An Investigation of Darwiche and Pearl's Postulates for Iterated Belief Update

Belief revision and update, two significant types of belief change, both focus on how an agent modify her beliefs in presence of new information. The most striking difference between them is that the former studies the change of beliefs in a static world while the latter concentrates on a dynamically-changing world. The famous AGM and KM postulates were proposed to capture rational belief revision and update, respectively. However, both of them are too permissive to exclude some unreasonable changes in the iteration. In response to this weakness, the DP postulates and its extensions for iterated belief revision were presented. Furthermore, Rodrigues integrated these postulates in belief update. Unfortunately, his approach does not meet the basic requirement of iterated belief update. This paper is intended to solve this problem of Rodrigues's approach. Firstly, we present a modification of the original KM postulates based on belief states. Subsequently, we migrate several well-known postulates for iterated belief revision to iterated belief update. Moreover, we provide the exact semantic characterizations based on partial preorders for each of the proposed postulates. Finally, we analyze the compatibility between the above iterated postulates and the KM postulates for belief update

TCon: A transparent congestion control deployment platform for optimizing WAN transfers

Nowadays, many web services (e.g., cloud storage) are deployed inside datacenters and may trigger transfers to clients through WAN. TCP congestion control is a vital component for improving the performance (e.g., latency) of these services. Considering complex networking environment, the default congestion control algorithms on servers may not always be the most efficient, and new advanced algorithms will be proposed. However, adjusting congestion control algorithm usually requires modification of TCP stacks of servers, which is difficult if not impossible, especially considering different operating systems and configurations on servers. In this paper, we propose TCon, a light-weight, flexible and scalable platform that allows administrators (or operators) to deploy any appropriate congestion control algorithms transparently without making any changes to TCP stacks of servers. We have implemented TCon in Open vSwitch (OVS) and conducted extensive test-bed experiments by transparently deploying BBR congestion control algorithm over TCon. Test-bed results show that the BBR over TCon works effectively and the performance stays close to its native implementation on servers, reducing latency by 12.76% on average

A fine-grained and transparent congestion control enforcement scheme

In practice, a single TCP congestion control is often used to handle all TCP connections on a Web server, e.g., Cubic for Linux by default. Considering complex and ever-changing networking environment, the default congestion control algorithm may not always be the most suitable one. Adjusting congestion control usually to meet different networking scenarios requires modification of servers' TCP stacks. This is difficult, if not impossible, due to various operating systems and different configurations on the servers. In this paper, we propose Mystique, a light-weight and flexible scheme that allows administrators (or operators) to deploy any congestion control schemes transparently without changing existing TCP stacks on servers. We have implemented Mystique in Open vSwitch (OVS) and conducted extensive test-bed experiments in public cloud environments. We have extensively evaluated Mystique and the results have demonstrated that it is able to effectively adapt to varying network conditions, and can always employ the most suitable congestion control for each TCP connection. Mystique can significantly reduce latency by up to 37.8% in comparison with other congestion controls

Mystique: a fine-grained and transparent congestion control enforcement scheme

TCP congestion control is a vital component for the latency of Web services. In practice, a single congestion control mechanism is often used to handle all TCP connections on a Web server, e.g., Cubic for Linux by default. Considering complex and ever-changing networking environment, the default congestion control may not always be the most suitable one. Adjusting congestion control to meet different networking scenarios usually requires modification of TCP stacks on a server. This is difficult, if not impossible, due to various operating system and application configurations on production servers. In this paper, we propose Mystique, a light-weight, flexible, and dynamic congestion control switching scheme that allows network or server administrators to deploy any congestion control schemes transparently without modifying existing TCP stacks on servers. We have implemented Mystique in Open vSwitch (OVS) and conducted extensive testbed experiments in both public and private cloud environments. Experiment results have demonstrated that Mystique is able to effectively adapt to varying network conditions, and can always employ the most suitable congestion control for each TCP connection. More specifically, Mystique can significantly reduce latency by 18.13% on average when compared with individual congestion controls

Reliable Mobile IP Multicast Based on Hierarchical Local Registration

In a mobile wireless networks, mobile link transmission is unreliable, the packets are easily lost, and the mobility of nodes may cause asynchronous problem. In order to resolve the problems of multicast reliability in wireless networks, a framework architecture of the mobile IP multicast is proposed, which is a reliable multicast architecture based on hierarchical local registration. Hierarchical management is taken use to shield the movements of mobile nodes in the domain. As a surprising result of that, the stability of multicast forwarding trees is improved. Besides, the switching delay and the resulting packets loss are reduced. A multicast information exchange center is set in the root node. The arrived multicast data is cached in the center until it is received by all mobile nodes in the domain. When any exchanges occur in nodes, the retransmission message is sent to the exchange center to retransmit the lost packets. In that case, the synchronization problem can be solved, and reliable multicast services for mobile nodes are provided

Generalized Linear Integer Numeric Planning

Classical planning aims to find a sequence of actions that guarantees goal achievement from an initial state. The representative framework of classical planning is based on propositional logic. Due to the weak expressiveness of propositional logic, many applications of interest cannot be formalized as a classical planning problem. Some extensions such as numeric planning and generalized planning (GP) are therefore proposed. Qualitative numeric planning (QNP) is a decidable class of numeric and generalized extensions and serves as a numeric abstraction of GP. However, QNP is still far from being perfect and needs further improvement. In this paper, we introduce another generalized version of numeric planning, namely generalized linear integer numeric planning(GLINP), which is a more suitable abstract framework of GP than QNP. In addition, we develop a general framework to synthesize solutions to GLINP problems. Finally, we evaluate our approach on a number of benchmarks, and experimental results justify the effectiveness and scalability of our proposed approach

Students’ experience of online learning during the COVID-19 pandemic:a province-wide survey study

Online learning is currently adopted by educational institutions worldwide to provide students with ongoing education during the COVID‐19 pandemic. Even though online learning research has been advancing in uncovering student experiences in various settings (i.e., tertiary, adult, and professional education), very little progress has been achieved in understanding the experience of the K‐12 student population, especially when narrowed down to different school‐year segments (i.e., primary and secondary school students). This study explores how students at different stages of their K‐12 education reacted to the mandatory full‐time online learning during the COVID‐19 pandemic. For this purpose, we conducted a province‐wide survey study in which the online learning experience of 1,170,769 Chinese students was collected from the Guangdong Province of China. We performed cross‐tabulation and Chi‐square analysis to compare students’ online learning conditions, experiences, and expectations. Results from this survey study provide evidence that students’ online learning experiences are significantly different across school years. Foremost, policy implications were made to advise government authorises and schools on improving the delivery of online learning, and potential directions were identified for future research into K‐12 online learning. PRACTITIONER NOTES: : Online learning has been widely adopted during the COVID‐19 pandemic to ensure the continuation of K‐12 education. Student success in K‐12 online education is substantially lower than in conventional schools. Students experienced various difficulties related to the delivery of online learning. : Provide empirical evidence for the online learning experience of students in different school years. Identify the different needs of students in primary, middle, and high school. Identify the challenges of delivering online learning to students of different age. : Authority and schools need to provide sufficient technical support to students in online learning. The delivery of online learning needs to be customised for students in different school years

Extensive evaluation on the performance and behaviour of TCP congestion control protocols under varied network scenarios

In recent decades, many TCP Congestion Control (CC) protocols have been proposed to improve the performance and reliability of TCP in various network scenarios. However, CC protocols are usually closely coupled with network conditions such as latency and packet loss. Considering that networks with different properties are common, e.g., wired/wireless LAN and Long Fat Networks (LFNs), investigating both performance and behaviors of CC protocols under varied network scenarios becomes crucial for both network management and development. In this paper, we conduct a comprehensive measurement study on the goodput, RTT, retransmission, friendliness, fairness, convergence time and stability of most widely-used CC protocols over wired LAN/WAN and wireless LAN (both 2.4GHz and 5GHz Wi-Fi). We also conduct comparative studies with respect to transmission cost, congested reverse path and bottleneck queue size in network simulator. Based on our analysis, we reveal several interesting and original observations. We found that the goodput of BBR is at least 22.5% lower than other CC protocols in wireless LAN due to insufficient pacing rate, even though it can always fully utilize the bottleneck bandwidth with low RTT in wired networks. We also observed that the total on-wire data volume of BBR is higher than CUBIC (e.g., 2.37% higher when RTT = 100ms and loss rate = 0.01%). In addition, BBR can fully utilize the bottleneck bandwidth in most queue sizes (≥ 20packets). Surprisingly, we noticed that as the default CC protocol in most modern operating systems, CUBIC is too aggressive and unfriendly in both LAN and wireless LAN, greatly suppressing the goodput of other competing CC protocols. More specifically for CUBIC in wireless LAN, it generates 129% more retransmissions than other CC protocols. Nevertheless, we have also seen that, in scenario with heavily-congested reverse path, CUBIC can provide full utilization on bottleneck bandwidth. Lastly, we also observed that BBR converges very quickly in all evaluated scenarios, while other CC protocols present varied results, e.g., Westwood+ and Veno converge faster in 5GHz Wi-Fi networks than 2.4GHz networks

An Interpretable Model With Forgetting Matrix For Deep Knowledge Tracing

Given that the current knowledge tracking model still has problems such as insufficient interpretability of the knowledge forgetting process and ignoring the relationship between different topics with the same knowledge concept. we propose an interpretable knowledge tracing model (KVFKT) based on key-value and forgetting. This approach keeps trace of the students' knowledge state matrices in each memory unit and also keeps trace of the forgetting matrices to monitor when the students' knowledge concepts were last reviewed. In addition, this model introduces the IRT two-parameter model from the perspective of educational psychology to further enhance the interpretability of the model. Finally, four real-world datasets are used to test the model, experimental results show that KVFKT can better trace students’ knowledge state and outperforms existing models in terms of ACC and AUC

Removal of Metal Catalyst in Multi-Walled Carbon Nanotubes with Combination of Air and Hydrogen Annealing Followed by Acid Treatment

Multi-walled carbon nanotubes (MWCNTs) prepared by the decomposition of CH4 on a Ni-MgO catalyst were treated with air and hydrogen annealing, and the combination of air and hydrogen annealing, respectively, followed by acid reflux. The treated MWCNTs were characterized by the techniques of transmission electron microscopy, thermogravimetric analysis and flame atomic absorption spectrometry. The results showed that hydrogen annealed MWCNTs were more air stable than air annealed ones. Followed by acid treatment, the combination of air and hydrogen annealing was more efficient than either air annealing or hydrogen annealing for the removal of catalyst in MWCNTs. For the treatment with 2 h of hydrogen annealing followed by 2 h of air annealing, the catalyst Ni remained in the purified sample was 10.8 mu g/g, and the yield rate was 82.3%. With 2 h of air annealing followed by 2 h of hydrogen annealing, the data were 5.8 mu g/g and 61.9%, respectively. The different functions of air and hydrogen during annealing were discussed.National Natural Science Foundation of China [20607017]; Natural Science Foundation of Fujian Province of China [D0610018