We design flexible fault tolerant gate gadgets that allow the data and the ancilla to be encoded using different codes. By picking a stabilizer code for the ancilla we are able to perform both Clifford and non-Cliffor...
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In a recent paper, we defined twisted unitary 1-groups and showed that they automatically induced error-detecting quantum codes. We also showed that twisted unitary 1-groups correspond to irreducible products of chara...
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Worldwide cotton is the most profitable cash *** year the production of this crop suffers because of several *** an early stage,computerized methods are used for disease detection that may reduce the loss in the produ...
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Worldwide cotton is the most profitable cash *** year the production of this crop suffers because of several *** an early stage,computerized methods are used for disease detection that may reduce the loss in the production of *** several methods are proposed for the detection of cotton diseases,however,still there are limitations because of low-quality images,size,shape,variations in orientation,and complex *** to these factors,there is a need for novel methods for features extraction/selection for the accurate cotton disease *** in this research,an optimized features fusion-based model is proposed,in which two pre-trained architectures called EfficientNet-b0 and Inception-v3 are utilized to extract features,each model extracts the feature vector of length N×*** that,the extracted features are serially concatenated having a feature vector lengthN×*** prominent features are selected usingEmperor PenguinOptimizer(EPO)*** method is evaluated on two publically available datasets,such as Kaggle cotton disease dataset-I,and Kaggle *** EPO method returns the feature vector of length 1×755,and 1×824 using dataset-I,and dataset-II,*** classification is performed using 5,7,and 10 folds *** Quadratic Discriminant Analysis(QDA)classifier provides an accuracy of 98.9%on 5 fold,98.96%on 7 fold,and 99.07%on 10 fold using Kaggle cotton disease dataset-I while the Ensemble Subspace K Nearest Neighbor(KNN)provides 99.16%on 5 fold,98.99%on 7 fold,and 99.27%on 10 fold using Kaggle cotton-leaf-infection dataset-II.
E-commerce systems have integrated big data analytics (BDA) as a core element, enabling personalized shopping experiences, crucial for customer loyalty and satisfaction. This research explores how intentional use of d...
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We introduce twisted unitary t-groups, a generalization of unitary t-groups under a twisting by an irreducible representation. We then apply representation theoretic methods to the Knill-Laflamme error correction cond...
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We perform a complete classification of all 56 subgroups of the two-qubit Clifford group containing the two-qubit Pauli group. We provide generators for these groups using gates familiar to the quantuminformation com...
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We propose a network service as a solution for video conference applications by constructing network layer routing strategies. Our approach takes into account the characteristics of conferencing flows, addresses vario...
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Depression is a prevalent mental health issue affecting individuals of all age groups *** to other mental health disorders,diagnosing depression presents significant challenges for medical practitioners and clinical e...
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Depression is a prevalent mental health issue affecting individuals of all age groups *** to other mental health disorders,diagnosing depression presents significant challenges for medical practitioners and clinical experts,primarily due to societal stigma and a lack of awareness and *** medical interventions such as therapies,medications,and brain stimulation therapy provide hope for treatment,there is still a gap in the efficient detection of *** methods,like in-person therapies,are both time-consuming and labor-intensive,emphasizing the necessity for technological assistance,especially through Artificial *** to this,in most cases it has been diagnosed through questionnaire-based mental status ***,this method often produces inconsistent and inaccurate ***,there is currently a lack of a comprehensive diagnostic framework that could be effective achieving accurate and robust diagnostic *** a considerable time,researchers have sought methods to identify symptoms of depression through individuals’speech and responses,leveraging automation systems and computer *** research proposed MDD which composed of multimodal data collection,preprocessing,and feature extraction(utilizing the T5 model for text features and the WaveNet model for speech features).Canonical Correlation Analysis(CCA)is then used to create correlated projections of text and audio features,followed by feature fusion through ***,depression detection is performed using a neural network with a sigmoid output *** proposed model achieved remarkable performance,on the Distress Analysis Interview Corpus-Wizard(DAIC-WOZ)dataset,it attained an accuracy of 92.75%,precision of 92.05%,and recall of 92.22%.For the E-DAIC dataset,it achieved an accuracy of 91.74%,precision of 90.35%,and recall of 90.95%.Whereas,on CD-III dataset(Custom Dataset for Depression),the model demo
The industry is rapidly transitioning from the 4.0 era to the 5.0 era, prompting renewed interest among scholars in scheduling problems. They allow operations to process and assemble various components simultaneously....
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Free Space Optical (FSO) communication systems are used to transmit high data rates over short distances through the atmosphere. However, the performance of FSO communication links can be severely impacted by atmosphe...
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