bluuebunny/crossref_metadata_2025 huggingface dataset:
A Hyperspectral Image Classification Method Based on Adaptive Spectral Spatial Kernel Combined with Improved Vision Transformer
Authors: Wang Aili , Xing Shuang , Zhao Yan , Wu Haibin , Iwahori Yuji
Published: August 2022

In recent years, methods based on deep convolutional neural networks (CNNs) have dominated the classification task of hyperspectral images. Although CNN-based HSI classification methods have the advantages of spatial feature extraction, HSI images are characterized by approximately continuous spectral information, usually containing hundreds of spectral bands. CNN cannot mine and represent the sequence properties of spectral features well, and the transformer model of attention mechanism proves its advantages in processing sequence data. This study proposes a new spectral spatial kernel combined with the improved Vision Transformer (ViT) to jointly extract spatial spectral features to complete classification task. First, the hyperspectral data are dimensionally reduced by PCA; then, the shallow features are extracted with an spectral spatial kernel, and the extracted features are input into the improved ViT model. The improved ViT introduces a re-attention mechanism and a local mechanism based on the original ViT. The re-attention mechanism can increase the diversity of attention maps at different levels. The local mechanism is introduced into ViT to make full use of the local and global information of the data to improve the classification accuracy. Finally, a multi-layer perceptron is used to obtain the classification result. Among them, the Focal Loss function is used to increase the loss weight of small-class samples and difficult-to-classify samples in HSI data samples and reduce the loss weight of easy-to-classify samples, so that the network can learn more useful hyperspectral image information. In addition, using the Apollo optimizer to train the HSI classification model to better update and compute network parameters that affect model training and model output, thereby minimizing the loss function. We evaluated the classification performance of the proposed method on four different datasets, and achieved good classification results on urban land object classification, crop classification and mineral classification, respectively. Compared with the state-of-the-art backbone network, the method achieves a significant improvement and achieves very good classification accuracy.
Development of a Reliable High-Performance WLP for a SAW Device
Authors: Chen Zuohuan , Yu Daquan
Published: August 2022

In this paper, we present wafer-level packaging technology for surface acoustic wave (SAW) filters with higher long-term reliability and better electrical performance. This article focuses on the package structure, fabrication processes, and reliability for the SAW filter wafer-level package (WLP). The key processes, including cavity wall (CW) dam formation through non-photosensitive film vias development using a laser drilling process, a redistribution layer (RDL), and ball-grid array formation are developed. In addition, a numerical study based on the finite element model has been conducted to analyze the stress distribution of Cu RDL traces. In addition, the CW dam and the roof layer are covered with polymer, which solves the delamination problem between the CW dam and the substrate. Meanwhile, after practical verification, the SAW filter WLP was resistant to encapsulating pressure using a high elastic modulus capping material, which solved the collapse problem. Additionally, a comparison of the RF filter package’s electrical performance following the preconditional level 3 and unbiased highly accelerated stress test revealed no differences in insertion attenuation across the passband (<0.2 dB, standard value: 1 dB). The final packages passed the reliability tests in the field of consumer electronics.
Blockchain Based Delay and Energy Harvest Aware Healthcare Monitoring System in WBAN Environment
Authors: Anbarasan Helen Sharmila , Natarajan Jaisankar
Published: August 2022

Wireless body area networks (WBANs) are a research area that supports patients with healthcare monitoring. In WBAN, the Internet of Things (IoT) is connected with WBAN for a smart/remote healthcare monitoring system in which various medical diseases are diagnosed. Quality of service (QoS), security and energy efficiency achievements are the major issues in the WBAN-IoT environment. Existing schemes for these three issues fail to achieve them since nodes are resource constrained and hence delay and the energy consumption is minimized. In this paper, a blockchain-assisted delay and energy aware healthcare monitoring (B-DEAH) system is presented in the WBAN-IoT environment. Both body sensors and environment sensors are deployed with dual sinks for emergency and periodical packet transmission. Various processes are involved in this paper, and each process is described as follows: Key registration for patients using an extended version of the PRESENT algorithm is proposed. Cluster formation and cluster head selection are implemented using spotted hyena optimizer. Then, cluster-based routing is established using the MOORA algorithm. For data transmission, the patient block agent (PBA) is deployed and authenticated using the four Q curve asymmetric algorithm. In PBA, three entities are used: classifier and queue manager, channel selector and security manager. Each entity is run by a special function, as packets are classified using two stream deep reinforcement learning (TS-DRL) into three classes: emergency, non-emergency and faulty data. Individual packets are put into a separate queue, which is called emergency, periodical and faulty. Each queue is handled using Reyni entropy. Periodical packets are forwarded by a separate channel without any interference using a multi objective based channel selection algorithm. Then, all packets are encrypted and forwarded to the sink nodes. Simulation is conducted using the OMNeT++ network simulator, in which diverse parameters are evaluated and compared with several existing works in terms of network throughput for periodic (41.75 Kbps) and emergency packets (42.5 Kbps); end-to-end delay for periodic (0.036 s) and emergency packets (0.028 s); packet loss rate (1.1%); residual energy in terms of simulation rounds based on periodic (0.039 J) and emergency packets (0.044 J) and in terms of simulation time based on periodic (8.35 J) and emergency packets (8.53 J); success rate for periodic (87.83%) and emergency packets (87.5%); authentication time (3.25 s); and reliability (87.83%).
Point Cloud Compression: Impact on Object Detection in Outdoor Contexts
Authors: Garrote Luís , Perdiz João , da Silva Cruz Luís A. , Nunes Urbano J.
Published: August 2022

Increasing demand for more reliable and safe autonomous driving means that data involved in the various aspects of perception, such as object detection, will become more granular as the number and resolution of sensors progress. Using these data for on-the-fly object detection causes problems related to the computational complexity of onboard processing in autonomous vehicles, leading to a desire to offload computation to roadside infrastructure using vehicle-to-infrastructure communication links. The need to transmit sensor data also arises in the context of vehicle fleets exchanging sensor data, over vehicle-to-vehicle communication links. Some types of sensor data modalities, such as Light Detection and Ranging (LiDAR) point clouds, are so voluminous that their transmission is impractical without data compression. With most emerging autonomous driving implementations being anchored on point cloud data, we propose to evaluate the impact of point cloud compression on object detection. To that end, two different object detection architectures are evaluated using point clouds from the KITTI object dataset: raw point clouds and point clouds compressed with a state-of-the-art encoder and three different compression levels. The analysis is extended to the impact of compression on depth maps generated from images projected from the point clouds, with two conversion methods tested. Results show that low-to-medium levels of compression do not have a major impact on object detection performance, especially for larger objects. Results also show that the impact of point cloud compression is lower when detecting objects using depth maps, placing this particular method of point cloud data representation on a competitive footing compared to raw point cloud data.
Validation of a Sensor-Based Dynamic Ski Deflection Measurement in the Lab and Proof-of-Concept Field Investigation
Authors: Thorwartl Christoph , Kröll Josef , Tschepp Andreas , Holzer Helmut , Teufl Wolfgang , Stöggl Thomas
Published: August 2022

Introduction: Ski deflection is a performance-relevant factor in alpine skiing and the segmental and temporal curvature characteristics (m−1) along the ski have lately received particular attention. Recently, we introduced a PyzoFlex® ski deflection measurement prototype that demonstrated high reliability and validity in a quasi-static setting. The aim of the present work is to test the performance of an enhanced version of the prototype in a dynamic setting both in a skiing-like bending simulation as well as in a field proof-of-concept measurement. Material and methods: A total of twelve sensor foils were implemented on the upper surface of the ski. The ski sensors were calibrated with an empirical curvature model and then deformed on a programmable bending robot with the following program: 20 times at three different deformation velocities (vslow, vmedium, vfast) with (1) central bending, (2) front bending, (3) back bending, (4) edging left, and (5) edging right. For reliability assessment, pairs of bending cycles (cycle 1 vs. cycle 10 and cycle 10 vs. cycle 20) at vslow, vmedium, and vfast and between pairs of velocity (vslow vs. vmedium and vslow vs. vfast) were evaluated by calculating the change in the mean (CIM), coefficient of variation (CV) and intraclass correlation coefficient (ICC 3.1) with a 95% confidence interval. For validity assessment, the calculated segment-wise mean signals were compared with the values that were determined by 36 infrared markers that were attached to the ski using an optoelectrical measuring system (Qualisys). Results: High reliability was found for pairs of bending cycles (CIM −0.69–0.24%, max CV 0.28%, ICC 3.1 > 0.999) and pairs of velocities (max CIM = 3.03%, max CV = 3.05%, ICC 3.1 = 0.997). The criterion validity based on the Pearson correlation coefficient was r = 0.98. The accuracy (systematic bias) and precision (standard deviation), were −0.003 m−1 and 0.047 m−1, respectively. Conclusions: The proof-of-concept field measurement has shown that the prototype is stable, robust, and waterproof and provides characteristic curvature progressions with plausible values. Combined with the high laboratory-based reliability and validity of the PyzoFlex® prototype, this is a potential candidate for smart ski equipment.
Effects of Missing Data on Heart Rate Variability Metrics
Authors: Cajal Diego , Hernando David , Lázaro Jesús , Laguna Pablo , Gil Eduardo , Bailón Raquel
Published: August 2022

Heart rate variability (HRV) has been studied for decades in clinical environments. Currently, the exponential growth of wearable devices in health monitoring is leading to new challenges that need to be solved. These devices have relatively poor signal quality and are affected by numerous motion artifacts, with data loss being the main stumbling block for their use in HRV analysis. In the present paper, it is shown how data loss affects HRV metrics in the time domain and frequency domain and Poincaré plots. A gap-filling method is proposed and compared to other existing approaches to alleviate these effects, both with simulated (16 subjects) and real (20 subjects) missing data. Two different data loss scenarios have been simulated: (i) scattered missing beats, related to a low signal to noise ratio; and (ii) bursts of missing beats, with the most common due to motion artifacts. In addition, a real database of photoplethysmography-derived pulse detection series provided by Apple Watch during a protocol including relax and stress stages is analyzed. The best correction method and maximum acceptable missing beats are given. Results suggest that correction without gap filling is the best option for the standard deviation of the normal-to-normal intervals (SDNN), root mean square of successive differences (RMSSD) and Poincaré plot metrics in datasets with bursts of missing beats predominance (p<0.05), whereas they benefit from gap-filling approaches in the case of scattered missing beats (p<0.05). Gap-filling approaches are also the best for frequency-domain metrics (p<0.05). The findings of this work are useful for the design of robust HRV applications depending on missing data tolerance and the desired HRV metrics.
MsWH: A Multi-Sensory Hardware Platform for Capturing and Analyzing Physiological Emotional Signals
Authors: Asiain David , Ponce de León Jesús , Beltrán José Ramón
Published: August 2022

This paper presents a new physiological signal acquisition multi-sensory platform for emotion detection: Multi-sensor Wearable Headband (MsWH). The system is capable of recording and analyzing five different physiological signals: skin temperature, blood oxygen saturation, heart rate (and its variation), movement/position of the user (more specifically of his/her head) and electrodermal activity/bioimpedance. The measurement system is complemented by a porthole camera positioned in such a way that the viewing area remains constant. Thus, the user’s face will remain centered regardless of its position and movement, increasing the accuracy of facial expression recognition algorithms. This work specifies the technical characteristics of the developed device, paying special attention to both the hardware used (sensors, conditioning, microprocessors, connections) and the software, which is optimized for accurate and massive data acquisition. Although the information can be partially processed inside the device itself, the system is capable of sending information via Wi-Fi, with a very high data transfer rate, in case external processing is required. The most important features of the developed platform have been compared with those of a proven wearable device, namely the Empatica E4 wristband, in those measurements in which this is possible.
Graph-Based Resource Allocation for Integrated Space and Terrestrial Communications
Authors: Ivanov Antoni , Tonchev Krasimir , Poulkov Vladimir , Manolova Agata , Neshov Nikolay N.
Published: August 2022

Resource allocation (RA) has always had a prominent place in wireless communications research due to its significance for network throughput maximization, and its inherent complexity. Concurrently, graph-based solutions for RA have also grown in importance, providing opportunities for higher throughput and efficiency due to their representational capabilities, as well as challenges for realizing scalable algorithms. This article presents a comprehensive review and analysis of graph-based RA methods in three major wireless network types: cellular homogeneous and heterogeneous, device-to-device, and cognitive radio networks. The main design characteristics, as well as directions for future research, are provided for each of these categories. On the basis of this review, the concept of Graph-based Resource allocation for Integrated Space and Terrestrial communications (GRIST) is proposed. It describes the inter-connectivity and coexistence of various terrestrial and non-terrestrial networks via a hypergraph and its attributes. In addition, the implementation challenges of GRIST are explained in detail. Finally, to complement GRIST, a scheme for determining the appropriate balance between different design considerations is introduced. It is described via a simplified complete graph-based design process for resource management algorithms.
Advanced Marine Predator Algorithm for Circular Antenna Array Pattern Synthesis
Authors: Owoola Eunice Oluwabunmi , Xia Kewen , Ogunjo Samuel , Mukase Sandrine , Mohamed Aadel
Published: August 2022

The pattern synthesis of antenna arrays is a substantial factor that can enhance the effectiveness and validity of a wireless communication system. This work proposes an advanced marine predator algorithm (AMPA) to synthesize the beam patterns of a non-uniform circular antenna array (CAA). The AMPA utilizes an adaptive velocity update mechanism with a chaotic sequence parameter to improve the exploration and exploitation capability of the algorithm. The MPA structure is simplified and upgraded to overcome being stuck in the local optimum. The AMPA is employed for the joint optimization of amplitude current and inter-element spacing to suppress the peak sidelobe level (SLL) of 8-element, 10-element, 12-element, and 18-element CAAs, taking into consideration the mutual coupling effects. The results show that it attains better performances in relation to SLL suppression and convergence rate, in comparison with some other algorithms for the optimization case.
Electrochemical Sensor Based on Iron(II) Phthalocyanine and Gold Nanoparticles for Nitrite Detection in Meat Products
Authors: Dorovskikh Svetlana I. , Klyamer Darya D. , Fedorenko Anastasiya D. , Morozova Natalia B. , Basova Tamara V.
Published: August 2022

Nitrites are widely used in the food industry, particularly for the preservation of meat products. Controlling the nitrate content in food is an important task to ensure people’s health is not at risk; therefore, the search for, and research of, new materials that will modify the electrodes in the electrochemical sensors that detect and control the nitrate content in food products is an urgent task. In this paper, we describe the electrochemical behavior of a glass carbon electrode (GCE), modified with a Fe(II) tetra-tert-butyl phthalocyanine film (FePc(tBu)4/GCE), and decorated with gold nanoparticles (Au/FePc(tBu)4/GCE); this electrode was deposited using gas-phase methods. The composition and morphology of such electrodes were examined using spectroscopy and electron microscopy methods, whereas the main electrochemical characteristics were determined using cyclic voltammetry (CV) and amperometry (CA) methods in the linear ranges of CV 0.25–2.5 mM, CA 2–120 μM in 0.1 M phosphate buffer (pH = 6.8). The results showed that the modification of bare GCEs, with a Au/FePc(tBu)4 heterostructure, provided a high surface-to-volume ratio, thus ensuring its high sensitivity to nitrite ions of 0.46 μAμM−1. The sensor based on the Au/FePc(tBu)4/GCE has a low limit of nitrite detection at 0.35 μM, good repeatability, and stability. The interference study showed that the proposed Au/FePc(tBu)4/GCE exhibited a selective response in the presence of interfering anions, and the analytical capability of the sensor was demonstrated by determining nitrite ions in real samples of meat products.
Synergistic Effect of NiO-Ga2O2-Graphene Heterostructures on Congo Red Photodegradation in Water
Authors: Shaalan Nagih M. , Rashad Mohamed , Awada Chawki
Published: August 2022

We studied the effect of the mixed phase of nickel oxide–gallium oxide–graphene (NiO-Ga2O2/G) heterostructure nanocomposite on the photocatalytic degradation of Congo red dye. The effect was investigated based on NiO-Ga2O2 junction, NiO-graphene, and Ga2O2-graphene contacts. The laser-induced graphene was embedded into NiO and NiO-Ga2O2. Raman spectra confirmed the fabrication of disordered graphene and the mixed phase between the oxides and graphene. HRTEM showed that very fine nanoparticles for both NiO and Ga2O2 with a size of ~7–10 nm were synthesized. Elemental compositional expressed the formation mixed phase. The effect of graphene content was investigated at 2 and 10% wt with NiO and the heterojunction of NiO-Ga2O2. The photocurrent studies was measured of these nanocomposite film deposited on two interdigitated gold electrodes, biased by 5.0 V and irradiated by the UV source. The results of photocatalysis measurements indicated an improvement occurred upon the heterojunction between Ga2O2 and NiO, however, a dramatic improvement was observed with the addition of graphene of 10%. The results expressed that the ternary phase of p-NiO/n-Ga2O2/graphene is promising in the photocatalytic application toward Congo red decomposition.
Wearable Biosensor Standardization: How to Make Them Smarter
Authors: Giorgi Giada , Tonello Sarah
Published: August 2022

The availability of low-cost plug-and-play devices may contribute to the diffusion of methods and technologies for the personalized monitoring of physiological parameters by wearable devices. This paper is focused on biosensors, which represent an interesting enabling technology for the real-time continuous acquisition of biological or chemical analytes of physio-pathological interest, e.g., metabolites, protein biomarkers, and electrolytes in biofluids. Currently available commercial biosensors are usually referred to as customized and proprietary solutions. However, the efficient and robust development of e-health applications based on wearable biosensors can be eased from device interoperability. In this way, even if the different modules belong to different manufacturers, they can be added, upgraded, changed or removed without affecting the whole data acquisition system. A great effort in this direction has already been made by the ISO/IEC/IEEE 21451 standard that introduces the concept of smart sensors by defining the main and essential characteristics that these devices should have. Following the guidelines provided by this standard, here we propose a set of characteristics that should be considered in the development of a smart biosensor and how they could be integrated into the existing standard.
Reduction and Degradation of Paraoxon in Water Using Zero-Valent Iron Nanoparticles
Authors: Okello Veronica A. , K’Owino Isaac O. , Masika Kevin , Shikuku Victor O.
Published: August 2022

Paraoxon is an emerging organophosphate pollutant that is commonly used as a pesticide and a drug, hence increasing the risk of contamination of water supplies. Its intensive use for vector control has led to pollutions in soil and water. Paraoxon is very toxic, with an LD50 of 2 to 30 mg/kg in rats. It can be metabolized in the body from parathion; thus, exposure can lead to serious health effects. In this study, zero valent iron (Fe°/ZVI NPs) nanoparticles were synthesized and investigated for the degradation of Paraoxon, a chemical warfare agent and insecticide, in an aqueous solution. The effects of solution pH, initial pollutant concentration, ZVI NPs dosage and contact time on mineralization efficiency were examined. Batch experiments demonstrated that 15 mg L−1 of Paraoxon was mineralized at degradation efficiencies of 75.9%, 63.9% and 48.9% after three-hour treatment with 6.0, 4.0 and 2.0% w/v Fe°, respectively. The calculated kinetic rate constant kobs was 0.4791 h−1, 0.4519 h−1 and 0.4175 h−1 after treating 10, 15 and 20 mg L−1 of Paraoxon solution with 6.0% w/v Fe, respectively. The degradation dynamics were described by the first-order kinetic law as evidenced by rate constants independent of the initial Paraoxon concentration. The degradation efficiency was strongly dependent on pH, increasing with a decrease in pH, with maximum removal at pH 4. p-nitrophenol was detected as a degradation product, suggesting cleavage of the O-P bond and hydrolysis as possible reaction processes. This study showed that Fe° particles have the potential for degrading Paraoxon.
Investigation on the Urban Grey Water Treatment Using a Cost-Effective Solar Distillation Still
Authors: Yusof Mohd Fazly , Zainol Mohd Remy Rozainy Mohd Arif , Riahi Ali , Zakaria Nor Azazi , Shaharuddin Syafiq , Juiani Siti Fairuz , Noor Norazian Mohamed , Zawawi Mohd Hafiz , Ikhsan Jazaul
Published: August 2022

Treating urban grey water with physical, chemical, and biological treatment techniques and reusing it as a sustainable non-potable water source has received much attention recently, yet there is a lack of studies regarding it. In this work, a typical slum nearby an urban household area in Malaysia was selected as a source of contaminated grey water which is located on the opposite side of a building site (100°29′ E and 5°7′ N) located in an urban area in a city in the Perak state, namely Parit Buntar, where the total urban grey water was being accumulated. Poor sanitation of that slum was seen to pose various health risks to the public, and hence, the importance of treating its grey water was perceived. Thus, this study was conducted to evaluate the performance of a low-cost double slope passive solar still by treating the grey water from the aforementioned slum, as well as to analyze the quality, quantity, and cost per liter of the produced water. Grey water was collected and filled in the solar still basin at s depth of 1 cm. The cover and basin of the solar still were made from transparent polythene film and black-painted stainless steel trough, respectively, while the frame was made from polyvinyl chloride (PVC), and the solar still was named PSSG1 abbreviated. PSSG1 was exposed to Malaysia’s climate conditions for several days from 8.00 a.m. to 6.00 p.m. at Universiti Sains Malaysia (USM), which was able to produce the maximum amount of water up to 4.11 L/m2·d with the cost per liter/m2 of only USD 0.0082. Water quality parameters tested showed that water produced from PSSG1 met the standards of the restricted and unrestricted reusable non-potable grey water, the World Health Organization (WHO), and the Malaysian class I drinking water standards. It was also found that the PSSG1 with higher average daily basin water temperature produced water with higher quality for the reuse applications and yielded healthier water compared to the water produced by some reported previous grey water treatment techniques. Therefore, the cost-effective PSSG1 can be used as a daily practical alternative for treating low-strength grey water collected from various urban household areas in Malaysia in order to assist pollutants removal from the drained urban grey waters.
RETRACTED: Investigation of the Physical Properties of Yarn Produced from Textile Waste by Optimizing Their Proportions
Authors: Memon Hafeezullah , Ayele Henock , Yesuf Hanur , Sun Li
Published: August 2022

Since textile waste recycling is a global challenge, there is an emerging need to explore this research direction due to the little knowledge about textile recycling. This study aimed to study the property of yarns produced from recycled textile/cotton fiber blends for proportion optimization and to check whether they can be used for denim fabric production. The properties of recycled fiber and virgin cotton spun on open-end having 4.5 Ne were investigated with fiber proportions of 20/80, 25/75, 30/70, 35/65, 40/60, 45/55, and 50/50. The results were analyzed with Design-Expert software, using central composite design to optimize the proportion. The 40/60 proportion had the optimum result, and by using this optimized proportion, 10 Ne yarn was produced and used for denim fabric production. The sample denim fabric produced used recycled yarn as a weft, showing that the recycled fiber turned yarn can be used in manufacturing products such as denim. The physical properties of the denim fabric confirmed that the recycled goods have wearable quality. Since this research can be applied on an industrial scale, it would benefit textile academia, industry, the environment, and society.
Development of Bio-Electrochemical Reactor for Groundwater Denitrification: Effect of Electric Current and Water Hardness
Authors: Ratananikom Khakhanang , Peungtim Prarunchaya , Phuinthiang Patcharaporn , Nakaruk Auppatham , Khanitchaidecha Wilawan
Published: August 2022

Nitrate-nitrogen (NO3-N) contaminating groundwater is an environmental issue in many areas, and is difficult to treat by simple processes. A bio-electrochemical reactor (BER) using copper wire and graphite plate was developed to purify the NO3-N-contaminated groundwater. The low (of 10 mA) and high (of 20 mA) electric currents were applied to the BERs, and various influent hardness levels from 20 to 80 mg/L as CaCO3 due to groundwater characteristics were supplied to clarify the total nitrogen removal efficiency and NO3-N removal mechanisms. In the BER-10, the bio-electrochemical reactions caused 85% of total nitrogen to be removed through heterotrophic and autohydrogenotrophic denitrification in the suspended sludge and biofilm. However, the chemical deposit occurring at the cathode from water hardness affected the decreasing denitrification performance; 12.6% of Mg and 8.8% of Ca elements were observed in the biofilm. The enhancement of electrochemical reactions in the BER-20 caused integrating electrochemical and bio-electrochemical reactions; the NO3-N was electrochemically reduced to NO2-N, and it was further biologically reduced to N2. A better total nitrogen removal of 95% was found; although, a larger deposit of Mg (22.8%) and Ca (10.8%) was observed. The relatively low dissolved H2 in the BER-20 confirmed that the deposit affected the decreasing gaseous H2 transfer and inhibition of autohydrogenotrophic denitrification in the suspended sludge. According to the microbial analysis, both heterotrophic and autohydrogenotrophic denitrification were obtained in the suspended sludge of both BERs; Nocadia (26.8%) was the most abundant genus in the BER-10, whereas Flavobacterium (27.1%) and Nocadia (25.0%) were the dominant genera in the BER-20.
Global Research Trends in Consumer Behavior and Sustainability in E-Commerce: A Bibliometric Analysis of the Knowledge Structure
Authors: Rita Paulo , Ramos Ricardo F.
Published: August 2022

Consumers are conscious of increasing online purchases and demand sustainable consumption friendly actions. Although there is increasing interest in this topic, the research status, development, and structure of consumer behavior and sustainability in e-commerce research is scarce. This study aims to analyze the intellectual, conceptual, and social knowledge of consumer behavior and sustainability in e-commerce research to generate new understandings. Data from 104 articles were collected from the Scopus database, and a bibliometric analysis was conducted. Results revealed a close relationship between the topic and city logistics, big data analysis, customer engagement, circular economy, online services, and omnichannel retail, showing the different research approaches and the transversal themes related to the topic. This study contributes to the sustainability academic research by identifying trends and suggesting future research topics.
The Correlation between Convenience Stores’ Distribution and Urban Spatial Function: Taking the FamilyMart Stores in Shanghai as an Example
Authors: Liao Shuling , Liu Kun , Yang Ying , Liu Yong
Published: August 2022

This manuscript mainly focuses on the correlation between the spatial distribution of convenience stores and the distribution of urban spatial functions. We took 1217 FamilyMart convenience stores within the Shanghai outer ring area as the research objects and used the calculation method of kernel density estimation. The results show that the distribution of Shanghai FamilyMart stores is centered on the three central urban areas of Huangpu District, Jing’an District, and Xuhui District; the high-density areas of convenience stores partially overlap with the city’s main center, and some do not. The research shows that in areas with a high distribution density of convenience stores, the establishment of the convenience stores has a strong correlation with urban spatial functions, and these continence stores have formalized a network deeply integrated with the community. We believe that, in the future, with the development of small retail businesses, these can be transformed into public activity spaces through space transformation and design, which promotes the sustainable development of community interaction and traditional retail business, stimulating the sustainability of community vitality. The results of this study show that this concept has a feasible spatial basis, and the research method can also be applied to the study of other small retail commercial spaces.
Common Sharing or Public Sharing: A Study on the Choice Behavior of Urban Citizens in Public Travel
Authors: Li Yapeng
Published: August 2022

Public travel is an important support for urban citizens’ production and life. As a collective choice behavior, there are different action logics behind the common sharing travel and public sharing travel in China. It is beneficial to provide public travel services to citizens and improve the performance of urban governance by sorting out the different public travel types and their inner choice logics. A fuzzy set of qualitative, comparative analyses reveals that citizens’ choice of common sharing travel or public sharing travel consists of two paths, in which user size, rule attainment, convenience, and travel distance are important triggers. The government and enterprises should improve the combined supply of each factor to enhance citizens’ public travel experience, guide citizens’ public travel choice behavior, and help the development of a common sharing travel industry so as to promote the construction of green transportation, public transport cities, and smart cities.
Sustainable Statehood: Reflections on Critical (Pre-)Conditions, Requirements and Design Options
Authors: Heinrichs Harald
Published: August 2022

Thirty years after the seminal UN conference on environment and development, where the global agenda for sustainable development was agreed upon by the international community, uncountable initiatives in public policy, business and civil society have been activated. Despite all efforts, pressure on life-supporting Earth systems remain on an ecologically, socially and economically unsustainable pathway. Global collective action for sustainable development has so far been insufficient regarding the scientifically well-diagnosed need for substantial transformation. Given that the world remains a world of nation states, notwithstanding processes of globalization and transnationalization, internationalization and subnationalization, the quest for sustainable statehood is of utmost importance. Based on the expectations of nation states expressed in the UN Transformation Agenda 2030, it is argued that underlying and cross-cutting structures, procedures and instruments of statehood, which precede decision-making processes and policy-making in specific fields of sustainable development, such as climate change or biodiversity, are of key relevance. In this regard critical requirements and (pre-)conditions for sustainable statehood are discussed and design options for sustainable statehood in the Anthropocene are proposed.
The Influence of Coal Meso-Structure on Adsorption Characteristics of Coking and Lean Coal
Authors: Shi Lei , Cai Tingting , Jiang Yulong , Su Xiaoyu , Zhang Leili
Published: August 2022

The non-uniform adsorption characteristics of coal strictly restrict the development and utilization of CBM, and the structure of coal is the fundamental reason for its non-uniform adsorption of methane. To investigate the fundamental causes of methane adsorption capacity differences in coal with various meso-structures, small coking coal and lean coal samples were subjected to isothermal adsorption, computed tomography (CT) scanning, scanning electron microscopy (SEM), and mercury intrusion porosimetry (MIP) to obtain the correlation between the meso-structure of coal and its non-uniform adsorption characteristics. The reasons for the differences in methane adsorption capacity between the specimens were summarized from the perspectives of material and structural heterogeneities, meso-morphology and pore size distribution. The following conclusions could be drawn: (1) The coal samples with different heterogeneity degrees exhibit varying methane adsorption capacities. (2) Compared to the specific surface area, the mineral composition exerts a greater influence on the adsorption capacity of the coal samples. (3) The gas adsorption capacities of the coal samples with similar meso-morphology and pore size distribution characteristics are similar, while among the coal samples with similar pore size distributions but different meso-morphologies, the gas adsorption capacities significantly differ.
A Physical Model-Based Data-Driven Approach to Overcome Data Scarcity and Predict Building Energy Consumption
Authors: Oh Kyoungcheol , Kim Eui-Jong , Park Chang-Young
Published: August 2022

Predicting building energy consumption needs to be anticipated to save building energy and effectively control the predictions. This study depicted the target building as a physical model to improve the learning performance in a data-scarce environment and proposed a model that uses simulation results as the input for a data-driven model. Case studies were conducted with different quantities of data. The proposed hybrid method proposed in this study showed a higher prediction accuracy showing a cvRMSE of 22.8% and an MAE of 6.1% than using the conventional data-driven method and satisfying the tolerance criteria of ASHRAE Guideline 14 in all the test cases.
Blockchain Technology and Artificial Intelligence Based Decentralized Access Control Model to Enable Secure Interoperability for Healthcare
Authors: Rana Sumit Kumar , Rana Sanjeev Kumar , Nisar Kashif , Ag Ibrahim Ag Asri , Rana Arun Kumar , Goyal Nitin , Chawla Paras
Published: August 2022

Healthcare, one of the most important industries, is data-oriented, but most of the research in this industry focuses on incorporating the internet of things (IoT) or connecting medical equipment. Very few researchers are looking at the data generated in the healthcare industry. Data are very important tools in this competitive world, as they can be integrated with artificial intelligence (AI) to promote sustainability. Healthcare data include the health records of patients, drug-related data, clinical trials data, data from various medical equipment, etc. Most of the data management processes are manual, time-consuming, and error-prone. Even then, different healthcare industries do not trust each other to share and collaborate on data. Distributed ledger technology is being used for innovations in different sectors including healthcare. This technology can be incorporated to maintain and exchange data between different healthcare organizations, such as hospitals, insurance companies, laboratories, pharmacies, etc. Various attributes of this technology, such as its immutability, transparency, provenance etc., can bring trust and security to the domain of the healthcare sector. In this paper, a decentralized access control model is proposed to enable the secure interoperability of different healthcare organizations. This model uses the Ethereum blockchain for its implementation. This model interfaces patients, doctors, chemists, and insurance companies, empowering the consistent and secure exchange of data. The major concerns are maintaining a history of the transactions and avoiding unauthorized updates in health records. Any transaction that changes the state of the data is reflected in the distributed ledger and can be easily traced with this model. Only authorized entities can access their respective data. Even the administrator will not be able to modify any medical records.
Application of the Maturity Model in Industrial Corporations
Authors: Ünal Cihan , Sungur Cemil , Yildirim Hakan
Published: August 2022

Enterprises need to evaluate for themselves whether they are ready for Industry 4.0 to survive and develop in the era of the Fourth Industrial Revolution. Therefore, it is necessary to conceptualize or develop an Industry 4.0 readiness and maturity model with basic model dimensions. The present study aimed to review the maturity models available in the literature and to develop and implement a comprehensive maturity model that would eliminate the problems in the existing models. Most maturity models developed lack vital dimensions such as laws, incentives, and corporate culture. While developing the model, AHP and expert opinions were used to determine the dimension weights. The model was applied to 87 businesses in various industries at the Ankara Chamber of Industry Industrial Park in Turkey. The developed model calculates the maturity level of the enterprise for six dimensions. The data on 61 corporations where Industry 4.0 technologies were adopted were analyzed based on demographic variables such as the year of establishment, industry, size, capital, and turnover. These findings demonstrated that Industry 4.0 was introduced recently in Turkey and businesses are required to take further steps to keep up with the global digital transformation. Since the number of industries and corporations that are aware of the Industry 4.0 technologies is limited in Ankara, Turkey, only a few businesses adopted the Industry 4.0 technologies. This developed model will make an important contribution to the literature with its unique dimensions. It would pave the way for further research in various industries in Turkey and other nations where Industry 4.0 investments are new.
A Comparative Analysis of the Impacts and Resilience of the Electricity Supply Industry against COVID-19 Restrictions in the United Kingdom, Malawi, and Uganda
Authors: Mujjuni Francis , Chivunga Joyce Nyuma , Betts Thomas , Lin Zhengyu , Blanchard Richard
Published: August 2022

In response to COVID-19, most countries implemented mitigative and suppressive measures to stem its spread. This study analysed their impacts on the operations, investments, and policies within the electricity supply industry (ESI) for the United Kingdom, Malawi, and Uganda. It further assessed ESI’s resilience capacities (prevention, absorption, adaptation, recovery, and transformation) and ultimately quantified resilience using SDG 7 targets. The study observed that in 2020, the UK had 143 days of lockdowns compared to 74 for Uganda and none for Malawi. The UK’s annual demand fell by 4.8% while Uganda and Malawi’s increased by 0.5% and 2.8%, respectively. During lockdowns, the UK lost 28% of its demand compared to 5.5% for Malawi and 24% for Uganda. It took the UK 8 months to recover its demand, which was correspondingly twice and four times longer than Uganda and Malawi. The degeneration in the level of system operations in the UK did not significantly affect electricity access and reliability contrary to Uganda and Malawi, whose impacts on their development commitments could span for years. This study underscores the necessity of evaluating resilience with respect to local development commitments. Moreover, several measures were proposed to enhance resilience mainly through actions meant to ensure business continuity.
Wine Supply Chain Network Configuration under a Water Footprint Cap
Authors: Aivazidou Eirini , Aidonis Dimitrios , Tsolakis Naoum , Achillas Charisios , Vlachos Dimitrios
Published: August 2022

As agriculture and industry exploit more than 90% of the global freshwater resources, water overuse and degradation have emerged as critical socio-environmental challenges for both nations and corporations. In this context, the water footprint concept was introduced in order to quantify the freshwater consumption and pollution of a territory or across a product’s life cycle. As research on water management in supply chains is growing, this work aims to integrate the perspective of freshwater resources into supply network configuration. Focusing on the agrifood sector, we have developed a mixed-integer linear programming model that can be used to minimize the operational costs under a water footprint cap in a wine supply chain network by selecting the optimal suppliers (vine growers), manufacturing sites (winemakers), and transportation modes (fuel-powered trucks). The optimization outcomes unveil that the wine network’s configurations (structure and fuel type) vary significantly depending on the values of the water footprint cap so as to balance the trade-off between economic and water-related environmental efficiency. Beyond the viticulture sector, the proposed model is anticipated to act as a paradigm for setting joint sustainable targets or caps to limit water use across supply chains.
Traceability Information Model for Sustainability of Black Soybean Supply Chain: A Systematic Literature Review
Authors: Anwar Syaiful , Perdana Tomy , Rachmadi Meddy , Noor Trisna Insan
Published: August 2022

Traceability information as a solution option becomes an important task for the industry in providing products, preparing sustainable raw materials, and ensuring adequate safety quality. The emergence of these demands makes the industry perform tracking in order to prepare product inventories ranging from raw materials to products that have been produced. Based on these reasons, the scope of this paper is to provide a systematic review of the literature on various aspects of implementing information traceability models and sustainability of supply chain on economic, social, environmental, technological, institutional, and infrastructural dimensions. For this purpose, we use the Scopus, Science Direct, EBSCO Host, and ProQuest databases. We used the PRISMA model to identify, filter, and test for the eligibility of articles to be included. We selected 52 articles contributed by this search engine. We found was that between 2018 to 2021 there was increasing interest in this research. The dominant traceability information model in the article uses blockchain, the rest use operations research (OR), Google Earth Engine (GEE), website-based, Unified Modeling Language (UML), Extensible Markup Language (XML), physical markup language (PML), logit, enterprise resource planning (ERP), soft independent modelling of class analogies (SIMCA), and Spatially Explicit Information on Production to Consumption Systems (SEI-PCS).
Asymmetric Height Distribution of Surfaces Machined by Hard Turning and Grinding
Authors: Molnar Viktor
Published: August 2022

The asymmetric height distribution of a machined surface can be useful from a tribological point of view in several cases. The purpose of this study is to analyze this asymmetry based on the 3D surface texture parameter skewness, providing technological parameter values that help in achieving favorable surfaces. A 16MnCr5 case-hardened steel (62–63 HRC) was machined by hard turning and grinding based on a comprehensive design of experiments and the topography of the surfaces was measured and analyzed. The texture parameter that informs about the height distribution of the surface points (skewness, Ssk) was compared to the volume parameters peak material volume (Vmp) and valley void volume (Vvv). The main finding is that negative Ssk values are found at low Vmp and Vvv values, which confirms the favorable tribological properties.