bluuebunny/crossref_metadata_2025 huggingface dataset:
A Laboratory for Creativity
Authors: Barbour Neal , Eason Becky
Published: February 2020

This chapter explores how design thinking, challenge-based learning, and project-based learning have been incorporated into a STEAM program named ARTspace at the Lawrence Arts Center in Lawrence, Kansas. Using examples of curriculum and practice undertaken over the last five years, the authors share the formation of three distinct assessment tools developed to measure metacognitive awareness of the invention process, creative self-efficacy, and the acquisition and retention of standards based STEAM content. The data presented from a three-year evaluation of the ARTspace program shows statistically significant gains in awareness of process-based thinking/practice as well as confidence in practicing innovation.
From Electronic Word of Mouth to Virtual and Augmented Reality
Authors: Nayak Sulakshana
Published: February 2020

This chapter reveals how service is an integral part of any customer value creation strategy and the role played by eWOM with respect to the restaurant industry by considering it in the context of Pune city, Maharashtra, India. It explores literature on eWOM in service industry, in general, and restaurant industry, in particular; additionally, the author employs Delphi method to seek responses from people within the restaurant industry to gauge the importance of eWOM in customer value creation. The world is progressing at a massive pace; international mega-trends only underpin this verity. The internet boom is at its pinnacle, smartphone diffusion is rising rapidly, and demographics are advancing. The chapter points out how “new” technologies such as Virtual Reality or Augmented Reality may change the way customers deal with restaurants.
Smart Store Base Grocery
Authors: Roy Amit
Published: February 2020

Marketing Intelligence is a new topic in marketing with scarce work published. Physical store base grocery is not transmitted digitally. In terms of reason the profit is lower in Portugal or other countries where the app is not available. Therefore, grocery store owners are less engaged with customers. Store owners are losing business interest and, finally, many stores have shut down. The information can emerge from several bases to analyze different kinds of e-commerce roles to show how e-commerce brings more profit and how physical store base grocery transmits digitally to engage customers and increase profit. The chapter uses different types of tools for effective decision making. Software marketing makes vital tactical decisions to exploit profits and success of the business. As a result, the chapter offers a digital model of smart store base Grocery app to engage customers and store owners in one platform for service of excellence, as well as facilitating future forecasting profit.
Detection of Glaucoma in Retinal Images Based on Multiobjective Approach
Authors: Singh Law Kumar , Pooja  , Garg Hitendra
Published: February 2020

Glaucoma is one of the major causes of blindness. Glaucoma is a condition due to increased pressure within the eyeball, causing progressive, irreversible and gradual loss of sight. It can be prevented only detection in disc ratio (CDR), ratio of blood vessel area in interior and superior side of the blood vessel in the nasal temporal side extracted from retinal fundus images. Reducing the number of features and reducing the error rate are two conflicting objectives. The proposed methodology aims to explore the use of Differential Evolution based multi objective feature selection technique to select a subset of features which minimize both our conflicting objectives. The performance of selected subset of features has been evaluated using KNN classification technique. It has been observed that said extracted subset of five features, KNN classification achieved better accuracy than any other subset of features.
Impact of Food and Beverage Quality on Passenger Satisfaction in Indian Railways
Authors: Dandotiya Ravi , Aggarwal Pranav , Gopal Ram
Published: February 2020

This study uses disconfirmation theory to evaluate a theoretical model, which explains the relationship of four constructs of the food and beverage quality, namely freshness, taste, presentation, and temperature. In addition, the effect of price on satisfaction is also measured. Food quality has been considered the basic component of customer satisfaction in restaurants, but there are very few studies in railway-related food and beverage quality. The objective of the research is to study the effect of food, beverage quality and price on passenger satisfaction in Indian railways. This study also tries to investigate key attributes related to food and beverage quality, which are important in improving overall satisfaction. The results show that all the food and beverage quality attributes and price significantly affect passenger satisfaction. Subsequent regression analysis exhibits that taste followed by presentation were the most important factors in achieving passenger satisfaction. The managers can focus on the key food and beverage attributes, which brings out the passenger satisfaction.
PVO-Based Multiple Message Segment Reversible Data Hiding
Authors: Chhabra Sahil , Jain Neeraj Kumar , Tomar Vipin
Published: February 2020

In this article, a reversible data hiding technique is proposed to embed multiple segments of a single message into a single cover image. This multiple message segment technique uses a pixel value ordering approach to embed the secret message. The splitting and randomization of the original secret message provides security from an attacker There are many digital formats for data hiding, like images, audio, and video, of which the digital image is the simplest format. Data hiding in image processing refers to inserting the secret message into digital images. Reversible data hiding (RDH) is a lossless technique, in which both the embedded secret message and the cover image is extracted by the receiver. The applications of RDH include medical and military imaging.
Review of Sentiment Detection
Authors: Gupta Smiley , Singh Jagtar
Published: February 2020

A large volume of user-generated data is evolving on a day-to-day basis, especially on social media platforms like Twitter, where people express their opinions and emotions regarding certain individuals or entities. This user-generated content becomes very difficult to analyze manually and therefore requires a need for an intelligent automated system which mines the opinions and organizes them using polarity metrics, representing the process of sentiment analysis. The motive of this review is to study the concept of sentiment analysis and discuss the comparative analysis of its techniques along with the challenges in this field to be considered for future enhancement.
Avatar-Based Automated Tools and Testing Cloud System as a Gateway of Modern Feedback Control in Digital Era
Authors: Mkrttchian Vardan
Published: February 2020

This article is an enhancement of “Avatars “HHH” Technology Education Cloud Platform on Sliding Mode Based Plug-Ontology as a Gateway to Improvement of Feedback Control Online Society” an article from IJICTHD volume 6 issue 3, published in 2014. This article proposes the concept of creating an automated software system for monitoring student knowledge in the learning process. It is proven that for successful students to learn remotely, it is necessary to develop a knowledge assessment system that takes into account the various learning features, as well as the individual characteristics of the student. The block structure of an automated software system is presented and its elements are discussed in relation to the educational process. The role of the teacher in the virtual learning system is discussed and an algorithm of the learning process in this system is presented. The author using own concept avatar-based automated tools and testing cloud system as a gateway of modern feedback control in digital era.
Implementation of an Interactive Information Sharing System for Disaster Measure Operation
Authors: Nakai Ryo , Ishida Tomoyuki
Published: February 2020

This study develops an interactive information sharing system for disaster measure operations, called “HyperRem.” It consists of the HyperRem-Master and the HyperRem-Node. The HyperRem-Master aggregates information held by meeting participants and visualizes it on a large display. The HyperRem-Node transmits information to the HyperRem-Master by flicking operation from mobile terminals and laptops owned by meeting participants. HyperRem saves screen states visualized on a large display to a database in chronological order, and the saved screen states can be reused. A reuse function and a playback function are implemented to reuse past screen states. The reuse function enables users to resume meetings by restoring past meeting contents to the large display. The playback function provides a review function for past meetings to absentees via a dedicated web page. The operability, functionality, effectiveness, and applicability of HyperRem were confirmed in an evaluation experiment with 10 subjects. The survey results of all five measures revealed an overwhelmingly positive response.
Identification of Telecom Volatile Customers Using a Particle Swarm Optimized K-Means Clustering on Their Personality Traits Analysis
Authors: Elfergany Abdelsadeq Khamis , Adl Ammar
Published: February 2020

This research uses the telecom customers personality traits (extraversion, agreeableness, and neuroticism) to identify the volatile customers that always use the negative word of mouth (NWOM) in communications with others. Hence, a combination of text analysis and a personality analysis tool has been used to determine the customers personality factors from their chatting textual data, A particle swarm optimized k-means was used in the clustering process. The results provide an overview on how a chatbot conversation text represent the customer behavior. Optimizing the k-means cluster using partial swarm achieves a higher accuracy than using the traditional clustering technique.
Fenomenologie van ziekte en abnormaliteit
Authors: Slatman Jenny
Published: February 2020

Phenomenology of illness and abnormality

Habitually, illness or disease is considered as something abnormal. Therefore, the distinction between health/illness is often conflated with the distinction normal/abnormal. Inspired by Kurt Goldstein’s work, Merleau-Ponty makes clear, however, that abnormality does not automatically coincide with pathology. It is also interesting to note that Merleau-Ponty nowhere uses the term “abnormal” to indicate the opposite of the normal person. Similar to Georges Canguilhem he uses the pair “the normal (person)” (le normal) – “the sick person”, “the pathological” (le malade, le pathologique). As Goldstein and Canguilhem make more explicit than Merleau-Ponty, the abnormal person or “deviant” is very often not sick. Instead of approaching physical symptoms from an external or statistical view (which might lead to the conclusion that something is abnormal), they claim that sickness should be defined by the patient’s own lived experience. Merleau-Ponty shares this view, but for different reasons. Goldstein and Canghuilhem, both trained clinicians, believe that patients’ own experiences should be central in clinical practice instead of objectifying measurements and tests. For Merleau-Ponty, the phenomenologist, objective physical features have no place within his phenomenology of lived bodily experience. Bracketing positivist scientific insights, phenomenology also excludes biomedical statistics from its analysis. If we assume that abnormality is a result from a comparison with what is statistically seen as normal, this means that a phenomenology of abnormal embodiment might seem a contradiction in terms. In this paper, however, I would like to show that abnormal embodiment can also be approached from a phenomenological perspective. While drawing on some ideas by Hacking on the history of statistical reasoning, I demonstrate how the statistics of abnormality directly interconnects with lived experience. Hacking explains how the descriptive “average” or “mean” has become the normative “normal”. Because our world is in many ways determined by averages, it is an illusion to think that phenomenology can just bracket statistics. The one who appears physically as abnormal can, comparable to the one who is ill, experience that his or her embodied possibilities to deal with the world dwindle. What I show in this article is that even though a clear distinction can be made between illness and abnormality, both can be accompanied by a reduction or disruption of the “I can”.
The Isotopx NGX and the ATONA Faraday Amplifiers
Authors: Cox Stephen E. , Hemming Sidney R. , Tootell Damian
Published: February 2020

Abstract. We installed the new Isotopx ATONA Faraday cup detector amplifiers on an Isotopx NGX mass spectrometer at Lamont-Doherty Earth Observatory in early 2018. The ATONA is a capacitive transimpedance amplifier, which differs from the traditional resistive transimpedance amplifier used on most Faraday detectors for mass spectrometry. Instead of a high gain resistor, a capacitor is used to accumulate and measure charge. The advantages of this architecture are a very low noise floor, rapid response time, stable baselines, and very high dynamic range. We show baseline noise measurements and measurements of argon from air and cocktail gas standards to demonstrate the capabilities of these amplifiers. The ATONA exhibits a noise floor better than a traditional 1013 Ω amplifier in normal noble gas mass spectrometer usage, superior gain and baseline stability, and an unrivaled dynamic range that makes it practical to measure beams ranging in size from below 10−16 A to above 10−9 A using a single amplifier.
REVIEW OF NOISE FILTERING ALGORITHM FOR PHOTON DATA
Authors: Huang J. P. , Xing Y. Q. , Qin L.
Published: February 2020

Abstract. As a continuation of Ice, Cloud, and Land Elevation Satellite-1 (ICESat-1)/Geoscience Laser Altimeter System (GLAS), the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) , which is equipped with the Advanced Topographic Laser Altimeter (ATLAS) system, was successfully launched in 2018. Since ICESat-1/GLAS has facilitated scientific results in the field of forest structure parameter estimation, how to use the ICESat-2/ATLAS photon cloud data to estimate forest structure parameters has become a hotspot in the field of spaceborne photon data application. However, due to the weak photon characteristics of the ICESat-2/ATLAS system, the system is extremely susceptible to noise, which poses a challenge for its subsequent accurate estimation of forest structural parameters. Aiming to filter out the noise photons, the paper introduces the advantages of the spaceborne lidar system ICESat-2/ATLAS than ICESat-1/GLAS. The paper summarizes the research of the simulated photon-counting lidar (PCL) noise filtering algorithm and noise filtering on spaceborne.
DYNAMIC MONITORING METHOD OF ILLEGAL BUILDINGS USING SPATIOTEMPORAL BIG DATA BASED ON URBAN HIGH LYING ZONES
Authors: Li B. S. , Tan Z. C.
Published: February 2020

Abstract. China's urban illegal buildings are emerging in an endless stream with a large number. There is a wide demand for urban illegal buildings monitoring in urban management departments, including Beijing, Shanghai, Guangzhou and other regions where urban management is facing increasingly serious problems of illegal buildings. It is urgent to solve the common problem of "urban disease" caused by urban illegal buildings, and a new automatic monitoring method that can reduce the cost of urban management is urgently needed. This kind of automated monitoring method of illegal buildings has a wide market demand in Urban Management and Law Enforcement and the Ministry of Land and Resources. Existing technologies cannot realize long-term, autonomous, rapid and intelligent dynamic real-time monitoring of urban illegal buildings, which leads to the problem that illegal buildings’ behaviors cannot be stopped in time. There is a possibility to solve these problems using the ubiquitous network of base stations in cities to monitor illegal buildings.This paper proposes a dynamic monitoring method of illegal buildings using spatiotemporal big data based on urban high lying zones. Through the Spatiotemporal sensor network technology, the tilt-type stereo camera is set up at the high lying zones around the survey area. According to the real-time ambient temperature and humidity numerical data fed back by the temperature and humidity sensor, the tilt-type stereo camera uses intelligent time-lapse photogrammetry technology to obtain multiple stereo pairs. The tilted remote sensor transmits the multiple stereo pairs to the urban dynamic analysis service network using wireless transmission. The urban dynamic analysis service network will complete a series of analysis and processing operations without any human intervention, and then transmit the results of the analysis to the early-warning terminal successively through the base station, WIFI and other wireless transmission methods. Finally, the illegal building data is uploaded to the terminal. That is to say, the urban dynamic analysis service network can realize the intelligent, automatic analysis and processing of spatial analysis server and the operation of calling all database data and storing data.The method proposed in this paper uses the high lying zones around the survey area to expand the monitoring range, improve the accuracy of monitoring data, realize long-term real-time monitoring, and fully utilize the characteristics of Spatiotemporal sensing network technology intelligent, autonomous, wireless transmission, etc., significantly reducing labor. It greatly shortens the process from the emergence to the discovery of illegal buildings in cities. The workload of monitoring has improved the efficiency of dynamic monitoring and warehousing of illegal buildings data in cities.
TOWARDS DESCRIBING FULL-SECTION DEFORMATIONS USING TERRESTRIAL LASER SCANNING IN THE BADALING TUNNEL (CHINA)
Authors: Wang J. , Zheng H. B. , Scaioni M.
Published: February 2020

Abstract. This paper focuses on the analysis of point clouds from terrestrial laser scanning to interpret possible deformations of the new Badaling Tunnel that was built for the Winter Olympics 2022 in the nearby of Beijing, China. A reference framework is established to compare data corresponding to various days with blocks of uniform columns and rows from an estimated tunnel axis. Filling holes and detecting outliers are performed for quasi-planar estimation, and refinement transformation is used to adjust the data errors between different days. Finally, the full-section deformations are detected in the form of distance discrepancies of representative points and are verified against total station measurements.
PRELIMINARY STUDY ON WAVELET DENOISING METHOD FOR INVERSION OF SNOW DEPTH IN GNSS-MR
Authors: Li F. F. , Liu L. L. , Huang L. K. , Zhou W. , Wang S.
Published: February 2020

Abstract. GNSS-MR technology inverts snow depth by using low-altitude SNR data. This information contains rich surface information. Due to the complex surface environment, the signal received by the receiver contains noise，during snow depth inversion, it is not possible to extract relatively "pure" snow information. Therefore, the wavelet denoising method is used to compare with the traditional polynomial. The results show that the snow depth RMSE of the polynomial inversion is 8cm and the error is 7cm. Wavelet denoising inversion The snow depth RMSE is 5cm and the error is 3cm. The experimental verification wavelet denoising method can better eliminate the systematic error and improve the inversion precision.
A METHOD OF FORESTRY DATA COLLECTION BASED ON ANDROID SYSTEM AND RTK
Authors: Zeng Y. , Lan G. W. , Pan Z. G. , Du Y. L. , Shi H. L.
Published: February 2020

Abstract. In our country, forestry resource is one of the most important resources, which are of great significance to national economic and sustainable development. The operation mode of only using a mobile terminal to acquire data cannot satisfy the requirements of forestry data collection. A common mobile terminal is widely used to collect data with the advantage of convenient and rapid in field, but the error range of its GNSS chip positioning is 5 to 10 meters. Both positioning accuracy and the accuracy of sublot area measurement cannot meet the requirement in forestry data acquisition. Although RTK has the advantage of high- precision positioning, its handhold terminal is specially used for mobile single point positioning, and it cannot be suitable for forestry special data collection, storage and visualization. Therefore, this paper presents the idea of using bluetooth communication technology to wirelessly connect RTK with Android mobile terminal, the high precision coordinate is obtained and used for storage and display on the screen in real-time. Combining ArcGIS for Android development kit with SpatiaLite database, this paper develops a set of high-precision and intelligent forestry data acquisition system based on Android platform to realize real-time data collection and sublot editing. Compare with conventional forestry data collection method, the method combines the mobile terminal of Android system with RTK can improve work efficiency, which also provides a more efficient technical means for forestry data collection.
HYPERSPECTRAL IMAGES CLASSIFICATION BASED ON FUSION FEATURES DERIVED FROM 1D AND 2D CONVOLUTIONAL NEURAL NETWORK
Authors: Jiang T. , Wang X. J.
Published: February 2020

Abstract. In recent years, deep learning technology has been continuously developed and gradually transferred to various fields. Among them, Convolutional Neural Network (CNN), which has the ability to extract deep features of images due to its unique network structure, plays an increasingly important role in the realm of Hyperspectral images classification. This paper attempts to construct a features fusion model that combines the deep features derived from 1D-CNN and 2D-CNN, and explores the potential of features fusion model in the field of hyperspectral image classification. The experiment is based on the deep learning open source framework TensorFlow with Python3 as programming environment. Firstly, constructing multi-layer perceptron (MLP), 1D-CNN and 2DCNN models respectively, and then, using the pre-trained 1D-CNN and 2D-CNN models as feature extractors, finally, extracting features via constructing the features fusion model. The general open hyperspectral datasets (Pavia University) were selected as a test to compare classification accuracy and classification confidence among different models. The experimental results show that the features fusion model obtains higher overall accuracy (99.65%), Kappa coefficient (0.9953) and lower uncertainty for the boundary and unknown regions (3.43%) in the data set. Since features fusion model inherits the structural characteristics of 1D-CNN and 2DCNN, the complementary advantages between the models are achieved. The spectral and spatial features of hyperspectral images are fully exploited, thus getting state-of-the-art classification accuracy and generalization performance.
FPGA-BASED ON-BOARD CUBIC CONVOLUTION INTERPOLATION FOR SPACEBORNE GEOREFERENCING
Authors: Liu D. Q. , Zhou G. Q. , Zhou X. , Li C. Y. , Wang F.
Published: February 2020

Abstract. This paper proposes a novel low-complexity implementation with one parameter two dimensions cubic convolution interpolation (2D-CCI) of image interpolation for spaceborne georeferencing. The experiment results demonstrate that (1) the proposed scheme can achieve better performance without increasing the computational complexity compared to the traditional CCI; (2) the number of multiplication and addition is reduced to 33.33% and 40% respectively compared with original CCI; (3) the occupied resources of LUTs, register, DSP and memory are reduced to 23.7%, 21.9%, 18.5% and 25%, respectively; (4) the speedup time of the proposed Implementation is about 25 times higher than that when using the PC-based implementation.
ANALYSIS OF TEMPORAL AND SPATIAL CHARACTERISTICS OF MANGROVE PHYSIOLOGICAL STRUCTURE PARAMETERS QUANTITATIVE INVERSION BASED ON TIME SERIES SENTINEL-2 – TAKING SHANKOU MANGROVE NATURE RESERVE AS AN EXAMPLE
Authors: Wang S. W. , He H. C. , Fu B. L. , Sun H. L.
Published: February 2020

Abstract. The physiological structure parameter of vegetation is an important index to measure the ecological health status of mangroves, and it is of great value to measure the ecological health status. Taking Shankou Mangrove Nature Reserve of Guangxi as the study area, The Chlorophyll-A/B(CAB),Leaf Area Index (LAI),Fractional Vegetation Cover (FVC) and Fraction of absorbed photo synthetically active radiation (FAPAR) were calculated by using Sentinel-2 image data to calculate the chlorophyll content of mangrove vegetation in the study area. The BP neural network algorithm is used to verify the accuracy difference between the inversion results and the corresponding products of MODIS, and the dynamic changes of physiological structure parameters of vegetation in mangroves are further studied. Results showed that: (1)The correlation coefficients between LAI, CAB, FAPAR, FVC and MODIS products were higher than 0.71 in 95% confidence interval in mangrove years, it is proved that Sentinel-2A/B multispectral image inversion of mangrove physiological structure parameters has high accuracy and quality. (2)The physiological structure parameters of mangroves fluctuated during the year. In February, the lowest values of LAI, CAB, FAPAR and FVC were 0.30, 0.08, 0.08 and 0.13, respectively. The highest values were 0.69 in October, 0.29 in December, 0.27 in August, 0.40 in April, 0.24 and 0.24 in September, and 0.27 and 0.33 in LAI in November, respectively, with the highest LAI in October, 0.29 in December, 0.27 in August, 0.40 in April, 0.24 and 0.24 in September, and 0.27 and 0.33 in November. The results provide the basis for the monitoring of mangrove vegetation change and provide a reference for ecological assessment and protection.
GENERATING TIME SERIES OF MEDIUM-RESOLUTION TEMPERATURE VEGETATION DROUGHT INDEX IMAGES USING A KALMAN FILTER METHOD FOR SOIL MOISTURE CHANGE ANALYSIS
Authors: Zhai H. , Huang F. , Qi H. , Ren Y. , Liu R. , Li B. , Chang S.
Published: February 2020

Abstract. Soil moisture is one of key environmental variables that affect vegetation cover and energy exchange between the land surface and the atmosphere. Satellite remote sensing technology can provide information for monitoring large-scale soil moisture dynamics quickly. The temperature vegetation dryness index (TVDI) acts as an effective indicator of inferring soil moisture status which is calculated according to the empirical parameterization of composed of the land surface temperature (LST) and the normalized difference vegetation index (NDVI) characteristic space. In this paper, the MODIS TVDI was calculated based on MODIS LST product (MOD11A2, 1 km) and NDVI data (derived from MOD09A1, 500m). Meanwhile, LST and NDVI from Landsat8 OLI images were estimated to obtain Landsat-based TVDI. Then, a Kalman filter algorithm was used to simulate TVDI time series data with 30m resolution and a revisit period of 8 days combining TVDI derived from Landsat and MODIS data. We selected the west of the Songnen Plain, China as the test area and high quality cloudy-free images during growing season (April to October) of 2018 as the input data. The predicted TVDI time series data of medium resolution not only improved the temporal resolution to capture the changes at fine scale within a short period, but also made up for the deficiency of low spatial resolution MODIS data. The results show that it is feasible to generate medium or high resolution TVDI time series data by applying different remote sensing data by Kalman filtering algorithm.
RESEARCH ON MULTI-SOURCE SATELLITE IMAGE DATABASE MANAGEMENT SYSTEM
Authors: Fu N. , Sun L. , Yang H. Z. , Ma J. , Liao B. Q.
Published: February 2020

Abstract. For the exploration and analysis of electricity, it is necessary to continuously acquire multi-star source, multi-temporal, multi-level remote sensing images for analysis and interpretation. Since the overall data has a variety of features, a data structure for multi-sensor data storage is proposed. On the basis of solving key technologies such as real-time image processing and analysis and remote sensing image normalization processing, the .xml file and remote sensing data geographic information file are used to realize effective organization between remote sensing data and remote sensing data. Based on GDAL design relational database, the formation of a relatively complete management system of data management, shared publishing and application services will maximize the potential value of remote sensing images in electricity remote sensing.
TOWARDS AN INTEGRATED EARTH OBSERVATION SCIENCE IN A BIG EARTH DATA ERA
Authors: Blaschke T.
Published: February 2020

Abstract. Earth observation (EO) data – including satellite-borne, airborne or drone-based imagery – have become indispensable for the monitoring of the environment. EO supports tackling the ‘grand challenges’ at global spatial scales, such as global change and climate variability technology but also retail or insurance. Like a macroscope, it opens research avenues to observe processes occurring over a wide range of spatial and temporal scales, from abrupt changes such as earthquakes, to decadal shifts such as growth and shrinkage of ice sheets. Particularly satellite data became a success story and empowered individuals, businesses and society. Until a few years ago, the term remote sensing mainly stood for a digital raster world view while the GIS community was inclined to the vector world. “Earth Observation” seems to be integrative and to accommodate various means of data acquisition from satellites, aircrafts, drones, to in situ measurements. Today the rapid growth of data science, the consumerization of GIS and remote sensing, and the continued spread of online cartographic tools are prompting a more holistic Earth Observation Science and interdisciplinary educational programmes.
Institutionalising a Withering Sense in Corporate Social Responsibility
Authors: Teck Tan Seng , Ayadurai Selvamalar , Chua William , Liang Tan Peng , Karuppiah Nanthakumar
Published: February 2020

Studies and writings on corporate social responsibility turned a full cycle with much ink spilled on this topic. From the inception of a divine origin, corporate social responsibility has now become a flamboyant display of numbers and statistics which corporations proudly present them to fulfil their legal obligations. It is ironic that a divine understanding of corporate social responsibility has now transpired to be a complex calculus of statistical tabulations, too often exhibited in annual and sustainability reports. Organisations become grossly mesmerised with the grandiosity of exceeding the prerequisites of ecological, environmental, social and economic performance supported by undisputable, verifiable and measurable data. Corporate social responsibility has become senseless and meaningless. This is not a research paper nor does it entail the rudiments of any research findings. Conversely, this paper alerts and perhaps cautions corporate social responsibility practitioners on the perils of their overarching emphasis on positivism. Corporate social responsibility cannot be quantified merely in numbers but on the contrary, it should involve truthful, honest and transparent dialectic communication with the stakeholders. Many corporations deceived and some still facing the remnants of their mistakes. The Volkswagen ‘diesel dupe’ crisis and Johnson & Johnson’s baby talc powder scandals are reminders of the same. This paper is a solemn reminder that corporations must be ‘awakened’ so that ethics is grounded to its core and not merely in the cosmetic forms of presentable statistics.
POTENSI KINETIC TYPOGRAPHY SEBAGAI MEDIA INFORMASI
Authors: Luthfiasari Annisa
Published: February 2020

Seiring dengan munculnya berbagai media komunikasi baru dan kebutuhan akan media digital yang terus meningkat, muncul suatu bentuk karya tipografi baru yaitu dalam bentuk kinetic typography. Menurut Hostetler, kinetic typography adalah kombinasi antara tipografi dan gerak (motion) atau biasa juga disebut sebagai typographic animation [2]. Peran tipografi (huruf) sebagai alat komunikasi tentunya tidak dapat dipungkiri lagi. Akan tetapi, dirasa perlu untuk mengkaji lebih jauh bagaimana tipografi bila diadaptasi dalam bentuk digital dan bertransformasi dalam bentuk time-based media. Dalam jurnal ini akan dibahas bagaimana potensi dari kinetic typography sebagai media informasi dengan mengintegrasikan beberapa teori untuk dapat diambil kesimpulan.
El sufijo «-ing» en español y catalán: análisis contrastivo desde la perspectiva lexicográfica
Authors: Prat Sabater Marta
Published: February 2020

El objetivo de este artículo consiste en realizar un análisis contrastivo entre español y catalán sobre el uso del sufijo -ing de procedencia inglesa. Para ello, se compara, en primer lugar, la mayor o menor aceptabilidad de anglicismos con esta terminación en los diccionarios normativos y de uso de ambas lenguas románicas. En segundo lugar, se demuestra que, además de tratarse de un morfema derivativo que forma parte de importaciones léxicas, posee un valor productivo en la creación o aceptación de nuevas palabras con esta terminación. Por último, la valoración de su presencia en el contexto lexicográfico sugiere constatar en futuros trabajos la vitalidad de este sufijo en el uso más espontáneo de las lenguas española y catalana.

The objective of this article is to carry out a contrastive analysis between Spanish and Catalan on the use of the English suffix -ing. For this purpose, the greater or lesser acceptability of anglicisms is compared, first, with this word ending in the normative and use dictionaries of both Romance languages. Secondly, it is shown that, besides being a derivative morpheme which is part of lexical imports, it has a productive value in the creation or acceptance of new words with this ending. Finally, the assessment of its presence in the lexicographical context suggests that future researches will verify the vitality of this suffix in the most spontaneous use of the Spanish and Catalan languages.
The role of nanotechnology in revolutionizing energy sector
Authors: Maksimović Mirjana , Forcan Miodrag
Published: February 2020

The need for modernization of the existing energy sector is driven by globally increasing energy demand, rising carbon emissions, global warming, and climate change. The world tends towards the sustainable and more environmentally friendly energy sector that will meet future energy demands by reducing the usage of raw and non-renewable materials and resources and decreasing energy consumption and pollution. Nanotechnology, as one of the key technologies of the 21st Century, holds the potential to revolutionize the entire energy sector, contributing to the development of more efficient and sustainable energy systems. The implementation of nanotechnology in the energy sector is in the various stages of research, development, and deployment. Nanotechnology’s solutions and approaches can help create innovative ways to produce, change, distribute, store and consume energy. This paper attempts to summarize some of the current nanotechnology applications in energy sector, emphasizing the associated benefits as well as risks and concerns. Present nanotechnology-based solution and approaches used in the energy sector confirms nanotechnology's potential to revolutionize the entire energy sector. Alongside the growing use of nanomaterials and nanoproducts, uncertainties on the nanotechnology potentially harmful influence on the environment, health, and safety rise as well, representing a main concern related to nanotechnology applications. In addition to the technological feasibility of the nanotechnology implementation in the energy sector, a wide range of other conditions, such as political, economical and social, influence the rate of implementation and acceptance of nanotechnological innovations in the energy sector.
Why primary prevention is important, and how to promote resilience: CADCA
Authors: Knopf Alison
Published: February 2020

Last week's annual leadership meeting of Community Anti‐Drug Coalitions of America (CADCA) focused, as it always does, on primary prevention. This is defined as preventing the use of drugs (including alcohol), mainly in youth. There were more than 3,200 attendees, 500 of whom were middle and high schoolers drawn from the coalitions funded by the Drug‐Free Communities (DFC) program, with CADCA member organizations benefiting from training in how to use this funding.
Investigating the Superoxide Formation and Stability in Mesoporous Carbon Perovskite Solar Cells with an Aminovaleric Acid Additive
Authors: Péan Emmanuel V. , De Castro Catherine S. , Dimitrov Stoichko , De Rossi Francesca , Meroni Simone , Baker Jenny , Watson Trystan , Davies Matthew L.
Published: February 2020

Perovskite solar cells have attracted a great deal of attention thanks to their high efficiency, ease of manufacturing, and potential low cost. However, the stability of these devices is considered their main drawback and needs to be addressed. Mesoporous carbon perovskite solar cells (m‐CPSC), consisting of three mesoporous layers (TiO2/ZrO2/C) infiltrated with CH3NH3PbI3 (MAPI) perovskite, have presented excellent lifetimes of more than 10 000 h when the additive NH2(CH2)4CO2HI (5‐ aminovaleric acid iodide; 5‐AVAI) is used to modify the perovskite structure. Yet, the role of 5‐AVAI in enhancing the stability has yet to be determined. Here, superoxide‐mediated degradation of MAPI m‐CPSC with and without the 5‐AVAI additive is studied using the fluorescence probe dihydroethidium for superoxide detection. In situ X‐ray diffractometry shows that aminovaleric acid methylammonium lead iodide (AVA‐MAPI) perovskite infiltrated in mesoporous layers presents higher stability in an ambient environment under illumination, evidenced by a slower decrease of the MAPI/PbI2 peak ratio. Superoxide yield measurements demonstrate that AVA‐MAPI generates more superoxide than regular MAPI when deposited on glass but generates significantly less when infiltrated in mesoporous layers. It is believed that superoxide formation in m‐CPSC is dependent on a combination of competitive factors including oxygen diffusion, sample morphology, grain size, and defect concentration.
Phosphorous‐Doped Graphite Layers with Outstanding Electrocatalytic Activities for the Oxygen and Hydrogen Evolution Reactions in Water Electrolysis
Authors: Liu Ziwu , Ai Jie , Sun Maomao , Han Fei , Li Zekun , Peng Qiancheng , Wang Quan‐De , Liu Jinlong , Liu Ling
Published: February 2020

Advances demonstrate that the incorporation of phosphorous into the network of nitrogen, sulfur, or fluorine‐doped carbon materials can remarkably enhance their oxygen and hydrogen evolution activities. However, the electrocatalytic behaviors of pristine phosphorous single‐doped carbon catalysts toward the oxygen and hydrogen evolution reactions (OER and HER) are rarely investigated and their corresponding active species are not yet explored. To clearly ascertain the effects of phosphorous doping on the OER and HER and identify the active sites, herein, phosphorous unitary‐doped graphite layers with different phosphorous species distributions are prepared and the correlations between the oxygen or hydrogen evolution activity and different phosphorous species are investigated, respectively. Results indicate that phosphorous single‐doped graphite layers show a superior oxygen evolution activity to most of the reported OER catalysts and the commercial IrO2 in alkaline medium, and comparable hydrogen evolution activity to most reported carbon catalysts in acidic medium. Moreover, the relevancies unveil that the COP species are the main OER active species, and the defects derived from the decomposition of C3P = O species are the main active sites for HER, as evidenced by density functional theory calculations, showing a new perspective for the design of more effective phosphorous‐containing water‐splitting catalysts.
Ratiometric Detection of Rifampin by Using Self‐Assembled Nanocomposites with Dual Fluorescence Emissions and Analysis of Two‐Dimensional Correlation Spectroscopy
Authors: Zhang Yanlin , Xu Na , Meng Lei
Published: February 2020

A new ratiometric fluorescence probe is constructed for the detection of rifampin (RIF). Amino‐modified silicon nanoparticles (SiNPs) and mercaptoundecanoic acid capped gold nanoclusters (MUA‐AuNCs) are self‐assembled into nanocomposites, showing dual fluorescence emissions, respectively, at 440 and 615 nm under a single excitation of 300 nm. The morphology, surface chemistry and optical properties of the nanocomposites are finely investigated through transmission electron microscopy (TEM), Fourier transforms infrared spectroscopy (FT‐IR), UV–vis absorbance, dynamic and steady state fluorescence spectroscopy. Owning to rich hydroxyl groups, RIF can bind with MUA‐AuNCs though hydrogen bonds resulting in the red fluorescence quenching. But the SiNPs keep their own blue fluorescence stable, which can act as an internal reference for ratiometric detection. By means of the ratio I615/I440, the linear relationship is established in the range from 0.1 to 5 μM with the detection limit of 0.04 μM. In addition, the synchronous and asynchronous fluorescence 2D correlation maps have been created to in‐depth study the relative detecting mechanism.
Study examines assault rates involving student‐athletes
Authors: Sutton Halley
Published: February 2020

Student‐athletes have been disciplined for sexual misconduct and assault at a rate three times higher than the general student population since 2014, according to data collected by the USA Today network. Football players were disciplined for sexual misconduct and assault the most frequently of all student‐athletes.
Familiarize yourself with budgeting best practices to boost your department's success
Authors: Pavlik Amelia
Published: February 2020

Among the long list of administrative duties that come with the job, the budgeting process often ranks as the one responsibility for which college athletics administrators feel least equipped to manage.
Did court dismiss student's Title IX harassment claim concerning alleged treatment by student‐athlete?
Authors: Gelpi Aileen
Published: February 2020

When the plaintiff was admitted to Lees‐McRae College, it accommodated her social anxiety disorder by providing special housing and access to the school therapist.
Teens not getting treatment after OD: Medicaid
Authors: Knopf Alison
Published: February 2020

How many studies will it take to show that young people are overdosing because they are not getting medications needed to treat their opioid use disorder (OUD)? The most recent study shows that this is not likely to change unless there is a system in place to link these young people to treatment, but earlier work by the same senior author shows the problem may be even deeper: stigma, bureaucracy, and lack of prescriber availability.
Developing Cheap and Mass‐Producible Graphite‐Filled Paper as an Anode Material for Microbial Electrochemical Technologies
Authors: Alvarez Esquivel Diana Y. , Brown Robert Keith , Knohl Stefan , Schröder Uwe
Published: February 2020

This study details, in‐depth, the development of graphite paper as electrodes, specifically anodes, for microbial electrochemical technologies. Processed natural graphite powders were used as an active filler substance in paper composites. Mechanical and electrical properties were balanced during development. Graphite papers with 80 wt% natural graphite content had tear lengths of 730±58 m and resistivities of 0.014±0.001 Ω cm. Electrochemically active biofilms on these materials, cultivated from biomass taken from the bioanodes of an already running bioelectrochemical reactor, were fed with acetate and yielded an average maximum current density of 0.855±0.135 as well as 0.489±0.148 mA cm−2 with a complex substrate mixture. All anodes exhibited similar performance to commonly used carbonaceous electrodes fed the same substrates. This places them as flexible and cheap electrode materials suitable for large‐scale microbial electrochemical technologies.
Dual‐mode multiple‐target tracking in wireless sensor networks based on sensor grouping and maximum likelihood estimation
Authors: Adhami Mohammad Hossein , Ghazizade Reza , Majidi Mohammad‐Hassan
Published: February 2020

The problem of tracking multiple mobile targets, using a wireless sensor network, is investigated in this paper. We propose a new sensor grouping algorithm, based on the maximum sensor separation distances (G‐MSSD), for estimating the location of multiple indistinguishable targets, either jointly or individually, depending on the distances between the generated groups. The joint tracking algorithm is formulated as a maximum likelihood (ML) estimator and solved through a modified version of the well‐known Gauss‐Newton (MGN) iterative method. We propose two candidate initial guesses for MGN based on G‐MSSD in joint tracking mode, while for the individual mode, the information of each group is used to estimate the location of only the corresponding target. The Cramer‐Rao lower bound (CRLB) for the variance of the proposed ML estimator is derived, and the potential conditions for reducing the CRLB are presented. Since tracking efficiency is affected by poor estimates, we present two criteria to evaluate the quality of estimates and detect the poor ones. An approach is also proposed for correcting the poor estimates, based on additional initial guesses. We demonstrate the effectiveness and accuracy of our proposed dual‐mode algorithm via simulation results and compare our results with the Multi‐Resolution search algorithm.