Cell Formation Problem (CFP) is a great combinatorial optimization problem. It comprises grouping of machines and parts into manufacturing cells for processing the parts. For this, we propose multi-objectives of CFP, with the objective to minimize (1) intercellular movements and (2) Cell Load Variation (CLV) in a given period of time. These multi-goals in CFP is assessed by utilizing mathematical modeling and soft computing techniques. Here a novel hybrid optimization algorithm combination of Discrete Cauchy Mutation Algorithm (DCMA) with Salp Swarm Algorithm (SSA) is presented. DCMA is the updated model of genetic algorithm and the hybridization of DCMA-SSA is maintained leading and gradually more powerful for engineering design problems compared with the existing algorithms. The performance of the hybrid algorithm is compared with the standard benchmark problems. The computational time of the proposed work, performs higher effectiveness while implementation.

Based on plenty of small hole experiments for pipe graphite impulse electrolytic machining, the article has studied effect of electrolyte concentration to shape accuracy, processing efficiency as well as gap current of pipe graphite electrolytic small hole. Departure from theory of electrolytic machining, the article has concluded by analyzing experimental data: with the increase of electrolyte concentration, the shape accuracy and processing efficiency of the pipe graphite impulse electrolytic machining can be enhanced to enhance the locality of the machining.

This research study is based on the smart skin and its usage in the different areas of field and also used in day to day activities in human surrounding. Miniaturizations, micro fabrication technologies (fabrics that contain sensors) are devices that can detect the human activities. Wearable devices that are linked with human skin are also known as smart skins. Smart skin is gradually increasing in the field of research a lot of development had been made in the past in diverse areas like medical, military, fitness, engineering, physiological tracking. Recent trends and challenges found which are: understand the applications and different approaches of applications, electronic framework issues, interface gadgets etc. Potential research areas of smart skin as: Augmented reality (mostly uses for communication, business, gaming training etc). Smart skin have most important role in technology to solve issues in every domain of research area. These devices are capable of sensing the changes that are been made in our daily activities.

Super-hydrophobicity of material surface has had relation with the surface energy of the material surface, which has even more affected by the micro structure of the material surface, among which, the micro structure of the material surface has directly affected its super-hydrophobic property, the super-hydrophobic property of the metal material can enhance waterproof, corrosion resistant, anti adhesion and anti-pollution, etc, which can effectively enhance its service life and property. The article has conducted micro structure machining of metal surface by adopting processing method of wire cut electrical discharge machining discharging, because its processing method has been electric spark discharging-plasma breakdown-heat dissolution, surface of the processed work piece will generate tiny protuberance and pit, however, this kind of structure has been similar to super-hydrophobic micro structure, therefore, the article has put forward method of processing super-hydrophobic micro structure of metal material by adopting WEDM and the article has analyzed the feasibility.

Abstract\nObjective: Various surgical techniques have been used to manage odontogenic keratocysts (OKCs). Here, we retrospectively evaluated OKC recurrence rates after enucleation, with and without application of Carnoy’s solution.\nMaterials and Methods: Seventy-seven patients with OKCs treated between 2007 and 2017 in the Department of Oral and Maxillofacial Surgery, Faculty of Dentistry, Istanbul University were included in this study. Treatment was performed via enucleation (Group I) or enucleation with application of Carnoy’s solution (Group II). The mean follow-up time was 46.7 months. The following data were recorded: management methods, patient sex and age, lesion location, and inflammation status.\nResults: The recurrence rates in Groups I and II were 13.1% and 6.1%, respectively; the difference was not statistically significant (p = 0.454). \nConclusions: The group treated with Carnoy’s solution tended to exhibit less recurrence.

The effective supply of human capital is the driving force for the sustainable growth of modern economy. The rapid development of China\'s sports service industry has been promoted by the rise of service economy and the healthy policy orientation of China . However, due to ineffective supply of human capital, China\'s sports service industry has experienced a development contradiction that the quality and efficiency of service has lagged behind the speed and scale, resulting in low economic contribution rate and imbalance between supply and demand of sports service industry. The ineffective supply of China\'s sports service industry is mainly manifested in three aspects: policy and system guarantee, human capital stock and application platform construction. Based on the background of supply-side reform, corresponding countermeasures and suggestions are put forward to promote the effective supply of human capital in China\'s sports service industry, aiming at promoting the high-quality development of sports service industry in essence.

The intelligent layout of two-dimensional irregular stamping blanks, which is a complicated matter under the control of multi-circumstances, cannot be best solved by any single algorithm. Aiming at solving this problem, based on the analysis of the traditional algorithm, this paper proposed a new kind of algorithm combined the dynamic positioning algorithm and the Hopfield artificial neural network. Building models for irregular parts produced by using the surrounding rectangle methods and graphic composition, on the basis of the dynamic positioning algorithm, the algorithm proposed in this paper goes to future optimize the calculation by using the neural network. Comparing with the traditional algorithm, The test results show that this technique not only has the advantages of high automation and fast-footed solution, but also improves the utilization of materials.

In this paper, we propose a compressive multiple-input multiple-output (MIMO) radar-based direction-of-arrival (DOA) estimation structure exploiting coprime frequencies, referred to as compressive coprime frequencies-based MIMO (CF-MIMO) radar. In the proposed structure, an equivalent coprime array is generated by transmitting signals with coprime frequencies. On the basis of obtaining an equivalent array with an extended array aperture and an increased number of virtual sensors provided by the MIMO array configuration, a coarray aperture is better utilized. The accuracy of the estimation is ensured while the system degrees of freedom (DOFs) is further improved. After the matched filters, the application of compressive sensing (CS) technology introduces a combining network, thus reducing the number of required front-end circuits and the overall system complexity. The compressing sensing technology based on group sparsity of signals is introduced into DOA estimation, and the group-LASSO algorithm is utilized to solve optimization problem in this paper. Next, in order to study the estimated performance of the proposed structure, we deduce the Cramér–Rao bound (CRB) for DOA estimation in detail. Accordingly, the rank condition to ensure the existence of CRB is also analyzed. Finally, the results of simulation experiments proved that the proposed structure has superior performance.

Bacterial cellulose (BC), a biopolymer, has gained importance in the recent past due to its physicochemical properties, which are desirable for various biotechnology, microbiological, and material science applications. Since cost is a significant limitation in the production of cellulose, there have been efforts to identify potential means of addressing this issue. Currently, all efforts are focused on using agricultural waste as a cost-effective substrate for the synthesis of microbial cellulose. Uncertainties abound regarding the capacity for large-scale commercial production of microbial cellulose using different types of waste materials. This study investigates researches on the feasibility of using waste as a source of carbon and nitrogen for commercial-scale production of bacterial cellulose. Preliminary findings reveal the potential to yield a high concentration of bacterial cellulose from various agricultural wastes. Moreover, recent research activities in the production of BC are also discussed. This review, at the same time, discusses some applications of BC briefly. The findings indicate the need to optimize culture conditions for improved production of bio-cellulose.