Quantum state-preparation control in noisy environment via most-likely paths

Finding optimal controls for open quantum systems needs to take into account effects from unwanted environmental noise. Since actual realizations or states of the noise are typically unknown, the usual treatment for the quantum system's decoherence dynamics is via the Lindblad master equation, which in essence describes an average evolution (mean path) of the system's state affected by the unknown noise. We here consider an alternative view of a noise-affected open quantum system, where the average dynamics can be unravelled into hypothetical noisy quantum trajectories, and propose a new control strategy for the state-preparation problem based on the likelihood of noise occurrence. We adopt the most-likely path technique for quantum state-preparation, constructing a stochastic path integral for noise variables and finding control functions associated with the most-likely noise to achieve target states. As a proof of concept, we apply the method to a qubit-state preparation under a dephasing noise and analytically solve for controlled Rabi drives for arbitrary target states. Since the method is constructed based on the probability of noise, we also introduce a fidelity success rate as a new measure of the state preparation and benchmark our most-likely path controls against the existing mean-path approaches.Comment: 20 pages, 8 figure

การพัฒนารูปแบบการดูแลประคับประคองแบบมีส่วนร่วม The Development of A Participatory Palliative Care Model

บทคัดย่อ วัตถุประสงค์: เพื่อพัฒนาและทดสอบรูปแบบการดูแลประคับประคองแบบมีส่วนร่วมต่อสมรรถนะพยาบาลวิชาชีพในโรงพยาบาลส่งเสริมสุขภาพตำบล วิธีการศึกษา: การศึกษามี 3 ระยะ ระยะที่ 1 วิเคราะห์สถานการณ์ บริบทของชุมชน และประเมินความต้องการพัฒนา ระยะที่ 2 กำหนดเป้าหมาย แก้ปัญหา การตัดสินใจ การเปลี่ยนแปลง การยอมรับ ความผูกพัน และความรับผิดชอบ โดยใช้แนวคิดการมีส่วนร่วม ร่วมกับพัฒนาสมรรถนะพยาบาลตาม Co2HoPE Model และสร้างแนวทางการดูแลผู้ป่วยประคับประคองในชุมชน ระยะที่ 3 ดำเนินการเยี่ยมบ้านและประเมินผลการดำเนินงาน คัดเลือกตัวอย่างแบบเจาะจงเป็นพยาบาลวิชาชีพในโรงพยาบาลส่งเสริมสุขภาพตำบลในเขต อ.เมือง จ.ลพบุรี 17 แห่ง 24 คน และผู้ป่วยโรคมะเร็งแบบประคับประคองในชุมชน อ.เมืองลพบุรี 10 คน ทดสอบพยาบาลด้วยแบบประเมินสมรรถนะการดูแลแบบประคับประคองก่อนและหลังการเยี่ยมบ้าน และประเมินความพึงพอใจของผู้ป่วยต่อการดูแลแบบประคับประคอง เปรียบเทียบคะแนนสมรรถนะก่อนและหลังการดูแลผู้ป่วย ผลการศึกษา: รูปแบบประกอบด้วย ระบบการส่งต่อแบบไร้รอยต่อ การพัฒนาสมรรถนะพยาบาลแบบประคองในชุมชน การดูแลแบบมีส่วนร่วม การแบ่งปันอุปกรณ์ และระบบเครือข่ายการดูแล คะแนนสมรรถนะของพยาบาลเพิ่มจาก 127.29 เป็น 176.88 คะแนน ซึ่งแตกต่างอย่างมีนัยสำคัญทางสถิติ (P-value < 0.05) พบความพึงพอใจของผู้ป่วยและผู้ดูแลระดับมากที่สุด สรุป: การดูแลประคับประคองแบบมีส่วนร่วมที่พัฒนาขึ้นทำให้สมรรถนะของพยาบาลสูงขึ้นและผู้ป่วยและผู้ดูแลมีความพึงพอใจในระดับมากที่สุด    คำสำคัญ: พัฒนารูปแบบ; การดูแลแบบประคับประคอง; การมีส่วนร่วม; คนไข้มะเร็ง; สมรรถนะ; พยาบาล   Abstract Objective: To develop and test the participatory palliative care model for nurses in sub-district health promoting hospitals. Method: Of the 3 study phases, phase 1 consisted of situational analysis, community context and needs for development. Phase 2 consisted of goal setting, problem solving, decision making, changes, acceptance, bond and responsibility using participation concept with the nurse competency development Co2HoPE Model. The guideline was and model was developed. In phase 3, the home care was carried out and evaluated. Twenty-four nurses from sub-district health promoting hospitals and 10 patients/care givers in Muang district, Lopburi province, Thailand were purposively selected. Nurses were tested for competency in palliative care before and after delivering home care. Patients/care givers were asked for satisfaction toward palliative care. Scores of nurse’s competency were compared. Results: The participatory palliative care consisted of 5 components namely seamless referral system, development of nurse’s competency in community palliative care, participatory care, device sharing, and care network. Score of nurse’s competences after the care (176.88 points) was significantly higher than that before the care (127.29 points) (P-value < 0.05). Satisfaction was at the highest level. Conclusion: The developed participatory palliative care for cancer patients improved nurse’s competency and satisfied the patients/care givers.   Keywords: model development; palliative care; participatory care, cancer patients, competency; nurse

Parallel KNN and Neighborhood Classification Implementations on GPU for Network Intrusion Detection

With a rapid growth of Internet community making a practical usage of numbers of application used in many areas, i.e., research, commercial, industry, and even in military, there are millions of reports on attacks and attempts to invade the system online; and that phenomenon has led the essential of intrusion detection system (IDS). Data mining is one of the promising approaches to deal with large scale dataset including attack detection and recognition based on attack traces as an example from KDD CUP 1999. However, one of its key limitations is the computational complexity, and thus, this research investigates the possibility to integrate parallel processing to enhance the detection speed-up implemented on NVIDIA CUDA GPU. Several proposals have focused on kNearest Neighbour (KNN) as one of the promising approaches due to its key advantage of simplicity and high precision; however, in addition to KNN evaluation, this research also proposes the integration of a simplified neighborhood classification (Neighborhood) using the percentage instead of group ranking resulting in higher accuracy gain with insignificantly increase of computational complexity trade-off

Maximum power point tracking of a small-scale compressed air energy storage system

The thesis is concerned with a small-scale compressed air energy storage (SS-CAES) system. Although these systems have relatively low energy density, they offer advantages of low environmental impact and ease of maintenance.The thesis focuses on solving a number of commonly known problems related to the perturb and observe (P&O) maximum power point tracking (MPPT) system for SS-CAES, including confusion under input power fluctuation conditions and operating point dither.A test rig was designed and built to be used for validation of the theoretical work. The rig comprised an air motor driving a permanent magnet DC generator whose power output is controlled by a buck converter. A speed control system was designed and implemented using a dSPACE controller. This enabled fast convergence of MPPT.Four MPPT systems were investigated. In the first system, the air motor characteristics were used to determine the operating speed corresponding to MPP for a given pressure. This was compared to a maximum efficiency point tracking (MEPT) system. Operating at the maximum power point resulted in 1% loss of efficiency compared to operating at the maximum efficiency point. But MPPT does not require an accurate model of the system that is needed for MEPT, which also requires more sensors.The second system that was investigated uses a hybrid MPPT approach that did not require a prior knowledge system model. It used the rate of change of power output with respect to the duty cycle of the buck converter as well as the change in duty cycle to avoid confusion under input power fluctuations. It also used a fine speed step in the vicinity of the MPP and a coarse speed step when the operating point was far from the MPP. Both simulation and experimental results demonstrate the efficiency of this proposed system.The third P&O MPPT system used a fuzzy logic approach which avoided confusion and eliminated operating point dither. This system was also implemented experimentally.A speed control system improved the controllable speed-range by using a buck-boost converter instead. The last MPPT system employed a hybrid P&O and incremental inductance (INC) approach to avoid confusion and eliminate operating point dither. The simulation results validate the design.Although the focus of the work is on SS-CAES, the results are generic in nature and could be applied to MPPT of other systems such as PV and wind turbine

Adapting Fleming-Type Learning Style Classifications to Deaf Student Behavior

This study presents the development of a novel integrated data fusion and assimilation technique to classify learning experiences and patterns among deaf students using Fleming’s model together with Thai Sign Language. Data were collected from students with hearing disabilities (Grades 7–9) studying at special schools in Khon Kaen and Udon Thani, Thailand. This research used six classification algorithms with data being resynthesized and improved via the application of feature selection, and the imbalanced data corrected using the synthetic minority oversampling technique. The collection of data from deaf students was evaluated using a 10-fold validation. This revealed that the multi-layer perceptron algorithm yields the highest accuracy. These research results are intended for application in further studies involving imbalanced data problems

E-Learning Model to Identify the Learning Styles of Hearing-Impaired Students

Deaf students apparently experience hardship in conventional learning; however, despite their inability to hear, nothing can stop them from reading. Although they perform impressively in memorizing the information, their literacy and reading capability still appear to be weak since they lack the chance to revise by listening and practicing repetitively. Currently, the teaching media for deaf students are quite rare and inadequate, forcing them to face difficulties in integrating new knowledge, even though most of the contents are in a form of written, printed, downloaded, or even accessible via an e-learning platform. However, it is crucial to bear in mind that each learner is different. There is evidence showing that some learners prefer particular methods of learning, also known as learning preferences or learning styles. Thus, the present study reports the sequence of learning styles obtained by using a modified VRK + TSL model that categorized students based on their learning styles. We also propose four different ways of teaching using content-adaptive learning styles, namely visual, reading/writing, kinesthetic, and Thai sign language. Based on personal preferences and the principle of universal design under synthesized learning, an e-learning model was developed to identify deaf learners’ learning styles. The objective is to provide e-learning to identify the learning styles of hearing-impaired students and to respond with up-to-date e-learning materials that can be used anywhere and at any time. These materials must support the education of deaf students. As a result, learners have increased efficiency and increased learning outcomes

E-Learning Model to Identify the Learning Styles of Hearing-Impaired Students

Deaf students apparently experience hardship in conventional learning; however, despite their inability to hear, nothing can stop them from reading. Although they perform impressively in memorizing the information, their literacy and reading capability still appear to be weak since they lack the chance to revise by listening and practicing repetitively. Currently, the teaching media for deaf students are quite rare and inadequate, forcing them to face difficulties in integrating new knowledge, even though most of the contents are in a form of written, printed, downloaded, or even accessible via an e-learning platform. However, it is crucial to bear in mind that each learner is different. There is evidence showing that some learners prefer particular methods of learning, also known as learning preferences or learning styles. Thus, the present study reports the sequence of learning styles obtained by using a modified VRK + TSL model that categorized students based on their learning styles. We also propose four different ways of teaching using content-adaptive learning styles, namely visual, reading/writing, kinesthetic, and Thai sign language. Based on personal preferences and the principle of universal design under synthesized learning, an e-learning model was developed to identify deaf learners’ learning styles. The objective is to provide e-learning to identify the learning styles of hearing-impaired students and to respond with up-to-date e-learning materials that can be used anywhere and at any time. These materials must support the education of deaf students. As a result, learners have increased efficiency and increased learning outcomes

A New Deep Learning Model for the Classification of Poisonous and Edible Mushrooms Based on Improved AlexNet Convolutional Neural Network

The difficulty involved in distinguishing between edible and poisonous mushrooms stems from their similar appearances. In this study, we attempted to classify five common species of poisonous and edible mushrooms found in Thailand, Inocybe rimosa, Amanita phalloides, Amanita citrina, Russula delica, and Phaeogyroporus portentosus, using the convolutional neural network (CNN) and region convolutional neural network (R-CNN). This study was motivated by the yearly death toll from eating poisonous mushrooms in Thailand. In this research, a method for the classification of edible and poisonous mushrooms was proposed and the testing time and accuracy of three pretrained models, AlexNet, ResNet-50, and GoogLeNet, were compared. The proposed model was found to reduce the duration required for training and testing while retaining a high level of accuracy. In the mushroom classification experiments using CNN and R-CNN, the proposed model demonstrated accuracy levels of 98.50% and 95.50%, respectively