammar can vary widely with little overlap beyond the most frequently used words of a language. While the linear approach may be suitable for learning topics in one’s first language (L1) since a rich linguistic schematic network has already been built, in the case of EFL students, this approach is flawed due to students’ lack of meaningful exposure and practice of the target language/vocabulary outside of the classroom, and as a result, second language (L2) learners forget much of the vocabulary that is studied. A different approach, via using a spiral syllabus, is proposed to teach L2 learners, which may build a richer schematic network and consequently strengthen long-term memory. In this interpretative analysis, the relationship between schema theory, memory, and its application to second language learning is explored. Justified by the theoretical research of schema theory and empirical studies of spaced repetition systems, a proposal for a spiral syllabus and the need for further research in this area is described.

Review of Szawerna (2007): A Corpus-Based Study of Nominalizations Predicated by English Deverbal Nouns In -tion

In A Corpus-Based Study of Nominalizations Predicated by English Deverbal Nouns in -tion, Michal Szawerna presents the results of his PhD research on -tion nominalizations. Szawerna’s approach is couched in the Cognitive Grammar framework as developed primarily by Langacker (1987 and 1991) and fits in with the traditional approach to nominalization in that it is essentially word-based (i.e. it focuses on the word level rather than on the nominalized NP as a whole or the discourse context in which it functions). As in most traditional analyses of nominalization, Szawerna takes the lexical-descriptive and aspectual properties of the base verb as starting point (described in cognitive terms) and then attempts to capture the distinct ‘profiles’ of the derivations in -tion in a schematic network of interrelated meanings. Since there are relatively few publications that have nominalizations as their sole focus (other monographs on nominalization are Marchand 1969; Heyvaert 2003; Nordrum 2007) and even fewer that consider derived nouns in -ion, Szawerna’s book is a welcome addition to the literature. Unfortunately, the carefulness with which the author tackles the issue is obscured by the book’s heavy-going style, long-winded explanations, repetitions and extensive use of abbreviations and cognitive terminology. The overall structure of the book, with only three chapters, two of which take up more than 100 pages, moreover makes for hard reading. Those willing to work their way through it, however, will find a rich overview of subtypes of -ion nominalizations and a serious attempt to map out the semantic intricacies of the -ion nominalization system.

Exploring Flowering Genes in Isabgol (Plantago ovata Forsk.) Through Transcriptome Analysis

Flowering is one of the major developmental processes that govern the economic yield of crop plants. However, little is known about the molecular mechanisms underlying flowering in Isabgol, an important high-value medicinal crop. Here, we analyzed the leaf transcriptome of early and late flowering genotypes by high throughput next-generation sequencing to uncover the genes and pathways involved in flowering time and flower development. Illumina paired-end sequencing of Isabgol leaves at the stem elongation stage, generated 8,976,119 and 4,282,684 reads respectively in DPO-14 (early flowering) and DPO-185 (late flowering) genotypes. The sequence assembly resulted in 40,175 and 39,533 transcripts respectively in early and late genotypes. A total of 17,768 (95.50) in DPO-14 and 21,255 (94.10) in DPO-185 CDS were annotated. There were 8981CDS were differentially expressed of which 1220 (13.58%) were significantly upregulated while 1485 (16.53%) CDS were significantly downregulated in DPO-185 compared with DPO-14. In total, 229 genes were identified belongs to distinct flowering pathways in Isabgol. A putative schematic network of flowering pathway regulation in Isabgol was proposed. Significant DEGs (60 genes) related to flowering time and flower development were detected between the early and late flowering genotypes. Significant differences in fold change expression of 17 genes were observed in early and late flowering genotypes. Many differentially expressed genes (DEGs) involved in flowering time and flower development were identified. The expression data will serve as a resource for unraveling the functions of specific genes involved in flower development in Isabgol and other plants. These findings are significant for further understanding of the molecular basis for flowering time regulation, breeding, and molecular biology in Isabgol as well as other crop plants.

Interconnected IoT Architectural Platforms and Applications

Future technology totally based on smart automation and smart information transfer. Internet of Things makes a bridge communication from appliances and industry to smart automation. Sensors of Internet of Things records the physical data from the appliances and industry and transfer accordingly for analytic and decision processing. Next in line to advancements, for example, RFID and Wireless Sensor Networks, the Internet Of Things has unearthed bolt upright interconnection of restrictive frameworks. IoT depicts the future condition of the interconnected network between these storehouses, empowering the revelation of tangible sensors and elucidation of data transfer amidst the things. This paper comes up with a schematic path and network empowerment to give the interconnections among different frameworks and platform based data transmission technology and information management.

A construction-based account of the synchrony and diachrony of the Chinese middle construction

Abstract Chinese middle construction (Chinese MC) uses the form ‘N+V+qilai+C’ to express passive meaning. This study has shown that Chinese MC’s internal connections can be reflected by its synchronic hierarchy. Chinese MC expands horizontally through argument structure and vertically through semantics and its expansion mechanism can be explained by the varying abstraction model of categorization which combines the prototype and the exemplar model. This study has also validated the truth that Chinese MC is a concept encompassing unclear boundaries within its members by using the schematic network model which is the combination of the radial set model and the overlapping set model to represent the internal connections of Chinese MC. By connecting Chinese MC with patient-subject sentences, this study has shown that the expansion of Chinese MC is affected by other structures. Finally, this study has unveiled the affinity between constructionalization and grammaticalization by examining how Chinese MC relates to V-qilai’s grammaticalization.

Automated Generation of Schematic Network Maps with Preservation of Main Structures

Abstract. Schematic (network) maps are helpful for people to perform route planning and orientation tasks. The London Underground Map designed by Harry Beck is an excellent example of such maps. Generally, there are three approaches to generate schematic maps: manual, semi-automated (or computer-aided) and fully automated. In the past twenty years, many researchers have been devoted to the development of automated methods for generation of schematic maps. In these automated methods, various sets of constraints are used. Most of these constraints are for geometric properties of individual features (such as the lengths and orientations of lines); a few constraints are for relations between features (such as the minimum distance threshold between non-incident edges); but none are explicitly for the main structures of whole networks. It is believed that preservation of the main structure is the most important, because main structure is represented by global features which is first recognized by a pre-attentive process in human cognition – a global-to-local process (in which local features are then recognized by an attentive process). It is hypothesized here that an automated method with the preservation of main structures of networks should be able to generate schematic maps with improved clarity and aesthetics.This paper describes the development of an automated method with the preservation of the main structures of line networks. In this method, automated schematization is treated as an optimization problem and is represented as a Mixed-Integer Programming (MIP) model, which consists of an objective function and a set of constraints. The preservation of main structures is modelled into constraints (i.e., making important lines straight and orientating them to specific directions) for the model. The MIP model is imported into a commercial optimization software called “IBM ILOG CPLEX Optimization Studio” (version 12.6.3) for the acquisition of optimal solutions (i.e., coordinates of vertices and edges on schematic maps). The whole process is shown in Figure 1.Experimental evaluations have been conducted with a set of real-life data as shown in Figure 2a and 2d. Schematic maps are generated by this new method with the preservation of main structures and by an old method without the particular consideration for main structures, as shown in Figures 2b, 2c, 2e and 2f. A psychological test with a questionnaire has been conducted, which consists of questions regarding “clarity”, “recognition of major lines”, “visual simplicity” and “satisfaction”. It is found that, in all these four aspects, the map generated by new methods with preservation of main structures have higher scores than those by the old method. These improvements are proved to be significant after paired-t tests.Therefore, it is concluded that the new automated method with the preservation of main structures can generate schematic maps with significant improvement in clarity and aesthetics. This study is helpful to improve automated methods for generation of schematic maps and other visual representations.

Integrating general principles into mixed-integer programming to optimize schematic network maps

ABSTRACTSchematic maps are popular for the representation of transport networks. Many automated methods have been developed to generate such maps. In these methods, optimization techniques work with various sets of constraints. Most of these constraints govern geometric properties of individual features. A few constraints address relationships among features, but none explicitly deal with the main structure of an entire network. We believe that preservation of main structure is the most important and preservation of relative relations is helpful. This is because human perception follows a global-to-local process. These constraints have recently been formed into four general principles, with two for global structure and two for relativity of features. This study develops an automated method by integrating these principles into the mixed-integer programming (MIP) framework. Experimental evaluations have been conducted with two sets of real-world transit networks. In comparison to the existing method, the proposed method has smaller fractal dimensions, better computational performance and higher scores in terms of clarity, recognition of major lines, visual simplicity and satisfaction. Therefore, it is concluded that the proposed method can generate schematic maps with improved clarity and aesthetics. The idea in this study is also helpful for the design of other visual representations.

Analyzing the genes related to nicotine addiction or schizophrenia via a pathway and network based approach

The prevalence of tobacco use in people with schizophrenia is much higher than in general population, which indicates a close relationship between nicotine addiction and schizophrenia. However, the molecular mechanism underlying the high comorbidity of tobacco smoking and schizophrenia remains largely unclear. In this study, we conducted a pathway and network analysis on the genes potentially associated with nicotine addiction or schizophrenia to reveal the functional feature of these genes and their interactions. Of the 276 genes associated with nicotine addiction and 331 genes associated with schizophrenia, 52 genes were shared. From these genes, 12 significantly enriched pathways associated with both diseases were identified. These pathways included those related to synapse function and signaling transduction, and drug addiction. Further, we constructed a nicotine addiction-specific and schizophrenia-specific sub-network, identifying 11 novel candidate genes potentially associated with the two diseases. Finally, we built a schematic molecular network for nicotine addiction and schizophrenia based on the results of pathway and network analysis, providing a systematic view to understand the relationship between these two disorders. Our results illustrated that the biological processes underlying the comorbidity of nicotine addiction and schizophrenia was complex, and was likely induced by the dysfunction of multiple molecules and pathways.

Unraveling the Root Proteome Changes and Its Relationship to Molecular Mechanism Underlying Salt Stress Response in Radish (Raphanus sativus L.).

To understand the molecular mechanism underlying salt stress response in radish, iTRAQ-based proteomic analysis was conducted to investigate the differences in protein species abundance under different salt treatments. In total, 851, 706, and 685 differential abundance protein species (DAPS) were identified between CK vs. Na100, CK vs. Na200, and Na100 vs. Na200, respectively. Functional annotation analysis revealed that salt stress elicited complex proteomic alterations in radish roots involved in carbohydrate and energy metabolism, protein metabolism, signal transduction, transcription regulation, stress and defense and transport. Additionally, the expression levels of nine genes encoding DAPS were further verified using RT-qPCR. The integrative analysis of transcriptomic and proteomic data in conjunction with miRNAs was further performed to strengthen the understanding of radish response to salinity. The genes responsible for signal transduction, ROS scavenging and transport activities as well as several key miRNAs including miR171, miR395, and miR398 played crucial roles in salt stress response in radish. Based on these findings, a schematic genetic regulatory network of salt stress response was proposed. This study provided valuable insights into the molecular mechanism underlying salt stress response in radish roots and would facilitate developing effective strategies toward genetically engineered salt-tolerant radish and other root vegetable crops.

De novo transcriptome analysis in radish (Raphanus sativus L.) and identification of critical genes involved in bolting and flowering.

BackgroundThe appropriate timing of bolting and flowering is pivotal for reproductive success in Brassicaceae crops including radish (Raphanus sativus L.). Although several flowering regulatory pathways had been described in some plant species, no study on genetic networks of bolting and flowering regulation was performed in radish. In this study, to generate dataset of radish unigene sequences for large-scale gene discovery and functional pathway identification, a cDNA library from mixed radish leaves at different developmental stages was subjected to high-throughput RNA sequencing (RNA-seq).ResultsA total of 54.64 million clean reads and 111,167 contigs representing 53,642 unigenes were obtained from the radish leaf transcriptome. Among these, 50,385 unigenes were successfully annotated by BLAST searching against the public protein databases. Functional classification and annotation indicated that 42,903 and 15,382 unique sequences were assigned to 55 GO terms and 25 COG categories, respectively. KEGG pathway analysis revealed that 25,973 unigenes were classified into 128 functional pathways, among which 24 candidate genes related to plant circadian rhythm were identified. Moreover, 142 potential bolting and flowering-related genes involved in various flowering pathways were identified. In addition, seven critical bolting and flowering-related genes were isolated and profiled by T-A cloning and RT-qPCR analysis. Finally, a schematic network model of bolting and flowering regulation and pathways was put forward in radish.ConclusionsThis study is the first report on systematic identification of bolting and flowering-related genes based on transcriptome sequencing and assembly in radish. These results could provide a foundation for further investigating bolting and flowering regulatory networks in radish, and facilitate dissecting molecular genetic mechanisms underlying bolting and flowering in Brassicaceae vegetable crops.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2633-2) contains supplementary material, which is available to authorized users.

A Constructional Analysis of Obligatory XVS Syntactic Structures

AbstractThe analysis of obligatory or formulaic XVS structures - as in “Here comes the sun” or “Now is the time to solve our problems” - has been neglected in the literature since it has been argued that there seems to be no linguistic variation involved in the use of these types of syntactic constructions. Here, I defend the view that obligatory XVS structures are productive, highly structured constructions which are worthy of serious linguistic investigation. On the basis of a corpus-based analysis of written and spoken texts, it is argued that the different obligatory XVS types distinguished in the literature are clear instances of constructions as understood in the Construction Grammar framework. Despite their formal and functional dissimilarities, the article shows that these XVS structures still relate to one another in systematic and predictable ways, and are in fact grouped in relation to a unit in the schematic network which is naturally most salient - the prototype - and form with it a family of nodes which are extensions from the prototype - in the system. In sum, the analysis here will show that obligatory XVS structures are constructions which form an interconnected, structured system or network and are best understood with reference to different forms of inheritance.

General Principles for Automated Generation of Schematic Network Maps

Usually, a street map contains various types of detailed information and appears to be crowded. As a result, to many users, a street map looks complicated and is not easy to read and follow. In fact, to a certain degree, too much detail makes the map uninformative and noisy. The London tube map, called a schematic or topological map in some literature, has often been cited as an excellent example of a simplified map. Algorithms have been developed by researchers to automate the generation of schematic maps for road networks. However, it is found that there is still a lack of defined general principles and here four general principles have been formulated for schematisation – the Principle of the Preservation of the Topological Relationship; the Principle of the Preservation of the Main Structure of the Line Network; the Principle of Relativity in Position; and the Principle of Relativity in Length. The first two are the principles of preservation: these two should never be violated. The last two are principles of relativity: it is very desirable to keep these two intact unless there is an absolute need to violate them.

General Principles for Automated Generation of Schematic Network Maps

General Principles for Automated Generation of Schematic Network Maps