scholarly journals AN ASSESSMENT OF USER PREFERENCE IN ARTIFICIAL PATHWAY LIGHTING IN URBAN PARKS; Cases from Greater Colombo region

2021 ◽  
Author(s):  
L.L.S. Wickremasinghe ◽  
◽  
A.A. Hettiarachchi ◽  
Keyword(s):  
Urban Parks ◽  
Lighting Design ◽  
User Preferences ◽  
User Preference ◽  
Light Sources ◽  
Night Time ◽  
Perceived Safety ◽  
Perception Of Safety ◽  
Photographic Analysis ◽  
Artificial Pathway

Urban parks are critical in converting cities to liveable spaces, where artificial lighting directly affects the users’ night-time experience. This study explores the urban park users’ preferences in artificial pathway lighting, through their subjective responses towards Brightness, Correlated Colour Temperature (CCT), and luminaires of the existing lighting design, at four popular urban parks in Colombo. The reasons for the said preferences were investigated under three overarching themes: perceived safety, perceived quality of light, and restorative experience. A mixed methods approach was employed for data collection, where questionnaires were used together with measurements, in-situ observations, and photographic analysis for better understanding. The user preferences were found to be directly associated with their perception of the lit environment. The existing brightness levels are insufficient for majority of the users and has affected their perception of safety. The poor selection and placement of luminaires have negatively affected the lighting quality, while the positive effect on the users’ restorative experience has induced a higher preference towards the CCT of the light sources. The results revealed that the majority of the users opted for changes in the current lighting design, indicating that the user needs and requirements are not effectively addressed in this regard.

The Research on the Application of Two Kinds of Light Sources in the Training Venue for Physical Education of Universities

2012 ◽  
Vol 430-432 ◽  
pp. 1786-1790 ◽  
Author(s):  
Shu Fang Li
Keyword(s):  
Energy Efficiency ◽  
High Pressure ◽  
Physical Education ◽  
Lighting Design ◽  
Light Sources ◽  
Metal Halide Lamp ◽  
Sodium Lamp ◽  
Electric Light ◽  
High Pressure Sodium Lamp ◽  
Power And Energy

The energy efficiency experiment of electric light is implemented according to the lighting design of the physical training venues. In the experiment, the corresponding illumination, power and energy efficiency ratio of the commonly used high pressure sodium lamp and metal halide lamp which work under the voltage ranging from 187V to 234V are experimentally measured and the lighting effect characteristics of the two kinds of electric light sources compared, proving that the high pressure sodium light source should be employed in the training venue for physical education of universities.

scholarly journals Predicting Implicit User Preferences with Multimodal Feature Fusion for Similar User Recommendation in Social Media

2021 ◽  
Vol 11 (3) ◽  
pp. 1064
Author(s):  
Jenq-Haur Wang ◽  
Yen-Tsang Wu ◽  
Long Wang
Keyword(s):  
Social Media ◽  
Feature Fusion ◽  
Relevant Information ◽  
Image Features ◽  
User Preferences ◽  
User Preference ◽  
Late Fusion ◽  
Multimodal Features ◽  
Fusion Methods ◽  
Text Features

In social networks, users can easily share information and express their opinions. Given the huge amount of data posted by many users, it is difficult to search for relevant information. In addition to individual posts, it would be useful if we can recommend groups of people with similar interests. Past studies on user preference learning focused on single-modal features such as review contents or demographic information of users. However, such information is usually not easy to obtain in most social media without explicit user feedback. In this paper, we propose a multimodal feature fusion approach to implicit user preference prediction which combines text and image features from user posts for recommending similar users in social media. First, we use the convolutional neural network (CNN) and TextCNN models to extract image and text features, respectively. Then, these features are combined using early and late fusion methods as a representation of user preferences. Lastly, a list of users with the most similar preferences are recommended. The experimental results on real-world Instagram data show that the best performance can be achieved when we apply late fusion of individual classification results for images and texts, with the best average top-k accuracy of 0.491. This validates the effectiveness of utilizing deep learning methods for fusing multimodal features to represent social user preferences. Further investigation is needed to verify the performance in different types of social media.

Time-aware cloud manufacturing service selection using unknown QoS prediction and uncertain user preferences

2021 ◽  
pp. 1063293X2110195
Author(s):  
Ying Yu ◽  
Shan Li ◽  
Jing Ma
Keyword(s):  
Time Series Prediction ◽  
Service Selection ◽  
Cloud Manufacturing ◽  
Service Evaluation ◽  
User Preferences ◽  
User Preference ◽  
Selection Methods ◽  
Qos Prediction ◽  
Qos Performance ◽  
Time Aware

Selecting the most efficient from several functionally equivalent services remains an ongoing challenge. Most manufacturing service selection methods regard static quality of service (QoS) as a major competitiveness factor. However, adaptations are difficult to achieve when variable network environment has significant impact on QoS performance stabilization in complex task processes. Therefore, dynamic temporal QoS values rather than fixed values are gaining ground for service evaluation. User preferences play an important role when service demanders select personalized services, and this aspect has been poorly investigated for temporal QoS-aware cloud manufacturing (CMfg) service selection methods. Furthermore, it is impractical to acquire all temporal QoS values, which affects evaluation validity. Therefore, this paper proposes a time-aware CMfg service selection approach to address these issues. The proposed approach first develops an unknown-QoS prediction model by utilizing similarity features from temporal QoS values. The model considers QoS attributes and service candidates integrally, helping to predict multidimensional QoS values accurately and easily. Overall QoS is then evaluated using a proposed temporal QoS measuring algorithm which can self-adapt to user preferences. Specifically, we employ the temporal QoS conflict feature to overcome one-sided user preferences, which has been largely overlooked previously. Experimental results confirmed that the proposed approach outperformed classical time series prediction methods, and can also find better service by reducing user preference misjudgments.

Women’s Perceptions of Safety After Domestic Violence: Exploring Experiences of a Safety Contact Program

Affilia ◽  
2019 ◽  
Vol 35 (2) ◽  
pp. 260-273
Author(s):  
Tania Westwood ◽  
Sarah Wendt ◽  
Kate Seymour
Keyword(s):  
Family Violence ◽  
Emotional Support ◽  
Intervention Program ◽  
Well Being ◽  
Small Scale ◽  
Perceived Safety ◽  
Perception Of Safety ◽  
Women’S Perceptions ◽  
Perceptions Of Safety ◽  
Integrated Program

This article explores women’s experiences of the women’s safety services associated with a South Australian integrated program for male perpetrators of domestic and family violence. As small scale and exploratory, the study aimed to understand impact of such services on women’s perceptions of safety. Interviews were conducted by telephone, using a semi-structured format, with 14 women whose partners or ex-partners had been referred to a perpetrator intervention program. Informed by a feminist standpoint perspective, thematic analysis was used to explore each woman’s experience and perception of safety. The findings of the study suggest that integrated domestic and family violence programs can improve women’s feelings of safety through the application of practical safety planning, timely intervention, emotional support, and trauma-focused practice. Importantly, while the behaviors and actions of perpetrators were clearly relevant to women’s perceived safety, it was apparent that focusing on women’s strengths and capacity for recovery can significantly impact on their continued sense of safety and well-being. This article also reiterates the importance of women’s perspectives in evaluating the effectiveness of perpetrator interventions.

scholarly journals Taman Restoratif: Kriteria Desain Taman untuk Mengurangi Tingkat Stress Pengunjung

2021 ◽  
Vol 1 (1) ◽  
pp. 20-27
Author(s):  
Jasmine C. U. Bachtiar ◽  
Hanson E. Kusuma ◽  
Zaedar Gazalba
Keyword(s):  
Urban Parks ◽  
Optimal Combination ◽  
Medium Density ◽  
High Scale ◽  
Recreational Facilities ◽  
Perceived Safety ◽  
Medium Scale ◽  
Sense Of Security ◽  
Reducing Stress ◽  
Different Levels

Urban parks are public recreational facilities that can provide many benefits, reducing stress from fatigue. However, some urban parks are not frequently visited because it feels very dark inside so that many parks are unkempt and empty of visitors. This study aims to determine how the comparison of park visitors' perceptions at different levels of closure based on the sense of security and restoration they received. This research is experimental in nature, so respondents are asked to rate several edited photos to determine the optimal combination of closure. Data was collected by distributing questionnaires online for two weeks (N = 272). Furthermore, the data were processed through the ANOVA test to see which combination of enclosure was rated the highest and the lowest based on perceived savety and restoration. The results show that visitors’ perceived safety can be achieved by applying a combination of closeness 8 (high density, far position, medium scale (6 meters)) and 9 (medium density, close position, high scale (9 meters)), while visitors’ perceived restoration tends to the same and not tied to different combinations of closure. The implementation of this study is how to design the tree enclosure in urban parks to increase the participation of residents visiting the park. Urban parks that are frequently visited will be sustainable in future, so maintaining parks can be started from designing enclosure of parks.

scholarly journals Evolutionary Social Poisson Factorizationfor Temporal Recommendation

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
ChunYan Yin ◽  
YongHeng Chen ◽  
Wanli Zuo
Keyword(s):  
Recommendation Systems ◽  
Predictive Performance ◽  
User Preferences ◽  
Social Model ◽  
User Preference ◽  
Latent Factors ◽  
Factorization Model ◽  
Real World Datasets ◽  
Item Attributes ◽  
The Impact

AbstractPreference-based recommendation systems analyze user-item interactions to reveal latent factors that explain our latent preferences for items and form personalized recommendations based on the behavior of others with similar tastes. Most of the works in the recommendation systems literature have been developed under the assumption that user preference is a static pattern, although user preferences and item attributes may be changed through time. To achieve this goal, we develop an Evolutionary Social Poisson Factorization (EPF$$\_$$ _ Social) model, a new Bayesian factorization model that can effectively model the smoothly drifting latent factors using Conjugate Gamma–Markov chains. Otherwise, EPF$$\_$$ _ Social can obtain the impact of friends on social network for user’ latent preferences. We studied our models with two large real-world datasets, and demonstrated that our model gives better predictive performance than state-of-the-art static factorization models.

Personalisation in Highly Dynamic Grid Services Environments

2009 ◽  
pp. 284-313
Author(s):  
Edgar Jembere ◽  
Matthew O. Adigun ◽  
Sibusiso S. Xulu
Keyword(s):  
User Preferences ◽  
User Preference ◽  
Grid Services ◽  
Context Aware Computing ◽  
Preference Representation ◽  
Use Of Services ◽  
Order Preference ◽  
Computing Environments ◽  
Preference Models ◽  
Intuitive Interpretation

Human Computer Interaction (HCI) challenges in highly dynamic computing environments can be solved by tailoring the access and use of services to user preferences. In this era of emerging standards for open and collaborative computing environments, the major challenge that is being addressed in this chapter is how personalisation information can be managed in order to support cross-service personalisation. The authors’ investigation of state of the art work in personalisation and context-aware computing found that user preferences are assumed to be static across different context descriptions whilst in reality some user preferences are transient and vary with changes in context. Further more, the assumed preference models do not give an intuitive interpretation of a preference and lack user expressiveness. This chapter presents a user preference model for dynamic computing environments, based on an intuitive quantitative preference measure and a strict partial order preference representation, to address these issues. The authors present an approach for mining context-based user preferences and its evaluation in a synthetic m-commerce environment. This chapter also shows how the data needed for mining context-based preferences is gathered and managed in a Grid infrastructure for mobile devices.

scholarly journals User-Adaptive Key Click Vibration on Virtual Keyboard

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Seokhee Jeon ◽  
Hongchae Lee ◽  
Jiyoung Jung ◽  
Jin Ryong Kim
Keyword(s):  
Mobile Device ◽  
Tactile Feedback ◽  
User Preferences ◽  
User Preference ◽  
Performance Study ◽  
Mobile Environment ◽  
Virtual Keyboard ◽  
User Groups ◽  
Environment Study ◽  
Future Work

This study focuses on design of user-adaptive tactile keyboard on mobile device. We are particularly interested in its feasibility of user-adaptive keyboard in mobile environment. Study 1 investigates how tactile feedback intensity of the virtual keyboard in mobile devices affects typing speed and user preference. We report how different levels of feedback intensity affect user preferences in terms of typing speed and accuracy in different user groups with different typing performance. Study 2 investigates different tactile feedback modes (i.e., whether feedback intensity is linearly increased, linearly decreased, or constant from the centroid of the key, and whether tactile feedback is delivered when a key is pressed, released, or both pressed and released). We finally design and implement user-adaptive tactile keyboards on mobile device to explore the design space of our keyboards. We close by discussing the benefits of our design along with its future work.

Sign in / Sign up

Export Citation Format

Share Document