PENGGUNAAN MIND MAP DALAM MATA KULIAH ANATOMI FISIOLOGI MANUSIA SEBAGAI INTEGRASI BERBAGAI KONSEP UNTUK MENINGKATKAN HASIL BELAJAR MAHASISWA TA 2014/2015 by Nurkhairo Hidayati

“…Signs or symbols that are used as well as color influence strengthening student understanding and memory. Each concept can be expressed with one word idea and visualized with a symbol or image. …”
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Exploiting Small Leakages in Masks to Turn a Second-Order Attack into a First-Order Attack and Improved Rotating Substitution Box Masking with Linear Code Cosets by Alexander DeTrano, Naghmeh Karimi, Ramesh Karri, Xiaofei Guo, Claude Carlet, Sylvain Guilley

“…We propose an attack targeting precomputed S-Boxes stored in nonvolatile memory. Our attack targets AES implemented in software protected by a low entropy masking scheme and recovers the masks with 91% success rate. …”
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Older Primary Care Patients’ Attitudes and Willingness to Screen for Dementia by Nicole R. Fowler, Anthony J. Perkins, Hilary A. Turchan, Amie Frame, Patrick Monahan, Sujuan Gao, Malaz A. Boustani

“…Eligible patients completed the Perceptions Regarding Investigational Screening for Memory in Primary Care (PRISM-PC) questionnaire and then were asked to undergo dementia screening by a telephone screening instrument. …”
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Data Imputation for Detected Traffic Volume of Freeway Using Regression of Multilayer Perceptron by Xiang Wang, Yingying Ma, Shengwen Huang, Yu Xu

“…A multilayer perceptron-multivariate imputation of chain equation (MLP-MICE) regression imputation method optimized by the limit-memory-BFGS algorithm is proposed, considering the temporal and spatial characteristics of traffic volume. …”
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Evaluation of Spatial and Temporal Performance of Deep Learning Models for Travel Demand Forecasting: Application to Bike-Sharing Demand Forecasting by Jaehyung Lee, Jinhee Kim

“…The results showed that the model with convolutional long short-term memory layers, which are effective at predicting spatiotemporal data, outperformed the other models in terms of aggregated performance. …”
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Deep Learning in Music Generation: A Comprehensive Investigation of Models, Challenges and Future Directions by Kong Xiangchen

“…This review explores various and recent deep learning models, such as Long Short-Term Memory (LSTM) networks, Transformer-based models, Reinforcement Learning (RL), and Diffusion-based architectures, and how they are applied to music generation. …”
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Reappraising double pendulum dynamics across multiple computational platforms by Sandy Herho, Faiz Fajary, Katarina Herho, Iwan Anwar, Rusmawan Suwarman, Dasapta Irawan

“…These were solved numerically using the efficient Runge-Kutta-Fehlberg method, implemented in Python, R, GNU Octave, and Julia, while runtimes and memory usage were extensively benchmarked across these environments. …”
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Therapeutic Potential of 5-HT2C Receptor Ligands by Nanna H. Jensen, Thomas I. Cremers, Florence Sotty

“…A large body of evidence supports a critical role of serotonin 2C receptors in mediating the interaction between serotonergic and dopaminergic systems, which is at the basis of their proposed involvement in the regulation of mood, affective behavior, and memory. In addition, their expression in specific neuronal populations in the hypothalamus would be critical for their role in the regulation of feeding behavior. …”
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Astrocyte and Neuronal Plasticity in the Somatosensory System by Robert E. Sims, John B. Butcher, H. Rheinallt Parri, Stanislaw Glazewski

“…This is thought to underlie learning and memory processes and so adaptation to a changing environment. …”
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A Case of Persistent Generalized Retrograde Autobiographical Amnesia Subsequent to the Great East Japan Earthquake in 2011 by Yuji Odagaki

“…He lost all information about his personal identity, and his memory was wholly lost until the disaster on 11 March 2011. …”
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Probabilistic Automated Model Compression via Representation Mutual Information Optimization by Wenjie Nie, Shengchuan Zhang, Xiawu Zheng

“…Deep neural networks, despite their remarkable success in computer vision tasks, often face deployment challenges due to high computational demands and memory usage. Addressing this, we introduce a probabilistic framework for automated model compression (Prob-AMC) that optimizes pruning, quantization, and knowledge distillation simultaneously using information theory. …”
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Enhancing environmental monitoring of harmful algal blooms with ConvLSTM image prediction by Sung Jae Kim, Yongbok Cho

“…These interpolated images are then used as input for a ConvLSTM (Convolutional Long Short-Term Memory) network, which integrates convolutional layers to capture spatial patterns and LSTM units to model temporal dependencies. …”
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Method of Evaluating and Predicting Traffic State of Highway Network Based on Deep Learning by Jiayu Liu, Xingju Wang, Yanting Li, Xuejian Kang, Lu Gao

“…Based on the deep learning theory, this paper proposes an evaluation and prediction model of highway network traffic state, which consists of a Fuzzy C-means (FCM) algorithm-based traffic state partition model, a Long Short-Term Memory (LSTM) algorithm-based traffic state prediction model, and a K-Means algorithm-based traffic state discriminant model. …”
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Specificity of Cognitive Impairment in Neurological Disease: A Methodological Critique of Parkinson’s Disease by H. J. Sagar

“…Sometimes, a relationship has been established between certain cognitive deficits and particular neurochemical deficits which has led to the notion of specific drug treatment, e.g. cholinergic deficits and memory failure in Alzheimer's disease. However, these conclusions are often potentially flawed by methodological inadequacies. …”
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Bile Acids and Their Value for Central Nervous System by Yu. O. Shulpekova, P. E. Tkachenko, E. N. Shirokova, I. V. Damulin

“…Clinical and experimental works are conclusive about the CNS bile acids influence on mitochondrial membrane, their antioxidative role and, probably, steroid-mediator involvement in indirect regulation of memory, attention, motor functions and appetite.Conclusion. …”
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Quasiprobabilistic Readout Correction of Midcircuit Measurements for Adaptive Feedback via Measurement Randomized Compiling by Akel Hashim, Arnaud Carignan-Dugas, Larry Chen, Christian Jünger, Neelay Fruitwala, Yilun Xu, Gang Huang, Joel J. Wallman, Irfan Siddiqi

“…Moreover, we show that this method can be extended to midcircuit measurements used for active feedback via quasiprobabilistic error cancellation, and we demonstrate the correction of measurement errors on an ancilla qubit used to detect and actively correct bit-flip errors on an entangled memory qubit. Our approach enables the correction of readout errors on large numbers of qubits and offers a strategy for correcting readout errors in adaptive circuits in which the results of midcircuit measurements are used to perform conditional operations on nonlocal qubits in real time.…”
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Reconfigurable group delay with tunable topological edge state based on phase transitions material Ge2Sb2Te5 in dual-band by Yao Lu, Qiaohong Yao, Mengdong He, Jiao Xu, Yuxiang Peng

“…The reconfigurable reflected group delay in dual-band presented in this paper has the potential to be used in high-efficiency memory for optical pulses and optical delay lines.…”
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SYSTEMIC GENERATION OF SOLVING NECESSARY PROFESSIONAL THE TASKS by Vladimir M. Nesterenko

“…Subsequently, the subject of action will be enough only to compare the new information, a new internal image created on the basis of transmitted information from a previously created and stored in the memory of the parametric network, taking into account the novelty and make a decision. …”
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Scalable data assimilation with message passing by Oscar Key, So Takao, Daniel Giles, Marc Peter Deisenroth

“…In combination with a GPU-accelerated implementation, we can scale the algorithm to very large grid sizes while retaining good accuracy and compute and memory requirements.…”
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REAL-TIME KERNEL FUNCTION SYNTHESIS FOR SOFTWAREDEFINED RADIO AND PHASE-FREQUENCY MEASURING DIGITAL SYSTEMS by I. E. Tarasov, D. S. Potekhin

“…The proposed hardware generator has a feature allowing to create high-order kernel functions, which is impossible with the approach based on storing coefficients in on-chip memory limited in size. An analysis performed in the article allows calculating a set of integration limits and corresponding damping coefficients for Gaussian modulating function. …”
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