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The advanced technology enables retailers to develop customer profile analysis (CPA) to implement personalized pricing. However, considering the efficiency of developing CPA, the benefit to different retailers of implementing more precise personalized pricing remains unclear. Thus, this essay aimed to investigate the impact of efficiency on participants’ strategies and profits in the supply chain.

A two-stage game model was introduced in the presence of a manufacturer who sets his wholesale price and a retailer that decides her CPA strategy. The equilibrium results were generated by backward induction.

Most retailers are willing to develop the highest CPA to implement perfect personalized pricing, but those inefficient retailers with high production costs would like to determine a middle CPA to implement bounded personalized pricing. The retailers’ profits may decrease with the efficiency of developing CPA when the efficiency is middle. In this case, as the efficiency improves, the manufacturer increases the wholesale price, resulting in lower demand and thus lower profits. Moreover, define a Pareto Improvement (PI) strategy as one that benefits both manufacturers and retailers. Therefore, uniform pricing is a PI when the unit cost is high and the efficiency is low; personalized pricing is a PI when the unit cost is low and the efficiency is low or high; otherwise, there is no PI.

This study is the first that investigates how the retailer develops CPA to implement personalized pricing on a comprehensive spectrum, which can provide practical insights for retailers with different efficiencies.

In response to the severe lag in tracking the response of the Stewart stability platform after adding overload, as well as the impact of nonlinear factors such as load and friction on stability accuracy, a new error attenuation function and a parallel stable platform active disturbance rejection control (ADRC) strategy combining cascade extended state observer (ESO) are proposed.

First, through kinematic modeling of the Stewart platform, the relationship between the desired pose and the control quantities of the six hydraulic cylinders is obtained. Then, a linear nonlinear disturbance observer was established to observe noise and load, to enhance the system’s anti-interference ability. Finally, verification was conducted through simulation.

Finally, stability analysis was conducted on the cascaded observer. Experiments were carried out on a parallel stable platform with six degrees of freedom involving rotation and translation. In comparison to traditional PID and ADRC control methods, the proposed control strategy not only endows the stable platform with strong antiload disturbance capability but also exhibits faster response speed and higher stability accuracy.

A new error attenuation function is designed to address the lack of smoothness at d in the error attenuation function of the ADRC controller, reducing the system ripple caused by it. Finally, a combination of linear and nonlinear ESOs is introduced to enhance the system's response speed and its ability to observe noise and load disturbances. Stability analysis of the cascade observer is carried out, and experiments are conducted on a six-degree-of-freedom parallel stable platform with both rotational and translational motion.

This study aimed to improve the financing credit evaluation for small and medium-sized real estate enterprises (SMREEs). A financing credit evaluation model was proposed, and a blockchain-driven financing credit evaluation framework was designed to improve the transparency, credibility and applicability of the financing credit evaluation process.

The design science research methodology was adopted to identify the main steps in constructing the financing credit model and blockchain-driven framework. The fuzzy analytic hierarchy process (FAHP)–entropy weighting method (EWM)–set pair analysis (SPA) method was used to design a financing credit evaluation model. Moreover, the proposed framework was validated using data acquired from actual cases.

The results indicate that: (1) the proposed blockchain-driven financing credit evaluation framework can effectively realize a transparent evaluation process compared to the traditional financing credit evaluation system. (2) The proposed model has high effectiveness and can achieve efficient credit ranking, reflect SMREEs' credit status and help improve credit rating.

This study proposes a financing credit evaluation model of SMREEs based on the FAHP–EWM–SPA method. All credit rating data and evaluation process data are immediately stored in the proposed blockchain framework, and the immutable and traceable nature of blockchain enhances trust between nodes, improving the reliability of the financing credit evaluation process and results. In addition, this study partially fulfills the lack of investigations on blockchain adoption for SMREEs' financing credit.

The purpose of this study is to provide a micro-nano chip automatic alignment system. Used for micron and nanometer channel alignment of microfluidic chip.

In this paper, combined with the reconstructed micro–nanoscale Hough transform theory, a “clamp–adsorb–rotate” chip alignment method is proposed. The designed alignment system includes a microscopic identification device, a clamping device and a suction device. After assembly, the straightness of the linear slide rail in the horizontal and vertical directions was tested, respectively. The results show that in the horizontal and vertical directions, the linearity error of the linear slide is +0.29 and 0.30 µm, respectively, which meets the requirement of chip alignment accuracy of 15 µm. In the direction of rotation, the angular error between the microchannel and the nanochannel is ±0.5°. In addition, an alignment flow experiment of the chip is designed. The results demonstrate that the closer the angle between the microchannel and the nanochannel is to 90°, the fluid fills the entire channel. Compared with the conventional method, the method and the assembly system realize fully automatic double-layer chip alignment.

A mechanical device designed by Hough transform theory can realize microfluidic chip alignment at nanometer and micron level.

The automatic alignment device adopts Hough transform principle and can be used for microfluidic chip alignment.

A robotic wheelchair system was designed to assist disabled people with disabilities to walk.

An anticipated sharing control strategy based on topological map is proposed in this paper, which is used to assist robotic wheelchairs to realize interactive navigation. Then, a robotic wheelchair navigation control system based on the brain-computer interface and topological map was designed and implemented.

In the field of robotic wheelchairs, the problems of poor use, narrow application range and low humanization are still not improved.

In the system, the topological map construction is not restricted by the environment structure, which helps to expand the scope of application; the shared control system can predict the users’ intention and replace the users’ decision to realize human-machine interactive navigation, which has higher security, robustness and comfort.

This paper aims to understand the influences of tris (2-hydroxyethyl) isocyanurate oleate and oleic acid tris (2-hydroxyethyl) isocyanurate phosphate ester on biodegradability and tribological performances of mineral lubricating oil.

Tris (2-hydroxyethyl) isocyanurate oleate and oleic acid tris (2-hydroxyethyl) isocyanurate phosphate ester were prepared and characterized by Fourier transform infrared spectrometer. The biodegradability and tribological properties of neat oil and its formulations were studied on a tester for fast evaluating biodegradability of lubricants and a four-ball tester, respectively. The worn surfaces were investigated by scanning electron microscope and X-ray photoelectron spectroscope.

Tris (2-hydroxyethyl) isocyanurate oleate and oleic acid tris (2-hydroxyethyl) isocyanurate phosphate ester both improved markedly the biodegradability, the anti-wear properties, friction-reducing properties and extreme pressure properties of base oil. The effect of oleic acid tris (2-hydroxyethyl) isocyanurate phosphate ester was better than tris (2-hydroxyethyl) isocyanurate oleate. The improvement of tribological performances was mainly ascribed to the formation of a complicated boundary lubrication film of tris (2-hydroxyethyl) isocyanurate oleate and oleic acid tris (2-hydroxyethyl) isocyanurate phosphate ester on the friction surfaces.

This paper has indicated that tris (2-hydroxyethyl) isocyanurate oleate and oleic acid tris (2-hydroxyethyl) isocyanurate phosphate ester effectively improve the biodegradability and tribological performances of mineral lubricating oil. Promoting biodegradation of mineral lubricant by additives is very significant for the development of petroleum-based biodegradable lubricants. These two additives not merely improve the tribological performances; more importantly, they improve the ecological performances.

Flexible pressure sensor arrays have promising applications in analog haptics, reconfiguration of sensory functions, artificial intelligence, wearable devices and human-computer interaction. The force disturbance generated by the connecting material between the sensor array units will reduce the detection accuracy of the unit. The purpose of this paper is to propose a flexible pressure sensor with interference immunity capability. A C-type bridge flexible piezoelectric structure is used to improve the pressure perturbation. The interference immunity capability of the sensor has been improved.

In this paper, a C-type pressure sensor array structure by rapid injection moulding is manufactured through the positive piezoelectric effect of a piezoelectric material. The feasibility of C-type interference immunity structure in a flexible sensor array is verified by further analysis and experiment. A flexible pressure sensor array with C-type interference immunity structure has been proposed.

In this paper, we present the results of the perturbation experiment results of the C-type pressure sensor array, showing that the perturbation error is less than 8%. The test of the flexible sensor array show that the sensor can identify the curved angle of up to 120 °, and the output sensitivity of the sensor in the horizontal state reaches 0.12 V/N, and the sensor can withstand the pressure of 80 N. The flexible sensor can work stably in the stretch rate range of 0–8.6% and the stretch length range of 0–6 mm.

In this paper, C-type pressure sensor array structure is fabricated by rapid injection moulding for the first time. The research in this paper can effectively reduce the disturbance of input pressure on the sensor’s internal array and improve the output accuracy. The sensor can intuitively reflect the number of fingers sliding on the sensor by the order in which the maximum voltage appears. Due to the strong interference immunity capability and flexibility of the flexible sensor array mechanism, it has a broad application prospect in the practical fields of haptic simulation, perceptual function reconstruction, artificial intelligence, wearable devices and human–computer interaction.

The COVID-19 pandemic has spurred a concurrent outbreak of false information online. Debunking false information about a health crisis is critical as misinformation can trigger protests or panic, which necessitates a better understanding of it. This exploratory study examined the effects of debunking messages on a COVID-19-related public chat on WhatsApp in Singapore.

To understand the effects of debunking messages about COVID-19 on WhatsApp conversations, the following was studied. The relationship between source credibility (i.e. characteristics of a communicator that affect the receiver's acceptance of the message) of different debunking message types and their effects on the length of the conversation, sentiments towards various aspects of a crisis, and the information distortions in a message thread were studied. Deep learning techniques, knowledge graphs (KG), and content analyses were used to perform aspect-based sentiment analysis (ABSA) of the messages and measure information distortion.

Debunking messages with higher source credibility (e.g. providing evidence from authoritative sources like health authorities) help close a discussion thread earlier. Shifts in sentiments towards some aspects of the crisis highlight the value of ABSA in monitoring the effectiveness of debunking messages. Finally, debunking messages with lower source credibility (e.g. stating that the information is false without any substantiation) are likely to increase information distortion in conversation threads.

The study supports the importance of source credibility in debunking and an ABSA approach in analysing the effect of debunking messages during a health crisis, which have practical value for public agencies during a health crisis. Studying differences in the source credibility of debunking messages on WhatsApp is a novel shift from the existing approaches. Additionally, a novel approach to measuring information distortion using KGs was used to shed insights on how debunking can reduce information distortions.

Synthetic aperture radar (SAR) imaging is the most computational intensive algorithm and this makes its implementation challenging for real-time application. This paper aims to present the chirp-scaling algorithm (CSA) for real-time SAR applications, using advanced field programmable gate array (FPGA) processor.

A chirp signal is generated and compressed using range Doppler algorithm in MATAB for validation. Fast Fourier transform (FFT) and multiplication operations with complex data types are the major units requiring heavy computation. Therefore, hardware acceleration is proposed and implemented on NEON-FPGA processor using NE10 and CEPHES library.

The heuristic analysis of the algorithm using timing analysis and resource usage is presented. It has been observed that FFT execution time is reduced by 61% by boosting the performance of the algorithm and speed of multiplication operation has been doubled because of the optimization.

Very few literatures have presented the FPGA-based SAR imaging implementation, where analysis of windowing technique was a major interest. This is a unique approach to implement the SAR CSA using a hybrid approach of hardware–software integration on Zynq FPGA. The timing analysis propagates that it is suitable to use this model for real-time SAR applications.

With the increasing number of mobile applications, efficiently recommending mobile applications to users has become a challenging problem. Although existing mobile application recommendation approaches based on user attributes and behaviors have achieved notable effectiveness, they overlook the diffusion patterns and interdependencies of topic-specific mobile applications among user groups. mobile applications among user groups. This paper aims to capture the diffusion patterns and interdependencies of mobile applications among user groups. To achieve this, a topic-aware neural network-based mobile application recommendation method, referred to as TN-MR, is proposed.

In this method, first, the user representations are enhanced by introducing a topic-aware attention layer, which captures both the topic context and the diffusion history context. Second, it exploits a time-decay mechanism to simulate changes in user interest. Multitopic user representations are aggregated by the time decay module to output the user representations of cascading representations under multiple topics. Finally, user scores that are likely to download the mobile application are predicted and ranked.

Experimental comparisons and analyses were conducted on the actual 360App data set, and the results demonstrate that the effectiveness of mobile application recommendations can be significantly improved by using TN-MR.

In this paper, the authors propose a mobile application recommendation method based on topic-aware attention networks. By capturing the diffusion patterns and dependencies of mobile applications, it effectively assists users in selecting their applications of interest from thousands of options, significantly improving the accuracy of mobile application recommendations.