Title: Research of Super-hydrophobic for Metal Material based on Wire Cut Electrical Discharge Machining

Abstract: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.

Title: A Compressive MIMO Radar-Based DOA Estimation Structure Exploiting Coprime Frequencies

Abstract: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.

Title: Systematic review of Agricultural Wastes for Production of Bacterial Cellulose

Abstract: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.

Title: Effect of pulse power supply on electrolytic processing performance of tubular electrodes

Abstract:The application of tube electrode for electrochemical machining (ECM) holes in the surface of nickel based alloy was investigated in this paper. The function of pulse power supply in electrochemical machining of tube electrode and the effect of pulse power supply on hole size and hole depth were obtained via analysising Pulse power supply on small holes forming, thus the reasons affecting the stability of electrochemical machining of small holes with tube electrode were obtained.

Title: Evaluation of Mechanical Properties of Bagasse/Palm Kernel Fibres for Fabrication of Automotive Brake Pads

Abstract:Composites which are having a good strength to less weight ratio can be applied to replace the conventionally used engineering materials. Natural fiber constitutes good properties nearly equal to that of artificial fibers. In many applications natural fiber can be applied and also it is an inexpensive material. Most of the natural fibersare extracted from the reissue of used agro products. This present study gives a brief characterization report of hybrid natural fiber composed of bagasse and palm kernel shell fiber, which is mixed in the ratio of 50:50. The mechanical properties of this natural hybrid fiber are studied by varying the micro structure to three different micron levels, such as 100, 200 and 250 µm. From this it is valid that the sample with a size of 100 µm gives a good result by carrying out material characterization test such as tensile test, compressive test density test, hardness and wear test.

Title: The Study of Electrolyte Concentration on Small Holes in Pulse Electrochemical Machining

Abstract:The application of tube electrode for electrochemical machining (ECM) holes in the surface of nickel based alloy was investigated in this paper. The distribution of interstitial electrolyte concentration in electrochemical machining of tube electrode and the effect of interstitial electrolyte concentration on hole size and hole depth were obtained via analysising electrolyte concentration distribution on small holes forming, thus the reasons affecting the stability of electrochemical machining of small holes with tube electrode were obtained.

Title: Gluconobacter Oxydans PIN7 as a Potential Producer of Cellulose from Fruit Wastes

Abstract:Cellulose is an essential polymer that is commonly produced from plants and bacteria in numerous industrial operations such as the biomedical and food industry. While the production of cellulose from plants is costly, bacterial cellulose (BC) is recognised to be one of the best types of cellulose produced. Therefore, this study aimed to create BC from different types of fruit wastes through isolation, identification, and characterisation procedures. A total of 50 fruit waste samples (watermelon, pineapple, mango, apple, and grape) were collected in Serdang, Selangor, Malaysia, whereby ten isolates from these samples were capable of producing BC. Ten selected isolates were analysed for morphological and biochemical tests, which showed all isolates matched the characteristics of BC producers. The BC production from each isolate was then evaluated using the batch culture technique that was cultivated in the Hestrin-Schramm medium. From the ten strains, only one isolate showed high BC production (3.48 g/L ± 0.17), which was from the pineapple sample. The BC produced by the isolate PIN7 was verified and characterised using X-ray diffraction (XRD) analysis, which showed the cellulose structure of the biofilm conformed and matched the cellulose I crystal structure that was rich in Iα mass fraction. That isolate PIN7 was finally identified using 16S rRNA analysis and indicated to be closely linked to Gluconobacter Oxydans, with a sequence identity of 98%. The strain was identified as G. oxydans PIN7. Hence, the potential to isolate PIN7 was tested and demonstrated to have a high capability in producing BC

Title: Direction-of-Arrival Estimation Using Sparse MIMO Radar: A Compressive Measurement Perspective

Abstract:Sparse multiple-input multiple-output (MIMO) radar can generated a sum-difference coarray with extended array aperture by using a group of antennas to transmit detection signals. However, when the number of physical array antennas is the same, the number of virtual antennas yielded by sum-difference coarray of sparse MIMO radar is much larger than that of traditional MIMO radar due to the extended inter-element spacing, which will cause a large increase in signal dimension. Therefore, when sparse MIMO radar is used for direction-of-arrival (DOA) estimation, the computational complexity is relatively high, which will affect the real-time estimation. To solve this problem, a DOA estimation structure based on compressive sparse MIMO radar is proposed in this paper. The corresponding system model is first constructed, and then, we introduce an estimation algorithm using compressive sensing method to deal with under-determined case. To make the system design easy to be finished in practice, several important system performance indexes are analyzed by deriving the Cramér-Rao bound (CRB) expression. Conclusions on the number of degrees of freedom (DOFs) are obtained. Through theoretical analysis and simulation validation, the proposed structure can greatly reduce the computational complexity while ensuring a certain estimation performance. In addition, the system design is flexible due to the use of the combining network, since the combining network divides the whole system into two parts that are relatively independent.

Title: Neighbourly regular strength of regular graphs

Abstract:A graph is said to be a neighbourly irregular graph (NI graph) if every pair of its adjacent vertices have distinct degrees. Let G be a simple graph of order n. The neighbourly regular strength of G is denoted by NRS(G) and is defined as the minimum positive integer k for which there is an NI graph of order n+k in which G is an induced subgraph. In this paper, we obtain the NRS of regular graphs and some related results. Also, we find the graphs of order n, for each n > 2, with NRS is exactly equal to n-2.

Title: Long Short-term Memory Neural Networks for Radar Waveform Recognition

Abstract:Accurate identification of radar waveforms is of great value in electronic reconnaissance and anti-reconnaissance. In this paper, a radar waveform automatic identification system for detecting, tracking and locating low intercept probability (LPI) radar is studied. This system can recognize eight LPI radar waveforms under low SNR conditions, including binary phase shift keying (BPSK), linear frequency modulation (LFM), Costas codes, Frank code, T1-T4 codes. Firstly, the system performs CWD time-frequency transform on LPI radar waveform to obtain two-dimensional time-frequency image. Then, it preprocesses two-dimensional time-frequency image, including detection and deletion of no-signal region, frequency domain filtering to remove noise, calculation of marginal frequency distribution to intercept useful frequency image, adaptive binarization and image adaptive processing. Finally, the pre-processed image is sent to the long-short memory network for off-line training and online recognition. The experimental results show that when SNR=-4dB, the overall recognition accuracy of the system for eight kinds of LPI radar waveforms can reach 98.38%.