Network Traffic Adaptation For Cloud Games

With the arrival of cloud technology, game accessibility and ubiquity have a bright future; Games can be hosted in a centralize server and accessed through the Internet by a thin client on a wide variety of devices with modest capabilities: cloud gaming. However, current cloud gaming systems have very strong requirements in terms of network resources, thus reducing the accessibility and ubiquity of cloud games, because devices with little bandwidth and people located in area with limited and unstable network connectivity, cannot take advantage of these cloud services. In this paper we present an adaptation technique inspired by the level of detail (LoD) approach in 3D graphics. It delivers multiple platform accessibility and network adaptability, while improving user's quality of experience (QoE) by reducing the impact of poor and unstable network parameters (delay, packet loss, jitter) on game interactivity. We validate our approach using a prototype game in a controlled environment and characterize the user QoE in a pilot experiment. The results show that the proposed framework provides a significant QoE enhancement

Level of detail based AI adaptation for agents in video games

This paper suggests multi-agent systems (MASs) for implementing game artificial intelligence (AI) for video games. One of main hindrances against using MASs technology in video games has been the real-time con- straints for frame rendering. In order to deal with the real-time constraints, we introduce an adaptation-oriented approach for maintaining frame rate in acceptable ranges. The adaptation approach is inspired from the level of detail (LoD) technique in 3D graphics. We introduce agent organizations for defining different roles of agents in game AI. The computational requirements of agent roles have been prioritized according to their functional roles in a game. In this way, adapting computational requirements of game AI works as a means for maintaining frame rate in acceptable ranges. The proposed approach has been evaluated through a pilot experiment by using a proof of concept game. The pilot experiment shows that LoD based adaptation allows maintaining frame rate in acceptable ranges and therefore enhancing the quality of service

Patient perspectives on online medication information seeking in Uganda: a cross-sectional exploration

This study explores pharmacists’ experiences and attitudes towards online medical information shared with them by their patients. A self-administered online survey questionnaire was designed and administered to 113 pharmacists within Kampala metropolitan, Uganda. The survey results highlight growth in patients’ inquiries about online acquired medication-related information from their pharmacists (n=105, 93%). Pharmacists highlighted that this online information-seeking behaviour enhances patients’ understanding of treatment. While generally, pharmacists in Uganda hold a positive attitude towards this trend, they, however, raised some concerns over the inaccuracy of online medication-related information presented to them by their patients 66 (58%), the internet promotion of unnecessary fear and worry about medication n=96 (92%), and the tendency for patients to take up more of the pharmacists’ time during their visits (n=68, 60%). Finally, this study revealed that pharmacist gender (r=0.722, t=9.078, p=0.000) and pharmacy ownership status (r=0.504, t=4.107, p=0.000) had a statistically significant relationship with pharmacists’ attitude towards patients’ acquisition of online medication-related information. Conclusively, this study shows that pharmacists in Kampala (Uganda) have a generally positive view of the online medication-related information-seeking by patients. This result suggests that technology use, specifically the Internet, in addressing healthcare needs is embraced in Sub-Saharan Africa. Therefore, this research contributes to the literature exploring online perceptions and attitudes towards medication related information-seeking among pharmacists

Detection and discrimination of cracked digitized paintings based on image processing methodology

With the passage of time, paintings can be damaged, and common deteriorations found in ancient paintings include cracking. Cracks can be caused by many factors, such as ageing, drying, and mechanical factors. The detection and restoration of crack formation on the earliest digitized paint surface concede great significance and safety for cultural heritages. particular, this paper is based on image processing methodology to detect and discriminate cracks. First, images are enhanced in the preprocessing stage for further processing. Then two proposed algorithms are employed to detect and separate medium and thin crack images. The experiments show better results compared with previous work. This study also confirms that the proposed image processing algorithms are an efficient and robust tool for the detection and discrimination of cracks

Deploying blockchains to simplify AI algorithm auditing

Artificial Intelligence has largely occupied various sectors in the world. A huge number of business companies have incorporated several machine learning algorithms for day-to-day decision making. With increasing applications of AI algorithms, the concerns regarding its outcomes have also increased due to bias. In AI algorithms, bias occurs due to multiple reasons including incomplete data, skewed data, human error and so on. These algorithms have the tendency to amplify partially and discrimination in the results instead of benefiting them. This makes it compulsory for the algorithms to be audited. Currently, AI algorithm auditing processes have several challenges including tendency of biases to be deeply ingrained into the system, making these difficult to mitigate; lack of transparency in decision making and many more. This study presents the emerging technology of blockchains to be a viable solution to the existing problem. It comprehensively discusses the suitability of blockchains for transparency in the process of algorithm auditing which is bound to easily capture the issue and the layer consisting it. Consequently, the process of algorithm auditing will be more convenient and more productive. Moreover, this review also discusses some potential challenges that need to be addressed and some future recommendations for this integration

Applied gamification to enhance customer loyalty for fintech industry

In this study, a mobile application prototype for fintech industry is proposed which aims to addresses users’ problems and engage them based on incentivized mechanism through applied gamification used for the users. Users will perform transactions and in return get some points as rewards, which they can use for cashback rewards or send these points to someone they want. For this research, Figma is used as a tool for designing wireframes and prototypes which later included in UseBerry to perform usability tests from users to collect their responses. Around 50 participants have been invited to collect their responses based on using the prototype and answering a few questions based on that. Results have shown an enormously positive response from users who really want to get incentives through their daily transactions and can get whatever benefits they are provided. However, this research is limited to a few features and more features and testing can be done based on the current response from the users which will directly impact user’s daily life and improve conversions for the banking and fintech industry

Mapping 123 million neonatal, infant and child deaths between 2000 and 2017

Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2—to end preventable child deaths by 2030—we need consistently estimated data at the subnational level regarding child mortality rates and trends. Here we quantified, for the period 2000–2017, the subnational variation in mortality rates and number of deaths of neonates, infants and children under 5 years of age within 99 low- and middle-income countries using a geostatistical survival model. We estimated that 32% of children under 5 in these countries lived in districts that had attained rates of 25 or fewer child deaths per 1,000 live births by 2017, and that 58% of child deaths between 2000 and 2017 in these countries could have been averted in the absence of geographical inequality. This study enables the identification of high-mortality clusters, patterns of progress and geographical inequalities to inform appropriate investments and implementations that will help to improve the health of all populations

Mapping child growth failure across low- and middle-income countries

Child growth failure (CGF), manifested as stunting, wasting, and underweight, is associated with high 5 mortality and increased risks of cognitive, physical, and metabolic impairments. Children in low- and middle-income countries (LMICs) face the highest levels of CGF globally. Here we illustrate national and subnational variation of under-5 CGF indicators across LMICs, providing 2000–2017 annual estimates mapped at a high spatial resolution and aggregated to policy-relevant administrative units and national levels. Despite remarkable declines over the study period, many LMICs remain far from the World Health 10 Organization’s ambitious Global Nutrition Targets to reduce stunting by 40% and wasting to less than 5% by 2025. Large disparities in prevalence and rates of progress exist across regions, countries, and within countries; our maps identify areas where high prevalence persists even within nations otherwise succeeding in reducing overall CGF prevalence. By highlighting where subnational disparities exist and the highest-need populations reside, these geospatial estimates can support policy-makers in planning locally 15 tailored interventions and efficient directing of resources to accelerate progress in reducing CGF and its health implications

Mapping disparities in education across low- and middle-income countries

Analyses of the proportions of individuals who have completed key levels of schooling across all low- and middle-income countries from 2000 to 2017 reveal inequalities across countries as well as within populations. Educational attainment is an important social determinant of maternal, newborn, and child health(1-3). As a tool for promoting gender equity, it has gained increasing traction in popular media, international aid strategies, and global agenda-setting(4-6). The global health agenda is increasingly focused on evidence of precision public health, which illustrates the subnational distribution of disease and illness(7,8); however, an agenda focused on future equity must integrate comparable evidence on the distribution of social determinants of health(9-11). Here we expand on the available precision SDG evidence by estimating the subnational distribution of educational attainment, including the proportions of individuals who have completed key levels of schooling, across all low- and middle-income countries from 2000 to 2017. Previous analyses have focused on geographical disparities in average attainment across Africa or for specific countries, but-to our knowledge-no analysis has examined the subnational proportions of individuals who completed specific levels of education across all low- and middle-income countries(12-14). By geolocating subnational data for more than 184 million person-years across 528 data sources, we precisely identify inequalities across geography as well as within populations.Peer reviewe