Semantic Cloud Research Articles

Applying self-supervised learning for semantic cloud segmentation of all-sky images

Abstract. Semantic segmentation of ground-based all-sky images (ASIs) can provide high-resolution cloud coverage information of distinct cloud types, applicable for meteorology-, climatology- and solar-energy-related applications. Since the shape and appearance of clouds is variable, and there is high similarity between cloud types, a clear classification is difficult. Therefore, most state-of-the-art methods focus on the distinction between cloudy and cloud-free pixels without taking into account the cloud type. On the other hand, cloud classification is typically determined separately at the image level, neglecting the cloud's position and only considering the prevailing cloud type. Deep neural networks have proven to be very effective and robust for segmentation tasks; however they require large training datasets to learn complex visual features. In this work, we present a self-supervised learning approach to exploit many more data than in purely supervised training and thus increase the model's performance. In the first step, we use about 300 000 ASIs in two different pretext tasks for pretraining. One of them pursues an image reconstruction approach. The other one is based on the DeepCluster model, an iterative procedure of clustering and classifying the neural network output. In the second step, our model is fine-tuned on a small labeled dataset of 770 ASIs, of which 616 are used for training and 154 for validation. For each of them, a ground truth mask was created that classifies each pixel into clear sky or a low-layer, mid-layer or high-layer cloud. To analyze the effectiveness of self-supervised pretraining, we compare our approach to randomly initialized and pretrained ImageNet weights using the same training and validation sets. Achieving 85.8 % pixel accuracy on average, our best self-supervised model outperforms the conventional approaches of random (78.3 %) and pretrained ImageNet initialization (82.1 %). The benefits become even more evident when regarding precision, recall and intersection over union (IoU) of the respective cloud classes, where the improvement is between 5 and 20 percentage points. Furthermore, we compare the performance of our best model with regards to binary segmentation with a clear-sky library (CSL) from the literature. Our model outperforms the CSL by over 7 percentage points, reaching a pixel accuracy of 95 %.

The need for local adaptation of smart infrastructure for sustainable economic management

At present, there are several growing problems for sustainable urban growth, and the typical policy strategies to tackle them are inadequate. In recent years, several governments have initiated numerous smart city and smart infrastructure programs aimed at enhancing the quality life of the people and helping town managers improve the public infrastructure activity and management. The usage of the Internet of Things (IoT) for infrastructure system enables the gathering, storing, incorporation, and analysis of large quantities and varieties of information relating to the status and output of infrastructure systems together with public activity through Cloud-based asset management systems, mobile apps, and Big Data analytics. In this paper, a master data management (MDM) approach has been proposed to unlock the importance of comprehensive network data for efficient, safe, and robust community development. In the market field, MDM is implemented for the organization of big data organizational and research applications. The proposed method includes an effective MDM solution for safe, efficient, and functional community design, commercial and open source MDM platforms, city development principles, smart city concept models, adaptive shared network backgrounds, semantic cloud technology, and specialists responsible for designing development, scalable platform technology for evaluating the input.

Addressing Semantics Standards for Cloud Portability and Interoperability in Multi Cloud Environment

The increasing demand for cloud computing has shifted business toward a huge demand for cloud services, which offer platform, software, and infrastructure for the day-to-day use of cloud consumers. Numerous new cloud service providers have been introduced to the market with unique features that assist service developers collaborate and migrate services among multiple cloud service providers to address the varying requirements of cloud consumers. Many interfaces and proprietary application programming interfaces (API) are available for migration and collaboration services among cloud providers, but lack standardization efforts. The target of the research work was to summarize the issues involved in semantic cloud portability and interoperability in the multi-cloud environment and define the standardization effort imminently needed for migrating and collaborating services in the multi-cloud environment.

Multilingual Approach to Word Sense Disambiguation Using word2vec and Sense Embedding With Semantic Cloud

Word Sense Disambiguation(WSD) is an open problem in the area of Natural language processing. Many WSD systems uses knowledge based unsupervised approach as it bares us from using tagged corpus. But this approach depends extensively on knowledge. Enhancing the knowledge for ambiguity resolution is one of the important issues in WSD. Although Multilingual lexical resource is an asset for knowledge based systems(KBS), many KBS have not yield satisfactory results due to lack of sufficient information required for disambiguation. Multilingual information can help boost the performance of WSD in various languages. Combining lexical semantic information from different languages helps improve WSD task. We make use of Babel Net, a huge multilingual resource provider to attain the task and design a semantic word cloud to provide high performance disambiguation by imposing additional knowledge.

A Corpus Based Study on Cross Cultural Adaption of Websites of Foreign-Invested Enterprises in Heilongjiang Province

Under the macro-environment of “The Belt and Road Initiative”, Heilongjiang province receives more foreign investment since 2013. This paper endeavors to collect website information of foreign-invested companies in Heilongjiang province and Heilongjiang local companies and build two corresponding corpuses. After analyzing data by using WMATRIX 4 tool, the author selects semantic clouds under the framework of Singh’s website content. Then after comparing data of Heilongjiang local companies and foreign invested companies in Heilongjiang province, the author tries to explain the data from Hofstede’s cultural dimensions, namely, individualism vs. collectivism, power distance, uncertainty avoidance and femininity vs. masculinity. Then suggestions on the website building to adapt to the local culture have been made. The study makes a useful attempt to explore the effectiveness of business communication across disciplines by using linguistic research perspectives and research methods.

Pueblos within Pueblos: Tlaxilacalli Communities in Acolhuacan, Mexico, ca. 1272–1692

Amid a self-similar stream of New Philology text presentations, additional perspectives on struggles initially following first contact, and book-length humanistic essays dealing with currently popular Western preoccupations and purporting, with limited success, to elucidate indigenous categories and cultures, Benjamin Johnson's analysis of the role of tlaxilacalli across four centuries in the eastern Basin of Mexico stands out as original, creative, and inviting of multidisciplinary engagement and collaboration. It serves as an exemplar of the productive use that can be made of certain aspects of the New Philology's output.The Acolhuacan region, heartland of the small precontact empire of modern-day Texcoco, the Aztec second city, offers unmatched density of documentation, as well as archaeological and ethnographic information, for approximately the last millennium. Johnson joins those who have succeeded in assimilating this complexity while identifying important underlying principles within it. The purpose of this attractively produced and heavily footnoted book is threefold. It posits an analytical equivalence between precontact and postcontact imperial structures to illustrate the role of tlaxilacalli in strengthening and vitiating the ruling processes of both regimes. It takes advantage of the detail in Texcocan documentation to tie individuals and households to known landscapes and local-level political processes. And it thereby highlights the role commoners played in the formation, maintenance, and dissolution of imperial structures.Johnson first must disambiguate the indigenous concept tlaxilacalli from the confused colonial semantic cloud of barrio, pueblo, altepemaitl, calpolli, altepetl, and so on—another revealing instance of the continued failure of the intrusive Spanish and their descendants to understand the cultures they confronted. Tlaxilacalli were face-to-face networks administered by commoners that incorporated compulsion and inequality while also offering security and community through rights and obligations involving landholding, kinship, and other affective attachments to specific landscapes. Tlaxilacalli offered submission to immature, developing imperial structures in exchange for a measure of autonomy, leading to policies of indirect rule on a microscale that made both precontact and postcontact imperial structures fractious and fragile.Chapter 1 posits a thirteenth-century origin of tlaxilacalli regimes in the northeastern Basin of Mexico, beginning their characterization by Johnson in terms of landholding, economic, and cultural forces within the larger context of precontact warring states. Chapter 2 studies precontact and first-contact imperial processes through the rapid rise of the Triple Alliance, facilitated by tlaxilacalli recruitment and support, and then the equally rapid redeployment of Texcocan tlaxilacalli in support of Hernando Cortés and invading indigenous groups to facilitate the entry of a new and, at the time, unknowable order. Cuauhtepoztlan, a tlaxilacalli within Tepetlaoztoc, comes under the microscope in the third chapter, in which Johnson, working from the outside in, applies a novel variety of techniques to describe this tlaxilacalli's hierarchical structures and processes, not only in terms of power but also in terms of attachment to community and landscape. The final three chapters further explore these themes across the sixteenth and seventeenth centuries, when tlaxilacalli became the sole refuge for the great majority of commoners—and their means of projecting political power. As the former indigenous elite, never that closely integrated into tlaxilacalli, became detached from their economic support, tlaxilacalli adopted and used new Catholic cultural content to confect new idioms of attachment to landscape and community that also enhanced success in the variably corrupt colonial legal process.Johnson's work thus identifies a durable, adaptive, indigenous concept and its expression in a range of entities of central importance across four centuries. He handles the existing evidence well while also adducing extensive new evidence, implicitly inviting other disciplines to understand tlaxilacalli more thoroughly. Archaeologists may wish to study its applicability to their evidence before and after the twelfth century as well as inside and outside the Basin of Mexico. They may finally be drawn into renewed fieldwork in Tepetlaoztoc by devising methods to work around deep soil disturbance by modern agriculture. Ethnohistorians may take up the challenge of further characterizing the tlaxilacalli's internal economic, political, and affective processes, as well as its exact articulation within imperial regimes. Ethnographers may seek commonalities between what they see on the ground today and prior patterns persisting through many centuries. The latter two groups will advocate for greater understanding of kinship, compadrazgo, succession, inheritance, and landholding within tlaxilacalli.None of these comments are a criticism of this work but rather an assurance of its importance and centrality for future research in indigenous political organization and process across the contact boundary to today. While publications of minute textual examination continue to abound alongside wide-ranging studies of iconography, religion, gender, and other cultural content, this book is a beacon reminding researchers to understand and appreciate, through indigenous categories, the everyday realities, practicalities, choices, and struggles of the people who produced the works they study. The responsibility to understand this basic context remains key to optimizing future scholarly output and rendering it meaningful in worldwide comparative conversations.

Lidar Mapping Optimization Based on Lightweight Semantic Segmentation

Lidar Simultaneous Localization and Mapping (LiDAR-SLAM) algorithm with semantic information is an open research question and it is such a time consuming task. The related work that focus on real-time LiDAR-SLAM has poor accuracy. To solve these problems, a lightweight semantic segmentation network to assist in localization and mapping is proposed in this paper. The method uses the lidar point clouds generated by the simulator and annotated manually in real world as the original input. Then, the semantic cloud is segmented by the semantic segmentation network to obtain the semantic information. Finally, the semantic information obtained by the segmentation is used to assist the localization and mapping.

Humanity and Humanitarianism: An Ambiguous Connection

The article discusses the relationship between the concepts of humanitarianism and humanity, which the author dissociates from each other, also separating them from the concept of humanism. The author believes that these concepts are often confused, they form a “semantic cloud,” intuitively comprehended as integrity and referring us to the image of man as the center of the world and the subject matter of discussion in ethics, aesthetics, psychology as well as philosophy and other “free arts.” However, these concepts need to be distinguished. Humanism represents a conceptual theoretical setting for considering a person as a free, independent and active being, while, in the author’s opinion, humanitarianism is a literary (philosophical and artistic) form of statements about a person. At the same time, humanity is meant as a characteristic of behavior and attitudes that motivate this behavior, such as the motives of kindness, philanthropy, benevolence. The article reveals the main features of humanitarianism and also shows that humanitarian texts are not always texts originating from attitudes of humanity and pursuing humanity. Literary reflection on the subject of a man does not necessarily need kindness and benevolence. The article provides examples of both the coincidence of humanitarianism and humanity and their divergence. The author draws attention to the existence of humanitarian but not humane texts, some of which cannot be attributed as philanthropic and other ones – as optimistic. The author considers it necessary not to confuse closely related concepts, denoting different aspects of human life and culture.

A Tool for Mapping and Editing of Cloud Patterns: the Semantic Cloud Patterns Editor

A Tool for Mapping and Editing of Cloud Patterns: the Semantic Cloud Patterns Editor

Cloud Service Description Model: An Extension of USDL for Cloud Services

There are a variety of well-designed specification-modelling-languages serving Internet services, however, none of them is capable of describing the special features of cloud services, from both technical and business points of view. The Unified Service Description Language (USDL) provides a new way to describe Internet services from business, operational, and technical perspectives. Nevertheless, there are various issues with USDL: it lacks a comprehensive specification model, particularly for cloud services, lacks a user-centric specification modeling paradigm, lacks a mechanism to measure cloud service attributes and to present the association relationship and re-usability of the attributes, and lacks semantic representation of cloud services. Based on the above issues, we propose a unified semantic Cloud Service Description Model (CSDM) in this paper. The proposed model will be extended from the basic structure of USDL, by defining cloud-service-specific attributes. Furthermore, an additional module, named transaction module, will be defined, which models the rating system of cloud services from several aspects, such as risk, trust, and reputation. The transaction module facilitates the capability of CSDM with regard to service ranking, and enhances its flexibility and extensibility by providing an extensible sub-module. In addition, we design an OWL-based annotation system to enrich the semantic expressivity of this model. Finally, a case study is provided to explain the application of this model in actual cloud services.

Multi-agent System for Cloud Manufacturing Process Planning

The fundamental concern of building a distributed Cloud manufacturing (CM) platform is how wide variety of manufacturing services (SaaS, PaaS, HaaS, IaaS) can be integrated under a common cloud platform? More technically, this concern is related to the classical data integration problem, i.e. how to universally map information from heterogeneous data sources. Adoption of CM may become possible if collaborative agents can automatically discover a set of suitable CM services, and invoke them in a particular order to achieve a certain manufacturing task. Cloud computing community suggested semantic web services in order to enable automatic discovery, invocation and orchestration of web services. In this paper, we describe a novel multi-agent framework, where agents are configured based on Belief, Desire, and Intention (BDI) formalism. In this proposed framework, agents are capable of autonomously discovering and orchestrating manufacturing services based on their intrinsic and extrinsic awareness of the manufacturing knowledge at its most contemporary state. The internal structure of agents are constructed by Horn-DL rules, arguing such DL-safe rules will be able to extract and analyze manufacturing knowledge bases, built with OWL-DL. This chapter also introduces a novel method of selecting suitable services, from the intrinsic semantic in Horn-DL rule. This integration of Horn-Dl and semantic cloud services is designed based on a logical extension of Horn-DL.

Metodología de trabajo colaborativo/cooperativo para la investigación, la formación y el aprendizaje en comunicación

Objective. The aim of this article is to systematize the collaborative / cooperative methodology used for research. Analysis of the impact of local socio-communicative discourses in the construction of the concept of Latin American youth identity. Colombia case. This study is based on the work done in 2015 at the Complutense University of Madrid, regarding values and valuations of young Latin American immigrants. In 2016, the methodology was implemented, with some variations, in Colombia and Argentina for the aforementioned research. This article offers a systematization of the methodology derived from the Colombian case.Methodology. This text describes the techniques used to obtain the data and indicates those used in its analysis. Thus, an applicable model is offered as a teaching-learning-research resource in the classroom, specifi­cally for communication and related areas. For the specifi­c study of Colombia, conducted with students of the School of Communication at University of Medellin, data was collected from the work within a research center and qualitative analysis tools such as the Atlas ti and exercises with semantic clouds (Tagxedo) were used for the interpretation.Findings and conclusions. The most relevant results are divided into two aspects. On the one hand, they are related to the advantages found in the application of a model for the teaching-learning-research triad from the perspective of collaborative / cooperative work. On the other hand, a guide is presented that serves as a guide for the development of activities that allow the methodology to be put into practice.

Semantic Cloud Architecture An Integration of Cloud and Semantic Web

In the last few years, the amount of structured data made available on the Web in semantic formats has grown by several orders of magnitude. On one side, the Linked Data effort has made available online hundreds of millions of entity descriptions based on the Resource Description Framework (RDF) in data sets. On the other hand, the Web 2.0 community has increasingly embraced the idea of data portability, and the first efforts have already produced billions of RDF equivalent triples either embedded inside HTML pages using micro formats or exposed directly using eRDF (embedded RDF) and RDFa (RDF attributes). In another side Cloud Computing is offering utility concerned IT services to users worldwide. It enables hosting of applications from consumers, scientific and business domains. The beauty of cloud computing is its simplicity. This paper focuses on the process of transitioning from IT architectures of today to Semantic Cloud Architecture. The emphasis is on collaborative work of business and enterprise architects to reduce operational costs and to achieve heights.

An approach to unified cloud service access, manipulation and dynamic orchestration via semantic cloud service operation specification framework

Cloud computing offers various computational resources via convenient on-demand service provision. Currently, heterogeneous services and cloud resources are usually utilized and managed through diverse service portals. This significantly limits the effectiveness and efficiency for tasks implementation. Fundamentally, it is due to the lack of adequate specifications for service concepts, operations and interfaces from diverse cloud service models and types. This paper proposes a service management operation semantic description framework for comprehensive cloud service operation specification. Relying on ontological modelling techniques, cloud service operations are specified via entity classification, attribute assertion, relationship assertion and annotation assertion. Further, the proposed framework benefits from operation reasoning application. It enables intelligent assistance for multiple operation preparation and remote execution tasks. Based on the approach, a cloud service operation ontology and a unified service access and manipulation system prototype are implemented. Extensive experiments are conducted over different cloud service providers and for distinct service models. Obtained results demonstrate that the approach outperforms existing practices by facilitating reliable and effective service access, manipulation and interaction tasks.

A Novel Semantic Cloud Computing Interoperability Model for Platform as a Service System

Cloud computing is the fastest growing, popular and most widely used technology in the current web. Interoperability is one of the major issues found in cloud environments where it is not an easy go for the cloud consumers to have a direct interaction with the cloud providers in order to request for a service. The semantic web technology is the most powerful growing technology to the current web which allows adding semantic metadata to the cloud services. Addition of Semantic web technologies to the cloud platforms provides scalable and efficient results to the consumers. This paper presents a semantic interoperability model which provides an improved interaction between the cloud Platform as a service provider and the cloud consumers. The semantic interoperability layer that sits between the cloud provider and the user does the semantic description generation of the service which helps in discovering the service and invoking the service with respect to the user’s request. This proposed method is done with the cloud service called Google app engine which is Platform as a service provided by Google and the semantic web technology tool used is JRDF, a framework for RDF and SPARQL Query language.

Peculiarities of Semantic Web-services Cloud Runtime

Abstract This paper is devoted to semantic description of the system that functions in a cloud runtime (like app store) providing business services available on demand (hereinafter, system). Business services are in fact information proceeding units that accept the given parameters and return business data. The described system ensures automatic collaboration between services and grants access to processing resources defined in the business process logic. We describe a business model that allows its users to find solutions of their tasks using published services or their collaborations.

A semantic cloud infrastructure for data-intensive medical research

The European virtual physiological human initiative develops a platform, called VPH-Share, for understanding physiological processes in the human body in terms of anatomical structure and biophysical mechanisms. Besides storing, sharing, integrating and linking a wide variety of heterogeneous bio-medical datasets relevant to the VPH community, the project envisions the facilitation of a secure data infrastructure, as well as search and exploration facilities based on semantic technologies. The data infrastructure and management platform are built on top of a hybrid cloud environment. The data management platform offers tools that cover the whole life-cycle of datasets including integration, selection, semantic annotation and publishing datasets as a service. A comprehensive user interface enables end-users to search and to explore bio-medical data with support of semantic technologies, concealing the complexity of the underlying service environment. In this paper we describe the data infrastructure that has emerged in context of the project.

Research on Semantic Processing for Internet of Things Based on Cloud Computing

Heterogeneous data produced by Internet of Things increased continually. Inconsistent semantics of data became obstacle of sharing data. To handle them effectively and intelligently, a semantic model for Internet of Things was proposed, which was based on semantic technology and cloud computing. Scalable distributed file system was the basis of storing mass data. Distributed inference engine, which was based on Map/Reduce operation model, had solved the problem of reasoning on mass ontology. Hierarchical semantic provided the basis of intelligent processing, which had reached consistent understanding between heterogeneous data. Global ontology laid emphasis on solving interoperation, local ontologies laid emphasis on personalized knowledge.

MTag: A model to enable collaborative medical tagging in medical blogs

Abstract Collaborative tagging is the practice of collaboratively creating and managing tags to annotate and categorize online content. Current collaborative tagging activities within medical blogs are done using free words chosen by users. These tags are not based on standard medical terminologies. The resulted tags are inefficient in terms of medical meanings and semantic interlinking capabilities. In this paper, MTag is presented as a new model for collaborative tagging in medical blogs, i.e. tagging blog entries with medical information. MTag includes two modules: the service module and the semantic module. The service module enables health professionals provide blog posts with auto-completed tags that represent actual medical terms and categorize their tags. Tags are mapped to URIs from online medical knowledge datasets to clarify their medical meaning. At the same time, the semantic module is equipped with a tag ontology which extends the Social Semantic Cloud of Tags (SCOT) ontology to consent medical specifications of tags. Eventually, a prototype is developed to test the MTag’s two modules. The results show that both modules are working properly.

Semantic Cloud for Mobile Technology

paper highlights and outlines the architecture of SCM (Semantic Cloud for Mobile), a blend of two emerging web technologies, semantic web and cloud computing, for revolutionizing data access and processing capabilities over mobile platform. The emphasis lies on decoupling of data processing and management from mobile hardware, alongwith the way SCM can be employed to resolve issues that have persisted over years, and exploring new opportunities that SCM may promise to offer.