Modelling home advantage for individual teams in UEFA Champions League football

Background:Home advantage(HA) is well documented in a wide range of team sports including association football(soccer).Although much attention has been paid to differences in the overall magnitude of HA between football competitions and across time,few studies have investigated HA at the team level.Methods:A novel method of estimating HA for individual teams,based solely on home performance,was used to compare HA between the highest performing teams and countries in the Union of European Football Associations(UEFA) Champions League over a 10-year period(2003/2004 to 2012/2013).Away disadvantage(AD) was also estimated based on each team's performance away from home.Poisson regression analysis was used to estimate covariate adjusted HA and AD in terms of the percentage of goals scored at home(HA) and conceded away from home(AD).Results:When controlling for differences in team ability,HA did not vary significantly between the 13 selected teams.There was evidence(p < 0.1),however,of between-team variation in AD,ranging from 45%(away advantage) to 68%(away disadvantage).When teams were grouped into the 11 selected countries,both HA and AD varied significantly(p < 0.02) between countries:HA ranged from 52% for Turkish teams to 70%for English teams,while AD ranged from 52%(France) to 67%(Turkey).Conclusion:Differences in style of play and tactical approaches to home and away matches may explain some of the variation in HA and AD between teams from different countries.

A succession and silviculture model for the broad-leaved Korean pine forests of Changbai Mountain Area

A succession and silviculture model (ZELIG.CBA) for broad-leaved Korean pine forest of Changbai Moutain Area was developed based on the framework of ZELIG model and characteristics of Broad-leaved Korean pine forests of Changbai area. ZELIG.CBA model consists four sub-models: growth model simulating annual increment of individual tree in forest, regeneration model simulating annual establishment of different tree species, mortality model simulating annual agerelated and stress-related morality; and silviculture model simulating the forest response to different silviculture scenario. The validation of the ZELIG.CBA showed that the accuracy of the model for the forest growth was more than 95%. The succession from clear cutting site simulating showed that the ZELIG.CBA model was stable for long term simulation. And selective cutting experiment showed that the optimal scenario for broad-leaved Korean pine forests was removal volume 30% combining with 30a rotation.

Acceptance Process Model of Patients’ Life with Terminally Ill in Home Hospice and Development of a Narrative Approach for Nurses

The prime aim of this study was to find a psychological process model of patients with terminally ill in home hospice investigating the contents of a narrative, and the secondary aim was to create a narrative approach program for nurses. Ten patients narrated their thinking or feelings along with some prepared questions in two sessions. Patients’ narrative data were categorized by a qualitative analysis and 34 categories were chosen. They perceived good points in home hospice like “Being able to spend time freely”, “Close relationships with care staffs and strong confidence”, though they perceived trouble points like “Suffering from putting burden on the people around me” or “Worries about economic problems”. They perceived psychological changes through illness like “Having peace of mind and becoming kind” “Desire for a natural death”. Moreover they perceived their life like “Acceptance of one’s life including illness” “My life lived with satisfaction”. They regarded as important things such as “Spending life time usefully” “Feelings of my family members and of those around me”, and as hopes “Hope to leave my living proof” “Living left time to the fullest”. From these categories, we propose an acceptance model of patients’ life and a narrative program for nurses.

Lessons learned from the hospital to home community care program in Singapore and the supporting AI multiple readmissions prediction model

In a prior practice and policy article published in Healthcare Science,we introduced the deployed application of an artificial intelligence(AI)model to predict longer‐term inpatient readmissions to guide community care interventions for patients with complex conditions in the context of Singapore's Hospital to Home(H2H)program that has been operating since 2017.In this follow on practice and policy article,we further elaborate on Singapore's H2H program and care model,and its supporting AI model for multiple readmission prediction,in the following ways:(1)by providing updates on the AI and supporting information systems,(2)by reporting on customer engagement and related service delivery outcomes including staff‐related time savings and patient benefits in terms of bed days saved,(3)by sharing lessons learned with respect to(i)analytics challenges encountered due to the high degree of heterogeneity and resulting variability of the data set associated with the population of program participants,(ii)balancing competing needs for simpler and stable predictive models versus continuing to further enhance models and add yet more predictive variables,and(iii)the complications of continuing to make model changes when the AI part of the system is highly interlinked with supporting clinical information systems,(4)by highlighting how this H2H effort supported broader Covid‐19 response efforts across Singapore's public healthcare system,and finally(5)by commenting on how the experiences and related capabilities acquired from running this H2H program and related community care model and supporting AI prediction model are expected to contribute to the next wave of Singapore's public healthcare efforts from 2023 onwards.For the convenience of the reader,some content that introduces the H2H program and the multiple readmissions AI prediction model that previously appeared in the prior Healthcare Science publication is repeated at the beginning of this article.

Research of Home Information Technology Adoption Model

The Information Technology at Home has caught the attention of various industries such as IT,Home Appliances,Communication,and Real Estate.Based on the information technology acceptance theories and family consumption behaviors theories,this study summarized and analyzed four key belief variables i.e.Perceived Value,Perceived Risk,Perceived Cost and Perceived Ease of Use,which influence the acceptance of home information technology.The study also summaries three groups of external variables.They are social,industrial,and family influence factors.The social influence factors include Subjective Norm;the industry factors include the Unification of Home Information Technological Standards,the Perfection of Home Information Industry Value Chain,and the Competitiveness of Home Information Industry;and the family factors include Family Income,Family Life Cycle and Family Educational Level.The study discusses the relationship among these external variables and cognitive variables.The study provides Home Information Technology Acceptance Model based on the Technology Acceptance Model and the characteristics of home information technology consumption.

佛手叶粉微波干燥动力学模型的建立及品质特性分析

为优化佛手叶粉的干燥效率与品质,以干基含水率、失水速率及感官评分等评估指标,探讨了间歇干燥模式、微波功率、装载量对干燥特性和感官品质的影响,旨在确定最佳干燥条件,并比较了热风与微波干燥后佛手叶粉在微观结构、色泽、叶绿素含量、吸湿性、溶解性及茶多酚含量等方面的差异。结果显示,20、30 s的间歇模式下的佛手叶粉品质最佳,时间较短,确定为最优干燥模式。微波功率和装载量对干燥速率产生显著影响,提高微波功率可有效缩短干燥时间,特别是缩短恒速干燥阶段;而在减速阶段,装载量对干燥速率的影响较小。在微波功率385 W,装载量20 g时,感官综合评分达到最高(16.5)。通过对比3种数学模型模拟干燥动力学过程,发现佛手叶水分比与干燥时间均存在非线性关系。但Page和Wang-Singh模型拟合效果显著,且Wang-Singh模型预测准确性更高,最佳拟合函数为M_(R)=(0.0011+0.0058X_(1)+0.0037X_(2))t^(2)-(0.086+0.1544X_(1)+0.086X_(2))t+1。与热风干燥相比,佛手老叶在最优干燥条件下制备的佛手叶超微粉呈疏松细小颗粒结构,色泽亮绿,感官品质(16.9)更优,润湿性和溶解性有所提升,且茶多酚和叶绿素保留率偏高。以上结果能够为佛手叶的精深加工提供科学指导。

上下文感知在Smart Home系统中的应用

针对Smart Home环境的复杂性问题,提出了利用上下文技术来提高其智能化的方法。阐述了在普适环境下的上下文在智能家居环境中的重要性,介绍了上下文和上下文感知计算的定义,采用了基元组的形式定义了不同的上下文信息;提出了基于上下文感知的Smart Home系统模型,并对其功能进行了详细的描述;在Smart Home系统中,应用该模型对具体的上下文实例进行了描述和推理。

基于跨理论模型的家庭护理在双相情感障碍抑郁发作患者中的应用

目的探讨基于跨理论模型的家庭护理在双相情感障碍(BD)抑郁发作患者中的应用效果。方法选取郑州市第九人民医院2022年1月至2023年1月收治的86例BD抑郁发作患者为研究对象,按随机数字表法分为干预组(43例)和对照组(43例)。对照组患者接受家庭护理干预,干预组患者接受基于跨理论模型的家庭护理干预,两组均接受为期3个月的护理干预。比较两组患者干预前、干预后汉密尔顿抑郁量表(HAMD)、Herth希望量表(HHI)评分、汉密尔顿焦虑量表(HAMA)、匹兹堡睡眠质量指数(PSQI)及自伤行为发生情况。结果干预3个月,两组患者HAMA、HAMD评分较干预前均降低,且干预组较对照组更低(P<0.05);两组患者PSQI评分较干预前均降低,且干预组低于对照组(P<0.05);两组患者HHI评分较干预前均升高,且干预组高于对照组(P<0.05);干预组干预期间自伤行为发生率低于对照组(P=0.044)。结论基于跨理论模型的家庭护理在BD抑郁发作患者中的应用效果显著,可有效降低患者焦虑、抑郁程度,改善睡眠质量,提高希望水平,降低自伤行为发生率。

日本居家养老服务模式在中国的应用研究——基于跨文化适应与本土实践

中国人口老龄化问题日益严重,为满足庞大的养老需求,探讨日本居家养老服务模式的核心特征,包括政策体系与法律框架、地方政府与社区参与、“人本”理念与多维服务、服务分类与个性化需求。分析日本居家养老服务模式在中国应用的适应性,包括文化和社会结构的匹配度、服务分类与个性化的借鉴潜力、多元资金来源与社会参与。研究发现,虽然日本的养老服务模式在多个方面都具有借鉴意义,但在中国实施还需要进行本土化改良,应加入家庭和社群元素,简化和本土化服务流程,加强实践保障,才能实现真正意义上的适应和应用。

Automatic image segmentation method for cotton leaves with disease under natural environment

In order to improve the image segmentation performance of cotton leaves in natural environment, an automatic segmentation model of diseased leaf with active gradient and local information is proposed. Firstly, a segmented monotone decreasing edge composite function is proposed to accelerate the evolution of the level set curve in the gradient smooth region. Secondly, canny edge detection operator gradient is introduced into the model as the global information. In the process of the evolution of the level set function, the guidance information of the energy function is used to guide the curve evolution according to the local information of the image, and the smooth contour curve is obtained. And the main direction of the evolution of the level set curve is controlled according to the global gradient information, which effectively overcomes the local minima in the process of the evolution of the level set function. Finally, the Heaviside function is introduced into the energy function to smooth the contours of the motion and to increase the penalty function Φ(x) to calibrate the deviation of the level set function so that the level set is smooth and closed. The results showed that the model of cotton leaf edge profile curve could be obtained in the model of cotton leaf covered by bare soil, straw mulching and plastic film mulching, and the ideal edge of the ROI could be realized when the light was not uniform. In the complex background, the model can segment the leaves of the cotton with uneven illumination, shadow and weed background, and it is better to realize the ideal extraction of the edge of the blade. Compared with the Geodesic Active Contour(GAC) algorithm, Chan-Vese(C-V) algorithm and Local Binary Fitting(LBF) algorithm, it is found that the model has the advantages of segmentation accuracy and running time when processing seven kinds of cotton disease leaves images, including uneven lighting, leaf disease spot blur, adhesive diseased leaf, shadow, complex background, unclear diseased leaf edges, and staggered condition. This model can not only conduct image segmentation of cotton leaves under natural conditions, but also provide technical support for the accurate identification and diagnosis of cotton diseases.

A Generalized Layered Radiative Transfer Model in the Vegetation Canopy

In this paper, a generalized layered model for radiation transfer in canopy with high vertical resolution is developed. Differing from the two-stream approximate radiation transfer model commonly used in the land surface models, the generalized model takes into account the effect of complicated canopy morphology and inhomogeneous optical properties of leaves on radiation transfer within the canopy. In the model, the total leaf area index （LAI） of the canopy is divided into many layers. At a given layer, the influences of diffuse radiation angle distributions and leaf angle distributions on radiation transfer within the canopy are considered. The derivation of equations serving the model are described in detail, and these can deal with various diffuse radiation transfers in quite broad categories of canopy with quite inhomogeneons vertical structures and uneven leaves with substantially different optical properties of adaxial and abaxial faces of the leaves. The model is used to simulate the radiation transfer for canopies with horizontal leaves to validate the generalized model. Results from the model are compared with those from the two-stream scheme, and differences between these two models are discussed.

A User-Centric Approach to Activity Recognition and Guidance in Semantic Smart Home

Wireless smart home system is to facilitate people's lives and it trend to adopt a more intelligent way to provide services. It is very desirable in the recent SH market for the system to recognize users' behaviors and automatically response the corresponding activities to satisfy users' actual demands. However, activity models in the existing approaches are usually defined separately through knowledge-driven methods. These approaches cause that the activity models can't be matched with the services dynamically. To address the problem, we develop the semantic association model and a novel approach of activity recognition and guidance is presented. In our approach, the smart devices and users' requirements are described by semantic models. When the requirements are detected and understood, smart gateway can provide appropriate services, achieving activity assistance. The semantic association model allows all related elements in smart home connect with each other logically. The approach has been implemented and the results show that the success rate of the approach based on semantic association model is higher than 33% at average as compared to the approach based on predefined models. The proposed approach can effectively help people who are in trouble with learning or remembering in the common life.

Research on the Path to Creating Home Gardening Brand Assets Based on Customers——A Case Study of Hongyue Garden Maker

In this paper,using the research method of grounded theory,with the competitive brand of home gardening—Hongyue Garden Maker as the specific object of study,we collect the data through interviews and surveys,conduct coding analysis step by step on the data,establish the brand asset creation path model consisting of some main dimensions including " brand salience"," brand performance"," brand image"," brand judgment"," brand feeling",and " brand resonance",and reveal the interaction and logical relationship between the above dimensions,so as to provide theoretical support for the asset creation of many kinds of home gardening and other brands.

Building an Architectural Component Model for a Telehealth Service

Models of services, processes and technology are useful tools for conceptualizing complex systems such as healthcare. The application of a component architecture helps illustrate the processes and technologies that are important to the operation of a health service and conceptualize the relationships between each component. Telehealth services are relatively recent and have characteristics that do not fit neatly into established models of health services. This paper analyzes the components used to build a telehealth in the home service in South Australia and the design choices that were taken. The service used commodity-based devices and systems to deliver simple to use, low-cost in the home care. Building on this analysis, the components required in an architectural component model of a telehealth service are identified enabling a provisional architecture for telehealth services to be derived from an existing internationally recognized architectural model for eHealth systems. Situated within the broad family of eHealth architectures, a Telehealth Architectural Model of telehealth processes, software, devices, common systems and ICT infrastructure is proposed that represents the components required to support telehealth and allows for customization of services according to clinical models of care.

浅谈leave的述谓结构系统

本文通过对谓词leave在语符模式物质域内方位、领属和性状系统内的述谓结构和体现关系的分析与概括,建立一个可操作的语符关系网络,从而证明语符关系网络是描述述谓结构的有力工具,它可以描述生成言语和理解言语共享的机制,并模拟机制的具体操作过程。

Systematic Analysis of Safety and Security Risks in Smart Homes

The revolution in Internet of Things(IoT)-based devices and applications has provided smart applications for humans.These applications range from healthcare to traffic-flow management,to communication devices,to smart security devices,and many others.In particular,government and private organizations are showing significant interest in IoT-enabled applications for smart homes.Despite the perceived benefits and interest,human safety is also a key concern.This research is aimed at systematically analyzing the available literature on smart homes and identifying areas of concern or risk with a view to supporting the design of safe and secure smart homes.For this systematic review process,relevant work in the most highly regarded journals published in the period 2016–2020(a section of 2020 is included)was analyzed.A final set of 99 relevant articles(journal articles,book sections,conference papers,and survey papers)was analyzed in this study.This analysis is focused on three research questions and relevant keywords.The systematic analysis results and key insights will help researchers and practitioners to make more informed decisions when dealing with the safety and security risks of smart homes,especially in emergency situations.

Smart Object Detection and Home Appliances Control System in Smart Cities

During the last decade the emergence of Internet of Things(IoT)based applications inspired the world by providing state of the art solutions to many common problems.From traffic management systems to urban cities planning and development,IoT based home monitoring systems,and many other smart applications.Regardless of these facilities,most of these IoT based solutions are data driven and results in small accuracy values for smaller datasets.In order to address this problem,this paper presents deep learning based hybrid approach for the development of an IoT-based intelligent home security and appliance control system in the smart cities.This hybrid model consists of;convolution neural network and binary long short term model for the object detection to ensure safety of the homes while IoT based hardware components like;Raspberry Pi,Amazon Web services cloud,and GSM modems for remotely accessing and controlling of the home appliances.An android application is developed and deployed on Amazon Web Services(AWS)cloud for the remote monitoring of home appliances.A GSM device and Message queuing telemetry transport(MQTT)are integrated for communicating with the connected IoT devices to ensure the online and offline communication.For object detection purposes a camera is connected to Raspberry Pi using the proposed hybrid neural network model.The applicability of the proposed model is tested by calculating results for the object at varying distance from the camera and for different intensity levels of the light.Besides many applications the proposed model promises for providing optimum results for the small amount of data and results in high recognition rates of 95.34%compared to the conventional recognition model(k nearest neighbours)recognition rate of 76%.

Modelling time series properties of Australian lending interest rates

The purpose of this paper is to examine the time series properties of Australian residential mortgage interest rates, and in doing so, establish whether or not selected home loan rates （product-level monthly home loan interest rates for CBA） exhibit the expected cyclical and seasonal variations and whether seasonality, if present, is stochastic or deterministic. In particular, due to a well established presence of cyclicality in financial markets＇ interest rates and strong correlation between financial markets＇ interest rates and home loan interest rates, the paper presumes that cyclicality is also to be found in home loan interest rates. Furthermore, the paper tests the hypothesis that home loan interest rates, for selected products, exhibit the three identified （＂Spring＂, ＂Autumn＂ and ＂The end of the Financial Year＂） season-related interest rate reductions. The paper uses a structural time series modelling approach and product-level home loan interest rates data from one of the biggest banks in Australia, Commonwealth Bank of Australia （CBA）. As expected, the results overall confirm the existence of cyclicality in home loan interest rates. With respect to the seasonality of home loan interest rate, although most of the analysed variables show the presence of statistically significant seasonal factors, the majority of the statistically significant seasonal factors observed cannot be attributed to any of the three considered seasonal effects.

Context-Aware System Modeling Based on Boolean Control Network

Boolean control network consists of a set of Boolean variables whose state is determined by other variables in the network. Boolean network is used for modeling complex system. In this paper, we have presented a model of a context-aware system used in smart home based on Boolean control networks. This modeling describes the relationship between the context elements (person, time, location, and activity) and services (Morning Call, Sleeping, Guarding, Entertainment, and normal), which is effective to logical inference. We apply semi tensor matrix product to describe the dynamic of the system. This matrix form of expression is a convenient and reasonable way to design logic control system.