bluuebunny/crossref_metadata_2025 huggingface dataset:
Participation in Community-Based Solid Waste Management in Nkulumane Suburb, Bulawayo, Zimbabwe
Authors: Sinthumule Ndidzulafhi Innocent , Mkumbuzi Sinqobile Helen
Published: February 2019

After years of conventional approaches to solid waste management (SWM), in 2009, Bulawayo City Council adopted a non-conventional approach in the form of community-based solid waste management (CBSWM). The success of a CBSWM depends on the participation of members of the public as well as private sector organisations. Yet there is no information documented about their involvement in such activities in the study area. This study provides an analysis of citizen knowledge, participation and their attitudes in SWM in Nkulumane suburb following implementation of a CBSWM project. Door-to-door surveys were undertaken in December 2017 and January 2018 during which interview-administered questionnaires were used to collect data from 375 randomly-selected households. Semi-structured interviews were also used to gather data from officials responsible for CBSWM. The study found that the CBSWM has not been successful in changing the waste disposal behaviour of citizens. It was also found that the community-based organisations (CBOs) have made no effort to implement alternative waste management practices of waste recycling and composting. Furthermore, lack of funds to improve waste infrastructure and infighting between the Environmental Management Agency (EMA) and the Bulawayo City Council have undermined the principles of CBSWM. The study concludes by suggesting strategies that could improve CBSWM in developing countries.
Optimal Bail-Out Dividend Problem with Transaction Cost and Capital Injection Constraint
Authors: Junca Mauricio , Moreno-Franco Harold A. , Pérez José Luis
Published: February 2019

We consider the optimal bail-out dividend problem with fixed transaction cost for a Lévy risk model with a constraint on the expected present value of injected capital. To solve this problem, we first consider the optimal bail-out dividend problem with transaction cost and capital injection and show the optimality of reflected ( c 1 , c 2 ) -policies. We then find the optimal Lagrange multiplier, by showing that in the dual Lagrangian problem the complementary slackness conditions are met. Finally, we present some numerical examples to support our results.
Statistics Learning Network Based on the Quadratic Form for SAR Image Classification
Authors: He Chu , He Bokun , Liu Xinlong , Kang Chenyao , Liao Mingsheng
Published: February 2019

The convolutional neural network (CNN) has shown great potential in many fields; however, transferring this potential to synthetic aperture radar (SAR) image interpretation is still a challenging task. The coherent imaging mechanism causes the SAR signal to present strong fluctuations, and this randomness property calls for many degrees of freedom (DoFs) for the SAR image description. In this paper, a statistics learning network (SLN) based on the quadratic form is presented. The statistical features are expected to be fitted in the SLN for SAR image representation. (i) Relying on the quadratic form in linear algebra theory, a quadratic primitive is developed to comprehensively learn the elementary statistical features. This primitive is an extension to the convolutional primitive that involves both nonlinear and linear transformations and provides more flexibility in feature extraction. (ii) With the aid of this quadratic primitive, the SLN is proposed for the classification task. In the SLN, different types of statistics of SAR images are automatically extracted for representation. Experimental results on three datasets show that the SLN outperforms a standard CNN and traditional texture-based methods and has potential for SAR image classification.
Development of a Multimode Field Deployable Lidar Instrument for Topographic Measurements of Unsaturated Soil Properties: Instrument Description
Authors: Salazar Sean E. , Garner Cyrus D. , Coffman Richard A.
Published: February 2019

The hydrological and mechanical behavior of soil is determined by the moisture content, soil water (matric) potential, fines content, and plasticity. However, these parameters are often difficult or impractical to determine in the field. Remote characterization of soil parameters is a non-destructive data collection process well suited to large or otherwise inaccessible areas. A ground-based, field-deployable remote sensor, called the soil observation laser absorption spectrometer (SOLAS), was developed to collect measurements from the surface of bare soils and to assess the in-situ condition and essential parameters of the soil. The SOLAS instrument transmits coherent light at two wavelengths using two, continuous-wave, near-infrared diode lasers and the instrument receives backscattered light through a co-axial 203-mm diameter telescope aperture. The received light is split into a hyperspectral sensing channel and a laser absorption spectrometry (LAS) channel via a multi-channel optical receiver. The hyperspectral channel detects light in the visible to shortwave infrared wavelengths, while the LAS channel filters and directs near-infrared light into a pair of photodetectors. Atmospheric water vapor is inferred using the differential absorption of the on- and off-line laser wavelengths (823.20 nm and 847.00 nm, respectively). Range measurement is determined using a frequency-modulated, self-chirped, coherent, homodyne detection scheme. The development of the instrument (transmitter, receiver, data acquisition components) is described herein. The potential for rapid characterization of physical and hydro-mechanical soil properties, including volumetric water content, matric potential, fines content, and plasticity, using the SOLAS remote sensor is discussed. The envisioned applications for the instrument include assessing soils on unstable slopes, such as wildfire burn sites, or stacked mine tailings. Through the combination of spectroradiometry, differential absorption, and range altimetry methodologies, the SOLAS instrument is a novel approach to ground-based remote sensing of the natural environment.
Evaluation of Bias Correction Methods for GOSAT SWIR XH2O Using TCCON data
Authors: Trieu Tran Thi Ngoc , Morino Isamu , Ohyama Hirofumi , Uchino Osamu , Sussmann Ralf , Warneke Thorsten , Petri Christof , Kivi Rigel , Hase Frank , Pollard David F. , Deutscher Nicholas M. , Velazco Voltaire A. , Iraci Laura T. , Podolske James R. , Dubey Manvendra K.
Published: February 2019

This study evaluated three bias correction methods of systematic biases in column-averaged dry-air mole fraction of water vapor (XH2O) data retrieved from Greenhouse Gases Observing Satellite (GOSAT) Short-Wavelength Infrared (SWIR) observations compared with ground-based data from the Total Carbon Column Observing Network (TCCON). They included an empirically multilinear regression method, altitude bias correction method, and combination of altitude and empirical correction for three cases defined by the temporal and spatial collocation around TCCON site. The results showed that large altitude differences between GOSAT observation points and TCCON instruments are the main cause of bias, and the altitude bias correction method is the most effective bias correction method. The lowest biases result from GOSAT SWIR XH2O data within a 0.5° × 0.5° latitude × longitude box centered at each TCCON site matched with TCCON XH2O data averaged over ±15 min of the GOSAT overpass time. Considering land data, the global bias changed from −1.3 ± 9.3% to −2.2 ± 8.5%, and station bias from −2.3 ± 9.0% to −1.7 ± 8.4%. In mixed land and ocean data, global bias and station bias changed from −0.3 ± 7.6% and −1.9 ± 7.1% to −0.8 ± 7.2% and −2.3 ± 6.8%, respectively, after bias correction. The results also confirmed that the fine spatial and temporal collocation criteria are necessary in bias correction methods.
Operational Monitoring of Illegal Fishing in Ghana through Exploitation of Satellite Earth Observation and AIS Data
Authors: Kurekin Andrey A. , Loveday Benjamin R. , Clements Oliver , Quartly Graham D. , Miller Peter I. , Wiafe George , Adu Agyekum Kwame
Published: February 2019

Over the last decade, West African coastal countries, including Ghana, have experienced extensive economic damage due to illegal, unreported and unregulated (IUU) fishing activity, estimated at about USD 100 million in losses each year. Illegal, unreported and unregulated fishing poses an enormous threat to the conservation and management of the dwindling fish stocks, causing multiple adverse consequences for fisheries, coastal and marine ecosystems and for the people who depend on these resources. The Integrated System for Surveillance of Illegal, Unlicensed and Unreported Fishing (INSURE) is an efficient and inexpensive system that has been developed for the monitoring of IUU fishing in Ghanaian waters. It makes use of fast-delivery Earth observation data from the synthetic aperture radar instrument on Sentinel-1 and the Multi Spectral Imager on Sentinel-2, detecting objects that differ markedly from their immediate background using a constant false alarm rate test. Detections are matched to, and verified by, Automatic Identification System (AIS) data, which provide the location and dimensions of ships that are legally operating in the region. Matched and unmatched data are then displayed on a web portal for use by coastal management authorities in Ghana. The system has a detection success rate of 91% for AIS-registered vessels, and a fast throughput, processing and delivering information within 2 h of acquiring the satellite overpass. However, over the 17-month analysis period, 75% of SAR detections have no equivalent in the AIS record, suggesting significant unregulated marine activity, including vessels potentially involved in IUU. The INSURE system demonstrated its efficiency in Ghana’s exclusive economic zone and it can be extended to the neighbouring states in the Gulf of Guinea, or other geographical regions that need to improve fisheries surveillance.
A Novel Pedestrian Dead Reckoning Algorithm for Multi-Mode Recognition Based on Smartphones
Authors: Xu Limin , Xiong Zhi , Liu Jianye , Wang Zhengchun , Ding Yiming
Published: February 2019

With the rapid development of smartphone technology, pedestrian navigation based on built-in inertial sensors in smartphones shows great application prospects. Currently, most smartphone-based pedestrian dead reckoning (PDR) algorithms normally require a user to hold the phone in a fixed mode and, thus, need to correct the gyroscope heading with inputs from other sensors, which restricts the viability of pedestrian navigation significantly. In this paper, in order to improve the accuracy of the traditional step detection and step length estimation method for different users, a state transition-based step detection method and a step length estimation method using a neural network are proposed. In order to decrease the heading errors and inertial sensor errors in multi-mode system, a multi-mode intelligent recognition method based on a neural network was constructed. On this basis, we propose a heading correction method based on zero angular velocity and an overall correction method based on lateral velocity limitation (LV). Experimental results show that the maximum positioning errors obtained by the proposed algorithm are about 0.9% of the total path length. The proposed novel PDR algorithm dramatically enhances the user experience and, thus, has high value in real applications.
Enhanced Regional Monitoring of Wheat Powdery Mildew Based on an Instance-Based Transfer Learning Method
Authors: Liu Linyi , Dong Yingying , Huang Wenjiang , Du Xiaoping , Luo Juhua , Shi Yue , Ma Huiqin
Published: February 2019

In order to monitor the prevalence of wheat powdery mildew, current methods require sufficient sample data to obtain results with higher accuracy and stable validation. However, it is difficult to collect data on wheat powdery mildew in some regions, and this limitation in sampling restricts the accuracy of monitoring regional prevalence of the disease. In this study, an instance-based transfer learning method, i.e., TrAdaBoost, was applied to improve the monitoring accuracy with limited field samples by using auxiliary samples from another region. By taking into account the representativeness of contributions of auxiliary samples to adjust the weight placed on auxiliary samples, an optimized TrAdaBoost algorithm, named OpTrAdaBoost, was generated to map regional wheat powdery mildew. The algorithm conducts this by: (1) producing uncertainty associated with each prediction based on the similarities, and calculating the representativeness contribution of all auxiliary samples by taking into account the overall uncertainty of the wheat powdery mildew map; (2) calculating the errors of the weak learners during the training process and using boosting to filter out the unreliable auxiliary samples by adjusting the weights of auxiliary samples; (3) combining all weak learners according to the weights of training instances to build a strong learner to classify disease severity. OpTrAdaBoost was tested using a dataset with 39 study area samples and 106 auxiliary samples. The overall monitoring accuracy was 82%, and the kappa coefficient was 0.72. Moreover, OpTrAdaBoost performed better than other algorithms that are commonly used to monitor wheat powdery mildew at the regional level. Experimental results demonstrated that OpTrAdaBoost was effective in improving the accuracy of monitoring wheat powdery mildew using limited field samples.
Multi-GPU Based Parallel Design of the Ant Colony Optimization Algorithm for Endmember Extraction from Hyperspectral Images
Authors: Gao Jianwei , Sun Yi , Zhang Bing , Chen Zhengchao , Gao Lianru , Zhang Wenjuan
Published: February 2019

Spectral unmixing is a vital procedure in hyperspectral remote sensing image exploitation. The linear mixture model has been widely utilized to unmix hyperspectral images by extracting a set of pure spectral signatures, called endmembers in hyperspectral jargon, and estimating their respective fractional abundances in each pixel of the scene. Many algorithms have been proposed to extract endmembers automatically, which is a critical step in the spectral unmixing chain. In recent years, the ant colony optimization (ACO) algorithm has been developed for endmember extraction from hyperspectral data, which was regarded as a combinatorial optimization problem. Although the ACO for endmember extraction (ACOEE) can acquire accurate endmember results, its high computational complexity has limited its application in the hyperspectral data analysis. The GPUs parallel computing technique can be utilized to improve the computational performance of ACOEE, but the architecture of GPUs determines that the ACOEE should be redesigned to take full advantage of computing resources on GPUs. In this paper, a multiple sub-ant-colony-based parallel design of ACOEE was proposed, in which an innovative mechanism of local pheromone for sub-ant-colonies is utilized to enable ACOEE to be preferably executed on the multi-GPU system. The proposed method can avoid much synchronization among different GPUs to affect the computational performance improvement. The experiments on two real hyperspectral datasets demonstrated that the computational performance of ACOEE significantly benefited from the proposed methods.
Fluorescent Sensors for the Detection of Heavy Metal Ions in Aqueous Media
Authors: De Acha Nerea , Elosúa César , Corres Jesús , Arregui Francisco
Published: February 2019

Due to the risks that water contamination implies for human health and environmental protection, monitoring the quality of water is a major concern of the present era. Therefore, in recent years several efforts have been dedicated to the development of fast, sensitive, and selective sensors for the detection of heavy metal ions. In particular, fluorescent sensors have gained in popularity due to their interesting features, such as high specificity, sensitivity, and reversibility. Thus, this review is devoted to the recent advances in fluorescent sensors for the monitoring of these contaminants, and special focus is placed on those devices based on fluorescent aptasensors, quantum dots, and organic dyes.
Simple Synthesis of Cobalt Carbonate Hydroxide Hydrate and Reduced Graphene Oxide Hybrid Structure for High-Performance Room Temperature NH3 Sensor
Authors: Wang Chang , Wang Huan , Zhao Dan , Wei Xianqi , Li Xin , Liu Weihua , Liu Hongzhong
Published: February 2019

A novel hybrid structure sensor based on cobalt carbonate hydroxide hydrate (CCHH) and reduced graphene oxide (RGO) was designed for room temperature NH3 detection. This hybrid structure consisted of CCHH and RGO (synthesized by a one-step hydrothermal method), in which RGO uniformly dispersed in CCHH, being used as the gas sensing film. The resistivity of the hybrid structure was highly sensitive to the changes on NH3 concentration. CCHH in the hybrid structure was the sensing material and RGO was the conductive channel material. The hybrid structure could improve signal-to-noise ratio (SNR) and the sensitivity by obtaining the optimal mass proportion of RGO, since the proportion of RGO was directly related to sensitivity. The gas sensor with 0.4 wt% RGO showed the highest gas sensing response reach to 9% to 1 ppm NH3. Compared to a conventional gas sensor, the proposed sensor not only showed high gas sensing response at room temperature but also was easy to achieve large-scale production due to the good stability and simple synthesis process.
CitySpeed: A Crowdsensing-Based Integrated Platform for General-Purpose Monitoring of Vehicular Speeds in Smart Cities
Authors: Costa Daniel G. , Damasceno Adson , Silva Ivanovitch
Published: February 2019

The development of crowdsensing-based technologies has allowed for the use of smartphones in large-scale data collection for different scopes of applications, mostly in a transparent and ubiquitous way. When concerning urban areas and smart city initiatives, the collection and further analysis of information about the highest number of vehicles is of paramount importance, potentially supporting more efficient mobility planning and management actions in modern cities. In this context, this article proposes a public general-purpose platform for acquisition and visualization of vehicular speeds, which can then be exploited by any additional application. For that, a crowdsensing-based mobile software application was developed to collect instantaneous speeds provided by smartphone GPS, formatting and distributing this information to a database system. Such historical data can then be exported or visualized through a web-based comprehensive interface, which provides valuable data when planning traffic mobility in cities; for example, indicating areas with heavier traffic over a certain time period. Therefore, allowing the use of many different search filters and supporting data delivery in the JSON format, the CitySpeed platform can provide services not supported by popular applications, such as Waze and Google Maps, and potentially assist smart city initiatives in this area.
Difficulty Orientations, Gender, and Race/Ethnicity: An Intersectional Analysis of Pathways to STEM Degrees
Authors: Nix Samantha , Perez-Felkner Lara
Published: February 2019

Is there a relationship between mathematics ability beliefs and STEM degrees? Fields such as physics, engineering, mathematics, and computer science (PEMC) are thought to require talent or brilliance. However, the potential effects of difficulty perceptions on students’ participation in STEM have yet to be examined using a gender and race/ethnicity intersectional lens. Using nationally representative U.S. longitudinal data, we measure gender and racial/ethnic variation in secondary students’ orientation towards mathematics difficulty. We observed nuanced relationships between mathematics difficulty orientation, gender, race/ethnicity, and PEMC major and degree outcomes. In secondary school, the gap between boys’ and girls’ mathematics difficulty orientations were wider than gaps between White and non-White students. Mathematics difficulty orientation was positively associated with both declaring majors and earning degrees in PEMC. This relationship varied more strongly based on gender than race/ethnicity. Notably, Black women show higher gains in predicted probability to declare a mathematics-intensive major as compared to all other women, given their mathematics difficulty orientations. This study’s findings show that both gender and racial/ethnic identities may influence the relationship between mathematics difficulty orientation and postsecondary STEM outcomes.
Relationships between Anxiety, Emotional Intelligence, and Motivational Climate among Adolescent Football Players
Authors: Castro-Sánchez Manuel , Zurita-Ortega Félix , Ubago-Jiménez José Luis , González-Valero Gabriel , García-Mármol Eduardo , Chacón-Cuberos Ramón
Published: February 2019

Background: Emotional and motivational factors are fundamental in the context of sport, as they directly relate to sports performance and anxiety. Methods: The present study aimed to analyze the relationships between motivational climate (MC), emotional intelligence (EI), and anxiety within a sample of footballers playing at a low level. The sample was composed of 282 registered football players aged between 16 and 18 years old (16.96 ± 0.77), playing in the lower tier in the province of Jaen (Spain). Data were self-reported, with participants responding to the Perceived Motivational Climate in Sport Questionnaire (PMCSQ-2), the Schutte Self-Report Inventory (SSRI), and the State Trait Anxiety Inventory (STAI). Results: The results showed that footballers who reported higher levels of state anxiety and trait anxiety also demonstrated lower EI and more negatively perceived and regulated their emotions. Moreover, an ego-oriented climate was associated with higher levels of anxiety, while a task-oriented climate was related to lower levels of anxiety and higher levels of EI. No relationship was identified between the emotional aspects of young footballers and holding a motivational orientation toward an ego climate. Conclusions: Football players who more greatly perceived a task-oriented climate had higher EI and usually reported lower levels of anxiety related to sport performance. It is therefore important to promote intrinsic motivations and develop the capacity of footballers to regulate their own emotions.
Sustainability Assessment of Annual and Permanent Crops: The Inspia Model
Authors: Trivino-Tarradas Paula , Gomez-Ariza Manuel R. , Basch Gottlieb , Gonzalez-Sanchez Emilio J.
Published: February 2019

The Initiative for Sustainable Productive Agriculture (INSPIA) project promotes best management practices for agriculture, to enhance the provision of ecosystem services through better stewardship of soil and water resources while ensuring high levels of productivity. This paper presents the INSPIA methodology for the assessment of sustainability and for guiding farmers on strategic decision-making at farm level, applicable to any kind of cropland. The methodology is based on the application of 15 best management practices, which are assessed through a set of 31 basic sustainability indicators that cover the economic, social and environmental dimensions both agreed by a panel of experts. Basic indicators are then grouped into 12 aggregated indicators, to build the final INSPIA composite index. The INSPIA methodology provides farmers and advisers with a tool to understand sustainability and which, to a certain extent, serves to improve performance toward sustainability. Results are presented in three different ways: a bar diagram with the whole set of basic indicator-values; a pie chart representing the sustainability split in the aggregated indicators; and a final sustainability index. In the medium and long term, the INSPIA methodology can help to monitor and assess agricultural and environmental policy implementation, as well as help improve its decision-making processes in the future.
An Analysis of the Tourist Mobility in the Island of Lanzarote: Car Rental Versus More Sustainable Transportation Alternatives
Authors: Martín Martín José , Guaita Martínez Jose , Molina Moreno Valentín , Sartal Rodríguez Antonio
Published: February 2019

Studies have shown that certain modes of tourist development jeopardize the environment, as in the case of mass tourism, especially in areas that require special protection. The goal of this study is to apply a proposal for studying sustainability of tourist mobility to a protected space, the island of Lanzarote, which has been declared a Biosphere Reserve by UNESCO. This paper seeks to figure out the mobility patterns of tourists, the criterion used to select a mode of transportation, the attitude of tourists towards the sustainability of transport, and its environmental implications by analyzing secondary sources and interviewing tourists. The results show that the tourism model of the island is based on scattered natural resources that tourists want to enjoy in a tailor-made visit, which makes it hard to give up individual transportation. The only environmentally sustainable alternative is opting for electric vehicles with charging stations in the aforementioned tourist spots.
Effects of Kyoto Protocol on CO2 Emissions: A Five-Country Rolling Regression Analysis
Authors: Wang Chien-Ho , Ko Ming-Hui , Chen Wan-Jiun
Published: February 2019

The current study illustrated the time variance of turning points in the relationship between carbon emissions and income to resolve heated debate on the different responsibility to climate change with 1950–2010 data of five development diversity countries—three developed countries (Germany, Italy, and Japan) and one developing country (India) and one newly industrialized economy (Taiwan). The article also examines the impact of the crisis on emission. The time-varying patterns in the turning points on environmental Kuznets curves (EKCs) were observed by a rolling regression technique with 1950–2010 data regarding the per capita CO2 emissions caused by fossil fuel combustion and the incomes of the countries. Several empirical findings were revealed from this analysis. Per capita CO2 emissions commonly decreased with varying magnitudes in the five countries over time. The EKC hypothesis regarding the CO2 emissions is affirmed again in this study. The announcement effects associated with the Kyoto Protocol was evidenced. As indicated by the occurring GDP of the turning point, there is a strong reduction trend in the income level of the turning points right before the years of Kyoto Protocol; and this decreasing trend nearly ended as the Kyoto protocol approached its end, except in Germany, where the occurring income of the turning points continued to have a decreasing trend. Although the global financial crisis had its effects in the world, the impacts on carbon dioxide emissions vary across countries.
Farmers’ Market Actors, Dynamics, and Attributes: A Bibliometric Study
Authors: Figueroa-Rodríguez Katia , Álvarez-Ávila María , Hernández Castillo Fabiola , Schwentesius Rindermann Rita , Figueroa-Sandoval Benjamín
Published: February 2019

Farmers’ markets aim to bring producers and consumers together under direct marketing schemes, also known as alternative food networks, for local and sustainable production and consumption of food. A number of studies concerning this subject have been published, however, as yet no updated reviews exist that might allow us to understand the trends in research on farmers’ markets. The objective of this study was to examine the farmers’ market literature using bibliometric tools. A total of 438 peer-reviewed publications, indexed in the abstract and citation meta-database Scopus (Elsevier®), for the period of 1979 to September 24, 2018, were considered. In the second phase, publications in the area of medicine were excluded, resulting in 295 publications being analyzed for the same period. The results showed that these publications focused on three main areas: markets, health programs, and food safety. Upon exclusion of the medical publications, the remaining works focused on farmers’ market actors, dynamics, and attributes: vendors (producers and others), consumers, the community, and supporting actors and institutions (government, NGOs, individuals). Therefore, it is concluded that there is no single type of farmers’ market, nor of farmers’ market vendors or consumers. This makes the reproduction of such spaces difficult, especially when the goals are to benefit local production systems or the nutrition of the local community.
A Hybrid Unequal Clustering Based on Density with Energy Conservation in Wireless Nodes
Authors: Han Tao , Bozorgi Seyed Mostafa , Orang Ayda Valinezhad , Hosseinabadi Ali Asghar Rahmani , Sangaiah Arun Kumar , Chen Mu-Yen
Published: February 2019

The Internet of things (IoT) provides the possibility of communication between smart devices and any object at any time. In this context, wireless nodes play an important role in reducing costs and simple use. Since these nodes are often used in less accessible locations, recharging their battery is hardly feasible and in some cases is practically impossible. Hence, energy conservation within each node is a challenging discussion. Clustering is an efficient solution to increase the lifetime of the network and reduce the energy consumption of the nodes. In this paper, a novel hybrid unequal multi-hop clustering based on density (HCD) is proposed to increase the network lifetime. In the proposed protocol, the cluster head (CH) selection is performed only by comparing the status of each node to its neighboring nodes. In this new technique, the parameters involving energy of nodes, the number of neighboring nodes, the distance to the base station (BS), and the layer where the node is placed in are considered in CH selection. So, in this new and simple technique considers energy consumption of the network and load balancing. Clustering is performed unequally so that cluster heads (CHs) close to BS have more energy for data relay. Also, a hybrid dynamic–static clustering was performed to decrease overhead. In the current protocol, a distributed clustering and multi-hop routing approach was applied between cluster members (CMs), to CHs, and CHs to BS. HCD is applied as a novel assistance to cluster heads (ACHs) mechanism, in a way that a CH accepts to use member nodes with suitable state to share traffic load. Furthermore, we performed simulation for two different scenarios. Simulation results showed the reliability of the proposed method as it was resulted in a significant increase in network stability and energy balance as well as network lifetime and efficiency.
Improving Sustainable Mobile Health Care Promotion: A Novel Hybrid MCDM Method
Authors: Liu Yupeng , Yang Yutao , Liu Yue , Tzeng Gwo-Hshiung
Published: February 2019

Identifying the key influencing factors that affected users’ adoption of sustainable mobile health care and improving alternative mobile health services continuously can help ordinary consumers (especially vulnerable populations) use extensive health resources cheaply and conveniently; which can increase the quality and equity of health services; so as to promote the sustainable development of medical resources. We integrated decision making trial and evaluation laboratory (DEMETEL)-based analytic network process (DANP) and a modified VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method to form a DDANPMV (DEMATEL+ DANP + Modified VIKOR) model to examine consumers’ adoption of mobile health care. This method was developed to not only help decision-makers evaluate alternative mobile health care and determine the best option, but also use to identify and improve the performance gap of alternative products with the goal of satisfying the aspirations of consumers. Four types of mobile health care products were analyzed. The results indicate that social norms; product image; and consumer trust are three key factors in consumer adoption. The results can guide policy design and implementation. The government and enterprises should improve mobile health care through these three aspects.
Supply Chain Innovation in Scientific Research Collaboration
Authors: Yuan Chih-Hung , Wu Yenchun Jim , Tsai Kune-muh
Published: February 2019

Innovations in supply chains and logistics, which help businesses reduce their costs and meet customer needs, have become increasingly vital. In this study, we first conducted a content analysis followed by a social network analysis to systematically review 104 research papers on supply chain innovation (SCI) that were published between 1987 and 2018. The results suggest that SCI research was originally concentrated in the United States and did not receive much attention in Europe and Asia, until more recently. An analysis of collaboration networks indicates that an SCI research community has just started to form, with the United Kingdom at the center of the international collaborative network. Implications of the study and directions for future research are summarized in detail, based on the systematic literature review.
Green Activity-Based Costing Production Planning and Scenario Analysis for the Aluminum-Alloy Wheel Industry under Industry 4.0
Authors: Tsai Wen-Hsien , Chu Po-Yuan , Lee Hsiu-Li
Published: February 2019

The industrial revolution has grown to the fourth generation, or so-called Industry 4.0. The literature on Industry 4.0 is quite extensive and involves many different dimensions; however, production costs under Industry 4.0 have seldom been discussed. On the other hand, environmental problems are increasingly serious nowadays. Activity-Based Costing is a mature accounting method that can easily trace direct and indirect product costs, based on activities, as well as trace the carbon tax to products, which may lead to different product combinations, in order to reduce environment problems. Thus, the purpose of this paper is to propose a green activity-based costing production planning model under Industry 4.0. In order to make the paper more realistic, we suggest three models with five possible scenarios: normal and material cost fluctuation, material cost discount, and carbon tax with the related cost function. The Aluminum-Alloy Wheel industry was chosen as the illustrative industry to present the results. The model provides managers with a way to deal with the cost problem under Industry 4.0 and to be able to handle the environmental issues in making production decisions. This paper also provides suggestions for governments that have not considered carbon taxation.
Why Buy Free? Exploring Perceptions of Bottled Water Consumption and Its Environmental Consequences
Authors: Ballantine Paul W. , Ozanne Lucie K. , Bayfield Rachel
Published: February 2019

This exploratory study examines the consumption motivations of those consumers who choose to buy bottled water, while at the same time exploring the perceptions they hold about the potential environmental consequences of their actions. Based upon a sample of sixteen participants aged from 19 to 56, our findings revealed five main themes as to why people purchase bottled water, including: (1) Health, comprising the two subthemes of personal health and cleanliness, (2) the bottle, (3) convenience, (4) taste, and (5) self-image. Our findings also highlighted the perceptions held about the environmental consequences of bottled water consumption and the considerable challenges marketers have to address if they are to persuade consumers to consider alternatives to this consumption practice.
Nexus of Electronic Word-Of-Mouth to Social Networking Sites: A Sustainable Chatter of New Digital Social Media
Authors: Hossain Md. , Jahan Nusrat , Fang Yuantao , Hoque Saiful , Hossain Md.
Published: February 2019

The purpose of this study was to examine how electronic word-of-mouth (eWOM) communication of Facebook is influenced by social exchanges, social capital, and service quality dimensions. The online survey was conducted with a pre-tested and self-administered questionnaire, and a structural equation model was used to examine the hypothetical relationships. The results of the structural model provide insights into four key antecedents for the effective use of eWOM communication from a social capital and exchange perspective. In particular, reciprocity, tie strength, trust, and interaction service quality significantly and positively influence eWOM communication, demonstrating that social media users engage in online communication when they have a positive perception toward these psychological dimensions. The comprehensive study offers an extended theoretical perspective on eWOM literature for emerging market context and clearly examines the influencing factors of eWOM that remain to be addressed in this context. Since eWOM is widely used in social media to promote viral marketing through its powerful connection and interpersonal relationship-building capabilities, the results of the study have important implications for the practitioners with respect to sustainable advertising and business strategies.
Strengthening Sensory Sustainability Science—Theoretical and Methodological Considerations
Authors: Heinrichs Harald
Published: February 2019

Sustainability science is marked by a quarter century of conceptual and methodological development. Based on innovative approaches, such as transformative transdisciplinarity, sustainability science makes the claim to contribute solution-oriented knowledge to sustainable development. Despite successful expansion and promising experiences, there are limitations to be considered. This article argues that the multisensorial reality of human life in socio-material practices has not been adequately captured in sustainability science. Theoretical approaches addressing the sensoriality and corporality of human existence as well as methodological approaches of ethnography and arts-based research to access relevant human dimensions beyond the cognitive are discussed, and the perspective of sensory sustainability science is sketched.
Ethics to Intersect Civic Participation and Formal Guidance
Authors: Bohle Martin , Nauen Cornelia E. , Marone Eduardo
Published: February 2019

Sound governance arrangement in socio-ecological systems (human niche) combines different means of sense-making. The sustainability of human niche-building depends on the governability of the social-ecological systems (SES) forming the niche. Experiences from small-scale marine fisheries and seabed mining illustrate how ethical frameworks, civic participation and formalised guidance combine in the context of a “blue economy”. Three lines of inquiries contextualise these experiences driving research questions, such as “what is the function of ethics for governability?” First, complex-adaptive SES are featured to emphasise the sense-making feedback loop in SES. Actors are part of this feedback loop and can use different means of sense-making to guide their actions. Second, the “Voluntary Guidelines for Sustainable Small-Scale Fisheries” and geoethical thinking are featured to highlight the relevance of actor-centric concepts. Third, Kohlberg’s model of “stages of moral adequacy” and the United Nations Convention on the Law of the Sea (UNCLOS) are used to show how to strengthen actor-centric virtue-ethics. Combining these lines of inquiry leads to the conclusion that ethical frameworks, civic participation and formalised guidance, when put in a mutual context, support governability and multi-actor/level policy-making. Further research could explore how creativity can strengthen civic participation, a feature only sketched here.
Post-1990s College Students Academic Sustainability: The Role of Negative Emotions, Achievement Goals, and Self-efficacy on Academic Performance
Authors: Liu Xinqiao , Gao Xueheng , Ping Siqing
Published: February 2019

In 1982, the “one-child policy” was implemented by China’s Constitution, which led to the majority of post-1990s college students in China being the only child in their family. Unique characteristics have been demonstrated in psychological development of post-1990s Chinese college students due to the lack of sibling companionship, and the relationship between their psychological state and academic performance can affect their future academic sustainability. This paper used Beijing College Students Panel Survey (BCSPS) data to study the role of negative emotions, achievement goals, and academic self-efficacy on academic performance and gives a panoramic description of the China’s post-1990s college students’ psychological states based on the four-year data of more than 2000 college students who enrolled in 2008. We then used regression analysis and a two-way fixed effect model to study the effects of the psychological state on academic performance. The research conclusions of the study are as follows: (1) The levels of negative emotions, achievement goals, and academic self-efficacy vary according to the grade and gender of college students; (2) among all negative emotions discussed, only anxiety presents a significant predictive effect on academic performance, while the effect of stress and depression is not significant; (3) the presence of level of mastery–approach goals is higher than the other three achievement goals, and college students’ academic self-efficacy keeps decreasing from freshman to junior year; (4) performance–approach goals and academic self-efficacy are identified as having a significant promoting effect on academic performance; (5) mastery–avoidance goals and performance–avoidance goals are proven to have a negative effect on academic performance. This paper discusses the contribution of the psychological sustainability and sustainable development to college students’ academic performance from a primary intervention perspective. We believe that it is feasible to improve academic achievement by improving noncognitive factors, such as mental state, to achieve academic sustainability.
A Note on Sign-Changing Solutions to the NLS on the Double-Bridge Graph
Authors: Noja Diego , Rolando Sergio , Secchi Simone
Published: February 2019

We study standing waves of the NLS equation posed on the double-bridge graph: two semi-infinite half-lines attached at a circle. At the two vertices, Kirchhoff boundary conditions are imposed. We pursue a recent study concerning solutions nonzero on the half-lines and periodic on the circle, by proving some existing results of sign-changing solutions non-periodic on the circle.
Noether-Like Operators and First Integrals for Generalized Systems of Lane-Emden Equations
Authors: Farooq M. Umar
Published: February 2019

Coupled systems of Lane–Emden equations are of considerable interest as they model several physical phenomena, for instance population evolution, pattern formation, and chemical reactions. Assuming a complex variational structure, we classify the generalized system of Lane–Emden type equations in relation to Noether-like operators and associated first integrals. Various forms of functions appearing in the considered system are taken, and it is observed that the Noether-like operators form an Abelian algebra for the corresponding Euler–Lagrange-type systems. Interestingly, we find that in many cases, the Noether-like operators satisfy the classical Noether symmetry condition and become the Noether symmetries. Moreover, we observe that the classical Noetherian integrals and the first integrals we determine using the complex Lagrangian approach turn out to be the same for the underlying system of Lane–Emden equations.
Reliability Enhancement of Edge Computing Paradigm Using Agreement
Authors: Wang Shu-Ching , Hsiung Wei-Shu , Hsieh Chia-Fen , Tsai Yao-Te
Published: February 2019

Driven by the vision of the Internet of Things (IoT), there has been a dramatic shift in mobile computing in recent years from centralized mobile cloud computing (MCC) to mobile edge computing (MEC). The main features of MECs are to promote mobile computing, network control, and storage to the edge of the network in order to achieve computationally intensive and latency-critical applications on resource-constrained mobile devices. Therefore, MEC is proposed to enable computing directly at the edge of the network, which can deliver new applications and services, especially for the IoT. In order to provide a highly flexible and reliable platform for the IoT, a MEC-based IoT platform (MIoT) is proposed in this study. Through the MIoT, the information asymmetrical symmetry between the consumer and producer can be reduced to a certain extent. Because of the IoT platform, fault tolerance is an important research topic. In order to deal with the impact of a faulty component, it is important to reach an agreement in the event of a failure before performing certain special tasks. For example, the initial time of all devices and the time stamp of all applications should be the same in a smart city before further processing. However, previous protocols for distributed computing were not sufficient for MIoT. Therefore, in this study, a new polynomial time and optimal algorithm is proposed to revisit the agreement problem. The algorithm makes all fault-free nodes decide on the same initial value with minimal rounds of message exchanges and tolerate the maximal number of allowable faulty components in the MIoT.
An Overview on the Standing Waves of Nonlinear Schrödinger and Dirac Equations on Metric Graphs with Localized Nonlinearity
Authors: Borrelli William , Carlone Raffaele , Tentarelli Lorenzo
Published: February 2019

We present a brief overview of the existence/nonexistence of standing waves for the NonLinear Schrödinger and the NonLinear Dirac Equations (NLSE/NLDE) on metric graphs with localized nonlinearity. First, we focus on the NLSE (both in the subcritical and the critical case) and, then, on the NLDE highlighting similarities and differences with the NLSE. Finally, we show how the two equations are related in the nonrelativistic limit by the convergence of the bound states.
Type-2 Multi-Fuzzy Sets and Their Applications in Decision Making
Authors: Kar Mohuya B. , Roy Bikashkoli , Kar Samarjit , Majumder Saibal , Pamucar Dragan
Published: February 2019

In a real-life scenario, it is undoable and unmanageable to solve a decision-making problem with the single stand-alone decision-aid method, expert assessment methodology or deterministic approaches. Such problems are often based on the suggestions or feedback of several experts. Usually, the feedback of these experts are heterogeneous imperfect information collected from various more or less reliable sources. In this paper, we introduce the concept of multi-sets over type-2 fuzzy sets. We have tried to propose an extension of type-1 multi-fuzzy sets into a type-2 multi-fuzzy set (T2MFS). After defining T2MFS, we discuss the algebraic properties of these sets including set-theoretic operations such as complement, union, intersection, and others with examples. Subsequently, we define two distance measures over these sets and illustrate a decision-making problem which uses the idea of type-2 multi-fuzzy sets. Furthermore, an application of a medical diagnosis system based on multi-criteria decision making of T2MFS is illustrated with a real-life case study.
Algebraic Structures of Neutrosophic Triplets, Neutrosophic Duplets, or Neutrosophic Multisets
Authors: Smarandache Florentin , Zhang Xiaohong , Ali Mumtaz
Published: February 2019

Neutrosophy (1995) is a new branch of philosophy that studies triads of the form (, , ), where  is an entity (i [...]