Perturbation Theory Based on Darboux Transformation on One-Dimensional Dirac Equation in Quantum Computation

We present the recent works \cite{trisetyarso2011} on the application of Darboux transformation on one-dimensional Dirac equation related to the field of Quantum Information and Computation (QIC). The representation of physical system in one-dimensional equation and its transformation due to the Bagrov, Baldiotti, Gitman, and Shamshutdinova (BBGS)-Darboux transformation showing the possibility admitting the concept of relativity and the trade-off of concurrent condition of quantum and classical physics play into the area of QIC. The applications in cavity quantum electrodynamics and on the proposal of quantum transistor are presented.Comment: 2 pages, 3 figures Information and Communication Technology (ICoICT), 201

Dirac four-potential tunings-based quantum transistor utilizing the Lorentz force

We propose a mathematical model of \textit{quantum} transistor in which bandgap engineering corresponds to the tuning of Dirac potential in the complex four-vector form. The transistor consists of $n$-relativistic spin qubits moving in \textit{classical} external electromagnetic fields. It is shown that the tuning of the direction of the external electromagnetic fields generates perturbation on the potential temporally and spatially, determining the type of quantum logic gates. The theory underlying of this scheme is on the proposal of the intertwining operator for Darboux transfomations on one-dimensional Dirac equation amalgamating the \textit{vector-quantum gates duality} of Pauli matrices. Simultaneous transformation of qubit and energy can be accomplished by setting the $\{\textit{control, cyclic}\}$-operators attached on the coupling between one-qubit quantum gate: the chose of \textit{cyclic}-operator swaps the qubit and energy simultaneously, while \textit{control}-operator ensures the energy conservation.Comment: 23 pages, 10 figures: Typo corrections. A new Subsection with massless Dirac-fermions in a uniform magnetic field is include

Confidence of AOI-HEP Mining Pattern

Attribute Oriented Induction High level Emerging Pattern (AOI-HEP) has been proven can mine frequent and similar patterns and the finding AOI-HEP patterns will be underlined with confidence mining pattern for each AOI-HEP pattern either frequent or similar pattern, and each dataset as confidence AOI-HEP pattern between frequent and similar patterns. Confidence per AOI-HEP pattern will show how interested each of AOI-HEP pattern, whilst confidende per dataset will show how interested each dataset between frequent and similar patterns. The experiments for finding confidence of each AOI-HEP pattern showed that AOI-HEP pattern with growthrate under and above 1 will be recognized as uninterested and interested AOI-HEP mining pattern since having confidence AOI-HEP mining pattern under and above 50% respectively. Furthermore, the uniterested AOI-HEP mining pattern which usually found in AOI-HEP similar pattern, can be switched to interested AOI-HEP mining pattern by switching their support positive and negative value scores

Machine learning in drug supply chain management during disease outbreaks: a systematic review

The drug supply chain is inherently complex. The challenge is not only the number of stakeholders and the supply chain from producers to users but also production and demand gaps. Downstream, drug demand is related to the type of disease outbreak. This study identifies the correlation between drug supply chain management and the use of predictive parameters in research on the spread of disease, especially with machine learning methods in the last five years. Using the Publish or Perish 8 application, there are 71 articles that meet the inclusion criteria and keyword search requirements according to Kitchenham's systematic review methodology. The findings can be grouped into three broad groupings of disease outbreaks, each of which uses machine learning algorithms to predict the spread of disease outbreaks. The use of parameters for prediction with machine learning has a correlation with drug supply management in the coronavirus disease case. The area of drug supply risk management has not been heavily involved in the prediction of disease outbreaks

Design considerations of RFID based baggage handling system, a literature review

, Harjanto Prabowo, Agung Trisetyarso, Meyliana, Achmad Nizar Hidayanto 2nd International Conference on Information Management and Technology, ICIMTech 2017 Yogyakarta; Indonesia 15 - 17 November 2017 978-153862930-