Dissecting Cloud Gaming Performance with DECAF

Cloud gaming platforms have witnessed tremendous growth over the past two years with a number of large Internet companies including Amazon, Facebook, Google, Microsoft, and Nvidia publicly launching their own platforms. While cloud gaming platforms continue to grow, the visibility in their performance and relative comparison is lacking. This is largely due to absence of systematic measurement methodologies which can generally be applied. As such, in this paper, we implement DECAF, a methodology to systematically analyze and dissect the performance of cloud gaming platforms across different game genres and game platforms. DECAF is highly automated and requires minimum manual intervention. By applying DECAF, we measure the performance of three commercial cloud gaming platforms including Google Stadia, Amazon Luna, and Nvidia GeForceNow, and uncover a number of important findings. First, we find that processing delays in the cloud comprise majority of the total round trip delay experienced by users, accounting for as much as 73.54% of total user-perceived delay. Second, we find that video streams delivered by cloud gaming platforms are characterized by high variability of bitrate, frame rate, and resolution. Platforms struggle to consistently serve 1080p/60 frames per second streams across different game genres even when the available bandwidth is 8-20× that of platform's recommended settings. Finally, we show that game platforms exhibit performance cliffs by reacting poorly to packet losses, in some cases dramatically reducing the delivered bitrate by up to 6.6× when loss rates increase from 0.1% to 1%. Our work has important implications for cloud gaming platforms and opens the door for further research on comprehensive measurement methodologies for cloud gaming.

OmniCrawl: Comprehensive Measurement of Web Tracking With Real Desktop and Mobile Browsers

Over half of all visits to websites now take place in a mobile browser, yet the majority of web privacy studies take the vantage point of desktop browsers, use emulated mobile browsers, or focus on just a single mobile browser instead. In this paper, we present a comprehensive web-tracking measurement study on mobile browsers and privacy-focused mobile browsers. Our study leverages a new web measurement infrastructure, OmniCrawl, which we develop to drive browsers on desktop computers and smartphones located on two continents. We capture web tracking measurements using 42 different non-emulated browsers simultaneously. We find that the third-party advertising and tracking ecosystem of mobile browsers is more similar to that of desktop browsers than previous findings suggested. We study privacy-focused browsers and find their protections differ significantly and in general are less for lower-ranked sites. Our findings also show that common methodological choices made by web measurement studies, such as the use of emulated mobile browsers and Selenium, can lead to website behavior that deviates from what actual users experience.

The method on measuring utilization index of agricultural technology

Utilization of technology as a research result is the foremost indicator towards the success of R&D as well as the measure of the multiplier effect concerning the usage of R&D budgets. However, to define the indicators and measurement of technology benefits is less considered. This study was aimed to determine the scope, indicators, and comprehensive measurement methods on the utilization of technology in the form of an index to standardize the value. Through literature studies, benchmarking of previous models and Focus Group Discussions, the measurement indicators of technology utilization index include: the availability of technology at the user’s location, the distribution of technology adoption, technology benefits, technology accessibility and user acceptance. Every variable for each indicator was based on the type of technology. The method for measuring the level of technology utilization using a composite index of four variables and calculation was carried out by weighting the importance of each variables based on the eigein value of Analytical Hierarchy Process. Three utilization categories were not utilized (index <1); underutilized (index 1 to 3); and high utilized (index> 3). As an example, the utilization index of a new superior varieties (VUB) of rice was high (3.75) with relatively good indicators on technology benefits and availability of VUB rice seed at the user’s location. Furthermore, the result implies that the method on measuring the utilization index is adequate to be widely applied for other types of technology.

Examination of Social Determinants of Health, District Health Needs, School Nurse Caseload, and Academic Outcomes in Washington State

The purpose of this study was to examine associations between caseload, social determinants, health needs, students meeting grade-level English and Math standards, and attendance. Data from the Washington State Open Data Portal and Report Card were combined with District Health Assessment data from 264 school districts. Analyses of variance and linear stepwise regression analyses were conducted. Key findings indicate significant differences in English and Math outcomes by caseloads, with higher caseload districts have lower percentages of students meeting English and Math standards, but not attendance. Caseload is a significant predictor of students meeting English and Math standards, after controlling for social determinants and district health needs. Findings point to the complexity of school nursing work and builds a foundation to guide future nursing research. Large prospective studies that allow for comprehensive measurement of structure, process and outcomes variables are needed to advance school nursing research.

Measuring the Total Logistics Costs at the Macro Level: A Study of Indonesia

Background: Efforts made to calculate the logistics costs in Indonesia, at the macro level, are facing various problems, due to the fact that there have been no national agreements—to any models employed—to calculate those costs. Moreover, limited data and information due to the lack of use of such integrated information technology to reduce the information asymmetry on the logistics processes and activities have created some additional problems. Objective: This study is aimed at reviewing the measurement model, of the logistics costs used in Indonesia, at the macro level. Method: It provides a potential measurement approach proposed by several previous studies as an alternative option that may help develop the existing models by elaborating on their limitations. Results: The results of this study emphasize the recognition of the components of the logistics costs and the formulation of a more accurate, transparent, and comprehensive measurement framework to improve the standard used to assess the logistics costs. Conclusion: Thus, the calculation output of the logistics costs is expected to be able to provide stakeholders with reliable information to develop an efficient logistics system. Furthermore, logistics costs will be more controllable, allowing Indonesia to achieve such comparative advantages.

Physical Activity Interventions and Their Effects on Cognitive Function in People with Dementia: A Systematic Review and Meta-Analysis

Background: Physical activity (PA) has emerged as an alternative nonpharmacological approach to effectively address the effects of dementia. The primary aim was to identify and summarize PA interventions and their effects on cognitive function among persons with dementia (PwD). Methods: A systematic review was conducted with a meta-analysis using different electronic databases, such as PubMed, Embase, APA PsycNET, and the Web of Science. The identified and selected studies were randomized controlled trials (RCTs) that were written in English, published between 2000 and 2020, and implemented among PwD who received a PA intervention and whose cognitive function was measured at baseline and during a follow-up. Results: Twenty-two PA intervention studies met the eligibility criteria and showed a medium-size effect on the cognitive function of PwD, 0.4803 (95% CI = 0.1901–0.7704), with a high percentage of heterogeneity (I2 = 86%, p ≤ 0.0001). Moreover, this review complements other reviews by including eight studies that have not previously been considered. Overall, studies have methodological limitations. However, six studies implemented in the past five years have shown more robust methodological designs, including larger sample sizes and more comprehensive measurement tools. Conclusion: It is not yet possible to draw a conclusion on the ideal PA intervention for this population due to the high proportion of heterogeneity within the included studies. More emphasis is needed on the intensity of PA monitoring and adherence to such programs.