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The Synthesis of Magnetic Nano-Sized Iron Oxide from Liquid Solution by Adding Organic Components
Oybek, Tursun Kulov,Park, No Jin,Jo, Soo Jeong,Lee, Eun Young,Kamalov, Sharo Futdin,He, Li Li,Jeong, Soon Wook,Kim, Sung Jin Trans Tech Publications, Ltd. 2011 Materials science forum Vol.695 No.-
<P>Titanium silicon carbide (Ti3SiC2) is a remarkable material for its combination of the best properties of metals and ceramics. The high purity Ti3SiC2 ceramic has been prepared by infiltration sintering (IS), and the effect of a small amount of Si on Ti3SiC2 ceramic formation was investigated. The results show that the purity of Ti3SiC2 ceramic could be increased significantly and the sintering time for Ti3SiC2 could be decreased remarkably when proper amount of Si was added in the starting mixture. The Ti3SiC2 sintered compact with a purity of 99.2wt% and a relative density of 97% was obtained by the infiltration sintering from a starting mixture composed of n(Ti):n(Si):n(TiC) = 1:0.3:2 at 1500 °C with holding time of 2/3h.</P>
Oybek Valijonovich Tuyboyov,Geo-Sung Lee,Gil-Yong Lee 한국정밀공학회 2023 International Journal of Precision Engineering and Vol.10 No.5
We develop multi-mode soft composite bending actuators based on glass fiber textiles interwoven with shape memory alloy (SMA) wires and a soft matrix of polydimethylsiloxane. We describe their detailed design and fabrication. We varied the interweaving patterns of SMA wires, such that the actuators exhibit multi-mode bending behaviors. Actuators with three different bending modes were fabricated, and their performances were evaluated in terms of curvature. We varied the stiffness of glass fiber textiles and the diameters of SMA wires. Bidirectional multi-mode actuations were achieved when SMA wires of different interwoven patterns were combined with glass fiber textiles. We present prototypes of such actuators and demonstrate their actuations. Finally, we prepared gripper prototypes using these actuators; they grasped different objects according to bending mode. Our technique will aid the development of soft robotics, as well as other scientific and engineering applications.
Khamzaev, Oybek,Kim, No-Ju 신영어영문학회 2021 신영어영문학 Vol.79 No.-
This research analyses the syllables and stress placement in Uzbek nouns and adjectives. Syllables in Uzbek are divided into heavy and light to explain quantity-sensitivity in stress placement: Heavy syllables tend to attract stress. Previous studies argued that in Uzbek, stress docks on the final syllable except for loan words. However, this rule encounters exceptions. Hence, we have come up with new stress rules. Uzbek nouns and adjectives are stressed on the rightmost heavy syllable which is usually, but not always, a final syllable. In addition, if words do not contain any heavy syllables, then stress falls on the final light syllable. Furthermore, with the morpho-phonologically made superlative degree adjectives, stress falls on the word-initial heavy syllable. Finally, we will make a three-way comparison between the Uzbek stress system, the English stress system, and the North Kyungsang Korean tonal system, identifying the similarities and differences among them.
Synthesis, Characterization and Functionalization of the Coated Iron Oxide Nanostructures
Tursunkulov, Oybek,Allabergenov, Bunyod,Abidov, Amir,Jeong, Soon-Wook,Kim, Sungjin The Korean Powder Metallurgy Institute 2013 한국분말재료학회지 (KPMI) Vol.20 No.3
The iron oxides nanoparticles and iron oxide with other compounds are of importance in fields including biomedicine, clinical and bio-sensing applications, corrosion resistance, and magnetic properties of materials, catalyst, and geochemical processes etc. In this work we describe the preparation and investigation of the properties of coated magnetic nanoparticles consisting of the iron oxide core and organic modification of the residue. These fine iron oxide nanoparticles were prepared in air environment by the co-precipitation method using of $Fe^{2+}$: $Fe^{3+}$ where chemical precipitation was achieved by adding ammonia aqueous solution with vigorous stirring. During the synthesis of nanoparticles with a narrow size distribution, the techniques of separation and powdering of nanoparticles into rather monodisperse fractions are observed. This is done using controlled precipitation of particles from surfactant stabilized solutions in the form organic components. It is desirable to maintain the particle size within pH range, temperature, solution ratio wherein the particle growth is held at a minimum. The iron oxide nanoparticles can be well dispersed in an aqueous solution were prepared by the mentioned co-precipitation method. Besides the iron oxide nanowires were prepared by using similar method. These iron oxide nanoparticles and nanowires have controlled average size and the obtained products were investigated by X-ray diffraction, FESEM and other methods.
Rakhmonalieva Farangis Oybek K,Tursunboev Timur Bakhtiyor Ugl,Hee-Cheol Kim 한국정보통신학회 2023 한국정보통신학회 종합학술대회 논문집 Vol.27 No.1
Leukemia is a cancer-related disease that can be fatal and affects people of all ages, including children and adults. It is the worlds top cause of death. It is specifically connected to White Blood Cells (WBC), which are accompanied by an increase in immature lymphocytes and harm to the bone marrow and/or blood. As a result, a timely and accurate cancer diagnosis is a crucial prerequisite for effective treatment that increases survival rates. In recent years, the use of deep learning models for cancer detection has received much attention due to their high accuracy and efficiency in the analysis of large volumes of medical data.
Reliable Fault Diagnosis Method Based on An Optimized Deep Belief Network for Gearbox
이철희,Oybek Eraliev,Ozodbek Xakimov,이철희 사단법인 유공압건설기계학회 2023 드라이브·컨트롤 Vol.20 No.4
High and intermittent loading cycles induce fatigue damage to transmission components, resulting in premature gearbox failure. To identify gearbox defects, numerous vibration-based diagnostics techniques, using several artificial intelligence (AI) algorithms, have recently been presented. In this paper, an optimized deep belief network (DBN) model for gearbox problem diagnosis was designed based on time-frequency visual pattern identification. To optimize the hyperparameters of the model, a particle swarm optimization (PSO) approach was integrated into the DBN. The proposed model was tested on two gearbox datasets: a wind turbine gearbox and an experimental gearbox. The optimized DBN model demonstrated strong and robust performance in classification accuracy. In addition, the accuracy of the generated datasets was compared using traditional ML and DL algorithms. Furthermore, the proposed model was evaluated on different partitions of the dataset. The results showed that, even with a small amount of sample data, the optimized DBN model achieved high accuracy in diagnosis