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This paper examines the problem of lack of historical data and inadequate consideration of factors influencing demand in the forecasting of demand for fast fashion clothing and proposes an improved Bass model for the forecasting of such a demand and the demand for new clothing products.

From the perspective of how to solve the lack of data and improve the precision of the clothing demand forecast, this paper studies the measurement of clothing similarity and the addition of demand impact factors. Using the fuzzy clustering–rough set method, the degree of resemblance of clothing is determined, which provides a basis for the scientific utilisation of historical data of similar clothing to forecast the demand for new clothing. Besides, combining the influence of consumer preferences and seasonality on demand forecasting, an improved Bass model for a fast fashion clothing demand forecast is proposed. Finally, with a forecasting example of demand for clothing, this study also tests the validity of the method.

The objective measurement method of clothing similarity in this paper solves the problem of the difficult forecasting of demand for fast fashion clothing due to a lack of sales data at the preliminary stage of the clothing launch. The improved Bass model combines, comprehensively, consumer preferences and seasonality and enhances the forecast precision of demand for fast fashion clothing.

The paper puts forward a scientific, quantitative method for the forecasting of new clothing products using historical sales data of similar clothing, thus solving the problem of lack of sales data of the fashion.

Man has been seeking an ideal existence for a very long time. In this existence, justice, love, and peace are no longer words, but actual experiences. How ever, with the American preemptive invasion and occupation of Afghanistan and Iraq and the subsequent prisoner abuse, such an existence seems to be farther and farther away from reality. The purpose of this work is to stop this dangerous trend by promoting justice, love, and peace through a change of the paradigm that is inconsistent with justice, love, and peace. The strong paradigm that created the strong nation like the U.S. and the strong man like George W. Bush have been the culprit, rather than the contributor, of the above three universal ideals. Thus, rather than justice, love, and peace, the strong paradigm resulted in in justice, hatred, and violence. In order to remove these three and related evils, what the world needs in the beginning of the third millenium is the weak paradigm. Through the acceptance of the latter paradigm, the golden mean or middle paradigm can be formulated, which is a synergy of the weak and the strong paradigm. In order to understand properly the meaning of these paradigms, however, some digression appears necessary.

The deposition of particles onto a substrate during the cold spraying (CS) process relies on severe plastic deformation, so there are various micro-defects induced by insufficient deformation and severe crushing. To solve the problems, many post-treat techniques have been used to improving the quality by eliminating the micro-defects. This paper aims to help scholars and engineers in this field a better and systematic understand of CS technology by summarizing the post-treatment technologies that have been investigated recently years.

This review summarizes the types of micro-defects and introduces the effect of micro-defects on the properties of CS coating/additive manufactured, illustrates the post-treatment technologies and its effect on the microstructure and performances, and finally outlooks the future development trends of post-treatments for CS.

There are significant discoveries in post-treatment technology to change the performance of cold spray deposits. There are also many limitations for post-treatment methods, including improved performance and limitations of use. Thus, there is still a strong requirement for further improvement. Hybrid post-treatment may be a more ideal method, as it can eliminate more defects than a single method. The proposed ultrasonic impact treatment could be an alternative method, as it can densify and flatten the CS deposits.

It is the first time to reveal the influence factors on the performances of CS deposits from the perspective of microdefects, and proposed corresponding well targeted post-treatment methods, which is more instructive for improving the performances of CS deposits.

This paper aims to control the deformation of a thin wall CrZrCu cylinder components (wall thickness 5 mm, diameter 400 mm) during thermal spray alumina-titania (AT13) coating by adjusting the spray parameters without deteriorating its quality evidently.

The deformation was controlled by lowering the temperature of the component in the way of adjusting the spray parameters. The main parameters adjust included extending the spraying distance, from normally 120 mm to 140 mm, decreasing plasma power from 50to 42 kW. An alumina-titanium (AT13) ceramic coating was chosen for protecting the substrate from corrosion. Microscopic morphology and phase analysis, insulation resistance testing, neutral salt test and electrochemical method were used to analyze the anti-corrosion and insulation performances of the coating.

The results indicate that, after adjusting the spraying parameters, the coating has a relatively high porosity, with an average value of 8.96 ± 0.77%. The bonding strength of the coating is relatively low, with an average value of 17.69 ± 0.85 MPa. However, after sealing, the polarization resistance of the coating in seawater can be maintained above 6.25 × 10⁶ Ω.cm² for an extended period. The coating has a high resistance (=1.1 M Ω), and there is no apparent galvanic corrosion when contacted with TC4 alloy. Additionally, analysis of corrosion products on the sample surface reveals that the samples with sprayed alumina-titanium ceramic show no copper corrosion products on the surface, and the coating remains intact, effectively isolating the corrosive medium.

By adjusting the spraying parameters, the deformation of the cylinder thin-walled component can be effectively controlled, making the φ 400 × 392 mm (thickness 5 mm) CrZrCu cylinder com-ponent with a maximum diameter deformation of only 0.14 mm. The satisfactory corrosion performances can be achieved under adjusting spraying parameters, which can guarantee the application of ceramic coating for weapon launching system of naval ships.

The purpose of this paper is to examine the performance of cold-sprayed Zn15Al alloy coating whether it is capable of protecting magnesium alloy from corrosion, and to compare it with arc-sprayed Zn15Al alloy coating.

In this paper, Zn15Al alloy coating was prepared with CS-6000 cold spraying system and HDX-800 arc-sprayed system. Corrosion behaviors of the two kinds of coatings were examined with potentiodynamic polarization curves methods combined with SEM, EDS, XRD, etc.

Corrosion behavior of cold-sprayed Zn15Al alloy coating is superior to arc-sprayed Zn15Al alloy coating. The bonding strength and density of cold-sprayed Zn15Al alloy coating is much higher than that of arc-sprayed Zn15Al alloy coating. The cold-sprayed coating has a dense structure which separate magnesium from corrosion medium completely. The samples behave as Zn15Al instead of AZ91D alloy. The coating has a low probability of pitting corrosion comparing with cold sprayed Al coating through potentiodynamic polarization curve.

Cold-sprayed Zn15Al coating can be used to improve the anticorrosion performance of magnesium significantly and low down the risk of pitting corrosion of coating.

Cold-sprayed Zn15Al coating is an environmentally friendly anticorrosion method for light alloy, which is also the most effective way among thermal spray, chemical vapor deposition, sol–gel, plating and anodizing or microarc oxidation.

The present paper used cold spray method to deposit Zn15Al coating, which has an overwhelming performance both in physical and anticorrosion to traditional thermal spray method.

With the continuous increase in Web services, efficient identification of Web services that meet developers’ needs and understanding their relationships remains a challenge. Previous research has improved recommendation effectiveness by using correlations between Web services through graph neural networks (GNNs), while it has not fully leveraged service descriptions, limiting the depth and diversity of learning. To this end, a Web services recommendation method called LLMSARec, based on Large Language Model and semantic alignment, is proposed. This study aims to extract potential semantic information from services and learn deeper relationships between services.

This method consists of two core modules: profile generation and maximizing mutual information. The profile generation module uses LLM to analyze the descriptions of services, infer and construct service profiles. Concurrently, it uses LLM as text encoders to encode inferred service profiles for enhanced service representation learning. The maximizing mutual information model aims to align the semantic features of the services text inferred by LLM with structural semantic features of the services captured by GNNs, thus achieving a more comprehensive representation of services. The aligned representation serves as an input for the model to identify services with superior matching accuracy, thereby enhancing the service recommendation capability.

Experimental comparisons and analyses were conducted on the Programmable Web platform data set, and the results demonstrated that the effectiveness of Web service recommendations can be significantly improved by using LLMSARec.

In this study, the authors propose a Web service recommendation approach based on Large Language Model and semantic alignment. By extracting latent semantic information from services and effectively aligning semantic features with structural features, new representations can be generated to significantly enhance recommendation accuracy.

Step length is a key factor for pedestrian dead reckoning (PDR), which affects positioning accuracy and reliability. Traditional methods are difficult to handle step length estimation of dynamic gait, which have larger error and are not adapted to real walking. This paper aims to propose a step length estimation method based on frequency domain feature analysis and gait recognition for PDR, which considers the effects of real-time gait.

The new step length estimation method transformed the acceleration of pedestrians from time domain to frequency domain, and gait characteristics of pedestrians were obtained and matched with different walking speeds.

Many experiments are conducted and compared with Weinberg and Kim models, and the results show that the average errors of the new method were improved by about 2 meters to 5 meters. It also shows that the proposed method has strong stability and device robustness and meets the accuracy requirements of positioning.

A sliding window strategy used in fast Fourier transform is proposed to implement frequency domain analysis of the acceleration, and a fast adaptive gait recognition mechanism is proposed to identify gait of pedestrians.

The purpose of this paper is to efficiently use as few sample points as possible to get a sufficiently explored design space and an accurate optimum for adaptive metamodel-based design optimization (AMBDO).

A parameterized lower confidence bounding (PLCB) scheme is proposed in which a cooling strategy is introduced to guarantee the balance between exploitation and exploration by varying weights of the predicting error and optimum of a metamodel. The proposed scheme is investigated by a set of test functions and a structural optimization problem, in which PLCB with four kinds of cooling control functions are studied. Moreover, other infill criteria (such as expected improvement and its extension versions) are taken into comparison.

Results show that the proposed PLCB (especially PLCB with the first cooling control function) based AMBDO method can find the optimum with fewer evaluations and maintain good accuracy, which means the proposed PLCB contributes to the excellent efficiency and accuracy in finding global optimal solutions.

The parameterized version of the lower confidence bound metric is proposed for AMBDO, typically used in the context of adaptive sampling in efficient global optimization.

This paper aims to verify weather atmospheric plasma spray (APS) in situ remelting posttreatment is effective for densifying the porous FeCoCrMoCBY amorphous alloy (FAA) coating and improving the antiabrasion and anticorrosion performances or not.

APS was used to deposit and in situ densify FAA coating on the 40Cr substrate. Scanning electron microscope, X-ray diffractometer, energy dispersive spectroscopy, neutral salt spray, hardness and wear behavior test were used to evaluate the densifying effects.

APS remelting technology can effectively improve the hardness of the coating by reducing the porosity. After remelting at 30 kW power, the hardness of the coating increased by about 260 HV0.2 and the porosity decreased to 2.78%. The amorphous content of the coating is 93.9%, which is about 3.5% lower than original powders. The electrochemical impedance spectrum and neutral salt spray test results show that APS remelting can reduce the corrosion rate by about 62.7%.

APS remelting method is firstly proposed in this work to replace laser remelting or laser cladding methods. APS remelting method can effectively improve the corrosion and abrasion resistance of the FAA coating by increasing the densification with much low recrystallization, which is big progress for application of FAA coatings.

This paper aims to examine the performance of low-pressure cold-sprayed zinc–nickel (Zn-Ni) composites coating, i.e. whether it has the same performance as Zn-Ni alloy coating.

In this paper, Zn-Ni composites coatings containing four different nickel contents were prepared with commercial DYMET 413 low-pressure cold spraying system under the same parameters. Corrosion behaviors of four kinds of coatings were examined with potentiodynamic polarization curves and electrochemical impedance spectroscopy methods, combined with scanning electron microscopy, energy-dispersive X-ray spectroscopy and X-ray diffraction.

Corrosion behavior of Zn-Ni composites coating is similar to Zn-Ni alloy coating. In the early stages of immersion, the anodic dissolution of zinc happens, which results in the formation of a zinc hydroxide layer. With the continuous infiltration of chloride ion, zinc hydroxide will get converted to zinc oxide, basic zinc chloride and basic zinc carbonate. The presence of nickel in coatings can prevent zinc hydroxide from converting into zinc oxide.

Further research should be done on improving the deposition efficiency, as the deposition efficiency of low-pressure cold spray is lower than 30 per cent.

Low-pressure cold spray coating can be used in cyclic dry/wet conditions to prolong the life of a steel structure.

Low-pressure cold spray Zn-Ni coating is an environmentally friendly anticorrosion method which can be used as an alternative of hexavalent chromium passivation coating.

Zn-Ni composite coating can be deposited on steel directly by low-pressure cold spray by mechanically mixing the powders together. The composite coating also has the same long-term anticorrosion performance as Zn-Ni alloy coating.