Local people in Sarawak, Malaysia produce sago starch, commonly referred as lemantak, using traditional method for authentic meals and delicacies. The quality of lemantak degrades with time due to its high moisture content limiting the potential for a wider market, and hence affecting the socio-economy of those whose livelihood depends on sago starch production. The objective of the present work was to evaluate the changes in the properties of traditionally processed dried Sarawak sago starch. In order to achieve this, sago starch was extracted using a well-established traditional process and was dried at 40°C to produce sago starch with moisture contents of 40%, 30%, 20% and 10% wet basis. The effect of moisture content on the physical properties was studied through colour analysis, microscopic analysis, and particle size distribution. Analysis on resistant starch content was also performed. Changes on the hydration and functional properties was monitored by measuring the water absorption index (WAI), water solubility index (WSI), swelling capacity (SC), and gelatinisation behaviour. Lastly, Fourier transform-infrared spectroscopy (FT-IR) was applied to observe the changes in amorphous and crystalline areas. The physical properties analysis showed changes in starch colour and granule surface; but the change on granule size varied. Dried starch with lower moisture content exhibited higher resistant starch, absorption index, and peak temperature, but lower solubility index, swelling capacity, peak viscosity, crystalline index, and amorphous index. It is suggested that moisture content affected the changes in traditionally processed sago starch properties which was influenced by few components namely polyphenol, lipid, amylose-lipid complex, and inter-molecular hydrogen bond.
Due to the complexity of autonomous mobile robot's requirement and drastic technological changes, the safe and efficient path tracking development is becoming complex and requires intensive knowledge and information, thus the demand for advanced algorithm has rapidly increased. Analyzing unstructured gain data has been a growing interest among researchers, resulting in valuable information in many fields such as path planning and motion control. Among those, motion control is a vital part of a fast, secure operation. Yet, current approaches face problems in managing unstructured gain data and producing accurate local planning due to the lack of formulation in the knowledge on the gain optimization. Therefore, this research aims to design a new gain optimization approach to assist researcher in identifying the value of the gain's product with a qualitative comparative study of the up-to-date controllers. Gains optimization in this context is to classify the near perfect value of the gain's product and processes. For this, a domain controller will be developed based on the attributes of the Fuzzy-PID parameters. The development of the Fuzzy Logic Controller requires information on the PID controller parameters that will be fuzzified and defuzzied based on the resulting 49 fuzzy rules. Furthermore, this fuzzy inference will be optimized for its usability by a genetic algorithm (GA). It is expected that the domain controller will give a positive impact to the path planning position and angular PID controller algorithm that meet the autonomous demand.
Laser-assisted high speed milling is a subtractive machining method that employs a laser to thermally soften a difficult-to-cut material's surface in order to enhance machinability at a high material removal rate with improved surface finish and tool life. However, this machining with high speed leads to high friction between workpiece and tool, and can result in high temperatures, impairing the surface quality. Use of conventional cutting fluid may not effectively control the heat generation. Besides, vegetable-based cutting fluids are invariably a major source of food insecurity of edible oils which is traditionally used as a staple food in many countries. Thus, the primary objective of this study is to experimentally investigate the effects of water-soluble sago starch-based cutting fluid on surface roughness and tool's flank wear using response surface methodology (RSM) while machining of 316 stainless steel. In order to observe the comparison, the experiments with same machining parameters are conducted with conventional cutting fluid. The prepared water-soluble sago starch based cutting fluid showed excellent cooling and lubricating performance. Therefore, in comparison to the machining using conventional cutting fluid, a decrease of 48.23% in surface roughness and 38.41% in flank wear were noted using presented approach. Furthermore, using the extreme learning machine (ELM), the obtained data is modeled to predict surface roughness and flank wear and showed good agreement between observations and predictions.
This study discloses a method for painting artwork using a CO2 laser. The continuous-wave laser beam, at a predetermined heat flux and a predetermined number of laser beam passes, mixes and displaces the plurality of colored polymer-based compositions, respectively, by way of melting and vaporizing them. Experiments showed a great accuracy of colors and designed patterns between the computer aided design (CAD) drawing and what was achieved after laser discoloration. It was found that lower values of power and speed provide sufficient energy and time to make a melt pool of colors and cause their vaporization from the surface. A detailed numerical simulation was performed to obtain a detailed understanding of the physics of laser interaction with paint using ABAQUS software. The comparative analysis indicated that the top layer of paint (including yellow and green colors) melted upon increasing cutting speed and employing one laser pass. For blue and red paints, two passes of lasers are required; in the case of red color, lower laser speed is also necessary to intensify the heat. This method can be applied for making art designs on each surface color because it is based on melting and vaporization using a laser.