bluuebunny/crossref_metadata_2025 huggingface dataset:
Short- and Long-Term Effects of Rehabilitation after Perimesencephalic Subarachnoid Hemorrhage
Authors: Schmitz Jens , Kashefiolasl Sepide , Brawanski Nina , Dinc Nazife , Gessler Florian , Senft Christian , Tritt Stephanie , Seifert Volker , Konczalla Jürgen
Published: October 2021

In about 25% of patients with spontaneous subarachnoid hemorrhage (SAH), a bleeding source cannot be identified during radiological diagnostics. Generally, the outcome of perimesencephalic or prepontine (PM) SAH is known to be significantly better than after non-PM SAH. Data about long-term follow-up concerning physical and mental health are scarce, so this study is reports on long-term results. We measured the influence of PM SAH on a quality-of-life modified Rankin (mRs) scale after six months. For long-term follow-up, a SF-36 questionnaire was used. Questionnaires were sent out between 18 and 168 months after ictus. In 37 patients, a long-term follow-up was available (up to 14 years after SAH). Data detected with the SF-36 questionnaire are compared to reference applicability to the standard population. In total, 37 patients were included for further analysis and divided in 2 subgroups; 13 patients (35%) received subsequent rehabilitation after clinical stay and 24 (65%) did not. In the short-term outcome, a significant improvement from discharge until follow-up was identified in patients with subsequent rehabilitation, but not in the matched pair group without rehabilitation. When PM SAH was compared to the standard population, a reduction in quality of life was identified in physical items (role limitations because of physical health problems, physical functioning) as well as in psychological items (role limitations because of emotional problems). Subsequent rehabilitation on PM SAH patients probably leads to an increase in independence and better mRs. While better mRs was shown at discharge in patients without subsequent rehabilitation, the mRs of rehabilitants was nearly identical after rehabilitation. Patients with good mRs also reached high levels of health-related quality of life (HRQoL) without rehabilitation. Thus, subsequent rehabilitation needs to be encouraged on an individual basis. Indication criteria for subsequent rehabilitation should be defined in further studies to improve patient treatment and efficiency in health care.
A Visual Aquaculture System Using a Cloud-Based Autonomous Drones
Authors: Ubina Naomi A. , Cheng Shyi-Chyi , Chen Hung-Yuan , Chang Chin-Chun , Lan Hsun-Yu
Published: October 2021

This paper presents a low-cost and cloud-based autonomous drone system to survey and monitor aquaculture sites. We incorporated artificial intelligence (AI) services using computer vision and combined various deep learning recognition models to achieve scalability and added functionality, in order to perform aquaculture surveillance tasks. The recognition model is embedded in the aquaculture cloud, to analyze images and videos captured by the autonomous drone. The recognition models detect people, cages, and ship vessels at the aquaculture site. The inclusion of AI functions for face recognition, fish counting, fish length estimation and fish feeding intensity provides intelligent decision making. For the fish feeding intensity assessment, the large amount of data in the aquaculture cloud can be an input for analysis using the AI feeding system to optimize farmer production and income. The autonomous drone and aquaculture cloud services are cost-effective and an alternative to expensive surveillance systems and multiple fixed-camera installations. The aquaculture cloud enables the drone to execute its surveillance task more efficiently with an increased navigation time. The mobile drone navigation app is capable of sending surveillance alerts and reports to users. Our multifeatured surveillance system, with the integration of deep-learning models, yielded high-accuracy results.
Efficient Drone-Based Rare Plant Monitoring Using a Species Distribution Model and AI-Based Object Detection
Authors: Reckling William , Mitasova Helena , Wegmann Karl , Kauffman Gary , Reid Rebekah
Published: October 2021

Monitoring rare plant species is used to confirm presence, assess health, and verify population trends. Unmanned aerial systems (UAS) are ideal tools for monitoring rare plants because they can efficiently collect data without impacting the plant or endangering personnel. However, UAS flight planning can be subjective, resulting in ineffective use of flight time and overcollection of imagery. This study used a Maxent machine-learning predictive model to create targeted flight areas to monitor Geum radiatum, an endangered plant endemic to the Blue Ridge Mountains in North Carolina. The Maxent model was developed with ten environmental layers as predictors and known plant locations as training data. UAS flight areas were derived from the resulting probability raster as isolines delineated from a probability threshold based on flight parameters. Visual analysis of UAS imagery verified the locations of 33 known plants and discovered four previously undocumented occurrences. Semi-automated detection of plant species was explored using a neural network object detector. Although the approach was successful in detecting plants in on-ground images, no plants were identified in the UAS aerial imagery, indicating that further improvements are needed in both data acquisition and computer vision techniques. Despite this limitation, the presented research provides a data-driven approach to plan targeted UAS flight areas from predictive modeling, improving UAS data collection for rare plant monitoring.
Leaf-Off and Leaf-On UAV LiDAR Surveys for Single-Tree Inventory in Forest Plantations
Authors: Lin Yi-Chun , Liu Jidong , Fei Songlin , Habib Ayman
Published: October 2021

LiDAR technology has been proven to be an effective remote sensing technique for forest inventory and management. Among existing remote sensing platforms, unmanned aerial vehicles (UAV) are rapidly gaining popularity for their capability to provide high-resolution and accurate point clouds. However, the ability of a UAV LiDAR survey to map under canopy features is determined by the degree of penetration, which in turn depends on the percentage of canopy cover. In this study, a custom-built UAV-based mobile mapping system is used for simultaneously collecting LiDAR and imagery data under different leaf cover scenarios in a forest plantation. Bare earth point cloud, digital terrain model (DTM), normalized height point cloud, and quantitative measures for single-tree inventory are derived from UAV LiDAR data. The impact of different leaf cover scenarios (leaf-off, partial leaf cover, and full leaf cover) on the quality of the products from UAV surveys is investigated. Moreover, a bottom-up individual tree localization and segmentation approach based on 2D peak detection and Voronoi diagram is proposed and compared against an existing density-based clustering algorithm. Experimental results show that point clouds from different leaf cover scenarios are in good agreement within a 1-to-10 cm range. Despite the point density of bare earth point cloud under leaf-on conditions being substantially lower than that under leaf-off conditions, the terrain models derived from the three scenarios are comparable. Once the quality of the DTMs is verified, normalized height point clouds that characterize the vertical forest structure can be generated by removing the terrain effect. Individual tree detection with an overall accuracy of 0.98 and 0.88 is achieved under leaf-off and partial leaf cover conditions, respectively. Both the proposed tree localization approach and the density-based clustering algorithm cannot detect tree trunks under full leaf cover conditions. Overall, the proposed approach outperforms the existing clustering algorithm owing to its low false positive rate, especially under leaf-on conditions. These findings suggest that the high-quality data from UAV LiDAR can effectively map the terrain and derive forest structural measures for single-tree inventories even under a partial leaf cover scenario.
Dynamical Invariants for Generalized Coherent States via Complex Quantum Hydrodynamics
Authors: Bonilla-Licea Moise , Schuch Dieter
Published: October 2021

For time dependent Hamiltonians like the parametric oscillator with time-dependent frequency, the energy is no longer a constant of motion. Nevertheless, in 1880, Ermakov found a dynamical invariant for this system using the corresponding Newtonian equation of motion and an auxiliary equation. In this paper it is shown that the same invariant can be obtained from Bohmian mechanics using complex Hamiltonian equations of motion in position and momentum space and corresponding complex Riccati equations. It is pointed out that this invariant is equivalent to the conservation of angular momentum for the motion in the complex plane. Furthermore, the effect of a linear potential on the Ermakov invariant is analysed.
A Unified Treatment of Tribo-Components Degradation Using Thermodynamics Framework: A Review on Adhesive Wear
Authors: Koottaparambil Lijesh , Khonsari M. M.
Published: October 2021

An extensive survey of open literature reveals the need for a unifying approach for characterizing the degradation of tribo-pairs. This paper focuses on recent efforts made towards developing unified relationships for adhesive-type wear under unlubricated conditions through a thermodynamic framework. It is shown that this framework can properly characterize many complex scenarios, such as degradation problems involving unidirectional, bidirectional (oscillatory and reciprocating motions), transient operating conditions (e.g., during the running-in period), and variable loading/speed sequencing.
A Combined Approach of Remote Sensing, GIS, and Social Media to Create and Disseminate Bushfire Warning Contents to Rural Australia
Authors: Perera Kithsiri , Tateishi Ryutaro , Akihiko Kondho , Herath Srikantha
Published: October 2021

Bushfires are an integral part of the forest regeneration cycle in Australia. However, from the perspective of a natural disaster, the impact of bushfires on human settlements and the environment is massive. In Australia, bushfires are the most disastrous natural hazards. According to the records of the Parliament of Australia, the recent catastrophic bushfires in NSW and Victoria burnt out over 10 million hectares of land, a figure more significant than any previous bushfire damage on record. After the deadly 2009 Black Saturday bushfires, which killed 173 people in Victoria, public attention to bushfires reached a new peak. Due to the disastrous consequences of bushfires, scientists have explored various methods to mitigate or even avoid bushfire damage, including the use of bushfire alerts. The present study adds satellite imagery and GIS-based semi-real-time bushfire contents to various bushfire warnings issued by government authorities. The new product will disseminate graphical bushfire contents to rural Australians through social media, using Google Maps. This low-cost Media GIS content can be delivered through highly popular smartphone networks in Australia through social media (Facebook and Twitter). We expect its success to encourage people to participate in disaster mitigation efforts as contributors in a participatory GIS network. This paper presents a case study to demonstrate the production process and the quality of media GIS content and further discusses the potential of using social media through the mobile network of Australia while paying attention to mobile blackspots. Media GIS content has the potential to link with the public information systems of local fire management services, disseminate contents through a mobile app, and develop into a fully automated media GIS content system to expand the service beyond bushfires.
Diagnosis and Management of Invasive Fungal Wound Infections in Burn Patients
Authors: Pruskowski Kaitlin A. , Mitchell Thomas A. , Kiley John L. , Wellington Trevor , Britton Garrett W. , Cancio Leopoldo C.
Published: October 2021

Invasive fungal wound infection (FWI) after burn injury, while uncommon, is associated with significant morbidity and mortality. There are numerous risk factors for FWI, including large burn size and incomplete excision of burn wounds. FWI can be challenging to diagnose. Close attention to changes in the physical examination and, in particular, to the appearance of burn wounds leads the burn team to be suspicious of FWI. Once FWI is suspected, histopathological evaluation of an incisional biopsy provides definitive diagnosis, while tissue culture enables identification of the causative organism to the species level and facilitates targeted antifungal therapy. Management of FWI focuses largely on aggressive surgical intervention, in addition to adjunctive systemic and topical antifungals and nonpharmacologic therapies. Treatment of FWI involves a multifaceted approach, which requires expertise from the entire multidisciplinary burn team.
Relationships in Diversity, Vegetation Indexes and Water Area in Terminal Lake of the Tarim River, Northwest China
Authors: Zhao Xinfeng , Lin Tao , Xu Hailiang , Aili Aishajiang , Zhao Wanyu , Yang Yongqiang
Published: October 2021

To examine the variation in water and vegetation coverage areas, the groundwater level and plant diversity in the terminal lake of the Tarim River, northwest China, both the monitoring data of a field survey consisting of surface samples and remote sensing data for 20 years (2000–2019) were analyzed by using field survey and indoor remote sensing methods. The results showed that (1): from 2000 to 2019, water and vegetation areas increased significantly, especially the trend of vegetation areas becoming more significant, with an average annual increase of 13.9 km2/a; (2): the plant diversity increased first and then decreased; the species richness and Pielou index in the study area were 9.0 and 0.80 in 2005, but only 2.00 and 0.08 in 2000, respectively; species composition tends to be simplified; (3): with the increase in the lake area, the groundwater level showed an up-lifted trend; the correlation between the two was significant, but there was a lag in the response of the groundwater level.
Social Impacts of a Mega-Dam Project as Perceived by Local, Resettled and Displaced Communities: A Case Study of Merowe Dam, Sudan
Authors: Abdullah Al-Noor , Rahman Sanzidur
Published: October 2021

The paper assesses social impacts of a mega-dam project (Merowe Dam in Sudan) as perceived by host and affected communities (i.e., upstream, downstream, and relocated residents), which is not commonly seen in the literature. Primary survey and interviews were conducted with 300 residents, government officials, the Dam Implementation Unit (DIU), NGOs and other key informants. Five inter-related areas of impact were scrutinized: (a) displacement of communities; (b) resettlement of displaced communities in a new location; (c) technological factors; (d) social mobility factors; and (e) economic and political institutions. Results show that Merowe Dam exerted positive as well as adverse social impacts on local communities. Increase in home sizes, opportunities for children’s schooling and quality of life improvement ranked as the top three positive impacts with residents located downstream scoring relatively higher than relocated and upstream residents. Relocated residents also showed positive attitudes towards the provision of essential services (schools, health facilities, availability of running water, electricity, marketplace, etc.), thereby enabling them to enjoy and flourish in their social lives. The adverse impacts are centered on intangible factors, such as, sentimental effects closely related to their feelings, loss of history, memories, nostalgia about the old place, and grievances regarding compensation packages and its management. Therefore, it is important to recognize the need for long-term monitoring of the resettlement process and provide emotional support to those displaced and resettled. Furthermore, there is also a need to address the livelihood requirements of local communities in the affected region.
The Role of Manager Compensation and Integrated Reporting in Company Value: Indonesia vs. Singapore
Authors: Utomo St. Dwiarso , Machmuddah Zaky , Hapsari Dian Indriana
Published: October 2021

The disclosure of integrated reporting elements can reduce information asymmetry for investors when valuing a company. This study aimed to empirically evaluate the effect of manager compensation, directly or indirectly, on firm value, through the mediating role of the disclosure of integrated reporting elements. The research sample included manufacturing companies listed on the Indonesia Stock Exchange (IDX) and the Singapore Stock Exchange (SGX). The method of analysis was PLS-SEM, using the WarpPLS 7.0 application. The results showed that compensation significantly affects firm value and the disclosure of integrated reporting elements. Integrated reporting has a significant positive impact on firm value. In addition, the disclosure of integrated reporting can mediate the impact of manager compensation on increasing firm value. This research theoretically supports agency theory, disclosure theory, and signal theory, although it is not fully applicable to each country or region of the sample company. The current research contributes to the understanding of the importance of a company’s integrated reporting disclosure in improving company value among investors. Integrated reporting describes how a company creates value over time. Our results also suggest that regulators should oblige public companies to disclose integrated reporting.
Multi-Regional Input–Output Tables for Macroeconomic Simulations in Poland’s Regions
Authors: Anagnostou Ageliki , Gajewski Pawel
Published: October 2021

The capacity of multi-regional input–output tables (MRIOTs) to investigate linkages across structures and subnational regions within a country makes them a useful and solid tool of various types of simulations. This study develops MRIOTs for the Polish regions that can be subsequently employed to macroeconomic simulations, including assessing internal policy impulse responses or testing the regional economic resilience to external shocks. For this purpose, we build three macro-regions, discuss how their structural features validate their use to study differentials in economic policy effects or regional economic resilience, and finally, describe the process of constructing the MRIOTs.
The Analysis and the Measurement of Poverty: An Interval-Based Composite Indicator Approach
Authors: Drago Carlo
Published: October 2021

The study of poverty and its quantification is a critical yet unresolved problem in social science. This work seeks to use a new composite indicator to assess poverty as a multidimensional concept. However, subjective decisions, such as various weighting systems on the indicator’s creation, may affect its perception. In order to solve this issue, we propose to use random different composite indicators based on simulated weightings and specifications to get a comprehensive interval-based composite indicator. Our method generates robust and trustworthy measurements based on a meaningful conceptual model of poverty. Furthermore, we use some interval parameters such as the upper bound, center, and lower bound to compare the different intervals related to the different statistical units and rankings to aid in analyzing extreme situations and policy scenarios. In Sicily, Calabria, Campania, and Puglia, we identify urgent circumstances. The findings reveal a consistent indicator measurement and the shadow sector’s influence on the final measurements.
Developing Public–Private Partnership Projects to Enhance Innovation Capability in the Defence Industry
Authors: Pukhova Marina Mikhailovna , Merkulina Irina Anatolievna , Bashkov Dmitry Yuryevich
Published: October 2021

The relevance of this study resides in the need to determine the key measures for a more effective application of the mechanism of public–private partnerships (PPP) in the implementation of large-scale infrastructure projects, aimed at developing the innovation potential of the Russian defence–industrial complex (DIC). Through the analysis of foreign practices of the application of PPP in the defence industry, representing a vast body of scientific and popular literature on the development of the defence industry in the U.S. and the countries of Europe and Asia, as well as a review of the domestic regulatory framework, the authors have identified the most common and key problems that are obstacles to the effective and sustainable development of PPP mechanisms, and their application not only in the civil, but also in the defence sector. This work pays specific attention to the requirements that are imposed on public and private partners in the process of implementing PPP projects in the context of SDO performance, along with the risks that are inevitably associated with the activities of each of the parties. As a result, the authors present a graphical interpretation of the algorithm for financing the state defence order (SDO) and disclose the system of interaction between the elements of a given algorithm, as well as formulating an essential recommendation for the further development of PPP in Russia.
The Effects of the Strategy and Goal on Business Performance as Mediated by Management Accounting Systems
Authors: Visedsun Nimnual , Terdpaopong Kanitsorn
Published: October 2021

Previous research in the literature often investigated the associations between management accounting systems and the success of organizations. However, little has been done in regard to the association of business strategies, goals, and firms’ performance while having management accounting tools as mediators. Management accounting systems are classified as traditional and strategic management accounting themes. Each theme, of course, implements different accounting tools. This article explores the degree to which, as mediated by management accounting systems, the business strategies and business goals of large Thai manufacturing companies influence their financial and non-financial performance. To gather the data, a survey questionnaire was developed. Of the 1500 companies selected for inclusion in the survey, 205 provided completed and usable responses for a response rate of 13.67%. Structural equation modeling (SEM) was used to analyze the relationships among the variables. The findings shed some light on what the management of a firm could expect concerning organizational performance from their business strategies, business goals, and the implementation of specific management accounting systems. Corporate strategies and corporate goals had a statistical influence on both the financial and non-financial performance of the large corporations in Thailand when mediated via strategic management accounting systems, while there was no influence when mediated by traditional management accounting systems. A greater understanding of the relationships and effects of which mediators should have been employed in organizations to bring forth business strategies and business goals and generate productive results for organizational performance is provided by this research. Choosing the appropriate performance mediators can help achieve corporate strategies and goals.
Teaching Writing in Vietnam’s Secondary and High Schools
Authors: Pham Vu Phi Ho , Truong Minh Hoa
Published: October 2021

The current study adopted features of a survey research design to examine the EFL high school teachers’ beliefs about writing and its teaching, their actual classroom practices, and the interplays between their beliefs and practices in the realm of EFL writing instruction. A sample of seventy-six EFL teachers from the eight selected high schools situated in Ho Chi Minh City was recruited for the current survey. The beliefs and practices of EFL writing instruction of these studied teachers were elicited through a thirty-nine-item questionnaire, which was qualitatively analyzed by SPSS 20.0. The study results showed that most of the participants held different views/orientations about writing skills and teaching writing, consisting of form-based, cognitive process-based, functional social-based, and interactive social-based views; nevertheless, the form-based orientation was still most dominant in their beliefs. On the contrary, in practice, most high school teachers followed the product approach, which underlies form-based orientation in lieu of different approaches, explicitly interpreting the writing section’s low results in the Vietnamese National GCSE examination in recent years.
Design, Analysis and Experimental Verification of the Self-Resonant Inverter for Induction Heating Crucible Melting Furnace Based on IGBTs Connected in Parallel
Authors: Dimitrov Borislav , Hayatleh Khaled , Barker Steve , Collier Gordana
Published: October 2021

The object of this research was a self-resonated inverter, based on paralleled Insulated-Gate Bipolar Transistors (IGBTs), for high-frequency induction heating equipment, operating in a wide range of output powers, applicable for research and industrial purposes. For the nominal installed capacity for these types of invertors to be improved, the presented inverter with a modified circuit comprising IGBT transistors connected in parallel was explored. The suggested topology required several engineering problems to be solved: minimisation of the current mismatch amongst the paralleled transistors; a precise analysis of the dynamic and static transistors’ parameters; determination of the derating and mismatch factors necessary for a reliable design; experimental verification confirming the applicability of the suggested topology in the investigated inverter. This paper presents the design and analysis of IGBT transistors based on datasheet parameters and mathematical apparatus application. The expected current mismatch and the necessary derating factor, based on the expected mismatch in transistor parameters in a production lot, were determined. The suggested design was experimentally tested and investigated using a self-resonant inverter model in a melting crucible induction laboratory furnace.
CCSDS 131.2-B-1 Transmitter Design on FPGA with Adaptive Coding and Modulation Schemes for Satellite Communications
Authors: Lamoral Coines Adrián , Jiménez Víctor P. Gil
Published: October 2021

Satellite communications are a well-established research area in which the main innovation of last decade has been the use of multi-carrier modulations and more robust channel coding techniques. However, in recent years, novel advanced signal processing has started being developed for these communications due to the increase in the signal processing capacity of transmitters and receivers. Although signal processing capabilities are increasing, they are still constrained by large limitations because these techniques need to be implemented in real hardware, thus making complexity a matter of critical importance. Therefore, this paper presents the design and implementation of a transmitter with adaptable coding and modulation on a field-programmable-gate-array (FPGA). The main motivation came from the standard CCSDS 131.2-B-1 which recommends that such a novel transmitter which has to date not been implemented in a real system The system was modeled by MATLAB with the purpose of being programmed in VHDL following the AXI-stream protocol between components. Behavioral simulation results were obtained in VIVADO and compared with MATLAB for verification purposes. The transmitter logical circuit was synthesized in a FPGA Zynq Ultrascale RFSoC ZU28DR, showing low resource consumption and correct functioning, leading us to conclude that the deployment of new communication systems in state-of-the-art hardware in satellite communications is justified.
Frequency Estimation for Grid-Tied Inverters Using Resonant Frequency Estimator
Authors: Zieliński Dariusz , Fatyga Karol
Published: October 2021

This paper introduces a new strategy of frequency estimation for grid-tied and stand-alone mode AC/DC power converters. Frequency stabilization is required, especially when operating in stand-alone mode with a Droop Control strategy, or in hybrid mode with a Diesel generator. It is also required to reduce or increase power output along with grid frequency changes. The novel strategy utilizes a resonant filter to estimate the frequency of the voltage grid and is referenced as a resonant-frequency-estimator (RFE). A mathematical background is presented for the proposed estimator and its performance is evaluated. It is compared with three common frequency estimation algorithms: SRF-FLL, DDSRF-FLL, and DSOGI-FLL. Results are presented for three cases: frequency swing, harmonics injection, and type B short-circuit. Results are analyzed and the conclusion shows that the proposed novel strategy has comparable parameters to commonly used frequency estimation algorithms while having a loopless structure.
Prediction and Early Detection of Karsts—An Overview of Methods and Technologies for Safer Drilling in Carbonates
Authors: Maksimov Danil , Pavlov Alexey , Sangesland Sigbjørn
Published: October 2021

The nature of carbonate deposition as well as diagenetic processes can cause the development of unique geological features such as cavities, vugs and fractures. These are called karsts. Encountering karsts while drilling can lead to serious consequences such as severe mud losses, drops of bottom hole assembly and gas kicks. To improve drilling safety in intervals of karstification, it is important to detect karsts as early as possible, preferably in advance. In this paper, we review methods and technologies that can be used for the prediction and early detection of karsts. In particular, we consider acoustic, resistivity, seismic and drilling-data methods. In addition to the inventions and technologies developed and published over the past 40 years, this paper identifies the advantages, limitations and gaps of these existing technologies and discusses the most promising methods for karst detection and prediction.
Multi-Mode Voltage Sag/Swell Generator Based on Three-Phase Inverter Circuit
Authors: Han Qiguo , Wang Xing , Hu Pengfei , Wang Maolin , Luo Xu , Hou Weihua
Published: October 2021

The voltage ride through capability of the major auxiliary variable-frequency drive (VFD) in large thermal power plants is the key technical issue of power grid and source coordination. In order to test the high voltage ride through (HVRT) and low voltage ride through (LVRT) capability of the auxiliary VFD, it is necessary to develop a power supply to simulate different grid voltage sag and swell accurately. In this paper, a generator (VSSG) based on the common three-phase inverter circuit that can simulate multi-mode voltage sag/swell is proposed. The designed main circuit consisting of transformer, rectifier, DC split capacitors, three-phase inverter, and LC-filter can generate single-phase and three-phase voltage sag, swell, and phase angle jumping flexibly. The developed control strategies composed of the double closed-loop control and the neutral voltage balance control achieve accurate output, fast dynamic response, and step-less adjustment. Simulation and experiment results verify the multi-mode voltage simulation performances of the proposed VSSG, which can be effectively used to emulate power grid voltage sag and swell phenomena under the IEEE 1159 and IEC standards.
Off-Grid Multi-Carrier Microgrid Design Optimisation: The Case of Rakiura–Stewart Island, Aotearoa–New Zealand
Authors: Mohseni Soheil , Brent Alan C. , Burmester Daniel
Published: October 2021

The establishment of the concept of sustainable, decentralised, multi-carrier energy systems, together with the declining costs of renewable energy technologies, has proposed changes in off-grid electrification interventions towards the development of integrated energy systems. Notwithstanding the potential benefits, the optimal capacity planning of such systems with multiple energy carriers—electricity, heating, cooling, hydrogen, biogas—is exceedingly complex due to the concurrent goals and interrelated constraints that must be relaxed. To this end, this paper puts forward an innovative new optimal capacity planning method for a first-of-its-kind stand-alone multiple energy carrier microgrid (MECM) serving the electricity, hot water, and transportation fuel demands of remote communities. The proposed off-grid MECM system is equipped with solar photovoltaic panels, wind turbines, a hydrogen-based energy storage system—including an electrolyser, a hydrogen reservoir, and a fuel cell—a hybrid super-capacitor/battery energy storage system, a hot water storage tank, a heat exchanger, an inline electric heater, a hydrogen refuelling station, and some power converters. The main objective of calculating the optimal size of the conceptualised isolated MECM’s components through minimising the associated lifetime costs is fulfilled by a specifically developed meta-heuristic-based solution algorithm subject to a set of operational and planning constraints. To evaluate the utility and effectiveness of the proposed method, as well as the technical feasibility and economic viability of the suggested grid-independent MECM layout, a numerical case study was carried out for Rakiura–Stewart Island, Aotearoa–New Zealand. Notably, the numeric simulation results highlight that the optimal solution presents a low-risk, high-yield investment opportunity, which is able to save the diesel-dependent community a significant 54% in electricity costs (including electrified space heating)—if financed as a community renewable energy project—apart from providing a cost-effective and resilient platform to serve the hot water and transportation fuel needs.
Assessment of a Nurse Led Energy Behavior Change Intervention in an NHS Community Hospital Ward
Authors: Sawyer Louise , Kemp Simon , James Patrick , Harper Michael
Published: October 2021

This paper investigates a nurse led, energy conservation behavioral intervention, in hospital wards of an NHS (National Health Service) community hospital (Trust). The information based intervention was adapted from “Operation TLC”, developed by environmental behavioral change charity Global Action Plan, and St Bartholomew’s Health NHS Trust, London. For this study, three identical older persons’ acute-care wards in terms of patient type, nursing levels, layout, electrical fittings (lighting & small power), elevation and orientation (one control ward and two intervention wards) were evaluated over a nine-month period. The paper demonstrates a co-dependent relationship between the quantitative data from the electricity and light monitors on the wards with the qualitative data gathered from staff comfort surveys and focus groups, and Trust policies. Our results show a 13% reduction in electricity consumption, primarily from preventing nursing staff in the intervention group from using prohibited secondary space heaters at night during the heating season and the introduction of a “quiet time” in the intervention group. During quiet time lights in the intervention group were turned off for an hour after lunch to encourage rest for patients to provide time for nursing staff to complete administrative tasks. Electricity reductions achieved during the intervention period were observed to continue into the 3-month post intervention period but at a reduced level.
An Energy Management System of Campus Microgrids: State-of-the-Art and Future Challenges
Authors: Muqeet Hafiz Abdul , Munir Hafiz Mudassir , Javed Haseeb , Shahzad Muhammad , Jamil Mohsin , Guerrero Josep M.
Published: October 2021

The multiple uncertainties in a microgrid, such as limited photovoltaic generations, ups and downs in the market price, and controlling different loads, are challenging points in managing campus energy with multiple microgrid systems and are a hot topic of research in the current era. Microgrids deployed at multiple campuses can be successfully operated with an exemplary energy management system (EMS) to address these challenges, offering several solutions to minimize the greenhouse gas (GHG) emissions, maintenance costs, and peak load demands of the microgrid infrastructure. This literature survey presents a comparative analysis of multiple campus microgrids’ energy management at different universities in different locations, and it also studies different approaches to managing their peak demand and achieving the maximum output power for campus microgrids. In this paper, the analysis is also focused on managing and addressing the uncertain nature of renewable energies, considering the storage technologies implemented on various campuses. A comparative analysis was also considered for the energy management of campus microgrids, which were investigated with multiple optimization techniques, simulation tools, and different types of energy storage technologies. Finally, the challenges for future research are highlighted, considering campus microgrids’ importance globally. Moreover, this paper is expected to open innovative paths in the future for new researchers working in the domain of campus microgrids.
A Multi-Stage Fault Diagnosis Method for Proton Exchange Membrane Fuel Cell Based on Support Vector Machine with Binary Tree
Authors: Xie Jiaping , Wang Chao , Zhu Wei , Yuan Hao
Published: October 2021

The reliability and durability of the proton exchange membrane (PEM) fuel cells are vital factors restricting their applications. Therefore, establishing an online fault diagnosis system is of great significance. In this paper, a multi-stage fault diagnosis method for the PEM fuel cell is proposed. First, the tests of electrochemical impedance spectroscopy under various fault conditions are conducted. Specifically, prone recoverable faults, such as flooding, membrane drying, and air starvation, are included, and different fault degrees from minor, moderate to severe, are covered. Based on this, an equivalent circuit model (ECM) is selected to fit impedance spectroscopy by the hybrid genetic particle swarm optimization algorithm, and then fault features are determined by the analysis of each model parameter under different fault conditions. Furthermore, a multi-stage fault diagnosis model is constructed with the support vector machine with the binary tree, in which fault features obtained from the ECM are used as the characteristic inputs to realize the fault classification (including fault type and fault degree) online. The results show that the accuracy of the basic fault test and subdivided fault test can reach 100% and 98.3%, respectively, which indicates that the proposed diagnosis method can effectively identify flooding, drying, and air starvation of PEM fuel cells.
Base Oil Process Modelling Using Machine Learning
Authors: Fadzil Muhamad Amir Mohd , Zabiri Haslinda , Razali Adi Aizat , Basar Jamali , Syamzari Rafeen Mohammad
Published: October 2021

The quality of feedstock used in base oil processing depends on the source of the crude oil. Moreover, the refinery is fed with various blends of crude oil to meet the demand of the refining products. These circumstances have caused changes of quality of the feedstock for the base oil production. Often the feedstock properties deviate from the original properties measured during the process design phase. To recalculate and remodel using first principal approaches requires significant costs due to the detailed material characterizations and several pilot-plant runs requirements. To perform all material characterization and pilot plant runs every time the refinery receives a different blend of crude oil will simply multiply the costs. Due to economic reasons, only selected lab characterizations are performed, and the base oil processing plant is operated reactively based on the feedback of the lab analysis of the base oil product. However, this reactive method leads to loss in production for several hours because of the residence time as well as time required to perform the lab analysis. Hence in this paper, an alternative method is studied to minimize the production loss by reacting proactively utilizing machine learning algorithms. Support Vector Regression (SVR), Decision Tree Regression (DTR), Random Forest Regression (RFR) and Extreme Gradient Boosting (XGBoost) models are developed and studied using historical data of the plant to predict the base oil product kinematic viscosity and viscosity index based on the feedstock qualities and the process operating conditions. The XGBoost model shows the most optimal and consistent performance during validation and a 6.5 months plant testing period. Subsequent deployment at our plant facility and product recovery analysis have shown that the prediction model has facilitated in reducing the production recovery period during product transition by 40%.
Controller Design for Three-Axis Stabilized Platform Using Adaptive Global Fast Terminal Sliding Mode Control with Non-Linear Differentiator
Authors: Feng Wenlong , Zhang Xiangyin
Published: October 2021

A neural network-based global fast terminal sliding mode control method with non-linear differentiator (NNFTSMC) is proposed in this paper to design the dynamic control system for three-axis stabilized platform. The dynamic model of the three-axis stabilized platform is established with various uncertainties and unknown external disturbances. To overcome the external disturbance and reduce the output chatter of the classical sliding mode control (SMC) system, the improved global fast terminal sliding mode control method using the nonlinear differentiator and neural network techniques is proposed and implemented in the three-axis stabilized platform system. The global fast terminal sliding mode controller can make the controlled state approach to the sliding surface in a finite time. To eliminate the system output chatter, the nonlinear differentiator is employed to obtain the differentiation of the signal. The neural network is introduced to estimate the uncertainties disturbances to improve the stability and the robustness of the control system. The stability and the robustness of the proposed control method are analyzed using the Lyapunov theory. The performance of the proposed NNFTSMC method is verified and compared with the classical proportion-integral-differential (PID) controller, SMC controller and fast terminal sliding mode controller (FTSMC) through the computer simulation. Results validate the effectiveness and robustness of the proposed NNFTSMC method in presence of uncertainties and unknown external disturbances.
Analysis of Safety Requirements for Securing the Semi-Trailer Truck on the Intermodal Railway Wagon
Authors: Opala Michał
Published: October 2021

The article presented the issue of securing semi-trailer trucks and trailers during their transport using intermodal railway wagons as a part of combined transport. This issue was analysed in different operational conditions related to loading level, cross-winds influence, inertia forces due to the emergency braking, and track curvature. According to general rules of loading and securing cargo, described in the internal and UIC regulations, the transported load should be positioned and secured with minimised risk of undesirable displacement or rolling over during transport. Basic analysis showed that adverse conditions such as strong winds or emergency braking may require adequate additional cargo protection. The lack thereof may result in a severe accident or damage to the transported vehicle or the nearby structures. The presented results for generic road and railway freight vehicles showed that the required anti-rollover torque for a semi-trailer mounted on the railway wagon platform may differ considerably (almost four times at the same maximum tested airflow speed) depending on the conditions related to aerodynamic and inertia influence. The potential weaknesses of the analysis relate to the impracticality of experimental tests for roll-over (or derailment) events under high levels of cross-wind, due to economic and safety reasons. The analysis can be extended in the future by including unsteady aerodynamic forces and a full-vehicle model based on the multi-body method for a specific design solution.
Investigation of Thermoplastic Polyurethane Finger Cushion with Magnetorheological Fluid for Soft-Rigid Gripper
Authors: Białek Marcin , Jędryczka Cezary , Milecki Andrzej
Published: October 2021

This paper presents a study of penetrating a pin into a magnetorheological fluid (MR) cushion focused on the force measurement. The research is supported by detailed finite element analysis (FEA) of the magnetic field distributions in several magnetic field exciters applied to control rheological properties of the MR inside the cushion. The cushion is a part of the finger pad of the jaw soft-rigid gripper and was made of thermoplastic polyurethane (TPU) using 3D printing technology. For the pin-penetrating setup, the use of a holding electromagnet and a magnetic holder were considered and verified by simulation as well as experiment. In further simulation studies, two design solutions using permanent magnets as the source of the magnetic field in the cushion volume to control MR fluid viscosity were considered. The primary aim of the study was to analyze the potential of using an MR fluid in a cushion pad and to investigate the potential for changing its viscosity using different magnetic field sources. The analysis included magnetic field simulations and tests of pin penetration in the cushion as an imitation of object grasping. Thus, an innovative application of 3D printing and TPU to work with MR fluid is proposed.
Mill Scale Addition to Reduce Hydrogen Sulfide Production in Anaerobic Digestion
Authors: Ahn Byung-Kyu , Kim Tae-Hoon , Seon Jiyun , Park Seung-Kyun , Yun Yeo-Myeong
Published: October 2021

Direct addition of sulfur-reducing agents during anaerobic digestion (AD) is very effective in controlling hydrogen sulfide (H2S) content in biogas, although one major problem is the high operational cost due to the large amount of chemicals used. The objective of this study was to remove H2S using a waste mill scale (MS) as a sulfur-reducing agent. To evaluate its feasibility, MS was added to AD fed with food waste (FW) at concentrations between 0 and 160 g MS/kg total chemical oxygen demand (TCOD) during the batch test, and the experimental results were compared to those of the batch test with the addition of iron chloride (FeCl3). Both FeCl3 and MS played an important role as electro-conductive materials in improving methane productivity by promoting direct interspecies electron transfer. An increase in H2S removal efficiency was observed with increases in both materials. In total, 30%, 60%, and 90% of H2S production based on the maximum sulfur in the form of H2S (control) was 3.7, 9.4, and 23.8 g FeCl3/kg TCOD and 13.3, 34.1, and 86.2 g MS/kg TCOD, respectively. This finding indicates that MS can be used as a sulfur-reducing agent substitute for H2S removal in AD fed with FW.
Measurement and Analysis of Infrasound Signals Generated by Operation of High-Power Wind Turbines
Authors: Malec Tomasz , Boczar Tomasz , Wotzka Daria , Kozioł Michał
Published: October 2021

The development of wind energy and the increasing number of installed wind turbines make it necessary to assess them in terms of the nuisance of the emitted infrasound noise generated by such devices. The article presents the results of measurements and analyses of infrasound emitted during the operation of wind turbines installed in various locations in Poland. Comparative analysis of noise levels in the infrasound and audible range has shown that acoustic energy is mainly in the low and infrasound frequency range, and the measured levels depend significantly on the weighting curves used. On the basis of the results, it was confirmed that the sound pressure level of infrasound signals emitted by the operation of high-power wind turbines, regardless of wind velocity, weather conditions, design solutions of turbines, operating time, rated capacity, does not exceed the criteria specified in the applicable legislation dealing with the assessment of infrasound noise on the working environment.