Background: Most dynamical models for genomic networks are built upon two current methodologies, one process-based and the other based on Boolean-type networks. Both are problematic when it comes to experimental desig...
详细信息
Background: Most dynamical models for genomic networks are built upon two current methodologies, one process-based and the other based on Boolean-type networks. Both are problematic when it comes to experimental design purposes in the laboratory. The first approach requires a comprehensive knowledge of the parameters involved in all biological processes a priori, whereas the results from the second method may not have a biological correspondence and thus cannot be tested in the laboratory. Moreover, the current methods cannot readily utilize existing curated knowledge databases and do not consider uncertainty in the knowledge. Therefore, a new methodology is needed that can generate a dynamical model based on available biological data, assuming uncertainty, while the results from experimental design can be examined in the laboratory. Results: We propose a new methodology for dynamical modeling of genomic networks that can utilize the interaction knowledge provided in public databases. The model assigns discrete states for physical entities, sets priorities among interactions based on information provided in the database, and updates each interaction based on associated node states. Whenever uncertainty in dynamics arises, it explores all possible outcomes. By using the proposed model, biologists can study regulation networks that are too complex for manual analysis. Conclusions: The proposed approach can be effectively used for constructing dynamical models of interaction-based genomic networks without requiring a complete knowledge of all parameters affecting the network dynamics, and thus based on a small set of available data.
Aiming at data from different data sources were data preprocessing and the establishment of a common mathematical model to analyze how to improve in the face of massive high-dimensional data mining efficiency and qual...
详细信息
Aiming at data from different data sources were data preprocessing and the establishment of a common mathematical model to analyze how to improve in the face of massive high-dimensional data mining efficiency and quality of the methods of association rules, and the rules for existing association metrics prone to a lot of redundant and loop rule this situation put forward the corresponding solutions, while the paper applied the high-dimensional data clustering algorithm based on hypergraph. Research article on high-dimensional data mining methods of data analysis for large data era has a certain significance to explore the methods and tools of mathematical analysis of big data era.
A multistage graph is center problem of computer science,many coordination and consistency problems can be convert into multistage graph *** obtained the fitness function by coding the vertex of multistage graph,and d...
详细信息
ISBN:
(纸本)9781467397155
A multistage graph is center problem of computer science,many coordination and consistency problems can be convert into multistage graph *** obtained the fitness function by coding the vertex of multistage graph,and designed the genetic algorithm for solving multistage graph *** results show that this algorithm is very effective and feasible.
To solve unpunctual delivery, low assembly line utilization and unbalanced production in the assembly shop scheduling of an automotive electronic components enterprise, the model of multi-model multiple assembly line ...
详细信息
To solve unpunctual delivery, low assembly line utilization and unbalanced production in the assembly shop scheduling of an automotive electronic components enterprise, the model of multi-model multiple assembly line mixed-lines assembling by turns was constructed and the model was solved by designing a series of optimal algorithms. In view of meeting the punctual delivery period, improving the utilization of assembly lines and the order fulfillment rate, the scheduling model was constructed different from the majority of similar models. The virtual sequence, a new neighborhood structure to avoid the adjustment in cycling improvement, was defined and combined with the scheduling rules and heuristics strategy to design three algorithms for solving the model. The performance of presented algorithms were analyzed and compared with the original scheduling results. The performance comparison results demonstrate the virtual tabu (Vtr-Tabu) algorithm can apply in the small and medium scale scheduling problem with better performance than other two. And the performance variation curves of three algorithms with the increasing of single parameter were analyzed. The computational results verify the effectiveness of the presented model and algorithms in improving delivery, the assembly line utilization and the order fulfillment rate.
Remote sensing algorithms often invert multiple measurements simultaneously to retrieve a group of geophysical parameters. In order to create a robust retrieval algorithm, it is necessary to ensure that there are more...
详细信息
Remote sensing algorithms often invert multiple measurements simultaneously to retrieve a group of geophysical parameters. In order to create a robust retrieval algorithm, it is necessary to ensure that there are more unique measurements than parameters to be retrieved. If this is not the case, the inversion might have multiple solutions and be sensitive to noise. In this letter, we introduce a methodology to calculate the number of (possibly fractional) "degrees of information" in a set of measurements, representing the number of parameters that can be retrieved robustly from that set. Since different measurements may not be mutually independent, the amount of duplicate information is calculated using the information-theoretic concept of total correlation (a generalization of mutual information). The total correlation is sensitive to the full distribution of each measurement and therefore accounts for duplicate information even if multiple measurements are related only partially and nonlinearly. The method is illustrated using several examples, and applications to a variety of sensor types are discussed.
Small spacecraft platforms are a promising low-cost approach to accelerate exploration of small bodies, addressing the space community's interest in origin science, planetary resources, and planetary defense. Howe...
详细信息
Small spacecraft platforms are a promising low-cost approach to accelerate exploration of small bodies, addressing the space community's interest in origin science, planetary resources, and planetary defense. However, they can be challenging platforms for detecting and imaging low brightness targets. Difficulties include constrained bandwidth, which limits the volume of data that can be downlinked;attitude instability, which limits exposure time;small instrument apertures, which reduce sensitivity;and cosmic ray contamination, which creates illusory sources. Mission designers can address all these problems simultaneously by shifting image analysis across the communications gap. Spacecraft can use onboard data analysis to detect sources directly, or downlink parsimonious summary products for detection on the ground. One promising approach is to acquire stacks of short consecutive exposures, and then coregister and coadd them onboard. This work analyzes a coaddition algorithm that is designed to be robust against small spacecraft challenges. We evaluate factors affecting performance, such as attitude control and camera noise systematics, in regimes typical of small spacecraft missions. We motivate the algorithm design by considering its application to NEAScout, a mission representing a new generation of small (sub-50kg) exploration spacecraft having very small instrument apertures and data rates below 1kbytes(-1). Here, onboard analysis allows detection and rendezvous with far smaller and fainter objects, dramatically reducing the cost and complexity of primitive bodies exploration.
There is a strong movement asserting the importance of quality education all over the world and for students of all ages. Many educators believe that in order to achieve this 21st century skills must be taught and tha...
详细信息
ISBN:
(纸本)9781479919086
There is a strong movement asserting the importance of quality education all over the world and for students of all ages. Many educators believe that in order to achieve this 21st century skills must be taught and that digital literacy should be coupled with rigorous Computer Science principles and computational thinking. Accordingly this work will describe a didactic experience in an introductory programming course by describing the context, pedagogical approach, content of the course based on a procedure-first approach, technologies used, research questions addressed, experimental design adopted, data collection and analysis and the main conclusion supported by qualitative and quantitative data. The research questions focus on understanding which is the best medium to designalgorithms by comparing flow chart and the Scratch programming language and by evaluating whether using textual language is worth the effort of the syntactic burden imposed by these languages. An analysis of quantitative and qualitative data revealed that both a visual programming and a flow-chart approach are suitable for algorithm design with no statistical difference in terms of number of errors and time taken to write the corresponding code in a textual language. However, the high number of errors suggest that using visual programming allows the student to focus on the problem solving activities.
In this paper, we propose two algorithms to realize a specific case of indeterminate finite summation operation introduced by multinomial theorem in computer-based simulations. One is the time-first algorithm, the rea...
详细信息
ISBN:
(纸本)9781467386005
In this paper, we propose two algorithms to realize a specific case of indeterminate finite summation operation introduced by multinomial theorem in computer-based simulations. One is the time-first algorithm, the realization of which can be temporally advantageous. The other is the space-first algorithm, of which the realization can be spatially advantageous. Our proposed algorithms are examined by simulations, and their efficiency and effectiveness are illustrated. Moreover, we also point out that, by appropriate modifications, these two algorithms can be generalized for more applications. The contributions in this paper can be used to solve a number of numerical computations of the indeterminate finite summations of series in computer-based simulations.
There has been significant recent interest in the area of group recommendations, where, given groups of users of a recommender system, one wants to recommend top-k items to a group that maximize the satisfaction of th...
详细信息
ISBN:
(纸本)9781450327589
There has been significant recent interest in the area of group recommendations, where, given groups of users of a recommender system, one wants to recommend top-k items to a group that maximize the satisfaction of the group members, according to a chosen semantics of group satisfaction. Examples semantics of satisfaction of a recommended item-set to a group include the so-called least misery (LM) and aggregate voting (AV). We consider the complementary problem of how to form groups such that the users in the formed groups are most satisfied with the suggested top-k recommendations. We assume that the recommendations will be generated according to one of the two group recommendation semantics - LM or AV. Rather than assuming groups are given, or rely on ad hoc group formation dynamics, our framework allows a strategic approach for forming groups of users in order to maximize satisfaction. We show that the problem is NP-hard to solve optimally under both semantics. Furthermore, we develop two efficient algorithms for group formation under LM and show that they achieve bounded absolute error. We develop efficient heuristic algorithms for group formation under AV. We validate our results and demonstrate the scalability and effectiveness of our group formation algorithms on two large real data sets.
Over the years, various path planning problems have been brought up and addressed. For example, shortest path first algorithm is usually adopted to search for the best route between a source and a destination for pack...
详细信息
ISBN:
(纸本)9781467382700
Over the years, various path planning problems have been brought up and addressed. For example, shortest path first algorithm is usually adopted to search for the best route between a source and a destination for packet transmission over a network. In that case, we add up the distance of every segment along each of the available routes and choose the one with the least value. Path planning problems of this sort often use evaluation functions that are commutative in nature. However, in case our objective is to plan a biking or driving route that is safe and / or fun, ordinary evaluation functions, especially commutative ones, usually fail to resolve the issue properly. Accordingly, in this paper, we propose an un-conventional non-commutative path planning strategy as well as algorithm to address the problem in a more efficient manner.
暂无评论