bluuebunny/crossref_metadata_2025 huggingface dataset:
Dimensionality Reduction and Classification of Hyperspectral Remote Sensing Image Feature Extraction
Authors: Li Hongda , Cui Jian , Zhang Xinle , Han Yongqi , Cao Liying
Published: September 2022

Terrain classification is an important research direction in the field of remote sensing. Hyperspectral remote sensing image data contain a large amount of rich ground object information. However, such data have the characteristics of high spatial dimensions of features, strong data correlation, high data redundancy, and long operation time, which lead to difficulty in image data classification. A data dimensionality reduction algorithm can transform the data into low-dimensional data with strong features and then classify the dimensionally reduced data. However, most classification methods cannot effectively extract dimensionality-reduced data features. In this paper, different dimensionality reduction and machine learning supervised classification algorithms are explored to determine a suitable combination method of dimensionality reduction and classification for hyperspectral images. Soft and hard classification methods are adopted to achieve the classification of pixels according to diversity. The results show that the data after dimensionality reduction retain the data features with high overall feature correlation, and the data dimension is drastically reduced. The dimensionality reduction method of unified manifold approximation and projection and the classification method of support vector machine achieve the best terrain classification with 99.57% classification accuracy. High-precision fitting of neural networks for soft classification of hyperspectral images with a model fitting correlation coefficient (R2) of up to 0.979 solves the problem of mixed pixel decomposition.
Towards Robustifying Image Classifiers against the Perils of Adversarial Attacks on Artificial Intelligence Systems
Authors: Anastasiou Theodora , Karagiorgou Sophia , Petrou Petros , Papamartzivanos Dimitrios , Giannetsos Thanassis , Tsirigotaki Georgia , Keizer Jelle
Published: September 2022

Adversarial machine learning (AML) is a class of data manipulation techniques that cause alterations in the behavior of artificial intelligence (AI) systems while going unnoticed by humans. These alterations can cause serious vulnerabilities to mission-critical AI-enabled applications. This work introduces an AI architecture augmented with adversarial examples and defense algorithms to safeguard, secure, and make more reliable AI systems. This can be conducted by robustifying deep neural network (DNN) classifiers and explicitly focusing on the specific case of convolutional neural networks (CNNs) used in non-trivial manufacturing environments prone to noise, vibrations, and errors when capturing and transferring data. The proposed architecture enables the imitation of the interplay between the attacker and a defender based on the deployment and cross-evaluation of adversarial and defense strategies. The AI architecture enables (i) the creation and usage of adversarial examples in the training process, which robustify the accuracy of CNNs, (ii) the evaluation of defense algorithms to recover the classifiers’ accuracy, and (iii) the provision of a multiclass discriminator to distinguish and report on non-attacked and attacked data. The experimental results show promising results in a hybrid solution combining the defense algorithms and the multiclass discriminator in an effort to revitalize the attacked base models and robustify the DNN classifiers. The proposed architecture is ratified in the context of a real manufacturing environment utilizing datasets stemming from the actual production lines.
Learning Observer-Based Sensor Fault-Tolerant Control of Distributed Generation in an Islanded Microgrid for Bus Voltage Stability Enhancement
Authors: Mao Jingfeng , Yin Chunyun , Zhang Xiaotong , Wu Aihua , Zhang Xudong
Published: September 2022

In order to improve robust operating performance and enhance bus voltage stability, a learning observer-based fault-tolerant control strategy is proposed for the distributed generation in islanded microgrid with sensor faults and uncertain disturbances. Firstly, the output feedback control theory and the linear matrix inequality method are used to design closed-loop controller for the voltage source inverter of distributed generation; secondly, a fault-tolerant model and control structure of the distributed generation in an islanded microgrid with sensor faults is analyzed. By employing the fault output signal conversion filter and proportional derivative type learning observer, the online estimation and real-time compensation of the sensor fault signal are realized. Thirdly, the system synthesis of output feedback control and fault-tolerant control is completed. Finally, the multi-scenario sensor fault scheme simulation experiment verifies that the proposed control strategy has strong sensor fault tolerance and adaptability.
Analysis of a Clapping Vibration Energy Harvesting System in a Rotating Magnetic Field
Authors: Wang Yi-Ren , Feng Chao-Kang , Cheng Chin-Han , Chen Pin-Tung
Published: September 2022

This technical note proposes a clapping vibration energy harvesting system (CVEH system) installed in a rotating system. This device includes a rotating wheel, a drive shaft that rotates the wheel, and a double elastic steel sheet fixed on the drive shaft. One of the free ends of the steel is fixed with a magnet, and the free end of the other elastic steel is fixed with a PZT patch. We also install an array of magnets on the periphery (rim) of the wheel. The rim magnets repulse the magnet on the elastic steel sheet of the transmission shaft, causing the elastic steel to oscillate periodically, and slap the piezoelectric patch installed on the other elastic steel sheet to generate electricity. In this study, the authors’ previous study on the voltage output was improved, and the accurate nonlinear natural frequency of the elastic steel was obtained by the dimensional analysis method. By adjusting the rotation speed of the wheel, the precise frequency was controlled to accurately excite the energy harvesting system and obtain the best output voltage. A simple experiment was also performed to correlate with the theoretical model. The voltage and power output efficiencies of the nonlinear frequency to linear frequency excitation of the CVEH system can reach 15.7% and 33.5%, respectively. This study confirms that the clapping VEH system has practical power generation benefits, and verifies that nonlinear frequencies are more effective than linear frequencies to excite the CVEH system to generate electricity.
User Based Development and Test of the EXOTIC Exoskeleton: Empowering Individuals with Tetraplegia Using a Compact, Versatile, 5-DoF Upper Limb Exoskeleton Controlled through Intelligent Semi-Automated Shared Tongue Control
Authors: Thøgersen Mikkel Berg , Mohammadi Mostafa , Gull Muhammad Ahsan , Bengtson Stefan Hein , Kobbelgaard Frederik Victor , Bentsen Bo , Khan Benjamin Yamin Ali , Severinsen Kåre Eg , Bai Shaoping , Bak Thomas , Moeslund Thomas Baltzer , Kanstrup Anne Marie , Andreasen Struijk Lotte N. S.
Published: September 2022

This paper presents the EXOTIC- a novel assistive upper limb exoskeleton for individuals with complete functional tetraplegia that provides an unprecedented level of versatility and control. The current literature on exoskeletons mainly focuses on the basic technical aspects of exoskeleton design and control while the context in which these exoskeletons should function is less or not prioritized even though it poses important technical requirements. We considered all sources of design requirements, from the basic technical functions to the real-world practical application. The EXOTIC features: (1) a compact, safe, wheelchair-mountable, easy to don and doff exoskeleton capable of facilitating multiple highly desired activities of daily living for individuals with tetraplegia; (2) a semi-automated computer vision guidance system that can be enabled by the user when relevant; (3) a tongue control interface allowing for full, volitional, and continuous control over all possible motions of the exoskeleton. The EXOTIC was tested on ten able-bodied individuals and three users with tetraplegia caused by spinal cord injury. During the tests the EXOTIC succeeded in fully assisting tasks such as drinking and picking up snacks, even for users with complete functional tetraplegia and the need for a ventilator. The users confirmed the usability of the EXOTIC.
FASTNN: A Deep Learning Approach for Traffic Flow Prediction Considering Spatiotemporal Features
Authors: Zhou Qianqian , Chen Nan , Lin Siwei
Published: September 2022

Traffic flow forecasting is a critical input to intelligent transportation systems. Accurate traffic flow forecasting can provide an effective reference for implementing traffic management strategies, developing travel route planning, and public transportation risk assessment. Recent deep learning approaches of spatiotemporal neural networks to predict traffic flow show promise, but could be difficult to separately model the spatiotemporal aggregation in traffic data and intrinsic correlation or redundancy of spatiotemporal features extracted by the filter of the convolutional network. This can introduce biases in the predictions that interfere with subsequent planning decisions in transportation. To solve the mentioned problem, the filter attention-based spatiotemporal neural network (FASTNN) was proposed in this paper. First, the model used 3-dimensional convolutional neural networks to extract universal spatiotemporal dependencies from three types of historical traffic flow, the residual units were employed to prevent network degradation. Then, the filter spatial attention module was constructed to quantify the spatiotemporal aggregation of the features, thus enabling dynamic adjustment of the spatial weights. To model the intrinsic correlation and redundancy of features, this paper also constructed a lightweight module, named matrix factorization based resample module, which automatically learned the intrinsic correlation of the same features to enhance the concentration of the model on information-rich features, and used matrix factorization to reduce the redundant information between different features. The FASTNN has experimented on two large-scale real datasets (TaxiBJ and BikeNYC), and the experimental results show that the FASTNN has better prediction performance than various baselines and variant models.
PINE: Post-Quantum Based Incentive Technique for Non-Cooperating Nodes in Internet of Everything
Authors: Balaji Ashwin , Dhurandher Sanjay Kumar , Woungang Isaac
Published: September 2022

The Internet of Everything (IoE) is a smart system that interconnects smart entities by incorporating low-cost or low-energy gadgets that are useful for communication with people, processes, data, and devices/things. In such an instantaneously connected environment, network-enabled heterogeneous devices may exhibit non-cooperative behaviour which may lead to the degradation of the network. To address this performance degradation, the proposed Post-quantum based Incentive technique for Non-cooperating nodes in internet of Everything (PINE) protocol provides an end-to-end reliable solution by incorporating location-aware post-quantum encryption in these networks while addressing the non-cooperative behaviour of the nodes by employing an effective strategy in a bi-directional multi-hop relay environment. This proposed protocol further aims to evaluate the consequences of non-cooperative nodes by considering various metrics, namely, number of nodes, message size, execution time, memory consumption, average residual energy, percentage of selfish nodes, and blackhole nodes detection, aiming to achieve significant accuracy in an IoE environment.
Recovery of Valuable Metals from Cathode—Anode Mixed Materials of Spent Lithium-Ion Batteries Using Organic Acids
Authors: Wang Kun , Zhang Guoquan , Luo Mingzhi
Published: September 2022

Spent lithium-ion batteries (LIBs) contain a large number of valuable metals and will be an important strategic resource in the future. Therefore, recycling is extremely important. In this work, acetic acid and hydrogen peroxide were used as leaching agents to recover valuable metals (lithium, cobalt, nickel, manganese, and aluminum) from cathode and anode materials (LiCoO2, LiAl0.2Co0.8O2, and C) of spent LIBs. The leaching solution and leaching residue were analyzed by inductive plasma optical emission spectrometry (ICP-OES), scanning electron microscopy (SEM), and X-ray diffraction (XRD). The optimum experimental conditions were obtained by changing the concentration of acetic acid, solid–liquid ratio, reaction temperature, time, and the concentration of hydrogen peroxide reducing agent. Under the experimental conditions of 2 M acetic acid, 4.0 vol.% H2O2, 20 g/L, and 70 °C for 40 min, the leaching rates of lithium, cobalt, nickel, manganese, and aluminum reached 98.56%, 94.61%, 96.39%, 97.97%, and 94.7%, respectively. This hydrometallurgical process is simple and environmentally friendly and maximizes the recovery of valuable metals from spent LIBs.
Editorial: Sustainable Municipal Solid Waste Management: A Local Issue with Global Impacts
Authors: Abu-Qdais Hani A. , Kurbatova Anna I.
Published: September 2022

On a global level, communities are generating and disposing of increasing quantities of solid waste [...]
Risk Assessment of Water Inrush in Tunnels: A Case Study of a Tunnel in Guangdong Province, China
Authors: Zhang Weifeng , Zhou Xuemin , Wei Wei , Cheng Xiaoyong
Published: September 2022

Fractured tectonic zones with developed groundwater are one of the major causes of water inrush in the construction of igneous tunnels; thus, it is highly important to assess the risk of water inrush. In this study, a total of six evaluation attributes, groundwater level, amount of inrush water, permeability coefficient, strength of the surrounding rock, rock integrity, and width of the jointed and fault fracture zone, were selected for the risk assessment of water inrush, and fuzzy theory was applied to the treatment of the uncertainty in the evaluation attributes. On this basis, the MULTIMOORA (multiple multi-objective optimization by ration analysis) and the model of nearness degree of incidence were combined to obtain the new model of MULTIMOORA–nearness degree of incidence for the risk assessment of water inrush. A deep-underground, extra-long tunnel under construction in southern China was used as an example for validation. The six tunnel sections assessed on site were ZK91 + 195~236, K91 + 169~186.5, K91 + 203~238, ZK94 + 238~198, K94 + 112~82, and K94 + 076~034. K94 + 112~82 was assessed at risk Level III, while the remainder were assessed at risk Level IV. The site conditions were also Level III for section K94 + 112~82 and Level IV for the remainder. The assessment results for the above six tunnel sections are consistent with the field conditions, which verified the validity of the model of the MULTIMOORA–nearness degree of incidence.
Study on the Microstructure Evolution and Strength Damage Mechanism of Dolomite under Dissolution Condition
Authors: Liu Wenlian , Liu Pengen , Xu Hanhua , Gong Bocheng , Ji Feng
Published: September 2022

Dolomite is a common type of natural soluble rock. The strength of rock decreases under the action of corrosion, which has a significant impact on the self-stability and long-term safety of the tunnel surrounding the rock. To reveal the microscopic structure evolution and strength-damage law of carbonate rock caused by chemical corrosion, a series of tests such as rock chemical corrosion test, rock uniaxial compression test and electron microscope scanning test are conducted at different pH values on the dolomite of the Doushantuo Formation. The rock dissolution at different pH values exhibits four typical stages: the initial dissolution stage, secondary dissolution acceleration stage, stable dissolution rate stage and dissolution attenuation stage. During the dissolution process, the initial dissolution rate is 25.91 times that of the stable stage, and the maximum strength attenuation is 76.2% after 21 days of dissolution. For macroscopic failure, the rock is developed from 1 to 2 external fractures to multiple internal and external fractures and penetrated, and the specimen transforms from brittle to flexible. For microstructure, the sample exhibits corrosion characteristics along the joint surface, intensified corrosion at the edge, etc. The porosity increase rate is 0.6%/d; however, the length–width ratio of the pores is maintained at 1.7–1.85, indicating that the development rate of pores in different directions is similar. The results of this study have enriched the study of the dolomite dissolution mechanism and, in addition, have important reference value for the stability evaluation of tunnel surrounding rock in karst environments.
Energy-Saving Manufacturing System Design with Two Geometric Machines
Authors: Yang Peiqi , Pei Zhi
Published: September 2022

In recent years, due to increasing energy costs and deteriorating environmental conditions, manufacturing enterprises have become more concerned with energy efficiency. This paper is dedicated to minimizing energy consumption while maintaining the target productivity of a two-machine geometric serial line. To address this problem, we propose a nonlinear model under productivity constraints, where the system energy consumption consists of three components, namely, the setup, the idle, and the normal working energy consumption. By analyzing the properties of the energy consumption function, a new heuristic method, i.e., the energy consumption minimization (ECM) algorithm, is proposed to obtain the optimal solution. In addition, we extend the formulation to further investigate the energy saving problem with varied buffer capacities and propose an energy-saving (ES) algorithm to solve it based on the problem structure. Furthermore, the effectiveness of the algorithms is verified by designing numerical examples, and the effects of energy consumption parameters, buffer capacity, target productivity, and breakdown probabilities on the total energy consumption and optimal solution are presented.
Review on Tunnel Communication Technology
Authors: Zhu Jianguo , Dong Yanyan , Zhang Jiancheng , Guo Feng , Lu Quanli , Lv Bin , Wu Jianqing
Published: September 2022

Tunnels account for an increasing proportion of highways. Due to the semi-closed structure of tunnels, signal communication is difficult in tunnels. This review analyzes the signal data transmission requirements of intelligent network management systems, such as lighting systems, wind protection systems, fire protection systems, and vehicle and pedestrian positioning systems in tunnels. The selection of signal coverage and transmission methods are also discussed. The advantages and disadvantages of various networking methods are analyzed. This paper summarizes the wireless signal transmission, wired signal transmission and signal transmission modes of different tunnel types.
A Comprehensive Metagenomic Analysis Framework Revealing Microbiome Profile and Potential for Hydrocarbon Degradation and Carbohydrate Metabolism in a Himalayan Artificial Lake
Authors: Kaushal Girija , Thakur Monika , Rai Amit Kumar , Singh Sudhir P.
Published: September 2022

The high-altitude lakes are ecological habitats accommodating a vast diversity of microbial populations. These microbes are efficient sources for a variety of enzymes. The objective of this study is to perform in-depth metagenomic profiling of an artificial lake ecosystem located in the Sikkim Himalayan region, deciphering the hydrocarbon degradation potential of this site and mining biocatalysts of industrial importance. In the present study, metagenomic analysis of an artificial Himalayan lake, located in North Sikkim, India, was performed. A comprehensive taxonomic and functional profiling revealed gene mapped to pathways for degradation of hydrocarbons such as toluene, benzoate, ethylbenzene, etc. This site was rich in iron, and the metagenomic investigation revealed genomic signatures of the iron-reducing bacterium; Geothrix fermentans. The appraisal of the carbohydrate metabolic potential of this site divulged the predominance of β-galactosidase genes. The artificial lake metagenome was further compared to publicly available saline and freshwater lakes. At the taxonomic, as well as functional levels, it was found to be closer to freshwater lake metagenome, e.g., Medonta Lake, US, and freshwater Vanda Lake, Antarctica. The microbial community profiling and functional contribution of the artificial Himalayan lake would be beneficial for mining genes encoding various industrially relevant enzymes.
Measuring the Psychological Behavior of Tourism Service Providers in Low-Income Regions: Implementing Effective Service Marketing and Performances Strategies
Authors: Xu Shaochen , Zhou Xiaofei , Ahmad Zeeshan
Published: September 2022

An effective marketing strategy is a critical contribution in any business including the tourism sector. Understanding marketing strategies increases business performance. The purpose of this study is to determine how service marketing strategies impact small town tourism business owners. Using an econometric model, the implementation of the 4P mixed strategy on the profitability and potential of service providers in Molise is investigated. Revenue, cost, and profit are the three areas analyzed. Results showed that service operators have to place emphasis on research and development, reflecting cultural identities and the adoption of modern media. Operators should emphasize marketing and sales promotions through websites and social media. Creating a quality brand and setting reasonable prices without exploiting consumers are essential strategies. In conclusion, strategies that emphasize knowledge management and team building should be put into practice. This study could help tourism businesses in small regions to be more sustainable. It is the first research study where Stan Shih’s innovation smiling curve has been used in an Italian region.
The Impact of the COVID-19 Pandemic on Retail in City Centres
Authors: Lashgari Yasaman S. , Shahab Sina
Published: September 2022

Over the past few decades, city centres and their retail spaces have undergone significant changes and have struggled to remain economically viable. The COVID-19 pandemic and the public health response to the crisis have exacerbated this situation and posed a serious challenge to the already economically struggling city centres. Recommendations for how city centres should respond to the current crisis are urgently needed, but despite this, few studies have focused on the impact of COVID-19 on retailing in city centres. This paper conducts a systematic review to provide a better understanding of how retail in city centres has been affected by the pandemic. It also offers insights to support better decision making about the future of retailing in city centres and provides recommendations for ensuring a sustainable future for city centres. The review, conducted between the 20th of November 2021 and the 20th of January 2022, shows that the COVID-19 pandemic and subsequent public health response have intensified some considerable changes in customer preferences and the role of city centres. As a result of these changes, more retailers have adopted multichannel retailing and repositioning strategies. This paper concludes that in order to create vibrant and sustainable city centres post-pandemic, decision makers should support the repurposing of vacant and underperforming retail spaces, promote an experience economy, and create episodic retail spaces.
Economic Planning of Energy System Equipment
Authors: Li Biao , Wang Tao , Dong Zhen , Geng Qian , Sun Yi
Published: September 2022

The asset wall (AW) model is widely used by energy companies to forecast the retirement size of equipment. The AW model is a method of arranging historical data in chronological order and then using extrapolation to predict trends in asset size volumes over time. However, most studies using the AW model treat all equipment as a whole and perform a flat extrapolation mechanically, ignoring the impact of technological improvements and price fluctuations. Furthermore, there are relatively few studies on the assetization of equipment replacement scale. This paper fits a Weibull distribution density function and uses Monte Carlo stochastic simulation to determine the retirement age of each piece of equipment, reducing the ambiguity and randomness generated by the AW approach of treating all equipment as a whole. This modified model is noted in this paper as the Weibull–Monte Carlo stochastic simulation asset model wall (WMCAW). The paper then investigated the assetization of equipment replacement size, comparing the three error indicators Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Root Mean Square Error (RMSE) in order to select the appropriate optimization model for price forecasting from several combinations of models. Finally, the paper verified the feasibility of the WMCAW model using various types of equipment decommissioned in 1970 and compared the forecasting effects of AW and WMCAW. It is found that the curve of the equipment replacement scale predicted by WMCAW is smoother than that of AW, and the forecasting results are more stable and scientific.
Precision Ventilation for an Open-Plan Office: A Study of Variable Jet Interaction between Two Active Chilled Beams
Authors: Latif Haider , Rahnama Samira , Maccarini Alessandro , Bradshaw Craig R. , Hultmark Goran , Nielsen Peter V. , Afshari Alireza
Published: September 2022

Precision ventilation is developed to achieve thermal comfort for occupants in an office by creating micro-climate zones. The present study aims to achieve individual thermal comfort for occupants with different metabolic rates by using higher airspeeds for enhancing heat transfer. The variable jet interaction between two ACBs with JetCone adjustments cause higher velocity jets to reach different regions of the occupied zone. The colliding jets from the center of a thermal isolated room were moved towards different zones in an office configuration with a constant room temperature of 23 °C. This study was conducted for five different cases in a room divided into four zones according to occupants’ metabolic rates. The experimental and CFD results show that occupants facing symmetrical airflow distribution and with a constant 1.2 metabolic rate (Case 1) had a similar predicted mean vote (PMV) index. The zones with higher-metabolic-rate occupants, i.e., 1.4 met and 1.6 met in cases 2 and 3 were exposed to air velocities up to 0.4 and 0.5 m/s, respectively. In case 4, the air velocity in the single zone with 1.6 met occupants was raised to 0.6 m/s by targeted airflow distribution achieved by adjusting JetCones. These occupants with higher metabolic rates were kept thermally neutral, in the −0.5 to +0.5 PMV range, by pushing the high velocity colliding jets from the center towards them. In case 5, the results showed that precision ventilation can maintain the individual thermal comfort of up to three different zones (in the same office space) by exposing the occupants with metabolic rates of 1.2, 1.4, and 1.6 met to airspeeds of 0.15, 0.45, and 0.55 m/s, respectively.
Smart Trams: A Design Proposal for a City of Interrelation
Authors: Bruno Davide Maria , Musante Guido , Dacarro Fabio
Published: September 2022

This paper illustrates a case study and the research hypothesis of a project elaborated by the authors for the city of Gwangmyeong in South Korea. The project, which has been developed as a design concept, consists of an innovative public transportation system that aims to favor social integration between parts of the city that might be potentially segregated from each other. Gwangmyeong’s plan fits into the debate on the Broken World, a social and economic condition recognized by many authors as a crucial problem of contemporary society. In this project, the means of transport, along with moving passengers and goods (in addition to waste), also host itinerant collective functions (school, work, etc.) spread in a capillary manner throughout the urban territory. The infrastructure is intended to serve as a social connective tissue of the different city districts. Although conceived in an Eastern context, the design concept is proposed to serve as a model for any new or existing environments in which greater integration is deemed necessary in favor of socially sustainable living conditions.
Research on Closed-Loop Supply Chain Decision Making and Recycling Channel Selection under Carbon Allowance and Carbon Trading
Authors: Lv Yang , Bi Xinhua , Li Quanxi , Zhang Haowei
Published: September 2022

The massive emission of carbon dioxide and other greenhouse gases has begun to threaten the survival of human beings and the balance of the Earth’s ecology. If carbon emission is left unchecked, we will face terrible consequences. Closed-loop supply chain operation is an effective way to improve economic and environmental benefits at the same time. This paper attempts to study the decision-making and recycling channel selection of CLSC under carbon allowance and carbon trading policies. This paper constructs a closed-loop supply chain consisting of a manufacturer, a retailer and a third-party recycler, and uses the Stackelberg game-theoretic method to decide variables such as the product price and recycling rate of CLSC under three recycling models. Through the analysis and comparison of the manufacturer’s profit of and the carbon emissions in different models, the following conclusions are drawn. (1) When the manufacturer recycles WEEE, the supply chain obtains the most profit. (2) When the retailer recycles WEEE, the carbon emissions of the supply chain are lowest. (3) The manufacturer tends to choose the M model, which is the manufacturer recycling model. The T model and the R model have little difference in carbon emissions. For easier management, the government prefers to choose the T model, which is the third-party recycler recycling model.
Sources of Intellectual Capital Acquisition
Authors: Sierotowicz Tomasz
Published: September 2022

Research related to intellectual capital (IC) concerns its use and impact on the selected results achieved by enterprises. IC is analysed as a single stream of enterprises’ internal resources. Since IC is used in the business activities of enterprises, it must also be acquired. However, research conducted so far does not cover the area of IC acquisition. The purpose of this paper is to present the results of research undertaken in a relatively new area of IC acquisition that has not been scientifically explored over a research period of several years. The research covered innovative small and medium enterprises (SMEs) that were developing software in Poland from 2005 to 2019. The data series allowed the use of dedicated analysis tools, including the dynamic changes over time, multidimensional comparison and cluster analysis. The primary conclusions revealed that the acquisition of IC is a process that takes place simultaneously and continuously in two independent streams—internal and external—and that the external sources of IC were more important for SMEs covered by the research. Continued research will allow comparative analyses between various branches or sectors of the economy to bring new knowledge about the importance of IC to the business activities of enterprises.
Are We Adapting to Climate Change? Evidence from the High-Quality Agri-Food Sector in the Veneto Region
Authors: Salpina Dana , Pagliacci Francesco
Published: September 2022

Adaptation to climate change is an issue of growing concern for the agri-food sector, particularly for Geographic Indications (GIs). Agri-food GIs are deeply grounded on the concept of terroir, whose key aspects can be altered by climate change. In this context, understanding whether and how agents involved in agri-food GIs production are adapting to climate change is a crucial issue, together with pointing out the role played by either economic incentives or subsidies in the implementation of adaptation measures. To answer these questions, this research focuses on the case of the agri-food sector of the Veneto Region. First, a subsample of agri-food GIs is identified. Second, a mixed-methods approach is implemented, including 14 semi-structured in-depth interviews with key informants and two focus group discussions to analyze the effects related to climate change and the implementation of adaptation measures. Different levels of concern regarding the effects of climate change are observed. Similarly, the implementation of adaptation measures largely varies in relation to the type of GI (e.g., animal-based or crop-based), crop system (annual or permanent crops) and altitude of the production areas (e.g., mountains or plain). Additionally, several groups of barriers to adaptation are outlined, including behavioral, socioeconomic, policy- and governance-related, informative and structural ones. Several recommendations are suggested: de jure recognition of the current functions of some Consortia and Producers Organizations, scaling up adaptation strategies beyond the GI system through cooperation and institutionalized networks and developing knowledge provision systems based on participatory approaches.
In the COVID-19 Era, When and Where Will You Travel Abroad? Prediction through Application of PPM Model
Authors: Kim Jeong-Joon , Lee Byeong-Cheol , Byun Hyo-Jeong
Published: September 2022

This study aimed to derive tourism motives and constraint factors that have changed or are newly applicable after COVID-19, and to identify the influencing relationships between these factors and complex aspects of tourism behavior intentions. For this purpose, the Push-Pull-Mooring model was used. To achieve the purpose of this study, prior literature and empirical studies were used to derive the primary measurement items through the primarily derived PPM model-based factors, and an online questionnaire survey was conducted with consumers who had had experience of overseas travel within the past two years. In total, 322 copies of the questionnaire were used for analysis. Through factor analyses, five push factors, four pull factors, and four mooring factors were derived. To understand tourism behavior intentions, each of the travel resumption times, preferred destination types, and preferred accommodation types were divided into three to conduct multinomial logistic regression analysis. The influence relationships between variables were verified to identify the changes in tourism behavior intentions caused by COVID-19, and the results indicated that some items of the PPM factors had significant influencing relationships with travel resumption times and preferred accommodation types. The preferred destination types were found to have significant influencing relationships with some items of the push/pull factors that were not found to have any influencing relationships with the mooring factors. This study is meaningful in that it presented motives and constraint factors for tourism behaviors from a new perspective based on changes in the tourism environment due to COVID-19, and the application of the PPM model and travel behavior is expected to be applied to diverse tourist behavior studies hereafter to achieve theoretical extensions.
Methodologies to Determine Geometrical Similarity Patterns as Experimental Models for Shapes in Architectural Heritage
Authors: Moyano Juan , Fernández-Alconchel María , Nieto-Julián Juan E. , Carretero-Ayuso Manuel J.
Published: September 2022

Today, plans to protect historic buildings focus on managing architectural heritage sustainably. Technical teams, such as architects and restorers, use massive data acquisition techniques, so an identification mechanism is required to select geometrical similarity patters to support hypothesis that guarantee historical data. Moreover, computational methods are required to understand the role of organic shapes in historic buildings. This paper first describes an extensive review of the literature and then the algorithms and methods to compare and to detect similar geometrical elements and complex patterns in architecture and archaeology. For this purpose, two key aspects are considered: the metric standpoint and historical-graphical features of the 3D models, i.e., composition, techniques, styles, and historical-graphical documentary sources. Research implies testing several methodological lines to know the similarity degree of complex organic shapes in architectural details through statistical analysis, software to assess point clouds, and complex curve analysis. The results have shown that the three procedures can be compared and that the bases of the pillars of both the Cathedral of Seville and the churches in Carmona, Jerez, and Morón are very similar; however, the base of the pillar of the church in Carmona presents scalability variations.
Asymptotic Properties of Quasi-Maximum Likelihood Estimators for Heterogeneous Spatial Autoregressive Models
Authors: Qiu Feng , Ding Hao , Hu Jianhua
Published: September 2022

In this paper, we address a class of heterogeneous spatial autoregressive models with all n(n−1) spatial coefficients taking m distinct true values, where m is independent of the sample size n, and we establish asymptotic properties of the maximum likelihood estimator and the quasi-maximum likelihood estimator for all parameters in the class of models, extending Lee’s work (2004). The rates of convergence of those estimators depend on the features of values taken by elements of the spatial weights matrix in this model. Under the situations where, based on the values of the weights, each individual will not only influence a few neighbors but also be influenced by only a few neighbors, the estimator can enjoy an n-rate of convergence and be asymptotically normal. However, when each individual can influence many neighbors or can be influenced by many neighbors and their number does not exceed o(n), singularity of the information matrix may occur, and various components of the estimators may have different (usually lower than n) rates of convergence. An inconsistent estimator is provided if some important assumptions are violated. Finally, simulation studies demonstrate that the finite sample performances of maximum likelihood estimators are good.
E-Connections on the ε-Anti-Kähler Manifolds
Authors: Chen Zhizhi , Li Yanlin , Gezer Aydin , Karakas Erkan , Karaman Cagri
Published: September 2022

The paper undertakes certain special forms of the quarter symmetric metric and non-metric connections on an ε-anti-Kähler manifold. Firstly, we deduce the relation between the Riemannian connection and the special forms of the quarter symmetric metric and non-metric connections. Then, we present some results concerning the torsion tensors of these connections. In addition, we find the forms of the curvature tensor, the Ricci curvature tensor and scalar curvature of such connections and we search the conditions for the ε-anti-Kähler manifold to be an Einstein space with respect to these connections. Finally, we study U(Ric)-vector fields with respect to these connections and give some results related to them.
The g-Extra Connectivity of the Strong Product of Paths and Cycles
Authors: Zhu Qinze , Tian Yingzhi
Published: September 2022

Let G be a connected graph and g be a non-negative integer. A vertex set S of graph G is called a g-extra cut if G−S is disconnected and each component of G−S has at least g+1 vertices. The g-extra connectivity of G is the minimum cardinality of a g-extra cut of G if G has at least one g-extra cut. For two graphs G1=(V1,E1) and G2=(V2,E2), the strong product G1⊠G2 is defined as follows: its vertex set is V1×V2 and its edge set is {(x1,x2)(y1,y2)|x1=x2 and y1y2∈E2; or y1=y2 and x1x2∈E1; or x1x2∈E1 and y1y2∈E2}, where (x1,x2),(y1,y2)∈V1×V2. In this paper, we obtain the g-extra connectivity of the strong product of two paths, the strong product of a path and a cycle, and the strong product of two cycles.
Generalized Preinvex Interval-Valued Functions and Related Hermite–Hadamard Type Inequalities
Authors: Khan Muhammad , Treanțǎ Savin , Soliman Mohamed
Published: September 2022

This study aims to connect the idea of inequalities with Riemann integral operators, which are of interest because of their characteristics and widespread use. We create a new Hermite–Hadamard type integral inequality for an
On Some Dynamic (ΔΔ)∇- Gronwall–Bellman–Pachpatte-Type Inequalities on Time Scales and Its Applications
Authors: El-Deeb Ahmed A. , El-Bary Alaa A. , Awrejcewicz Jan
Published: September 2022

In the present paper, some new generalizations of dynamic inequalities of Gronwall–Bellman–Pachpatte-type on time scales are established. Some integral and discrete Gronwall–Bellman–Pachpatte-type inequalities that are given as special cases of main results are original. The main results are proved by using the dynamic Leibniz integral rule on time scales. To highlight our research advantages, several implementations of these findings are presented. Symmetry plays an essential role in determining the correct methods to solve dynamic inequalities.
Applications of a q-Differential Operator to a Class of Harmonic Mappings Defined by q-Mittag–Leffler Functions
Authors: Khan Mohammad Faisal , Al-shbeil Isra , Khan Shahid , Khan Nazar , Haq Wasim Ul , Gong Jianhua
Published: September 2022

Many diverse subclasses of analytic functions, q-starlike functions, and symmetric q-starlike functions have been studied and analyzed by using q-analogous values of integral and derivative operators. In this paper, we define a q-analogous value of differential operators for harmonic functions with the help of basic concepts of quantum (q-) calculus operator theory; and introduce a new subclass of harmonic functions associated with the Janowski and q-Mittag–Leffler functions. We obtain several useful properties of the new class, such as necessary and sufficient conditions, criteria for analyticity, compactness, convexity, extreme points, radii of starlikeness, radii of convexity, distortion bounds, and integral mean inequality. Furthermore, we discuss some applications of this study in the form of some results and examples and highlight some known corollaries for verifying our main results presented in this investigation. Finally, the conclusion section summarizes the fact about the (p,q)-variations.
Properties of q-Symmetric Starlike Functions of Janowski Type
Authors: Saliu Afis , Al-Shbeil Isra , Gong Jianhua , Malik Sarfraz Nawaz , Aloraini Najla
Published: September 2022

The word “symmetry” is a Greek word that originated from “symmetria”. It means an agreement in dimensions, due proportion, and arrangement; however, in complex analysis, it means objects remaining invariant under some transformation. This idea has now been recently used in geometric function theory to modify the earlier classical q-derivative introduced by Ismail et al. due to its better convergence properties. Consequently, we introduce a new class of analytic functions by using the notion of q-symmetric derivative. The investigation in this paper obtains a number of the latest important results in q-theory, including coefficient inequalities and convolution characterization of q-symmetric starlike functions related to Janowski mappings.
Stochastic Model for the LMS Algorithm with Symmetric/Antisymmetric Properties
Authors: Becker Augusto Cesar , Kuhn Eduardo Vinicius , Matsuo Marcos Vinicius , Benesty Jacob , Paleologu Constantin , Dogariu Laura-Maria , Ciochină Silviu
Published: September 2022

This paper presents a stochastic model for the least-mean-square algorithm with symmetric/antisymmetric properties (LMS-SAS), operating in a system identification setup with Gaussian input data. Specifically, model expressions are derived to describe the mean weight behavior of the (global and virtual) adaptive filters, learning curves, and evolution of some correlation-like matrices, which allow predicting the algorithm behavior. Simulation results are shown and discussed, confirming the accuracy of the proposed model for both transient and steady-state phases.
Analysis of Traction and Unfolding Dynamics of Space-Symmetric Flexible Webs for UAV Interception and Capture
Authors: Liu Yiming , Xiong Ziming , Qiu Yanyu , Yan Fuhuai , Ma Chao
Published: September 2022

A new type of flexible web with a spatial symmetry structure is proposed to address the interception and acquisition of UAVs. It is different from the existing flexible web structure. According to the mechanical characteristics of the flexible web, the dynamic analysis model of the flexible web is established through theoretical deduction. Through finite element simulation calculation, the flexible webs of three different spatial symmetric structures are compared and analyzed. The internal force and air attitude of the three flexible webs are discussed. Among them, the new flexible web has a lag time of 0.162 s and a flight height of 11.624 m. The above simulation parameters are better than those of the other two symmetrical structures. It was proved that the new spatial symmetric flexible web has good traction and deployment performance. In addition, a ground verification test is designed and carried out. The web attitude and flight altitude parameters are compared with the simulation and test results. It is found that the simulation and experimental process of the new symmetric structure web are in good agreement, the synchronization of attitude change is good, and the flight altitude error of the two is controlled at about 5%. The feasibility and effectiveness of this method are proven and it can provide a reference for the research of flexible interception and acquisition of UAVs.
An Improved Regularity Criterion for the 3D Magnetic Bénard System in Besov Spaces
Authors: Naqeeb Muhammad , Hussain Amjad , Alghamdi Ahmad M.
Published: September 2022

This article notably targets the more general (extended) function spaces by investigating the regularity of the weak solutions or turbulent solutions to the Cauchy problem of the 3D magnetic Bénard system by converting it into mathematical symmetric form, in the absence of thermal diffusion, in terms of pressure. In that regard, we successfully improved the results by obtaining sufficient integrable regularity conditions for the pressure and gradient pressure in the homogeneous Besov spaces.
Experimental Study on Bending Resistance of New Type Joint of Prestressed Concrete Pipe Pile
Authors: Wang Bo , Qi Lei , Yang Yongdong
Published: September 2022

In the field of PHC pile joints, it is important that prestressed high-strength concrete pipe piles are referred to as PHC pipe piles. In conventional hoops, bamboo-like joints protrude from the pile joint position at the surface of the pile. Driving the pile in, disturbing the soil around the pile, and affecting the frictional resistance are serious issues. To address such issues, herein, a new type of clamping joint is proposed. A new method is presented to determine the size of the new joint that is flushed with the surface of the pile at the joint position. Bending resistance tests are conducted on four types of new joints for common pipe piles to study the deformation development process, bending bearing capacity, and damage characteristics of the new joints. Cracks are mainly distributed in the pure bending section and are approximately symmetrically distributed along both sides of the joint; there is no obvious cracking and damage in the joint until the pile cracks. Under the same bending moment, the deflection in the span of all specimens is greater than the deflection at the loading point.