Zheng Jin, Xiaomin Ren, Chuanli Qin, Bohong Li, Shuai Quan and Xuduo Bai
The purpose of this paper is to develop feasible composite electrodes with a long cycle life and large specific capacitance and to investigate optimal ratio between aniline and…
Abstract
Purpose
The purpose of this paper is to develop feasible composite electrodes with a long cycle life and large specific capacitance and to investigate optimal ratio between aniline and activated carbon materials.
Design/methodology/approach
PANI/AC composite electrode materials were synthesised by in situ polymerisation of aniline on activated carbon with ammonium persulphate as oxidant. Hybrid supercapacitors are assembled by putting Ni‐MH battery separator between positive and negative electrodes. The electrochemical performances of PANI/AC composite electrode materials and supercapacitors are studied.
Findings
The results show that the optimal ratio between aniline and activated carbon is 1:1.08. The specific capacitance of polyaniline electrode materials is 956 F g−1. The specific capacitance of supercapacitors is 159.37 F g−1. This result could be attributed to the pseudocapacitive effect of Ni(OH)2. What's more, the activated carbon addition reduced the resistance of polymer electrode materials thus improving the cyclic life.
Research limitations/implications
The supercapacitors can be used in the field of automobiles and can solve the problems of energy shortage and environmental pollutions.
Originality/value
A hybrid supercapacitor, which was immersed in alkaline solution, was assembled by putting Ni‐MH battery separator between two electrodes Ni(OH)2 as positive electrode and polyaniline composites as negative electrode. In the case of alkaline solution, the capacitive performance of hybrid supercapacitor was improved and excellent.
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Shuai Yang, Bin Wang, Junyuan Tao, Zhe Ruan and Hong Liu
The 6D pose estimation is a crucial branch of robot vision. However, the authors find that due to the failure to make full use of the complementarity of the appearance and…
Abstract
Purpose
The 6D pose estimation is a crucial branch of robot vision. However, the authors find that due to the failure to make full use of the complementarity of the appearance and geometry information of the object, the failure to deeply explore the contributions of the features from different regions to the pose estimation, and the failure to take advantage of the invariance of the geometric structure of keypoints, the performances of the most existing methods are not satisfactory. This paper aims to design a high-precision 6D pose estimation method based on above insights.
Design/methodology/approach
First, a multi-scale cross-attention-based feature fusion module (MCFF) is designed to aggregate the appearance and geometry information by exploring the correlations between appearance features and geometry features in the various regions. Second, the authors build a multi-query regional-attention-based feature differentiation module (MRFD) to learn the contribution of each region to each keypoint. Finally, a geometric enhancement mechanism (GEM) is designed to use structure information to predict keypoints and optimize both pose and keypoints in the inference phase.
Findings
Experiments on several benchmarks and real robot show that the proposed method performs better than existing methods. Ablation studies illustrate the effectiveness of each module of the authors’ method.
Originality/value
A high-precision 6D pose estimation method is proposed by studying the relationship between the appearance and geometry from different object parts and the geometric invariance of the keypoints, which is of great significance for various robot applications.
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Vahid Nikpey Pesyan, Yousef Mohammadzadeh, Ali Rezazadeh and Habib Ansari Samani
The study aims to examine the impact of cultural dependency stemming from exchange rate fluctuations (specifically the US dollar) on herding behavior in the housing market across…
Abstract
Purpose
The study aims to examine the impact of cultural dependency stemming from exchange rate fluctuations (specifically the US dollar) on herding behavior in the housing market across 31 provinces of Iran from Q2 2011 to Q1 2022, using a spatial econometrics approach. After confirming the presence of spatial effects, the Dynamic Spatial Durbin Panel Model with Generalized Common Effects (SDM-DPD(GCE)) was selected from various spatial models for these provinces.
Design/methodology/approach
The study examines the impact of cultural dependency stemming from exchange rate fluctuations (specifically the US dollar) on herding behavior in the housing market across 31 provinces of Iran from Q2 2011 to Q1 2022, using a spatial econometrics approach. After confirming the presence of spatial effects, the Dynamic Spatial Durbin Panel Model with Generalized Common Effects (SDM-DPD(GCE)) was selected from various spatial models for these provinces.
Findings
The model estimation results indicate that fluctuations in the free market exchange rate of the dollar significantly and positively impact the housing market in both target and neighboring regions, fostering herding behavior characterized by cultural dependency within the specified timeframe. Additionally, the study found that variables such as the inflation rate, population density index and the logarithm of stock market trading volume have significant and positive impacts on the housing market. Conversely, the variable representing the logarithm of the distance from the provincial capital, Tehran, significantly and negatively impacts the housing market across Iranian provinces.
Originality/value
Given that housing is a fundamental need for households, the dramatic price increases in this sector (for instance, a more than 42-fold increase from 2011–2021) have significantly impacted the welfare of Iranian families. Currently, considering the average housing price in Tehran is around 50 million Tomans, and the average income of worker and employee groups is 8 million Tomans (as of 2021), the time required to purchase a 100-square-meter house, even with a 30% savings rate and stable housing prices, is approximately 180 years. Moreover, the share of housing and rent expenses in household budgets now constitutes about 70%. The speculative behavior in this market is so acute that, despite 25 million of Iran’s 87 million population being homeless or renting, over 2.5 million vacant homes (12% of the total housing stock) are not used. Therefore, various financial behaviors and decisions affect Iran’s housing market. Herd behavior is triggered by the signal of national currency devaluation (with currency exchange rates increasing more than 26-fold between 2011 and 2021) and transactions at higher prices in certain areas (particularly in northern Tehran) (Statistical Center of Iran, 2023). Given the origins of housing price surges, a price increase in one area quickly spreads to other regions, resulting in herd behavior in those areas (spillover effect). Consequently, housing market spikes in Iran tend to follow episodes of currency devaluation. Therefore, considering the presented discussions, one might question whether factors other than economic ones (such as herd behavior influenced by dependence culture) play a role in the rising housing prices. Or, if behavioral factors were indeed contributing to the increase in housing prices, what could be the cause of this herd movement? Has the exchange rate, particularly fluctuations in the free market dollar rate, triggered herd behavior in the housing market across Iran’s provinces? Or has the proximity and neighborhood effect been influential in the increase or decrease in housing prices in the market?
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The objective of this paper is to investigate the impact of the information sharing of the dynamic demand on green technology innovation and profits in supply chain from a…
Abstract
Purpose
The objective of this paper is to investigate the impact of the information sharing of the dynamic demand on green technology innovation and profits in supply chain from a long-term perspective.
Design/methodology/approach
The authors consider a supply chain consisting of a manufacturer and a retailer. The retailer has access to the information of dynamic demand of the green product, whereas the manufacturer invests in green technology innovation. Differential game theory is adopted to establish three models under three different scenarios, namely (1) decentralized decision without information sharing of dynamic demand (Model N-D), (2) decentralized decision with information sharing of dynamic demand (Model S-D) and (3) centralized decision with information sharing of dynamic demand (Model S-C).
Findings
The optimal equilibrium results show that information sharing of dynamic demand can improve the green technology innovation level and increase the green technology stocks only in centralized supply chain. In the long term, the information sharing of dynamic demand can make the retailer more profitable. If the influence of green technology innovation on green technology stocks is great enough or the cost coefficient of green technology innovation is small enough, the manufacturer and decentralized supply chain can benefit from information sharing. In centralized supply chain, the value of demand information sharing is greater than that of decentralized supply chain.
Originality/value
The authors used game theory to investigate demand information sharing and the green technology innovation in a supply chain. Specially, the demand information is dynamic, which is a variable that changes over time. Moreover, our research is based on a long-term perspective. Thus, differential game is adopted in this paper.
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Adib Bin Rashid, Abu Saleh Md. Nakib Uddin, Fahima Akter Azrin, Khondker Safin Kaosar Saad and Md Enamul Hoque
The main objective of this paper is to illustrate an analytical view of different methods of 3D bioprinting, variations, formulations and characteristics of biomaterials. This…
Abstract
Purpose
The main objective of this paper is to illustrate an analytical view of different methods of 3D bioprinting, variations, formulations and characteristics of biomaterials. This review also aims to discover all the areas of applications and scopes of further improvement of 3D bioprinters in this era of the Fourth Industrial Revolution.
Design/methodology/approach
This paper reviewed a number of papers that carried evaluations of different 3D bioprinting methods with different biomaterials, using different pumps to print 3D scaffolds, living cells, tissue and organs. All the papers and articles are collected from different journals and conference papers from 2014 to 2022.
Findings
This paper briefly explains how the concept of a 3D bioprinter was developed from a 3D printer and how it affects the biomedical field and helps to recover the lack of organ donors. It also gives a clear explanation of three basic processes and different strategies of these processes and the criteria of biomaterial selection. This paper gives insights into how 3D bioprinters can be assisted with machine learning to increase their scope of application.
Research limitations/implications
The chosen research approach may limit the generalizability of the research findings. As a result, researchers are encouraged to test the proposed hypotheses further.
Practical implications
This paper includes implications for developing 3D bioprinters, developing biomaterials and increasing the printability of 3D bioprinters.
Originality/value
This paper addresses an identified need by investigating how to enable 3D bioprinting performance.
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Prathamesh Gaikwad and Sandeep Sathe
The purpose of this paper is to study and analyze the effects of fly ash (FA) as a mineral admixture on compressive strength (CS), carbonation resistance and corrosion resistance…
Abstract
Purpose
The purpose of this paper is to study and analyze the effects of fly ash (FA) as a mineral admixture on compressive strength (CS), carbonation resistance and corrosion resistance of reinforced concrete (RC). In addition, the utilization of inexpensive and abundantly available FA as a cement replacement in concrete has several benefits including reduced OPC usage and elimination of the FA disposal problem.
Design/methodology/approach
Reinforcement corrosion and carbonation significantly affect the strength and durability of the RC structures. Also, the utilization of FA as green corrosion inhibitors, which are nontoxic and environmentally friendly alternatives. This review discusses the effects of FA on the mechanical characteristics of concrete. Also, this review analyzes the impact of FA as a partial replacement of cement in concrete and its effect on the depth of carbonation in concrete elements and the corrosion rate of embedded steel as well as the chemical composition and microstructure (X-ray diffraction analysis and scanning electron microscopy) of FA concrete were also reviewed.
Findings
This review provides a clear analysis of the available study, providing a thorough overview of the current state of knowledge on this topic. Regarding concrete CS, the findings indicate that the incorporation of FA often leads to a loss in early-age strength. However, as the curing period increased, the strength of fly ash concrete (FAC) increased with or even surpassed that of conventional concrete. Analysis of the accelerated carbonation test revealed that incorporating FA into the concrete mix led to a shallower carbonation depth and slower diffusion of carbon dioxide (CO2) into the concrete. Furthermore, the half-cell potential test shows that the inclusion of FA increases the durability of RC by slowing the rate of steel-reinforcement corrosion.
Originality/value
This systematic review analyzes a wide range of existing studies on the topic, providing a comprehensive overview of the research conducted so far. This review intends to critically assess the enhancements in mechanical and durability attributes (such as CS, carbonation and corrosion resistance) of FAC and FA-RC. This systematic review has practical implications for the construction and engineering industries. This can support engineers and designers in making informed decisions regarding the use of FA in concrete mixtures, considering both its benefits and potential drawbacks.
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Muhittin Sagnak, Yigit Kazancoglu, Yesim Deniz Ozkan Ozen and Jose Arturo Garza-Reyes
The aim of the present study is to overcome some of the limitations of the FMEA method by presenting a theoretical base for considering risk evaluation into its assessment…
Abstract
Purpose
The aim of the present study is to overcome some of the limitations of the FMEA method by presenting a theoretical base for considering risk evaluation into its assessment methodology and proposing an approach for its implementation.
Design/methodology/approach
Fuzzy AHP is used to calculate the weights of the likelihood of occurrence (O), severity (S) and difficulty of detection (D). Additionally, the prospect-theory-based TODIM method was integrated with fuzzy logic. Thus, fuzzy TODIM was employed to calculate the ranking of potential failure modes according to their risk priority numbers (RPNs). In order to verify the results of the study, in-depth interviews were conducted with the participation of industry experts.
Findings
The results are very much in line with prospect theory. Therefore, practitioners may apply the proposed method to FMEA. The most crucial failure mode for a firm's attention is furnace failure followed by generator failure, crane failure, tank failure, kettle failure, dryer failure and operator failure, respectively.
Originality/value
The originality of this paper consists in integrating prospect theory with the FMEA method in order to overcome the limitations naturally inherent in the calculation of the FMEA's RPNs.
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Yongsheng Zhao, Jiaqing Luo, Ying Li, Caixia Zhang and Honglie Ma
The combination of improved PSO (IPSO) algorithm and artificial neural network (ANN) model for intelligent monitoring of the bearing performance of the hydrostatic turntable.
Abstract
Purpose
The combination of improved PSO (IPSO) algorithm and artificial neural network (ANN) model for intelligent monitoring of the bearing performance of the hydrostatic turntable.
Design/methodology/approach
This paper proposes an artificial neural network model based on IPSO algorithm for intelligent monitoring of hydrostatic turntables.
Findings
The theoretical model proposed in this paper improves the accuracy of the working performance of the static pressure turntable and provides a new direction for intelligent monitoring of the static pressure turntable. Therefore, the theoretical research in this paper is novel.
Originality/value
Theoretical novelties: an ANN model based on the IPSO algorithm is designed to monitor the load-bearing performance of a static pressure turntable intelligently; this study show that the convergence accuracy and convergence speed of the IPSO-NN model have been improved by 52.55% and 10%, respectively, compared to traditional training models; and the proposed model could be used to solve the multidimensional nonlinear problem in the intelligent monitoring of hydrostatic turntables.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2024-0081/
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Rusty Stough and Christian Graham
Access to media is more available now than ever before, both physically and digitally. This study was used to investigate the underlying personality traits that influence the…
Abstract
Purpose
Access to media is more available now than ever before, both physically and digitally. This study was used to investigate the underlying personality traits that influence the decision to purchase either physical or digital books, and extend theory on access to art and provide a unique lens through which marketers can sell digital media.
Design/methodology/approach
Study 1 is a field study in which data were collected from several comic book readers and collectors to look at the role that psychological ownership plays in influencing the likelihood of buying physical or digital comics. Specifically, study 1 includes consumers' need for uniqueness and tech savviness as potential influencers. Study 2 extends the findings of study into a new context and manipulates, rather than measures, the identity of the participants. Study 2 looks at the effects of turning a digital object into a non-fungible token (NFT).
Findings
This paper demonstrates that consumers who have a high consumer need for uniqueness (CNFU) are more likely to prefer physical media to digital media. Further, it is shown that preference for physical media leads, on average, to more purchases and that the consumer's psychological ownership mediates the effects of CNFU. In addition, this paper shows that higher degrees of tech savviness led to a preference for digital media. Finally, this paper shows that when consumers identify with a collector identity, turning a digital item into an NFT increases their preference for that object.
Originality/value
This work builds off recent research into physical and digital media and is one of the first to examine the specific personality types that prefer each.