This research is motivated by the incomplete use of quantum in existing learning algorithms, so that the proposed learning algorithm is not optimal. Research (Fahri & Neven, 2018) shows that the proposed method of...
This research is motivated by the incomplete use of quantum in existing learning algorithms, so that the proposed learning algorithm is not optimal. Research (Fahri & Neven, 2018) shows that the proposed method of architectural form still uses classical architecture but inputs, weights and targets already use a quantum approach. Based on the results of previous studies, it shows that quantum computing is better than classical computation. Many researchers use quantum computing in the proposed learning algorithm. The model proposed is a quantum circuit architecture with the quantum perceptron method consisting of a quantum bit gate that uses a quantum computational approach as the architecture of the quantum perceptron learning algorithm. Then the authors conduct training and testing of the proposed quantum circuit architecture to test the quantum circuit model that the author proposes. The result of this research is a quantum circuit model with the quantum perceptron method which can be used to solve the learning optimization problem by using a quantum circuit architecture with 5 measurement measurements to show error training and testing = 0, with 9 measurements showing an error training of 1.13%, error testing 2.06%.
The precise diagnosis of urinary stones is crucial for devising effective treatment strategies. The diagnostic process, however, is often complicated by the low contrast between stones and surrounding tissues, as well...
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Gurame Soang Latin name Osphronomus Labirynthici gouramy including fish, that as the fish have gills and breathing apparatus in the form of additional gills (Labyrinth). One important factor in fish farming Soang Gura...
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Cognitive diagnosis plays a crucial role in Intelligent Tutor Systems, which aims to diagnose learners' cognitive states according to learners' observable records, such as exercise records. However, this paper...
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The fractional differential equation Lβu = f posed on a compact metric graph is considered, where β > 0 and L = κ2 − ∇(a∇) is a second-order elliptic operator equipped with certain vertex conditions and sufficie...
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Data mining is an analytical process of knowledge discovery in large and complex data sets. Many studies wish to explore data, to find information so that knowledge can be obtained through the grouping process, classi...
Data mining is an analytical process of knowledge discovery in large and complex data sets. Many studies wish to explore data, to find information so that knowledge can be obtained through the grouping process, classification, rules discovery, associations and data mining visualization which shows similarity. Periodic data often occurs in business applications and sciences that has big size, high dimension and continuously updated. The similarity in periodic data is based on several approaches. One of common approaches is to transform periodic series into other domains so that dimensions are reduced, followed by index mechanism. Many studies of time series do not give optimal result because limited to extracting data not able to represent time series and its pattern which is then change into rules. Rules can be found in time series data, but they are still constrained by over fitting and difficult to present. It causes time series data and non linier function of data mining decision can't be optimal. The basic idea in the method proposed is to do periodic discretization for sub-sequential formation. These sub-sequences are grouped through a measure of similarity. The simple rule-finding technique is applied to obtain hidden rules in the temporal pattern. The optimal time series data expected to generate the uncertainty trend, previously unknown and can be used to make decisions or forecasting in the future.
In the modern power market, electricity trading is an extremely competitive industry. More accurate price forecast is crucial to help electricity producers and traders make better decisions. In this paper, a novel met...
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The aim purposed of this research is to evaluate clinical management information system called (E-CLINIC) which is integrated with the Primary Care (Pcare) application provided by Indonesia sosial healt insurance orga...
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The main treatment modality for oropharyngeal cancer (OPC) is radiotherapy, where accurate segmentation of the primary gross tumor volume (GTVp) is essential. However, accurate GTVp segmentation is challenging due to ...
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OBJECTIVEThis study aimed to develop and evaluate the effectiveness of a chatbot-based prototype model called SCIMORT, designed to improve the communication skills of undergraduate students in Diagnostic Imaging and R...
OBJECTIVEThis study aimed to develop and evaluate the effectiveness of a chatbot-based prototype model called SCIMORT, designed to improve the communication skills of undergraduate students in Diagnostic Imaging and Radiotherapy at Universiti Kebangsaan Malaysia. MATERIALS & METHODSThis pilot and survey study involved the development of the SCIMORT module, which included the creation of a 3D virtual patient with visual and auditory cues. The SCIMORT module was evaluated by surveying 28 participants from the PDR cohorts. The questionnaire was designed to assess user acceptance and engagement of SCIMORT, and the expert validation of the questionnaire was assessed using Content Validity Ratio and Cronbach Alpha Coefficient. RESULTSA total of 28 participants from the PDR cohorts were enrolled in these projects. In the first phase, the virtual patient developed for SCIMORT exhibited visual cues such as blinking and eye movement, as well as auditory cues, including verbal responses and intonation of voice. During the second phase, expert validation of the questionnaire yielded favourable RESULTS: , with a Content Validity Ratio exceeding 83% and a Cronbach Alpha Coefficient surpassing 70%. However, both the control group (users' acceptance = 3.919 ± 1.245; users' engagement = 3.526 ± 1.270) and the Trial group (users' acceptance = 3.953 ± 1.114; users' engagement = 3.568 ± 1.142) showed neutral outcomes. CONCLUSIONThe SCIMORT module proved to be an effective tool for pre-clinical learning of communication skills in radiotherapy. However, the control and the Trial groups exhibited neutral results regarding users' acceptance and engagement. Further improvements are needed to make the module more interactive and adaptable to student needs.
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