bluuebunny/crossref_metadata_2025 huggingface dataset:
Improving the Accuracy of Decawave’s UWB MDEK1001 Location System by Gaining Access to Multiple Ranges
Authors: Jiménez Antonio R. , Seco Fernando
Published: March 2021

The location of people, robots, and Internet-of-Things (IoT) devices has become increasingly important. Among the available location technologies, solutions based on ultrawideband (UWB) radio are having much success due to their accuracy, which is ideally at a centimeter level. However, this accuracy is degraded in most common indoor environments due to the presence of obstacles which block or reflect the radio signals used for ranging. One way to circumvent this difficulty is through robust estimation algorithms based on measurement redundancy, permitting to minimize the effect of significantly erroneous ranges (outliers). This need for redundancy often conflicts with hardware restraints put up by the location system’s designers. In this work, we present a procedure to increase the redundancy of UWB systems and demonstrate it with the help of a commercial system made by Decawave. This system is particularly easy to deploy, by configuring a network of beacons (anchors) and devices (tags) to be located; however, its architecture presents a major disadvantage as each tag to be located can only measure ranges to a maximum of four anchors. This limitation is embedded in the Positioning and Networking Stack (PANS) protocol designed by Decawave, and therefore is not easy to bypass without a total redesign of the firmware. In this paper, we analyze the strategies that we have been able to identify in order to provide this equipment with multiple range measurements, and thus enable each tag to be positioned with more than four measured ranges. We will see the advantages and disadvantages of each of these strategies, and finally we will adopt a solution that we implemented to be able to measure up to eight ranges for each mobile device (tag). This solution implies the duplication of the tags at the mobile user, and the creation of a double interleaved network of anchors. The range among tags and the eight beacons is obtained through an API via a wireless BLE protocol at a 10 Hz rate. A robustified Extended Kalman filter (EKF) is designed to estimate, by trilateration, the position of the pair of mobile tags, using eight ranges. Two different scenarios are used to make localization experimentation: a laboratory and an apartment. Our position estimation, which exploits redundant information and performs outlier removal, is compared with the commercial solution limited to four ranges, demonstrating the need and advantages of our multi-range approach.
A Smartphone Camera Colorimetric Assay of Acetylcholinesterase and Butyrylcholinesterase Activity
Authors: Pohanka Miroslav , Zakova Jitka
Published: March 2021

Acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) can serve as biochemical markers of various pathologies like liver disfunction and poisonings by nerve agents. Ellman’s assay is the standard spectrophotometric method to measure cholinesterase activity in clinical laboratories. The authors present a new colorimetric test to assess AChE and BChE activity in biological samples using chromogenic reagents, treated 3D-printed measuring pads and a smartphone camera as a signal detector. Multiwell pads treated with reagent substrates 2,6-dichlorophenolindophenyl acetate, indoxylacetate, ethoxyresorufin and methoxyresorufin were prepared and tested for AChE and BChE. In the experiments, 3D-printed pads containing indoxylacetate as a chromogenic substrate were optimal for analytical purposes. The best results were achieved using the red (R) channel, where the limit of detection was 4.05 µkat/mL for BChE and 4.38 µkat/mL for AChE using a 40 µL sample and a 60 min assay. The major advantage of this method is its overall simplicity, as samples are applied directly without any specific treatment or added reagents. The assay was also validated to the standard Ellman’s assay using human plasma samples. In conclusion, this smartphone camera-based colorimetric assay appears to have practical applicability and to be a suitable method for point-of-care testing because it does not require specific manipulation, additional education of staff or use of sophisticated analytical instruments.
A Highly Birefringent Photonic Crystal Fiber for Terahertz Spectroscopic Chemical Sensing
Authors: Yang Tianyu , Zhang Liang , Shi Yunjie , Liu Shidi , Dong Yuming
Published: March 2021

A photonic crystal fiber (PCF) with high relative sensitivity was designed and investigated for the detection of chemical analytes in the terahertz (THz) regime. To ease the complexity, an extremely simple cladding employing four struts is adopted, which forms a rectangular shaped core area for filling with analytes. Results of enormous simulations indicate that a minimum 87.8% relative chemical sensitivity with low confinement and effective material absorption losses can be obtained for any kind of analyte, e.g., HCN (1.26), water (1.33), ethanol (1.35), KCN (1.41), or cocaine (1.50), whose refractive index falls in the range of 1.2 to 1.5. Besides, the PCF can also achieve high birefringence (∼0.01), low and flat dispersion, a large effective modal area, and a large numerical aperture within the investigated frequency range from 0.5 to 1.5 THz. We believe that the proposed PCF can be applied to chemical sensing of liquid and THz systems requiring wide-band polarization-maintaining transmission and low attenuation.
A New Hybrid Sensitive PANI/SWCNT/Ferrocene-Based Layer for a Wearable CO Sensor
Authors: Savin Mihaela , Mihailescu Carmen-Marinela , Avramescu Viorel , Dinulescu Silviu , Firtat Bogdan , Craciun Gabriel , Brasoveanu Costin , Pachiu Cristina , Romanitan Cosmin , Serban Andreea-Bianca , Ion Alina Catrinel , Moldovan Carmen
Published: March 2021

Developing a sensing layer with high electroactive properties is an important aspect for proper functionality of a wearable sensor. The polymeric nanocomposite material obtained by a simple electropolymerization on gold interdigitated electrodes (IDEs) can be optimized to have suitable conductive properties to be used with direct current (DC) measurements. A new layer based on polyaniline:poly(4-styrenesulfonate) (PANI:PSS)/single-walled carbon nanotubes (SWCNT)/ferrocene (Fc) was electrosynthesized and deposed on interdigital transducers (IDT) and was characterized in detail using electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), scanning electron microscopy (SEM), Raman spectroscopy, X-ray photoemission spectroscopy (XPS), and X-ray diffraction (XRD). The sensor characteristics of the material towards carbon monoxide (CO) in the concentration range of 10–300 ppm were examined, showing a minimal relative humidity interference of only 1% and an increase of sensitivity with the increase of CO concentration. Humidity interference could be controlled by the number of CV cycles when a compact layer was formed and the addition of Fc played an important role in the decrease of humidity. The results for CO detection can be substantially improved by optimizing the number of deposition cycles and enhancing the Fc concentration. The material was developed for selective detection of CO in real environmental conditions and shows good potential for use in a wearable sensor.
Refractive Index Sensors Based on Long-Period Grating in a Negative Curvature Hollow-Core Fiber
Authors: Stawska Hanna Izabela , Popenda Maciej Andrzej
Published: March 2021

Long-period optical fiber gratings (LPGs) are one of the widely used concepts for the sensing of refractive index (RI) changes. Negative curvature hollow-core fibers (NCHCFs), with their relatively large internal diameters that are easy to fill with liquids, appear as a very interesting medium to combine with the idea of LPGs and use for RI sensing. However, to date, there has been no investigation of the RI sensing capabilities of the NCHCF-based LPGs. The results presented in the paper do not only address this matter, but also compare the RI sensitivities of the NCHCFs alone and the gratings. By modeling two revolver-type fibers, with their internal diameters reflecting the results of the possible LPG-inscription process, the authors show that the fibers’ transmission windows shift in response to the RI change, resulting in changes in RI sensitivities as high as −4411 nm/RIU. On the contrary, the shift in the transmission dip of the NCHCF-based LPGs corresponds to a sensitivity of −658 nm/RIU. A general confirmation of these results was ensured by comparing the analytical formulas describing the sensitivities of the NCHCFs and the NCHCF-based LPGs.
Real-Time Musculoskeletal Kinematics and Dynamics Analysis Using Marker- and IMU-Based Solutions in Rehabilitation
Authors: Stanev Dimitar , Filip Konstantinos , Bitzas Dimitrios , Zouras Sokratis , Giarmatzis Georgios , Tsaopoulos Dimitrios , Moustakas Konstantinos
Published: March 2021

This study aims to explore the possibility of estimating a multitude of kinematic and dynamic quantities using subject-specific musculoskeletal models in real-time. The framework was designed to operate with marker-based and inertial measurement units enabling extensions far beyond dedicated motion capture laboratories. We present the technical details for calculating the kinematics, generalized forces, muscle forces, joint reaction loads, and predicting ground reaction wrenches during walking. Emphasis was given to reduce computational latency while maintaining accuracy as compared to the offline counterpart. Notably, we highlight the influence of adequate filtering and differentiation under noisy conditions and its importance for consequent dynamic calculations. Real-time estimates of the joint moments, muscle forces, and reaction loads closely resemble OpenSim’s offline analyses. Model-based estimation of ground reaction wrenches demonstrates that even a small error can negatively affect other estimated quantities. An application of the developed system is demonstrated in the context of rehabilitation and gait retraining. We expect that such a system will find numerous applications in laboratory settings and outdoor conditions with the advent of predicting or sensing environment interactions. Therefore, we hope that this open-source framework will be a significant milestone for solving this grand challenge.
Forecasting Nonlinear Systems with LSTM: Analysis and Comparison with EKF
Authors: Llerena Caña Juan Pedro , García Herrero Jesús , Molina López José Manuel
Published: March 2021

Certain difficulties in path forecasting and filtering problems are based in the initial hypothesis of estimation and filtering techniques. Common hypotheses include that the system can be modeled as linear, Markovian, Gaussian, or all at one time. Although, in many cases, there are strategies to tackle problems with approaches that show very good results, the associated engineering process can become highly complex, requiring a great deal of time or even becoming unapproachable. To have tools to tackle complex problems without starting from a previous hypothesis but to continue to solve classic challenges and sharpen the implementation of estimation and filtering systems is of high scientific interest. This paper addresses the forecast–filter problem from deep learning paradigms with a neural network architecture inspired by natural language processing techniques and data structure. Unlike Kalman, this proposal performs the process of prediction and filtering in the same phase, while Kalman requires two phases. We propose three different study cases of incremental conceptual difficulty. The experimentation is divided into five parts: the standardization effect in raw data, proposal validation, filtering, loss of measurements (forecasting), and, finally, robustness. The results are compared with a Kalman filter, showing that the proposal is comparable in terms of the error within the linear case, with improved performance when facing non-linear systems.
Underwater Object Recognition Using Point-Features, Bayesian Estimation and Semantic Information
Authors: Himri Khadidja , Ridao Pere , Gracias Nuno
Published: March 2021

This paper proposes a 3D object recognition method for non-coloured point clouds using point features. The method is intended for application scenarios such as Inspection, Maintenance and Repair (IMR) of industrial sub-sea structures composed of pipes and connecting objects (such as valves, elbows and R-Tee connectors). The recognition algorithm uses a database of partial views of the objects, stored as point clouds, which is available a priori. The recognition pipeline has 5 stages: (1) Plane segmentation, (2) Pipe detection, (3) Semantic Object-segmentation and detection, (4) Feature based Object Recognition and (5) Bayesian estimation. To apply the Bayesian estimation, an object tracking method based on a new Interdistance Joint Compatibility Branch and Bound (IJCBB) algorithm is proposed. The paper studies the recognition performance depending on: (1) the point feature descriptor used, (2) the use (or not) of Bayesian estimation and (3) the inclusion of semantic information about the objects connections. The methods are tested using an experimental dataset containing laser scans and Autonomous Underwater Vehicle (AUV) navigation data. The best results are obtained using the Clustered Viewpoint Feature Histogram (CVFH) descriptor, achieving recognition rates of 51.2%, 68.6% and 90%, respectively, clearly showing the advantages of using the Bayesian estimation (18% increase) and the inclusion of semantic information (21% further increase).
Improving the Detection of the Contact Point in Active Sensing Antennae by Processing Combined Static and Dynamic Information
Authors: Mérida-Calvo Luis , Feliu-Talegón Daniel , Feliu-Batlle Vicente
Published: March 2021

The design and application of sensing antenna devices that mimic insect antennae or mammal whiskers is an active field of research. However, these devices still require new developments if they are to become efficient and reliable components of robotic systems. We, therefore, develop and build a prototype composed of a flexible beam, two servomotors that drive the beam and a load cell sensor that measures the forces and torques at the base of the flexible beam. This work reports new results in the area of the signal processing of these devices. These results will make it possible to estimate the point at which the flexible antenna comes into contact with an object (or obstacle) more accurately than has occurred with previous algorithms. Previous research reported that the estimation of the fundamental natural frequency of vibration of the antenna using dynamic information is not sufficient as regards determining the contact point and that the estimation of the contact point using static information provided by the forces and torques measured by the load cell sensor is not very accurate. We consequently propose an algorithm based on the fusion of the information provided by the two aforementioned strategies that enhances the separate benefits of each one. We demonstrate that the adequate combination of these two pieces of information yields an accurate estimation of the contacted point of the antenna link. This will enhance the precision of the estimation of points on the surface of the object that is being recognized by the antenna. Thorough experimentation is carried out in order to show the features of the proposed algorithm and establish its range of application.
Internet of Things: Evolution, Concerns and Security Challenges
Authors: Malhotra Parushi , Singh Yashwant , Anand Pooja , Bangotra Deep Kumar , Singh Pradeep Kumar , Hong Wei-Chiang
Published: March 2021

The escalated growth of the Internet of Things (IoT) has started to reform and reshape our lives. The deployment of a large number of objects adhered to the internet has unlocked the vision of the smart world around us, thereby paving a road towards automation and humongous data generation and collection. This automation and continuous explosion of personal and professional information to the digital world provides a potent ground to the adversaries to perform numerous cyber-attacks, thus making security in IoT a sizeable concern. Hence, timely detection and prevention of such threats are pre-requisites to prevent serious consequences. The survey conducted provides a brief insight into the technology with prime attention towards the various attacks and anomalies and their detection based on the intelligent intrusion detection system (IDS). The comprehensive look-over presented in this paper provides an in-depth analysis and assessment of diverse machine learning and deep learning-based network intrusion detection system (NIDS). Additionally, a case study of healthcare in IoT is presented. The study depicts the architecture, security, and privacy issues and application of learning paradigms in this sector. The research assessment is finally concluded by listing the results derived from the literature. Additionally, the paper discusses numerous research challenges to allow further rectifications in the approaches to deal with unusual complications.
Reference Frame Unification of IMU-Based Joint Angle Estimation: The Experimental Investigation and a Novel Method
Authors: Yi Chunzhi , Jiang Feng , Yang Chifu , Chen Zhiyuan , Ding Zhen , Liu Jie
Published: March 2021

Inertial measurement unit (IMU)-based joint angle estimation is an increasingly mature technique that has a broad range of applications in clinics, biomechanics and robotics. However, the deviations of different IMUs’ reference frames, referring to IMUs’ individual orientations estimating errors, is still a challenge for improving the angle estimation accuracy due to conceptual confusion, relatively simple metrics and the lack of systematical investigation. In this paper, we clarify the determination of reference frame unification, experimentally study the time-varying characteristics of reference frames’ deviations and accordingly propose a novel method with a comprehensive metric to unify reference frames. To be specific, we firstly define the reference frame unification (RFU) and distinguish it with drift correction that has always been confused with the term RFU. Secondly, we design a mechanical gimbal-based experiment to study the deviations, where sensor-to-body alignment and rotation-caused differences of orientations are excluded. Thirdly, based on the findings of the experiment, we propose a novel method to utilize the consistency of the joint axis under the hinge-joint constraint, gravity acceleration and local magnetic field to comprehensively unify reference frames, which meets the nonlinear time-varying characteristics of the deviations. The results on ten human subjects reveal the feasibility of our proposed method and the improvement from previous methods. This work contributes to a relatively new perspective of considering and improving the accuracy of IMU-based joint angle estimation.
An Improved Equilibrium Optimizer with Application in Unmanned Aerial Vehicle Path Planning
Authors: Tang An-Di , Han Tong , Zhou Huan , Xie Lei
Published: March 2021

The unmanned aerial vehicle (UAV) path planning problem is a type of complex multi-constraint optimization problem that requires a reasonable mathematical model and an efficient path planning algorithm. In this paper, the fitness function including fuel consumption cost, altitude cost, and threat cost is established. There are also four set constraints including maximum flight distance, minimum flight altitude, maximum turn angle, and maximum climb angle. The constrained optimization problem is transformed into an unconstrained optimization problem by using the penalty function introduced. To solve the model, a multiple population hybrid equilibrium optimizer (MHEO) is proposed. Firstly, the population is divided into three subpopulations based on fitness and different strategies are executed separately. Secondly, a Gaussian distribution estimation strategy is introduced to enhance the performance of MHEO by using the dominant information of the populations to guide the population evolution. The equilibrium pool is adjusted to enhance population diversity. Furthermore, the Lévy flight strategy and the inferior solution shift strategy are used to help the algorithm get rid of stagnation. The CEC2017 test suite was used to evaluate the performance of MHEO, and the results show that MHEO has a faster convergence speed and better convergence accuracy compared to the comparison algorithms. The path planning simulation experiments show that MHEO can steadily and efficiently plan flight paths that satisfy the constraints, proving the superiority of the MHEO algorithm while verifying the feasibility of the path planning model.
3D DCT Based Image Compression Method for the Medical Endoscopic Application
Authors: Xue Jiawen , Yin Li , Lan Zehua , Long Mingzhu , Li Guolin , Wang Zhihua , Xie Xiang
Published: March 2021

This paper proposes a novel 3D discrete cosine transform (DCT) based image compression method for medical endoscopic applications. Due to the high correlation among color components of wireless capsule endoscopy (WCE) images, the original 2D Bayer data pattern is reconstructed into a new 3D data pattern, and 3D DCT is adopted to compress the 3D data for high compression ratio and high quality. For the low computational complexity of 3D-DCT, an optimized 4-point DCT butterfly structure without multiplication operation is proposed. Due to the unique characteristics of the 3D data pattern, the quantization and zigzag scan are ameliorated. To further improve the visual quality of decompressed images, a frequency-domain filter is proposed to eliminate the blocking artifacts adaptively. Experiments show that our method attains an average compression ratio (CR) of 22.94:1 with the peak signal to noise ratio (PSNR) of 40.73 dB, which outperforms state-of-the-art methods.
A Review of Recent Distributed Optical Fiber Sensors Applications for Civil Engineering Structural Health Monitoring
Authors: Bado Mattia Francesco , Casas Joan R.
Published: March 2021

The present work is a comprehensive collection of recently published research articles on Structural Health Monitoring (SHM) campaigns performed by means of Distributed Optical Fiber Sensors (DOFS). The latter are cutting-edge strain, temperature and vibration monitoring tools with a large potential pool, namely their minimal intrusiveness, accuracy, ease of deployment and more. Its most state-of-the-art feature, though, is the ability to perform measurements with very small spatial resolutions (as small as 0.63 mm). This review article intends to introduce, inform and advise the readers on various DOFS deployment methodologies for the assessment of the residual ability of a structure to continue serving its intended purpose. By collecting in a single place these recent efforts, advancements and findings, the authors intend to contribute to the goal of collective growth towards an efficient SHM. The current work is structured in a manner that allows for the single consultation of any specific DOFS application field, i.e., laboratory experimentation, the built environment (bridges, buildings, roads, etc.), geotechnical constructions, tunnels, pipelines and wind turbines. Beforehand, a brief section was constructed around the recent progress on the study of the strain transfer mechanisms occurring in the multi-layered sensing system inherent to any DOFS deployment (different kinds of fiber claddings, coatings and bonding adhesives). Finally, a section is also dedicated to ideas and concepts for those novel DOFS applications which may very well represent the future of SHM.
Development of a Point-of-Care Assay for HIV-1 Viral Load Using Higher Refractive Index Antibody-Coated Microbeads
Authors: Sher Mazhar , Coleman Benjamin , Caputi Massimo , Asghar Waseem
Published: March 2021

The detection of viruses using imaging techniques is challenging because of the weak scattering of light generated by the targets of sizes in the nanometer range. The system we have developed overcomes the light scattering problems by utilizing antibody-coated microbeads of higher index of refraction that can specifically bind with viruses and increase the acceptance angle. Using the new technology, we have developed a portable, cost-effective, and field-deployable platform for the rapid quantification of HIV-1 viral load for point-of-care (POC) settings. The system combines microfluidics with a wide field of view lensless imaging technology. Highly specific antibodies are functionalized to a glass slide inside a microchip to capture HIV-1 virions. The captured virions are then bound by antibody-conjugated microbeads, which have a higher refraction index. The microbeads—HIV-1 virions complexes generate diffraction patterns that are detected with a custom-built imaging setup and rapidly and accurately quantified by computational analysis. This platform technology enables fast nanoscale virus imaging and quantification from biological samples and thus can play a significant role in the detection and management of viral diseases.
The Use of Infrared Thermography to Develop and Assess a Wearable Sock and Monitor Foot Temperature in Diabetic Subjects
Authors: Torreblanca González José , Gómez-Martín Beatriz , Hernández Encinas Ascensión , Martín-Vaquero Jesús , Queiruga-Dios Araceli , Martínez-Nova Alfonso
Published: March 2021

One important health problem that could affect diabetics is diabetic foot syndrome, as risk of ulceration, neuropathy, ischemia and infection. Unnoticed minor injuries, subsequent infection and ulceration may end in a foot amputation. Preliminary studies have shown a relationship between increased skin temperature and asymmetries between the same regions of both feet. In the preulceration phase, to develop a smart device able to control the temperature of these types of patients to avoid this risk might be very useful. A statistical analysis has been carried out with a sample of foot temperature data obtained from 93 individuals, of whom 44 are diabetics and 49 nondiabetics and among them 43% are men and 57% are women. Data obtained with a thermographic camera has been successful in providing a set of regions of interest, where the temperature could influence the individual, and the behavior of several variables that could affect these subjects provides a mathematical model. Finally, an in-depth analysis of existing sensors situated in those positions, namely, heel, medial midfoot, first metatarsal head, fifth metatarsal head, and first toe has allowed for the development of a smart sock to store temperatures obtained every few minutes in a mobile device.
A Comparative Analysis of Signal Decomposition Techniques for Structural Health Monitoring on an Experimental Benchmark
Authors: Civera Marco , Surace Cecilia
Published: March 2021

Signal Processing is, arguably, the fundamental enabling technology for vibration-based Structural Health Monitoring (SHM), which includes damage detection and more advanced tasks. However, the investigation of real-life vibration measurements is quite compelling. For a better understanding of its dynamic behaviour, a multi-degree-of-freedom system should be efficiently decomposed into its independent components. However, the target structure may be affected by (damage-related or not) nonlinearities, which appear as noise-like distortions in its vibrational response. This response can be nonstationary as well and thus requires a time-frequency analysis. Adaptive mode decomposition methods are the most apt strategy under these circumstances. Here, a shortlist of three well-established algorithms has been selected for an in-depth analysis. These signal decomposition approaches—namely, the Empirical Mode Decomposition (EMD), the Hilbert Vibration Decomposition (HVD), and the Variational Mode Decomposition (VMD)—are deemed to be the most representative ones because of their extensive use and favourable reception from the research community. The main aspects and properties of these data-adaptive methods, as well as their advantages, limitations, and drawbacks, are discussed and compared. Then, the potentialities of the three algorithms are assessed firstly on a numerical case study and then on a well-known experimental benchmark, including nonlinear cases and nonstationary signals.
Development of a Compound Speckle Interferometer for Precision Three-Degree-of-Freedom Displacement Measurement
Authors: Hsieh Hung-Lin , Sun Bo-Yen
Published: March 2021

In this study, a compound speckle interferometer for measuring three-degree-of-freedom (3-DOF) displacement is proposed. The system, which combines heterodyne interferometry, speckle interferometry and beam splitting techniques, can perform precision 3-DOF displacement measurements, while still having the advantages of high resolution and a relatively simple configuration. The incorporation of speckle interferometry allows for non-contact displacement measurements by detecting the phase of the speckle interference pattern formed from the convergence of laser beams on the measured rough surface. Experiments were conducted to verify the measurement capabilities of the system, and the results show that the proposed system has excellent measurement capabilities suitable for future real-world applications.
Marker Placement Reliability and Objectivity for Biomechanical Cohort Study: Healthy Aging in Industrial Environment (HAIE—Program 4)
Authors: Malus Jan , Skypala Jiri , Silvernail Julia Freedman , Uchytil Jaroslav , Hamill Joseph , Barot Tomas , Jandacka Daniel
Published: March 2021

In large cohort studies, due to the time-consuming nature of the measurement of movement biomechanics, more than one evaluator needs to be involved. This may increase the potential occurrence of error due to inaccurate positioning of markers to the anatomical locations. The purpose of this study was to determine the reliability and objectivity of lower limb segments length by multiple evaluators in a large cohort study concerning healthy aging in an industrial environment. A total of eight evaluators performed marker placements on five participants on three different days. Evaluators placed markers bilaterally on specific anatomical locations of the pelvis, thigh, shank and foot. On the right foot, markers were placed in anatomical locations to define a multi-segmental foot model. The position of the marker at the anatomical locations was recorded by a motion capture system. The reliability and objectivity of lower limb segment lengths was determined by the intraclass correlation coefficient of a two-way random model and of the two-way mixed model, respectively. For all evaluators for all segments, the average reliability and objectivity was greater than 0.8, except for the metatarsus segment (0.683). Based on these results, we can conclude that multiple evaluators can be engaged in a large cohort study in the placement of anatomical markers.
An FDA-Based Approach for Clustering Elicited Expert Knowledge
Authors: Barrera-Causil Carlos , Correa Juan , Zamecnik Andrew , Torres-Avilés Francisco , Marmolejo-Ramos Fernando
Published: March 2021

Expert knowledge elicitation (EKE) aims at obtaining individual representations of experts’ beliefs and render them in the form of probability distributions or functions. In many cases the elicited distributions differ and the challenge in Bayesian inference is then to find ways to reconcile discrepant elicited prior distributions. This paper proposes the parallel analysis of clusters of prior distributions through a hierarchical method for clustering distributions and that can be readily extended to functional data. The proposed method consists of (i) transforming the infinite-dimensional problem into a finite-dimensional one, (ii) using the Hellinger distance to compute the distances between curves and thus (iii) obtaining a hierarchical clustering structure. In a simulation study the proposed method was compared to k-means and agglomerative nesting algorithms and the results showed that the proposed method outperformed those algorithms. Finally, the proposed method is illustrated through an EKE experiment and other functional data sets.
Senior Consumer Motivations and Perceived Value of Robot Service Restaurants in Korea
Authors: Kwak Min-Kyu , Lee JeungSun , Cha Seong-Soo
Published: March 2021

This research empirically tested a theoretical model by defining senior customers’ intentions to use robot service restaurants emerging in South Korea. Non-face-to-face services have become increasingly important for seniors. Therefore, restaurant marketers should cater to senior customers’ needs by sustaining robot service restaurants. The study analyzed 243 questionnaires to verify the reliability and validity of the measurement items. The research hypotheses were examined using structural equation modeling (SEM). The suggested model comprised three stages: motivated consumer innovativeness (MCI), perceived value, and planned behavior (attitude, intention to use). The results revealed that senior customers’ perceived values positively influenced attitude and were enhanced by hedonically MCI (hMCI) and socially MCI. Moreover, the hedonic and social elements of motivation improved the attitude and usage intentions of robot service restaurants for senior customers. However, these relationships differed in terms of the income level of the customer groups. For the low-income senior-level group, hMCI was more influential on the perceived value. This study is meaningful because it analyzes the effect of MCI of seniors on the perceived value of robot service restaurants, which are growing rapidly in South Korea. It has empirically proved the moderating effect of different income groups, providing practical implications.
Consumer Intention to Participate in E-Waste Collection Programs: A Study of Smartphone Waste in Indonesia
Authors: Sari Diana Puspita , Masruroh Nur Aini , Asih Anna Maria Sri
Published: March 2021

Indonesia is a developing country with a low-level e-waste management system based on a limited number of informal initiatives. E-waste requires proper management procedures, which involve the design of a reverse logistics management network. Consumers play a critical role in such a network, because the network runs when they willingly participate as suppliers of waste. This paper applies the Theory of Planned Behavior framework and extends it using Reverse Logistics drivers, the Value Belief Norm Theory, and facility accessibility to explain consumer intention to participate in e-waste collection programs. A survey was conducted on smartphone users in Indonesia, with a total of 324 valid questionnaires. The results showed that government drivers, facility accessibility, and personal attitudes significantly influence consumer intentions. Environmental concern has a positive influence on consumer intentions through the variables of the Theory of Planned Behavior and perceived behavioral control through government drivers. This study shows the need for integration, because the variables reinforce each other. However, neither economic drivers nor subjective norms significantly influence consumer intentions. This finding distinguishes Indonesia from other countries, especially developed countries, in that e-waste collection programs have not become part of the culture in Indonesia. For this reason, Indonesia needs regulations, as the most influential variable, to regulate the implementation of such a program.
International Comparison of the Efficiency of Agricultural Science, Technology, and Innovation: A Case Study of G20 Countries
Authors: Guo Xiangyu , Deng Canhui , Wang Dan , Du Xu , Li Jiali , Wan Bowen
Published: March 2021

An efficiency-oriented innovation analysis will enhance the understanding of the operational quality related to the transformation process of limited innovation investments for improving innovation outputs. The purpose of this study was to measure the static-dynamic efficiency of agricultural science, technology, and innovation (ASTI) and identify the efficiency determinants across the Group of Twenty (G20) countries. First, the static comprehensive efficiency of ASTI was measured employing the Data Envelopment Analysis (DEA)-BCC model, and some of the binding constraints to higher efficiency were investigated. Then, we applied the DEA-Malmquist index model to calculate the efficiency change of ASTI in certain periods and decomposed the sources of efficiency change. Finally, the G20 countries were classified into four-level clusters based on the rankings of efficiency measurement and capability evaluation of ASTI to locate the type of ASTI level and identify the type change in both the efficiency and capability. The empirical results indicate the following. (1) The efficiency range of the G20 developing countries was relatively larger than the G20 developed countries. The G20 developed countries showed a fluctuating downward trend, while the G20 developing countries showed an upward trend from the perspective of efficient proportion. The R&D expenditure redundancy and the agricultural journal papers deficiency were the main binding constraints to the higher efficiency of ASTI. (2) The total factor productivity change (TFPC) of ASTI showed an alternating trend of “decline–growth–continuous decline–growth recovery”, where the G20 developed countries experienced “growth–decline–growth” and the G20 developing countries underwent a fluctuating upward trend. The TFPC of ASTI in most G20 countries was primarily due to technological change. (3) The G20 developed countries usually had advantages in capacity, while the G20 developing countries performed better in efficiency.
Casual Carpooling: A Strategy to Support Implementation of Mobility-as-a-Service in a Developing Country
Authors: Gandia Rodrigo , Antonialli Fabio , Nicolaï Isabelle , Sugano Joel , Oliveira Julia , Oliveira Izabela
Published: March 2021

Mobility-as-a-Service (MaaS) offers tailored-made, on-demand mobility solutions to users by integrating on a single service subscription, public and private transport modes. However, the concept is still uncertain, and its current development and applicability is centered on developed countries. On the other hand, we advocate that MaaS is modular, adaptable, and applicable to several realities. In developing countries where public transport is mostly inefficient and insufficient, MaaS could help to “balance the scale” with private transport offerings, such as ridesharing. Casual carpooling could be an affordable alternative. Not only for being a low-tech transport mode but also for optimizing vehicle usage of idle seats. In that optics, we have identified drivers who would facilitate integrating casual practices into a MaaS. To identify the motivating factors behind casual carpooling and propose a strategy to implement it in a MaaS scheme, a quantitative survey was applied to 307 university students in the city Lavras, Brazil. Data were analyzed using descriptive statistical techniques. We assumed that casual carpooling is sustained by solidarity, simplicity, and agility; no costs to passengers; and institutionalized pickup points. Then, we identify principal strategic components to implement such an initiative. We concluded that casual carpooling as a low-tech transport mode could enhance local strategy for implementing an eco-innovative MaaS in places with inefficient public transport offerings.
Does Aiming for Long-Term Non-Decreasing Flow of Timber Secure Carbon Accumulation: A Lithuanian Forestry Case
Authors: Mozgeris Gintautas , Kazanavičiūtė Vaiva , Juknelienė Daiva
Published: March 2021

Lithuanian forestry has long been shaped by the classical normal forest theory, aiming for even long-term flow of timber, and the aspiration to preserve domestic forest resources, leading to very conservative forest management. With radically changing forest management conditions, climate change mitigation efforts suggest increasing timber demands in the future. The main research question asked in this study addresses whether current forest management principles in Lithuania can secure non-decreasing long-term flow of timber and carbon accumulation. The development of national forest resources and forestry was simulated for the next century using the Kupolis decision support system and assuming that current forest management is continued under the condition of three scenarios, differing by climate change mitigation efforts. Potential development trends of key forest attributes were analysed and compared with projected carbon stock changes over time, incorporating major forest carbon pools—biomass, harvested wood products and emission savings due to energy and product substitution. The key finding was that the total carbon balance should remain positive in Lithuania during the next one hundred years; however, it might start to decrease after several decades, with steadily increasing harvesting and a reduced increase of forest productivity. Additionally, incorporating the harvested wood and CO2 emissions savings in carbon balance evaluations is essential.
Integrated Testing of Building Fabric Thermal Performance for Calibration of Energy Models of Three Low-Energy Dwellings in the UK
Authors: Gupta Rajat , Gregg Matt
Published: March 2021

This paper presents the methodology and results of in situ testing of building fabric thermal performance to calibrate as-built energy models of three low-energy dwellings in the UK, so as to examine the gap between as-designed and as-built energy performance. The in situ tests included repeat testing of air permeability (AP) integrated with thermal imaging survey and heat flux measurements of the building fabric elements, along with concurrent monitoring of indoor temperature during the pre-occupancy stage. Despite being designed to high thermal standards, wall and roof U-values were measured to be higher than expected. Thermal imaging surveys revealed air leakage pathways around door/window openings, penetrations and junctions between walls and ceilings, indicating poor detailing and workmanship. AP was found to have increased after the initial test due to post-completion alteration to the building fabric. Though the results did not meet design expectation, they were within the UK Building Regulations. Calibration of energy models with temperature monitoring provided a less extreme energy performance gap than simply replacing the designed values with test results. Insights from this study have reinforced the need for building regulations to require integrated testing of building fabric as part of housing delivery to ensure performance targets are realised.
Sustainability Assessment of Intensified Forestry—Forest Bioenergy versus Forest Biodiversity Targeting Forest Birds
Authors: Mörtberg Ulla , Pang Xi-Lillian , Treinys Rimgaudas , Trubins Renats , Mozgeris Gintautas
Published: March 2021

Intensified forestry can be seen as a solution to climate change mitigation and securing energy supply, increasing the production of forest bioenergy feedstock as a substitution for fossil fuels. However, it may come with detrimental impacts on forest biodiversity, especially related to older forests. The aim of this study was to assess the sustainability of intensified forestry from climate-energy and biodiversity perspectives, targeting forest bird species. For this purpose, we applied the Landscape simulation and Ecological Assessment (LEcA) tool to the study area of Lithuania, having high ambitions for renewables and high forest biodiversity. With LEcA, we simulated forest growth and management for 100 years with two forest management strategies: Business As Usual (BAU) and Intensive forestry (INT), the latter with the purpose to fulfil renewable energy goals. With both strategies, the biomass yields increased well above the yields of the reference year, while the biodiversity indicators related to forest bird habitat to different degrees show the opposite, with lower levels than for the reference year. Furthermore, Strategy INT resulted in small-to-no benefits in the long run concerning potential biomass harvesting, while substantially affecting the biodiversity indicators negatively. The model results have the potential to inform policy and forest management planning concerning several sustainability goals simultaneously.
What Will Remain? Predicting the Representation in Protected Areas of Suitable Habitat for Endangered Tropical Avifauna in Borneo under a Combined Climate- and Land-Use Change Scenario
Authors: Singh Minerva , Badcock-Scruton Jessamine , Collins C. Matilda
Published: March 2021

The responses of threatened tropical avian species to projected climate change and land-use change are important for evaluating the ability of the existing protected areas to provide habitat to these species under future scenarios in biodiversity hotspots. This study uses Maxent, a species distribution model that employs a maximum entropy machine learning approach to map the spatial distributions of habitats suitable for the International Union for Conservation of Nature threatened birds under present and future climate and land-use change in Borneo. We find that the existing protected areas provide very low coverage of the threatened bird species’ suitable habitat areas (95%CI = 9.3–15.4%). Analysis of habitat suitability projections for 18 species of threatened birds suggests that in 2050, under Special Report on Emissions Scenarios A1B and B1, avian species with currently little suitable habitat may gain area but lose in the proportion of this that is protected. Large-ranged species are likely to lose habitat area and this will inflate the proportion of this remaining in protected areas. The present availability of suitable habitat was the most important determinant of future habitat availability under both the scenarios. Threat level, as measured by the International Union for Conservation of Nature and the habitat preferences considered here, Lowland or Lowland–Montane, are poor predictors of the amount of habitat contraction or expansion undergone by the species.
Framework for Sustainable Recovery of Tourism in Protected Areas
Authors: Bhammar Hasita , Li Wendy , Molina Christel Maria Moller , Hickey Valerie , Pendry Jo , Narain Urvashi
Published: March 2021

Tourism in protected areas was a fast-growing segment within the global travel and tourism industry prior to the economic fallout from the COVID-19 pandemic. As a development pathway, tourism generated foreign exchange for countries endowed with natural assets (protected areas, pristine landscapes, forests, oceans, wildlife), contributed to conservation revenues, and provided local development benefits for communities. However, the spread of COVID-19 and its associated travel restrictions severely impacted this sector. In this review, we describe the main challenges preventing the sector from achieving its development potential. We propose a framework to steer tourism in protected areas as a green recovery initiative, so that it may rebound sustainably and continue to support biodiversity conservation and socio-economic development.