Frequency-splitting Dynamic MRI Reconstruction using Multi-scale 3D Convolutional Sparse Coding and Automatic Parameter Selection

Department of Computer Science and EngineeringIn this thesis, we propose a novel image reconstruction algorithm using multi-scale 3D con- volutional sparse coding and a spectral decomposition technique for highly undersampled dy- namic Magnetic Resonance Imaging (MRI) data. The proposed method recovers high-frequency information using a shared 3D convolution-based dictionary built progressively during the re- construction process in an unsupervised manner, while low-frequency information is recovered using a total variation-based energy minimization method that leverages temporal coherence in dynamic MRI. Additionally, the proposed 3D dictionary is built across three different scales to more efficiently adapt to various feature sizes, and elastic net regularization is employed to promote a better approximation to the sparse input data. Furthermore, the computational com- plexity of each component in our iterative method is analyzed. We also propose an automatic parameter selection technique based on a genetic algorithm to find optimal parameters for our numerical solver which is a variant of the alternating direction method of multipliers (ADMM). We demonstrate the performance of our method by comparing it with state-of-the-art methods on 15 single-coil cardiac, 7 single-coil DCE, and a multi-coil brain MRI datasets at different sampling rates (12.5%, 25% and 50%). The results show that our method significantly outper- forms the other state-of-the-art methods in reconstruction quality with a comparable running time and is resilient to noise.ope

Natural Language Generation From Ontologies Using Grammatical Framework

The paper addresses the problem of automatic generation of natural language descriptions for ontology-described artifacts. The motivation for the work is the challenge of providing textual descriptions of automatically generated scientific workflows (e.g., paragraphs that scientists can include in their publications). The extended abstract presents a system which generates descriptions of sets of atoms derived from a collection of ontologies. The system, called nlgPhylogeny, demonstrates the feasibility of the task in the Phylotastic project, that aims at providing evolutionary biologists with a platform for automatic generation of phylogenetic trees given some suitable inputs. nlgPhylogeny utilizes the fact that the Grammatical Framework (GF) is suitable for the natural language generation (NLG) task; the abstract shows how elements of the ontologies in Phylotastic, such as web services, inputs and outputs of web services, can be encoded in GF for the NLG task

ACTUAL SITUATION OF HUMAN RESOURCES WITH BACHELOR’S DEGREE OF SPORTS MAJORING IN BASKETBALL AT BAC NINH SPORT UNIVERSITY OF VIETNAM

The study investigated the assessing the actual situation of human resources with bachelor’s degree in Basketball major, Bac Ninh Sport University of Viet Nam in the period of 2015-2019 through the following criteria: characteristics of the major graduates and job searching results of the bachelors after graduation. The result showed that the percentage of enrolled and graduated students majoring in Basketball accounts for a high percentage of the total students in the university. However, the number of students majoring in Basketball does the right job after leaving university is still low. The level of meeting the social requirements of Bachelors of Sports majoring in Basketball is mainly at the average level.  Article visualizations

Changes of benthic macroinvertebrates in Thi Vai River and Cai Mep Estuaries under polluted conditions with industrial wastewater

The pollution on the Thi Vai River has been spreading out rapidly over the two lasted decades caused by the wastewater from the industrial parks in the left bank of Thi Vai River and Cai Mep Estuaries. The evaluation of the benthic macroinvertebrate changes was very necessary to identify the consequences of the industrial wastewater on water quality and aquatic ecosystem of Thi Vai River and Cai Mep Estuaries. In this study, the variables of benthic macroinvertebrates and water quality were investigated in Thi Vai River and Cai Mep Estuaries, Southern Vietnam. The monitoring data of benthic macroinvertebrates and water quality parameters covered the period from 1989 to 2015 at 6 sampling sites in Thi Vai River and Cai Mep Estuaries. The basic water quality parameters were also tested including pH, dissolved oxygen (DO), total nitrogen, and total phosphorus. The biodiversity indices of benthic macroinvertebrates were applied for water quality assessment. The results showed that pH ranged from 6.4 – 7.6 during the monitoring. The DO concentrations were in between 0.20 – 6.70 mg/L. The concentrations of total nitrogen and total phosphorous ranged from 0.03 – 5.70 mg/L 0.024 – 1.380 mg/L respectively. Macroinvertebrate community in the study area consisted of 36 species of polychaeta, gastropoda, bivalvia, and crustacea, of which, species of polychaeta were dominant in species number. The benthic macroinvertebartes density ranged from 0 – 2.746 individuals/m2 with the main dominant species of Neanthes caudata, Prionospio malmgreni, Paraprionospio pinnata, Trichochaeta carica, Maldane sarsi, Capitella capitata, Terebellides stroemi, Euditylia polymorpha, Grandidierella lignorum, Apseudes vietnamensis. The biodiversity index values during the monitoring characterized for aquatic environmental conditions of mesotrophic to polytrophic. Besides, species richness positively correlated with DO, total nitrogen, and total phosphorus. The results confirmed the advantage of using benthic macroinvertebrates and their indices for water quality assessment

STUDY ON MULTI-OBJECTIVE OPTIMIZATION OF THE TURNING PROCESS OF EN 10503 STEEL BY COMBINATION OF TAGUCHI METHOD AND MOORA TECHNIQUE

In this study, the multi-objective optimization problem of turning process was successfully solved by a Taguchi combination method and MOORA techniques. In external turning process of EN 10503 steel, surface grinding process, the orthogonal Taguchi L9 matrix was selected to design the experimental matrix with four input parameters namely insert nose radius, cutting velocity, feed rate, and depth of cut. The parameters that were chosen as the evaluation criteria of the machining process were the surface roughness (Ra), the cutting force amplitudes in X, Y, Z directions, and the material removal rate (MRR). Using Taguchi method and MOORA technique, the optimized results of the cutting parameters were determined to obtain the minimum values of surface roughness and cutting force amplitudes in X, Y, Z directions, and maximum value of MRR. These optimal values of insert nose radius, cutting velocity, feed rate, and cutting depth were 1.2 mm, 76.82 m/min, 0.194 mm/rev, and 0.15 mm, respectively. Corresponding to these optimal values of the input parameters, the surface roughness, cutting force amplitudes in X, Y, Z directions, and material removal rate were 0.675 µm, 124.969 N, 40.545 N, 164.206 N, and 38.130 mm3/s, respectively. The proposed method in this study can be applied to improve the quality and effectiveness of turning processes by improving the surface quality, reducing the cutting force amplitudes, and increasing the material removal rate. Finally, the research direction was also proposed in this stud

Optimal generation for wind-thermal power plant systems with multiple fuel sources

In this paper, the combined wind and thermal power plant systems are operated optimally to reduce the total fossil fuel cost (TFFC) of all thermal power plants and supply enough power energy to loads. The objective of reducing TFFC is implemented by using antlion algorithm (ALA), particle swarm optimization (PSO) and Cuckoo search algorithm (CSA). The best method is then determined based on the obtained TFFC from the three methods as dealing with two study cases. Two systems with eleven units including one wind power plant (WPP) and ten thermal power plants are optimally operated. The two systems have the same characteristic of MFSs but the valve loading effects (VLEs) on thermal power plants are only considered in the second system. The comparisons of TFFC from the two systems indicate that CSA is more powerful than ALA and PSO. Furthermore, CSA is also superior to the two methods in terms of faster search process. Consequently, CSA is a powerful method for the problem of optimal generation for wind-thermal power plant systems with consideration of MFSs from thermal power plants