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The purpose of this paper is to study the microstructure and properties of Sn-3.5Ag and Sn-3.5Ag-0.5Sb lead-free solder alloys with and without a rotating magnetic field (RMF).

Optical microscopy, scanning electron microscopy and X-ray diffraction were used to analyze the effect of an RMF on the microstructure of the solders. Differential scanning calorimetry was used to study the influence of the RMF on the thermal characteristics of the solders. The mechanical properties of the alloys were determined by tensile measurements at different strain rates.

The ß-Sn grains and intermetallic compounds for the Sn-3.5Ag and Sn-3.5Ag-0.5Sb lead-free solder alloys were refined under an RMF, and the morphology of the ß-Sn grains changed from dendritic to equiaxed. The pasty range was significantly reduced under an RMF. The ultimate tensile strength (UTS) of Sn-3.5Ag improved under the RMF, whereas the UTS of Sn-3.5Ag-0.5Sb decreased slightly. The addition of Sb to the Sn-3.5Ag alloy significantly enhanced the UTS and elongation (El.%) of the samples. The UTS of the solder increased with increasing strain rate.

The results revealed that the application of RMF in the molten alloy had a significant effect on its microstructure and mechanical properties. The thermal characteristics of the Sn-3.5Ag and Sn-3.5Ag-0.5Sb solder alloys were improved under the RMF. This research is expected to fill a knowledge gap regarding the behaviour of Sn-Ag solder alloys under RMF.

The purpose of this paper is to solve the shortage of the existing methods for the prediction of network security situations (NSS). Because the conventional methods for the prediction of NSS, such as support vector machine, particle swarm optimization, etc., lack accuracy, robustness and efficiency, in this study, the authors propose a new method for the prediction of NSS based on recurrent neural network (RNN) with gated recurrent unit.

This method extracts internal and external information features from the original time-series network data for the first time. Then, the extracted features are applied to the deep RNN model for training and validation. After iteration and optimization, the accuracy of predictions of NSS will be obtained by the well-trained model, and the model is robust for the unstable network data.

Experiments on bench marked data set show that the proposed method obtains more accurate and robust prediction results than conventional models. Although the deep RNN models need more time consumption for training, they guarantee the accuracy and robustness of prediction in return for validation.

In the prediction of NSS time-series data, the proposed internal and external information features are well described the original data, and the employment of deep RNN model will outperform the state-of-the-arts models.

The purpose of this study is to investigate the effects of Ce and Sb doping on the microstructure and thermal mechanical properties of Sn-1.0Ag-0.5Cu lead-free solder. The effects of 0.5%Sb and 0.07%Ce doping on microstructure, thermal properties and mechanical properties of Sn-1.0Ag-0.5Cu lead-free solder were investigated.

According to the mass ratio, the solder alloys were prepared from tin ingot, antimony ingot, silver ingot and copper ingot with purity of 99.99% at 400°C. X-ray diffractometer was adopted for phase analysis of the alloys. Optical microscopy, scanning electron microscopy and energy dispersive spectrometer were used to study the effect of the Sb and Ce doping on the microstructure of the solder. Then, the thermal characteristics of alloys were characterized by a differential scanning calorimeter (DSC). Finally, the ultimate tensile strength (UTS), elongation (EL.%) and yield strength (YS) of solder alloys were measured by tensile testing machine.

With the addition of Sb and Ce, the ß-Sn and intermetallic compounds of solders were refined and distributed more evenly. With the addition of Sb, the UTS, EL.% and YS of Sn-1.0Ag-0.5Cu increased by 15.3%, 46.8% and 16.5%, respectively. The EL.% of Sn-1.0Ag-0.5Cu increased by 56.5% due to Ce doping. When both Sb and Ce elements are added, the EL.% of Sn-1.0Ag-0.5Cu increased by 93.3%.

The addition of 0.5% Sb and 0.07% Ce can obtain better comprehensive performance, which provides a helpful reference for the development of Sn-Ag-Cu lead-free solder.

Project portfolio benefit (PPB) evaluation is crucial for project portfolio management decisions. However, PPB is complex in composition and affected by synergy and ambidexterity. Ignoring these characteristics can result in inaccurate assessments, impeding the management and optimization of benefit. Considering the above complexity of PPB evaluation, this study aims to propose a refined PPB evaluation model to provide decision support for organizations.

A back propagation neural network optimized via genetic algorithm and pruning algorithm (P-GA-BPNN) is constructed for PPB evaluation. First, the benefit evaluation criteria are established. Second, the inputs and expected outputs for model training and testing are determined. Then, based on the optimization of BPNN via genetic algorithm and pruning algorithm, a PPB evaluation model is constructed considering the impacts of ambidexterity and synergy on PPB. Finally, a numerical example was applied to validate the model.

The results indicate that the proposed model can be used for effective PPB evaluation. Moreover, it shows superiority in terms of MSE and fitting effect through extensive comparative experiments with BPNN, GA-BPNN, and SVM models. The robustness of the model is also demonstrated via data random disturbance experiment and 10-cross-validation. Therefore, the proposed model could serve as a valuable decision-making tool for PPB management.

This study extends prior research by integrating the impacts of synergy and ambidexterity on PPB when conducting PPB evaluation, which facilitates to manage and enhance PPB. Besides, the structural redundancy of existing assessment methods is solved through the dynamic optimization of the network structure via the pruning algorithm, enhancing the effectiveness of PPB decision-making tools.

This study aims to take boutique luxury hotels as its research subject to enrich the view on the self-positioned image of luxury hotels and simultaneously compare this image with the one perceived by customers. It also investigates whether a gap exists between the two images.

The best-rated boutique luxury hotel in Hong Kong is selected as the case hotel. Through the interpretation and discussion of high-frequency wordlists and semantic co-occurrence network charts, major topics in the hotel’s self-presented image and customers’ perceived image are identified accordingly.

Five dimensions (event making, exquisite food, excellent amenities and services, special function venue and promotion) used by hotels to form their boutique luxury image are recognised. Between hotels’ self-positioned image and customers’ perceived images, minor similarities such as the recognition of excellent amenities and services were confirmed but considerable differences were identified, indicating the ineffective marketing by the boutique luxury hotel despite its success in terms of ranking. Managerial suggestions on how to address the image discrepancy were proposed.

This study contributes insights into hotel image discrepancy among social media platforms in luxury hotel segments by adding the category of boutique luxury hotels. It also identifies the implications for enhancing the development of a hotel image to meet customers’ needs and expectations.

酒店的自我定位形象与顾客感知形象——以香港某精品豪华酒店为例

本研究试图以精品豪华酒店为研究对象, 丰富豪华酒店自我定位形象的视角, 同时将其与顾客感知的形象进行比较, 考察二者之间是否存在差距。

本文选取香港评分最佳的精品豪华酒店为案例酒店。通过对高频词表和语义共现网络图的解读和讨论, 识别出酒店自我呈现形象和顾客感知形象中的主要话题。

酒店利用五个维度（活动打造、精致的食物、优质的设施和服务、特殊的功能场所和促销）来塑造其精品豪华形象。在酒店的自我定位形象和顾客的感知形象之间, 发现了一些细微的相似之处, 如对优质设施和服务的认可, 但差异之处相当大, 表明尽管精品豪华酒店取得了优秀的排名, 但其营销效果不佳。本文提出了解决形象差异的管理建议。

本研究通过增加精品豪华酒店类别的案例, 有助于深入了解豪华酒店细分市场中社交媒体平台之间的酒店形象差异。本文还确定了促进酒店形象发展的影响, 以满足客户需求和期望。

Imagen auto-posicionada del hotel versus imagen percibida por los clientes: un estudio de caso de un hotel boutique de lujo en Hong Kong.

Este estudio se esfuerza por tomar a los hoteles boutique de lujo como tema de investigación para profundizar en el conocimiento sobre la imagen de los hoteles de lujo y compar el posicionamiento presentado por el hotel con el que perciben los clientes. También investiga si existe una brecha entre las dos imágenes.

Para el caso se selecciona el mejor hotel de lujo calificado en Hong Kong. A través de la interpretación y discusión de listas de palabras de alta frecuencia y gráficos de redes de coincidencia semántica se identifican los principales temas en la imagen presentada por el hotel y la imagen percibida de los clientes.

Se reconocen cinco dimensiones (creación de eventos, comida exquisita, excelentes comodidades y servicios, lugar de funciones especiales y promoción) utilizadas por los hoteles para formar su imagen de lujo boutique. Entre la imagen auto-posicionada de los hoteles y las imágenes percibidas por los clientes, se confirmaron pequeñas similitudes, como el reconocimiento de excelentes comodidades y servicios, pero se identificaron diferencias considerables, lo que indica la comercialización ineficaz del hotel boutique de lujo a pesar de su éxito en términos de clasificación. Se propusieron sugerencias gerenciales sobre cómo abordar la discrepancia de imagen.

Este estudio aporta información sobre la discrepancia de imagen del hotel entre las plataformas de redes sociales en los segmentos de hoteles de lujo al agregar la categoría de hoteles boutique de lujo. También identifica las implicaciones para mejorar el desarrollo de una imagen de hotel que satisfaga las necesidades y expectativas del cliente.

With respect to severe working conditions such as heavy load and impact, this paper aims to investigate the friction reduction and anti-wear performance of kaolin and molybdenum dialkyl dithiophosphate (MoDDP) composite lubricant additives to improve the lubrication effect of a single additive.

A four-ball friction test was carried out to determine the optimal concentration of kaolin and organic molybdenum additives and the tribological properties of the kaolin/MoDDP composite lubricant additives. A ring block test of composite lubricant additives was designed to investigate its lubrication performance under the severe working conditions of low speed, heavy load and impact.

The results showed that the optimal addition mass fractions of kaolin and MoDDP were 4.0 and 1.5 Wt.%, respectively, when kaolin and MoDDP were used as single lubricant additives. Compared with the single additive, the 4.0 Wt.% kaolin/1.5 Wt.% MoDDP composite lubricant additive showed excellent friction reduction and anti-wear effects under heavy load and impact conditions. Physicochemical analysis of the wear surface revealed that the lamellar kaolin additive and MoDDP had excellent synergistic effects, and the friction process promoted the generation of lubricant films containing a chemically reactive layer of MoS₂, MoO₂, FeS₂ and Fe₂O₃ and a physically adsorbent layer containing SiO₂ and Al₂O₃, which play important roles in anti-wear and friction reduction.

The excellent friction reduction and anti-wear effects of lamellar silicate minerals and the excellent antioxidant properties and good synergistic effects of molybdenum were comprehensively used to develop the composite additives with great lubricating properties.

The purpose of this paper is to empirically analyze the effects of stock price synchronicity and herding behavior of qualified foreign institutional investors (QFII) on stock price crash risk, especially the mediating effect of herding behavior of QFII on the relation of stock price synchronicity and stock price crash risk.

Taking China’s A-share listed companies from 2005 to 2014 and QFII holding shares data as the research sample, this study calculates herding effect index, sock price synchronicity index and stock price crash risk index, and perform linear regression.

This study concludes that, either herding behavior of QFII or the stock price synchronicity can increase the stock price crash risk. Further study reveals that, the herding behavior of QFII also improves the effect of stock price synchronicity on stock price crash risk. Namely, herding behavior of QFII acts as the mediating role between stock price synchronicity and stock price crash risk.

This study empirically analyzes and verifies the mediating roles of herding behavior of QFII in affecting the relation of sock price synchronicity and stock price crash risk for the first time. The findings of this study contribute to the study of the role of QFII in stabilizing Chinese security market.