2,577 research outputs found
3-Phenyl-2-(piperidin-1-yl)-3,5,6,8-tetraÂhydro-4H-thioÂpyrano[3′,4′:2,3]thieno[5,4-d]pyrimidin-4-one
In the title compound, C20H21N3OS2, the piperidinyl ring has a distorted chair conformation. Weak interÂmolecular C—H⋯O hydrogen bonds link the molÂecules into centrosymmetric dimers. The crystal packing exhibits short interÂmolecular S⋯S distances of 3.590 (2) Å
Optimization-Based Artificial Bee Colony Algorithm for Data Collection in Large-Scale Mobile Wireless Sensor Networks
Data collection is a fundamental operation in various mobile wireless sensor networks (MWSN) applications. The energy of nodes around the Sink can be untimely depleted owing to the fact that sensor nodes must transmit vast amounts of data, readily forming a bottleneck in energy consumption; mobile wireless sensor networks have been designed to address this issue. In this study, we focused on a large-scale and intensive MWSN which allows a certain amount of data latency by investigating mobile Sink balance from three aspects: data collection maximization, mobile path length minimization, and network reliability optimization. We also derived a corresponding formula to represent the MWSN and proved that it represents an NP-hard problem. Traditional data collection methods only focus on increasing the amount data collection or reducing the overall network energy consumption, which is why we designed the proposed heuristic algorithm to jointly consider cluster head selection, the routing path from ordinary nodes to the cluster head node, and mobile Sink path planning optimization. The proposed data collection algorithm for mobile Sinks is, in effect, based on artificial bee colony. Simulation results show that, in comparison with other algorithms, the proposed algorithm can effectively reduce data transmission, save energy, improve network data collection efficiency and reliability, and extend the network lifetime
catena-Poly[[(1,12,15,26-tetraÂaza-5,8,19,22-tetraÂoxa-3,4:9,10:17,18:23,24-tetraÂbenzocycloÂoctaÂcosane-κ4 N 1,N 12,N 15,N 26)nickel(II)]-μ-terephthalato-κ2 O 1:O 4]
In the title compound, [Ni(C8H4O4)(C36H44N4O4)]n, the NiII atom is coordinated in a distorted octaÂhedral geometry by the four N atoms of the 1,12,15,26-tetraÂaza-5,8,19,22-tetra-oxa-3,4:9,10:17,18:23,24-tetraÂbenzocycloÂoctaÂcosane ligand and two O atoms from the terephthalate dianions. The NiII atoms, which lie on inversion centres, are linked via terephthalate ligands to form a chain structure along [101]. The structure is stabilized by three intraÂmolecular and one interÂmolecular N—H⋯O hydrogen bonds
Ethyl 2-amino-6-benzyl-4,5,6,7-tetraÂhydroÂthieno[2,3-c]pyridine-3-carboxylÂate
In the title compound, C17H20N2O2S, the tetraÂhydroÂpyridine ring adopts an envelope conformation with the N atom at the flap position; the phenyl ring makes a dihedral angle of 81.06 (10)° with the thioÂphene ring. The amino group links with the carbonyl O atom via intraÂmolecular N—H⋯O hydrogen bonding, forming a six-membered ring. In the crystal, interÂmolecular N—H⋯O hydrogen bonds link the molÂecules into infinite chains running along the b axis
Sparse Representation for Wireless Communications:A Compressive Sensing Approach
Sparse representation can efficiently model signals in different applications to facilitate processing. In this article, we will discuss various applications of sparse representation in wireless communications, with a focus on the most recent compressive sensing (CS)-enabled approaches. With the help of the sparsity property, CS is able to enhance the spectrum efficiency (SE) and energy efficiency (EE) of fifth-generation (5G) and Internet of Things (IoT) networks
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