Garbage prediction using regression analysis for municipal corporations of Indian cities by Raj Kumar Sharma, Manisha Jailia

“…To establish a connection between the variables, the descriptive study employs statistical techniques to learn about the composition of data collected from municipal corporations and conduct correlation analysis. …”
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Automated depression detection via cloud based EEG analysis with transfer learning and synchrosqueezed wavelet transform by Sara Bagherzadeh, Mohammad Reza Norouzi, Amirhesam Ghasri, Pouya Tolou Kouroshi, Sepideh Bahri Hampa, Fatemeh Farokhshad, Ahmad Shalbaf

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COMPARING FORECASTS OF AGRICULTURAL SECTOR EXPORT VALUES USING SARIMA AND LONG SHORT-TERM MEMORY MODELS by Aleytha Ilahnugrah Kurnadipare, Sri Amaliya, Khairil Anwar Notodiputro, Yenni Angraini, Laily Nissa Atul Mualifah

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ImmuProgML: machine learning-based dissection of cancer-immune dynamics during tumor progression to improve immunotherapy by Hanxiao Zhou, Lan Mei, Qianyi Lu, Yakun Zhang, Yue Sun, Caiyu Zhang, Han Jiang, Jiajun Zhou, Xia Li, Yunpeng Zhang, Shangwei Ning

“…Methods We developed ImmuProgML framework by integrating multi-omics data and dynamic network biomarker (DNB) analysis to identify key pathways and critical stages in cancer progression, tested in melanoma and non-small cell lung cancer (NSCLC). …”
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Dynamic Text Augmentation for Robust Sentiment Analysis: Enhancing Model Performance With EDA and Multi-Channel CNN by Komang Wahyu Trisna, Jinjie Huang, Yuanjian Chen, I Gede Juliana Eka Putra

“…The rapid growth of social media has revolutionized the way individuals share and access opinions, generating vast amounts of textual data containing diverse sentiments. Sentiment analysis enables organizations to derive valuable insights from this data, facilitating improved decision-making. …”
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Research on the Time Series Prediction of Acoustic Emission Parameters Based on the Factor Analysis–Particle Swarm Optimization Back Propagation Model by Xuebin Xie, Meng Wang

“…These ten parameters collectively affect the accuracy of AE monitoring. Factor analysis is employed to process the normalized AE data, simplifying the data structure and identifying common variables. …”
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Novel Deep Learning-Based Facial Forgery Detection for Effective Biometric Recognition by Hansoo Kim

“…The network employs a shallow architecture with wide feature maps to enhance efficiency and precision. …”
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Design of smart agriculture based on big data and Internet of things by Chunling Li, Ben Niu

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Deep learning driven prediction and comparative study of surrounding rock deformation in high speed railway tunnels by Zeping Yang, Zhikai Cheng, Da Wu

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The Degree-Constrained Adaptive Algorithm Based on the Data Aggregation Tree by Xiaogang Qi, Zhaohui Zhang, Lifang Liu, Mande Xie

“…There exists a defect that the energy of some nodes rapidly expires because the degrees of nodes differ significantly, and the delay time is not considered. Based on the above analysis, a new algorithm called DADAT (a Degree-based Adaptive algorithm for Data Aggregation Tree) is proposed. …”
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Prefetching Scheme for Massive Spatiotemporal Data in a Smart City by Lian Xiong, Zhengquan Xu, Hao Wang, Shan Jia, Li Zhu

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Potential protective factors against negative interpersonal influence regarding COVID-19 vaccination - A cross-sectional study on Covid-19 vaccine discussion networks by Fruzsina Albert, Mercédesz Gerdán, Beáta Dávid, Zoltán Brys

“…Binomial logistic Least Absolute Shrinkage and Selection Operator (LASSO) regression and average marginal effects (AMEs) were calculated.Our multivariate analysis identified four correlates of COVID-19 vaccination refusal: at least one influenza inoculation in the past, the ratio of vaccinated alters in COVID-19 vaccine discussion networks, health knowledge level and social-norm espousal. …”
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Evolution of deep learning tooth segmentation from CT/CBCT images: a systematic review and meta-analysis by Wai Ying Kot, Sum Yin Au Yeung, Yin Yan Leung, Pui Hang Leung, Wei-fa Yang

“…This systematic review and meta-analysis aims to evaluate the evolution and performance of deep learning in tooth segmentation. …”
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A Novel 3D Convolutional Neural Network-Based Deep Learning Model for Spatiotemporal Feature Mapping for Video Analysis: Feasibility Study for Gastrointestinal Endoscopic Video Cla... by Mrinal Kanti Dhar, Mou Deb, Poonguzhali Elangovan, Keerthy Gopalakrishnan, Divyanshi Sood, Avneet Kaur, Charmy Parikh, Swetha Rapolu, Gianeshwaree Alias Rachna Panjwani, Rabiah Aslam Ansari, Naghmeh Asadimanesh, Shiva Sankari Karuppiah, Scott A. Helgeson, Venkata S. Akshintala, Shivaram P. Arunachalam

“…To address data imbalance, 60 matched pairs of videos are randomly selected across 20 experimental runs. …”
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ACTIONS REGARDING INCREASING OF EFFICENCY OF ELECTRIC NETWORK by Gritsai M.

“…The retrospective analysis of losses of energy in the electrical network of several institutions of the Academy of Sciences of Moldova is executed. …”
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Towards interactive AI-authoring with prototypical few-shot classifiers in histopathology by Petr Kuritcyn, Rosalie Kletzander, Sophia Eisenberg, Thomas Wittenberg, Volker Bruns, Katja Evert, Felix Keil, Paul K. Ziegler, Katrin Bankov, Peter Wild, Markus Eckstein, Arndt Hartmann, Carol I. Geppert, Michaela Benz

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Data aggregation scheme based on SDN for internet of things by Bowei WANG, Jin TAN, Wenbin JIANG

“…There are many redundant parts in the data generated and transmitted by IoT devices.Transmitting this data reduces network lifetime and bandwidth.Aiming at the problem,the aggregation gateway layer was proposed,and a SDN-based IoT data aggregation architecture and algorithm were designed.The simulation analysis shows that compared with the architecture of the ordinary gateway and OF-GW,the network lifetime is improved by about 32.6%,and the amount of data packets sent by the sensing layer to the network layer is reduced by 6.1% to 55.1%.Compared with the LEACH algorithm,the designed rule algorithm reduces the average delay of data aggregation by about 24.1%,while avoiding data loss and improving the accuracy of data aggregation.…”
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Detection method of LDoS attacks based on combination of ANN ＆ KPCA by Zhijun WU, Liang LIU, Meng YUE

“…Low-rate denial-of-service (LDoS) attack is a new type of attack mode for TCP protocol.Characteristics of low average rate and strong concealment make it difficult for detection by traditional DoS detecting methods.According to characteristics of LDoS attacks,a new LDoS queue future was proposed from the router queue,the kernel principal component analysis (KPCA) method was combined with neural network,and a new method was present to detect LDoS attacks.The method reduced the dimensionality of queue feature via KPCA algorithm and made the reduced dimension data as the inputs of neural network.For the good sell-learning ability,BP neural network could generate a great LDoS attack classifier and this classifier was used to detect the attack.Experiment results show that the proposed approach has the characteristics of effectiveness and low algorithm complexity,which helps the design of high performance router.…”
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Adopting GIS to Enhance Alexandrian Urban Cultural Heritage: The Case of Alexandria, Egypt by Esraa Othman, Sarah Abdelghany, Tarek Farghaly

“…A four-stage framework was applied: (1) compiling a multi-source geodatabase of 294 heritage assets in addition to transport nodes; (2) digitising attributes for value scoring based on five National Organisation of Urban Harmony (NOUH) criteria; (3) conducting spatial analytics—hot-spot, nearest-neighbour, buffer, and network analysis—together with a six-parameter walkability index; and (4) translating findings into policy-relevant interventions and interactive web maps. …”
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Patch-Based Deep-Learning Model With Limited Training Dataset for Liver Tumor Segmentation in Contrast-Enhanced Hepatic Computed Tomography by Yuqiao Yang, Muneyuki Sato, Ze Jin, Kenji Suzuki

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