User Level Research Articles

Online Food Delivery Apps: Customer Perception towards Restaurant and Home-Made Food Delivery in Chennai

This study delves into the landscape of online food delivery applications, examining their impact, trends, and potential avenues for growth. Through an empirical research method employing a questionnaire, data was collected from a diverse sample of 400 individuals in Chennai, exploring the preferences, habits, and satisfaction levels of users. Firstly, demographic factors such as age and gender exhibit a direct correlation with customer satisfaction or preferences, indicating individualised landscape of preferences. Swiggy emerges as the preferred platform among respondents, primarily attributed to its safe and quick delivery options. The study proposes the incorporation of home-made food deliveries, not only as a consumer benefit but also as a source of new employment opportunities, particularly for homemakers. This study provides understanding of the online food delivery landscape, offering actionable insights for companies to navigate the challenges, capitalise on emerging trends, and foster sustainable growth in this dynamic and competitive industry.

Increasing complexity in Aerodynamic Gradient flux calculations inside the roughness sublayer applied on a two-year dataset

Over tall canopies such as forests the atmospheric surface layer is subdivided into an inertial sublayer (ISL) and a roughness sublayer (RSL). Inside the RSL the classic aerodynamic gradient method using Monin-Obukhov similarity theory (MOST) by itself does not represent the gradient well and is insufficient to calculate fluxes. Over the past decades multiple studies have proposed methods to extend MOST to account for the different turbulent conditions within the RSL, containing a wide range of approaches and complexity. In this study we investigate how much complexity is necessary to calculate the flux more accurately and what we can learn from the respective complexity. A large dataset is required to assess the statistical robustness of the respective complexity during different environmental conditions. To this end, we study and apply the effect of forest roughness and directional heterogeneity in our flux calculations on a two-year dataset (2009-2010) of the sensible heat flux measured over a Douglas fir forest in the Netherlands. We apply standard MOST, an observational based method (the α-factor) and a physically based method (Harman and Finnigan, 2007, 2008) (hereafter HF07/08) together with a range of methods for the displacement height (d). Our results show that both a simple method (the α-factor) and a complex method (HF07/08) are able to more accurately represent the flux but that, as expected, standard MOST (regardless of the method estimating d) alone is insufficient. Both the α-factor and (HF07/08) allow to analyze large scale patterns in canopy turbulence. Differences between the methods lie in the level of detail and practical usability.

Gaze-contingent adaptation of VR stereo parameters for cybersickness prevention

Extended exposure to virtual reality displays has been linked to the emergence of cybersickness, characterized by symptoms such as nausea, dizziness, fatigue, and disruptions in eye movements. The main objective of our study is to examine the effects of real-time fine-tuning of stereo parameters and blurriness in virtual reality on the discomfort level of users who are experiencing motion sickness triggered by the display. Our hypothesis proposes that by dynamically correcting the rendering settings, the symptoms of motion sickness can be relieved and the overall VR user experience can be improved. Our methodology commences with a prediction model for the comfort level of the viewer based on their gaze parameters, such as pupil diameter, blink count, gaze position, and fixation duration. We then propose a method to dynamically adapt the stereoscopic rendering parameters by considering the predicted comfort level of the viewer.

Driver-to-Driver Communication Skills: Contributing Factors to Traffic Accidents on South African Roads?

Road traffic accidents are associated with different factors, such as nonsignalised road networks, inexperienced drivers, a lack of communication skills, distraction, and the visual or cognitive impairment of road users, which have led to this increase in traffic accidents. Understanding these factors in alignment with road user communication skills can provide solutions that can reduce traffic fatalities. Road users’ communication is predominantly formal in nature; informal means of communication also exist but are not given proper attention during the driving training and licence testing processes. Therefore, this study investigated the communication skills between drivers as a factor contributing to traffic accidents in South African cities. Consequently, 16 traffic scenarios of communication between drivers were simulated using PTV Vissim 2022 and Blender 3.0 software, and a semistructured interview questionnaire was used to collect data from South African road users. The questionnaire was further used to evaluate the confidence level of road users concerning informal communication. The data were analysed via regression analysis to establish the relationship between traffic accidents and miscommunication between drivers. The information gathered and analysed from this study helps us to understand the informal communication types between drivers and establish where communication loss exists, which could potentially lead to a traffic accident. The results also show that the misinterpretation of communication signals can present the possibility of a traffic safety risk.

Analysis of Concentric and Eccentric Power in Flywheel Exercises Depending on the Subjects' Strength Level and Body Mass.

Asencio, P, García-Valverde, A, Albaladejo-García, C, Beato, M, Moreno-Hernández, FJ, and Sabido, R. Analysis of concentric and eccentric power in flywheel exercises depending on the subjects' strength level and body mass. J Strength Cond Res 38(8): 1394-1400, 2024-The objective of this study is to describe how flywheel exercise mechanical outputs are affected by the athletes' body mass (BM) and strength level and by the exercise type. Forty-six recreational athletes came to a laboratory 3 times. On the first day, descriptive data, squat (1 repetition maximum: 1RM) and flywheel familiarization were performed. After a second day of familiarization, subjects performed a randomized flywheel exercise-testing protocol of squat and split squat exercises. The variables used for data analysis were peak concentric power and peak eccentric power, eccentric/concentric ratio, and their relationship with 1RM/BM. Subjects were assigned to a stronger or weaker group according to their 1RM/BM ratio. Group differences were found in absolute values of eccentric overload (EOL) ( p < 0.01; effect size [ES] = 0.51) and EOL/BM ( p < 0.01; ES = 0.46) only in the split squat. Absolute power values in the concentric phase showed differences between inertial load ( p < 0.01; ES = 0.41). The stronger group did not present significant differences between inertial loads during squat ( p < 0.01; ES = 0.46), but they showed different ratios with light inertias in comparison with the weaker group ( p < 0.01; ES = 0.46). There were significant differences between groups with light inertias in split squat (nondominant) and squat exercises ( p < 0.05; ES = 0.29) in the eccentric and concentric phases ( p < 0.116; ES = 0.20). Squat and split squat exercises present different profiles depending on the training level. In conclusion, it is recommended that practitioners perform a test to understand the inertial load-power profile (concentric, eccentric, and their ratio) for each exercise and also consider the user's strength level for selection of the inertial load and for the exercise to use in training.

Metamorphosis of EduX: a comparative study for education in the metaverse

This research explores critical aspects of the ongoing educational transition from traditional two-dimensional digital platforms toward immersive realities in the metaverse. In this work, a networked, collaborative, ubiquitous, and immersive platform, “EduX” is developed to host different educational sessions. Several metrics are tracked and compared with parallel sessions using traditional digital platforms used by educational institutions, particularly during and after the Covid-19 pandemic, such as Zoom, MS Teams, and Black Board Ultra as the Learning Management System. Four groups of students from different domains of knowledge (n = 396) participated in the study, whereby each group was split into two subgroups, taking their session via EduX and BBUltra, followed by post-assessments and discussions. Using a mixed methods approach, quantitative and qualitative data were collected and analyzed to examine the influence of the platform on engagement, performance, and overall student achievements. The discussed results demonstrate superior usability and user experience levels of the proposed platform, with higher levels of engagement, leading to significantly improved attainments. Other than demonstrating the efficacy and feasibility of the platform, this work establishes fundamental metrics to be considered by software and hardware solution providers, academic institutions, and the research community concerned with the convergence towards immersive technologies.

Multimedia Courseware for Teaching Chinese as a Second Language

This paper introduces an interactive multimedia (IMM) courseware prototype entitled “Learn Chinese with Ease” (LCE), a specialised instructional tool developed for Teaching Chinese as a Second Language (TCSL) at tertiary level. It is restricted to non-Chinese heritage students and students with non-Chinese speaking backgrounds. This research aimed to evaluate the students’ perceived level of usability of the LCE courseware prototype for TCSL using a usability questionnaire. In order to obtain the students’ feedbacks pertaining to their experience in interacting with the LEC courseware prototype, a usability evaluation study was conducted. The research participants completed a courseware usability questionnaire (CUQ) that was designed to measure the usability of the courseware prototype focused on two quality attributes: (1) Interface Quality with two research constructs (Section A: User interface design, and Section B: Navigation and interactivity), and (2) Information Quality (Section C: Instructional Content). It also investigated the user preference through the final section in the questionnaire. The CUQ was constructed as five-point Likert scales, labelling with 1-Strongly Disagree, 2-Disagree, 3-Neutral, 4-Agree and 5-Strongly Agree, which was adapted from the questionnaires by Aris et al. (2006) and Bahrudin et al. (2011). Reliability testing on CUQ using Cronbach’s alpha showed that the Cronbach’s alpha coefficient of all the four sections in CUQ were above 0.8, indicating the questionnaire was well-constructed and reliable. Research participants were asked to rate their agreement with the statements in the four sections, ranging from strongly disagree to strongly agree. Results for the students’ assessment of the usability of the LCE courseware prototype show that the students had positive perceptions toward the information quality and interface quality of the LEC courseware for educational contexts to support the pedagogy of TCSL. The research findings also indicate that many students prefer using the IMM courseware in Chinese learning compared to traditional instruction methods reliant on paper textbook.

Medication dispenser with touch screen and consumption authenticator for monitoring adherence to medication in the elderly

The elderly population continues to grow, this population has many chronic conditions, which is why they take multiple pills at the same time, this situation makes it difficult for them to take their medications at the appropriate time, which can cause health complications and even death. death. The objective of this research is to improve medication adherence using a medication dispenser that allows authenticating medication consumption accurately with a high level of usability. To do this, we implemented a dispenser with an alarm system that can be configured from a graphical interface, with internet of things (IoT) to remotely monitor the intake of pills and authenticate their consumption through artificial vision that will use the instant messaging system to inform the caregiver about the situation and finally measure the dispenser usability.

PERANCANGAN APLIKASI CEK RADIUS OUTLET PT. IJS BERBASIS WEB MENGGUNAKAN METODE HAVERSINE FORMULA

PT. IJS is a company engaged in marketing cafe and restaurant culinary franchise licenses. Opening a new franchise has rules in the form of a radius between locations that cannot be close together. This company still uses a conventional way of checking the location radius, so it takes longer and is less efficient in the checking process. Based on this problem, the researchers built a check radius outlet application for PT. Web-based IJS calculates the shortest distance using the waterfall model and the Haversine Formula method. The designed application is tested using a black box, comparing the system results with actual conditions using an odometer and user acceptance tests. Furthermore, the black box test results were declared successful, and an accuracy value of 94% was obtained with actual conditions. The user acceptance test received a usability level percentage of 89.93% which is very strong from the user's point of view. Keywords: Black Box, Franchise, Metode Haversine Formula, UAT, Waterfall

Recovery-oriented care in long-term mental health settings: Relationship between the active recovery triad (ART) model, recovery-oriented care, and recovery of service users.

The active recovery triad (ART) model provides guidelines for recovery-oriented care in long-term mental health care. The aim of this study is to evaluate whether compliance to the principles of the ART model is related to recovery-oriented care, service user recovery and satisfaction. A prospective study was conducted including two measurements, in which we investigated compliance to the principles of the ART model (ART fidelity), recovery-oriented care as measured by the Recovery-Oriented Practices Index-Revised (ROPI-R) at team level (n = 18) and outcome measures on service user level (n = 101) related to personal recovery, social roles, level of functioning, clinical recovery, transition, and satisfaction. We used multilevel modeling to evaluate these relationships. There was a significant association between active recovery triad (ART) fidelity and the ROPI-R. We did not find a significant association between overall ART fidelity and service user outcomes. Yet, we did find that higher ART fidelity in the domains "cooperation in the triad," "professionalization of staff," and "team structure" were related to improved clinical recovery, functioning, social roles, and performance of activities. However, higher ART fidelity in the domain "healing environment" was related to poorer functioning, and a higher score in the domain "safety and prevention of coercion" was related to poorer social roles and performance of activities. We can conclude that compliance to the principles of the ART model is related to recovery-oriented care, measured with the ROPI-R. In addition, the findings suggest that in particular elements in the ART model are related to meaningful recovery outcomes. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Alertness Assured: Sleep Detection and Video Control Technology

Abstract: The system utilizes advanced computer vision algorithms to analyze real-time video streams, employing techniques such as facial landmark detection and eye movement tracking. By continuously monitoring these visual cues, the system can accurately detect signs of drowsiness, such as drooping eyelids or prolonged eye closures, prompting timely interventions to prevent accidents or errors caused by fatigue. In addition to detecting drowsiness, the system also evaluates the user's attention levels by analysing head orientation and facial expressions. By tracking head movements and assessing changes in facial expressions indicative of engagement or distraction, the system provides valuable insights into the user's cognitive state. This attention assessment component enables the system to adapt its feedback and intervention strategies based on the user's level of alertness and focus. To enhance user awareness and responsiveness, the system employs graphical visualization techniques to display real-time feedback on drowsiness and attention status. Visual indicators, such as color-coded alerts or dynamic graphs depicting attention trends, provide users with intuitive insights into their cognitive performance, empowering them to make informed decisions about their work habits or driving patterns. Moreover, the system utilizes auditory alerts to supplement visual feedback, ensuring that users receive timely notifications even in noisy or visually demanding environments. Whether it's a gentle reminder to take a short break or a more urgent warning about escalating drowsiness levels, auditory cues serve as an effective means of alerting users to potential risks and encouraging proactive intervention

Digital cognitive stimulation in elderly breast cancer patients: the Cog-Tab-Age feasibility study

BackgroundElderly cancer patients often experience cognitive difficulties that can affect their quality of life and autonomy. However, they are rarely included in clinical trials, and only one study has explored the feasibility of cognitive training in this population. While digital cognitive training has been successful in improving cognition in younger patients, its feasibility in elderly patients requires evaluation.ObjectivesThis feasibility study primarily focused on evaluating patients’ ability to use digital cognitive stimulation (usability). Secondary objectives were to evaluate acceptability, adherence, and satisfaction with regard to digital cognitive stimulation in elderly breast cancer patients.MethodsElderly breast cancer patients at least 70 years old who were receiving cancer treatment (chemotherapy, targeted therapy, and/or radiotherapy) were recruited. Cognitive complaints were evaluated at baseline using the Functional Assessment of Cancer Therapy-Cognitive Function scale (FACT-Cog). Participants were invited to attend three 20-minute sessions of digital cognitive stimulation using HappyNeuron PRESCO software App on tablets, with the first session being supervised by a neuropsychologist and the two others being performed independently either at home or at the cancer center. We hypothesized that participants would spend 10 of the 20 min of the given time with the tablet completing exercises (training time). Thus, the usability of digital cognitive stimulation was defined as completing at least three exercises during the training time (10 min) of one of the two training sessions in autonomy. The proportion of patients who agreed to participate (acceptability) and completion of planned sessions (adherence) were also estimated. Satisfaction was evaluated post-intervention through a self-report questionnaire.Results240 patients were initially screened, 60% (n = 145) were eligible and 38% agreed to participate in the study. Included patients (n = 55) had a mean age of 73 ± 3 years, 96% an ECOG score of 0–1 and were undergoing radiotherapy (64%), and/or chemotherapy (47%) and/or targeted therapy (36%) for stage I-II breast cancer (79%). Most patients reported significant cognitive complaints (82%) and 55% had previous experience with digital tools (n = 30). The usability rate was 92%, with 46 out of 50 evaluable participants completing at least three exercises during the training time. The adherence rate was 88%, with 43/50 participants completing all planned sessions. Participants were largely satisfied with the cognitive intervention format (87%). They preferred to complete sessions at the cancer center under the supervision of the neuropsychologist than alone at home (90%).ConclusionsThe high level of usability, adherence and satisfaction in this study shows for the first time the feasibility of digital cognitive stimulation in cancer patients older than 70 years. However, the intervention should be proposed only to patients reporting cognitive complaints and should be structured and supervised to improve acceptability and adherence.Trial RegistrationClinicalTrials identifier: NCT04261153, registered on 07/02/2020.

The influence of customer experience on loyalty through satisfaction as an intervening variable for users of maxim online transportation services in the city of semarang

The high level of online transportation users in Indonesia creates intense competition and to be able to survive in the midst of competition, companies must improve their performance in various aspects to be able to create a good experience for their users so that there is high satisfaction so that user loyalty to the company continues to survive and increase. This research aims to determine the influence of customer experience on user loyalty through satisfaction with users of Maxim online transportation services in Semarang City. This type of research is explanatory research with a sample size of 96 respondents who are Maxim users in Semarang City. with a sampling technique using non-probability sampling with a multistage purposive sampling method. The population in this research is the people of Semarang City who have used Maxim. The data analysis method uses SmartPLS 3.2.9 software. The research results prove that the mediating relationship between customer experience and loyalty through satisfaction as an intervening variable is partial mediation. The suggestion in this research is that Maxim is expected to pay more attention to aspects that can influence user experience so that users feel maximum satisfaction when using Maxim.

Gamification Approach for Interactive Learning of Lean Manufacturing Activities

The gamification approach is popular method in education as it has been widely utilized in many fields. The project focuses on designing a game for interactive learning of lean manufacturing activities to create an alternative learning method that would gain interest and efficiency in learning. Integration of gamification approach and interactive learning method was used to illustrate a virtual lean manufacturing education and training by means of users’ interaction towards provided interactive learning materials and participation in playing the designed game. Input of the project which is learning materials was developed by analysing numerous articles regarding common lean manufacturing tools and practices. Interactive elements such as animation, sound effects, lecture voice, and videos were applied in each learning material to deliver an adequate understanding of each topic. Construction of the game platform is being developed using ActivePresenter software which includes simulation videos of the production line using FlexSim software to visualize a real production floor which provides a clearer picture of the production system for users. The game should include a basic assessment of lean manufacturing practices by considering its complexity and difficulty level for users with inadequate or does not have experience in the field. The outcome of the project is expected to successfully design a basic game platform for lean manufacturing education by means of interactive learning. Users will be able to learn lean manufacturing systems using the designed interactive learning materials included in the games and self-assess themselves as the game publishes the correct and best answer option in case they answer wrongly.

Electronic Immunization Registry in Rwanda: Qualitative Study of Health Worker Experiences.

Monitoring childhood immunization programs is essential for health systems. Despite the introduction of an electronic immunization registry called e-Tracker in Rwanda, challenges such as lacking population denominators persist, leading to implausible reports of coverage rates of more than 100%. This study aimed to assess the extent to which the immunization e-Tracker responds to stakeholders' needs and identify key areas for improvement. In-depth interviews were conducted with all levels of e-Tracker users including immunization nurses, data managers, and supervisors from health facilities in 5 districts of Rwanda. We used an interview guide based on the constructs of the Human, Organization, and Technology-Fit (HOT-Fit) framework, and we analyzed and summarized our findings using the framework. Immunization nurses reported using the e-Tracker as a secondary data entry tool in addition to paper-based forms, which resulted in considerable dissatisfaction among nurses. While users acknowledged the potential of a digital tool compared to paper-based systems, they also reported the need for improvement of functionalities to support their work, such as digital client appointment lists, lists of defaulters, search and register functions, automated monthly reports, and linkages to birth notifications and the national identity system. Reducing dual documentation for users can improve e-Tracker use and user satisfaction. Our findings can help identify additional digital health interventions to support and strengthen the health information system for the immunization program.

The Development and Utilization of an Electronic Assessment Software in Dental Education: A Comprehensive Evaluation

Purpose/ObjectivesThis article introduces the Key Electronic Assessment Platform (KEAP), an electronic-based assessment platform created in-house at the College of Dentistry (COD), King Saud bin Abdulaziz University for Health Sciences (KSAU-HS), Riyadh, Saudi Arabia. It highlights the platform’s integral value and demand within the educational system. MethodsThe article introduces the KEAP system design and architecture, describes its features, tests, and implementation in addition to its maintenance and security. It also presents the outcomes of KEAP utilization and the level of users’ satisfaction. ResultsThe KEAP item bank has been expanded by more than 26,500 questions over the last four academic years and 1,255 exams have been administered. KEAP provides a highly secure structured framework for assessment planning, conduction, and evaluation. More than 90% of students and faculty are satisfied or very satisfied with their experience using the KEAP system indicating that it is well accepted by the end users. ConclusionsThe development of KEAP is based on contextual factors in COD, KSAU-HS with the aim of creating a process for assessment that is valid, efficient, standardized, and highly secure. KEAP’s design and successful implementation can provide a successful example of implementing electronic-based assessment in higher education.

Mitigating Alert Fatigue in Cloud Monitoring Systems: A Machine Learning Perspective

Next generation networks will be largely based on monitoring and telemetry tools that are essential for maintaining optimal performance, ensuring security, managing costs, and performing fault detection and resolution. An integral part of the overall monitoring strategy is alerting, which provides administrators with the necessary information to proactively or reactively manage and optimize network services. However, when monitoring systems generate an excessive number of alerts, many of which may not be actionable or may not represent critical issues, the phenomenon of alert fatigue occurs. Alert fatigue refers to a situation where the volume and the speed of the continuous influx of alerts becomes so overwhelming that the network administrators become desensitized and do not respond to them. To this end, and inspired by recent trends in network automation, where human intervention tends to be minimized, we introduce an alert fatigue mitigation mechanism in monitoring focusing on cloud computing infrastructures. In particular, a composite machine learning methodology is proposed in order to select which alerts will be hidden and which ones will be presented to the administrators. Additionally, to personalize the results, the proposed approach considers the level of users’ experience along with the alert features to further optimize the accuracy of the alert filtering mechanism. The research has been conducted in a realistic environment of a leading monitoring enterprise, Netdata, which provided two datasets for testing our approach. Furthermore, the attained results of the filtering mechanism were evaluated by expert engineers of the company that verified the output of the proposed framework. Specifically, the outcomes confirm that our proposed methodology mitigates the alert fatigue problem with an accuracy that surpass 90% in most cases.

TRANSFIGURATIONS OF THE COMPUTERIZED MATHEMATICS FINAL EXAM: HOW WAS THE RESULTS OF COMPUTERIZED ADAPTIVE TEST-BASED ASSESSMENT?

Abstract Computerized Adaptive Test (CAT) allows the use of targeted tests, that is, each test taker obtains items that match his or her ability level. The purpose of this research is to find out the final semester exam with the CAT model. The research methodology is descriptive quantitative. Purposive sampling technique was used to take a sample of 73 students. The results of this study indicate that the CAT used in this semester final exam based on Moodle can select test items given to test takers adaptively according to the user's ability level. The very high ability category was 42 students, the high ability category was 11 students, the medium ability category was 9 students, the low ability category was 4 students, and the very low ability category was 7 students. Overall, the ability of learners is in the high category.

"We are pleading for the government to do more": Road user perspectives on the magnitude, contributing factors, and potential solutions to road traffic injuries and deaths in Ghana.

Road traffic collisions disproportionately impact Ghana and other low- and middle-income countries. This study explored road user perspectives regarding the magnitude, contributing factors, and potential solutions to road traffic collisions, injuries, and deaths. We designed a qualitative study of 24 in-depth interviews with 14 vulnerable road users (pedestrians, occupants of powered 2- and 3-wheelers, cyclists) and ten non-vulnerable road users in four high-risk areas in November 2022. We used a mixed deductive (direct content analysis) and inductive (interpretive phenomenological analysis) approach. In the direct content analysis, a priori categories based on Haddon's Matrix covered human, vehicle, socioeconomic environment, and physical environment factors influencing road traffic collisions, along with corresponding solutions. We used inductive analysis to identify emerging themes. Participants described frequent and distressing experiences with collisions, and most often reported contributing factors, implementation gaps, and potential solutions within the human (road user) level domain of Haddon's Matrix. Implementation challenges included sporadic enforcement, reliance on road users' adherence to safety laws, and the low quality of the existing infrastructure. Participants expressed that they felt neglected and ignored by road safety decision-makers. This research emphasizes the need for community input for successful road safety policies in Ghana and other low- and middle-income countries, calling for greater governmental support an action to address this public health crisis. We recommend the government collaborates with communities to adapt existing interventions including speed calming, footbridges, and police enforcement, and introduces new measures that meet local needs.

Fairness and Diversity in Recommender Systems: A Survey

Recommender systems (RS) are effective tools for mitigating information overload and have seen extensive applications across various domains. However, the single focus on utility goals proves to be inadequate in addressing real-world concerns, leading to increasing attention to fairness-aware and diversity-aware RS. While most existing studies explore fairness and diversity independently, we identify strong connections between these two domains. In this survey, we first discuss each of them individually and then dive into their connections. Additionally, motivated by the concepts of user-level and item-level fairness, we broaden the understanding of diversity to encompass not only the item level but also the user level. With this expanded perspective on user and item-level diversity, we re-interpret fairness studies from the viewpoint of diversity. This fresh perspective enhances our understanding of fairness-related work and paves the way for potential future research directions. Papers discussed in this survey along with public code links are available at: https://github.com/YuyingZhao/Awesome-Fairness-and-Diversity-Papers-in-Recommender-Systems .