scholarly journals Digitalization and Information Management Mechanism of Sports Events Based on Multisensor Node Cooperative Perception Model

2022 ◽  
Vol 2022 ◽  
pp. 1-11
Author(s):  
Yi Liu ◽  
Yaodong Wang ◽  
Yuntong Tan ◽  
Jie Ma ◽  
Yan Zhuang ◽  
...  
Keyword(s):  
Service Providers ◽  
Experimental Comparison ◽  
Event Data ◽  
Media Effect ◽  
Service Model ◽  
Recommendation Algorithm ◽  
Data Set ◽  
Sports Events ◽  
Event Recommendation ◽  
User Groups

In the process of developing major sports events, how to guide providers and users to provide and utilize the archives information resources of major sports events and realize the interaction between them is an important problem to be solved urgently in the development of major sports events and the archive service of major sports events. By analyzing the present situation of archive service of major sports events, especially the analysis of the opposite dependent subjects of service providers and users, we can see that the continuous development of archive services for major sports events will inevitably lead to constant changes in user groups and user needs, guided by the theory of information retrieval, knowledge management, and media effect. According to the service model of archive service of major sports events, the archive service model of specific sports events is constructed. In this paper, four kinds of event recommendation models are applied to the collected marathon event data for experiments. Through experimental comparison, the effectiveness of content-based recommendation algorithm technology in the event network data set is verified, and an algorithm model suitable for marathon event recommendation is obtained. Experiments show that the comprehensive event recommendation model based on term frequency–inverse document frequency (TF-IDF) text weight and Race2vec entry sequence has the best recommendation performance on marathon event data set. According to the recommendation target of the event and the characteristics of the event data type, we can choose a single or comprehensive recommendation algorithm to build a model to realize the event recommendation.

Customer-Related Social Stressors

2015 ◽  
Vol 14 (4) ◽  
pp. 165-181 ◽  
Author(s):  
Sarah Dudenhöffer ◽  
Christian Dormann
Keyword(s):  
Service Providers ◽  
Principal Component ◽  
Well Being ◽  
Emotional Dissonance ◽  
Social Stressors ◽  
Data Set ◽  
Confirmatory Factor Analyses ◽  
Confirmatory Factor ◽  
Service Jobs ◽  
Single Data

Abstract. The purpose of this study was to replicate the dimensions of the customer-related social stressors (CSS) concept across service jobs, to investigate their consequences for service providers’ well-being, and to examine emotional dissonance as mediator. Data of 20 studies comprising of different service jobs (N = 4,199) were integrated into a single data set and meta-analyzed. Confirmatory factor analyses and explorative principal component analysis confirmed four CSS scales: disproportionate expectations, verbal aggression, ambiguous expectations, disliked customers. These CSS scales were associated with burnout and job satisfaction. Most of the effects were partially mediated by emotional dissonance. Further analyses revealed that differences among jobs exist with regard to the factor solution. However, associations between CSS and outcomes are mainly invariant across service jobs.

Approximate Bayesian inference for joint linear and partially linear modeling of longitudinal zero-inflated count and time to event data

2021 ◽  
pp. 096228022110028
Author(s):  
T Baghfalaki ◽  
M Ganjali
Keyword(s):  
Linear Model ◽  
Joint Modeling ◽  
Partially Linear Model ◽  
Event Data ◽  
Time To Event ◽  
Data Set ◽  
Partially Linear ◽  
Time To Event Data ◽  
Count Response ◽  
Approximate Bayesian

Joint modeling of zero-inflated count and time-to-event data is usually performed by applying the shared random effect model. This kind of joint modeling can be considered as a latent Gaussian model. In this paper, the approach of integrated nested Laplace approximation (INLA) is used to perform approximate Bayesian approach for the joint modeling. We propose a zero-inflated hurdle model under Poisson or negative binomial distributional assumption as sub-model for count data. Also, a Weibull model is used as survival time sub-model. In addition to the usual joint linear model, a joint partially linear model is also considered to take into account the non-linear effect of time on the longitudinal count response. The performance of the method is investigated using some simulation studies and its achievement is compared with the usual approach via the Bayesian paradigm of Monte Carlo Markov Chain (MCMC). Also, we apply the proposed method to analyze two real data sets. The first one is the data about a longitudinal study of pregnancy and the second one is a data set obtained of a HIV study.

scholarly journals They Do Their Best, but Their Best Isn’t Good Enough: How Social Housing Can Support Older Tenants Aging in Place

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 23-23
Author(s):  
Christine Sheppard ◽  
Andrea Austen ◽  
Sander Hitzig
Keyword(s):  
Older Adults ◽  
Social Housing ◽  
Service Providers ◽  
Policy Implications ◽  
Service Model ◽  
Building Trust ◽  
Age In Place ◽  
Access To Health ◽  
The City

Abstract Toronto Community Housing (TCH) is the second largest social housing landlord in North America, and is home to over 27,000 older adults, half of whom live in 83 “seniors-designated” buildings. There is inadequate and inconsistent delivery of services in these buildings, negatively impacting tenants’ ability to age in place. We conducted two half-day consultations with service providers (n=74) and tenants (n=100) to identify strategies to improve unit condition, promote stable tenancies (i.e., prevent evictions) and enhance access to health and support services for older adults living in TCH. Through facilitated discussion, participants identified their top two recommendations for each priority area and reflected on the strategies that were hardest and easiest to implement, as well as the ones that would have the most and least impact on quality of life for older tenants. Participants recognized the need for more education as a way to empower older tenants and reduce stigma associated with unit condition issues (e.g., pest problems) and arrears. More frequent touch points with tenants was also recommended as a way to identify older adults at-risk of eviction and work proactively (instead of reactively) to support them. Service providers and tenants believed that system navigators working directly in the buildings would be a key facilitator to building trust and helping older tenants access needed services. Outcomes of the have several program and policy implications for TCH, as they partner with the City of Toronto to design a new integrated service model for the seniors-designated buildings.

scholarly journals Collaborative Filtering Recommendation Algorithm Based on TF-IDF and User Characteristics

2021 ◽  
Vol 11 (20) ◽  
pp. 9554
Author(s):  
Jianjun Ni ◽  
Yu Cai ◽  
Guangyi Tang ◽  
Yingjuan Xie
Keyword(s):  
Collaborative Filtering ◽  
User Characteristics ◽  
Recommendation Algorithm ◽  
Data Set ◽  
Rating Data ◽  
User Similarity ◽  
Public Data ◽  
Weighted Algorithm ◽  
Collaborative Filtering Algorithm ◽  
The Impact

The recommendation algorithm is a very important and challenging issue for a personal recommender system. The collaborative filtering recommendation algorithm is one of the most popular and effective recommendation algorithms. However, the traditional collaborative filtering recommendation algorithm does not fully consider the impact of popular items and user characteristics on the recommendation results. To solve these problems, an improved collaborative filtering algorithm is proposed, which is based on the Term Frequency-Inverse Document Frequency (TF-IDF) method and user characteristics. In the proposed algorithm, an improved TF-IDF method is used to calculate the user similarity on the basis of rating data first. Secondly, the multi-dimensional characteristics information of users is used to calculate the user similarity by a fuzzy membership method. Then, the above two user similarities are fused based on an adaptive weighted algorithm. Finally, some experiments are conducted on the movie public data set, and the experimental results show that the proposed method has better performance than that of the state of the art.

scholarly journals Dynamics of Political Protests

2018 ◽  
Vol 72 (2) ◽  
pp. 485-521 ◽  
Author(s):  
Graig R. Klein ◽  
Patrick M. Regan
Keyword(s):  
Collective Action ◽  
The State ◽  
Event Data ◽  
Data Set ◽  
Government Response ◽  
Political Protests ◽  
The Arab Spring ◽  
The Relationship ◽  
State Responses ◽  
Cross National

AbstractThe links between protests and state responses have taken on increased visibility in light of the Arab Spring movements. But we still have unanswered questions about the relationship between protest behaviors and responses by the state. We frame this in terms of concession and disruption costs. Costs are typically defined as government behaviors that impede dissidents’ capacity for collective action. We change this causal arrow and hypothesize how dissidents can generate costs that structure the government's response to a protest. By disaggregating costs along dimensions of concession and disruption we extend our understanding of protest behaviors and the conditions under which they are more (or less) effective. Utilizing a new cross-national protest-event data set, we test our theoretical expectations against protests from 1990 to 2014 and find that when protesters generate high concession costs, the state responds in a coercive manner. Conversely, high disruption costs encourage the state to accommodate demands. Our research provides substantial insights and inferences about the dynamics of government response to protest.

Azimuth estimation capabilities of the ARCESS regional seismic array

1993 ◽  
Vol 83 (4) ◽  
pp. 1213-1231
Author(s):  
Dorthe B. Carr
Keyword(s):  
Time Window ◽  
Source Region ◽  
Event Data ◽  
Small Aperture ◽  
Data Set ◽  
Low Frequencies ◽  
Source Regions ◽  
The Mean ◽  
Local Geology ◽  
Regional Arrays

Abstract The effect of local geology and noise conditions on the performance of a small regional array is investigated by comparing the regional Pn backazimuth estimation capabilities of the ARCESS array in northern Norway to the NORESS array. A broadband frequency-wavenumber estimator was used to calculate backazimuths from the Pn arrival for each of 203 regional events recorded at ARCESS while varying element spacing, frequency band, and time window. Most of the errors in backazimuth are less than 20° when appropriate parameter combinations are used, and mean backazimuth errors are close to zero. The best results are obtained using a 13-element configuration that has a 1.4 km aperture and a maximum station spacing of about 600 m. With the 13-element configuration and the data filtered to include frequencies between 3 and 10 Hz, the mean errors for the 203 event data set are less than 0.9°, and S.D. are as small as 16.9°. There are differences seen in the backazimuth estimation capabilities of ARCESS and NORESS with specific parameter combinations. The larger aperture configurations (10- and 17-elements) have smaller means at ARCESS, although the precision is about the same. The estimates using unfiltered data at ARCESS are poor, because of local noise conditions that increase the level of background noise at low frequencies. Overall the precision is better at NORESS, but both regional arrays have the best results using the 13-element configuration and filtering the data in the middle frequency range (3 to 10 Hz). Other factors investigated include SNR and source region. Backazimuth estimation statistics improve if only events with 5 dB of SNR are included in the data set at both ARCESS and NORESS. The mean errors move closer to zero and standard deviations decrease. The differences between the two arrays are not as pronounced. There are some path effects from different source regions around the ARCESS array. However, combinations of small aperture configurations and middle (3 to 10 Hz) frequency bands work well for events over the entire distance range of 30 to 1200 km. ARCESS and NORESS have similar backazimuth estimation capabilities even though there are differences in the local geology and noise conditions. Because a 13-element configuration produces reliable results for both arrays, it would be reasonable to reduce the number of elements in a regional array. This in turn will reduce the costs associated with building and deploying small regional arrays.

PrivItem2Vec: A privacy-preserving algorithm for top-N recommendation

2021 ◽  
Vol 17 (12) ◽  
pp. 155014772110612
Author(s):  
Zhengqiang Ge ◽  
Xinyu Liu ◽  
Qiang Li ◽  
Yu Li ◽  
Dong Guo
Keyword(s):  
Time Series ◽  
Internet Of Things ◽  
Privacy Protection ◽  
Short Term Memory ◽  
Short Term ◽  
Recommendation Algorithm ◽  
Data Set ◽  
Term Memory ◽  
Protection Mechanism ◽  
Long Short Term Memory

To significantly protect the user’s privacy and prevent the user’s preference disclosure from leading to malicious entrapment, we present a combination of the recommendation algorithm and the privacy protection mechanism. In this article, we present a privacy recommendation algorithm, PrivItem2Vec, and the concept of the recommended-internet of things, which is a privacy recommendation algorithm, consisting of user’s information, devices, and items. Recommended-internet of things uses bidirectional long short-term memory, based on item2vec, which improves algorithm time series and the recommended accuracy. In addition, we reconstructed the data set in conjunction with the Paillier algorithm. The data on the server are encrypted and embedded, which reduces the readability of the data and ensures the data’s security to a certain extent. Experiments show that our algorithm is superior to other works in terms of recommended accuracy and efficiency.

What makes an optimal delivery for PrEP against HIV: A qualitative study in MSM

2022 ◽  
pp. 095646242110608
Author(s):  
Janice Y. C. Lau ◽  
Ngai-Sze Wong ◽  
Krystal C. K. Lee ◽  
Tsz-Ho Kwan ◽  
Grace C. Y. Lui ◽  
...  
Keyword(s):  
Qualitative Study ◽  
Service Providers ◽  
Effective Means ◽  
Qualitative Assessment ◽  
Theory Approach ◽  
Service Model ◽  
Structured Interviews ◽  
Sexually Transmitted ◽  
Ethnic Chinese ◽  
Sex With Men

Background Pre-exposure prophylaxis (PrEP) is an effective means of HIV prevention for men who have sex with men (MSM), a key population whose engagement is crucial for achieving effective public health outcomes. An optimal service model would be important in planning the implementation of PrEP in places where such service has not been established. Methods A qualitative study was conducted to delineate the attributes of an optimal PrEP service model for MSM in Hong Kong, a city where no formal PrEP programs existed. Twenty purposively sampled MSM who were enrollees of two pilot PrEP projects participated in the semi-structured interviews promoting story-telling. The coded data were thematically analyzed following Grounded Theory approach, focusing on uncovering a typology of the essential attributes of an optimal PrEP service model, and the reasons for such preferences. Results Participating MSM were all ethnic Chinese and aged 26 to 52 years. All had received PrEP from pilot projects in conjunction with periodic screening of sexually transmitted infections (STI), HIV antibody, and plasma creatinine. Four major themes emerged as regards the attributes of a preferred PrEP service: (i) comprehensiveness of HIV/STI and safety monitoring; (ii) convenient unitary service; (iii) stigma-free PrEP access and protecting confidentiality; and (iv) affordable price. Whereas regular provision of PrEP was acceptable to MSM, unaffordability and related stigma were the anticipated challenges for potential service providers. Conclusions The qualitative assessment of MSM’s preference for PrEP service delivery has yielded important information on the many facets of a desirable service model.

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