Propagating functional dependencies with conditions

The dependency propagation problem is to determine, given a view defined on data sources and a set of dependencies on the sources, whether another dependency is guaranteed to hold on the view. This paper investigates dependency propagation for recently proposed conditional functional dependencies (CFDs). The need for this study is evident in data integration, exchange and cleaning since dependencies on data sources often only hold conditionally on the view. We investigate dependency propagation for views defined in various fragments of relational algebra, CFDs as view dependencies, and for source dependencies given as either CFDs or traditional functional dependencies (FDs). (a) We establish lower and upper bounds, all matching , ranging from PTIME to undecidable. These not only provide the first results for CFD propagation, but also extend the classical work of FD propagation by giving new complexity bounds in the presence of finite domains. (b) We provide the first algorithm for computing a minimal cover of all CFDs propagated via SPC views; the algorithm has the same complexity as one of the most efficient algorithms for computing a cover of FDs propagated via a projection view, despite the increased expressive power of CFDs and SPC views. (c) We experimentally verify that the algorithm is efficient. </jats:p

Study on vibration characteristics of rolling mill based on vibration absorber

The vertical vibration often occurs during the rolling production, which has an influence on the accuracy of rolling mill. In order to effectively suppress the vertical vibration of the rolling equipment, the rolling mill model with vibration absorber device was established. Based on the main resonance singularity of the rolling mill system, the best combination of opening parameters was obtained. The best combination of opening parameters helps the rolling mill system work in a stable area. Finally, the effects of different vibration absorber parameters on the vibration characteristics of the rolling mill system were analyzed. Results show that the vibration absorber device can effectively improve the stability of the rolling mill system

Constrained Clustering Based on the Link Structure of a Directed Graph

In many segmentation applications, data objects are often clustered based purely on attribute-level similarities. This practice has neglected the useful information that resides in the link structure among data objects and the valuable expert domain knowledge about the desirable cluster assignment. Link structure can carry worthy information about the similarity between data objects (e.g. citation), and we should also incorporate the existing domain information on preferred outcome when segmenting data. In this paper, we investigate the segmentation problem combining these three sources of information, which has not been addressed in the existing literature. We propose a segmentation method for directed graphs that incorporates the attribute values, link structure and expert domain information (represented as constraints). The proposed method combines these three types of information to achieve good quality segmentation on data which can be represented as a directed graph. We conducted comprehensive experiments to evaluate various aspects of our approach and demonstrate the effectiveness of our method

Water Pipeline Leakage Detection Based on Machine Learning and Wireless Sensor Networks

The detection of water pipeline leakage is important to ensure that water supply networks can operate safely and conserve water resources. To address the lack of intelligent and the low efficiency of conventional leakage detection methods, this paper designs a leakage detection method based on machine learning and wireless sensor networks (WSNs). The system employs wireless sensors installed on pipelines to collect data and utilizes the 4G network to perform remote data transmission. A leakage triggered networking method is proposed to reduce the wireless sensor network’s energy consumption and prolong the system life cycle effectively. To enhance the precision and intelligence of leakage detection, we propose a leakage identification method that employs the intrinsic mode function, approximate entropy, and principal component analysis to construct a signal feature set and that uses a support vector machine (SVM) as a classifier to perform leakage detection. Simulation analysis and experimental results indicate that the proposed leakage identification method can effectively identify the water pipeline leakage and has lower energy consumption than the networking methods used in conventional wireless sensor networks

FlexEdge: Digital Twin-Enabled Task Offloading for UAV-Aided Vehicular Edge Computing

Integrating unmanned aerial vehicles (UAVs) into vehicular networks have shown high potentials in affording intensive computing tasks. In this paper, we study the digital twin driven vehicular edge computing networks for adaptively computing resource management where an unmanned aerial vehicle (UAV) named FlexEdge acts as a flying server. In particular, we first formulate an energy consumption minimization problem by jointly optimizing UAV trajectory and computation resource under the practical constraints. To address such a challenging problem, we then build the computation offloading process as a Markov decision process and propose a deep reinforcement learning-based proximal policy optimization algorithm to dynamically learn the computation offloading strategy and trajectory design policy. Numerical results indicate that our proposed algorithm can achieve quick convergence rate and significantly reduce the system energy consumption.Comment: 6 pages, 6 figure

Modelling and stimulation of target tracking and localization in wireless sensor network

Lociranje i praćenje pomične mete je jedno od glavnih ciljeva u istraživanju aplikacija mreže bežičnog senzora. Od velike je važnosti na vojnom planu. Istraživači su predložili mnoge algoritme za precizno lokaliziranje mete. Trociklična metoda uzajamnih presijecanja zasnovana na indikatoru jačine primljenog signala može preskočiti procjenu potrošnje oslabljene prijenosne snage za točno lociranje mete. Kako bi se izbjegla velika greška koja se događa kada meta promijeni pravac kretanja, ovaj rad predlaže algoritam kojim se predviđa točka u kojoj će ona promijeniti putanju. Tom se metodom može poboljšati aproksimacija između izabrane i stvarne putanje te povećati točnost lokaliziranja i praćenja cijelog sustava.Localization and tracking of moving target is one of the research focuses of wireless sensor network applications. It has great value in military field. Researchers have proposed many algorithms to complete target localization precisely. Tri-cyclic mutual crosses method based on received signal strength indicator can skip the estimation of transmitting attenuation consumption to locate the target accurately. For the great error happening when the target turns its direction, this paper proposes an algorithm to predict the turning point of its motion path. This method can improve the approximation between depicted and real trajectory, and promote the localization and tracking accuracy of whole system

Association of the low-density lipoprotein cholesterol/high-density lipoprotein cholesterol ratio and concentrations of plasma lipids with high-density lipoprotein subclass distribution in the Chinese population

<p>Abstract</p> <p>Background</p> <p>To evaluate the relationship between the low-density lipoprotein cholesterol (LDL-C)/high-density lipoprotein cholesterol (HDL-C) ratio and HDL subclass distribution and to further examine and discuss the potential impact of LDL-C and HDL-C together with TG on HDL subclass metabolism.</p> <p>Results</p> <p>Small-sized preβ₁-HDL, HDL_3band HDL_3aincreased significantly while large-sized HDL_2aand HDL_2bdecreased significantly as the LDL-C/HDL-C ratio increased. The subjects in low HDL-C level (< 1.03 mmol/L) who had an elevation of the LDL-C/HDL-C ratio and a reduction of HDL_2b/preβ₁-HDL regardless of an undesirable or high LDL-C level. At desirable LDL-C levels (< 3.34 mmol/L), the HDL_2b/preβ₁-HDL ratio was 5.4 for the subjects with a high HDL-C concentration (≥ 1.55 mmol/L); however, at high LDL-C levels (≥ 3.36 mmol/L), the ratio of LDL-C/HDL-C was 2.8 in subjects, and an extremely low HDL_2b/preβ₁-HDL value although with high HDL-C concentration.</p> <p>Conclusion</p> <p>With increase of the LDL-C/HDL-C ratio, there was a general shift toward smaller-sized HDL particles, which implied that the maturation process of HDL was blocked. High HDL-C concentrations can regulate the HDL subclass distribution at desirable and borderline LDL-C levels but cannot counteract the influence of high LDL-C levels on HDL subclass distribution.</p