bluuebunny/crossref_metadata_2025 huggingface dataset:
Design of Adaptive-Robust Controller for Multi-State Synchronization of Chaotic Systems with Unknown and Time-Varying Delays and Its Application in Secure Communication
Authors: Kekha Javan Ali Akbar , Shoeibi Afshin , Zare Assef , Hosseini Izadi Navid , Jafari Mahboobeh , Alizadehsani Roohallah , Moridian Parisa , Mosavi Amir , Acharya U. Rajendra , Nahavandi Saeid
Published: January 2021

In this paper, the multi-state synchronization of chaotic systems with non-identical, unknown, and time-varying delay in the presence of external perturbations and parametric uncertainties was studied. The presence of unknown delays, unknown bounds of disturbance and uncertainty, as well as changes in system parameters complicate the determination of control function and synchronization. During a synchronization scheme using a robust-adaptive control procedure with the help of the Lyapunov stability theorem, the errors converged to zero, and the updating rules were set to estimate the system parameters and delays. To investigate the performance of the proposed design, simulations have been carried out on two Chen hyper-chaotic systems as the slave and one Chua hyper-chaotic system as the master. Our results showed that the proposed controller outperformed the state-of-the-art techniques in terms of convergence speed of synchronization, parameter estimation, and delay estimation processes. The parameters and time delays were achieved with appropriate approximation. Finally, secure communication was realized with a chaotic masking method, and our results revealed the effectiveness of the proposed method in secure telecommunications.
A Wrist Sensor Sleep Posture Monitoring System: An Automatic Labeling Approach
Authors: Jeng Po-Yuan , Wang Li-Chun , Hu Chaur-Jong , Wu Dean
Published: January 2021

In the hospital, a sleep postures monitoring system is usually adopted to transform sensing signals into sleep behaviors. However, a home-care sleep posture monitoring system needs to be user friendly. In this paper, we present iSleePost—a user-friendly home-care intelligent sleep posture monitoring system. We address the labor-intensive labeling issue of traditional machine learning approaches in the training phase. Our proposed mobile health (mHealth) system leverages the communications and computation capabilities of mobile phones for provisioning a continuous sleep posture monitoring service. Our experiments show that iSleePost can achieve up to 85 percent accuracy in recognizing sleep postures. More importantly, iSleePost demonstrates that an easy-to-wear wrist sensor can accurately quantify sleep postures after our designed training phase. It is our hope that the design concept of iSleePost can shed some lights on quantifying human sleep postures in the future.
On the Effect of Training Convolution Neural Network for Millimeter-Wave Radar-Based Hand Gesture Recognition
Authors: Zhang Kang , Lan Shengchang , Zhang Guiyuan
Published: January 2021

The purpose of this paper was to investigate the effect of a training state-of-the-art convolution neural network (CNN) for millimeter-wave radar-based hand gesture recognition (MR-HGR). Focusing on the small training dataset problem in MR-HGR, this paper first proposed to transfer the knowledge with the CNN models in computer vision to MR-HGR by fine-tuning the models with radar data samples. Meanwhile, for the different data modality in MR-HGR, a parameterized representation of temporal space-velocity (TSV) spectrogram was proposed as an integrated data modality of the time-evolving hand gesture features in the radar echo signals. The TSV spectrograms representing six common gestures in human–computer interaction (HCI) from nine volunteers were used as the data samples in the experiment. The evaluated models included ResNet with 50, 101, and 152 layers, DenseNet with 121, 161 and 169 layers, as well as light-weight MobileNet V2 and ShuffleNet V2, mostly proposed by many latest publications. In the experiment, not only self-testing (ST), but also more persuasive cross-testing (CT), were implemented to evaluate whether the fine-tuned models generalize to the radar data samples. The CT results show that the best fine-tuned models can reach to an average accuracy higher than 93% with a comparable ST average accuracy almost 100%. Moreover, in order to alleviate the problem caused by private gesture habits, an auxiliary test was performed by augmenting four shots of the gestures with the heaviest misclassifications into the training set. This enriching test is similar with the scenario that a tablet reacts to a new user. The results of two different volunteer in the enriching test shows that the average accuracy of the enriched gesture can be improved from 55.59% and 65.58% to 90.66% and 95.95% respectively. Compared with some baseline work in MR-HGR, the investigation by this paper can be beneficial in promoting MR-HGR in future industry applications and consumer electronic design.
Reliable Time Propagation Algorithms for PMF and RBPMF
Authors: Sung Chang-Ky , Lee Sang Jeong
Published: January 2021

This paper addresses the reliable time propagation algorithms for Point Mass Filter (PMF) and Rao–Blackwellized PMF (RBPMF) for the nonlinear estimaton problem. The conventional PMF and RBPMF process the probability diffusion for the time propagation with the direct sampled-values of the process noise. However, if the grid interval is not dense enough, it fails to represent the statistical characteristics of the noise accurately so the performance might deteriorate. To overcome that problem, we propose time propagation convolution algorithms adopting Moment Matched Gaussian Kernel (MMGK) on regular grids through mass linear interpolation. To extend the dimension of the MMGK that can accurately describe the noise moments up to the kernel length, we propose the extended MMGK based on the outer tensor product. The proposed time propagation algorithms using one common kernel through the mass linear interpolation not only improve the performance of the filter but also significantly reduce the computational load. The performance improvement and the computational load reduction of the proposed algorithms are verified through numerical simulations for various nonlinear models.
Comprehensive Bird Preservation at Wind Farms
Authors: Gradolewski Dawid , Dziak Damian , Martynow Milosz , Kaniecki Damian , Szurlej-Kielanska Aleksandra , Jaworski Adam , Kulesza Wlodek J.
Published: January 2021

Wind as a clean and renewable energy source has been used by humans for centuries. However, in recent years with the increase in the number and size of wind turbines, their impact on avifauna has become worrisome. Researchers estimated that in the U.S. up to 500,000 birds die annually due to collisions with wind turbines. This article proposes a system for mitigating bird mortality around wind farms. The solution is based on a stereo-vision system embedded in distributed computing and IoT paradigms. After a bird’s detection in a defined zone, the decision-making system activates a collision avoidance routine composed of light and sound deterrents and the turbine stopping procedure. The development process applies a User-Driven Design approach along with the process of component selection and heuristic adjustment. This proposal includes a bird detection method and localization procedure. The bird identification is carried out using artificial intelligence algorithms. Validation tests with a fixed-wing drone and verifying observations by ornithologists proved the system’s desired reliability of detecting a bird with wingspan over 1.5 m from at least 300 m. Moreover, the suitability of the system to classify the size of the detected bird into one of three wingspan categories, small, medium and large, was confirmed.
Gait Analysis under Spatial Navigation Task in Elderly People—A Pilot Study
Authors: Pawlaczyk Natalia , Szmytke Magdalena , Meina Michał , Lewandowska Monika , Stępniak Justyna , Bałaj Bibianna , Dreszer Joanna
Published: January 2021

A decline in the Spatial Navigation (SN) abilities has been observed in the course of healthy aging. Walking is an inseparable part of the navigation process; however, research tasks overlook this aspect in studies involving seniors. The present study was designed to overcome this limitation by recording gait parameters during natural environment navigation and to determine gait indicators that most accurately assign the participants to the proper age category. Thirteen elderly (mean age = 69.1 ± 5.4 year) and sixteen young women (mean age = 21.5 ± 2.2 year) equipped with gait sensors were asked to learn a path while walking in a real building (Learning Phase), reproduce the path (Memory Phase) and reach targets after a 30 min delay (Delayed Phase). The Receiver Operating Characteristics (ROC) analysis showed that our self-developed Gait Style Change indicator, that is, the difference in the probability of feet landing between particular SN task phases, classified the participants into either the elderly or the young group with the highest accuracy (0.91). The second most important indicator, the Task-Related (step counts in each SN task phase), achieved the accuracy discrimination of 0.83. The gait indicators, comprising single gait parameters measured while navigating, might be considered as accurately differentiating older from younger people.
Real-Time Instance Segmentation of Traffic Videos for Embedded Devices
Authors: Panero Martinez Ruben , Schiopu Ionut , Cornelis Bruno , Munteanu Adrian
Published: January 2021

The paper proposes a novel instance segmentation method for traffic videos devised for deployment on real-time embedded devices. A novel neural network architecture is proposed using a multi-resolution feature extraction backbone and improved network designs for the object detection and instance segmentation branches. A novel post-processing method is introduced to ensure a reduced rate of false detection by evaluating the quality of the output masks. An improved network training procedure is proposed based on a novel label assignment algorithm. An ablation study on speed-vs.-performance trade-off further modifies the two branches and replaces the conventional ResNet-based performance-oriented backbone with a lightweight speed-oriented design. The proposed architectural variations achieve real-time performance when deployed on embedded devices. The experimental results demonstrate that the proposed instance segmentation method for traffic videos outperforms the you only look at coefficients algorithm, the state-of-the-art real-time instance segmentation method. The proposed architecture achieves qualitative results with 31.57 average precision on the COCO dataset, while its speed-oriented variations achieve speeds of up to 66.25 frames per second on the Jetson AGX Xavier module.
Two-Stage Fast DOA Estimation Based on Directional Antennas in Conformal Uniform Circular Array
Authors: Xie Yao , Huang Mo , Zhang Yuanyuan , Duan Tao , Wang Changyuan
Published: January 2021

In conformal array radar, due to the directivity of antennas, the responses of the echo signals between different antennas are distinct, and some antennas cannot even receive the target echo signal. These phenomena significantly affect the accuracy of direction-of-arrival (DOA) estimation. To implement accurate DOA estimation in a conformal uniform circular array (UCA) composed of directional antennas, the two-stage fast DOA estimation algorithm is proposed. In the pre-processing stage, multi-target decoupling and target detection are mainly used to obtain the targets’ range bin indexes set; in the rough-precise DOA estimation stage, the amplitude and phase information of each antenna are used for rough DOA estimation and precise DOA estimation, respectively. Based on simulation and actual anechoic chamber radar experiments, and through quantitative analyses of the accuracy, validity and elapsed time of the two-stage fast DOA estimation algorithm compared with the directional antenna MUSIC (DA-MUSIC), sub-array MUSIC (S-MUSIC) and Capon-like algorithms, results indicate that the two-stage fast DOA estimation algorithm can rapidly and accurately estimate DOAs in a multi-target scenario without the range-angle pair-matching procedure. Lower computational complexity and superior estimation accuracy provide the two-stage fast DOA estimation algorithm a broader application prospect in the practical engineering field.
Hearing Loss Is Associated with Increased Variability in Double Support Period in the Elderly
Authors: Szeto Betsy , Zanotto Damiano , Lopez Erin M. , Stafford John A. , Nemer John S. , Chambers Adam R. , Agrawal Sunil K. , Lalwani Anil K.
Published: January 2021

Hearing loss is a disabling condition that increases with age and has been linked to difficulties in walking and increased risk of falls. The purpose of this study is to investigate changes in gait parameters associated with hearing loss in a group of older adults aged 60 or greater. Custom-engineered footwear was used to collect spatiotemporal gait data in an outpatient clinical setting. Multivariable linear regression was used to determine the relationship between spatiotemporal gait parameters and high and low frequency hearing thresholds of the poorer hearing ear, the left ear, and the right ear, respectively, adjusting for age, sex, race/ethnicity, and the Dizziness Handicap Inventory–Screening version score. Worsening high and low frequency hearing thresholds were associated with increased variability in double support period. Effects persisted after adjusting for the effects of age and perceived vestibular disability and were greater for increases in hearing thresholds for the right ear compared to the left ear. These findings illustrate the importance of auditory feedback for balance and coordination and may suggest a right ear advantage for the influence of auditory feedback on gait.
Automated Counting Grains on the Rice Panicle Based on Deep Learning Method
Authors: Deng Ruoling , Tao Ming , Huang Xunan , Bangura Kemoh , Jiang Qian , Jiang Yu , Qi Long
Published: January 2021

Grain number per rice panicle, which directly determines grain yield, is an important agronomic trait for rice breeding and yield-related research. However, manually counting grains of rice per panicle is time-consuming, laborious, and error-prone. In this research, a grain detection model was proposed to automatically recognize and count grains on primary branches of a rice panicle. The model used image analysis based on deep learning convolutional neural network (CNN), by integrating the feature pyramid network (FPN) into the faster R-CNN network. The performance of the grain detection model was compared to that of the original faster R-CNN model and the SSD model, and it was found that the grain detection model was more reliable and accurate. The accuracy of the grain detection model was not affected by the lighting condition in which images of rice primary branches were taken. The model worked well for all rice branches with various numbers of grains. Through applying the grain detection model to images of fresh and dry branches, it was found that the model performance was not affected by the grain moisture conditions. The overall accuracy of the grain detection model was 99.4%. Results demonstrated that the model was accurate, reliable, and suitable for detecting grains of rice panicles with various conditions.
Characteristic Analysis and Structural Design of Hollow-Core Photonic Crystal Fibers with Band Gap Cladding Structures
Authors: Wan Bowei , Zhu Lianqing , Ma Xin , Li Tianshu , Zhang Jian
Published: January 2021

Due to their flexible structure and excellent optical characteristics hollow-core photonic crystal fibers (HC-PCFs) are used in many fields, such as active optical devices, communications, and optical fiber sensing. In this paper, to analyze the characteristics of HC-PCFs, we carried out finite element analysis and analyzed the design for the band gap cladding structure of HC-PCFs. First, the characteristics of HC19-1550 and HC-1550-02 in the C-band were simulated. Subsequently, the structural optimization of the seven-cell HC-1550-02 and variations in characteristics of the optimized HC-1550-02 in the wavelength range 1250–1850 nm were investigated. The simulation results revealed that the optimal number of cladding layers is eight, the optimal core radius is 1.8 times the spacing of adjacent air holes, and the optimal-relative thickness of the core quartz-ring is 2.0. In addition, the low confinement loss bandwidth of the optimized structure is 225 nm. Under the transmission bandwidth of the optimized structure, the core optical power is above 98%, the confinement loss is below 9.0 × 10−3 dB/m, the variation range of the effective mode field area does not exceed 10 μm2, and the relative sensitivity is above 0.9570. The designed sensor exhibits an ultra-high relative sensitivity and almost zero confinement loss, making it highly suitable for high-sensitivity gas or liquid sensing.
Urban Green Infrastructure Monitoring Using Remote Sensing from Integrated Visible and Thermal Infrared Cameras Mounted on a Moving Vehicle
Authors: Fuentes Sigfredo , Tongson Eden , Gonzalez Viejo Claudia
Published: January 2021

Climate change forecasts higher temperatures in urban environments worsening the urban heat island effect (UHI). Green infrastructure (GI) in cities could reduce the UHI by regulating and reducing ambient temperatures. Forest cities (i.e., Melbourne, Australia) aimed for large-scale planting of trees to adapt to climate change in the next decade. Therefore, monitoring cities’ green infrastructure requires close assessment of growth and water status at the tree-by-tree resolution for its proper maintenance and needs to be automated and efficient. This project proposed a novel monitoring system using an integrated visible and infrared thermal camera mounted on top of moving vehicles. Automated computer vision algorithms were used to analyze data gathered at an Elm trees avenue in the city of Melbourne, Australia (n = 172 trees) to obtain tree growth in the form of effective leaf area index (LAIe) and tree water stress index (TWSI), among other parameters. Results showed the tree-by-tree variation of trees monitored (5.04 km) between 2016–2017. The growth and water stress parameters obtained were mapped using customized codes and corresponded with weather trends and urban management. The proposed urban tree monitoring system could be a useful tool for city planning and GI monitoring, which can graphically show the diurnal, spatial, and temporal patterns of change of LAIe and TWSI to monitor the effects of climate change on the GI of cities.
How to Achieve Compliance with GDPR Article 17 in a Hybrid Cloud Environment
Authors: Kelly Miriam , Furey Eoghan , Curran Kevin
Published: January 2021

On 25 May 2018, the General Data Protection Regulation (GDPR) Article 17, the Right to Erasure (“Right to be Forgotten”) came into force, making it vital for organisations to identify, locate and delete all Personally Identifiable Information (PII) where a valid request is received from a data subject to erase their PII and the contractual period has expired. This must be done without undue delay and the organisation must be able to demonstrate that reasonable measures were taken. Failure to comply may incur significant fines, not to mention impact to reputation. Many organisations do not understand their data, and the complexity of a hybrid cloud infrastructure means they do not have the resources to undertake this task. The variety of available tools are quite often unsuitable as they involve restructuring so there is one centralised data repository. This research aims to demonstrate that compliance with GDPR’s Article 17 Right to Erasure (“Right to be Forgotten”) is achievable in a hybrid cloud environment by following a list of recommendations. However, full retrieval, all of the time will not be possible, but we show that small organisations running an ad-hoc hybrid cloud environment can demonstrate that reasonable measures were taken to be Right to Erasure (“Right to be Forgotten”) compliant.
Addressing Thermal Comfort in Regional Energy Poverty Assessment with Nussbaumer’s MEPI
Authors: Robles-Bonilla Tiare , Cedano Karla G.
Published: January 2021

Research on energy poverty (EP) started in the United Kingdom and other Western European countries in response to the Oil Crisis in 1973. In the last few years, the European community has made important breakthroughs on the topic, by establishing clear terminology as well as funding different multidisciplinary and intersectoral task groups that have EP understanding and alleviation as their goal. Several different methodologies have been developed to measure EP. For instance, the multidimensional energy poverty index (MEPI) by Nussbaumer et al. (2012) has been successfully used in Africa and in seven Latin American countries. Mexico does not have an official measure, indicator, or index on EP. However, a very important energy service has been overlooked: thermal comfort. In the present work, MEPI was understood as an energy services deprivation calculation, and thermal comfort was included. Understanding the regional nature of thermal comfort, we searched for weather-based regionalizations that could address a whole country diversity. We applied two regionalizations, one strongly related to political divisions (called climatic), and a another used for household design and construction standards (bioclimatic). The bioclimatic regionalization had a better fit when assessing energy services deprivation, since it addresses exclusively geographical and weather conditions, instead of the artificial political divisions. Having better ways to assess the level of EP in the local context is a key factor to develop effective public policies that might alleviate EP in a sustainable way.
Global Imbalances: The Role of Institutions, Financial Development and FDI in the Context of Financial Crises
Authors: Silva Carlos A. , Ordeñana Xavier , Vera-Gilces Paul , Jiménez Alfredo
Published: January 2021

This paper examines the role of the quality of institutions, financial development and FDI on current account imbalances, which narrowed during the Global Financial Crisis. In doing so, we utilize (i) a sample of 49 advanced and emerging economies during 1984–2014; (ii) a novel three-clustered indices of institutional quality and (iii) two measures of financial development, the share of FDI and a measure of financial crisis in addition to standard determinants of the current account. We find that the better the quality of institutions and the greater the financial development, the larger are current account deficits; meanwhile, FDI contributes to boost current account balances. Moreover, financial crisis episodes tend to improve current account balances, particularly for countries that are highly open to trade and to receive FDI, as in the case of advanced economies and East Asian countries.
Mobility Behaviour in View of the Impact of the COVID-19 Pandemic—Public Transport Users in Gdansk Case Study
Authors: Przybylowski Adam , Stelmak Sandra , Suchanek Michal
Published: January 2021

The COVID-19 pandemic, like an earthquake, shocked our civilization and is still having a devastating effect on our lives. Guaranteeing an appropriate level of safety in the conditions of an epidemic is a highly problematic issue due to the subjectivism of social individuals, their diverse attitudes, and past life experiences. Taking into account the World Health Organisation (WHO) guidelines regarding the pandemic, authorities all around the world have reacted by issuing the necessary sets of advice and legal acts. This resulted in immediate and severe implications on mobility styles. The purpose of this paper was to investigate the impact of COVID-19 on mobility behaviours with special regard to public transport users, in terms of their willingness to travel and their safety criteria perceptions. The city of Gdańsk, in Poland, located on the Baltic Sea, has been taken as an example. The hypothesis was as follows: the epidemic phenomenon may substantially affect mobility behaviours in terms of subjective levels of safety and the mental comfort of public transport users, resulting in avoiding this form of transport. In accordance with the survey results, carried out among the users, 90% of respondents resigned or limited their usage. Almost 75% of them plan to return to using public transport when the epidemic situation has stabilized. The others, unfortunately, have completely lost hope that public transport will ever be safe. These results indicate decisively that the future of public transport in cities, and the willingness of passengers to use it once the epidemic is over, depends majorly on the perceived comfort and safety during the epidemic. This means that transport policies should be focused on enhancing these perceptions and making sure that the image of public transport is not in further decline; otherwise, it could mean an almost impossible effort to encourage passengers to return to using sustainable modes of transport in the future.
Sustainable Process and Product Innovation in the Eyewear Sector: The Role of Industry 4.0 Enabling Technologies
Authors: Murmura Federica , Bravi Laura , Santos Gilberto
Published: January 2021

This paper aims to provide the reader with an organic view of the eyewear sector considering both market and quality aspects and evaluating the role of Industry 4.0 in process and product innovation for managing consumer health, analyzing a case study of a leading multinational company in the eyewear and ophthalmic lenses sector. The research has been developed with a qualitative approach. The study is a conceptual development and it uses an exploratory interview to create a single case study. The case study was developed with the realization by the researcher of a semi-structured interview. The selected interlocutor was the Innovation Manager of Alpha Optics. It has been decided to focus the attention on this figure, as it was responsible for the realization and introduction into the company of Industry 4.0 enabling technologies for developing health innovations. From this case study it was possible to observe how the connection with the trends that influence the demand for eyeglasses is a driving factor for product innovation. Products increasingly adapted to the needs of young people and the use of digital devices seem to be the ones on which the greatest number of innovations are concentrated.
A Methodology for Assessing the Implementation Potential for Retrofitted and Multifunctional Urban Green Infrastructure in Public Areas of the Global South
Authors: Fluhrer Tanja , Chapa Fernando , Hack Jochen
Published: January 2021

Urban green infrastructure (UGI) provides multiple functions that combine ecological and social benefits. UGI is being increasingly promoted and implemented in the Global North. In other parts of the world, such as in the Global South, infrastructures for UGI implementation and promotion are sparse. The state of infrastructure development and informal settlements in the Global South present different constraints and demands that should be explicitly addressed. This study presents an approach to addressing the specific conditions and physical limitations of UGI development in urban areas of the Global South. A four-step methodology was developed to assess the implementation potential for retrofitted and multifunctional urban green infrastructure in public areas. This methodology consists of (1) an initial site analysis, (2) defining design criteria and general strategies, (3) exploring the different dimensions of multifunctionality as the basis for deriving spatial typologies, and (4) assessing spatial suitability for potential placements for UGI elements. The methodology was applied to a study area in the metropolitan region of San José, Costa Rica. The results indicate the potential to improve the hydrological (up to 34% of surface runoff reduction), ecological (an increase of green space by 2.2%, creation of 1500 m length of roadside greenery and two new habitat types), and social conditions (2200 m of road type upgrading) of the site through UGIs. This assessment of different multifunctionality dimensions can serve as a guide for future UGI promotion and implementation in urban areas of the Global South.
Thermal Performance Assessment of Walls Made of Three Types of Sustainable Concrete Blocks by Means of FEM and Validated through an Extensive Measurement Campaign
Authors: Blanco Jesús M. , Frómeta Yokasta García , Madrid Maggi , Cuadrado Jesús
Published: January 2021

The thermal behavior of three different walls, made with and without by-products, is assessed by means of the Finite Element Method, aiming to evaluate its performance in terms of the sustainable construction of the blocks. Results were compared to those obtained from an experimental campaign, aiming at validation of the model. The by-products used for the blocks were “lime sludge” and “sawdust”, whose performance was compared against the traditional blocks made of concrete as a reference, aiming to demonstrate its sustainability, showing decreases of the thermal transmittance up to 10.5%. Additionally, following the same methodology, the thermal behavior of these above-mentioned blocks but now with added internal insulation made of “recycled cellulose” was assessed, showing higher decreases up to 25.5%, increasing sustainability by addressing an additional reduction in waste, so the right combination of using by-products and the insulating filler in their cavities has been revealed as a promising way of optimizing the walls, offering a relevant improvement in energy savings. Finally, when comparing the U-values of the blocks made of concrete without insulation versus those made of by-products, with insulation, improvements up to 33.3% were reached. The adaptation of the procedure through a moisture correction factor was also incorporated.
Co-Creating New Directions for Service Robots in Hospitality and Tourism
Authors: Fusté-Forné Francesc , Jamal Tazim
Published: January 2021

Research on the relationship between automation services and tourism has been rapidly growing in recent years and has led to a new service landscape where the role of robots is gaining both practical and research attention. This paper builds on previous reviews and undertakes a comprehensive analysis of the research literature to discuss opportunities and challenges presented by the use of service robots in hospitality and tourism. Management and ethical issues are identified and it is noted that practical and ethical issues (roboethics) continue to lack attention. Going forward, new directions are urgently needed to inform future research and practice. Legal and ethical issues must be proactively addressed, and new research paradigms developed to explore the posthumanist and transhumanist transitions that await. In addition, closer attention to the potential of “co-creation” for addressing innovations in enhanced service experiences in hospitality and tourism is merited. Among others, responsibility, inclusiveness and collaborative human-robot design and implementation emerge as important principles to guide future research and practice in this area.
Effect of Selected Cooking Ingredients for Nixtamalization on the Reduction of Fusarium Mycotoxins in Maize and Sorghum
Authors: Odukoya Julianah Olayemi , De Saeger Sarah , De Boevre Marthe , Adegoke Gabriel Olaniran , Audenaert Kris , Croubels Siska , Antonissen Gunther , Vermeulen Karel , Gbashi Sefater , Njobeh Patrick Berka
Published: January 2021

Although previous studies have reported the use of nixtamalization for mycotoxins reduction in maize, the efficacy of calcium hydroxide and other nixtamalization cooking ingredients for mycotoxin reduction/decontamination in sorghum and other cereals still need to be determined. The current study investigated the effect of five nixtamalization cooking ingredients (wood ashes, calcium hydroxide, sodium hydroxide, potassium hydroxide, and calcium chloride) on the reduction of Fusarium mycotoxins in artificially contaminated maize and sorghum using liquid chromatography-tandem mass spectrometry. All tested cooking ingredients effectively reduced levels of mycotoxins in the contaminated samples with reduction initiated immediately after the washing step. Except for the calcium chloride nixtamal, levels of fumonisin B1, B2, and B3 in the processed sorghum nixtamal samples were below the limit of detection. Meanwhile, the lowest pH values were obtained from the maize (4.84; 4.99), as well as sorghum (4.83; 4.81) nejayote and nixtamal samples obtained via calcium chloride treatment. Overall, the results revealed that the tested cooking ingredients were effective in reducing the target mycotoxins. In addition, it pointed out the potential of calcium chloride, though with reduced effectiveness, as a possible greener alternative cooking ingredient (ecological nixtamalization) when there are environmental concerns caused by alkaline nejayote.
Streamflow Forecasting via Two Types of Predictive Structure-Based Gated Recurrent Unit Models
Authors: Zhao Xuehua , Lv Hanfang , Wei Yizhao , Lv Shujin , Zhu Xueping
Published: January 2021

Data-intelligent methods designed for forecasting the streamflow of the Fenhe River are crucial for enhancing water resource management. Herein, the gated recurrent unit (GRU) is coupled with the optimization algorithm improved grey wolf optimizer (IGWO) to design a hybrid model (IGWO-GRU) to carry out streamflow forecasting. Two types of predictive structure-based models (sequential IGWO-GRU and monthly IGWO-GRU) are compared with other models, such as the single least-squares support vector machine (LSSVM) and single extreme learning machine (ELM) models. These models incorporate the historical streamflow series as inputs of the model to forecast the future streamflow with data from January 1956 to December 2016 at the Shangjingyou station and from January 1958 to December 2016 at the Fenhe reservoir station. The IGWO-GRU model exhibited a strong ability for mapping in streamflow series when the parameters were carefully tuned. The monthly predictive structure can effectively extract the instinctive hydrological information that is more easily learned by the predictive model than the traditional sequential predictive structure. The monthly IGWO-GRU model was found to be a better forecasting tool, with an average qualification rate of 91.66% in two stations. It also showed good performance in absolute error and peak flow forecasting.
Are Biocrusts and Xerophytic Vegetation a Viable Green Roof Typology in a Mediterranean Climate? A Comparison between Differently Vegetated Green Roofs in Water Runoff and Water Quality
Authors: Rocha Bernardo , Paço Teresa , Luz Ana , Palha Paulo , Milliken Sarah , Kotzen Benzion , Branquinho Cristina , Pinho Pedro , de Carvalho Ricardo
Published: January 2021

Green roofs can be an innovative and effective way of mitigating the environmental impact of urbanization by providing several important ecosystem services. However, it is known that the performance of green roofs varies depending on the type of vegetation and, in drier climates, without resorting to irrigation, these are limited to xerophytic plant species and biocrusts. The aim of this research was therefore to compare differently vegetated green roofs planted with this type of vegetation. A particular focus was their ability to hold water during intense stormwater events and also the quality of the harvested rainwater. Six test beds with different vegetation compositions were used on the roof of a building in Lisbon. Regarding stormwater retention, the results varied depending on the composition of the vegetation and the season. As for water quality, almost all the parameters tested were higher than the Drinking Water Directive from the European Union (EU) and Word Health Organization (WHO) guidelines for drinking-water quality standards for potable water. Based on our results, biocrusts and xerophytic vegetation are a viable green roof typology for slowing runoff during stormwater events.
Analysis of the Incidence and Clinical Features of Colorectal Nonadenocarcinoma in Korea: A National Cancer Registry-Based Study
Authors: Nam Soomin , Kim Dongwook , Jung Kyuwon , Choi Yoon Jung , Kang Jung Gu
Published: January 2021

Purpose: Although most colorectal malignancies are adenocarcinomas from mucosa, various types of malignant and benign tumors can develop. Due to extremely low incidence, little research has been conducted. The purpose was to assess incidence and compare it according to demographic factors.Methods: Data from the Korea National Cancer Registry from 2007 to 2016 were used. The crude incidence, age-standard incidence rate (ASR) of colorectal nonadenocarcinomas were calculated.Results: Over 11 years, there were 267,142 patients with colorectal malignancies. The patients of 14,495 (5.43%) were diagnosed with nonadenocarcinoma. The ASR was 2.52 per 100,000 in men and 1.56 in women. Lesions were classified according to histologic categories; neuroendocrine tumor (NET) was the most common malignancy (10,919 [75.33%]). Nonadenocarcinoma was the most common in 40s and 50s (40 to 49 years, 3,530 [24.35%]; 50 to 59 years, 3,991 [27.53%]). Lymphoma was high (54.46%) in patients in teenagers. Proportion of NET decreased with age and that of carcinoma increased with age. Carcinoma, sarcoma, and lymphoma were more common among men and melanoma was more common among women. The most common site was the rectum (11,066 [76.34%]). Lymphoma occurred more frequently in proximal colon. Melanoma, gastrointestinal stromal tumor, and NET occurred mostly in rectum. A total of 10,155 patients (70.06%) were classified as having localized disease.Conclusion: This study is meaningful as it is the first study to examine incidence of colorectal nonadenocarcinoma. Differences in incidence of different lesions based on demographic factors were identified. This study will play a role in cancer prevention and diagnosis projects.
Da interação à aprendizagem: uma reflexão neurobiológica sobre aprender
Authors: Moreira de Souza Adriano Junio
Published: January 2021

Atualmente, não há dúvida de que o cérebro está diretamente relacionado a funções superiores e que os neurônios são sua unidade morfofisiológica básica. O cérebro adulto possui cerca de 80 bilhões de neurônios, e cada neurônio se comunica com milhares de outros através de suas extensões axonais e dendríticas. Por ser dinâmico, a capacidade mais impressionante do cérebro e aprender com a experiência. Vários fenômenos, como processos de sinalização celular e formação de memória, afetam diretamente o aprendizado. Como será discutido neste artigo, é necessário considerar as tendências constitucionais do cérebro em relação ao ensino, como concluiremos, o cérebro aprende muito mais quando estimulado adequadamente, em um ambiente amigável e livre de estresse excessivo.
Methods and tools of parallel event processing for creating new generation of security monitoring systems
Authors:   St. Petersburg institute of informatics and automation of the Russian Academy of Sciences, Kotenko I.V. , Komashinskiy N.A. , Saenko I.B. , Bashmakov A.V. ,   Admiral Makarov State University of Maritime and Inland Shipping
Published: January 2021

Parallel event processing methods and tools needed for creating new generation systems of security monitoring are analyzed. Possibilities of data processing for intrusion detection based on functional approach are considered. Based on the results of the analysis, the specifi cation of the main stages of the parallel event processing and the scheme of their implementation as part of new generation intelligent systems of security monitoring are presented.
Special software and mathematical support for controlling the reconfiguration of on-board systems of small-sized spaces
Authors:   Research Institute of Space Systems named after A.A. Maksimov – the branch of Khrunichev State Research and Production Space Center, Zaichenko Yu.V. , Kulakov А.Yu. ,   Saint Petersburg Federal Research Center of the Russian Academy of Sciences, Sokolov B.V. ,   Saint Petersburg Federal Research Center of the Russian Academy of Sciences, Cherniy А.N. ,   Research Institute of Space Systems named after A.A. Maksimov – the branch of Khrunichev State Research and Production Space Center
Published: January 2021

The article presents the results of studies devoted to the development of technologies, models, methods and algorithms for confi guration and reconfi guration control of on-board systems (OBS) of small-size spacecraft (SSS) in the interests of increasing their survivability and their experimental development using the created prototypes of software systems for ground and on-board functional modules.
Investigation of the structural and functional reliability of small spacecraft in solving orientation problems
Authors:   Federal state budgetary military educational institution of higher education «Military space Academy named after A.F.Mozhaysky» of the Ministry of defense of the Russian Federation, Pavlov A.N. , Kylakov A.Yu. ,   Saint Petersburg Federal Research Center of the Russian Academy of Sciences, Vorotyagin V.N. ,   Federal state budgetary military educational institution of higher education «Military space Academy named after A.F.Mozhaysky» of the Ministry of defense of the Russian Federation, Umarov A.B. ,   Saint Petersburg Federal Research Center of the Russian Academy of Sciences
Published: January 2021

At the stages of design, creation and application of small spacecraft to develop solutions aimed at increasing their stability, it is necessary to assess the indicators of structural and functional reliability of elements of onboard systems, taking into account the involvement of various modes of operation. This article presents the results of a study of the influence of confi gurations of sensors of the attitude control system on the structural and functional reliability of a small spacecraft when solving task of determining the attitude in various modes of operation.
Effect of the spacecraft roll on the effectiveness of solving the problem of observing marine objects
Authors:   St. Petersburg branch of the applied problems Section at the Presidium of the Russian Academy of Sciences, Kalinov M. I. , Rodionov V. A. , Cherkashin V. G. ,   research Institute of shipbuilding and armament of the Navy VUNTS Navy «Naval Academy»
Published: January 2021

Purpose: Currently, the use of space observation systems (ESS) with spacecraft (SC), the angles of destabilization of which have signifi cant deviations from the standard values, is of particular relevance. The article offers an approach to evaluating the possible results of the use of the ESR in these conditions. Materials and methods. The article offers an original approach based on the use of methods and models of the theory of the effectiveness of space systems to assess the impact of the SPACECRAFT roll on the effectiveness of solving the problem of observing marine objects. Results. In order to solve the tasks set, the authors of the article improved the scenario-time method for evaluating the effectiveness of the use of SSC for conditions of changing the angle of roll of the SPACECRAFT. The article shows how, by implementing this improved method in simulation models of the functioning of the OSN and drawing possible scenarios for the actions of the monitoring object (МО), it is possible to evaluate the possible results of the system and plan its application in the interests of information consumers. Conclusion: The proposed improved scenario-time method for evaluating the effectiveness of the use of an ESR for conditions of changing the angle of roll of the SPACECRAFT has great prospects, since it is based on fundamental and applied results obtained so far in the theory and practice of using space systems for various purposes.
Service for determining forest taxational indicators based on automated processing of multispectral remote sensing data
Authors:   A.F. Mozhaysky’s Military-Space Academy, Grigoreva О.V. , Markov А.V. , Saidov А.G.
Published: January 2021

The article considers a service for providing consumers with various levels of information about forest taxing indicators based on the processing of multispectral data recorded by modern domestic remote sensing spacecraft in the optical spectrum range.
Principles of information systems design for creation of thematic services based on integrated use of ground-aerospace data and modeling results
Authors:   SPC RAS, Zelentsov V.A. , Semenov A.S.
Published: January 2021

The paper describes an architecture and examples of information technologies and systems implementation for automating interdisciplinary projects accomplishment and creating thematic services that require utilizing Earth remote sensing data. It is proposed using approaches based on a service-oriented architecture, web services technologies, and technologies based on the Business Process Execution Language to organize the interaction of system components. Testing results show that the proposed approaches ensure achieving maximum automation of systems running, high reliability of the results, and user friendliness.
Managing information processes in systems for modeling natural objects
Authors:   SPC RAS, Potryasaev S.A. , Pimanov I.Yu.
Published: January 2021

The paper proposes a methodological approach and software for managing information processes in systems for modeling natural objects on the example of a system for operational forecasting of fl oods. The proposed approach is based on application of cyber-physical systems, the industrial Internet and fog computing concepts. The results of testing the technologies for managing information processes demonstrate increasing both reliability of modeling and effi ciency of using the fl ood forecasting system computing resources.
Technologies and principles of unstructured distributed data processing in the context of modern media content providing
Authors:   St. Petersburg institute for Informatics and automation of the Russian Academy of Sciences, Kuleshov S.V. , Zaytseva A.A. , Levashkin S.P. ,   Povolzhskiy State University of Telecommunications and Informatics
Published: January 2021

Purpose The COVID-19 pandemic is creating serious challenges for modern society that leads to develop new information models and methods of digital monitoring not only of the spread of the virus, but also of the socio-economic environment. Materials and methods: As sources for clarifying the parameters of such models, it is advisable to choose not a limited set of predefi ned Internet sources, but unstructured media data on an unlimited set of resources, which leads to the need to build a system for complex monitoring of social phenomena. Such system can supplement and correct mathematical and information models for the spread of viruses, aimed at minimizing the damage caused by any pandemic. Results: It is proposed to create a software system that includes a Data Retrieving subsystem (for collecting and preprocessing media data) combined with a headless browser. This allows to build a system for monitoring of social phenomena, complementing mathematical and information models of the spread of viruses, aimed at minimizing the damage they cause. The feature of developed system is the using of a natural language processing framework based on the associative-ontological approach, and software implementation of the adaptive-behavioral SEIR model, as well as a subsystem for interpreting the collected data, generating metadata for identifying and correcting the model. Conclusions: The proposed system allows to make more balanced management decisions based on the analysis of the current situation in the infosphere. An additional advantage of the system is the ability to identify poorly predictable reactions of society to certain events expressed in media content.