bluuebunny/crossref_metadata_2025 huggingface dataset:
Physics-Based Device Models and Progress Review for Active Piezoelectric Semiconductor Devices
Authors: Oh Hongseok , Dayeh Shadi A.
Published: July 2020

Piezoelectric devices transduce mechanical energy to electrical energy by elastic deformation, which distorts local dipoles in crystalline materials. Amongst electromechanical sensors, piezoelectric devices are advantageous because of their scalability, light weight, low power consumption, and readily built-in amplification and ability for multiplexing, which are essential for wearables, medical devices, and robotics. This paper reviews recent progress in active piezoelectric devices. We classify these piezoelectric devices according to the material dimensionality and present physics-based device models to describe and quantify the piezoelectric response for one-dimensional nanowires, emerging two-dimensional materials, and three-dimensional thin films. Different transduction mechanisms and state-of-the-art devices for each type of material are reviewed. Perspectives on the future applications of active piezoelectric devices are discussed.
Wearable Sensor Network for Biomechanical Overload Assessment in Manual Material Handling
Authors: Giannini Paolo , Bassani Giulia , Avizzano Carlo Alberto , Filippeschi Alessandro
Published: July 2020

The assessment of risks due to biomechanical overload in manual material handling is nowadays mainly based on observational methods in which an expert rater visually inspects videos of the working activity. Currently available sensing wearable technologies for motion and muscular activity capture enables to advance the risk assessment by providing reliable, repeatable, and objective measures. However, existing solutions do not address either a full body assessment or the inclusion of measures for the evaluation of the effort. This article proposes a novel system for the assessment of biomechanical overload, capable of covering all areas of ISO 11228, that uses a sensor network composed of inertial measurement units (IMU) and electromyography (EMG) sensors. The proposed method is capable of gathering and processing data from three IMU-based motion capture systems and two EMG capture devices. Data are processed to provide both segmentation of the activity and ergonomic risk score according to the methods reported in the ISO 11228 and the TR 12295. The system has been tested on a challenging outdoor scenario such as lift-on/lift-off of containers on a cargo ship. A comparison of the traditional evaluation method and the proposed one shows the consistency of the proposed system, its time effectiveness, and its potential for deeper analyses that include intra-subject and inter-subjects variability as well as a quantitative biomechanical analysis.
Sign Language Recognition Using Wearable Electronics: Implementing k-Nearest Neighbors with Dynamic Time Warping and Convolutional Neural Network Algorithms
Authors: Saggio Giovanni , Cavallo Pietro , Ricci Mariachiara , Errico Vito , Zea Jonathan , Benalcázar Marco E.
Published: July 2020

We propose a sign language recognition system based on wearable electronics and two different classification algorithms. The wearable electronics were made of a sensory glove and inertial measurement units to gather fingers, wrist, and arm/forearm movements. The classifiers were k-Nearest Neighbors with Dynamic Time Warping (that is a non-parametric method) and Convolutional Neural Networks (that is a parametric method). Ten sign-words were considered from the Italian Sign Language: cose, grazie, maestra, together with words with international meaning such as google, internet, jogging, pizza, television, twitter, and ciao. The signs were repeated one-hundred times each by seven people, five male and two females, aged 29–54 y ± 10.34 (SD). The adopted classifiers performed with an accuracy of 96.6% ± 3.4 (SD) for the k-Nearest Neighbors plus the Dynamic Time Warping and of 98.0% ± 2.0 (SD) for the Convolutional Neural Networks. Our system was made of wearable electronics among the most complete ones, and the classifiers top performed in comparison with other relevant works reported in the literature.
Analytical TCP Model for Millimeter-Wave 5G NR Systems in Dynamic Human Body Blockage Environment
Authors: Moltchanov Dmitri , Ometov Aleksandr , Kustarev Pavel , Evsutin Oleg , Hosek Jiri , Koucheryavy Yevgeni
Published: July 2020

Dynamic blockage of radio propagation paths between the user equipment (UE) and the 5G New Radio (NR) Base Station (BS) induces abrupt rate fluctuations that may lead to sub-optimal performance of the Transmission Control Protocol (TCP) protocol. In this work, we characterize the effects of dynamic human blockage on TCP throughput at the 5G NR air interface. To this aim, we develop an analytical model that expresses the TCP throughput as a function of the round-trip time (RTT), environmental, and radio system parameters. Our results indicate that the blockage affects TCP throughput only when the RTT is comparable to the blocked and non-blocked state durations when the frequency of state changes is high. However, such conditions are not typical for dynamic body blockage environments allowing TCP to benefit from the high bandwidth of 5G NR systems fully.
Detection and Measurement of Matrix Discontinuities in UHPFRC by Means of Distributed Fiber Optics Sensing
Authors: Sawicki Bartłomiej , Bassil Antoine , Brühwiler Eugen , Chapeleau Xavier , Leduc Dominique
Published: July 2020

Following the significant improvement in their properties during the last decade, Distributed Fiber Optics sensing (DFOs) techniques are nowadays implemented for industrial use in the context of Structural Health Monitoring (SHM). While these techniques have formed an undeniable asset for the health monitoring of concrete structures, their performance should be validated for novel structural materials including Ultra High Performance Fiber Reinforced Cementitious composites (UHPFRC). In this study, a full scale UHPFRC beam was instrumented with DFOs, Digital Image Correlation (DIC) and extensometers. The performances of these three measurement techniques in terms of strain measurement as well as crack detection and localization are compared. A method for the measurement of opening and closing of localized fictitious cracks in UHPFRC using the Optical Backscattering Reflectometry (OBR) technique is verified. Moreover, the use of correct combination of DFO sensors allows precise detection of microcracks as well as monitoring of fictitious cracks’ opening. The recommendations regarding use of various SHM methods for UHPFRC structures are given.
Forcecardiography: A Novel Technique to Measure Heart Mechanical Vibrations onto the Chest Wall
Authors: Andreozzi Emilio , Fratini Antonio , Esposito Daniele , Naik Ganesh , Polley Caitlin , Gargiulo Gaetano D. , Bifulco Paolo
Published: July 2020

This paper presents forcecardiography (FCG), a novel technique to measure local, cardiac-induced vibrations onto the chest wall. Since the 19th century, several techniques have been proposed to detect the mechanical vibrations caused by cardiovascular activity, the great part of which was abandoned due to the cumbersome instrumentation involved. The recent availability of unobtrusive sensors rejuvenated the research field with the most currently established technique being seismocardiography (SCG). SCG is performed by placing accelerometers onto the subject’s chest and provides information on major events of the cardiac cycle. The proposed FCG measures the cardiac-induced vibrations via force sensors placed onto the subject’s chest and provides signals with a richer informational content as compared to SCG. The two techniques were compared by analysing simultaneous recordings acquired by means of a force sensor, an accelerometer and an electrocardiograph (ECG). The force sensor and the accelerometer were rigidly fixed to each other and fastened onto the xiphoid process with a belt. The high-frequency (HF) components of FCG and SCG were highly comparable (r > 0.95) although lagged. The lag was estimated by cross-correlation and resulted in about tens of milliseconds. An additional, large, low-frequency (LF) component, associated with ventricular volume variations, was observed in FCG, while not being visible in SCG. The encouraging results of this feasibility study suggest that FCG is not only able to acquire similar information as SCG, but it also provides additional information on ventricular contraction. Further analyses are foreseen to confirm the advantages of FCG as a technique to improve the scope and significance of pervasive cardiac monitoring.
An Intelligent Opportunistic Routing Algorithm for Wireless Sensor Networks and Its Application Towards e-Healthcare
Authors: Bangotra Deep Kumar , Singh Yashwant , Selwal Arvind , Kumar Nagesh , Singh Pradeep Kumar , Hong Wei-Chiang
Published: July 2020

The lifetime of a node in wireless sensor networks (WSN) is directly responsible for the longevity of the wireless network. The routing of packets is the most energy-consuming activity for a sensor node. Thus, finding an energy-efficient routing strategy for transmission of packets becomes of utmost importance. The opportunistic routing (OR) protocol is one of the new routing protocol that promises reliability and energy efficiency during transmission of packets in wireless sensor networks (WSN). In this paper, we propose an intelligent opportunistic routing protocol (IOP) using a machine learning technique, to select a relay node from the list of potential forwarder nodes to achieve energy efficiency and reliability in the network. The proposed approach might have applications including e-healthcare services. As the proposed method might achieve reliability in the network because it can connect several healthcare network devices in a better way and good healthcare services might be offered. In addition to this, the proposed method saves energy, therefore, it helps the remote patient to connect with healthcare services for a longer duration with the integration of IoT services.
Quadrotor-Based Lighthouse Localization with Time-Synchronized Wireless Sensor Nodes and Bearing-Only Measurements
Authors: Kilberg Brian G. , Campos Felipe M. R. , Schindler Craig B. , Pister Kristofer S. J.
Published: July 2020

Some robotic localization methods, such as ultra wideband localization and lighthouse localization, require external localization infrastructure in order to operate. However, there are situations where this localization infrastructure does not exist in the field, such as robotic exploration tasks. Deploying low power wireless sensor networks (WSNs) as localization infrastructure can potentially solve this problem. In this work, we demonstrate the use of an OpenWSN network of miniaturized low power sensor nodes as localization infrastructure. We demonstrate a quadrotor performing laser-based relative bearing measurements of stationary wireless sensor nodes with known locations and using these measurements to localize itself. These laser-based measurements require little computation on the WSN nodes, and are compatible with state-of-the-art 2 mm × 3 mm monolithic wireless system-on-chips (SoCs). These capabilities were demonstrated on a Crazyflie quadcopter using an Extended Kalman Filter and a network of motes running the OpenWSN wireless sensor network stack. The RMS error for X positioning was 0.57 m and the error for Y positioning was 0.39 m. This is the first use of an OpenWSN sensor network to support robotic localization. Furthermore, simulations show that these same measurements could be used for localizing sensor motes with unknown locations in the future.
Sensors for Cryogenic Isotope-Separation Column
Authors: Dulf Eva H. , Festila Clement
Published: July 2020

Cryogenic isotope-separation equipment is special, encountered in relative few research centers in the world. In addition to the main equipment used in the operation column, a broad range of measuring devices and actuators are involved in the technological process. The proper sensors and transducers exhibit special features; therefore, common, industrial versions cannot be used. Three types of original sensors with electronic adapters are presented in the present study: a sensor for the liquid carbon monoxide level in the boiler, a sensor for the liquid nitrogen level in the condenser and a sensor for the electrical power dissipated in the boiler. The integration of these sensors in the pilot equipment is needed for comprehensive system monitoring and control. The sensors were tested on the experimental equipment from the National Institute for Research and Development of Isotopic and Molecular Technologies from Cluj-Napoca.
The Use of IoT Technology in Smart Cities and Smart Villages: Similarities, Differences, and Future Prospects
Authors: Cvar Nina , Trilar Jure , Kos Andrej , Volk Mojca , Stojmenova Duh Emilija
Published: July 2020

Initially, the concept of Smart Cities (urban settlement) originated from the Internet of Things (IoT) technology, however, the use of IoT technology can be extended to the concept of Smart Villages (rural settlement) as well, improving the life of the villagers, and the communities as a whole. Yet, the rural settlements have slightly different requirements than the urban like settlements. If application of IoT in Smart Cities can be characterized by densification of IoT to day-to-day life, following cities’ structural characteristics of being densely settled places, IoT empowered Smart Villages are usually a system of dispersion and deficiency. In this manner, this research paper will address and discuss different application areas of IoT technology, identifying differences, but also similarities in both ecosystems, while trying to illuminate the standardization efforts that can be applicable in both contexts. In our text we will propose the following IoT application domains, which will also serve as a base for research on smart villages: 1. Natural Resources and Energy, 2. Transport and Mobility, 3. Smart Building, 4. Daily Life, 5. Government, and 6. Economy and Society. By providing an overview of technical solutions that support smart solutions in Smart Cities and Smart Villages this research paper will evaluate how, with IoT empowered Smart Villages and Smart Cities, an overall improvement of quality of life of their inhabitants can be achieved.
Validation of Marker-Less System for the Assessment of Upper Joints Reaction Forces in Exoskeleton Users
Authors: Pasinetti Simone , Nuzzi Cristina , Covre Nicola , Luchetti Alessandro , Maule Luca , Serpelloni Mauro , Lancini Matteo
Published: July 2020

This paper presents the validation of a marker-less motion capture system used to evaluate the upper limb stress of subjects using exoskeletons for locomotion. The system fuses the human skeletonization provided by commercial 3D cameras with forces exchanged by the user to the ground through upper limbs utilizing instrumented crutches. The aim is to provide a low cost, accurate, and reliable technology useful to provide the trainer a quantitative evaluation of the impact of assisted gait on the subject without the need to use an instrumented gait lab. The reaction forces at the upper limbs’ joints are measured to provide a validation focused on clinically relevant quantities for this application. The system was used simultaneously with a reference motion capture system inside a clinical gait analysis lab. An expert user performed 20 walking tests using instrumented crutches and force platforms inside the observed volume. The mechanical model was applied to data from the system and the reference motion capture, and numerical simulations were performed to assess the internal joint reaction of the subject’s upper limbs. A comparison between the two results shows a root mean square error of less than 2% of the subject’s body weight.
A Novel Multi-Focus Image Fusion Network with U-Shape Structure
Authors: Pan Tao , Jiang Jiaqin , Yao Jian , Wang Bin , Tan Bin
Published: July 2020

Multi-focus image fusion has become a very practical image processing task. It uses multiple images focused on various depth planes to create an all-in-focus image. Although extensive studies have been produced, the performance of existing methods is still limited by the inaccurate detection of the focus regions for fusion. Therefore, in this paper, we proposed a novel U-shape network which can generate an accurate decision map for the multi-focus image fusion. The Siamese encoder of our U-shape network can preserve the low-level cues with rich spatial details and high-level semantic information from the source images separately. Moreover, we introduce the ResBlocks to expand the receptive field, which can enhance the ability of our network to distinguish between focus and defocus regions. Moreover, in the bridge stage between the encoder and decoder, the spatial pyramid pooling is adopted as a global perception fusion module to capture sufficient context information for the learning of the decision map. Finally, we use a hybrid loss that combines the binary cross-entropy loss and the structural similarity loss for supervision. Extensive experiments have demonstrated that the proposed method can achieve the state-of-the-art performance.
Low Cost and Compact FMCW 24 GHz Radar Applications for Snowpack and Ice Thickness Measurements
Authors: Pomerleau Patrick , Royer Alain , Langlois Alexandre , Cliche Patrick , Courtemanche Bruno , Madore Jean-Benoît , Picard Ghislain , Lefebvre Éric
Published: July 2020

Monitoring the evolution of snow on the ground and lake ice—two of the most important components of the changing northern environment—is essential. In this paper, we describe a lightweight, compact and autonomous 24 GHz frequency-modulated continuous-wave (FMCW) radar system for freshwater ice thickness and snow mass (snow water equivalent, SWE) measurements. Although FMCW radars have a long-established history, the novelty of this research lies in that we take advantage the availability of a new generation of low cost and low power requirement units that facilitates the monitoring of snow and ice at remote locations. Test performance (accuracy and limitations) is presented for five different applications, all using an automatic operating mode with improved signal processing: (1) In situ lake ice thickness measurements giving 2 cm accuracy up to ≈1 m ice thickness and a radar resolution of 4 cm; (2) remotely piloted aircraft-based lake ice thickness from low-altitude flight at 5 m; (3) in situ dry SWE measurements based on known snow depth, giving 13% accuracy (RMSE 20%) over boreal forest, subarctic taiga and Arctic tundra, with a measurement capability of up to 3 m in snowpack thickness; (4) continuous monitoring of surface snow density under particular Antarctic conditions; (5) continuous SWE monitoring through the winter with a synchronized and collocated snow depth sensor (ultrasonic or LiDAR sensor), giving 13.5% bias and 25 mm root mean square difference (RMSD) (10%) for dry snow. The need for detection processing for wet snow, which strongly absorbs radar signals, is discussed. An appendix provides 24 GHz simulated effective refractive index and penetration depth as a function of a wide range of density, temperature and wetness for ice and snow.
A Tool to Calculate the Level of Occupancy in Indoor and Outdoor Spaces Using BLE and Open Data to Be Published in Real-Time
Authors: Mateos Sánchez Montserrat , Berjón Gallinas Roberto , Beato Gutiérrez M. Encarnación , Fermoso García Ana M.
Published: July 2020

The ability to know the precise level of occupancy in an indoor or outdoor space in real time could have multiple applications. It is a well-known problem for which a number of technologies have been proposed over time. The recent emergence of BLE beacon technology has provided a solution to the problem. This study presents a tool that uses beacons and user smartphones to determine the level of occupancy in indoor and outdoor spaces, providing real-time information that can be published as open data and subsequently used by other applications. The tool was tested in a university environment in real-life situations and has produced promising results in obtaining an occupancy count.
Groundwater Resources Assessment for Sustainable Development in South Sudan
Authors: Lasagna Manuela , Bonetto Sabrina Maria Rita , Debernardi Laura , De Luca Domenico Antonio , Semita Carlo , Caselle Chiara
Published: July 2020

The economic activities of South Sudan (East-Central Africa) are predominantly agricultural. However, food insecurity due to low agricultural production, connected with weather conditions and lack of water infrastructure and knowledge, is a huge problem. This study reports the results of a qualitative and quantitative investigation of underground and surface water in the area of Gumbo (east of Juba town) that aims to assure sustainable water management, reducing diseases and mortality and guaranteeing access to irrigation and drinking water. The results of the study demonstrate the peculiarity of surface and groundwater and the critical aspects to take into account for the water use, particularly due to the exceeding of limits suggested by the WHO and national regulation. The outcomes provide a contribution to the scientific overview on lithostratigraphic, hydrochemical and hydrogeological setting of a less-studied area, characterized by sociopolitical instability and water scarcity. This represents a first step for the improvement of water knowledge and management, for sustainable economic development and for social progress in this African region.
Identification of Patterns and Influential Factors on Civil Protection Personnel Opinions and Views on Different Aspects of Flood Risk Management: The Case of Greece
Authors: Diakakis Michalis , Damigos Dimitris G. , Kallioras Andreas
Published: July 2020

The views and perceptions of the civil protection community have a central position in any risk management process or initiative, and are crucial to its success. However, knowledge of the views and perceptions of officials, and what affects them remains limited in the current literature. This work uses questionnaires to explore the views of civil protection personnel in Greece on different elements of flood risk management and identify factors that influence them. Results provide a basic understanding of officials’ views, indicating certain shortcomings in various sectors and dissatisfaction in several aspects of everyday practice. Interestingly, responses of participants to perception- and knowledge-related questions show a pattern, relating to respondents’ attributes and characteristics, such as experience, age, qualifications, and others. On the contrary, their views on everyday practice issues of flood risk management are associated with the type of position they have in the civil protection community. The findings contribute to the overall effort to improve the understanding of the characteristics of civil protection organizations across Europe, as a means to enhance cooperation.
Weight Approximation for Spatial Outcomes
Authors: Simon Jay
Published: July 2020

When preferences explicitly include a spatial component, it can be challenging to assign weights to geographic regions in a way that is both pragmatic and accurate. In multi-attribute decision making, weights reflect cardinal information about preferences that can be difficult to assess thoroughly in practice. Recognizing this challenge, researchers have developed several methods for using ordinal rankings to approximate sets of cardinal weights. However, when the set of weights reflects a set of geographic regions, the number of weights can be enormous, and it may be cognitively challenging for decision makers to provide even a coherent ordinal ranking. This is often the case in policy decisions with widespread impacts. This paper uses a simulation study for spatial preferences to evaluate the performance of several rank-based weight approximation methods, as well as several new methods based on assigning each region to a tier expressing the extent to which it should influence the evaluation of policy alternatives. The tier-based methods do not become more cognitively complex as the number of regions increases, they allow decision makers to express a wider range of preferences, and they are similar in accuracy to rank-based methods when the number of regions is large. The paper then demonstrates all of these approximation methods with preferences for water usage by census block in a United States county.
Long-Term Validation and Governance Role in Contemporary Urban Tree Monitoring: A Review
Authors: Klobucar Blaz , Östberg Johan , Jansson Märit , Randrup Thomas Barfoed
Published: July 2020

Urban trees provide important ecosystem services, across ownership and governance structures, and tree inventories are an important tool enabling urban foresters and green space managers to monitor and perform the sustainable management of urban trees. For optimal management of urban trees, a better understanding is needed concerning how urban tree inventories can provide long-term monitoring overviews across administrative borders, and how inventory protocols should be adapted to address specific practitioner issues. In this review, 98 articles on urban tree inventories were examined, the primary focus being sampling design. A governance arrangement approach was applied to identify the policy-making arrangements behind the inventories. Stratification is commonly used in the sampling design, despite being problematic for long-term representativeness. Only 10% of the stratification sampling designs identified were considered as having long-term validity. The studies frequently relied on an individual sampling design aimed at a particular issue, as opposed to using an existing longitudinal sampling network. Although private trees can constitute over 50% of the urban tree population, 41% of the studies reviewed did not include private trees at all. Urban tree inventories focused primarily on tree data on a local scale. Users or private tree owners are commonly not included in these studies, and limited attention is paid to economic, cultural or social factors. A long-term validation of sampling methods in urban areas, and a multi-lateral approach to tree inventories, are needed to maintain long-term operational value for local managers in securing ecosystem service provisions for entire urban forests.
Reduced Value Added Tax (VAT) Rate on Books as a Tool of Indirect Public Funding in the Cultural Sector
Authors: Kopeć Katarzyna
Published: July 2020

The article concentrates on the relationship between reduced value added tax (VAT) rate on books and readership level as a projected goal in cultural policy. To figure out this complex link, the paper explores the contribution of public management and economy to this knowledge to uncover the potential of following assumptions: (1) Reduced VAT rate results in the fall in book prices for consumers; (2) lower book prices stimulate the demand for books; (3) higher consumption of books (book purchase) is reflected in a higher level of readership. Indirect funding is very often worth more (quantitatively) than a direct mode of subsidizing. Indirect instruments, including VAT reduction, are not always the simplest way towards a cultural policy target. Despite great potential as an indirect funding tool, the VAT reduction requires a high-quality ex-ante assessment, and mid-term evaluation to verify the effectiveness and consequences of using VAT as a tax exemption in the cultural policy.
How Can Ski Resorts Get Smart? Transdisciplinary Approaches to Sustainable Winter Tourism in the European Alps
Authors: Polderman Annemarie , Haller Andreas , Viesi Diego , Tabin Xavier , Sala Stefano , Giorgi Annamaria , Darmayan Loïc , Rager Jakob , Vidovič Jelena , Daragon Quentin , Verchère Yves , Zupan Uroš , Houbé Nadine , Heinrich Kati , Bender Oliver , Bidault Yann
Published: July 2020

Climate change and the call for reduction of greenhouse gas emissions, the efficient use of (renewable) energy, and more resilient winter tourism regions, forces ski resorts across the European Alps to look for “smart” approaches to transition towards a sustainable, low-carbon economy. Drawing on the smart-city concept and considering the different historical developments of Alpine resorts, the Smart Altitude Decision-Making Toolkit was developed using a combination of an energy audit tool, a WebGIS, and collaborative and innovative living labs installed in Les Orres (France), Madonna di Campiglio (Italy), Krvavec (Slovenia), and Verbier (Switzerland). This step-by-step Decision-Making Toolkit enables ski resorts to get feedback on their energy demand, an overview of the locally available sources of renewable energy, and insights regarding their potential for improving their energy efficiency by low-carbon interventions. The Decision-Making Toolkit is suitable for knowledge transfer between stakeholders within living labs and moreover provides the flexibility for tailor-made low-carbon strategies adapting to the unique assets and situatedness of ski resorts.
Improving Sustainability of Smart Cities through Visualization Techniques for Big Data from IoT Devices
Authors: Lavalle Ana , Teruel Miguel A. , Maté Alejandro , Trujillo Juan
Published: July 2020

Fostering sustainability is paramount for Smart Cities development. Lately, Smart Cities are benefiting from the rising of Big Data coming from IoT devices, leading to improvements on monitoring and prevention. However, monitoring and prevention processes require visualization techniques as a key component. Indeed, in order to prevent possible hazards (such as fires, leaks, etc.) and optimize their resources, Smart Cities require adequate visualizations that provide insights to decision makers. Nevertheless, visualization of Big Data has always been a challenging issue, especially when such data are originated in real-time. This problem becomes even bigger in Smart City environments since we have to deal with many different groups of users and multiple heterogeneous data sources. Without a proper visualization methodology, complex dashboards including data from different nature are difficult to understand. In order to tackle this issue, we propose a methodology based on visualization techniques for Big Data, aimed at improving the evidence-gathering process by assisting users in the decision making in the context of Smart Cities. Moreover, in order to assess the impact of our proposal, a case study based on service calls for a fire department is presented. In this sense, our findings will be applied to data coming from citizen calls. Thus, the results of this work will contribute to the optimization of resources, namely fire extinguishing battalions, helping to improve their effectiveness and, as a result, the sustainability of a Smart City, operating better with less resources. Finally, in order to evaluate the impact of our proposal, we have performed an experiment, with non-expert users in data visualization.
An Accurate Inverse Model for the Detection of Leaks in Sealed Landfills
Authors: Vocciante Marco , Meshalkin Valery
Published: July 2020

Leaks from landfills to underlying soil layers are one of the main problems that endanger the sustainability of waste disposal in landfills. Indeed, the possible failing of in-situ equipment can give rise to serious pollution consequences or costly inspection work in the landfill body. In this paper, we develop the time dependent mathematical relationship between the concentration of water at the surface of the landfill and the flux at the bottom of the landfill. This makes it possible to detect a leak using non-expensive measurements made at the surface of the landfill. The resulting model is obtained by analytically solving Richard’s equation with a piecewise linear boundary condition at the bottom. The unknown coefficients of the piecewise linear functions, which can be estimated using the measurements at the surface, provide the necessary information for detecting leaks. The algorithm has been numerically tested using simulated data of rain precipitation. The method proposed could be conveniently used to complement the usual monitoring techniques due to the limited costs of its implementation.
Performance Improvement of PEM Fuel Cell Using Variable Step-Size Incremental Resistance MPPT Technique
Authors: Rezk Hegazy , Fathy Ahmed
Published: July 2020

The output power of a fuel cell mainly depends on the operating conditions such as cell temperature and membrane water content. The fuel cell (FC) power versus FC current graph has a unique maximum power point (MPP). The location of the MPP is variable, depending on the operating condition. Consequently, a maximum power point tracker (MPPT) is highly required to ensure that the fuel cell operates at an MPP to increase its performance. In this research work, a variable step-size incremental resistance (VSS-INR) tracking method was suggested to track the MPP of the proton exchange membrane (PEMFC). Most of MPPT methods used with PEMFC require at least three sensors: temperature sensor, water content sensor, and voltage sensor. However, the proposed VSS-INR needs only two sensors: voltage and current sensors. The step size of the VSS-INR is directly proportional to the error signal. Therefore, the step size will become small as the error becomes very small nearby the maximum power point. Accordingly, the accuracy of the VSS-INR tracking method is high in a steady state. To test and validate the VSS-INR, nine different scenarios of operating conditions, including normal operation, only temperature variation, only variation of water content in the membrane, and both variations of temperature and water content simultaneously, were used. The obtained results were compared with previously proposed methods, including particle swarm optimization (PSO), perturb and observe (P&O), and sliding mode (SM), under different operating conditions. The results of the comparison confirmed the superiority of VSS-INR compared with other methods in terms of the tracking efficiency and steady-state fluctuations.
Energy and Economic Life Cycle Assessment of Cool Roofs Applied to the Refurbishment of Social Housing in Southern Spain
Authors: Dominguez-Delgado Antonio , Domínguez-Torres Helena , Domínguez-Torres Carlos-Antonio
Published: July 2020

Energy refurbishment of the housing stock is needed in order to reduce energy consumption and meet global climate goals. This is even more necessary for social housing built in Spain in the middle of the last century since its obsolete energy conditions lead to situations of indoor thermal discomfort and energy poverty. The present study carries out a life cycle assessment of the energy and economic performance of roofs after being retrofitted to become cool roofs for the promotion of social housing in Seville (Spain). Dynamic simulations are made in which the time dependent aging effect on the energy performance of the refurbished cool roofs is included for the whole lifespan. The influence of the time dependent aging effect on the results of the life cycle economic analysis is also assessed. A variety of scenarios are considered in order to account for the aging effect in the energy performance of the retrofitted cool roofs and its incidence while considering different energy prices and monetary discount rates on the life cycle assessment. This is made through a dynamic life cycle assessment in order to capture the impact of the aging dynamic behavior correctly. Results point out significant savings in the operational energy. However, important differences are found in the economic savings when the life cycle analysis is carried out since the source of energy and the efficiency of the equipment used for conditioning strongly impact the economic results.
Development of a New Methodology to Identity Promising Technology Areas Using M&A Information
Authors: Choi Jinho , Chang Yong Sik
Published: July 2020

In this paper, we suggest a new methodology to identify promising technology areas by analyzing merger and acquisition (M&A) information. First, we present decision models for estimating the velocity and acceleration of M&A transactions to identify promising areas based on M&A information. Second, we identify the promising technology areas with longitudinal analyses of M&As over the entire period. Third, cross-sectional analysis is proposed to determine which technology areas are more promising through a relative comparison among technology areas within the IT sector for a specific period. The main significance of our research is that it is a prior data-based analytic method based on M&A transaction information to identify the growth of industry and technology. We hope this study will provide insights for R&D (Research&Development) policymakers and investment firms as a new approach that complements previous methods in exploring promising industry or technology areas.
Gasoline to Diesel Consumption Ratio: A New Socioeconomic Indicator of Carbon Dioxide Emissions in China
Authors: Li Zhe , Sun Renjin , Qin Manman , Hu Dongou
Published: July 2020

In recent years, gross domestic product (GDP) has grown rapidly in China, but the growth rate of carbon dioxide (CO2) emissions has begun to decline. Some scholars have put forward the environmental Kuznets curve (EKC) hypothesis for CO2 emissions in China. This paper utilized the panel data of 30 provinces in China from 1997 to 2016 to verify the EKC hypothesis. To explore the real reasons behind the EKC, the index gasoline to diesel consumption ratio (GDCR) was introduced in this paper. The regression results showed that CO2 emissions and GDP form an inverted U-shaped curve. This means that the EKC hypothesis holds. The regression results also showed that a 1% GDCR increase was coupled with a 0.118186% or 0.114056% CO2 emission decrease with the panel fully modified ordinary least squares or panel dynamic ordinary least squares method, respectively. This means that CO2 emissions negatively correlate with GDCR. From the discussion of this paper, the growth rate reduction of CO2 emissions is caused by the economic transition in China. As changes of GDCR can, from a special perspective, reflect the economic transition, and as GDCR is negatively correlated with CO2 emissions, GDCR can sometimes be used as a new socioeconomic indicator of carbon dioxide emissions in China.
The Priority of Factors of Building Government as a Platform with Analytic Hierarchy Process Analysis
Authors: Seo Hyungjun , Myeong Seunghwan
Published: July 2020

Nowadays, the Government as a Platform (GaaP) based on cloud computing and network, has come to be considered a new structure to manage efficiently data-driven administration in the public sector. When the GaaP concept was first introduced, the ICT infrastructures that could underpin GaaP were not sufficiently developed. However, the recent digital transformation has transformed the previous electronic government, which was system- and architecture-oriented. As part of the next generation of government models, GaaP may reinvent the government at a lower cost but with better performance, similar to the case of electronic government two decades ago. This study attempted to determine the priority of factors of GaaP by using the analytic hierarchy process (AHP) methodology. Because of the GaaP characteristics, we drew the main components for building GaaP from previous studies and a group interview with experts. The study results show that experts tend to prefer publicness in terms of building GaaP. Most of the factors that the experts weighed with the highest importance are related to the public sector, which revealed that governments should focus on their primary duty, regardless of the origin and characteristics of the platform in GaaP. However, since GaaP allows governments to be more horizontal and innovative, the platform approach can fundamentally shift the existing processes and culture of the public sector. The enhanced activity of citizens with ICT can also accelerate the introduction of GaaP. Finally, the study showed that a data-driven GaaP is necessary to efficiently handle big data, contract services, and multiple levels of on-line and off-line channels. In this public platform, government, citizens, and private sector organizations can work cooperatively as partners to seamlessly govern the hyper-connected society.
Effects of COVID-19 on Indian Energy Consumption
Authors: Aruga Kentaka , Islam Md. Monirul , Jannat Arifa
Published: July 2020

Just after the Indian government issued the first lockdown rule to cope with the increasing number of COVID-19 cases in March 2020, the energy consumption in India plummeted dramatically. However, as the lockdown relaxed, energy consumption started to recover. In this study, we investigated how COVID-19 cases affected Indian energy consumption during the COVID-19 crisis by testing if the lockdown release had a positive impact on energy consumption and if richer regions were quicker to recover their energy consumption to the level before the lockdown. Using the autoregressive distributed lag (ARDL) model, the study reveals that a long-run relationship holds between the COVID-19 cases and energy consumption and that the COVID-19 cases have a positive effect on Indian energy consumption. This result indicates that as lockdown relaxed, energy consumption started to recover. However, such a positive impact was not apparent in the Eastern and North-Eastern regions, which are the poorest regions among the five regions investigated in the study. This implies that poorer regions need special aid and policy to recover their economy from the damage suffered from the COVID-19 crisis.
Economic and Environmental Impact Assessment of Renewable Energy from Biomass
Authors: Bacenetti Jacopo
Published: July 2020

For a holistic evaluation of sustainability, the economic and environmental aspects should be considered jointly to avoid trade-offs between the two dimensions. In this manuscript, the themes addressed, and the approaches used in this Special Issue “Economic and Environmental Impact Assessment of Renewable Energy from Biomass” to investigate the sustainability are summarized. Different approaches such as Energy Analysis, Life Cycle Assessment, technical and economic evaluation of key processes are applied to different renewable energy pathways (biogas, wood biomass, by-product valorization, etc.). The different manuscripts accepted in this Special Issue increases our comprehension and understanding of the relation between economic and environmental performances of renewable energy from biomass.
Promotion of Polish Cinema Abroad as an Element of Nation Branding. Case Study of “Cold War” (2018) by Pawel Pawlikowski
Authors: Hess Agnieszka , Najbor Joanna
Published: July 2020

The subject of this article is nation branding in the culture market, namely the role cinematography plays in creating a nation brand. Sustainability and sustainable development in the film industry is conditioned by variety in cultural promotion channels. The aim of the authors is to prove that appropriately organised cinematography promotion abroad can positively influence the image of a given country. The first section deals with the relationship between media and sustainable development, as well as with theoretical definitions of branding and the nation brand. Subsequently, cinematography in the context of branding is discussed. The core of this work is a case study of film promotion abroad from the institutional perspective of the Polish Film Institute. The promotional strategy for “Cold War” (2018) directed by Paweł Pawlikowski has been analysed, as this motion picture is considered one of the biggest successes of post-1989 Polish cinematography. Factors positively influencing its popularity were analysed alongside their influence on the general perception of Polish cinema abroad. Based on the results of empirical studies, the authors present their discussion of the functional state and the role of Polish cinematography on the global circuit, as well as attempt to verify its importance in relation to sustainability.
The Association between Regular Use of Ridesourcing and Walking Mode Choice in Cairo and Tehran
Authors: Mostofi Hamid , Masoumi Houshmand , Dienel Hans-Liudger
Published: July 2020

The rapid adoption of ridesourcing poses challenges for researchers and policymakers in the Middle East and North Africa (MENA), as it is an evolving new transport mode, and there is little research explaining its effects on mobility behaviors in this region. There is a concern that ridesourcing, which offers convenient and relatively cheap door to door services, encourages citizens to replace their sustainable travel modes, like walking, with car use. This effect has been studied relatively well in metropolises of the West, but less in the MENA agglomerations. This paper investigates whether regular use of ridesourcing impacts the walking mode choice in Cairo and Tehran. The analysis uses the results of 4926 face-to-face interviews in these two cities to compare the preference for using a vehicle instead of walking between regular users of ridesourcing and other motorized modes, including public bus, urban transit rails, private car, and traditional taxi. The findings indicate that in Cairo, the regular ridesourcing users are more likely than regular users of public transport to use a vehicle instead of walking inside their neighborhood. However, in both cities, ridesourcing users are less likely than regular private car users to replace walking by using vehicles.
The Impact of Urban Transportation Infrastructure on Air Quality
Authors: Guo Yujing , Zhang Qian , Lai Kin Keung , Zhang Yingqin , Wang Shubin , Zhang Wanli
Published: July 2020

While previous study has confirmed significant correlation between infrastructure construction and air quality, little is known about the nature of the relationship. In this paper, we intend to fill this gap by using the Panel Smooth Transition Regression (PSTR) model to discuss the nonlinear relationship between transportation infrastructure construction and air quality. The panel data includes 280 cities in China for the period 2000-2017. We find that the transportation infrastructure investment is positively correlated to the air quality when the GDP per capita is below RMB 7151 or the number of motor vehicle population per capita is below 37 (vehicles per 10,000 persons) where the model is in the lower regime, and that the transportation infrastructure investment is negatively correlated to the air quality when the GDP per capita is greater than RMB 7151 or the number of motor vehicle population per capita is larger than 37 (vehicles per 10,000 persons) where the model is in the upper regime. The empirical results of the three sub-samples, including eastern, western and central regions, are similar to that of the national level. Furthermore, increasing transportation infrastructure investment is conducive to improving air quality. Urban bus services, green area, population density, wind speed and rainfall are also conducive to reducing air pollution, but the role of environmental regulation is not significant. After adding the instrumental variable (urban built-up area), the conclusions are further supported. Finally, relevant policy recommendations for reducing air pollution are proposed based on the empirical results.