A new bonding-tool solution to improve stitch bondability

A new bonding-tool solution is proposed to improve stitch bondability by creating a new surface morphology on the tip surface of a wire-bonding tool (capillary). The surface has relatively deep lines with no fixed directions. This new capillary has less slipping between the wire and the capillary tip surface and provides better coupling effect between them. Experiments of wire bonding on unstable lead frames/substrates, alloyed wire (2N gold wire) bonding, and copper wire bonding were carried out to confirm the effect of the new capillary on the stitch bondability. The experimental results are promising and have proved that the use of the new capillary could improve the bondability of the stitch bond and minimize the occurrence of short tail defects and non-sticking on lead during bonding.     

Sequential Data Fusion via Vector Spaces: Fusion of Heterogeneous Data in the Complex Domain

A sequential data fusion approach via higher dimensional vector spaces is introduced. This is achieved by making use of the representation of directional signals within the field of complex numbers $C$ . The concept of data fusion is next introduced and the place of the proposed approach within that framework is identified. The benefits of such an approach are illustrated and a range of possible applications is shown. The concept introduced is supported by a real world case study which focuses on simultaneous forecasting of wind speed and direction. The architectures and learning algorithms which support this concept are introduced and their distributed sequential fusion nature is highlighted.     

Synthesis and Characterization of NiO Nano‐Spheres by Templating on Chitosan as a Green Precursor

In this study, nickel oxide was prepared through the calcination of extrusion dripped chitosan/nickel nitrate beads. The morphology and structural properties of the products were studied using various characterization techniques. Uniformly distributed nickel oxide was formed as observed from the studies of surface morphology where the processing parameters play a huge role on the resulting morphology. TEM results have shown that nickel oxide with crystallite sizes of 10–30 nm was obtained. The Fourier‐transform infrared spectra studies show an intense peak at 525 cm^?1, which is attributed to the vibration of Ni–O bond. Furthermore, the XRD results show NiO diffraction peaks correspond to (111), (200), (220), (311), and (222) which indicates that a bunsenite structure with a face‐centered cubic phase was produced in this study. The usage of 500°C as the lower limit in this study is justified due to the complete removal of the templating material as seen in the thermalgravimetric analysis studies. Furthermore, it was obtained that the largest surface area of nickel oxide synthesized using this technique is 48.024 m²/g with pore sizes of 19.843 nm. The usage of chitosan as a green template for the synthesis of nanoparticles has shown promising results which allows a more economical and sustainable approach for the fabrication of nanomaterials.     

Facile modification of polysulfone hollow-fiber membranes via the incorporation of well-dispersed iron oxide nanoparticles for protein purification

Protein existence in wastewater is an important issue in wastewater management because proteins are generally present as contaminants and foulants. Hence, in this study, we focused on designing a polysulfone (PSf) hollow-fiber membrane embedded with hydrophilic iron oxide nanoparticles (IONPs) for protein purification by means of ultrafiltration. Before membrane fabrication, the dispersion stability of the IONPs was enhanced by the addition of a stabilizer, namely, citric acid (CA). Next, PSf–IONP–CA nanocomposite hollow-fiber membranes were prepared via a dry–wet spinning process and then characterized in terms of their hydrophilicity and morphology. Ultrafiltration and adsorption experiments were then conducted with bovine serum albumin as a model protein. The results that an IONP/CA weight ratio of 1:20 contributed to the most stable IONP dispersion. It was also revealed that the membrane incorporated with IONP–CA at a weight ratio of 1:20 exhibited the highest pure water permeability (58.6 L m⁻² h⁻¹ bar⁻¹) and protein rejection (98.5%) while maintaining a low protein adsorption (3.3 μg/cm²). The addition of well-dispersed IONPs enhanced the separation features of the PSf hollow-fiber membrane for protein purification. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47502.     

Mechanical reinforcement of polyethylene using n‐alkyl group‐functionalized multiwalled carbon nanotubes: Effect of alkyl group carbon chain length and density

Polyethylene (PE) is one of the most produced synthetic resins in the world. Functionalized multiwalled carbon nanotube (MWCNT) is a potential nanoscale filler to realize the next generation strong and multifunctional PE composites. We demonstrate that MWCNTs grafted with short n‐alkyl groups are effective nanofillers for mechanical reinforcement of PE composites. At 1 wt% filler loading, the yield stress and Young's modulus improve significantly up to 54 and 63% compared with neat PE, respectively. Among ductile properties, tensile strength increases up to 30%; ultimate strain is preserved; and toughness increases up to 33%. More important, we show that short n‐alkyl groups can be grafted on MWCNTs much easier than long chain polymers. Further, we find that alkyl groups of C14–C18 chains have the optimum length for reinforcement. The optimum density of grafted alkyl groups is around 0.390–0.423 μmol/mg when the C14 alkyl groups are used. Overall, the results manifest that MWCNTs grafted with n‐alkyl groups with suitable length and density are efficient nanoscale fillers for high‐performance PE composites. POLYM. ENG. SCI., 54:336–344, 2014. © 2013 Society of Plastics Engineers     

New Approach to High-Pressure Nuclear Magnetic Resonance with Anvil Cells

A novel approach that uses radio-frequency microcoils in the high-pressure region of anvil cells with Nuclear Magnetic Resonance (NMR) experiments is described. High-sensitivity Al NMR data at 70 kbar for Al metal are presented for the first time. An expected decrease in the Al Knight shift at 70 kbar is observed, as well as an unexpected change in the local charge symmetry at the Al nucleus. The latter is not predicted by chemical structure analysis under high pressure.     

Software‐processed edge‐ and level‐adaptive overdrive (SELAO) method for high‐quality motion pictures

Abstract— In this paper, a software‐processed edge‐ and level‐adaptive overdrive (SELAO) method, which is a novel overdrive technique that utilizes not only a temporal change of gray levels but also a spatial edge intensity of motion pictures, is proposed. The SELAO method is a software video‐processing technology to improve motion‐picture quality rendered on LCDs more than is possible with a conventional SLAO method without edge‐adaptive overdrive, and it works in real time on commonly used personal computers (PCs).     

An Investigation on Noisy Environments in Evolutionary Multiobjective Optimization

In addition to satisfying several competing objectives, many real-world applications are also characterized by a certain degree of noise, manifesting itself in the form of signal distortion or uncertain information. In this paper, extensive studies are carried out to examine the impact of noisy environments in evolutionary multiobjective optimization. Three noise-handling features are then proposed based upon the analysis of empirical results, including an experiential learning directed perturbation operator that adapts the magnitude and direction of variation according to past experiences for fast convergence, a gene adaptation selection strategy that helps the evolutionary search in escaping from local optima or premature convergence, and a possibilistic archiving model based on the concept of possibility and necessity measures to deal with problem of uncertainties. In addition, the performances of various multiobjective evolutionary algorithms in noisy environments, as well as the robustness and effectiveness of the proposed features are examined based upon five benchmark problems characterized by different difficulties in local optimality, nonuniformity, discontinuity, and nonconvexity     

Examining the Effectiveness of Gamification in Human Computation

Within the human computation paradigm, gamification is increasingly gaining interest. This is because an enjoyable experience generated by game features can be a powerful approach to attract participants. Although potentially useful, little research has been conducted into understanding the effectiveness of gamification in human computation. In this experimental study, we operationalized effectiveness as perceived engagement and user acceptance and examined it by comparing the performance of a gamified human computation system against a non-gamified version. We also investigate the determinants of acceptance and how their effects differ between these two systems. Analysis of our data found that participants experienced more engagement and showed higher behavioral intentions toward the gamified system. Moreover, perceived output quality and perceived engagement were significant determinants of acceptance of the gamified system. In contrast, determinants for acceptance of the non-gamified system were perceived output quality and perceived usability.