bluuebunny/crossref_metadata_2025 huggingface dataset:
Green Audit for the Environmental Sustainability
Authors: Ganga G.
Published: February 2019

Green Audit works as an environmental consultancy and reviews organizations with the aim of monitoring the performance of companies and organizations whose activities might threaten the environment and the health of citizens. Green Audit is to give citizens the information they need to be able to question when an institute or organization is destroying the environment which we all depend on. Most of the public and private organizations do not have suitable strategies to inspect or suggest the control measures be taken to avoid or reduce such environmental risk, which provided the impetus for the establishment of Green Audit. Green Audit undertakes and supports independent studies in the general areas of environmental public health, pollution, energy efficiency, and social and policy research in relevant areas. It has become increasingly clear that the scientific measurement and appraisal of human health risks, including pollution, are in the hands of the government and establishment-controlled organizations.
Green Public Procurement as a Leverage for Sustainable Development
Authors: Litardi Irene , Fiorani Gloria , Alimonti Daniele , Appolloni Andrea
Published: February 2019

The chapter aims to highlight the advantages of GPP practices to address the environmental and economic problems, laying on the experiences of the European countries. The research has the objective to reconstruct the state of the art of green public procurement through the lens of a cross-country comparative analysis at European level. After introducing a systematic review of the literature and the core regulations of the GPP practice, the chapter underlines the results of a multidimensional analysis on a cluster of 80 GPP practices (sample updated to February 2014), identified in European Union and implemented by governments in 25 countries at central, regional, and local government level. The framework of analysis builds on several dimensions, mapping the main results on the following levels: geographic origin, the government level, GPP implementation period, main criteria for implementation, as well as environmental and economic impact of such practices.
Ethics in Research and Teaching
Authors: Celikdemir Deniz Zaptcioglu
Published: February 2019

The chapter aims to explain the importance of ethics in research and teaching. First, it focuses on ethical studies. It expresses the implications that are necessary for a study to be ethical. The researcher has a vital role in conducting an ethical research. There are some critical points, which the researcher should take into account. For each field, various research methods are used. Therefore, different ethical codes and implications should be adapted in accordance with the research method in order to have ethical studies. In addition to research ethics, researchers also have a responsibility as an author to share his/her research with others by publishing it. Unethical behaviors such as fabrication, falsification, plagiarism will be explained. Lastly, a lecturer is responsible for giving lectures, teaching, and assessing the students. For a lecturer to assess its students fairly, s/he should be ethical. The lecturer should provide ethics in teaching.
Capital Budgeting and Public Investment Projects in Ukraine
Authors: Krupa Olha
Published: February 2019

This chapter discusses the budget process for public capital investments in Ukraine, presents controversies in the current process, and offers several avenues for improvement. In doing so, the author provides a description of the country's normative capital public budgeting framework, presents the institutional setup, and tracks Ukraine's public capital expenditure trends for nearly three decades (1991-2016). The study then discusses implementation, audit, and performance issues in Ukraine's public capital expenditure management and provides recommendations. Because of the country's limited fiscal capacity as compared to its massive infrastructure needs, the author posits that Ukraine can no longer afford to delay or ignore its most pressing public capital investment needs. Because the current list of capital investment proposals is underfunded and too long, the author suggests that the government focuses on finishing strategic, high-priority public projects, while other capital spending proposals target private sector financing once it becomes more readily available.
Public Capital Budgeting and Management Process in Russia
Authors: Ermasova Natalia B. , Ermasova Polina
Published: February 2019

This chapter provides a case study from Russia regarding public capital budgeting and management at the federal, state, and local levels. This chapter presents an analysis of four main components of Russian capital budgeting system including (1) long-term public capital planning, (2) annual public budgeting and financing, (3) project execution, and (4) public infrastructure evaluation. This research explains the general challenges of capital budgeting process after the several decades of financial and budget reforms. This chapter presents the structure and classification of the capital budget as well as recent trends in capital expenditure levels in Russia. The authors review the capital resource allocations across sectors based on investment needs and national priorities in Russia. The chapter explains public investment management processes and presents recommendations to improve the efficiency of public capital budgeting in Russia.
Current Studies Based on the Investigation of the Attitudes Towards the Internet in Higher Education
Authors: Mata Liliana
Published: February 2019

The aim of the chapter is to analyze the most recent studies on attitudes towards the internet in higher education. In recent years, there have been studies that focus on investigating the attitudes of students and teachers towards the use of internet in higher education. Thematic content analysis was used to investigate the studies conducted in the period 1998-2018 to measure the attitudes towards the internet. The thematic content analysis of the studies determined establishing the following three categories: 1) studies focused on investigating attitudes towards the implications of internet use; 2) studies based on identifying the relationship between attitudes towards the Internet and different variables; 3) studies centered on exploring attitudes of different members of higher education. The analysis of studies over the last 20 years contributes to determine the action directions for initiating new studies in this field.
Indigenous Languages Learning Through Serious Games Based on Second Language Acquisition Theories
Authors: Sánchez-Acevedo Miguel A.
Published: February 2019

When new educational games are developed for teaching languages, a set of ideas or intuitions about how students can gain more knowledge are used; however, few of them are based on a solid theory or substantiated with linguistic research. This chapter presents a brief review about second language acquisition theories; describes the importance of recovering, maintaining, and transmitting indigenous languages; and analyzes efforts made for enhancing bilingual education. Serious games are presented as an alternative for learning indigenous languages, and guidelines to develop serious games implementing second language acquisition theories are proposed. Finally, a discussion about challenges and future trends in recovering, maintaining, and transmitting indigenous languages is presented.
Temporal Asynchrony of Socio-Technical Devices in Distance Learning?
Authors: Inghilterra Xavier
Published: February 2019

This chapter is based on a research that has been focusing on social sharing device effects and on students' practices of collaboration, communication, and mediation. The author has analyzed the recurring temporal split between academic environment and students' sphere in a context of distance learning. The goal is to understand the origin of the collaborative process of collective apprentice which is illustrated in the communities of apprenticeship outside the academic institution. A netnographic observation was conducted with Bachelor and Master's degrees in a private training center. The author assumes the information and communication socio-technical devices participate in the horizontalization of student practices. The author has highlighted the paradox of these learning communities, which are, unwittingly, in a process of social domination by having choosing a priori a decentralized structure. In light of the social criticism of the time, the observation reveals that digital technologies cause a temporal acceleration.
Higher Education and Web 2.0
Authors: Isaias Pedro , Miranda Paula , Pífano Sara
Published: February 2019

The abundance of evidence of Web 2.0's value in educational settings has provided both educators and researchers with prized information about the application of a panoply of technologies. The experience that this evidence portrays can be used to meaningfully direct teachers in their own ventures of Web 2.0 implementation. In online learning environments, any collaboration between the students must occur with the support of technology, so it is fundamental that technology functions as an enabler, maximizing the opportunities that online settings offer, and that students can tap into those technologies to enhance their learning experience. This chapter focuses on the implementation of Web 2.0 within higher education from the viewpoint of e-learning experts. It reports on the findings of on online questionnaire that examined both the barriers and the best practices of implementation and that was applied internationally among researchers and teachers in the higher education sector.
E-Learning Strategies for Emerging Economies in the Knowledge Era
Authors: Baporikar Neeta
Published: February 2019

With the coming of the digital age over a period of the last three decades, the letter “e” is used to refer to the electronic world. Formerly known as computer-based training, e-learning has also come of age and is increasingly oriented to real-time learning, that is, activities facilitating simultaneous interaction between learners and instructors. Further, the knowledge explosion makes it more a necessity than a luxury even for emerging economies to consider the e-learning platforms and adopt e-learning strategies. The objectives of this chapter are to understand the essentials of effective e-learning strategies and identify the barriers and facilitators in embedding e-learning for emerging economies so as to align well in this knowledge era. The methodology adopted is in depth literature review and grounded theory approach. Contextual analysis and is restricted to effectiveness of e-learning from an emerging economy point of view.
Recent Molecular Approaches for Development of Value-Added Products From Lignocellulosic Food Waste
Authors: Mulla Javed Abdulsalam
Published: February 2019

The escalating global population has led to an ever-increasing demand for food processing industries, and as a result, the generation of huge amounts of food waste. The severity of this problem is augmented due to dawdling development of effective waste treatment and disposal strategies. In a quest of potential alternative bioenergy resources, lignocellulose is proven to be a good, abundantly available raw material on the land as a leftover of agricultural and industrial byproduct made up cellulose, hemicelluloses, and lignin. It is mostly utilized for biofuels, bio-ethanol production, and other value-added products. The development of the conversion of lignocellulosic biomass to fine chemicals still remains a big challenge. The deciphering molecular mechanism and effective cellulase and hemicellulases producing microorganisms might successfully be accomplished with transcriptome, proteome, and recombinant DNA technology; these are discussed in this chapter.
Fermented Foods and Their Production
Authors: Thorat Suresh Sopanrao
Published: February 2019

Fermented foods have been produced throughout recorded history. Recently, fermented foods have experienced renewed interest stemming from concerns with nutrition and the increase in vegetarian and natural foods diets. This chapter explores fermented foods and their production.
Recent Insight Into Fermented Foods and Production
Authors: Bhalani Dixit V. , Chandel Arvind Kumar Singh , Thakur Poonam Singh
Published: February 2019

The fermented beverages and foods either of plant or animal source play a vital role in the food of society in several parts of the world. The fermented of foods not only afford vital sources of nutrients but also have abundant potential in maintaining health and also preventing various diseases. The bacteria and yeasts are the major groups of microorganisms related to traditional fermented of the foods. Numerous diverse types of traditional fermented beverages and foods are formed at domestic level in the various countries. The advancement of fermentation technology provides value addition to waste food by their complete conversion into the different value-added products. The recent research suggests that the biological functions of fermented foods affect the health due to functional microbes involved during fermentation which provides several health-promoting benefits to the consumers. The emphasis of this chapter is to describe the fermentation technology and their potential to minimize the wastage of foods by conversion of value-added products and their benefits.
Utilization and Management of Food Waste
Authors: Naikare Shriram M.
Published: February 2019

The food industry generates a huge amount of waste annually around the globe from a variety of sources. Approximately one third of all food produced today goes to landfill as waste. The food waste is not only a humanitarian problem, but also a serious economic and environmental pollution problem. The global volume of food wastage has been reported to around 1.3bn tones worth to about $165 bn. In India, about 40% of the food produced is wasted, which is estimated to about Rs. 50,000 crores worth every year. The important types of food wastes generated are agricultural residue, processed food, fruit and vegetable processing, marine food, dairy processing, meat and poultry, hotel and restaurant, etc. The food industrial waste can be converted into byproducts mainly based on the processing of fruits and vegetables and allied food manufacturing, supply and distribution, livestock feed, using it as source of bioactive compounds, useful bioenergy production, artificial fertilizer and decomposed manure, a variety of chemicals, antioxidant, nutraceuticals, etc.
Together We Will Reduce the Food Loss
Authors: Raju Celin Tennis , Mariyatra Mahimaidoss Baby
Published: February 2019

In September 2015, the United Nations General Assembly adopted a set of 17 Sustainable Development Goals (SDGs), which include Target 12.3's call for halving food waste and reducing food losses worldwide by 2030. One-third of all food produced each year in the world is never eaten, while at the same time nearly 800 million people go hungry. This situation urges us to take immediate resolutions and steps towards reduction of food waste and food loss. This cannot be done by one person or overnight. This requires systematic analysis in various layers and collective and appropriate effort. This target can be achieved altogether by various sectors including government organizations; non-government organizations; and private companies in collaboration with schools; colleges; universities; research institutes; religion-based organizations such as temples, churches, etc.; and charity-based organizations. This book chapter will discuss the various steps that can possibly be adopted and implemented to address the serious issue of reduction of food waste and food loss.
The Future of Digital Game-Based Learning (DGBL) in Shaping Intercultural Communication Competency
Authors: Yousof Ahmed Karam , Abousamra Nahla
Published: February 2019

Although intercultural communication has long been a vital issue, accelerating globalization and immigration over the past century have increased its importance. Therefore, it is imperative that education and training in intercultural communication are created and continually evaluated for effectiveness. One operative new strategy is the use of digital game-based learning (DGBL) in intercultural communication training. This chapter aims at explaining—from theoretical and practical perspectives—the effectiveness of DGBL to enhance intercultural communication skills. The chapter expounds on the effectiveness of utilizing DGBL as a pedagogical tool in education and training. It then concludes with demonstrating the research results of using HERO I® as an example of the effectiveness of DGBL for cultural competency training. This interconnectedness between theory and practice projects the future of DGBL in shaping intercultural communication competency.
Cultural Landscape
Authors: Uzun Funda Varnaci , Somuncu Mehmet
Published: February 2019

The “cultural landscape” has been a fundamental concept in geography and was first defined as “landscape modified by human activity” by the German geographer Friedrich Ratzel in 1890. It was introduced to American geography in the 1920s by Carl O. Sauer (American geographer). Since the 1960s, the concept has been widely used in human geography, anthropology, environmental management, and other related fields. One of the major factors that contributed to the recent popularity of its use, on a global scale, was the adoption of cultural landscapes in the International Convention for the World Heritage Convention by the United Nations Educational, Scientific, and Cultural Organization (UNESCO) in 1992. In this chapter, the basis of this concept, its emergence, and its relationships with other scientific disciplines, particularly geography, will be discussed. Moreover, the place of cultural landscapes within protected areas and UNESCO world heritage sites will be more specifically addressed.
Semantic Web and Geospatial Unique Features Based Geospatial Data Integration
Authors: Zhang Ying , Li Chaopeng , Chen Na , Liu Shaowen , Du Liming , Wang Zhuxiao , Ma Miaomiao
Published: February 2019

Since large amount of geospatial data are produced by various sources and stored in incompatible formats, geospatial data integration is difficult because of the shortage of semantics. Despite standardised data format and data access protocols, such as Web Feature Service (WFS), can enable end-users with access to heterogeneous data stored in different formats from various sources, it is still time-consuming and ineffective due to the lack of semantics. To solve this problem, a prototype to implement the geospatial data integration is proposed by addressing the following four problems, i.e., geospatial data retrieving, modeling, linking and integrating. First, we provide a uniform integration paradigm for users to retrieve geospatial data. Then, we align the retrieved geospatial data in the modeling process to eliminate heterogeneity with the help of Karma. Our main contribution focuses on addressing the third problem. Previous work has been done by defining a set of semantic rules for performing the linking process. However, the geospatial data has some specific geospatial relationships, which is significant for linking but cannot be solved by the Semantic Web techniques directly. We take advantage of such unique features about geospatial data to implement the linking process. In addition, the previous work will meet a complicated problem when the geospatial data sources are in different languages. In contrast, our proposed linking algorithms are endowed with translation function, which can save the translating cost among all the geospatial sources with different languages. Finally, the geospatial data is integrated by eliminating data redundancy and combining the complementary properties from the linked records. We mainly adopt four kinds of geospatial data sources, namely, OpenStreetMap(OSM), Wikmapia, USGS and EPA, to evaluate the performance of the proposed approach. The experimental results illustrate that the proposed linking method can get high performance in generating the matched candidate record pairs in terms of Reduction Ratio(RR), Pairs Completeness(PC), Pairs Quality(PQ) and F-score. The integrating results denote that each data source can get much Complementary Completeness(CC) and Increased Completeness(IC).
CloudGanga
Authors: Barik Rabindra K.
Published: February 2019

The present research paper proposes and develops a Cloud computing based Spatial Data Infrastructure (SDI) Model named as CloudGanga for sharing, analysis and processing of geospatial data particularly in River Ganga Basin management in India. The main purpose of the CloudGanga is to integrate all the geospatial information such as dam location, well location, irrigation project, hydro power project, canal network and central Water Commission gauge stations locations related to River Ganga. CloudGanga can help the decision maker/ planner or common users to get enough information for their further research and studies. The open source software (Quantum GIS) has been used for the development of geospatial database. QGIS Plugin has been linked with Quantum GIS for invoking cloud computing environment. It has also discussed about the various overlay analysis in CloudGanga environment. In the present research, machine learning approaches are also used in a R tool for well locations which are associated with the basin of River Ganga.
A Practical UAV Remote Sensing Methodology to Generate Multispectral Orthophotos for Vineyards
Authors: Mathews Adam J.
Published: February 2019

This paper explores the use of compact digital cameras to remotely estimate spectral reflectance based on unmanned aerial vehicle imagery. Two digital cameras, one unaltered and one altered, were used to collect four bands of spectral information (blue, green, red, and near-infrared [NIR]). The altered camera had its internal hot mirror removed to allow the sensor to be additionally sensitive to NIR. Through on-ground experimentation with spectral targets and a spectroradiometer, the sensitivity and abilities of the cameras were observed. This information along with on-site collected spectral data were used to aid in converting aerial imagery digital numbers to estimates of scaled surface reflectance using the empirical line method. The resulting images were used to create spectrally-consistent orthophotomosaics of a vineyard study site. Individual bands were subsequently validated with in situ spectroradiometer data. Results show that red and NIR bands exhibited the best fit (R2: 0.78 for red; 0.57 for NIR).
Integrated Multi-Scalar Approach for 3D Cultural Heritage Acquisitions
Authors: Russo Michele , Manferdini Anna Maria
Published: February 2019

This contribution presents the results of investigations on the reliability of techniques based on the Structure from Motion approach used for 3D digitizations of build heritage. In particular, we tested the performances of different SfM technologies within an architectural survey context and we developed a procedure with the purpose of easing the work of surveyors called to restore digital representations of artifacts at different scales of complexity. The restored 3D models were compared among each other and with a gold standard acquisition. These analysis led to qualitative and quantitative evaluations and to considerations on times and skills required by all tested technologies. In this work strengths and weaknesses are highlighted and the integration of different technologies is presented, as it represents the best solution in many and recurrent multi-scalar contexts.
A Large Margin Learning Method for Matching Images of Natural Objects With Different Dimensions
Authors: Zhou Haoyi , Zhou Jun , Yang Haichuan , Yan Cheng , Bai Xiao , Liu Yunlu
Published: February 2019

Imaging devices are of increasing use in environmental research requiring an urgent need to deal with such issues as image data, feature matching over different dimensions. Among them, matching hyperspectral image with other types of images is challenging due to the high dimensional nature of hyperspectral data. This chapter addresses this problem by investigating structured support vector machines to construct and learn a graph-based model for each type of image. The graph model incorporates both low-level features and stable correspondences within images. The inherent characteristics are depicted by using a graph matching algorithm on extracted weighted graph models. The effectiveness of this method is demonstrated through experiments on matching hyperspectral images to RGB images, and hyperspectral images with different dimensions on images of natural objects.
Assessment of the Contribution of Crowd Sourced Data to Post-Earthquake Building Damage Detection
Authors: Hassanzadeh Reza , Nedovic-Budic Zorica
Published: February 2019

This paper compares the results of building damage detection based on Crowd Sourced (CS) data, image processing of remotely sensed (RS) data and predictive modelling with institutional spatial data (Spatial Data Infrastructure - SDI). In particular, it focuses on the contribution of Crowd Sourcing to detecting post-earthquake building damages, while also considering the integration of Crowd Sourced with two other data sources (RS and modelling). To simulate CS data submission following the 2003 earthquake in Bam City (Iran) a survey was administered to the population which experienced the earthquake. The results obtained from this and two other sources are compared with the Actual Earthquake (AE) data by cross-tabulation analysis and McNemar's Chi Square Test. When assessed against AE data, the average accuracy levels of assessments based on the use of RS data and CS data integrated with each RS data and predictive modelling and with both, show a statistically significant increase relative to the predictive modelling. While this research does not provide for a full assessment of the value of CS data alone and in fact finds it slightly inferior to predictive modelling, it suggests that Crowd Sourcing could be a useful source of information, especially if combined with other sources.
Characterization of Fire Regime Descriptors in Botswana Using Remotely Sensed Data
Authors: Molefe John Isaac
Published: February 2019

Despite its role and relevance in environmental management at all scales the use of fire has been contentious. The absence of information on fire parameters compounds the situation. This study derives fire parameter information for Botswana by analyzing MODIS fire data for (2001-2012), using conditional statements, and cluster mapping in ArcGIS. The study also related the fire information to other variables to examine how they interact with fire. The results of the study indicates that over the 12 year period the burned area has exhibited an upward trend. It has also shown that most of the fire in the country occur over the late dry season when the fires are potentially destructive. A south-north transect of fire frequency is observed, accompanied by an inverse relationship between frequency and intensity. Of all the factors, rainfall (0.638) and biomass(NDVI) (0.355) were the most significant contributors to the fire activity. The study demonstrated the utility of the MODIS fire data in characterizing the fire regime of the country and thus contribute to the policy process.
The Use of Social Media for Urban Planning
Authors: Neuhaus Fabian
Published: February 2019

User data created in the digital context has increasingly been of interest to analysis and spatial analysis in particular. Large scale computer user management systems such as digital ticketing and social networking are creating vast amount of data. Such data systems can contain information generated by potentially millions of individuals. This kind of data has been termed big data. The analysis of big data can in its spatial but also in a temporal and social nature be of much interest for analysis in the context of cities and urban areas. This chapter discusses this potential along with a selection of sample work and an in-depth case study. Hereby the focus is mainly on the use and employment of insight gained from social media data, especially the Twitter platform, in regards to cities and urban environments. The first part of the chapter discusses a range of examples that make use of big data and the mapping of digital social network data. The second part discusses the way the data is collected and processed. An important section is dedicated to the aspects of ethical considerations. A summary and an outlook are discussed at the end.
Water Quality Mapping of Yamuna River Stretch Passing Through Delhi State Using High Resolution Geoeye-2 Imagery
Authors: Said Saif , Hussain Athar , Sharma Garima
Published: February 2019

The present article utilizes high resolution Geoeye 2 imagery for mapping and monitoring pollution concentrations of 22 km stretch of river Yamuna passing through Delhi state, by developing regression models between water quality parameters (WQP's) and the corresponding spectral reflectance values. Water samples collected from the sampling locations were analysed for 20 WQP's and grouped into four classes namely; (WQP)organic, (WQP)inorganic, (WQP)anion and (WQP)cation. Several spectral band combinations as well as single bands were probed for performing multiple linear regression (MLR) analysis with the four WQP classes. Results reveal relatively strong positive correlations for band combination viz. [mean RGB × √B/R] with all four WQP classes yielding high R2 value (∼0.85) and RMSE (∼1.03) amongst other selected band combinations. Spatial distribution maps were generated that substantiates to the actual in-situ pollution concentration levels thereby evidences the potential of high resolution Geoeye-2 imagery for monitoring and mapping pollution concentrations in the water bodies.
Geospatial Mashups in Web GIS for Tourism Infrastructure
Authors: Chaudhuri Somnath , Ray Nilanjan
Published: February 2019

A Mashup is the process of merging multiple sources of data, both spatial and non-spatial, into a single integrated spatial display. It is about extracting spatial data from a non-spatial source and combining with other spatial data and finally displaying it on a map. Mashups can potentially combine any type of contents and functions over the web, regardless of whether a formal interface of programming is available (Fu et al., 2011). The present study discusses the basic architecture of the Geospatial Mashups in Web GIS and its application in tourism promotion.
Environmental Object Recognition in a Natural Image
Authors: Aryal Jagannath , Josselin Didier
Published: February 2019

Natural images, which are filled with intriguing stimuli of spatial objects, represent our cognition and are rich in spatial information. Accurate extraction of spatial objects is challenging due to the associated spatial and spectral complexities in object recognition. In this paper, the authors tackle the problem of spatial object extraction in a GEOgraphic Object Based Image Analysis framework taking psychological and mathematical complexities into account. In doing so, the authors experimented with human and GEOBIA based recognition and segmentation in an image of an area of natural importance, the Ventoux Mountain, France. Focus was given to scales, color, and texture properties at multiple levels in delineating the candidate spatial objects from the natural image. Such objects along with the original image were provided to the human subjects in two stages and three different groups of samples. The results of two stages were collated and analyzed. The analysis showed that there exist different ways to comprehend the geographical objects according to priori knowledge.
Application of Data Fusion for Uncertainty and Sensitivity Analysis of Water Quality in the Shenandoah River
Authors: Mbuh Mbongowo Joseph
Published: February 2019

This article is aimed at demonstrating the feasibility of combining water quality observations with modeling using data fusion techniques for efficient nutrients monitoring in the Shenandoah River (SR). It explores the hypothesis; “Sensitivity and uncertainty from water quality modeling and field observation can be improved through data fusion for a better prediction of water quality.” It models water quality using water quality simulation programs and combines the results with field observation, using a Kalman filter (KF). The results show that the analysis can be improved by using more observations in watersheds where minor variations to the analysis result in large differences in the subsequent forecast. Analyses also show that while data fusion was an invaluable tool to reduce uncertainty, an improvement in the temporal scales would also enhance results and reduce uncertainty. To examine how changes in the field observation affects the final KF analysis, the fusion and lab analysis cross-validation showed some improvement in the results with a very high coefficient of determination.
Cloud-Based Geo-Information Infrastructure to Support Agriculture Activity Monitoring
Authors: Akhter Shamim , Aida Kento
Published: February 2019

Agriculture activity monitoring needs to deal with large amount of data originated from various organizations (weather station, agriculture repositories, field management, farm management, universities, etc.) and mass people. Therefore, a scalable environment with flexible information access, easy communication and real time collaboration from all types of computing devices, including mobile handheld devices as smart phones, PDAs and iPads, Geo-sensor devices, and etc. are essential. It is mandatory that the system must be accessible, scalable, and transparent from location, migration and resources. In addition, the framework should support modern information retrieval and management systems, unstructured information to structured information processing (IBM Info Stream, text analytic, pig & hive, etc.), task prioritization, task distribution (Hadoop), workflow and task scheduling system, processing power and data storage (Amazon S3 and Google BigTable). Thus, High Scalability Computing (HSC) or Cloud based system can be a prominent and convincing solution for this circumstance.
The Fundamentals and Applications of Geo-Spatial Research
Authors: Maphanyane Joyce Gosata , Mapeo Read Brown Mthanganyika , Akinola Modupe O.
Published: February 2019

This chapter is about the fundamentals of geo-spatial research. The Earth's make-up and position in the entirety of the universe and its systems thereof is revealed. It also categorizes the Earth movements into types, causative effects, and their measurable, predictable time beat. It resonates together with Chapter 2 to form a bigger picture. The scenario draws out whole complete discussions of geoscience study on the origins of matter, space, time and energy entities. The revelations of what is known about the Cosmos today and therefore the Universe is the painstaking work of several scientists. This knowledge is fundamental to all Geo-spatial science research. For one to successfully carry out the research of this nature, it is imperative that one is fully conversant with how the Universe and therefore the Earth and its systems function. The discussions also include a map as a reporting platform for processes of the geospatial science research.
When Competitive Intelligence Meets Geospatial Intelligence
Authors: Othenin-Girard Christophe , Guillemette Manon G. , Foley Eric , Caron Claude
Published: February 2019

Given current economic uncertainties, organizations need to efficiently generate new knowledge and incorporate it into their products and services. In this regard, competitive intelligence provides such strategic knowledge to support the creation of competitive advantages. Part of the knowledge created by competitive intelligence concerns the geographical components forming the basis of geospatial analysis. This study sought to identify, among some 40 competitive analytical methods, those that may be enhanced by geospatial intelligence capabilities. To this end, the authors identified the key subject area of each competitive analytical method and the key spatial analysis operations with geospatial intelligence capability, and then they identified those with a strong potential for providing more strategic knowledge when used in combination. They provide various case scenarios to support their propositions. The results demonstrate that geospatial intelligence may leverage competitive intelligence by more efficiently highlighting business opportunities.
Screen Time, Temporality, and (Dis)embodiment
Authors: Santos Eduardo J. , Bannell Ralph Ings , Leporace Camila De Paoli
Published: February 2019

In this chapter, the authors will attempt to answer two related questions: How is our cognitive experience with time enacted and extended? Has the cognitive dimension of the experience of time lost its reference in the body? The background reviews relevant literature and shows the motivation for the main discussion of the chapter, especially the contrast between the authors' approach and the traditional symbolic-representational view. The principal argument will be that the dimension of the organism's coupling with the environment that can be called engagement with material culture—or things—has been undertheorized in the literature. Bringing this dimension into the analysis can, the authors argue, help explain how we experience psychological time. What's more, it can help understand the kinds of extra-bodily extensions that might explain why the use of technologies does not threaten disembodiment.
Time Orientation and Media Use
Authors: Barbosa Cláudia , Pedro Luís
Published: February 2019

Digital consumer devices have penetrated our everyday lives, providing a platform to—with great efficiency and easiness—solve problems, communicate and exchange information, participate in remote activities, and even socialize. This increasing popularity provides the impetus for a rising dependency, which translates into a growing number of hours spent with the various types of media available. However, while the time we dedicate to media increases (at the cost of other activities), the number of hours that we have available (per day, per week, per month, etc.) cannot, giving rise to media multitasking behaviors. Some studies suggest that time orientation—either as a cultural construct or an individual preference—can influence one's media use habits, predicting (or not) multiple media use. There are, however, other perspectives suggesting that media use can actually affect one's time orientation. This chapter will attempt to assess both of these outlooks.
A Critical Review of Social Screen Time Management by Youngsters in Formal Educational Contexts
Authors: Varsori Enrickson , Pereira Sara
Published: February 2019

Several studies value the importance of technologies in everyday social processes, stressing loudly its positive effects for time control and management. However, the use of digital technology is increasingly said to co-produce the ways youngsters experience daily lives, as these are increasingly weaved in media hyperconnections, in several insidious and multiple forms, and in a continuous and enduring manner. This text focuses on the state of the art about the extension and nature of these co-productive processes, highlighting the effects of the technological means of communication on youngster's time representations and experiences, namely considering the social networks and other interactional devices that are now constituting increasingly more the individual identity, despite its intangibleness. The goal is to critically analyze the existing literature on time, technology, and youth, presenting its main contributions from a conceptual, methodological and practical point of view, including the use and the ways in media hyperconnections.
Prediction of Heart Diseases Using Data Mining Techniques
Authors: Masih Nancy , Ahuja Sachin
Published: February 2019

Health care organizations accumulate large amount of healthcare data, but it is not ‘extracted' to draw hidden patterns which can prove efficient for the decision making process. Data mining techniques can be used to gain insights by discovering hidden patterns which remain undetected manually. Data analytics proves to be useful in detection and identification of the diseases. A complete analysis has been conducted on the FHS (Framingham Heart Study) using various data analytic techniques viz. Decision tree, Naïve Bayes, Support vector machine (SVM) and Artificial neural network (ANN) and the results were ranked according to the accuracy. ANN produce better results than other classification algorithms. The output helps to find out the prominent features that cause heart disease and also identifies the most common features that must be analyzed for prediction of deaths due to heart disease. Despite various studies carried out on heart diseases, the main focus of this study is prediction of heart disease on the dataset of FHS by using various classification algorithms to achieve high accuracy.
Classification and Space Cluster for Visualizing GeoInformation
Authors: Osaragi Toshihiro
Published: February 2019

It is necessary to classify numerical values of spatial data when representing them on a map so that, visually, it can be as clearly understood as possible. Inevitably some loss of information from the original data occurs in the process of this classification. A gate loss of information might lead to a misunderstanding of the nature of original data. At the same time, when we understand the spatial distribution of attribute values, forming spatial clusters is regarded as an effective means, in which values can be regarded as statistically equivalent and distribute continuous in the same patches. In this study, a classification method for organizing spatial data is proposed, in which any loss of information is minimized. Also, a spatial clustering method based on Akaike's Information Criterion is proposed. Some numerical examples of their applications are shown using actual spatial data for the Tokyo metropolitan area.
Anomaly Region Detection Based on DMST
Authors: Zhang Sulan , Wan Jiaqiang
Published: February 2019

Anomaly region detection aims at finding spatial outliers or spatial anomalous clusters. Generally, detection approaches cover spatial neighbor's discovery with spatial attributes and anomaly measurement of spatial regions according to non-spatial attributes. In this article, an anomaly region detection method using Delaunay minimal spanning tree (DMST for short) is proposed. First, a Delaunay minimal spanning tree is constructed. Then, the current longest edge of the tree is iteratively cut and anomaly regions are concurrently detected. Finally, the shortest edge of the related bipartite graph is taken as the anomaly measurement. The proposed method could avoid the disturbance of bad reference neighbors and generate anomaly regions keeping atomicity.
Language-Independent Type Inference of the Instances from Multilingual Wikipedia
Authors: Wu Tianxing , Qi Guilin , Luo Bin , Zhang Lei , Wang Haofen
Published: February 2019

Extracting knowledge from Wikipedia has attracted much attention in recent ten years. One of the most valuable kinds of knowledge is type information, which refers to the axioms stating that an instance is of a certain type. Current approaches for inferring the types of instances from Wikipedia mainly rely on some language-specific rules. Since these rules cannot catch the semantic associations between instances and classes (i.e. candidate types), it may lead to mistakes and omissions in the process of type inference. The authors propose a new approach leveraging attributes to perform language-independent type inference of the instances from Wikipedia. The proposed approach is applied to the whole English and Chinese Wikipedia, which results in the first version of MulType (Multilingual Type Information), a knowledge base describing the types of instances from multilingual Wikipedia. Experimental results show that not only the proposed approach outperforms the state-of-the-art comparison methods, but also MulType contains lots of new and high-quality type information.
Tourism Marketing Platform on Mobile Internet
Authors: Xiao Yunhua
Published: February 2019

With the progress of science and technology, the development and improvement of internet technology and smart phones are gradually popular in the daily life; this world has achieved a swift transition to the mobile internet era from the traditional internet era. Various tourist areas have established “Digital Scenic Spots” in recent years, making the internet combine tightly with tourism. The construction of scenic-spot marketing platforms based on internet is an important component of constructing “Digital scenic spot.” In this article, a tourism marketing platform on the mobile internet is established by analyzing the mobile internet mainstream technology and its application in tourism marketing. In this article, the architecture of the marketing system uses the MVC pattern with a three-tier distributed structure and the logic layer of the system uses a construction of JavaBean and EJB. The article also builds a WeChat marketing model based on MM-TIP. The result of research provides some reference for constructing tourism marketing platform based on mobile internet.
Comparator Synthesis Using Distributed Genetic Algorithm and HSPICE Optimization
Authors: Takai Nobukazu , Suzuki Kento , Sugawara Yoshiki
Published: February 2019

In this paper, we propose an automatic design method that determines comparator topology and satisfies desired specification of the comparator by combining distributed genetic algorithm and HSPICE optimization function.In the comparator synthesis, new topology is created using known circuit topology information.After creating the topology, optimization of element values of the comparator is executed by distributed genetic algorithm and HSPICE optimization.As a target value example, specification of HA163S02 is used.Simulation results indicate that the proposed method can design the comparator despite the number of specifications and elements of circuit increase compared to the conventional methods.Furthermore, the performance of the automatic designed comparator is better than that of conventional comparators.
Noise Filter for Surface Shape Measurement in Digital Holography
Authors: Takahashi Yoshitaka , Shingu Masakazu , Saito Masatoshi , Nakajima Toru , Sekiguchi Ryutaro , Chiba Masataka
Published: February 2019

Phase difference image using phase-shifting digital holography is one of the prospective methods for non-contact shape measurement. For the application, filtering of the obtained image is needed to reduce the speckle noise. Conventional filter, e.g. moving average filter, causes loss of the shape information especially around the region with high steepness. To solve this problem novel filter has been developed that kept steepness of the shape in noise reduction. The filtered data were compared with conventionally filtering ones and the former was closer to the data observed by a laser measuring microscope.
High-Frequency Low-Distortion One-Tone and Two-Tone Signal Generation Using Arbitrary Waveform Generator
Authors: Shibuya Shohei , Yanagida Tomonori , Asami Koji , Kobayashi Haruo
Published: February 2019

This paper describes analysis, simulation and experiment verification of high-frequency one-tone and two-tone low-distortion signal generation methods with an arbitrary waveform generator (AWG) for analog/mixed-signal IC testing. Our previously proposed phase switching method was limited to low-frequency signal generation, and it cannot be used directly for high-frequency signal generation. We propose here a method for generating a low-distortion high-frequency signal (i.e., the frequency close to the Nyquist frequency of the AWG) with an AWG, and show its theoretical analysis and simulation results. With this proposed method, 3rd order harmonics of the generated signal are suppressed simply by changing the AWG program (or waveform memory contents)—AWG nonlinearity identification is not required—and spurious components, generated far from the signal band, are relatively easy to remove using an analog filter.