Tumor Segmentation and Classification Using Machine Learning Approaches

Medical image processing has recently developed progressively in terms of methodologies and applications to increase serviceability in health care management. Modern medical image processing employs various methods to diagnose tumors due to the burgeoning demand in the related industry. This study uses the PG-DBCWMF, the HV area method, and CTSIFT extraction to identify brain tumors that have been combined with pancreatic tumors. In terms of efficiency, precision, creativity, and other factors, these strategies offer improved performance in therapeutic settings. The three techniques, PG-DBCWMF, HV region algorithm, and CTSIFT extraction, are combined in the suggested method. The PG-DBCWMF (Patch Group Decision Couple Window Median Filter) works well in the preprocessing stage and eliminates noise. The HV region technique precisely calculates the vertical and horizontal angles of the known images. CTSIFT is a feature extraction method that recognizes the area of tumor images that is impacted. The brain tumor and pancreatic tumor databases, which produce the best PNSR, MSE, and other results, were used for the experimental evaluation

PREMILINARY RESEARCH ON ARSENIC POLLUTION OF SURFACE AND GROUND WATER IN TRA NANG GOLD EXPLOITATION REGION-LAM DONG PROVINCE AND CAO LANH TOWN-DONG THAP PROVINCE

Joint Research on Environmental Science and Technology for the Eart

Interaction between triphenylphosphine or 1,2-bis(diphenylphosphino)ethane with some complexes K[PtCl3(olefin)] (olefin: methyleugenol, safrole, isopropyl eugenoxyacetate)

Novel study on the interaction between K[PtCl3(olefin)] (olefin: methyleugenol, safrole and isopropyl eugenoxyacetate) with TPP and DPPE shows that TPP and DPPE readily replace the olefins to form complexes [PtCl2(TPP)2] (P4), [PtCl2(DPPE)] (P5) and [Pt(DPPE)2]Cl2 (P6). P4 possesses trans configuration when the molar ratio of the mono olefin and TPP of 1:1. When the ratio is 1:2, P4 is a mixture of trans and cis isomers of which trans one is prevailing. The cis isomer trends to convert to trans one in chloroform solvent. P5 and P6 were formed when the molar ratio of mono isopropyl eugenoxyacetate and DPPE of 1:1 and 1:2, respectively. The structures of P4÷P6 were elucidated by Pt analysis, ESI-MS, IR and 1H NMR spectra studies. Keywords. Pt(II) complexes, olefins, phosphine derivatives

Design and Analysis of Ternary m-sequences with Interleaved Structure by d-Transform

Multilevel sequences find more and more applications in modern modulation schemes [4QPSK, 8QPSK,16QAM..]  for the 3G ,4G system air interface [1,2].Furthermore, in modern cryptography they are also widerly used. It is also interesting to point out that the length L of these sequences are composite numbers( L=NS),that means the sequence can be easily implemented by interleaving S subsequences, each of length S.Therefore, the methods to develop multilevel sequence with interleaved structure draw a lot of attentions [3, 4]. In this contribution, a method for design and analysis of ternary m-sequences with interleaved structure is presented, based on the d-transform, Which turns out to be a very effective and versal tool for this purpose. Simulations have been made to verify the theory. We first introduce d-transform and its properties and then work out the procedure to design an interleaving sequence in d-transform. Keywords: d-transform,q-ary sequences, interleaved sequence

Optimization of compressed air assisted-turning-burnishing process for improving machining quality, energy reduction and cost-effectiveness

The burnishing process is used to enhance the machining quality via improving the surface finish, surface hardness, wear-resistance, fatigue, and corrosion resistance, and it is mostly used in aerospace, biomedical, and automotive industries to improve reliability and performance of the component. The combined turning and burnishing process is therefore considered as an effective solution to enhance both machining quality and productivity. However, the trade-off analysis between energy consumption, surface characteristics, and production costs has not been well-addressed and investigated. This study presents an optimization of the compressed air assisted-turning-burnishing (CATB) process for aluminum alloy 6061, aimed to decrease the energy consumption as well as surface roughness and to enhance the Vicker hardness of the machined surface. The machining parameters for consideration include the machining speed, feed rate, depth of cut, burnishing force, and the ball diameter. The improved Kriging models were used to construct the relations between machining parameters and the technological response characteristics of the machined surface. The optimal machining parameters were obtained utilizing the desirability approach. The energy based-cost model was developed to assess the effectiveness of the proposed CATB process. The findings showed that the selected optimal outcomes of the depth of cut, burnishing force, diameter, feed rate, and machining speed are 0.66 mm, 196.3 N, 8.0 mm, 0.112 mm/rev, and 110.0 m/min, respectively. The energy consumption and surface roughness are decreased by 20.15% and 65.38%, respectively, while the surface hardness is improved by 30.05%. The production cost is decreased by 17.19% at the optimal solution. Finally, the proposed CATB process shows a great potential to replace the traditional techniques which are used to machine non-ferrous metals

Vec2Face-v2: Unveil Human Faces from their Blackbox Features via Attention-based Network in Face Recognition

In this work, we investigate the problem of face reconstruction given a facial feature representation extracted from a blackbox face recognition engine. Indeed, it is a very challenging problem in practice due to the limitations of abstracted information from the engine. We, therefore, introduce a new method named Attention-based Bijective Generative Adversarial Networks in a Distillation framework (DAB-GAN) to synthesize the faces of a subject given his/her extracted face recognition features. Given any unconstrained unseen facial features of a subject, the DAB-GAN can reconstruct his/her facial images in high definition. The DAB-GAN method includes a novel attention-based generative structure with the newly defined Bijective Metrics Learning approach. The framework starts by introducing a bijective metric so that the distance measurement and metric learning process can be directly adopted in the image domain for an image reconstruction task. The information from the blackbox face recognition engine will be optimally exploited using the global distillation process. Then an attention-based generator is presented for a highly robust generator to synthesize realistic faces with ID preservation. We have evaluated our method on the challenging face recognition databases, i.e., CelebA, LFW, CFP-FP, CP-LFW, AgeDB, CA-LFW, and consistently achieved state-of-the-art results. The advancement of DAB-GAN is also proven in both image realism and ID preservation properties.Comment: arXiv admin note: substantial text overlap with arXiv:2003.0695

Current medical product development for diagnosis, surgical planning and treatment in the areas of Neurosurgery, Orthopeadic and Dental-Cranio-Maxillofacial surgery in Vietnam

With the population of 86 million and good GDP growth in recent decades, the medical market in Vietnam is growing fast. However, most of the medical technology products are imported, and the number of locally manufactured ones is limited and they do not have the high competition capability in term of quality, quantity and types. In this paper, the current product development in Vietnam for diagnosis, surgical planning and treatment in the areas of Rehabilitation, Neurosurgery, Orthopeadic and Dental-Cranio-Maxillofacial surgery is presented. A roadmap for medical technology development in Vietnam is propose