Ryerson University

About: Ryerson University is a education organization based out in Toronto, Ontario, Canada. It is known for research contribution in the topics: Population & Poison control. The organization has 7671 authors who have published 20164 publications receiving 394976 citations. The organization is also known as: Ryerson Polytechnical Institute & Ryerson Institute of Technology.

Great Expectations: The Relation Between Expectancies and Adjustment During the Transition to University1

Abstract: The nature of students' expectations about university, and their relation with adjustment in university, were examined in a longitudinal investigation. Prior to starting university, participants responded to open-ended questions regarding their expectations about university. At this time, and during their 1st, 2nd, and 4th years of study, measures of adjustment were completed. Four distinct types of expectations about university were identified: optimistic, prepared, fearful, and complacent. Students whose expectations were fearful reported more stress, depression, and poorer university adjustment than did individuals with other types of expectations, particularly prepared. Moreover, group differences in university adjustment existed throughout students' 4 years at university, and were not attributable to self-reported previous levels of personal adjustment or academic achievement.

An architecture for integrating UMTS and 802.11 WLAN networks

Abstract: Cellular networks, e.g. UMTS provide voice and data services to mobile users. In hot spots where users need high speed data services operators can deploy low-cost high-speed WLANs, e.g. 802.11, to cover hot-spots. This paper proposes a possible architecture of integrating UMTS and 802.11 WLAN. The architecture allows a mobile node to maintain data (PS) connection through WLAN and voice (CS) connection through UMTS in parallel. This is especially attractive because WLAN is currently used primarily for high-speed best-effort data service only.

Deep Reinforcement Learning for Collaborative Edge Computing in Vehicular Networks

Abstract: Mobile edge computing (MEC) is a promising technology to support mission-critical vehicular applications, such as intelligent path planning and safety applications. In this paper, a collaborative edge computing framework is developed to reduce the computing service latency and improve service reliability for vehicular networks. First, a task partition and scheduling algorithm (TPSA) is proposed to decide the workload allocation and schedule the execution order of the tasks offloaded to the edge servers given a computation offloading strategy. Second, an artificial intelligence (AI) based collaborative computing approach is developed to determine the task offloading, computing, and result delivery policy for vehicles. Specifically, the offloading and computing problem is formulated as a Markov decision process. A deep reinforcement learning technique, i.e., deep deterministic policy gradient, is adopted to find the optimal solution in a complex urban transportation network. By our approach, the service cost, which includes computing service latency and service failure penalty, can be minimized via the optimal workload assignment and server selection in collaborative computing. Simulation results show that the proposed AI-based collaborative computing approach can adapt to a highly dynamic environment with outstanding performance.

Effect of self-healing on strength and durability of zeolite-immobilized bacterial cementitious mortar composites

Abstract: There is a compelling economic incentive to develop concrete materials that can repair its own damage, increase durability and prevent structural failure This research investigated the potential of adding two different mineral producing bacteria into two types of cementitious mortar matrix to enhance self-healing ability for autonomous crack repair In this study, zeolite was used as a carrier material to protect bacteria in high pH environment normally exists in concrete The spore forming ability and ureolytic activity of zeolite-immobilized bacteria were investigated in order to examine potential for producing healing compounds The self-healing ability of bacteria incorporated normal and fiber reinforced mortars was judged based on the development of compressive strength and permeation properties of cracked specimens with age as well as micro-structural characterization of crack healing compounds using scanning electron microscopy (SEM), energy dispersive spectrometer (EDS) and X-ray diffraction