Issue 9: From the Guest Editors

Welcome to Issue 9 of the Online Journal of Space Communication as we discuss the Global Navigation Satellite System, its past, present and the direction its taking us

An Assessment Model For Information System’s Risk Based On Entropy Method And Grey Theory

In the process of risk assessment of information system, the risk assessment method and model are the key point. This paper analyzes the risk assessment methods of the information system, and points out the limitations of some methods. Considering the grey and dynamic characteristics of the evaluation index, the evaluation model based on Entropy Method and Grey Theory is presented, and the validity of the method is demonstrated by an example

System Dynamics Based Simulation Study On Storage and Distribution Integration of Electronic Commerce Enterprise

With the strong advocacy of national policies and the rapid development of electronic commerce, offline logistics operation has become the key to efficient and fast e-commerce. This paper will use the system dynamic method to build an integrated warehousing and distribution system of e-commerce, applying the computer simulation to analyze the change of each parameter after the target inventory and delay time have changed. Suggestions will be put forward at last: building of an info-sharing mechanism, reducing the delay time via active coordination, predicting the target inventory of distribution center on time. Through these to reduce the average cost and the possibility of short supply at distribution center, and thus guarantee the delivery quality and speed, optimize buyers’ shopping experience, form a virtuous circle and enhance the overall competence of the supply chain

Intelligent In-Vehicle Device Based on ARM-Linux Techniques

A new Intelligent Transportation System (ITS) is introduced and some ideas about instruction trigger position (ITP) are presented. The design of terminal devices based on an embedded ARM-Linux system in vehicles is presented in detail, including the design and development of both hardware and software

Neighborhood Overlapped Propagation Algorithm For Community Detection Based On Label Time-Sequence

The community detection algorithms based on label propagation (LPA) receive broad attention for the advantages of near-linear complexity and no prerequisite for any object function or cluster number. However, the propagation of labels contains uncertainty and randomness, which affects the accuracy and stability of the LPA algorithm. In this study, we propose an efficient detection method based on COPRA with Time-sequence (COPRA_TS). Firstly, the labels are sorted according to a new label importance measure. Then, the label of each vertex is updated according to time-sequence topology measure. The experiments on both the artificial datasets and the real-world datasets demonstrate that the quality of communities discovered by COPRA_TS algorithm is improved with a better stability. At last some future research topics are given

FoxO gene family evolution in vertebrates

<p>Abstract</p> <p>Background</p> <p>Forkhead box, class O (FoxO) belongs to the large family of forkhead transcription factors that are characterized by a conserved forkhead box DNA-binding domain. To date, the FoxO group has four mammalian members: FoxO1, FoxO3a, FoxO4 and FoxO6, which are orthologs of DAF16, an insulin-responsive transcription factor involved in regulating longevity of worms and flies. The degree of homology between these four members is high, especially in the forkhead domain, which contains the DNA-binding interface. Yet, mouse FoxO knockouts have revealed that each FoxO gene has its unique role in the physiological process. Whether the functional divergences are primarily due to adaptive selection pressure or relaxed selective constraint remains an open question. As such, this study aims to address the evolutionary mode of FoxO, which may lead to the functional divergence.</p> <p>Results</p> <p>Sequence similarity searches have performed in genome and scaffold data to identify homologues of FoxO in vertebrates. Phylogenetic analysis was used to characterize the family evolutionary history by identifying two duplications early in vertebrate evolution. To determine the mode of evolution in vertebrates, we performed a rigorous statistical analysis with FoxO gene sequences, including relative rate ratio tests, branch-specific <it>d</it>_<it>N</it>/<it>d</it>_{<it>S </it>}ratio tests, site-specific <it>d</it>_<it>N</it>/<it>d</it>_{<it>S </it>}ratio tests, branch-site <it>d</it>_<it>N</it>/<it>d</it>_{<it>S </it>}ratio tests and clade level amino acid conservation/variation patterns analysis. Our results suggest that FoxO is constrained by strong purifying selection except four sites in FoxO6, which have undergone positive Darwinian selection. The functional divergence in this family is best explained by either relaxed purifying selection or positive selection.</p> <p>Conclusion</p> <p>We present a phylogeny describing the evolutionary history of the FoxO gene family and show that the genes have evolved through duplications followed by purifying selection except for four sites in FoxO6 fixed by positive selection lie mostly within the non-conserved optimal PKB motif in the C-terminal part. Relaxed selection may play important roles in the process of functional differentiation evolved through gene duplications as well.</p

Grey theory based BP-NN co-training for dense sequence long-term tendency prediction

The file attached to this record is the author's final peer reviewed version.Purpose - The purpose of this paper is to solve the problems existing in topic popularity prediction in online social networks and advance a fine-grained and long-term prediction model for lack of sufficient data. Design/methodology/approach - Based on GM(1,1) and neural networks, a cotraining model for topic tendency prediction is proposed in this paper. The interpolation based on GM(1,1) is employed to generate fine-grained prediction values of topic popularity time series and two neural network models are considered to achieve convergence by transmitting training parameters via their loss functions. Findings - The experiment results indicate that the integrated model can effectively predict dense sequence with higher performance than other algorithms, such as NN and RBF_LSSVM. Furthermore, the Markov chain state transition probability matrix model is used to improve the prediction results. Practical implications - Fine-grained and long-term topic popularity prediction, further improvement could be made by predicting any interpolation in the time interval of popularity data points. Originality/value - The paper succeeds in constructing a co-training model with GM(1,1) and neural networks. Markov chain state transition probability matrix is deployed for further improvement of popularity tendency prediction

ReCGiP, a database of reproduction candidate genes in pigs based on bibliomics

<p>Abstract</p> <p>Background</p> <p>Reproduction in pigs is one of the most economically important traits. To improve the reproductive performances, numerous studies have focused on the identification of candidate genes. However, it is hard for one to read all literatures thoroughly to get information. So we have developed a database providing candidate genes for reproductive researches in pig by mining and processing existing biological literatures in human and pigs, named as ReCGiP.</p> <p>Description</p> <p>Based on text-mining and comparative genomics, ReCGiP presents diverse information of reproduction-relevant genes in human and pig. The genes were sorted by the degree of relevance with the reproduction topics and were visualized in a gene's co-occurrence network where two genes were connected if they were co-cited in a PubMed abstract. The 'hub' genes which had more 'neighbors' were thought to be have more important functions and could be identified by the user in their web browser. In addition, ReCGiP provided integrated GO annotation, OMIM and biological pathway information collected from the Internet. Both pig and human gene information can be found in the database, which is now available.</p> <p>Conclusions</p> <p>ReCGiP is a unique database providing information on reproduction related genes for pig. It can be used in the area of the molecular genetics, the genetic linkage map, and the breeding of the pig and other livestock. Moreover, it can be used as a reference for human reproduction research.</p