The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Yantai Shu - One of the best experts on this subject based on the ideXlab platform.
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tcp Unfairness in ad hoc wireless networks and a neighborhood red solution
ACM IEEE International Conference on Mobile Computing and Networking, 2005Co-Authors: Mario Gerla, Yantai ShuAbstract:Significant TCP Unfairness in ad hoc wireless networks has been reported during the past several years. This Unfairness results from the nature of the shared wireless medium and location dependency. If we view a node and its interfering nodes to form a "neighborhood", the aggregate of local queues at these nodes represents the distributed queue for this neighborhood. However, this queue is not a FIFO queue. Flows sharing the queue have different, dynamically changing priorities determined by the topology and traffic patterns. Thus, they get different feedback in terms of packet loss rate and packet delay when congestion occurs. In wired networks, the Randomly Early Detection (RED) scheme was found to improve TCP fairness. In this paper, we show that the RED scheme does not work when running on individual queues in wireless nodes. We then propose a Neighborhood RED (NRED) scheme, which extends the RED concept to the distributed neighborhood queue. Simulation studies confirm that the NRED scheme can improve TCP Unfairness substantially in ad hoc networks. Moreover, the NRED scheme acts at the network level, without MAC protocol modifications. This considerably simplifies its deployment.
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enhancing tcp fairness in ad hoc wireless networks using neighborhood red
ACM IEEE International Conference on Mobile Computing and Networking, 2003Co-Authors: Mario Gerla, Yantai ShuAbstract:Significant TCP Unfairness in ad hoc wireless networks has been reported during the past several years. This Unfairness results from the nature of the shared wireless medium and location dependency. If we view a node and its interfering nodes to form a "neighborhood", the aggregate of local queues at these nodes represents the distributed queue for this neighborhood. However, this queue is not a FIFO queue. Flows sharing the queue have different, dynamically changing priorities determined by the topology and traffic patterns. Thus, they get different feedback in terms of packet loss rate and packet delay when congestion occurs. In wired networks, the Randomly Early Detection (RED) scheme was found to improve TCP fairness. In this paper, we show that the RED scheme does not work when running on individual queues in wireless nodes. We then propose a Neighborhood RED (NRED) scheme, which extends the RED concept to the distributed neighborhood queue. Simulation studies confirm that the NRED scheme can improve TCP Unfairness substantially in ad hoc networks. Moreover, the NRED scheme acts at the network level, without MAC protocol modifications. This considerably simplifies its deployment.
Roberto De Vogli - One of the best experts on this subject based on the ideXlab platform.
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perceived teacher Unfairness and headache in adolescence a cross national comparison
International Journal of Public Health, 2013Co-Authors: Michela Lenzi, Roberto De Vogli, Massimo Santinello, Alessio Vieno, Veronika Ottova, Tibor Baska, Robert Griebler, Inese Gobina, Margarida Gaspar De MatosAbstract:OBJECTIVES: The present study examines the prevalence of headache in early adolescents in 21 European and North-American countries and the role of perceived teacher Unfairness in predicting this health complaint across different countries. METHODS: Data were taken from the "Health Behaviour in School-aged Children" study (HBSC), a World Health Organization cross-national survey on health behaviors in 11-, 13- and 15-year-old students. Headache and perceived teacher Unfairness were measured through a self-administered questionnaire filled out by 115,212 adolescents. RESULTS: The overall prevalence of frequent headaches (at least once a week) was 28.8%, ranging from 18.9% in Slovenia to 49.4% in Israel. After adjusting for gender, grade, family affluence, school achievement, being bullied and lifestyles (drinking, smoking, eating and physical activity), teacher Unfairness showed a significant association with frequent headache in all but two countries (Ukraine and Luxembourg). CONCLUSIONS: Our results show that headache is a common health symptom in European and North-American countries, even though there are substantial differences in its prevalence across countries. The study indicates that perceived teacher Unfairness can be a significant predictor of frequent headache during adolescence, and this association is consistent across countries. Language: en
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primary headache in italian early adolescents the role of perceived teacher Unfairness
Headache, 2009Co-Authors: Massimo Santinello, Alessio Vieno, Roberto De VogliAbstract:Background.- The impact of perceived teacher Unfairness on headache incidence has previously been insufficiently investigated. Objective.- The aims of the study are to analyze the prevalence of headache among Italian early adolescents as well as to examine the role of perceived teacher Unfairness and classmate social support in predicting this health outcome. Methods.- Data were taken from the "Health Behaviour in School Aged Children," a cross-sectional survey investigating health behaviors among early adolescents in selected European countries. Headache, perceived teacher Unfairness, and classmate social support were measured through a self-administered questionnaire filled out by a representative sample of 4386 (48.4% males) Italian students (11, 13, and 15 years old). Covariates included demographic characteristics (age, gender) and socioeconomic status (parental educational attainment), and other confounding psychological factors (eg, family empowerment, bullying). Results.- Prevalence of frequent headaches (at least once a week) was about 40%. Girls were more likely to report frequent headaches compared with boys. Prevalence of frequent headaches increased with age. After adjusting for age and gender, teacher Unfairness showed a significant association with frequent headache (P Language: en
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Unfairness and the social gradient of metabolic syndrome in the whitehall ii study
Journal of Psychosomatic Research, 2007Co-Authors: Roberto De Vogli, Eric J Brunner, Michael MarmotAbstract:Objectives: Little work has investigated the relationship between Unfairness and risk factors for heart disease. We examine the role of Unfairness in predicting the metabolic syndrome and explaining the social gradient of the metabolic syndrome. Methods: The design is a prospective study with an average follow-up of 5.8 years. Participants were 4128 males and 1715 females of 20 civil service departments in London (Whitehall II study). Sociodemographics, Unfairness, employment grade, behavioral risk factors, and other psychosocial factors were measured at baseline (Phase 3, 1991-1993). Waist circumference, triglycerides, high-density lipoprotein (HDL) cholesterol, fasting glucose, and hypertension were used to define metabolic syndrome at follow-up (Phase 5, 1997-2000), according to the National Cholesterol Education Program/Adult Treatment Panel III guidelines. Results: Unfairness is positively associated with waist circumference, hypertension, triglycerides, and fasting glucose and negatively associated with serum HDL cholesterol. High levels of Unfairness are also associated with the metabolic syndrome [odds ratio (OR)=1.72, 95% CI=1.31-2.25], after adjustment for age and gender. After additional adjustment for employment grade, behavioral risk factors, and other psychosocial factors, the relationship between high Unfairness and metabolic syndrome weakened but remained significant (OR=1.37, 95% CI=1.00-1.93). When adjusting for Unfairness, the social gradient of metabolic syndrome was reduced by approximately 10%. Conclusion: Unfairness may be a risk factor for the metabolic syndrome and its components. Future research is needed to study the biological mechanisms linking Unfairness and the metabolic syndrome.
Mario Gerla - One of the best experts on this subject based on the ideXlab platform.
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tcp Unfairness in ad hoc wireless networks and a neighborhood red solution
ACM IEEE International Conference on Mobile Computing and Networking, 2005Co-Authors: Mario Gerla, Yantai ShuAbstract:Significant TCP Unfairness in ad hoc wireless networks has been reported during the past several years. This Unfairness results from the nature of the shared wireless medium and location dependency. If we view a node and its interfering nodes to form a "neighborhood", the aggregate of local queues at these nodes represents the distributed queue for this neighborhood. However, this queue is not a FIFO queue. Flows sharing the queue have different, dynamically changing priorities determined by the topology and traffic patterns. Thus, they get different feedback in terms of packet loss rate and packet delay when congestion occurs. In wired networks, the Randomly Early Detection (RED) scheme was found to improve TCP fairness. In this paper, we show that the RED scheme does not work when running on individual queues in wireless nodes. We then propose a Neighborhood RED (NRED) scheme, which extends the RED concept to the distributed neighborhood queue. Simulation studies confirm that the NRED scheme can improve TCP Unfairness substantially in ad hoc networks. Moreover, the NRED scheme acts at the network level, without MAC protocol modifications. This considerably simplifies its deployment.
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enhancing tcp fairness in ad hoc wireless networks using neighborhood red
ACM IEEE International Conference on Mobile Computing and Networking, 2003Co-Authors: Mario Gerla, Yantai ShuAbstract:Significant TCP Unfairness in ad hoc wireless networks has been reported during the past several years. This Unfairness results from the nature of the shared wireless medium and location dependency. If we view a node and its interfering nodes to form a "neighborhood", the aggregate of local queues at these nodes represents the distributed queue for this neighborhood. However, this queue is not a FIFO queue. Flows sharing the queue have different, dynamically changing priorities determined by the topology and traffic patterns. Thus, they get different feedback in terms of packet loss rate and packet delay when congestion occurs. In wired networks, the Randomly Early Detection (RED) scheme was found to improve TCP fairness. In this paper, we show that the RED scheme does not work when running on individual queues in wireless nodes. We then propose a Neighborhood RED (NRED) scheme, which extends the RED concept to the distributed neighborhood queue. Simulation studies confirm that the NRED scheme can improve TCP Unfairness substantially in ad hoc networks. Moreover, the NRED scheme acts at the network level, without MAC protocol modifications. This considerably simplifies its deployment.
Angela Zhou - One of the best experts on this subject based on the ideXlab platform.
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Residual Unfairness in Fair Machine Learning from Prejudiced Data
arXiv: Machine Learning, 2018Co-Authors: Nathan Kallus, Angela ZhouAbstract:Recent work in fairness in machine learning has proposed adjusting for fairness by equalizing accuracy metrics across groups and has also studied how datasets affected by historical prejudices may lead to unfair decision policies. We connect these lines of work and study the residual Unfairness that arises when a fairness-adjusted predictor is not actually fair on the target population due to systematic censoring of training data by existing biased policies. This scenario is particularly common in the same applications where fairness is a concern. We characterize theoretically the impact of such censoring on standard fairness metrics for binary classifiers and provide criteria for when residual Unfairness may or may not appear. We prove that, under certain conditions, fairness-adjusted classifiers will in fact induce residual Unfairness that perpetuates the same injustices, against the same groups, that biased the data to begin with, thus showing that even state-of-the-art fair machine learning can have a "bias in, bias out" property. When certain benchmark data is available, we show how sample reweighting can estimate and adjust fairness metrics while accounting for censoring. We use this to study the case of Stop, Question, and Frisk (SQF) and demonstrate that attempting to adjust for fairness perpetuates the same injustices that the policy is infamous for.
Massimo Santinello - One of the best experts on this subject based on the ideXlab platform.
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perceived teacher Unfairness and headache in adolescence a cross national comparison
International Journal of Public Health, 2013Co-Authors: Michela Lenzi, Roberto De Vogli, Massimo Santinello, Alessio Vieno, Veronika Ottova, Tibor Baska, Robert Griebler, Inese Gobina, Margarida Gaspar De MatosAbstract:OBJECTIVES: The present study examines the prevalence of headache in early adolescents in 21 European and North-American countries and the role of perceived teacher Unfairness in predicting this health complaint across different countries. METHODS: Data were taken from the "Health Behaviour in School-aged Children" study (HBSC), a World Health Organization cross-national survey on health behaviors in 11-, 13- and 15-year-old students. Headache and perceived teacher Unfairness were measured through a self-administered questionnaire filled out by 115,212 adolescents. RESULTS: The overall prevalence of frequent headaches (at least once a week) was 28.8%, ranging from 18.9% in Slovenia to 49.4% in Israel. After adjusting for gender, grade, family affluence, school achievement, being bullied and lifestyles (drinking, smoking, eating and physical activity), teacher Unfairness showed a significant association with frequent headache in all but two countries (Ukraine and Luxembourg). CONCLUSIONS: Our results show that headache is a common health symptom in European and North-American countries, even though there are substantial differences in its prevalence across countries. The study indicates that perceived teacher Unfairness can be a significant predictor of frequent headache during adolescence, and this association is consistent across countries. Language: en
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primary headache in italian early adolescents the role of perceived teacher Unfairness
Headache, 2009Co-Authors: Massimo Santinello, Alessio Vieno, Roberto De VogliAbstract:Background.- The impact of perceived teacher Unfairness on headache incidence has previously been insufficiently investigated. Objective.- The aims of the study are to analyze the prevalence of headache among Italian early adolescents as well as to examine the role of perceived teacher Unfairness and classmate social support in predicting this health outcome. Methods.- Data were taken from the "Health Behaviour in School Aged Children," a cross-sectional survey investigating health behaviors among early adolescents in selected European countries. Headache, perceived teacher Unfairness, and classmate social support were measured through a self-administered questionnaire filled out by a representative sample of 4386 (48.4% males) Italian students (11, 13, and 15 years old). Covariates included demographic characteristics (age, gender) and socioeconomic status (parental educational attainment), and other confounding psychological factors (eg, family empowerment, bullying). Results.- Prevalence of frequent headaches (at least once a week) was about 40%. Girls were more likely to report frequent headaches compared with boys. Prevalence of frequent headaches increased with age. After adjusting for age and gender, teacher Unfairness showed a significant association with frequent headache (P Language: en
