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Search Results: 1 - 10 of 41773 matches for " Bo Cheng "
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Single machine slack due-window assignment and scheduling of linear time-dependent deteriorating jobs and a deteriorating maintenance activity
Bo Cheng,Ling Cheng
Computer Science , 2014,
Abstract: In this paper, we consider the slack due-window assignment model and study a single machine scheduling problem of linear time-dependent deteriorating jobs and a deteriorating maintenance activity. The cost for each job consists of four components: earliness, tardiness, window location and window size. The objective is to schedule the jobs and to assign the maintenance activity and due-windows such that the total cost among all the jobs is minimized. A polynomial-time algorithm with the running time not exceeding $O(n^2logn)$ to give a solution to this problem is introduced, where $n$ is the number of jobs.
Single Machine Slack Due-Window Assignment and Scheduling of Linear Time-Dependent Deteriorating Jobs and a Deteriorating Maintenance Activity  [PDF]
Bo Cheng, Ling Cheng
Open Access Library Journal (OALib Journal) , 2018, DOI: 10.4236/oalib.1104907
Abstract: In this paper, we consider the slack due-window assignment model and study a single machine scheduling problem of linear time-dependent deteriorating jobs and a deteriorating maintenance activity. The objective is to find the job schedule having an assigned maintenance activity and due-windows with the minimum total cost consisting of costs of earliness, tardiness, window location and window size. A polynomial-time algorithm is presented in this paper with time complexity for n jobs.
Pinning Forces in Superconductors from Periodic Ferromagnetic Dot Array  [PDF]
Wei Jiang Yeh, Bo Cheng, Tony Ragsdale
Journal of Modern Physics (JMP) , 2010, DOI: 10.4236/jmp.2010.16052
Abstract: Using the London equation, we derive a formula by which the pinning force from magnetic dots can be cal-culated. We numerically calculate the interaction between ferromagnetic dots and vortices in type II super-conductors under various conditions. It is found that the pinning force of the magnetic dot with 50 nm thick-ness reaches 3.5 × 10-11 N that is one order magnitude stronger than the intrinsic pinning force in cuprate at 77 K. We investigate various parameter dependences of the pinning force. It is found that the most effective way to increase the pinning force is to increase the thickness of the dot. The pinning force is weakly de-pendent on both the size and magnetic permeability of the dots. When temperature increases, the pinning force linearly decreases. And when the magnetic field increases, the attraction force increases linearly in the low field region.
Optimal Scheduling of PEV Charging/Discharging in Microgrids with Combined Objectives  [PDF]
Chong Cao, Ming Cheng, Bo Chen
Smart Grid and Renewable Energy (SGRE) , 2016, DOI: 10.4236/sgre.2016.74008
Abstract: While renewable power generation and vehicle electrification are promising solutions to reduce greenhouse gas emissions, it faces great challenges to effectively integrate them in a power grid. The weather-dependent power generation of renewable energy sources, such as Photovoltaic (PV) arrays, could introduce significant intermittency to a power grid. Meanwhile, uncontrolled PEV charging may cause load surge in a power grid. This paper studies the optimization of PEV charging/discharging scheduling to reduce customer cost and improve grid performance. Optimization algorithms are developed for three cases: 1) minimize cost, 2) minimize power deviation from a pre-defined power profile, and 3) combine objective functions in 1) and 2). A Microgrid with PV arrays, bi-directional PEV charging stations, and a commercial building is used in this study. The bi-directional power from/to PEVs provides the opportunity of using PEVs to reduce the intermittency of PV power generation and the peak load of the Microgrid. Simulation has been performed for all three cases and the simulation results show that the presented optimization algorithms can meet defined objectives.
Prediction of Criminal Suspects Based on Association Rules and Tag Clustering  [PDF]
Bo Cheng, Weihong Li, Haoxin Tong
Journal of Software Engineering and Applications (JSEA) , 2019, DOI: 10.4236/jsea.2019.123003
Abstract: To date, not many studies have been conducted on criminal prediction. In this study, the criminal data related to city S is divided into a training data set and a validation data set at a 1:1 ratio in light of the personal tag data and the travel and accommodation data of criminals and ordinary people in city S. Firstly, the FP-growth algorithm is adopted to calculate association rules between the criminals and the ordinary people in their travel and hotel accommodation data, in order to discover criminal suspects based on association rules. Secondly, the DBSCAN algorithm is employed for clustering of the tag data of the criminals and the ordinary people, followed by similarity calculation, in order to discover criminal suspects based on tag clustering. Lastly, intersection operation is performed on the above two sets of criminal suspects, and the resulting intersection is verified against the criminal validation set for elimination of criminals who appear in the intersection so as to obtain final criminal suspects. Results show that a set of 648 criminal suspects is retrieved based on the association rules calculated by the FP-growth algorithm, while a set of 973 criminal suspects is retrieved based on DBSCAN clustering and cosine similarity of the personal tags; the number of criminal suspects is narrowed down to 567 after the intersection operation of the two sets, and 419 of the 567 criminal suspects are further verified to be criminals using the validation set, thereby leaving the other 148 to be the final criminal suspects and giving a prediction accuracy of 73.9%. The data mining method of criminal suspects based on association rules and tag clustering in this study has been successfully applied to the police system of city S, and the experiment proves the effectiveness of this method in detecting criminal suspects.
Structures and dynamics of glass-forming colloidal liquids under spherical confinement
Bo Zhang,Xiang Cheng
Physics , 2015,
Abstract: Recent theories have predicted that when a supercooled liquid approaches the glass transition, particle clusters with a special "amorphous order" nucleate within the liquid, which lead to static correlations dictating the dramatic slowdown of liquid relaxation. The prediction, however, has yet to be verified in 3D experiments. Here, we design a colloidal system, where particles are confined inside spherical cavities with an amorphous layer of particles pinned at boundary. Using this novel system, we capture the amorphous-order particle clusters and demonstrate the development of a static correlation. Moreover, by investigating the dynamics of spherically confined samples, we reveal a profound influence of the static correlation on the relaxation of colloidal liquids. In analogy to glass-forming liquids with randomly pinned particles, we propose a simple relation for the change of the configurational entropy of confined colloidal liquids, which quantitatively explains our experimental findings and illustrates a divergent static length scale during colloidal glass transition.
Influence of Particle Size and Temperature on Gasification Performance in Externally Heated Gasifier  [PDF]
Yu Feng, Bo Xiao, Klaus Goerner, Gong Cheng, Jingbo Wang
Smart Grid and Renewable Energy (SGRE) , 2011, DOI: 10.4236/sgre.2011.22018
Abstract: In the present study the catalytic steam gasification of biomass to produce hydrogen-rich gas with calcined dolomite as catalyst in an externally heated fixed bed reactor was investigated. The influence of the reactor temperature on yield and product composition was studied at the temperature range of 700 PoPC-900 PoPC. Over the ranges of experimental con-ditions examined, tar was completely decomposed as temperature increases from 800P oPC to 900 PoPC. Higher temperature resulted in more HR2R and COR2R production, and dry gas yield. The highest H2 content of 51.02 V%, and the highest HR2 Ryield of 1.66 mP3P/kg biomass were observed at the highest temperature level of 900P oPC.
Influence of Catalyst and Temperature on Gasification Performance by Externally Heated Gasifier  [PDF]
Yu Feng, Bo Xiao, Klaus Goerner, Gong Cheng, Jingbo Wang
Smart Grid and Renewable Energy (SGRE) , 2011, DOI: 10.4236/sgre.2011.23021
Abstract: In the present study the catalytic steam gasification of biomass to produce hydrogen-rich gas with calcined dolomite and Nano-NiO/γ-Al2O3 as catalyst in an externally heated fixed bed reactor was investigated. The influence of the catalyst and reactor temperature on yield and product composition was studied at the temperature range of 700oC - 900oC. Over the ranges of experimental conditions examined, calcined dolomite revealed better catalytic performance, at the presence of steam, tar was completely decomposed as temperature increases from 800oC to 900oC. Higher temperature resulted in more H2 and CO2 production, and dry gas yield. The highest H2 content of 51.02 mol%, and the highest H2 yield of 1.66 m3/kg biomass were observed at the highest temperature level of 900oC.
A Personalized Cloud Services Recommendation Based on Cooperative Relationship between Services  [PDF]
Chengwen Zhang, Jiali Bian, Bo Cheng, Lingfei Li
Journal of Software Engineering and Applications (JSEA) , 2013, DOI: 10.4236/jsea.2013.612074
Abstract:

A personalized recommendation for cloud services, which is based on usage history and the cooperative relationship of cloud services, is presented. According to service groups, a service group could be defined as several services that were used together by one user at a time, and cooperative relationship between each two services can be calculated. In the process of recommendation, the services which are highly related to the service that the user has selected would be obtained firstly, the result should then take the QoS (Quality of Service) similarity between service’s QoS and user’s preference into account, so the final result combining the cooperative relationship and similarity will meet the functional needs of users and also meet the users personalized non-functional requirements. The simulation proves that the algorithm works effectively.

Finger-vein image recognition combining modified hausdorff distance with minutiae feature matching  [PDF]
Cheng-Bo Yu, Hua-Feng Qin, Lian Zhang, Yan-Zhe Cui
Journal of Biomedical Science and Engineering (JBiSE) , 2009, DOI: 10.4236/jbise.2009.24040
Abstract: In this paper, we propose a novel method for finger-vein recognition. We extract the features of the vein patterns for recognition. Then, the minutiae features included bifurcation points and ending points are extracted from these vein patterns. These feature points are used as a geometric representation of the vein patterns shape. Finally, the modified Hausdorff distance algorithm is provided to evaluate the identifica-tion ability among all possible relative positions of the vein patterns shape. This algorithm has been widely used for comparing point sets or edge maps since it does not require point cor-respondence. Experimental results show these minutiae feature points can be used to perform personal verification tasks as a geometric rep-resentation of the vein patterns shape. Fur-thermore, in this developed method. we can achieve robust image matching under different lighting conditions.
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