Harbin Institute of Technology

About: Harbin Institute of Technology is a education organization based out in Harbin, China. It is known for research contribution in the topics: Microstructure & Control theory. The organization has 88259 authors who have published 109297 publications receiving 1603393 citations. The organization is also known as: HIT.

Distributed Data Aggregation Scheduling in Wireless Sensor Networks

Abstract: Data aggregation is an essential operation in wireless sensor network applications. This paper focuses on the data aggregation scheduling problem. Based on maximal independent sets, a distributed algorithm to generate a collision-free schedule for data aggregation in wireless sensor networks is proposed. The time latency of the aggregation schedule generated by the proposed algorithm is minimized using a greedy strategy. The latency bound of the schedule is 24D + 6 Delta + 16, where D is the network diameter and Delta is the maximum node degree. The previous data aggregation algorithm with least latency has the latency bound (Delta- Delta 1)R, where R is the network radius. Thus in our algorithm Delta contributes to an additive factor instead of a multiplicative factor, which is a significant improvement. To the best of our knowledge, the proposed algorithm is the first distributed algorithm for data aggregation scheduling. This paper also proposes an adaptive strategy for updating the schedule when nodes fail or new nodes join in a network. The analysis and simulation results show that the proposed algorithm outperforms other aggregation scheduling algorithms.

Mussel-Inspired Surface Engineering for Water-Remediation Materials

Abstract: Mussel-inspired chemistry, as a powerful tool to manipulate material properties, has been widely studied and implemented in surface engineering of a variety of materials for multipurpose functionalization. With the rapid development of this field, more flexible and efficient modification strategies for surface engineering and application modes have been developed recently. It is therefore critical to update the broader scientific community on the important advances in this interdisciplinary field. Here, we summarize recent progress in mussel-inspired chemistry and its emerging applications in water remediation. The reaction and adhesion mechanisms of polydopamine, as well as its chemical and physical properties, are discussed. The functionalization strategies are categorized into post-functionalization, co-deposition, and pre-modification, and the roles of mussel-inspired surface coatings are highlighted in filtration, adsorbing, and catalytic materials as well as the burgeoning area of photothermal distillation materials.

SOD-MTGAN: Small Object Detection via Multi-Task Generative Adversarial Network

Abstract: Object detection is a fundamental and important problem in computer vision. Although impressive results have been achieved on large/medium sized objects in large-scale detection benchmarks (e.g. the COCO dataset), the performance on small objects is far from satisfactory. The reason is that small objects lack sufficient detailed appearance information, which can distinguish them from the background or similar objects. To deal with the small object detection problem, we propose an end-to-end multi-task generative adversarial network (MTGAN). In the MTGAN, the generator is a super-resolution network, which can up-sample small blurred images into fine-scale ones and recover detailed information for more accurate detection. The discriminator is a multi-task network, which describes each super-resolved image patch with a real/fake score, object category scores, and bounding box regression offsets. Furthermore, to make the generator recover more details for easier detection, the classification and regression losses in the discriminator are back-propagated into the generator during training. Extensive experiments on the challenging COCO dataset demonstrate the effectiveness of the proposed method in restoring a clear super-resolved image from a blurred small one, and show that the detection performance, especially for small sized objects, improves over state-of-the-art methods.

LncRNA2Target v2.0: a comprehensive database for target genes of lncRNAs in human and mouse

Abstract: Long non-coding RNAs (lncRNAs) play crucial roles in regulating gene expression, and a growing number of researchers have focused on the identification of target genes of lncRNAs. However, no online repository is available to collect the information on target genes regulated by lncRNAs. To make it convenient for researchers to know what genes are regulated by a lncRNA of interest, we developed a database named lncRNA2Target to provide a comprehensive resource of lncRNA target genes in 2015. To update the database this year, we retrieved all new lncRNA-target relationships from papers published from 1 August 2014 to 30 April 2018 and RNA-seq datasets before and after knockdown or overexpression of a specific lncRNA. LncRNA2Target database v2.0 provides a web interface through which its users can search for the targets of a particular lncRNA or for the lncRNAs that target a particular gene, and is freely accessible at http://123.59.132.21/lncrna2target.

Detection of Melamine in Milk Products by Surface Desorption Atmospheric Pressure Chemical Ionization Mass Spectrometry

Abstract: Without any sample pretreatment, trace amounts of melamine in various milk products were rapidly detected noting the characteristic fragments (i.e., m/z 110, 85, and 60) in the MS/MS spectrum of protonated melamine molecules (m/z 127) recorded by using surface desorption atmospheric pressure chemical ionization mass spectrometry. Signal responses of the most abundant ionic fragment (m/z 85) of protonated melamine were well correlated with the amounts of melaime in milk products, showing a dynamic range about 5 orders of magnitude. The limit of detection (LOD) was found to be 3.4 × 10−15 g/mm2 (S/N = 3) for the detection of pure melamine deposited on the paper surface, which was much lower than that for detection of melamine in powdered milk (1.6 × 10−11 g/mm2, S/N = 3) or liquid milk (1.3 × 10−12 g/mm2, S/N = 3). The significant difference in LOD was ascribed to the relatively strong molecular interactions between melamine and the matrix such as proteins in the milk products. As demonstrated using desorpt...