The Advances in Neuromorphic Computing and Brain-Inspired Systems (ANCBIS). by DanielRaj K, Ponseka G, Bharath Sanjai Lordwin D J3

“…Key technologies such as memristive devices, spiking neural networks, and brain-inspired learning algorithms show promise in applications like pattern recognition, sensory processing, and autonomous decision-making. …”
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O możliwości zredefiniowania niepowodzeń szkolnych. Rekonstrukcja zmiany myślenia studentek – przyszłych nauczycielek wczesnej edukacji by Grażyna Szyling

“…The results of the analyses show that the most significant modification concerns inclusion into the area of school failures also students commonly regarded as those „not having learning difficulties”, which extends the definition of this notion with the sense of “being insufficient” and leads to, inter alia, the relativisation of the term “bad grade”. …”
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Student Attitudes towards Guided Inquiry Approach Supported by Digital Stories by Merve Berika Kansoy, Ayse Sert-Cibik

“…It was revealed how the learning environment, teacher, student and lecturing affect the attitudes of the students participating in the studies towards inquiry…”
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Exploiting Interslice Correlation for MRI Prostate Image Segmentation, from Recursive Neural Networks Aspect by Qikui Zhu, Bo Du, Baris Turkbey, Peter Choyke, Pingkun Yan

“…In the past several years, approaches based on deep learning technology have made significant progress on prostate segmentation. …”
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Integrating ethics and democratic principles in chemistry education: a case study by Stojanovska Marina

“…Through reflective exercises and collaborative learning, pre-service teachers engage critically with the ethical implications of their future profession. …”
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Anomaly Detection for Aviation Safety Based on an Improved KPCA Algorithm by Xiaoyu Zhang, Jiusheng Chen, Quan Gan

“…In this paper, an improved kernel principal component analysis (KPCA) method is proposed to search for signatures of anomalies in flight datasets through the squared prediction error statistics, in which the number of principal components and the confidence for the confidence limit are automatically determined by OpenMP-based K-fold cross-validation algorithm and the parameter in the radial basis function (RBF) is optimized by GPU-based kernel learning method. Performed on Nvidia GeForce GTX 660, the computation of the proposed GPU-based RBF parameter is 112.9 times (average 82.6 times) faster than that of sequential CPU task execution. …”
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Software Design Challenges in Time Series Prediction Systems Using Parallel Implementation of Artificial Neural Networks by Narayanan Manikandan, Srinivasan Subha

“…For the last two decades, a large number of Artificial Neural Networks based learning models have been proposed to solve the problems of financial data and get accurate results in prediction of the future trends and prices. …”
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Teacher’s Readiness Toward Artificial Intelligence in The School of North Bali by M. Rokhman Purnama, I Putu Iwan Krisna Adnyana, Afrianto T.L Sogen, Gede Indrawan, Made Hery Santosa

“…In the future, in enabling AI to be used effectively to improve learning standards, government support needs to conduct specialized AI training at various school levels from urban to rural areas, in particular, stronger institutional support, and better school infrastructure and facilities to enhance teachers' readiness to face the digital revolution in education.…”
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Time perspective and significance of life events in adolescence by N. P. Shilova, A. K. Vladyko

“…For example, modern youth associate “learning at school” positively with entertainment and negatively with study and work in the past and with communication and contacts in the future. …”
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Chinese Unknown Word Recognition for PCFG-LA Parsing by Qiuping Huang, Liangye He, Derek F. Wong, Lidia S. Chao

“…In addition, a novel method, using graph-based semisupervised learning (SSL), is proposed to improve the syntax parsing of unknown words. …”
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A Bayesian Network Approach to Causation Analysis of Road Accidents Using Netica by Xin Zou, Wen Long Yue

“…By taking Adelaide Central Business District (CBD) in South Australia as a case, the Bayesian network structure was established by integrating K2 algorithm with experts’ knowledge, and Expectation-Maximization algorithm that could process missing data was adopted to conduct the parameter learning in Netica, thereby establishing the Bayesian network model for the causation analysis of road accidents. …”
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The efficiency of international relations of regional higher educational institutions in a globalised context by M.M. Chunayev

“…The conducted research, comparisons, and analyses facilitated the development of a comprehensive approach to learning theoretical concepts and models, which can be applied in teaching practices. …”
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Wavelet Denoising of Vehicle Platform Vibration Signal Based on Threshold Neural Network by Mingzhu Li, Zhiqian Wang, Jun Luo, Yusheng Liu, Sheng Cai

“…According to the characteristics of VPVS, a novel thresholding function is constructed, and then its optimized threshold is selected through unsupervised learning of TNN. The original VPVS mixed in trend and random noise is constructed as VPVS model. …”
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Development of PMRI Module in NTT Local Cultural Context to Improve Numeracy Literacy by Julindra Lesmana Baria, Agustin Fatmawati, Nia Kurniaty Rukman

“… This research aims to develop a PMRI-based learning module with the context of NTT to improve students' numeracy literacy. …”
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THE EFFECT OF VOCABULARY TOWARDS WRITING SKILL WITH READING SKILL AS MODERATING EFFECT by Paskalina Widiastuti Ratnaningsih, Catharina Clara

“…Hence, vocabulary is important in English language learning to support writing and reading. Regarding the importance of vocabulary, writing, and reading, the aim of this research is to test the effect of vocabulary mastery towards writing ability in English. …”
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CoTF-reg reveals cooperative transcription factors in oligodendrocyte gene regulation using single-cell multi-omics by Jerome J. Choi, John Svaren, Daifeng Wang

“…Next, we train a deep learning model to predict each TG expression using the co-binding TFs’ expressions. …”
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Multiobjective Prioritized Workflow Scheduling in Cloud Computing Using Cuckoo Search Algorithm by Babuli Sahu, Sangram Keshari Swain, Sudheer Mangalampalli, Satyasis Mishra

“…., Max–Min, first come first serve, minimum completion time, Min–Min, resource allocation security with efficient task scheduling in cloud computing-hybrid machine learning, and Round Robin. Our proposed approach is outperformed by minimizing energy consumption by 15% and reducing service level agreement violations by 22%.…”
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Comparing Project Complexity across Different Industry Sectors by Marian Bosch-Rekveldt, Hans Bakker, Marcel Hertogh

“…Further research could be focused on the subjective character of complexity as well as on the application of cross-sector learning, since this research does show similarities between large technical projects in different sectors.…”
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State Mode and Management Style: the Difficulties of Democratic Transformation by E. V. Okhotsky

“…In the result remain on top of the bureaucracy, the corruption, the brutality, the callousness and irresponsibility, and the bottom begins to dominate legal nihilism, distrust of authorities, double standards.Analyzing the distinguished types of styles, the author stops at the optimally-effective style performance focuses on the value of the benefits and ways of learning, introduces into scientific circulation the concept of “style of meanness and hypocrisy” – style, based on lies, double standards, fraud, provocations and corruption.This article presents some value judgments made appropriate generalizations and conclusions, analyzes the actions taken by a state in respect of establishing proper order in the system of public administration and public service. …”
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SPECTRUMNET: Cooperative Spectrum Monitoring Using Deep Neural Networks by M. Suriya, M. G. Sumithra

“…A deep neural network model for intelligent wireless signal identification to perform spectrum monitoring is proposed to perform efficient sensing at low SNR (signal to noise ratio) and preserve hyperspectral image features. A hybrid deep learning model called SPECTRUMNET (spectrum sensing using deep neural network) is presented. …”
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