bluuebunny/crossref_metadata_2025 huggingface dataset:
Fabrication of Poly(butylene succinate)/Carbon Black Nanocomposite Foams with Good Electrical Conductivity and High Strength by a Supercritical CO2 Foaming Process
Authors: Chen Zhou , Hu Junfeng , Ju Jiajun , Kuang Tairong
Published: November 2019

Lightweight, high-strength and electrically conductive poly(butylene succinate) (PBS)/ carbon black (CB) nanocomposite foams with a density of 0.107–0.344 g/cm3 were successfully fabricated by a solid-state supercritical CO2 (ScCO2) foaming process. The morphology, thermal and dynamic mechanical properties, and rheological behavior of the PBS/CB nanocomposites were studied. The results indicate that the CB nanofiller was well dispersed in the PBS matrix and the presence of a proper CB nanofiller can accelerate the rate of crystallization, improve the thermal stability, enhance the stiffness, and increase the complex viscosity of PBS/CB nanocomposites. These improved properties were found to play an important role in the foaming process. The results from foaming experiments showed that the PBS/CB nanocomposite foams had a much smaller cell size, a higher cell density, and a more uniform cell morphology as compared to neat PBS foams. Furthermore, the PBS/CB nanocomposite foams also possessed low density (0.107–0.344 g/cm3), good electrical conductivity (~0.45 S/cm at 1.87 vol % CB loading), and improved compressive strength (108% increase), which enables them to be used as lightweight and high-strength functional materials.
Flexible Conductive Polymer Film Grafted with Azo-Moieties and Patterned by Light Illumination with Anisotropic Conductivity
Authors: Kalachyova Yevgeniya , Guselnikova Olga , Hnatowicz Vladimir , Postnikov Pavel , Švorčík Vaclav , Lyutakov Oleksiy
Published: November 2019

In this work, we present the method for the creation of an anisotropic electric pattern on thin poly(3,4-ethylenedioxythiophene): polystyrene sulfonate (PEDOT:PSS) films through PSS grafting by azo-containing moieties followed by light-induced polymers redistribution. Thin PEDOT:PSS films were deposited on the flexible and biodegradable polylactic acid (PLLA) substrates. The light-sensitive azo-groups were grafted to PSS using the diazonium chemistry followed by annealing in methanol. Local illumination of azo-grafted PEDOT:PSS films through the lithographic mask led to the conversion of azo-moieties in Z-configuration and further creation of the lateral gradient of azo-isomers along the film surface. The concentration gradient led to the migration of PSS away from the illuminated area, increasing the PEDOT chains’ concentration and the corresponding increase of local electrical conductivity in the illuminated place. Utilization of mask with linear pattern results in the appearance of conductive PEDOT-rich and non-conductive PSS-rich lines on the film surface, and final, lateral anisotropy of electric properties. Our work gives an optical lithography-based alternative to common methods for the creation of anisotropic electric properties, based on the spatial confinement of conductive polymer structures or their mechanical strains.
A Mechanistic Model of Mass Transfer in the Extraction of Bioactive Compounds from Intact Sorghum Pericarp
Authors: Susanti Devi Yuni , Sediawan Wahyudi Budi , Fahrurrozi Mohammad , Hidayat Muslikhin
Published: November 2019

The extraction of phytochemical compounds from intact red sorghum grains was developed as an alternative process for producing bioactive material in the pharmaceutical industry. A mechanistic model is needed to better understand the process and enable predictive simulations for designing commercial-scale extraction systems. This paper presents a mathematical model for predicting phytochemical concentrations in the solvent and inside the pericarp of the grain at different positions during the extraction. The model is based on the mass transfer mechanism from inside the pericarp to its solid surface by diffusion, and then from the surface to a solvent during the extraction of bioactive compounds. It was numerically solved while using finite-difference approximation. The parameters considered were effective diffusivity inside the pericarp (Dep), mass transfer coefficient from the pericarp surface to the solvent (kc), and distribution coefficient (H). The model simulates the extraction performance, including the yield and bioactive compounds’ concentrations in the extract and inside the pericarp at various positions and times. A sensitivity analysis of the changes in each involved parameter provided sufficient information for increasing the performance of the model. A validation test that compared the results of the simulation with those of established analytical solutions showed that the model has high accuracy. Hence, the model can be applied in quantitative evaluations to improve productivity in the pharmaceutical industry.
Modern Modeling Paradigms Using Generalized Disjunctive Programming
Authors: Chen Qi , Grossmann Ignacio
Published: November 2019

Models involving decision variables in both discrete and continuous domain spaces are prevalent in process design. Generalized Disjunctive Programming (GDP) has emerged as a modeling framework to explicitly represent the relationship between algebraic descriptions and the logical structure of a design problem. However, fewer formulation examples exist for GDP compared to the traditional Mixed-Integer Nonlinear Programming (MINLP) modeling approach. In this paper, we propose the use of GDP as a modeling tool to organize model variants that arise due to characterization of different sections of an end-to-end process at different detail levels. We present an illustrative case study to demonstrate GDP usage for the generation of model variants catered to process synthesis integrated with purchasing and sales decisions in a techno-economic analysis. We also show how this GDP model can be used as part of a hierarchical decomposition scheme. These examples demonstrate how GDP can serve as a useful model abstraction layer for simplifying model development and upkeep, in addition to its traditional usage as a platform for advanced solution strategies.
New Aspects on the Modeling of Dithiolactone-Mediated Radical Polymerization of Vinyl Monomers
Authors: Benitez-Carreón Anete Joceline , Soriano-Moro Jesús Guillermo , Vivaldo-Lima Eduardo , Guerrero-Santos Ramiro , Penlidis Alexander
Published: November 2019

A kinetic model for the dithiolactone-mediated radical polymerization of vinyl monomers based on the persistent radical effect and reversible addition (negligible fragmentation) was used to calculate the polymerization rate and describe molar mass development in the polymerization of methyl methacrylate at 60 °C, using 2,2-azobisisobutyronitrile (AIBN) as an initiator, as well as dihydro-5-phenyl-2(3H)-thiophenethione (DTL1) and dihydro-2(3H)-thiophenethione (DTL2) as controllers. The model was implemented in the PREDICI commercial software. A good agreement between experimental data and model predictions was obtained.
Theoretical Analysis of Forced Segmented Temperature Gradients in Liquid Chromatography
Authors: Hayat Adnan , An Xinghai , Qamar Shamsul , Warnecke Gerald , Seidel-Morgenstern Andreas
Published: November 2019

An equilibrium model is applied to study the effect of forced temperature gradients introduced through heat exchange via specific segments of the wall of a chromatographic column operating with a liquid mobile phase. For illustration of the principle, the column is divided into two segments in such a manner that the first segment is kept at a fixed reference temperature, while the temperature of the second segment can be changed stepwise through fixed heating or cooling over the column wall to modulate the migration speeds of the solute concentration profiles. The method of characteristics is used to obtain the solution trajectories analytically. It is demonstrated that appropriate heating or cooling in the second segment can accelerate or decelerate the specific concentration profiles in order to improve certain performance criteria. The results obtained verify that the proposed analysis is well suited to evaluate the application of forced segmented temperature gradients. The suggested gradient procedure provides the potential to reduce the cycle time and, thus, improving the production rate of the chromatographic separation process compared to conventional isothermal (isocratic) operation.
Robot-Assisted Floor Surface Profiling Using Low-Cost Sensors
Authors: Wilson Scott , Potgieter Johan , Arif Khalid Mahmood
Published: November 2019

Low cost and accurate 3D surface profiling can help in numerous industry applications including inspection tasks, cleaning, minimizing bumps in navigation of non-uniform terrain, aid navigation, and road/pavement condition analysis. However, most of the available systems are costly or inaccessible for widespread use. This research presents investigation into the capability of cheap and accessible sensors to capture the floor surface profile information. A differential drive robotic platform has been developed to perform testing and conduct the research. 2D localization methods are extrapolated into 3D for the floor capturing process. Two different types of sensors, a 2D laser scanner and an RGB-D camera, are used for comparison of the floor profile capture ability. The robotic system is able to successfully capture the floor surface profile of a number of different type floors such as carpet, asphalt, and a coated floor. A key finding is that the surface itself is a significant factor on the measured profile, i.e., dirt or other materials can cause false height measurements. Overall, the methodology has proved a successful real time solution for creating a point cloud of the floor surface.
Satellite Retrieval of Downwelling Shortwave Surface Flux and Diffuse Fraction under All Sky Conditions in the Framework of the LSA SAF Program (Part 2: Evaluation)
Authors: Carrer Dominique , Moparthy Suman , Vincent Chloé , Ceamanos Xavier , C. Freitas Sandra , Trigo Isabel F.
Published: November 2019

High frequency knowledge of the spatio-temporal distribution of the downwelling surface shortwave flux (DSSF) and its diffuse fraction (fd) at the surface is nowadays essential for understanding climate processes at the surface–atmosphere interface, plant photosynthesis and carbon cycle, and for the solar energy sector. The European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility for Land Surface Analysis operationally delivers estimation of the MDSSFTD (MSG Downwelling Surface Short-wave radiation Fluxes—Total and Diffuse fraction) product with an operational status since the year 2019. The method for retrieval was presented in a companion paper. Part 2 now focuses on the evaluation of the MDSSFTD algorithm and presents a comparison of the corresponding outputs, i.e., total DSSF and diffuse fraction (fd) components, against in situ measurements acquired at four Baseline Surface Radiation Network (BSRN) stations over a seven-month period. The validation is performed on an instantaneous basis. We show that the satellite estimates of DSSF and fd meet the target requirements defined by the user community for all-sky (clear and cloudy) conditions. For DSSF, the requirements are 20 Wm−2 for DSSF < 200 Wm−2, and 10% for DSSF ≥ 200 Wm−2. The mean bias error (MBE) and relative mean bias error (rMBE) compared to the ground measurements are 3.618 Wm−2 and 0.252%, respectively. For fd, the requirements are 0.1 for fd < 0.5, and 20% for fd ≥ 0.5. The MBE and rMBE compared to the ground measurements are −0.044% and −17.699%, respectively. The study also provides a separate analysis of the product performances for clear sky and cloudy sky conditions. The importance of representing the cloud–aerosol radiative coupling in the MDSSFTD method is discussed. Finally, it is concluded that the quality of the aerosol optical depth (AOD) forecasts currently available is accurate enough to obtain reliable diffuse solar flux estimates. This quality of AOD forecasts was still a limitation a few years ago.
Category-Sensitive Domain Adaptation for Land Cover Mapping in Aerial Scenes
Authors: Fang Bo , Kou Rong , Pan Li , Chen Pengfei
Published: November 2019

Since manually labeling aerial images for pixel-level classification is expensive and time-consuming, developing strategies for land cover mapping without reference labels is essential and meaningful. As an efficient solution for this issue, domain adaptation has been widely utilized in numerous semantic labeling-based applications. However, current approaches generally pursue the marginal distribution alignment between the source and target features and ignore the category-level alignment. Therefore, directly applying them to land cover mapping leads to unsatisfactory performance in the target domain. In our research, to address this problem, we embed a geometry-consistent generative adversarial network (GcGAN) into a co-training adversarial learning network (CtALN), and then develop a category-sensitive domain adaptation (CsDA) method for land cover mapping using very-high-resolution (VHR) optical aerial images. The GcGAN aims to eliminate the domain discrepancies between labeled and unlabeled images while retaining their intrinsic land cover information by translating the features of the labeled images from the source domain to the target domain. Meanwhile, the CtALN aims to learn a semantic labeling model in the target domain with the translated features and corresponding reference labels. By training this hybrid framework, our method learns to distill knowledge from the source domain and transfers it to the target domain, while preserving not only global domain consistency, but also category-level consistency between labeled and unlabeled images in the feature space. The experimental results between two airborne benchmark datasets and the comparison with other state-of-the-art methods verify the robustness and superiority of our proposed CsDA.
Electro-Mechanical Ionic Channel Modeling for Uterine Contractions and Oxytocin Effect during Pregnancy
Authors: Lin Yiqi , Zhang Mengxue , La Rosa Patricio S. , Wilson James D. , Nehorai Arye
Published: November 2019

Uterine contractions during normal pregnancy and preterm birth are an important physiological activity. Although the cause of preterm labor is usually unknown, preterm birth creates very serious health concerns in many cases. Therefore, understanding normal birth and predicting preterm birth can help both newborn babies and their families. In our previous work, we developed a multiscale dynamic electrophysiology model of uterine contractions. In this paper, we mainly focus on the cellular level and use electromyography (EMG) and cell force generation methods to construct a new ionic channel model and a corresponding mechanical force model. Specifically, the ionic channel model takes into consideration the knowledge of individual ionic channels, which include the electrochemical and bioelectrical characteristics of individual myocytes. We develop a new sodium channel and a new potassium channel based on the experimental data from the human myometrium and the average correlations are 0.9946 and 0.9945, respectively. The model is able to generate the single spike, plateau type and bursting type of action potentials. Moreover, we incorporate the effect of oxytocin on changing the properties of the L-type and T-type calcium channels and further influencing the output action potentials. In addition, we develop a mechanical force model based on the new ionic channel model that describes the detailed ionic dynamics. Our model produces cellular mechanical force that propagates to the tissue level. We illustrate the relationship between the cellular mechanical force and the intracellular ionic dynamics and discuss the relationship between the application of oxytocin and the output mechanical force. We also propose a simplified version of the model to enable large scale simulations using sensitivity analysis method. Our results show that the model is able to reproduce the bioelectrical and electromechanical characteristics of uterine contractions during pregnancy.
General Mental Health Is Associated with Gait Asymmetry
Authors: Nagano Hanatsu , Sarashina Eri , Sparrow William , Mizukami Katsuyoshi , Begg Rezaul
Published: November 2019

Wearable sensors are being applied to real-world motion monitoring and the focus of this work is assessing health status and wellbeing. An extensive literature has documented the effects on gait control of impaired physical health, but in this project, the aim was to determine whether emotional states associated with older people’s mental health are also associated with walking mechanics. If confirmed, wearable sensors could be used to monitor affective responses. Lower limb gait mechanics of 126 healthy individuals (mean age 66.2 ± 8.38 years) were recorded using a high-speed 3D motion sensing system and they also completed a 12-item mental health status questionnaire (GHQ-12). Mean step width and minimum foot-ground clearance (MFC), indicative of tripping risk, were moderately correlated with GHQ-12. Ageing and variability (SD) of gait parameters were not significantly correlated with GHQ-12. GHQ-12 scores were, however, highly correlated with left-right gait control, indicating that greater gait symmetry was associated with better mental health. Maintaining good mental health with ageing may promote safer gait and wearable sensor technologies could be applied to gait asymmetry monitoring, possibly using a single inertial measurement unit attached to each shoe.
Comparative Analysis between Error-State and Full-State Error Estimation for KF-Based IMU/GNSS Integration against IMU Faults
Authors: Liu Wei , Song Dan , Wang Zhipeng , Fang Kun
Published: November 2019

Considering the inertial measurement unit (IMU) faults risk of an unmanned aerial vehicle (UAV), this paper provides an analysis of the error overboundings of position estimation in a tightly coupled IMU/global navigation satellite system (GNSS) integrated architecture under the IMU fault conditions using an error-state EKF-based approach and provides a comparison to a recently published EKF-based full state method. Simulation results show that both the error overboundings of the error-state and full-state EKFs can fit the state error against the IMU faults, but the error-state EKF is more suitable for UAV navigation system integrity assurance due to its higher calculation eciency. This study will be extended to the integrity monitoring of multisensor systems.
A Simply Equipped Fourier Ptychography Platform Based on an Industrial Camera and Telecentric Objective
Authors: Zhang Shaohui , Zhou Guocheng , Wang Ying , Hu Yao , Hao Qun
Published: November 2019

Fourier ptychography microscopy (FPM) is a recently emerged computational imaging method, which combines the advantages of synthetic aperture and phase retrieval to achieve super-resolution microscopic imaging. FPM can bypass the diffraction limit of the numerical aperture (NA) system and achieve complex images with wide field of view and high resolution (HR) on the basis of the existing microscopic platform, which has low resolution and wide field of view. Conventional FPM platforms are constructed based on basic microscopic platform and a scientific complementary metal–oxide–semiconductor (sCMOS) camera, which has ultrahigh dynamic range. However, sCMOS, or even the microscopic platform, is too expensive to afford for some researchers. Furthermore, the fixed microscopic platform limits the space for function expansion and system modification. In this work, we present a simply equipped FPM platform based on an industrial camera and telecentric objective, which is much cheaper than sCMOS camera and microscopic platform and has accurate optical calibration. A corresponding algorithm was embedded into a conventional FP framework to overcome the low dynamic range of industrial cameras. Simulation and experimental results showed the feasibility and good performance of the designed FPM platform and algorithms.
Are Smart-City Projects Citizen-Centered?
Authors: Sánchez-Teba Eva M. , Bermúdez-González Guillermo J.
Published: November 2019

Smart cities have become a new urban model for thinking and designing cities in the connected society. It is time to ask ourselves what kind of city we want and need. There is still a long way to go in relation to the role of citizenship in the field of smart cities. This autoethnography reveals different contradictions found during the preparation of my doctoral thesis, which studied the citizens’ perception of smart city policies in a city in southern Spain, in my double role as a doctoral student/researcher and public manager. Many of the statements and conclusions of different scientific research contrasted with the reality that I was experiencing in my daily work. My conclusions can help in the current debate on which cities we want to build at a time when the population is concentrated in cities and where it is necessary to respond to not only the economic, but also the social and environmental problems posed by sustainability
Exploring the Relationship between Urbanization and the Eco-Environment: A Case Study of Beijing
Authors: Huang Yi , Qiu Qianqian , Sheng Yehua , Min Xiangqiang , Cao Yuwei
Published: November 2019

Beijing is one of the most developed cities in China and has experienced a series of environmental problems. In accordance with the Major Function Zone planning, Beijing is divided into four zones in an attempt to coordinate development between urban areas and the eco-environment. Classic coupling model uses statistical data to evaluate the interactions of these two subsystems; however, it lacks the capability to express dynamic changes to land cover. Thus, we extracted land cover data from Landsat images and examined the urbanization and eco-environment level as well as the coupling coordination in Beijing and its functional zones. The main conclusions are as follows. (1) Between 2001 and 2011, both urbanization and the eco-environment level in Beijing and its functional zones grew steadily. Different zones coordinated together according to their own characteristics, and the overall coupling coordination of the city transformed from the “basically balanced” to the “superiorly balanced” stage of development. (2) After 2011, the condition of the eco-environment worsened in Beijing and in most of the function zones, while the coordination between increased urbanization and the worsened eco-environment may be a result of environmental lag. This study integrated land cover data into the coupling mode and fully utilized the advantages of spatiotemporal analysis and the coupling model. In other words, the spatiotemporal analysis explains the land cover changes visually over the research period, while the coupling model explores the interaction mechanisms between urbanization and the eco-environment. The land cover data enriches the coupling theory and provides a reference for evaluating the effectiveness of local development policy.
Impact of Population and Workforce Aging on Economic Growth: Case Study of Taiwan
Authors: Huang Wen-Hsin , Lin Yen-Ju , Lee Hsien-Feng
Published: November 2019

Taiwan’s population is aging at a fast pace, and its aged society is expected to transition into a hyper-aged society within eight years. Population aging has been a matter of international concern; however, there remain differing views about its economic impact. Thus, this study aims to examine the impact of population and workforce aging on Taiwan using quarterly data from 1981–2017. The empirical results demonstrate that an aging workforce has a significantly positive impact on the rate of economic growth. However, the old-age dependency ratio has a significantly negative effect on economic growth. The empirical findings indicate that human capital is essential for total factor productivity (TFP) growth and that workforce and population aging mainly impact productivity through TFP. Accounting for policy factors, increasing the supply of the eldercare workforce and foreign manpower contribute toward countering the negative impact of an aging population on national economic growth. Policies on retirement, pension systems, health care, and human capital accumulation that target the aged population are discussed, accompanied by policy suggestions.
Priolog: Mining Important Logs via Temporal Analysis and Prioritization
Authors: Tak Byungchul , Park Seorin , Kudva Prabhakar
Published: November 2019

Log analytics are a critical part of the operational management in today’s IT services. However, the growing software complexity and volume of logs make it increasingly challenging to mine useful insights from logs for problem diagnosis. In this paper, we propose a novel technique, Priolog, that can narrow down the volume of logs into a small set of important and most relevant logs. Priolog uses a combination of log template temporal analysis, log template frequency analysis, and word frequency analysis, which complement each other to generate an accurately ranked list of important logs. We have implemented this technique and applied to the problem diagnosis task of the popular OpenStack platform. Our evaluation indicates that Priolog can effectively find the important logs that hold direct hints to the failure cause in several scenarios. We demonstrate the concepts, design, and evaluation results using actual logs.
Is Sustainable Economic Development Possible Thanks to the Deployment of ICT?
Authors: Fernández-Portillo Antonio , Almodóvar-González Manuel , Coca-Pérez José Luís , Jiménez-Naranjo Héctor Valentín
Published: November 2019

Achieving sustainable economic development is one of humanity’s greatest challenges, and, in this regard, the United Nations has promoted a line of research based on sustainable economic development. In view of this, our study focused on the sustainable economic development of nations, specifically, development through the deployment of information and communication technologies (ICTs). Academic researchers recognize the importance of ICT for economic and sustainable development, but there is controversy in the literature regarding two opposing points of view. First, there is a view that advances in ICT support Gross Domestic Product (GDP) growth, while, on the other hand, the view is that there is no relationship between these two factors. In view of this, we conducted a study where the objective was to determine whether investing in ICT contributes to sustainable economic development (measured by the GDP per capita) of European Union countries. We used Eurostat data and applied the partial least-squares (PLS) method to address the study. This approach allowed us to analyze European Union countries from 2014 to 2017, using fairly rigorous data. The most outstanding result was that ICT accounted for most of the explained variance in GDP per capita (GDPpp), and, specifically, the most representative indicator was “digital public services.” Therefore, we concluded that investing in the deployment of ICT supports the sustainable economic development of European Union countries. These countries should focus on investing in improved connectivity in areas with poor communications, as well as in training area inhabitants in the use and development of ICT to obtain greater development using these tools and technologies.
Temporal Characteristics of Waterfronts in Wuhan City and People’s Behavioral Preferences Based on Social Media Data
Authors: Wu Jing , Chen Xirui , Chen Shulin
Published: November 2019

The appeal and vibrancy of urban waterfronts are catalysts for urban progress and sustainable urban development. This study aims to thoroughly explore the temporal characteristics of waterfront vibrancy and explore people’s behavioral preferences for various types of waterfronts at various times. On the basis of social media data, this study uses the seasonal index analysis method to classify waterfronts. Then, the kernel density estimation was used to analyze the spatial structure of different types of waterfronts. Finally, temporally weighted regression was used to indicate people’s preferences for various types of waterfronts. In general, results show the different temporal characteristics of users in waterfronts at different times and their behavioral preferences for waterfronts as the reasons behind these preface characteristics. First, on weekdays, people tend to visit daily waterfronts close to residences, and people find it convenient to walk after 18:00 and engage in recreational activities dominated by consumption and exercise, which reach a peak at 22:00–24:00. Second, on weekends, people prefer the weekend waterfronts with complete entertainment facilities and cultural themes. The natural seasonal waterfronts with seasonal landscapes attract people in various seasons, such as spring and autumn, whereas the social seasonal waterfront may be more attractive during high seasons, especially in March and June, due to big water events or nearby colleges and universities. Therefore, the government should improve the facilities of various types of waterfronts to satisfy people’s preferences at different times and help in proposing targeted suggestions with reference to future city waterfront planning and space design, contributing to the waterfronts’ vitality improvement, urban features, and promotion of urban sustainable development.
How to Achieve Sustainable Development of Mobile Payment through Customer Satisfaction—The SOR Model
Authors: Chen Su-Chang , Chung Kuo Cheng , Tsai Ming Yueh
Published: November 2019

In recent years, due to smartphones being more popular and the wireless network infrastructure improving, individuals are no longer constrained by the workflow on personal computers. Therefore, business operators are constantly launching new mobile application services for everyday life. This study mainly explores how mobile payment adopts the determinants, and adds utilitarian value, hedonic value and salesperson performance as antecedences to understand whether utilitarian value, hedonic value and salesperson behavior can affect satisfaction through determinants, as well as to understand consumers’ mobile payment usage intention through the stimulus-response model. The research objectives of this study are mainly mobile payment users in Taiwan. 425 valid questionnaires were received. This study uses a structural equation model to analyze the data. This study’s results indicate that utilitarian value, hedonic value and salesperson selling behaviors positively affects customers’ satisfaction, which customers’ satisfaction positively affects mobile payment usage intention. The research results could provide mobile payment operators with references in the design and implementation of the mobile payment and application process, thereby accelerating the popularization of mobile payment.
Daytime or Overnight Deliveries? Perceptions of Drivers and Retailers in São Paulo City
Authors: Dias Pedro A. P. , Yoshizaki Hugo , Favero Patricia , Vieira Jose Geraldo Vidal
Published: November 2019

This research aims to analyze the perception of logistics operators and retailers regarding freight deliveries in the city of São Paulo. Based on a survey applied to 100 logistics operators and 84 retailers, the data were analyzed by descriptive statistics and multiple correspondence analysis (MCA) was used to investigate the logistics efficiency of off-hours deliveries (OHD) and to indicate issues when carrying out OHD. From that sample, noise appears as the most critical issue of OHD for retailers. From the results, most logistics operators and retailers prefer to deliver cargo at night. The advantages of making OHD are the ability to check/store goods, the accuracy in the delivery schedule due to traffic conditions, and the ease of parking a vehicle to offload goods. Public authorities should improve the infrastructure to receive goods, including public lighting conditions and sidewalks. The correspondence analysis method showed that the level of customer service quality depends on the punctuality of the trucks and the ability to check and store goods. Furthermore, by highlighting the logistics efficiency and issues related to daytime and overnight deliveries by carriers and receivers, it can guide public polices and initiatives of other companies, an aspect that has been lacking in the literature.
Improvement on Social Representation of Climate Change through a Knowledge-Based MOOC in Spanish
Authors: Ferrari Enzo , Ballegeer Anne-Marie , Fuertes Miguel Angel , Herrero Pablo , Delgado Laura , Corrochano Diego , Andrés-Sánchez Santiago , Marc Bisquert Kylyan , Garcia-Vinuesa Antonio , Meira Pablo , Martinez Fernando , Ruiz Camilo
Published: November 2019

Climate Change is the most important threat to our society and all species on Earth. Large alterations in the climate are affecting every aspect of our society and in order to limit this impact we must decarbonize the economy before 2050. Although science presents solid evidence on the magnitude of the problem and outlines precisely the consequences, people do not act accordingly and do not consider this issue a priority for their survival. The reason behind this paradox might be a non-appropriate Social Representation of Climate Change in society as the Social Representation conditions and forms the response of the society. In this paper, we extend previous investigations of how this Social Representation is formed in order to find ways to improve it through a Massive Online Open Course on the Science of Climate Change. Using a validated questionnaire, we investigated the knowledge dimension of the Social Representation of Climate Change in a group of students of a MOOC on Climate Change. A pre- and posttest revealed general improvements in all the categories that were considered in this study. A detailed analysis showed different degrees of improvement for different groups, providing new insights in the efficiency of knowledge-based online courses. Well designed Massive Online Open Courses, based on scientific evidence, targeted to the general public might improve the Social Representation of Climate Change, which may in turn trigger awareness and an effective mobilization to address this important and urgent topic.
Emerging Urban Forests: Opportunities for Promoting the Wild Side of the Urban Green Infrastructure
Authors: Kowarik Ingo , Hiller Anne , Planchuelo Greg , Seitz Birgit , von der Lippe Moritz , Buchholz Sascha
Published: November 2019

Many cities aim to increase urban forest cover to benefit residents through the provision of ecosystem services and to promote biodiversity. As a complement to traditional forest plantings, we address opportunities associated with “emerging urban forests” (i.e., spontaneously developing forests in cities) for urban biodiversity conservation. We quantified the area of successional forests and analyzed the species richness of native and alien plants and of invertebrates (carabid beetles, spiders) in emerging forests dominated by alien or native trees, including Robinia pseudoacacia, Acer platanoides, and Betula pendula. Emerging urban forests were revealed as shared habitats of native and alien species. Native species richness was not profoundly affected by the alien (co-)dominance of the canopy. Instead, native and alien plant species richnesses were positively related. Numbers of endangered plants and invertebrates did not differ between native- and alien-dominated forest patches. Patterns of tree regeneration indicate different successional trajectories for novel forest types. We conclude that these forests (i) provide habitats for native and alien species, including some endangered species, (ii) allow city dwellers to experience wild urban nature, and (iii) support arguments for adapting forests to dynamic urban environments. Integrating emerging urban forests into the urban green infrastructure is a promising pathway to sustainable cities and can complement traditional restoration or greening approaches.
An Extensive Investigation of an Eco-Approach Controller under a Partially Connected and Automated Vehicle Environment
Authors: Jiang Huifu , Hu Jia , Park Byungkyu Brian , Wang Meng , Zhou Wei
Published: November 2019

This study evaluated the performance of an eco-approach control system at signalized intersections under a partially connected and automated vehicle (CAV) environment. This system has the first eco-approach controller able to function with the existence of surrounding human-driven traffic. A previous evaluation only confirmed its benefits. The purpose of this study was to conduct a further extensive test on the controller to identify room for improvement. Two different networks were tested, including an isolated signalized intersection and a corridor with two signalized intersections. The measures of effectiveness (MOEs) adopted were throughput and fuel consumption. All the before-and-after MOEs were compared using t-tests. The results indicate that the controller generally improved the fuel efficiency without harm to the mobility, and its environmental performance was affected by the minimum CAV speed, green ratio, congestion level, and marker penetration rate of CAVs. A detailed investigation revealed that no significant environmental benefit was generated under high congestion levels when the minimum speed of CAVs was more than 20 mph, and the shockwaves caused by the eco-approach control may result in a gating effect that reduces the throughput at the upstream intersection of the corridor under high congestion levels.
A Novel Intelligence Approach of a Sequential Minimal Optimization-Based Support Vector Machine for Landslide Susceptibility Mapping
Authors: Pham Binh Thai , Prakash Indra , Chen Wei , Ly Hai-Bang , Ho Lanh Si , Omidvar Ebrahim , Tran Van Phong , Bui Dieu Tien
Published: November 2019

The main objective of this study is to propose a novel hybrid model of a sequential minimal optimization and support vector machine (SMOSVM) for accurate landslide susceptibility mapping. For this task, one of the landslide prone areas of Vietnam, the Mu Cang Chai District located in Yen Bai Province was selected. In total, 248 landslide locations and 15 landslide-affecting factors were selected for landslide modeling and analysis. Predictive capability of SMOSVM was evaluated and compared with other landslide models, namely a hybrid model of the cascade generalization optimization-based support vector machine (CGSVM), individual models, such as support vector machines (SVM) and naïve Bayes trees (NBT). For validation, different quantitative criteria such as statistical based methods and area under the receiver operating characteristic curve (AUC) technique were used. Results of the study show that the SMOSVM model (AUC = 0.824) has the highest performance for landslide susceptibility mapping, followed by CGSVM (AUC = 0.815), SVM (AUC = 0.804), and NBT (AUC = 0.800) models, respectively. Thus, the proposed novel SMOSVM model is a promising method for better landslide susceptibility mapping and prediction, which can be applied also in other landslide prone areas.
Impact of Vegetation on Perceived Safety and Preference in City Parks
Authors: Lis Aleksandra , Pardela Łukasz , Iwankowski Paweł
Published: November 2019

The aim of this study was to determine the impact of safety-related environmental characteristics in a city park on users’ preferences and whether this impact can be explained by perceived safety. The factors examined were physical and visual accessibility as well as the effectiveness of concealment created by plants in various spatial systems. We used 112 photographs taken in city parks for the study. Studies have shown that visual and physical accessibility varies in terms of impact on preferences and safety—as a result, we tested only visual accessibility and effectiveness. Correlation and regression analyses confirmed that vegetation in a park that obstructs views and can offer concealment reduces our sense of safety. In addition, such vegetation has a negative effect on preference. However, mediation analysis showed that this sense of safety or danger means that dense vegetation (low visual accessibility yet highly effective in offering concealment) is less preferred as a landscape feature. After excluding the impact brought to bear by the sense of safety, the studied features of vegetation had no significant impact on preferences. This means that plants and vegetation layouts of varying densities can be used in completely safe parks and this will probably not adversely affect the feelings of the users.
Effect of Seasonal Characteristics of Temperature and Relative Humidity on Chloride Diffusion Process in Concrete: A Preliminary Theoretical Study
Authors: Pan Zichao , Li Tianhua , Ruan Xin
Published: November 2019

The chloride diffusion process can be greatly affected by the temperature and relative humidity. Annual average temperature and relative humidity are often adopted in analytical models to calculate chloride profiles. These models, however, cannot consider the seasonal characteristics of temperature and relative humidity. This paper presents a theoretical study to solve the above problem. The temperature and relative humidity in several major cities in China are first collected. Then, the governing equation of one-dimensional chloride diffusion is solved by both analytical and numerical methods using the annual and monthly average temperature and relative humidity, respectively. Based on these two methods, a parameter called “seasonal correction coefficient” is introduced into the analytical models. The values of the coefficient for major cities in China are obtained. Based on the results, it is found that: (1) the analytical solution with annual average temperature and relative humidity is questionable to calculate chloride profiles for typical cities, (2) the seasonal correction coefficient is independent on the apparent chloride diffusivity, affected slightly by the activation energy of chloride ions during diffusion and greatly by the critical relative humidity for common water-to-cement ratios of ordinary Portland cement (OPC) mortar and concrete.
Application of Differential Transform to Multi-Term Fractional Differential Equations with Non-Commensurate Orders
Authors: Rebenda Josef
Published: November 2019

The differential transformation, an approach based on Taylor’s theorem, is proposed as convenient for finding an exact or approximate solution to the initial value problem with multiple Caputo fractional derivatives of generally non-commensurate orders. The multi-term differential equation is first transformed into a multi-order system and then into a system of recurrence relations for coefficients of formal fractional power series. The order of the fractional power series is discussed in relation to orders of derivatives appearing in the original equation. Application of the algorithm to an initial value problem gives a reliable and expected outcome including the phenomenon of symmetry in choice of orders of the differential transformation of the multi-order system.
Improved Image Splicing Forgery Detection by Combination of Conformable Focus Measures and Focus Measure Operators Applied on Obtained Redundant Discrete Wavelet Transform Coefficients
Authors: Subramaniam Thamarai , Jalab Hamid A. , Ibrahim Rabha W. , Mohd Noor Nurul F.
Published: November 2019

The image is the best information carrier in the current digital era and the easiest to manipulate. Image manipulation causes the integrity of this information carrier to be ambiguous. The image splicing technique is commonly used to manipulate images by fusing different regions in one image. Over the last decade, it has been confirmed that various structures in science and engineering can be demonstrated more precisely by fractional calculus using integrals or derivative operators. Many fractional-order-based techniques have been used in the image-processing field. Recently, a new specific fractional calculus, called conformable calculus, was delivered. Herein, we employ the combination of conformable focus measures (CFMs), and focus measure operators (FMOs) in obtaining redundant discrete wavelet transform (RDWT) coefficients for improving the image splicing forgery detection. The process of image splicing disorders the content of tampered image and causes abnormality in the image features. The spliced region’s boundaries are usually blurring to avoid detection. To make use of the blurred information, both CFMs and FMOs are used to calculate the degree of blurring of the tampered region’s boundaries for image splicing detection. The two public image datasets IFS-TC and CASIA TIDE V2 are used for evaluation of the proposed method. The obtained results of the proposed method achieved accuracy rate 98.30% for Cb channel on IFS-TC image dataset and 98.60% of the Cb channel on CASIA TIDE V2 with 24-D feature vector. The proposed method exhibited superior results compared with other image splicing detection methods.
Self-Supervised Contextual Data Augmentation for Natural Language Processing
Authors: Park Dongju , Ahn Chang Wook
Published: November 2019

In this paper, we propose a novel data augmentation method with respect to the target context of the data via self-supervised learning. Instead of looking for the exact synonyms of masked words, the proposed method finds words that can replace the original words considering the context. For self-supervised learning, we can employ the masked language model (MLM), which masks a specific word within a sentence and obtains the original word. The MLM learns the context of a sentence through asymmetrical inputs and outputs. However, without using the existing MLM, we propose a label-masked language model (LMLM) that can include label information for the mask tokens used in the MLM to effectively use the MLM in data with label information. The augmentation method performs self-supervised learning using LMLM and then implements data augmentation through the trained model. We demonstrate that our proposed method improves the classification accuracy of recurrent neural networks and convolutional neural network-based classifiers through several experiments for text classification benchmark datasets, including the Stanford Sentiment Treebank-5 (SST5), the Stanford Sentiment Treebank-2 (SST2), the subjectivity (Subj), the Multi-Perspective Question Answering (MPQA), the Movie Reviews (MR), and the Text Retrieval Conference (TREC) datasets. In addition, since the proposed method does not use external data, it can eliminate the time spent collecting external data, or pre-training using external data.