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.

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.

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

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.

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.

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%.

Introduction: Exclusive breastfeeding mothers need additional food to increase the quality and quantity of milk. Moringa biscuits are one additional food that is easy to consume and has high nutritional value. This study aims to assess whether breastfeeding mothers\' acceptance of Moringa biscuits as supplementary food during breastfeeding helps maintain exclusive breastfeeding\nMethods: This was an experimental study with a posttest only with control group design. The subjects were 24 nursing mothers. Those in the intervention groups were given 50 grams of moringa cookies each day for six months and were asked about their perception of the biscuits. The relationship between exclusive breastfeeding and Moringa cookies consumption was analyzed by the chi-square test.\nResults: The overall score for the biscuits was 81.67. The highest score was the amount (94), followed by the form (87), then the packing (82). Size is rated 77, and the lowest score is the taste and color (75). Furthermore, the overall value for the perception of Moringa biscuits as a supplementary food was 81.25. The result of chi-square test for cookies consumption and exclusive breastfeeding was p=1.000.\nConclusion: Nursing mothers enjoy to consume Moringa biscuits as complementary food, although the consumption of moringa cookies does not affect in maintaining exclusive breastfeeding.