Erratum to: Charge transfer in graphene/polymer interfaces for CO2 detection

Nano Research - The order of the authors in the original version of this article was unfortunately incorrect on the first page and the first page of the ESM. Instead of Myungwoo Son1, Yusin Pak1,...     

Applying Job Shop Scheduling to SMEs Manufacturing Platform to Revitalize B2B Relationship

A small and medium enterprises (SMEs) manufacturing platform aims to perform as a significant revenue to SMEs and vendors by providing scheduling and monitoring capabilities. The optimal job shop scheduling is generated by utilizing the scheduling system of the platform, and a minimum production time, i.e., makespan decides whether the scheduling is optimal or not. This scheduling result allows manufacturers to achieve high productivity, energy savings, and customer satisfaction. Manufacturing in Industry 4.0 requires dynamic, uncertain, complex production environments, and customer-centered services. This paper proposes a novel method for solving the difficulties of the SMEs manufacturing by applying and implementing the job shop scheduling system on a SMEs manufacturing platform. The primary purpose of the SMEs manufacturing platform is to improve the B2B relationship between manufacturing companies and vendors. The platform also serves qualified and satisfactory production opportunities for buyers and producers by meeting two key factors: early delivery date and fulfillment of processing as many orders as possible. The genetic algorithm (GA)-based scheduling method results indicated that the proposed platform enables SME manufacturers to obtain optimized schedules by solving the job shop scheduling problem (JSSP) by comparing with the real-world data from a textile weaving factory in South Korea. The proposed platform will provide producers with an optimal production schedule, introduce new producers to buyers, and eventually foster relationships and mutual economic interests.     

A Hemispherical Image Sensor Array Fabricated with Organic Photomemory Transistors

Hemispherical image sensors simplify lens designs, reduce optical aberrations, and improve image resolution for compact wide-field-of-view cameras. To achieve hemispherical image sensors, organic materials are promising candidates due to the following advantages: tunability of optoelectronic/spectral response and low-temperature low-cost processes. Here, a photolithographic process is developed to prepare a hemispherical image sensor array using organic thin film photomemory transistors with a density of 308 pixels per square centimeter. This design includes only one photomemory transistor as a single active pixel, in contrast to the conventional pixel architecture, consisting of select/readout/reset transistors and a photodiode. The organic photomemory transistor, comprising light-sensitive organic semiconductor and charge-trapping dielectric, is able to achieve a linear photoresponse (light intensity range, from 1 to 50 W m⁻²), along with a responsivity as high as 1.6 A W⁻¹ (wavelength = 465 nm) for a dark current of 0.24 A m⁻² (drain voltage = −1.5 V). These observed values represent the best responsivity for similar dark currents among all the reported hemispherical image sensor arrays to date. A transfer method was further developed that does not damage organic materials for hemispherical organic photomemory transistor arrays. These developed techniques are scalable and are amenable for other high-resolution 3D organic semiconductor devices.     

Study on the solidification cracking behaviour of high strength aluminum alloy welds: Effects of alloying elements and solidification behaviours

The solidification cracking susceptibility of the 7000 series Al-Zn-Mg high strength aluminum alloy has been studied. The cracking behaviour of the specimens were evaluated by a Tig-a-Ma-Jig Varestraint test process under various augmented strain conditions. It has been experimentally observed that the addition of copper decreased the solidification cracking resistivity of the high strength aluminum alloy weld metal by increasing the total crack length (TCL). The effect of the addition of manganese on the solidification cracking behaviour is found to be beneficial by markedly decreasing the solidification cracking susceptibility as the manganese content increases from 0.3 to 0.7%. This enhancement by manganese is understood to be attributed to the reduction of the mushy zone size during the solidification process. The effects of chromium and zirconium additions are also investigated. The weld metal containing zirconium is less sensitive to the solidification cracking than the weld metal containing chromium. In addition, the solidification behaviours of the tested alloys are also investigated and it is found that as the solidification temperature range (T) becomes narrow, the solidified structure becomes more dendritic in its features which is believed to create higher solidification cracking resistance.     

Development of a mobile robotic system for working in the double-hulled structure of a ship

Shipbuilding processes involve highly dangerous manual welding operations. Welding ship walls inside double-hulled structures presents a particularly hazardous environment for workers. This paper describes the “Rail Runner X” (RRX), a new robotic system that can move autonomously inside the walls of a double-hulled ship and automatically execute the required welding processes. The RRX robotic system is composed of a mobile platform and a welding robot consisting of a 3P3R serial manipulator. The robot is used to weld U-shaped trajectories located between two longitudinal stiffeners. The mobile platform enables traverse movements onto neighboring longitudinal stiffeners. The entire cross section of the robotic system is small enough to be placed inside the double-hulled structure via a conventional access hole from the outside shipyard floor. The overall engineering design process that led to the final robot solution developed is presented in this paper, including kinematic analysis data and experimental results for verifying the autonomous movement and welding performance.     

Underdetermined Convolutive Blind Source Separation via Time–Frequency Masking

In this paper, we consider the problem of separation of unknown number of sources from their underdetermined convolutive mixtures via time-frequency (TF) masking. We propose two algorithms, one for the estimation of the masks which are to be applied to the mixture in the TF domain for the separation of signals in the frequency domain, and the other for solving the permutation problem. The algorithm for mask estimation is based on the concept of angles in complex vector space. Unlike the previously reported methods, the algorithm does not require any estimation of the mixing matrix or the source positions for mask estimation. The algorithm clusters the mixture samples in the TF domain based on the Hermitian angle between the sample vector and a reference vector using the well known k -means or fuzzy c -means clustering algorithms. The membership functions so obtained from the clustering algorithms are directly used as the masks. The algorithm for solving the permutation problem clusters the estimated masks by using k-means clustering of small groups of nearby masks with overlap. The effectiveness of the algorithm in separating the sources, including collinear sources, from their underdetermined convolutive mixtures obtained in a real room environment, is demonstrated.     

Nanotextured superhydrophobic micromesh

A superhydrophobic micromesh covered with nanoprotrusions has been introduced and its applicability to a waterproof mobile phone speaker has been evaluated. The nanotextured superhydrophobic micromesh showed excellent water repellency, self-cleaning and waterproofing performances. In a waterproof speaker test using the fabricated nanotextured micromesh, the micromesh did not lose its waterproof function at 2 m water depth and did not form a remnant water film after being removed from the water. The packaged speaker showed almost the same sound quality before and after dipping at a 2 m water depth. These results demonstrate that the superhydrophobic nanotextured micromesh could be directly applicable for various products that need to resist water penetration, yet allow the transmission of gases and sound/light waves.     

Feature detection of triangular meshes based on tensor voting theory

This paper presents n-dimensional feature recognition of triangular meshes that can handle both geometric properties and additional attributes such as color information of a physical object. Our method is based on a tensor voting technique for classifying features and integrates a clustering and region growing methodology for segmenting a mesh into sub-patches. We classify a feature into a corner, a sharp edge and a face. Then, finally we detect features via region merging and cleaning processes. Our feature detection shows good performance with efficiency for various dimensional models.