bluuebunny/crossref_metadata_2025 huggingface dataset:
Time-Resolved Spectroscopy of Fluorescence Quenching in Optical Fibre-Based pH Sensors
Authors: Ehrlich Katjana , Choudhary Tushar R. , Ucuncu Muhammed , Megia-Fernandez Alicia , Harrington Kerrianne , Wood Harry A. C. , Yu Fei , Choudhury Debaditya , Dhaliwal Kev , Bradley Mark , Tanner Michael G.
Published: October 2020

Numerous optodes, with fluorophores as the chemical sensing element and optical fibres for light delivery and collection, have been fabricated for minimally invasive endoscopic measurements of key physiological parameters such as pH. These flexible miniaturised optodes have typically attempted to maximize signal-to-noise through the application of high concentrations of fluorophores. We show that high-density attachment of carboxyfluorescein onto silica microspheres, the sensing elements, results in fluorescence energy transfer, manifesting as reduced fluorescence intensity and lifetime in addition to spectral changes. We demonstrate that the change in fluorescence intensity of carboxyfluorescein with pH in this “high-density” regime is opposite to that normally observed, with complex variations in fluorescent lifetime across the emission spectra of coupled fluorophores. Improved understanding of such highly loaded sensor beads is important because it leads to large increases in photostability and will aid the development of compact fibre probes, suitable for clinical applications. The time-resolved spectral measurement techniques presented here can be further applied to similar studies of other optodes.
Optical Axons for Electro-Optical Neural Networks
Authors: Hulea Mircea , Ghassemlooy Zabih , Rajbhandari Sujan , Younus Othman Isam , Barleanu Alexandru
Published: October 2020

Recently, neuromorphic sensors, which convert analogue signals to spiking frequencies, have been reported for neurorobotics. In bio-inspired systems these sensors are connected to the main neural unit to perform post-processing of the sensor data. The performance of spiking neural networks has been improved using optical synapses, which offer parallel communications between the distanced neural areas but are sensitive to the intensity variations of the optical signal. For systems with several neuromorphic sensors, which are connected optically to the main unit, the use of optical synapses is not an advantage. To address this, in this paper we propose and experimentally verify optical axons with synapses activated optically using digital signals. The synaptic weights are encoded by the energy of the stimuli, which are then optically transmitted independently. We show that the optical intensity fluctuations and link’s misalignment result in delay in activation of the synapses. For the proposed optical axon, we have demonstrated line of sight transmission over a maximum link length of 190 cm with a delay of 8 μs. Furthermore, we show the axon delay as a function of the illuminance using a fitted model for which the root mean square error (RMS) similarity is 0.95.
Drive-By-Wire Development Process Based on ROS for an Autonomous Electric Vehicle
Authors: Arango J. Felipe , Bergasa Luis M. , Revenga Pedro A. , Barea Rafael , López-Guillén Elena , Gómez-Huélamo Carlos , Araluce Javier , Gutiérrez Rodrigo
Published: October 2020

This paper presents the development process of a robust and ROS-based Drive-By-Wire system designed for an autonomous electric vehicle from scratch over an open source chassis. A revision of the vehicle characteristics and the different modules of our navigation architecture is carried out to put in context our Drive-by-Wire system. The system is composed of a Steer-By-Wire module and a Throttle-By-Wire module that allow driving the vehicle by using some commands of lineal speed and curvature, which are sent through a local network from the control unit of the vehicle. Additionally, a Manual/Automatic switching system has been implemented, which allows the driver to activate the autonomous driving and safely taking control of the vehicle at any time. Finally, some validation tests were performed for our Drive-By-Wire system, as a part of our whole autonomous navigation architecture, showing the good working of our proposal. The results prove that the Drive-By-Wire system has the behaviour and necessary requirements to automate an electric vehicle. In addition, after 812 h of testing, it was proven that it is a robust Drive-By-Wire system, with high reliability. The developed system is the basis for the validation and implementation of new autonomous navigation techniques developed within the group in a real vehicle.
Security Evaluation under Different Exchange Strategies Based on Heterogeneous CPS Model in Interdependent Sensor Networks
Authors: Peng Hao , Liu Can , Zhao Dandan , Hu Zhaolong , Han Jianmin
Published: October 2020

In the real Internet of Everything scenario, many large-scale information systems can be converted into interdependent sensor networks, such as smart grids, smart medical systems, and industrial Internet systems. These complex systems usually have multiple interdependent sensor networks. Small faults or failure behaviors between networks may cause serious cascading failure effects of the entire system. Therefore, in this paper, we will focus on the security of interdependent sensor networks. Firstly, by calculating the size of the largest functional component in the entire network, the impact of random attacks on the security of interdependent sensor networks is analyzed. Secondly, it compares and analyzes the impact of cascading failures between interdependent sensor networks under different switching edge strategies. Finally, the simulation results verify the effect of the security of the system under different strategies, and give a better exchange strategy to enhance the security of the system. In addition, the research work in this article can help design how to further optimize the topology of interdependent sensor networks by reducing the impact of cascading failures.
Acceleration Magnitude at Impact Following Loss of Balance Can Be Estimated Using Deep Learning Model
Authors: Kim Tae Hyong , Choi Ahnryul , Heo Hyun Mu , Kim Hyunggun , Mun Joung Hwan
Published: October 2020

Pre-impact fall detection can detect a fall before a body segment hits the ground. When it is integrated with a protective system, it can directly prevent an injury due to hitting the ground. An impact acceleration peak magnitude is one of key measurement factors that can affect the severity of an injury. It can be used as a design parameter for wearable protective devices to prevent injuries. In our study, a novel method is proposed to predict an impact acceleration magnitude after loss of balance using a single inertial measurement unit (IMU) sensor and a sequential-based deep learning model. Twenty-four healthy participants participated in this study for fall experiments. Each participant worn a single IMU sensor on the waist to collect tri-axial accelerometer and angular velocity data. A deep learning method, bi-directional long short-term memory (LSTM) regression, is applied to predict a fall’s impact acceleration magnitude prior to fall impact (a fall in five directions). To improve prediction performance, a data augmentation technique with increment of dataset is applied. Our proposed model showed a mean absolute percentage error (MAPE) of 6.69 ± 0.33% with r value of 0.93 when all three different types of data augmentation techniques are applied. Additionally, there was a significant reduction of MAPE by 45.2% when the number of training datasets was increased by 4-fold. These results show that impact acceleration magnitude can be used as an activation parameter for fall prevention such as in a wearable airbag system by optimizing deployment process to minimize fall injury in real time.
Energy-Efficient Connected-Coverage Scheme in Wireless Sensor Networks
Authors: Xu Yun , Jiao Wanguo , Tian Mengqiu
Published: October 2020

In the wireless sensor network, the lifetime of the network can be prolonged by improving the efficiency of limited energy. Existing works achieve better energy utilization, either through node scheduling or routing optimization. In this paper, an efficient solution combining node scheduling with routing protocol optimization is proposed in order to improve the network lifetime. Firstly, to avoid the redundant coverage, a node scheduling scheme that is based on a genetic algorithm is proposed to find the minimum number of sensor nodes to monitor all target points. Subsequently, the algorithm prolongs the lifetime of the network through choosing redundant sleep nodes to replace the dead node. Based on the obtained minimum coverage set, a new routing protocol, named Improved-Distributed Energy-Efficient Clustering (I-DEEC), is proposed. When considering the energy and the distance of the sensor node to the sink, a new policy choosing the cluster head is proposed. To make the energy load more balanced, uneven clusters are constructed. Meanwhile, the data communication way of sensor nodes around the sink is also optimized. The simulation results show that the proposed sensor node scheduling algorithm can reduce the number of redundant sensor nodes, while the I-DEEC routing protocol can improve the energy efficiency of data transmission. The lifetime of the network is greatly extended.
New Procedure for the Kinematic and Power Analysis of Cyclists in Indoor Training
Authors: Calvo José Antonio , Álvarez-Caldas Carolina , San Román José Luis , Gutiérrez-Moizant Ramón
Published: October 2020

In this research, the performance and movements of amateur and professional cyclists were analyzed. For this, reflective markers have been used on different parts of the body of the participants in conjunction with sports cameras and a mobile power meter. The trajectories of the markers have been obtained with the software Kinovea and subsequently analyzed using error ellipses. It is demonstrated that the error ellipses help determine movement patterns in the knees, back, and hip. The covariance of the error ellipses can be indicative of the alignment and symmetry of the frontal movement of the knees. In addition, it allows verifying the alignment of the spine and the symmetry of the hip. Finally, it is shown that it is necessary to consider the uncertainty of the power devices since it considerably affects the evaluation of the cyclists’ performance. Devices with high uncertainty will demand a greater effort from the cyclist to meet the power required in the endurance test developed. The statistical magnitudes considered help to analyze power and evaluate the cyclists’ performance.
Centre of Pressure Estimation during Walking Using Only Inertial-Measurement Units and End-To-End Statistical Modelling
Authors: Podobnik Janez , Kraljić David , Zadravec Matjaž , Munih Marko
Published: October 2020

Estimation of the centre of pressure (COP) is an important part of the gait analysis, for example, when evaluating the functional capacity of individuals affected by motor impairment. Inertial measurement units (IMUs) and force sensors are commonly used to measure gait characteristic of healthy and impaired subjects. We present a methodology for estimating the COP solely from raw gyroscope, accelerometer, and magnetometer data from IMUs using statistical modelling. We demonstrate the viability of the method using an example of two models: a linear model and a non-linear Long-Short-Term Memory (LSTM) neural network model. Models were trained on the COP ground truth data measured using an instrumented treadmill and achieved the average intra-subject root mean square (RMS) error between estimated and ground truth COP of 12.3 mm and the average inter-subject RMS error of 23.7 mm which is comparable or better than similar studies so far. We show that the calibration procedure in the instrumented treadmill can be as short as a couple of minutes without the decrease in our model performance. We also show that the magnetic component of the recorded IMU signal, which is most sensitive to environmental changes, can be safely dropped without a significant decrease in model performance. Finally, we show that the number of IMUs can be reduced to five without deterioration in the model performance.
Spectral Reflectance Can Differentiate Tracheal and Esophageal Tissue in the Presence of Bodily Fluids and Soot
Authors: Berard David , Sen Chirantan , Nawn Corinne D. , Blackburn August N. , Ryan Kathy L. , Blackburn Megan B.
Published: October 2020

Endotracheal intubation is a common life-saving procedure implemented in emergency care to ensure patient oxygenation, but it is difficult and often performed in suboptimal conditions leading to high rates of patient complications. Undetected misplacement in the esophagus is a preventable complication that can lead to fatalities in 5–10% of patients who undergo emergency intubation. End-tidal carbon dioxide monitoring and other proper placement detection methods are useful, yet the problem of misplacement persists. Our previous work demonstrated the utility of spectral reflectance sensors for differentiating esophageal and tracheal tissues, which can be used to confirm proper endotracheal tube placement. In this study, we examine the effectiveness of spectral characterization in the presence of saline, blood, “vomit”, and soot in the trachea. Our results show that spectral properties of the trachea that differentiate it from the esophagus persist in the presence of these substances. This work further confirms the potential usefulness of this novel detection technology in field applications.
Can Tracking Data Help in Assessing Interpersonal Contact Exposure in Team Sports during the COVID-19 Pandemic?
Authors: Gonçalves Bruno , Mendes Romeu , Folgado Hugo , Figueiredo Pedro , Travassos Bruno , Barros Henrique , Campos-Fernandes Adalberto , Beckert Paulo , Brito João
Published: October 2020

During the COVID-19 pandemic, the temporary closure of physical activity and sports facilities, and the generalized cancellation or postponement of sports events have a massive impact on social and economic development. In this study, we explored the feasibility of using tracking data from a football match to assess interpersonal contact between individuals by calculating two measures of respiratory exposure. The dynamic tracking positioning of all players and referees during one international football match was analyzed. For each individual, two measures of respiratory exposure were calculated, based on the 2 m interpersonal distance recommendations for contact tracing for COVID-19 control. Overall, individuals spent a median of 0:12 mm:ss (IQR = 0:45 mm:ss) exposed to interpersonal contact of fewer than 2 m from others. The highest value of exposure was observed between two players of opposing teams (6:35 mm:ss). The results suggest that tracking data can be used to assess respiratory exposure to interpersonal contact in team sports, such as football. The measures of exposure calculated can be used to the prompt identification of high-risk contacts of COVID-19 cases during a match or a training session, but also the risk stratification of different sports and physical activities.
A New Long-Term Downward Surface Solar Radiation Dataset over China from 1958 to 2015
Authors: Hou Ning , Zhang Xiaotong , Zhang Weiyu , Xu Jiawen , Feng Chunjie , Yang Shuyue , Jia Kun , Yao Yunjun , Cheng Jie , Jiang Bo
Published: October 2020

Downward surface solar radiation (Rs) plays a dominant role in determining the climate and environment on the Earth. However, the densely distributed ground observations of Rs are usually insufficient to meet the increasing demand of the climate diagnosis and analysis well, so it is essential to build a long-term accurate Rs dataset. The extremely randomized trees (ERT) algorithm was used to generate Rs using routine meteorological observations (2000–2015) from the Climate Data Center of the Chinese Meteorological Administration (CDC/CMA). The estimated Rs values were validated against ground measurements at the national scale with an overall correlation coefficient value of 0.97, a mean bias of 0.04 Wm−2, a root-mean-square-error value of 23.12 Wm−2, and a mean relative error of 9.81%. It indicates that the estimated Rs from the ERT-based model is reasonably accurate. Moreover, the ERT-based model was used to generate a new daily Rs dataset at 756 CDC/CMA stations from 1958 to 2015. The long-term variation trends of Rs at 454 stations covering 46 consecutive years (1970–2015) were also analyzed. The Rs in China showed a significant decline trend (−1.1 Wm−2 per decade) during 1970–2015. A decreasing trend (−2.8 Wm−2 per decade) in Rs during 1970–1992 was observed, followed by a recovery trend (0.23 Wm−2 per decade) during 1992–2015. The recovery trends at individual stations were found at 233 out of 454 stations during 1970–2015, which were mainly located in southern and northern China. The new Rs dataset would substantially provide basic data for the related studies in agriculture, ecology, and meteorology.
An Information-Centric Semantic Data Collection Tree for Wireless Sensor Networks
Authors: Dinh Ngoc-Thanh , Kim Younghan
Published: October 2020

Data collection is an important application of wireless sensor networks (WSNs) and Internet of Things (IoT). Current routing and addressing operations in WSNs are based on IP addresses, while data collection and data queries are normally information-centric. The current IP-based approach incurs significant management overheads and is inefficient for semantic data collection and queries. To address the above issue, this paper proposes a semantic data collection tree (sDCT) construction scheme to build up a semantic data collection tree for wireless sensor networks. The semantic tree is rooted at the edge/sink and supports data collection tasks, queries, and configurations efficiently. We implement the sDCT in Contiki and evaluate the performance of the sDCT in comparison with the state-of-the-art scheme, 6LoWPAN/RPL and L2RMR, using telosb sensors under various scenarios. The obtained results show that the sDCT achieves a significant improvement in terms of the energy efficiency and the packet transmissions required for data collection or a query task compared to 6LoWPAN/RPL and L2RMR.
Theoretical and Experimental Study of Heterodyne Phase-Sensitive Dispersion Spectroscopy with an Injection-Current-Modulated Quantum Cascade Laser
Authors: Wang Zhen , Cheong Kin-Pang , Li Mingsheng , Wang Qiang , Ren Wei
Published: October 2020

We report the theoretical and experimental study of calibration-free heterodyne phase-sensitive dispersion spectroscopy (HPSDS) in the mid-infrared using a direct current modulated mid-infrared quantum cascade laser (QCL). The modulation of QCL current at several hundred MHz or higher generates the synchronous frequency and intensity modulation of the QCL emission. An analytical model of the phase of the beat note signal in HPSDS is derived by considering the absorption and dispersion processes and incorporating the QCL modulation parameters. In the experiment, a 4.5 μm QCL modulated at 350 MHz was used to measure N2O at 200 Torr in a 10 cm gas cell. The N2O concentrations inferred from the analytical model were compared with the nominal values to show good agreement over the concentration range of 189−805 ppm with a standard deviation <3%. When the QCL wavelength was locked at the line-center of the molecular transition, it was of interest to find that the theoretical model was simplified to that used for near-infrared HPSDS with an electro-optical modulator for laser modulation.
Deep Learning Applied to Vegetation Identification and Removal Using Multidimensional Aerial Data
Authors: F. Pinto Milena , G. Melo Aurelio , M. Honório Leonardo , L. M. Marcato André , G. S. Conceição André , O. Timotheo Amanda
Published: October 2020

When performing structural inspection, the generation of three-dimensional (3D) point clouds is a common resource. Those are usually generated from photogrammetry or through laser scan techniques. However, a significant drawback for complete inspection is the presence of covering vegetation, hiding possible structural problems, and making difficult the acquisition of proper object surfaces in order to provide a reliable diagnostic. Therefore, this research’s main contribution is developing an effective vegetation removal methodology through the use of a deep learning structure that is capable of identifying and extracting covering vegetation in 3D point clouds. The proposed approach uses pre and post-processing filtering stages that take advantage of colored point clouds, if they are available, or operate independently. The results showed high classification accuracy and good effectiveness when compared with similar methods in the literature. After this step, if color is available, then a color filter is applied, enhancing the results obtained. Besides, the results are analyzed in light of real Structure From Motion (SFM) reconstruction data, which further validates the proposed method. This research also presented a colored point cloud library of bushes built for the work used by other studies in the field.
The Relocation Problem of Field Calibrated Low-Cost Sensor Systems in Air Quality Monitoring: A Sampling Bias
Authors: Tancev Georgi , Pascale Céline
Published: October 2020

This publication revises the deteriorated performance of field calibrated low-cost sensor systems after spatial and temporal relocation, which is often reported for air quality monitoring devices that use machine learning models as part of their software to compensate for cross-sensitivities or interferences with environmental parameters. The cause of this relocation problem and its relationship to the chosen algorithm is elucidated using published experimental data in combination with techniques from data science. Thus, the origin is traced back to insufficient sampling of data that is used for calibration followed by the incorporation of bias into models. Biases often stem from non-representative data and are a common problem in machine learning, and more generally in artificial intelligence, and as such a rising concern. Finally, bias is believed to be partly reducible in this specific application by using balanced data sets generated in well-controlled laboratory experiments, although not trivial due to the need for infrastructure and professional competence.
Statistical Study of the Seasonal Variations in TEC Depletion and the ROTI during 2013–2019 over Hong Kong
Authors: Li Qiang , Zhu Yanbo , Fang Kun , Fang Jisi
Published: October 2020

Equatorial plasma bubbles (EPBs) can cause large total electron content (TEC) gradient magnitudes and significant density irregularities. In this paper, depletions and irregularities due to EPBs are identified by using the Global Positioning System (GPS)-TEC time series extracted from nine Global Navigation Satellite System (GNSS) stations over Hong Kong near the equatorial ionization anomaly (EIA) crest region from 2013 to 2019. The correlation analyses between the daily variation in the rate of TEC change index (ROTI) and that of the EPB occurrence rate, depth, and duration are presented. The monthly EPB occurrence rate, depth, duration, and ROTI show strong seasonal variations, with maxima during equinoctial seasons, especially during the moderate-to-high solar activity years of 2013–2016. Furthermore, two seasonal asymmetries can be clearly seen for these parameters from 2013 to 2016. The EPB occurrences rate, depth, and duration vary annually with the solar radio flux at 10.7 cm (F10.7) index. The correlation analyses of the EPB occurrence rate, depth, and duration are found to be much more strongly correlated with the F10.7 index on an annual basis than on a monthly basis. The correlation analysis of monthly variations shows the impacts of solar activity on EPB occurrence, depth, and duration are seasonally dependent, which is significantly greater in the equinoctial seasons and summer than in winter.
Operational Decisions and Sustainability: A Brazilian Case of a Drugs Distribution Center
Authors: Campos João Thiago de G. A. A. , Vivas Renato de Castro , Ferreira Adonias Magdiel Silva , Freires Francisco Gaudêncio Mendonça
Published: October 2020

Recently, the supply chain in the pharmaceutical sector, which is important economically to the healthcare industry worldwide, has received special attention owing to different factors involved in the distribution of drugs. Furthermore, it has an important role in global sustainability as organizations base their efficient decisions on the results from performance analysis of economic indicators. Thus, the sustainability of operations decisions must be analyzed to achieve better decision efficiency. This study integrates analytical methods of operational activities evaluation for a drug distribution center in a pharmaceutical logistic organization to analyze the sustainability of its operations. Furthermore, a proposed framework incorporates time variability management (TVM) decisions into a trade-off analysis of triple bottom-line (TBL) sustainability dimensions and operations managers’ decisions. The framework is a real-time data-gathering decision system that evaluates processes using stochastic simulation and process efficacity based on control-chart analysis and analyzes the trade-off performance. Managers’ decisions on time variability is modeled using an Analytical Hierarchy Process. The results of the trade-off analysis of sustainability and TVM indicate that economic dimensions have a higher impact on an organization than social and environmental dimensions. Managers assume that social and environmental impacts are less important to organizations’ performance. Environmental and social dimensions have different impacts on time variability decisions, where managers assume that operations’ time reduction has more impact on the social dimension, while operations’ time increase has a higher environmental impact. Thus, the framework is an effective tool for analyzing the sustainability of operations decisions, which is associated with variability analysis.
Research on Pharmaceutical Product Life Cycle Patterns for Sustainable Growth
Authors: Teramae Fumio , Makino Tomohiro , Sengoku Shintaro , Lim Yeongjoo , Natori Takashi , Kodama Kota
Published: October 2020

An important agenda of pharmaceutical companies is the establishment of therapeutic area strategies, drug modality, and geographic strategies for research and development. It is worthwhile to understand the changes in therapeutic area, modality and internationalization of the top-selling pharmaceutical drugs over the past. Hence, the purposes of this study are to investigate changes in therapeutic area, modality and internationalization of the top-selling drugs and to identify their life cycle patterns. We compared the top-selling drugs between 2011 and 2017, and found that the percentages of nichebuster cancer drugs and home region-oriented drugs have increased whereas the proportions of traditional blockbuster cardiovascular drugs and global drugs have decreased. We compared product life cycle patterns via a Kruskal–Wallis test, and identified the features of product life cycle patterns per therapeutic area and modality. We performed a case study on drugs in the same class with the same pharmacological mechanism but found no differences across cases. Our results provide insights into therapeutic area strategies that consider life cycle patterns and geographic strategies that consider the competitive advantages of home region-oriented drugs. Finally, we presented new and simple models of life cycle patterns. This approach may help such enterprises establish and maintain sustainable growth.
The Mechanism of Distribution Effectiveness of Territory Emergency Public Storage Materials
Authors: Yang Jianliang , Hou Hanping , Ju Yingjie , Gu Shiling , Qian Zeqiang , Wang Xuan
Published: October 2020

The effective distribution of public storage materials is the key to realizing rapid and accurate rescue of territories, which could truly solve the “last kilometer” problem of emergency rescue. At present, it is relatively rare to study the rapid and accurate distribution of emergency supplies by taking demand forecasts, emergency reserves, and distribution models as an organic whole. In view of the bottleneck of rapid and accurate rescue in the complex disaster environment, this paper selects various means such as field research, literature retrieval, and previous case analysis and uses the system analysis method. Next, this paper explains that the three main factors that affect the distribution of public storage materials are the demand of “black box”, the scarcity of materials, and the blindness of distribution and constructs an effective analysis framework of demand predictability, material availability, and distribution accuracy. Finally, this paper puts forward the triangle structure framework of demand forecasting, virtual public storage, and comprehensive distribution and further explains the triangle structure relationship, operation mechanism, and operation strategy of effective distribution of public storage materials.
An Experimental and Environmental Evaluation of Mortars with Recycled Demolition Waste from a Hospital Implosion in Rio de Janeiro
Authors: Grabois Thiago Melo , Caldas Lucas Rosse , Julião Nathália Rodrigues , Toledo Filho Romildo Dias
Published: October 2020

Construction and demolition waste generation have increased significantly over the century, many times, as a result of obsolete buildings that lead the effort toward demolition. This paper investigates the environmental performance of mortars developed with recycled concrete from the partial building demolition of the Clementino Fraga Filho University Hospital in Rio de Janeiro, Brazil. Life Cycle Assessment is associated with experimental data to validate the application of the residue as an alternative to cement-based mortars. Natural river sand and recycled concrete aggregates, both at a micrometer scale, are employed in the production of four different mortars of compressive strength ranging 50 MPa. The aggregates’ replacement rates defined are 15, 25, and 50% in volume. The recycled microparticles’ mineralogical composition was determined by SEM images and XRD analysis. In addition, the attached cement paste surrounding the original aggregate particle was quantified by chemical attack. Rheological and mechanical properties of the resulting mortars were assessed by the Vane spindle rheometer and uniaxial compressive strength experiments, respectively. The approach to mortars’ environmental performance considered a cradle-to-gate scope using different sensitivity analysis parameters. We demonstrated the feasibility of developing an eco-efficient mortar taking advantage of rarely applied recycled particles. Compressive strength and environmental performance (particularly, the ozone layer depletion potential and abiotic resource depletion potential categories) increased with the aggregate replacement rate. In addition, the rheological results provided relevant data, still insufficient to recycled aggregate mortars, presenting an exponential increase of yield stress with effective water to cement ratio.
Development of an IoT-Based Health Promotion System for Seniors
Authors: Liu Chia-Hui , Tu Jih-Fu
Published: October 2020

With a reducing fertility rate and the increase in life expectancy in Taiwan, the changing structure of the population has pushed Taiwan into an aged society. The demand for elderly care environments is rapidly increasing. However, to prevent an illness for the elderly is better than to treat it. Monitoring of an individual’s health is required as a periodic activity. Using wireless technology combined with physiological measurement techniques and home care equipment can assist elderly individuals to promote health and the health care service at home. In this research, a wireless sensor network has been adopted to develop context aware health promotion for an elderly-care system. The system is divided into three subsystems: the IoT-based physiological information subsystem, the context awareness-based service subsystem, and the elderly nutrition diet and health promotion subsystem. In this system, users also can select an Aging Diet Module or an Aging Exercise Module in our app. After the user selects the Aging Diet Module, the system will record and give suggestions. Moreover, the system can integrate long-term elderly diet and exercise records, and then, assist elderly to complete personal nutrition assessment and health management. The research goal is to construct a health promotion system utilizing IoT technology. In this paper, the system’s functions and implementation approaches are introduced.
Towards Forklift Safety in a Warehouse: An Approach Based on the Automatic Analysis of Resource Flows
Authors: Cantini Alessandra , De Carlo Filippo , Tucci Mario
Published: October 2020

Warehouse management is a discipline that has gained importance in recent decades. In the era of the Digital Revolution and Industry 5.0, to enable a company to attain a competitive advantage, it is necessary to identify smart improvement tools that help search for warehouse problems and solutions. A good tool to highlight issues related to layout and resource flows is the spaghetti chart which, besides being used to minimize waste according to lean philosophy, can also be used to assess warehouse safety and reliability and improve the plant sustainability. This article shows how to exploit “smart spaghetti” (spaghetti chart automatically generated by smart tracking devices) to conceive improvements in the layout and work organization of a warehouse, reducing the risk of collision between forklifts and improving the operators’ safety. The methodology involves automatically mapping the spaghetti charts (searching for critical areas where the risk of collision is high) and identifying interventions to be carried out to avoid near misses. “Smart spaghetti” constitutes a valuable decision support tool to identify potential improvements in the system through changes in the layout or in the way activities are performed. This work shows an application of the proposed technique in a pharmaceutical warehouse.
Strategic Orientations and Absorptive Capacity on Economic and Environmental Sustainability: A Study among the Batik Small and Medium Enterprises in Malaysia
Authors: Nawi Noorshella Che , Al Mamun Abdullah , Daud Raja Rosnah Raja , Nasir Noorul Azwin Md
Published: October 2020

This research intended to evaluate the effects of innovation orientation (INO), customer orientation (CSO), supplier orientation (SPO), network orientation (NWO), and absorptive capacity (ABC) on economic and environmental sustainability among the Batik small and medium enterprises (SMEs) in Malaysia. This study adopted a cross-sectional design and collected quantitative data using self-reported adopted scales from 213 randomly selected Batik SMEs from Kelantan and Terengganu, Malaysia. The results revealed that INO, CSO, and ABC had a positive and significant effect on the economic sustainability (ECS) of the Batik SMEs in Malaysia. The effects of SPO and NWO on ECS were positive but not statistically significant. It was found that ECS significantly and positively affected the environmental sustainability (ENS) of the Batik SMEs in Malaysia. Besides that, ECS mediated the effects of CSO and ABC on the ENS of the Batik SMEs in Malaysia. Furthermore, important performance matrix analysis revealed that the most important factors for ENS were Batik SMEs’ ECS, absorptive capacity, and INO. For the performance of ENS, the most important factors were CSO, SPO, and NWO. The Batik SMEs and entrepreneurial development programs and policies should focus on innovation and CSO as well as improving ABC to sustain in today’s competitive business environment.
A Model Tree-Based Vehicle Emission Model at Freeway Toll Plazas
Authors: Xu Yueru , Wang Chao , Zheng Yuan , Sun Zhuoqun , Ye Zhirui
Published: October 2020

With the increased concern over sustainable development, many efforts have been made to alleviate air quality deterioration. Freeway toll plazas can cause serious pollution, due to the increased emissions caused by stop-and-go operations. Different toll collections and different fuel types obviously influence the vehicle emissions at freeway toll plazas. Therefore, this paper proposes a model tree-based vehicle emission model by considering these factors. On-road emissions data and vehicle operation data were obtained from two different freeway toll plazas. The statistical analysis indicates that different methods of toll collection and fuel types have significant impacts on vehicle emissions at freeway toll plazas. The performance of the proposed model was compared with a polynomial regression method. Based on the results, the mean absolute percentage error (MAPE), root mean squared error (RMSE), and mean absolute error (MAE) of the proposed model were all smaller, while the R-squared value increased from 0.714 to 0.833. Finally, the variations of vehicle emissions at different locations of freeway toll plazas were calculated and shown in heat maps. The results of this study can help better estimate the vehicle emissions and give advice to the development of electronic toll collection (ETC) lanes and relevant policies at freeway toll plazas.
Shipment Policy for an Economic Production Quantity Model Considering Imperfection and Transportation Cost
Authors: Hayat Mubashir , Salah Bashir , Ullah Misbah , Hussain Iftikhar , Khan Razaullah
Published: October 2020

Determining replenishment lot size and number of shipments in a traditional production setup has been of great interest among researchers during the last decades. In order to survive modern competition, the manufacturer has to make good decisions about the lot size that is to be shipped to the retailer. Recently, several researchers have developed mathematical models for modelling different real-world situations; however, these models are lacking due to a combination of imperfection in process and shipment lot sizing. Therefore, in the proposed research, shipment policy for an imperfect production setup has been developed with transportation costs taken into consideration. The model analyzed lot sizing for manufacturers and retailers with imperfections in terms of equally sized shipments. Furthermore, an all-unit-discount policy for shipment is considered in the proposed research, and at the end, numerical computation and sensitivity analyses are carried out to gain more insight into the specifications of the model.
Carpoolers’ Perceived Accessibility of Carpooling
Authors: Friman Margareta , Lättman Katrin , Olsson Lars E.
Published: October 2020

In order to constitute a realistic option to existing travel modes, carpooling needs to be able to offer adequate levels of accessibility. Insights into how carpooling services affect perceived accessibility up until now remain unexplored. In this study we explore carpooling experiences of 122 users in Sweden and examine a number of possible determinants of the perceived accessibility of carpooling. Results show that carpooling is not perceived by the users as particularly accessible with low levels across the sample. Moreover, multiple linear hierarchical regression analyses show that simplicity of travel, population density, years of education, and school and work-trips appear to affect perceptions of accessibility of carpooling, whereas travel time and cost appear not to. The final model explains a third of the variance in perceived accessibility of carpooling, thus nearly two thirds of the variation is still unaccounted for. Future research should explore further possible determinants of perceived accessibility of carpooling in order to explain, understand, and counteract the low levels of accessibility that appear to be linked to this specific travel mode.
Sustainability of Underground Hydro-Technologies: From Ancient to Modern Times and toward the Future
Authors: Valipour Mohammad , Ahmed Abdelkader T. , Antoniou Georgios P. , Sala Renato , Parise Mario , Salgot Miquel , Sanaan Bensi Negar , Angelakis Andreas N.
Published: October 2020

An underground aqueduct is usually a canal built in the subsurface to transfer water from a starting point to a distant location. Systems of underground aqueducts have been applied by ancient civilizations to manage different aspects of water supply. This research reviews underground aqueducts from the prehistoric period to modern times to assess the potential of achieving sustainable development of water distribution in the sectors of agriculture and urban management, and provides valuable insights into various types of ancient underground systems and tunnels. The review illustrates how these old structures are a testament of ancient people’s ability to manage water resources using sustainable tools such as aqueducts, where the functionality works by using, besides gravity, only “natural” engineering tools like inverted siphons. The study sheds new light on human’s capability to collect and use water in the past. In addition, it critically analyzes numerous examples of ancient/historic/pre-industrial underground water supply systems that appear to have remained sustainable up until recent times. The sustainability of several underground structures is examined, correlated to their sound construction and regular maintenance. Moreover, several lessons can be learned from the analysis of ancient hydraulic works, particularly now, as many periodically hydrologic crises have occurred recently, overwhelmingly impacted by climate change and/or over-exploitation and degradation of available water resources.
Psychological Safety in Aviation New Product Development Teams: Case Study of 737 MAX Airplane
Authors: Naor Michael , Adler Nicole , Pinto Gavriel David , Dumanis Alon
Published: October 2020

The goal of current study is to discern the antecedents of two airplane accidents involving the Boeing MAX 737. The theory of normal accidents serves as a lens to comprehend the hazard stemming from MAX design with dissonance between two critical systems: engine propulsion and flight control. Cooper’s framework further delineates lack of psychological safety during prototype development from the project’s inception along six dimensions: management/supervision, safety systems, risk, work pressure, competence, and procedures/rules. The analysis indicates dearth of leadership commitment for a safety culture under time pressure and budget constraint. Our results corroborate the paramount importance of the pilot’s extensive simulator training in order to test the interaction between the innovative Maneuvering Characteristics Augmentation System and human behavior response time. Lessons gleaned from the study include three insights. First, the importance of meticulously testing a prototype during the new product development stage and the hazard stemming from improvisation to extend the life of outdated engineering design. Second, the necessity of regulatory authorities, such as the Federal Aviation Administration, undergoing a modernization process by invigorating their ranks with data scientists attuned to 21st century skills in big data analytics. Third, FAA should diminish the delegation of self-certified permits to manufacturers.
Oleotourism: A Comparison of Three Mediterranean Countries
Authors: D’Auria Anna , Marano-Marcolini Carla , Čehić Ana , Tregua Marco
Published: October 2020

The recent trends in the tourism industry, as well as the attention paid by scholars, practitioners, and institutions, show the relevance of natural tourism as a lever for local development (United Nations World Tourism Organization -UNWTO-, 2005). In this scenario, the business of oleotourism, namely, a form of domestic tourism based on activities related to olive oil production, its tasting, and some connected rural experiences such as harvesting, is continuously—albeit slowly—growing in Europe and especially in the Mediterranean area. Scholars agree that oleotourism plays a key role for multiple reasons, due to its relations to local territories, firms, resources, and other forms of tourism, also favoring sustainable development. Due to the interplay with the local context, the authors plan to combine and compare the evidence from three Mediterranean countries offering examples of tourism initiatives based on olive oil, namely, Spain, Italy, and Croatia. The similarities and differences emerging from the comparison will expand the understanding of this phenomenon and lead to the highlighting of key features and choices in favoring its development in the coming years. Therefore, this research, through the analysis of both theoretical and practical evidences and data from the local contexts, aims to identify additional knowledge for scholars, managers, and policy-makers. The results of the analysis allow the authors to conclude that, although each of the three countries is in a different stage of development, they all have elements that seem to be common to this type of tourism. Finally, it is concluded that oleotourism can be characterized as a form of sustainable tourism, given the preservation of local customs and landscapes, the participation of the resident community, or the development of quality and food safety labels.
The State of the Art of Use of the Concept of Ecosystem Services within Spatial Plans in the Czech Republic
Authors: Schneider Jiří , Kubíčková Hana
Published: October 2020

Although the use and management of ecosystem services (ES) resources and the promotion of their provision are a standard and necessary part of spatial planning tools and documents, a direct implementation of this concept is exceptional. Researchers and entire projects have so far focused mainly on identification of ecosystem services and their resources in urban environment, or on the analysis of their occurrence in spatial planning documents. That was the goal of our research as well. Spatial planning documents, systematically and methodically re-defined using ecosystem services, are what is still lacking. Our article presents the results of the analysis of the use of ecosystem services in spatial plans of five cities, regional centers in the Czech Republic. We used a text evaluation methodology focused on the explicit and implicit expression of ecosystem services. We analyzed the overall approach to the creation of spatial plans. In addition to the spatial plans, we also analyzed their assignments (SPA). We found that the current spatial planning methodology does not work with the ecosystem services approach (ESA) systemically. It focuses mainly on ES resources and implicitly envisages their provision. SPAs are a more flexible and effective tool for enforcing ESA in spatial planning than the lengthy legislative process. However, this presupposes greater knowledge of SPA among the public and decision makers.