bluuebunny/crossref_metadata_2025 huggingface dataset:
Ensemble Mode and Singular Value Based Road Texture-Skid Study
Authors: Fang Tuo , Guo Runhua , Si Youqiang
Published: August 2021

Traffic accidents occur frequently every year. Skid-resistance performance is an important indicator in evaluating road safety. In this paper, the road surface texture information is obtained by a line laser scanner. The original two-dimensional (2D) signal is decomposed into eight intrinsic mode functions by complementary ensemble empirical mode decomposition (CEEMD). Eight intrinsic mode functions compose an 800 × 8 data matrix. The matrix is decomposed by singular value decomposition (SVD), and singular value vectors are obtained. The singular values are summed and linearly fitted to the friction value measured by the British pendulum friction meter. The study finds that the singular value sum of one to five has a good linear correlation with the friction value with the goodness of fit greater than 0.8. At the same time, contour arithmetic mean deviation Ra is applied for verification. The results show that the singular value sum has a strong correlation with Ra. When the number of Intrinsic Mode Function (IMF) decomposition is greater than eight, there is a good correlation between the number of IMF and the friction value from IMF2 to IMF6. When the number of IMF decomposition is less than eight, the singular value sum numbers with R2 more than 0.8 gradually decrease. It is suggested that the road surface friction performance can be estimated by solving the singular value of the 2D signal. It provides new technical support for the detection and evaluation of anti-skid performance.
Corrosion Protection of Injection Molded Porous 440C Stainless Steel by Electroplated Zinc Coating
Authors: Kultamaa Matti , Mönkkönen Kari , Saarinen Jarkko J. , Suvanto Mika
Published: August 2021

Zinc electroplating was used to enhance corrosion resistance of porous metal injection molded 440C stainless steel. Controlled porosity was achieved by the powder space holder technique and by using sodium chloride as a space holder material. The internal pore structure of porous 440C was deposited by zinc using electroplating with three different electrolytes of zinc acetate, zinc sulfate, and zinc chloride. Our results show that all zinc depositions on porous 440C samples significantly improved corrosion resistance. The lowest corrosion was observed with zinc acetate at 30 wt.% porosity. The developed zinc coated porous 440C samples have potential in applications in corrosive environments.
The Effect of Specimen Size and Test Procedure on the Creep Behavior of ME21 Magnesium Alloy
Authors: Camin Bettina , Gille Maximilian
Published: August 2021

Lightweight constructions and materials offer the opportunity to reduce CO2 emissions in the transport sector. As components in vehicles are often exposed to higher temperatures above 40% of the melting temperature, there is a risk of creep. The creep behavior usually is investigated based on standard procedures. However, lightweight constructions frequently have dimensions not adequately represented by standardized specimen geometries. Therefore, comparative creep experiments on non-standardized miniature and standardized specimens are performed. Due to a modified test procedure specified by a miniature creep device, only the very first primary creep stage shows a minor influence, but subsequently, no effect on the creep process is detected. The creep behavior of hot extruded and heat treated ME21 magnesium alloy is investigated. It is observed that the creep parameters determined by the miniature and standard creep tests are different. As the deviations are systematic, qualitatively, evidence of the creep behavior is achieved. The creep parameters obtained, and particularly the creep strain and the strain rate, show a higher creep resistance of the miniature specimen. An initial higher number of twinned grains and possible multiaxiality in the gauge volume of the miniature specimen can be responsible.
Broadband Active Control of Transverse Scattering from All-Dielectric Nanoparticle
Authors: Yu Huiwen , Zhu Hongjia , Li Jinyang , Cao Zhaolong , Chen Huanjun
Published: August 2021

Steering electromagnetic scattering by subwavelength objects is usually accompanied by the excitation of electric and magnetic modes. The Kerker effect, which relies on the precise overlapping between electric and magnetic multipoles, is a potential approach to address this challenge. However, fundamental limitations on the reconfigurability and tunability challenge their future implementation in practical applications. Here, we demonstrate a design approach by applying coherent control to a silicon nanodisk. By utilizing an experimentally feasible two-wave excitation, this coherent light-by-light control enables a highly reconfigurable, broadband, and tunable transverse scattering, extending the feasibility of unidirectional scattering in various practical scenarios, including on-chip integrations and optical communications.
Investigation of Mid-Infrared Broadband Second-Harmonic Generation in Non-Oxide Nonlinear Optic Crystals
Authors: Kim Ilhwan , Lee Donghwa , Lee Kwang Jo
Published: August 2021

The mid-infrared (mid-IR) continuum generation based on broadband second harmonic generation (SHG) (or difference frequency generation) is of great interest in a wide range of applications such as free space communications, environmental monitoring, thermal imaging, high-sensitivity metrology, gas sensing, and molecular fingerprint spectroscopy. The second-order nonlinear optic (NLO) crystals have been spotlighted as a material platform for converting the wavelengths of existing lasers into the mid-IR spectral region or for realizing tunable lasers. In particular, the spectral coverage could be extended to ~19 µm with non-oxide NLO crystals. In this paper, we theoretically and numerically investigated the broadband SHG properties of non-oxide mid-IR crystals in three categories: chalcopyrite semiconductors, defect chalcopyrite, and orthorhombic ternary chalcogenides. The technique is based on group velocity matching between interacting waves in addition to birefringent phase matching. We will describe broadband SHG characteristics in terms of beam propagation directions, spectral positions of resonance, effective nonlinearities, spatial walk-offs between interacting beams, and spectral bandwidths. The results will show that the spectral bandwidths of the fundamental wave allowed for broadband SHG to reach several hundreds of nm. The corresponding SH spectral range spans from 1758.58 to 4737.18 nm in the non-oxide crystals considered in this study. Such broadband SHG using short pulse trains can potentially be applied to frequency up-conversion imaging in the mid-IR region, in information transmission, and in nonlinear optical signal processing.
Seeding Resilient Restoration: An Indicator System for the Analysis of Tree Seed Systems
Authors: Atkinson Rachel J. , Thomas Evert , Roscioli Federico , Cornelius Jonathan P. , Zamora-Cristales Rene , Franco Chuaire Maria , Alcázar Carolina , Mesén Francisco , Lopez Hariet , Ipinza Roberto , Donoso Pablo J. , Gallo Leonardo , Nieto Victor , Ugarte Julio , Sáenz-Romero Cuauhtémoc , Fremout Tobias , Jalonen Riina , Gaisberger Hannes , Vinceti Barbara , Valette Michel , Bosshard Ennia , Ekué Marius , Wiederkehr Guerra Gabriela , Kettle Chris
Published: August 2021

Achieving multi-million-hectare commitments from countries around the world to restore degraded lands in resilient and sustainable ways requires, among other things, huge volumes of tree planting material. Seed systems encompassing all forest reproductive material (e.g., seeds, cuttings, stakes, and wildings), are key to ensuring that sufficient planting material with a diverse range of suitable species, adapted to local conditions and capable of persisting under a changing climate, is available for restoration projects. The ideal structure of a seed system integrates five components: seed selection and innovation, seed harvesting and production, market access, supply and demand, quality control, and an enabling environment. We propose 15 indicators to evaluate these key components and trial them by assessing national seed systems in 7 Latin American countries. We conclude that the indicators enable a straightforward assessment of the strengths and weaknesses of national seed systems, thus assisting governments to identify key areas for improvement and opportunities for horizontal learning.
Predicting Depression in Community Dwellers Using a Machine Learning Algorithm
Authors: Cho Seo-Eun , Geem Zong Woo , Na Kyoung-Sae
Published: August 2021

Depression is one of the leading causes of disability worldwide. Given the socioeconomic burden of depression, appropriate depression screening for community dwellers is necessary. We used data from the 2014 and 2016 Korea National Health and Nutrition Examination Surveys. The 2014 dataset was used as a training set, whereas the 2016 dataset was used as the hold-out test set. The synthetic minority oversampling technique (SMOTE) was used to control for class imbalances between the depression and non-depression groups in the 2014 dataset. The least absolute shrinkage and selection operator (LASSO) was used for feature reduction and classifiers in the final model. Data obtained from 9488 participants were used for the machine learning process. The depression group had poorer socioeconomic, health, functional, and biological measures than the non-depression group. From the initial 37 variables, 13 were selected using LASSO. All performance measures were calculated based on the raw 2016 dataset without the SMOTE. The area under the receiver operating characteristic curve and overall accuracy in the hold-out test set were 0.903 and 0.828, respectively. Perceived stress had the strongest influence on the classifying model for depression. LASSO can be practically applied for depression screening of community dwellers with a few variables. Future studies are needed to develop a more efficient and accurate classification model for depression.
Molecular and Clinical Insights on the Complex Interaction between Oxidative Stress, Apoptosis, and Endobiota in the Pathogenesis of Endometriosis
Authors: Doroftei Bogdan , Ilie Ovidiu-Dumitru , Balmus Ioana-Miruna , Ciobica Alin , Maftei Radu , Scripcariu Ioana , Simionescu Gabriela , Grab Delia , Stoian Irina , Ilea Ciprian
Published: August 2021

Endometriosis (EMS) remains, to date, an intriguing and debilitating gynecological disorder that possesses a multifactorial substrate. Recent studies with the objective of elucidating its etiology highlighted the antagonistic effect of EMS on a multiple of processes involved in homeostasis. Although the current oxidative biomarkers clearly reveal the consequences induced by EMS, its implication in the associated inflammatory reactions could be much more complex. Besides the overproduction of reactive oxygen species (ROS) that leads to an exacerbated oxidative response, it also changes the normal expression of several pro-inflammatory modulators, reflected by the fluctuating activity of several pro- and anti-apoptotic mediators whose expression is impaired. In light of this topic, several studies elucidate the involvement of apoptosis in EMS, being brought controversial findings, even reports with no significant change. Further, some authors reported an abnormal expression of multiple genes that are crucial for the overall functionality of the female reproductive system. Cumulatively, it seems that the subsequent oxidative imbalance and apoptosis process impairment could further disrupt the normal removal of unnecessary biological products. Based on all gathered evidence, we could argue that the related stress state could determine human endobiota impairment, which could further participate in the inflammatory and main antioxidant enzyme changes occurring in EMS. Moreover, a correlation between endobiota integrity, inflammation, and oxidative stress (OS) was suggested in relation to the possible predisposition to pathogen determined infections.
Hardness of Resin Cements Polymerized through Glass-Ceramic Veneers
Authors: Aldryhim Hanan , El-Mowafy Omar , McDermott Peter , Prakki Anuradha
Published: August 2021

(1) Background: The aim of this study is to evaluate the hardness of resin cements polymerized through ceramic disks under different process factors (ceramic type and thickness, light-polymerization units and polymerization time); (2) Method: Three types of ceramic blocks were used (IPS e.max CAD; Celtra Duo; VITABLOCS). Ceramic disks measuring 0.5 mm, 1.0 mm and 1.5 mm were cut from commercial blocks. Two resin cements (Rely X Veneer and Variolink Esthetic) were polymerized through the ceramic specimens using distinct light-polymerization units (Deep-cure; Blue-phase) and time intervals (10 and 20 s). Hardness of cement specimens was measured using microhardness tester with a Knoop indenter. Data were statistically analyzed using factorial ANOVA (α = 5%); (3) Results: Mean microhardness of Rely X Veneer cement was significantly higher than that of Variolink Esthetic. Deep-cure resulted in higher mean microhardness values compared to Blue-phase at 0.5- and 1-mm specimen thicknesses. Moreover, a direct correlation was found between polymerization time and hardness of resin cement; (4) Conclusions: Surface hardness was affected by resin cement type and ceramic thickness, and not affected by ceramic types, within evaluated conditions. Increasing light-polymerization time significantly increased the hardness of the cement.
Education Regarding and Adherence to Recommended Nutrition Guidelines among Dental Students
Authors: Frayna Camille , Devantier Christoffer , Harris Braden , Kingsley Karl , Polanski Joshua M.
Published: August 2021

The Dietary Guidelines for Americans (DGA) were developed to reduce or prevent many types of chronic illness, including cancer, heart disease and diabetes. Healthcare provider recommendations may be influenced by understanding of and adherence to the DGA, which may be incorporated into provider training, medical and dental clinical curricula—although few studies have evaluated adherence to the DGA among dental students. This approved retrospective study of voluntary student responses from a first-year dental school nutrition course included a short dietary and exercise survey administered as part of the DGA learning module. A total of N = 299 students completed the voluntary nutrition survey, yielding a response rate of 91.4%. Daily fruit and vegetable intake, dairy and whole grain servings among UNLV-SDM students were significantly lower than the DGA recommendations but higher than U.S. averages for 18–30-year-olds—although neither group met DGA recommendations. This study represents one of the first to evaluate the dietary intake of U.S. dental students for comparison with the DGA for positive health behaviors. These data demonstrate a lack of adherence to the DGA among highly educated dental students and the need for the curricular inclusion of diet and nutrition into the dental school curriculum.
The Information Loss of a Stochastic Map
Authors: Fullwood James , Parzygnat Arthur J.
Published: August 2021

We provide a stochastic extension of the Baez–Fritz–Leinster characterization of the Shannon information loss associated with a measure-preserving function. This recovers the conditional entropy and a closely related information-theoretic measure that we call conditional information loss. Although not functorial, these information measures are semi-functorial, a concept we introduce that is definable in any Markov category. We also introduce the notion of an entropic Bayes’ rule for information measures, and we provide a characterization of conditional entropy in terms of this rule.
Impact of Input Data on Intelligence Partitioning Decisions for IoT Smart Camera Nodes
Authors: Leal Isaac Sánchez , Shallari Irida , Krug Silvia , Jantsch Axel , O’Nils Mattias
Published: August 2021

Image processing systems exploit image information for a purpose determined by the application at hand. The implementation of image processing systems in an Internet of Things (IoT) context is a challenge due to the amount of data in an image processing system, which affects the three main node constraints: memory, latency and energy. One method to address these challenges is the partitioning of tasks between the IoT node and a server. In this work, we present an in-depth analysis of how the input image size and its content within the conventional image processing systems affect the decision on where tasks should be implemented, with respect to node energy and latency. We focus on explaining how the characteristics of the image are transferred through the system until finally influencing partition decisions. Our results show that the image size affects significantly the efficiency of the node offloading configurations. This is mainly due to the dominant cost of communication over processing as the image size increases. Furthermore, we observed that image content has limited effects in the node offloading analysis.
Decision Tree Application to Classification Problems with Boosting Algorithm
Authors: Zhao Long , Lee Sanghyuk , Jeong Seon-Phil
Published: August 2021

A personal credit evaluation algorithm is proposed by the design of a decision tree with a boosting algorithm, and the classification is carried out. By comparison with the conventional decision tree algorithm, it is shown that the boosting algorithm acts to speed up the processing time. The Classification and Regression Tree (CART) algorithm with the boosting algorithm showed 90.95% accuracy, slightly higher than without boosting, 90.31%. To avoid overfitting of the model on the training set due to unreasonable data set division, we consider cross-validation and illustrate the results with simulation; hypermeters of the model have been applied and the model fitting effect is verified. The proposed decision tree model is fitted optimally with the help of a confusion matrix. In this paper, relevant evaluation indicators are also introduced to evaluate the performance of the proposed model. For the comparison with the conventional methods, accuracy rate, error rate, precision, recall, etc. are also illustrated; we comprehensively evaluate the model performance based on the model accuracy after the 10-fold cross-validation. The results show that the boosting algorithm improves the performance of the model in accuracy and precision when CART is applied, but the model fitting time takes much longer, around 2 min. With the obtained result, it is verified that the performance of the decision tree model is improved under the boosting algorithm. At the same time, we test the performance of the proposed verification model with model fitting, and it could be applied to the prediction model for customers’ decisions on subscription to the fixed deposit business.
Review on Control Techniques for EV Bidirectional Wireless Chargers
Authors: Triviño Alicia , Gonzalez-Gonzalez Jose M. , Castilla Miguel
Published: August 2021

Due to their flexibility, Electric Vehicles (EVs) constitute an important asset for the integration of renewable energy sources in the Smart Grid. In particular, they should have a dual role: as a controllable load and as a mobile generator with a low inertia. To perform these tasks, chargers must provide the electronics with a power flow from the grid to the vehicle and vice versa. This bidirectionality can also be implemented in wireless chargers. The power converters, the compensation networks and the coil misalignment must be considered when designing the control of these systems. This paper presents a review about the proposed algorithms to control the active and the reactive power flow in a bidirectional wireless charger.
Deep Multi-Image Steganography with Private Keys
Authors: Kweon Hyeokjoon , Park Jinsun , Woo Sanghyun , Cho Donghyeon
Published: August 2021

In this paper, we propose deep multi-image steganography with private keys. Recently, several deep CNN-based algorithms have been proposed to hide multiple secret images in a single cover image. However, conventional methods are prone to the leakage of secret information because they do not provide access to an individual secret image and often decrypt the entire hidden information all at once. To tackle the problem, we introduce the concept of private keys for secret images. Our method conceals multiple secret images in a single cover image and generates a visually similar container image containing encrypted secret information inside. In addition, private keys corresponding to each secret image are generated simultaneously. Each private key provides access to only a single secret image while keeping the other hidden images and private keys unrevealed. In specific, our model consists of deep hiding and revealing networks. The hiding network takes a cover image and secret images as inputs and extracts high-level features of the cover image and generates private keys. After that, the extracted features and private keys are concatenated and used to generate a container image. On the other hand, the revealing network extracts high-level features of the container image and decrypts a secret image using the extracted feature and a corresponding private key. Experimental results demonstrate that the proposed algorithm effectively hides and reveals multiple secret images while achieving high security.
Designing a Multiaxial Extensometric Force Platform: A Manufacturing Experience
Authors: Beingolea Jorge Rodolfo , Rodrigues Helder Andrade , Zegarra Milagros , Sulla-Espinoza Erasmo , Torres-Silva Romildo , Rendulich Jorge
Published: August 2021

Studies that lead to the development of more accessible and low-cost electronic technologies and devices for biomechanical and biomedical analysis applications are becoming increasingly needed. In this work, the development of a multiaxial extensometric force platform will be addressed, aiming to improve the sensitivity and reduce the costs of existing platforms. Additionally, this platform can be used for analysis and characterization of flight time and postural characterization of volleyball athletes. As a result, a functional and easily produced prototype was created, due to the processes used (final cost of the developed platform—USD$100). The interfaces of visualization and analysis of the device functions were designed in LabView. The purpose of the experiments is to perform flight analysis of athletes, and all functions designed for the platform strength and endurance are focused on that same purpose. The prototype’s functions were evaluated by applying loads from 700 to 1000 N (Newtons) and its future integration with other instruments such as the surface electromyography (EMG) and an electrocardiogram (ECG) is expected to form an instrument kit that improves the characterization of studies of balance, strength and muscular endurance.
Diagnosis of Alzheimer’s Disease Based on the Modified Tresnet
Authors: Xu Zelin , Deng Hongmin , Liu Jin , Yang Yang
Published: August 2021

In the medical field, Alzheimer’s disease (AD), as a neurodegenerative brain disease which is very difficult to diagnose, can cause cognitive impairment and memory decline. Many existing works include a variety of clinical neurological and psychological examinations, especially computer-aided diagnosis (CAD) methods based on electroencephalographic (EEG) recording or MRI images by using machine learning (ML) combined with different preprocessing steps such as hippocampus shape analysis, fusion of embedded features, and so on, where EEG dataset used for AD diagnosis is usually is large and complex, requiring extraction of a series of features like entropy features, spectral feature, etc., and it has seldom been applied in the AD detection based on deep learning (DL), while MRI images were suitable for both ML and DL. In terms of the structural MRI brain images, few differences could be found in brain atrophy among the three situations: AD, mild cognitive impairment (MCI), and Normal Control (NC). On the other hand, DL methods have been used to diagnose AD incorporating MRI images in recent years, but there have not yet been many selective models with very deep layers. In this article, the Gray Matter (GM) Magnetic Resonance Imaging (MRI) is automatically extracted, which could better distinguish among the three types of situations like AD, MCI, and NC, compared with Cerebro Spinal Fluid (CSF) and White Matter (WM). Firstly, FMRIB Software Library (FSL) software is utilized for batch processing to remove the skull, cerebellum and register the heterogeneous images, and the SPM + cat12 tool kits in MATLAB is used to segment MRI images for obtaining the standard GM MRI images. Next, the GM MRI images are trained by some new neural networks. The characteristics of the training process are as follows: (1) The Tresnet, as the network that achieves the best classification effect among several new networks in the experiment, is selected as the basic network. (2) A multi-receptive-field mechanism is integrated into the network, which is inspired by neurons that can dynamically adjust the receptive fields according to different stimuli. (3) The whole network is realized by adding multiple channels to the convolutional layer, and the size of the convolution kernel of each channel can be dynamically adjusted. (4) Transfer learning method is used to train the model for speeding up the learning and optimizing the learning efficiency. Finally, we achieve the accuracies of 86.9% for AD vs. NC, 63.2% for AD vs. MCI vs. NC respectively, which outperform the previous approaches. The results demonstrate the effectiveness of our approach.
Assessment of Ground Regeneration around Borehole Heat Exchangers between Heating Seasons in Cold Climates: A Case Study in Bialystok (NE, Poland)
Authors: Piotrowska-Woroniak Joanna
Published: August 2021

Based on the experimental studies, the process of ground regeneration around the borehole loaded with brine-water heat pumps working exclusively for heating purposes in the period of four consecutive heating seasons in a cold climate was presented. The research was conducted in north-eastern Poland. The aim of the work is to verify the phenomenon of thermal ground regeneration in the period between heating seasons on the basis of the recorded data and to check whether the ground is able to regenerate itself and at what rate. It was noticed that the ground does not fully regenerate, especially during heating seasons with lower temperatures. In the analyzed period, from 22 September 2016 to 12 October 2020, the ground probably cooled irreversibly by 1.5 °C. In order to illustrate and evaluate the speed of changes in the ground, the one’s profile with an undisturbed temperature field was presented for each month of the year. The presented results can be a very important source of information for the analysis of geothermal conditions occurring in the ground. They can be used to verify mathematical models and conduct long-term simulations that allow us to see the complexity of the processes taking place in the ground.
Outage Estimation in Electric Power Distribution Systems Using a Neural Network Ensemble
Authors: Das Sanjoy , Kankanala Padmavathy , Pahwa Anil
Published: August 2021

Outages in an overhead power distribution system are caused by multiple environmental factors, such as weather, trees, and animal activity. Since they form a major portion of the outages, the ability to accurately estimate these outages is a significant step towards enhancing the reliability of power distribution systems. Earlier research with statistical models, neural networks, and committee machines to estimate weather-related and animal-related outages has reported some success. In this paper, a deep neural network ensemble model for outage estimation is proposed. The entire input space is partitioned with a distinct neural network in the ensemble performing outage estimate in each partition. A novel algorithm is proposed to train the neural networks in the ensemble, while simultaneously partitioning the input space in a suitable manner. The proposed approach has been compared with the earlier approaches for outage estimation for four U.S. cities. The results suggest that the proposed method significantly improves the estimates of outages caused by wind and lightning in power distribution systems. A comparative analysis with a previously published model for animal-related outages further establishes the overall effectiveness of the deep neural network ensemble.
Wear Resistance of Spark Ignition Engine Piston Rings in Hydrogen-Containing Environments
Authors: Kindrachuk Myroslav , Volchenko Dmytro , Balitskii Alexander , Abramek Karol F. , Volchenko Mykola , Balitskii Olexiy , Skrypnyk Vasyl , Zhuravlev Dmytro , Yurchuk Alina , Kolesnikov Valerii
Published: August 2021

We describe the external and internal hydrogen interaction on contacting surfaces in the “cylinder–piston rings” friction coupling. Under the influence of high temperatures and pressure, the oil in the combustion chamber at a temperature up to 1473 K decomposes and forms small amounts of water. External hydrogen (H2) is subsequently formed. Hydrogen removal from the piston rings reduces the heterogeneity of the structure, residual stresses, and uneven physical and chemical properties of the near-surface layers, which reduces the stress concentration and, as a consequence, results in an improvement in the performance characteristics of the surface layers of the friction couple “cylinder-piston rings” of the spark ignition engine.
Review of Wood Biomass Cyclone Burner
Authors: Choe Kangil
Published: August 2021

Despite the technology for wood biomass combustion being much more advantageous when compared to traditional burners, such as the Stoker or fluidized burner, there has been scant research on the topic of wood biomass cyclone burners. The purpose of this paper is to review biomass cyclone burner technology, which includes theory, design, and combustion, in terms of the chemistry and properties of wood biomass, emission related to NOx and CO, and application of the burner, such as co-firing with coal and gasification firing. The design factors for type 2 cyclone burners have been identified through the following three dimensionless numbers: swirl intensity (S), Strouhal number (St), and Reynolds number (Re). The lowest CO and NOx of type 2 cyclone burners have been sought for pulverized and non-pulverized wood biomass. The benefits of the co-firing of wood biomass in a cyclone burner with coal, have been presented in respect to combustion efficiency, alkali retention, and the amount of K and Na. The results evidently reveal the reduction in clinker and slag generation, which are the biggest concern to wood biomass combustion. The recent results of gasification studies using type 2 cyclone burners are compared, in terms of producer gases and syngases (H2, CO, CO2, CH4).
Airflow Fluctuation from Linear Diffusers in an Office Building: The Thermal Comfort Analysis
Authors: Borowski Marek , Łuczak Rafał , Halibart Joanna , Zwolińska Klaudia , Karch Michał
Published: August 2021

In buildings, the HVAC systems are responsible for a major part of the energy consumption. Incorrect design or selection of the system and improper installation, operation, and maintenance of the systems’ elements may result in increased energy consumption. It is worth remembering that the main aim of the appropriate system is to maintain the high quality of the indoor environment. Appropriate selection of the HVAC solution ensures both thermal and quality parameters of the air, independently of the internal and external heat loads. The microclimate of a room is affected not only by air temperature, humidity, and purity, but also by air velocity in the occupied zone. The proper air velocity distribution prevents discomfort, particularly at workstations. Based on the measurements in the office building, an analysis of velocity profiles of air supplying two different types of linear diffusers was carried out. The analysis was made based on the results of measurements performed with thermoanemometers in the actual facility. During the study, temperature of the supply air was lower that the air in the room. Analysis was focused on the airflow fluctuation and its impact on the users’ comfort. This is an obvious topic but extremely rarely mentioned in publications related to air diffusers. The results show the importance of air fluctuation and its influence on the users’ comfort. During the measurements, the instantaneous air velocity for one of the analyzed types of the diffuser was up to 0.34 m/s, while the average value from the period of 240 s for the same measuring point was relatively low: it was 0.19 m/s. Only including the airflow variability over time allowed for choosing the type of diffuser, which ensures the comfort of users. The measurements carried out for two linear diffusers showed differences in the operation of these diffusers. The velocity in the occupied zone was much higher for one type (0.36 m/s, 3.00 m from diffusers) than for another one (0.22 m/s, 5.00 m from diffusers). The improper selection of the diffuser’s type and its location may increase the risk of the draft in the occupied zone.
System-Independent Irradiance Sensorless ANN-Based MPPT for Photovoltaic Systems in Electric Vehicles
Authors: Cortés Baldwin , Tapia Roberto , Flores Juan J.
Published: August 2021

The integration of photovoltaic systems (PVS) in electric vehicles (EV) increases the vehicle’s autonomy by providing an additional energy source other than the battery. However, current solar cell technology generates around 200 W for a 1.4 m2 panel (to be installed on the roof of the EV) at stable irradiance conditions. This limitation in production and the sudden changes in irradiance produced by shadows of clouds, buildings, and other structures make developing a fast and efficient maximum power point tracking (MPPT) technique in this area necessary. This article proposes an artificial neural network (ANN)-based MPPT, called DS-ANN, that uses manufacturer datasheet parameters as inputs to the network to address this problem. The Bayesian backpropagation-regularization performs the training, ensuring that the MPPT technique operates satisfactorily on different PVS without retraining. We simulated the response of 20 commercial modules against actual irradiance data to validate the proposed method. The results show that our method achieves an average tracking efficiency of 99.66%, improving by 1.21% over an enhanced P&O method.
Production of Negative-Emissions Steel Using a Reducing Gas Derived from DFB Gasification
Authors: Pissot Sébastien , Thunman Henrik , Samuelsson Peter , Seemann Martin
Published: August 2021

A dual fluidized bed (DFB) gasification process is proposed to produce sustainable reducing gas for the direct reduction (DR) of iron ore. This novel steelmaking route is compared with the established process for DR, which is based on natural gas, and with the emerging DR technology using electrolysis-generated hydrogen as the reducing gas. The DFB-DR route is found to produce reducing gas that meets the requirement of the DR reactor, based on existing MIDREX plants, and which is produced with an energetic efficiency comparable with the natural gas route. The DFB-DR path is the only route considered that allows negative CO2 emissions, enabling a 145% decrease in emissions relative to the traditional blast furnace–basic oxygen furnace (BF–BOF) route. A reducing gas cost between 45–60 EUR/MWh is obtained, which makes it competitive with the hydrogen route, but not the natural gas route. The cost estimation for liquid steel production shows that, in Sweden, the DFB-DR route cannot compete with the natural gas and BF–BOF routes without a cost associated with carbon emissions and a revenue attributed to negative emissions. When the cost and revenue are set as equal, the DFB-DR route becomes the most competitive for a carbon price >60 EUR/tCO2.
Optimization Control Strategy for Large Doubly-Fed Induction Generator Wind Farm Based on Grouped Wind Turbine
Authors: Zhou Shijia , Rong Fei , Ning Xiaojie
Published: August 2021

This paper proposes a grouped, reactive power optimization control strategy to maximize the active power output of a doubly-fed induction generator (DFIG) based on a large wind farm (WF). Optimization problems are formulated based on established grouped loss models and the reactive power limits of the wind turbines (WTs). The WTs in the WF are grouped to relieve computational burden. The particle swarm optimization (PSO) algorithm is applied to optimize the distribution of reactive power among groups, and a proportional control strategy is used to distribute the reactive power requirements in each group. Furthermore, the proposed control strategy optimizes the reactive power distribution between the stator and the grid side converter (GSC) in each WT. The proposed control strategy greatly reduces the number of variables for optimization, and increases the calculation speed of the algorithm. Thus, the control strategy can not only increase the active power output of the WF but also enable the WF to track the reactive power dispatching instruction of the power grid. A simulation of the DFIG WF is given to verify the effectiveness of the proposed control strategy at different wind speeds and reactive power references.
A Study of Eutectic Temperature of Sugar Mixture for Thermal Energy Storage
Authors: Wisutthimateekorn Suchanun , Lerkkasemsan Nuttapol
Published: August 2021

We studied Phase Change Materials (PCMs), which can be used as thermal energy storage for temperatures lower than 120 °C: They can store both sensible heat from a changing temperature and latent heat from changing the state of a substance. The advantage of storing energy in a PCM is that it can be reused continuously, without the degradation of efficiency. Here, the PCM mixture consists of fructose and xylitol and thus, this PCM can be used to store energy below 120 °C. The calculated Excess Gibbs Energy and activity coefficient of xylitol and fructose decreased as the fraction of xylitol increased. We tested a system, which included an evacuated tubular collector and—fructose mixtures. The system with the PCM maintained a water temperature ~14 °C higher than water without the PCM. This PCM system could store 248 kJ/kg. The xylitol—fructose mixture had a market price ~$US 4.62 $/kg (2018 price), so compared to other PCMs, xylitol-fructose was cheap and store energy efficiently.
Improving the Efficiency of Maritime Infrastructures through a BIM-Based Building Energy Modelling Approach: A Case Study in Naples, Italy
Authors: Barone Giovanni , Buonomano Annamaria , Forzano Cesare , Giuzio Giovanni Francesco , Palombo Adolfo
Published: August 2021

Worldwide, the design, renovation, and sustainable management of port buildings play a crucial role for sustainability. In this framework, a computer simulation of a building’s thermal behaviour is an almost mandatory tool for making informed decisions. However, the development of a building energy model is a challenging task that could discourage its adoption. A possible solution would be to exploit an existing Building Information Modeling (BIM) model to automatically generate an accurate and flexible Building Energy Modeling (BEM) one. Such a method, which can substantially improve decision-making processes, still presents some issues and needs to be further investigated, as also detectable from the literature on the topic. In this framework, a novel workflow to extrapolate BIM data for energy simulation is proposed and analysed in this paper. Here, the BIM to BEM approach was tested as a useful tool for the maritime industry to improve the implementation of effective energy-saving measures. Specifically, in order to prove the capabilities of the proposed method, a maritime passenger station in Naples was chosen as case study and investigated by comparing different strategies to reduce the annual primary energy consumption. The optimal level of modelling detail required by a trustable building energy assessment was also investigated. By the proposed method, interesting primary energy savings (ranging from 24 to 41%) are achieved and CO2 emissions avoided (ranging from 16 to 34 tons CO2/year) for the investigated building, proving the potential of this approach. Definitely, this paper proves the validity of the proposed methodology and emphasizes its numerous benefits towards the achievements of the most modern sustainability standards.
Study on Image Correction and Optimization of Mounting Positions of Dual Cameras for Vehicle Test
Authors: Lee Si-Ho , Kim Bong-Ju , Lee Seon-Bong
Published: August 2021

Among surrounding information-gathering devices, cameras are the most accessible and widely used in autonomous vehicles. In particular, stereo cameras are employed in academic as well as practical applications. In this study, commonly used webcams are mounted on a vehicle in a dual-camera configuration and used to perform lane detection based on image correction. The height, baseline, and angle were considered as variables for optimizing the mounting positions of the cameras. Then, a theoretical equation was proposed for the measurement of the distance to the object, and it was validated via vehicle tests. The optimal height, baseline, and angle of the mounting position of the dual camera configuration were identified to be 40 cm, 30 cm, and 12°, respectively. These values were utilized to compare the performances of vehicles in stationary and driving states on straight and curved roads, as obtained by vehicle tests and theoretical calculations. The comparison revealed the maximum error rates in the stationary and driving states on a straight road to be 3.54% and 5.35%, respectively, and those on a curved road to be 9.13% and 9.40%, respectively. It was determined that the proposed method is reliable because the error rates were less than 10%.
How Cultural Heritage Studies Based on Dendrochronology Can Be Improved through Two-Way Communication
Authors: Edvardsson Johannes , Almevik Gunnar , Lindblad Linda , Linderson Hans , Melin Karl-Magnus
Published: August 2021

A significant part of our cultural heritage consists of wood. Research on historical wooden structures and artefacts thereby provides knowledge of people’s daily lives and the society in which they lived. Dendrochronology is a well-established dating method of wood that can also provide valuable knowledge about climate dynamics, environmental changes, silviculture, and cultural transformations. However, dendrochronology comes with some limitations that end users in cultural heritage sciences must be aware of, otherwise their surveys may not be ultimately performed. We have drawn attention to studies in which dendrochronological results have been misinterpreted, over-interpreted, or not fully utilized. On the other hand, a rigorous dendrochronological survey may not respond to the request of information in practice. To bridge this rigour-relevance gap, this article has considered and reviewed both the dendrochronology’s science-perspective and the practitioner’s and end user’s call for context appropriate studies. The material for this study consists of (i) interviews with researchers in dendrochronology and end users represented by cultural heritage researchers with focus on building conservation and building history in Sweden, and (ii) a review of dendrochronological reports and the literature where results from the reports have been interpreted. From these sources we can conclude that a continuous two-way communication between the dendrochronologists and end users often would have resulted in improved cultural heritage studies. The communication can take place in several steps. Firstly, the design of a sampling plan, which according to the current standard for sampling of cultural materials often is required, is an excellent common starting point for communication. Secondly, the survey reports could be developed with a more extensive general outline of the method and guidance in how to interpret the results. Thirdly, the potential contribution from dendrochronology is often underused, foreseeing historical information on local climate, silviculture, and choice of quality of the wooden resource, as the focus most often is the chronological dating. Finally, the interpretation of the results should consider all the available sources where dendrochronology is one stake for a conciliant conclusion.
Rural Residents’ Participation Intention in Community Forestry-Challenge and Prospect of Community Forestry in Sri Lanka
Authors: Ekanayake E. M. B. P. , Xie Yi , Ahmad Shahzad
Published: August 2021

The contribution of local communities has become widely recognized as a better alternative in forest management than the traditional command-based control approach. However, several years later of implementation, most programs were failed due to a lack of community participation, imposing an uncertain future for community forestry. This paper examines rural Sri Lankans’ participation intention in community forestry (CF) program by using the Probit regression model. Randomly selected 300 individuals representing both CF members and non-CF members were interviewed for the study. The study results indicate that rural residents’ intention in future CF program negatively correlated with the participation status (CF membership) of individuals. Accordingly, CF members show less participation intention in future CF program than non-CF members. Socio-economic variables such as education level (p < 0.01) and the occupation of head of the household (p < 0.05) and total household income (p < 0.01) have significant influences on individuals’ participation intention in CF. In addition, non-monetary benefits derived from CF and perception on the product regulation and conflict mitigation are also appeared to significantly and positively affect villagers’ intention. The findings also revealed the knowledge gap on the purpose of the CF program and CF policy design. Hence, require immediate attention to improve awareness. Moreover, failure to raise local people’s participation intention in CF may indicate inadequate or ineffective government policies. Therefore, the Department of Forest Conservation should take sound measures to ensure that community-based forest management policies are consistently implemented at different administrative levels across the country and its rightness should be evaluated strictly.
Resilience of a Fire-Maintained Pinus palustris Woodland to Catastrophic Wind Disturbance: 10 Year Results
Authors: Goode J. Davis , Kleinman Jonathan S. , Hart Justin L.
Published: August 2021

Increased interest in ecosystem recovery and resilience has been driven by concerns over global change-induced shifts in forest disturbance regimes. In frequent-fire forests, catastrophic wind disturbances modify vegetation-fuels-fire feedbacks, and these alterations may shift species composition and stand structure to alternative states relative to pre-disturbance conditions. We established permanent inventory plots in a catastrophically wind-disturbed and fire-maintained Pinus palustris woodland in the Alabama Fall Line Hills to examine ecosystem recovery and model the successional and developmental trajectory of the stand through age 50 years. We found that sapling height was best explained by species. Species with the greatest mean heights likely utilized different regeneration mechanisms. The simulation model projected that at age 50 years, the stand would transition to be mixedwood and dominated by Quercus species, Pinus taeda, and P. palustris. The projected successional pathway is likely a function of residual stems that survived the catastrophic wind disturbance and modification of vegetation-fuels-fire feedbacks. Although silvicultural interventions will be required for this system to exhibit pre-disturbance species composition and structure, we contend that the ecosystem was still resilient to the catastrophic disturbance because similar silvicultural treatments were required to create and maintain the P. palustris woodland prior to the disturbance event.