Using Graph Theory to Create a 3D Miniscaped, Non-Linear Level

This study focuses on how to use the Graph Theory and the Dominion Theory to design a three-dimensional (3D) non-linear, miniscaped level layout in a video game. Using these theories, the researcher aimed to aid players in navigating non-linear levels (which are notoriously difficult to traverse). Consequently, the researcher created a methodology outlining the best practices for constructing a level using Graph Theory and Dominion Theory. The researcher constructed a game level in The Elder Scrolls V: Skyrim to explore the effectiveness of this methodology. Testers played the level and provided feedback regarding their experiences. The researcher analyzed this data to confirm or deny their methodology’s accuracy

Sensor Node Easy Moving Monitoring Region Location Algorithm in Internet of Things

Because of the influence from geographical location, weather and other kinds of circumstances in monitored areas, the shift of the node location and non-uniform distribution, this paper proposed an improved DV-Hop location algorithm. First of all, the package structure by changing the anchor nodes to reduce the number of hops data acquisition phase node data storage; introducing weights to the average hop distance calculation phase the original average hop distance calculation method was improved, and between the node and anchor node distance calculated on the basis of reference anchor nodes are different; then, iterative refinement of node localization stage through the use of multilateral measurement method and Taylor series. Finally, simulation experiment of this method, and compared with the existing methods, the results prove that the method in this paper can greatly reduce positioning errors without adding hardware equipment and network traffic, improve the positioning accuracy, a better solution to the problem of node localization networking monitoring area

Testing Higher-order Clusterability on graphs

Analysis of higher-order organizations, usually small connected subgraphs called motifs, is a fundamental task on complex networks. This paper studies a new problem of testing higher-order clusterability: given query access to an undirected graph, can we judge whether this graph can be partitioned into a few clusters of highly-connected motifs? This problem is an extension of the former work proposed by Czumaj et al. (STOC' 15), who recognized cluster structure on graphs using the framework of property testing. In this paper, a good graph cluster on high dimensions is first defined for higher-order clustering. Then, query lower bound is given for testing whether this kind of good cluster exists. Finally, an optimal sublinear-time algorithm is developed for testing clusterability based on triangles

TPGNN: Learning High-order Information in Dynamic Graphs via Temporal Propagation

Temporal graph is an abstraction for modeling dynamic systems that consist of evolving interaction elements. In this paper, we aim to solve an important yet neglected problem -- how to learn information from high-order neighbors in temporal graphs? -- to enhance the informativeness and discriminativeness for the learned node representations. We argue that when learning high-order information from temporal graphs, we encounter two challenges, i.e., computational inefficiency and over-smoothing, that cannot be solved by conventional techniques applied on static graphs. To remedy these deficiencies, we propose a temporal propagation-based graph neural network, namely TPGNN. To be specific, the model consists of two distinct components, i.e., propagator and node-wise encoder. The propagator is leveraged to propagate messages from the anchor node to its temporal neighbors within $k$-hop, and then simultaneously update the state of neighborhoods, which enables efficient computation, especially for a deep model. In addition, to prevent over-smoothing, the model compels the messages from $n$-hop neighbors to update the $n$-hop memory vector preserved on the anchor. The node-wise encoder adopts transformer architecture to learn node representations by explicitly learning the importance of memory vectors preserved on the node itself, that is, implicitly modeling the importance of messages from neighbors at different layers, thus mitigating the over-smoothing. Since the encoding process will not query temporal neighbors, we can dramatically save time consumption in inference. Extensive experiments on temporal link prediction and node classification demonstrate the superiority of TPGNN over state-of-the-art baselines in efficiency and robustness.Comment: Under revie

A Traffic State Detection Tool for Freeway Video Surveillance System

AbstractTraffic state is one of the most important traffic flow parameters to both the traffic management center and the traveler. It's difficult to extract traffic data using surveillance cameras because of the wider field, panning and zooming of the surveillance cameras. To leverage the existing surveillance camera infrastructure, a surveillance video based traffic state detection system is proposed. The proposed system can estimate traffic flow speed and road space occupancy, and recognize three typical traffic states (congested, slow, and smooth). Experimental results show that the system had good adaptation and high accuracy in daytime

Restoration of horizontal stability in complete acromioclavicular joint separations: surgical technique and preliminary results

BACKGROUND: Our purpose was to investigate the clinical efficacy of arthroscope-assisted acromioclavicular ligament reconstruction in combination with double endobutton coracoclavicular ligament reconstruction for the treatment of complete acromioclavicular joint dislocation. METHODS: During the period from February 2010 to October 2012, ten patients with Rockwood types IV and V acromioclavicular joint dislocation were hospitalized and nine were treated with acromioclavicular ligament reconstruction combined with double endobutton of coracoclavicular ligament reconstruction. The improvement in shoulder functions was assessed using a Constant score and visual analog scale (VAS) system. RESULTS: The mean follow-up period was 33.6 ± 5.4 months. The mean Constant scores improved from 25.2 ± 6.6 preoperatively to 92.4 ± 6.5 postoperatively, while the mean VAS score decreased from 5.9 ± 1.4 to 1.2 ± 0.9; significant differences were observed. The final follow-up revealed that excellent outcomes were achieved in eight patients and good outcome in two patients. CONCLUSION: Arthroscope-assisted acromioclavicular ligament reconstruction in combination with double endobutton of coracoclavicular ligament reconstruction is an effective approach for treatment of acute complete acromioclavicular joint dislocation

A New Method for Conflict Resoluton Based on Multi-Agent Reinforcement Learning Algorithms

Conflict resolution is a research topic for game theory (GT) and conflict analysis. A decision support system (DSS) is very helpful for conflict decision making. Reinforcement learning (RL) is an efficient method to learn knowledge by agents themselves. Although successful applications of RL have been reported in single-agent domain, a lot of work should be done in the case of multi-agent domain. Nash Q-learning is a famous learning algorithm for multi-agent RL. Based on the Nash Q-learning, a novel DSS: multi-agent RL based DSS (MRLDSS) is proposed in this paper and is tested by using several typical examples of conflict resolution. Experimental results show that the proposed architecture and algorithm can solve conflict resolution problems correctly and efficiently

Effectiveness and safety of Compound Danshen injection as treatment for pregnancy-induced hypertension: A metaanalysis

Purpose: To systematically evaluate the effectiveness and safety of Compound Danshen injection in patients with pregnancy-induced hypertension (PIH).Methods: PubMed, Embase, Cochrane Library, Chinese biomedical literature database (CBM), VIP (xiAn), China National Knowledge Infrastructure (CNKI) and Wan Fang databases were searched up to March 20, 2018, for all randomized controlled trials (RCTs) on the use of Compound Danshen injection in patients with PIH. Data were extracted from included studies after assessing the quality of literature. Revman 5.3 software was used for statistical analysis．Results: A total of 18 RCTs involving 1735 patients were included. The results of meta-analysis indicated that the study group was superior to the control group in clinical effectiveness (RR = 1.15, 95 % CI: 1.02 - 1.30); intrauterine fetal distress (RR = 0.26, 95 % CI: 0.09 - 0.70); cesarean section (RR = 0.72, 95 % CI: 0.58 - 0.90), and neonatal asphyxia (RR = 0.23, 95 % CI: 0.11 - 0.48). There were no statistical differences in fetal heart rate abnormalities (RR = 0.58, 95 %, CI: 0.33 - 1.02, p > 0.05) and postpartum hemorrhage (RR = 0.86, 95 % CI: 0.53 - 1.42) between the two groups.Conclusion: Treatment of PIH with Compound Danshen injection (alone or in combination) is superior to the use of conventional western medical treatment in safety and effectiveness. However, higher quality clinical studies are needed to confirm these results because most trials included in this study were of low quality.Keywords: Pregnancy-induced hypertension (PIH), Compound Danshen injection, Meta-analysi

Effects of Furnished Cage Type on Behavior and Welfare of Laying Hens

This study was conducted to compare the effects of layout of furniture (a perch, nest, and sandbox) in cages on behavior and welfare of hens. Two hundred and sixteen Hyline Brown laying hens were divided into five groups (treatments) with four replicates per group: small furnished cages (SFC), medium furnished cages type I (MFC-I), medium furnished cages type II (MFC-II), and medium furnished cages type III (MFC-III) and conventional cages (CC). The experiment started at 18 week of age and finished at 52 week of age. Hens’ behaviors were filmed during the following periods: 8:00 to 10:00; 13:00 to 14:00; 16:00 to 17:00 on three separate days and two hens from each cage were measured for welfare parameters at 50 wk of age. The results showed that feeding and laying of all hens showed no effect by cage type (p>0.05), and the hens in the furnished cages had significantly lower standing and higher walking than CC hens (p0.05). The hens in MFC-I, −II, and −III showed a significant higher socializing behavior than SFC and CC (p<0.05). The lowest perching was for the hens in SFC and the highest perching found for the hens in MFC-III. Overall, the hens in CC showed poorer welfare conditions than the furnished cages, in which the feather condition score, gait score and tonic immobility duration of the hens in CC was significantly higher than SFC, MFC-I, MFC-II, and MFC-III (p<0.05). In conclusion, the furnished cage design affected both behavior and welfare states of hens. Overall, MFC-III cage design was better than SFC, MFC-I, and MFC-II cage designs