Letter to the Editor:Hardy–Weinberg equilibrium and association study of insertion/deletion polymorphism of ACE gene and Alzheimer’s disease in Egyptian patients

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Ontology-based decision tree model for prediction in a manufacturing network

This paper aims to create a predictive model, which will assist in the allocation of newly received orders in a manufacturing network. The manufacturing network, which is taken as a case study in this research, consists of more than 300 small manufacturing enterprises with a central company as the project managing integrator. The methodology presents the mapping of a PROSA (Product-Resource-Order-Staff Architecture) based ontology model on a decision tree, which was created with the Waikato Environment for Knowledge Analysis (WEKA) application. Furthermore, the methodology also demonstrates the formulation of the Semantic Web Rule Language (SWRL) rules from the WEKA decision tree with the help of MATLAB programming. The paper validated the result generated by the ontology model with the results of the decision tree model

Knowledge and agent-based system for decentralised scheduling in manufacturing

The aim of the research paper is to develop algorithms for manufacturers’ agents that would allow them to sequence their own operation plans and to develop a multi-agent infrastructure to allow operation pair agents to cooperatively adjust the timing of manufacturing operations. The scheduling problem consisted of jobs with fixed process plans and of manufacturers collectively offering the necessary operations for the jobs. Manufacturer agents sequenced and pair agents timed each operation as and when required. Timing an operation triggered a cascade of conflicts along the job process plan that other pair agents would pick up on and would take action accordingly. The conventional approach performs conflict resolution in series and manufacturer agents as well as pair agents wait until they are allowed to sequence and time the next operation. The limiting assumption behind that approach was systematically removed, and the proposed approach allowed manufacturers to perform operation scheduling in parallel, cutting down tenfold on the computation time. The multi-agent infrastructure consists of the Protégé knowledge base, the Pellet semantic reasoner and the Workflows and Agent Development Environment (WADE). The case studies used were the MT6, MT10 and LA19 job shop scheduling problems; and an industrial use case was provided to give context to the manufacturing environment investigated. Although there were benefits from the decentralised manufacturing system, we noted an optimality loss of 34% on the makespans. However, for scalability, our approach showed good promise

Towards decentralised job shop scheduling as a web service

This paper aims to investigate the fundamental requirements for a cloud-based scheduling service for manufacturing, notably manufacturer priority to scheduling service, resolution of schedule conflict, and error-proof data entry. A flow chart of an inference-based system for manufacturing scheduling is proposed and a prototype was designed using semantic web technologies. An adapted version of the Muth and Thompson 10 × 10 scheduling problem (MT10) was used as a case study and two manufacturing companies represented our use cases. Using Microsoft Project, levelled manufacturer operation plans were generated. Semantic rules were proposed for constraints calculation, scheduling and verification. Pellet semantic reasoner was used to apply those rules onto the case study. The results include two main findings. First, our system effectively detected conflicts when subjected to four types of disturbances. Secondly, suggestions of conflict resolutions were effective when implemented albeit they were not efficient. Consequently, our two hypotheses were accepted which gave merit for future works intended to develop scheduling as a web service. Future works will include three phases: (1) migration of our system to a graph database server, (2) a multi-agent system to automate conflict resolution and data entry, and (3) an optimisation mechanism for manufacturer prioritisation to scheduling services

Nonpolar GaN-Based VCSELs with Lattice-Matched Nanoporous Distributed Bragg Reflector Mirrors

Wide-bandgap optoelectronic devices have undergone significant advancements with the advent of commercial light-emitting diodes and edge-emitting lasers in the violet-blue spectral region. They are now ubiquitous in several lighting, communication, data storage, display, and sensing applications. Among the III-nitride emitters, vertical-cavity surface-emitting lasers (VCSELs) have attracted significant attention in recent years due to their inherent advantages over edge-emitting lasers. The small active volume enables single-mode operation with low threshold currents and high modulation bandwidths. Their surface-normal device geometry is conducive to the cost-effective formation of high-density 2D arrays while simplifying on-chip wafer testing. Furthermore, the low beam divergence and circular beam profiles in VCSELs allow efficient fiber coupling. Nevertheless, GaN-based VCSELs are still in the early stages of development. Several challenges need to be addressed before high-performance devices can be commercially realized. One such challenge is the lack of high-quality distributed Bragg reflector (DBR) mirrors. Conventionally, epitaxial and dielectric DBRs are used which often involve complex growth and fabrication techniques. This dissertation provides an alternative approach where subwavelength air-voids (nanopores) are introduced in alternating layers of doped/undoped GaN to form the DBR structure. Selective electrochemical etching creates nanopores in the doped layers, reducing the effective refractive index relative to the surrounding undoped GaN. Using only 16-pairs, DBR reflectance \u3e99.9% could be achieved. Several research groups have shown optically pumped VCSELs using nanoporous DBRs on c-plane. However, there are no reports of electrically injected nanoporous VCSELs. Using m-plane GaN substrates, we have demonstrated the first ever electrically injected GaN-based VCSEL using a lattice-matched nanoporous DBR. The nonpolar m-plane orientation is beneficial for leveraging the higher per-pass gain and polarization-pinning properties absent in c-plane. Lasing under pulsed operation at room temperature was observed at 409 nm with a linewidth of ~0.6 nm and a maximum output power of ~1.5 mW. This is the highest output power from m-plane VCSELs to date with relatively stable operation at elevated temperatures. All tested devices were linearly polarization-pinned in the a-direction with high polarization ratios \u3e0.9. Overall, the nanoporous DBRs help in mitigating some of the issues that limit the performance of III-nitride VCSELs