Analysis of Planning Risk Volume for Heart during Radiotherapy Delivery with Breath-Hold Technique for Carcinoma of Left Breast by Radhika Jain, Rose Kamal, Manoj K. Semwal, Deepak Thaper, Shefali Kanwar, Tripti Saxena

“…From the shift values, the systematic and random errors were estimated which were used to estimate PRV margin for the heart after incorporating the rotational errors with the translational errors. …”
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Toward reliable diabetes prediction: Innovations in data engineering and machine learning applications by Md. Alamin Talukder, Md. Manowarul Islam, Md Ashraf Uddin, Mohsin Kazi, Majdi Khalid, Arnisha Akhter, Mohammad Ali Moni

“…Methods In this paper, an effective data preprocessing pipeline has been implemented to process the data and random oversampling to balance the data, handling the imbalance distributions of the observational data more sophisticatedly. …”
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New image encryption algorithm based on double chaotic system and compressive sensing by Yuguang YANG, Guodong CAO

“…Image encryption technology plays an important role in today’s multimedia applications and Internet information security transmission.However, most image encryption algorithms still have problems, for example, cipher images occupied high bandwidth during transmission, image encryption speed is slow, image encryption algorithms are not associated with plain image, and there is no complete ciphertext feedback mechanism.These problems all affect the security and easy use of image encryption algorithms.In order to solve the above problems, the compressive sensing technology and chaotic system were studied, and a new image encryption algorithm based on double chaotic system and compressive sensing with plaintext association was proposed.The plaintext image association key was used to associate the plain image hash value with the Logistic chaotic system parameters.Discrete wavelet transform, was used to sparse the plain image.Then the random measurement matrix was generated by the Logistic chaos system, and the image was encrypted once by combining the compressive sensing technique and the random measurement matrix to obtain the intermediate image.The intermediate image was hashed again, and the Rucklidge chaos system initial value was associated with the plain image hash value together.The Rucklidge chaotic system and encryption algorithm were used to control the intermediate image for secondary encryption and accordingly obtain the cipher image.The encryption algorithm was a new plaintext correlation encryption algorithm, which used the image’s own pixel value to control the scrambling of the intermediate image.It also enhanced the plaintext association and established a ciphertext feedback mechanism.Simulation results and performance analysis show that the algorithm has good encryption performance.The encrypted image can be compressed according to the compression ratio, effectively reducing the size of the cipher image.Moreover, it is resistant to common attacks such as known plaintext attack, selective plaintext attack and differential attack, which is better than other common image encryption algorithms.…”
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Twitter Sentiment Analysis Towards Candidates of the 2024 Indonesian Presidential Election by Rhoma Cahyanti, Desiana Nurul Maftuhah, Aris Budi Santoso, Indra Budi

“…The result of the study also discovered that random forest and neural networks have the best performance for sentiment analysis.…”
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Structural reliability analysis of steel structural covering based on the theory of evidence by S. A. Solov’ev, A. E. In’kov, A. A. Solov’eva, V. A. Smirnov

“…In practical problems of assessment and analysis of structural reliability, data on random variables can be obtained in the interval form (qualitative uncertainty), while the classic methods of reliability analysis do not allow to estimate reliability in the presence of such data. …”
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Effects of yoga on depressive symptoms in women with pregnancy: A systematic review and meta-analysis by Sasinun Punsuwun, Sarah Oerther, Chuntana Reangsing

“…The overall effect size using random-effects model was g = 1.120 (95%CI .52, 1.72, p < .001). …”
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Energy Efficiency in Smart Buildings through Prediction modeling and Optimization Using a Modified Whale Optimization Algorithm by El Assri Nasima, Ennejjar Mohammed, Jallal Mohammed Ali, Chabaa Samira, Zeroual Abdelouhab

“…In the case of ANN, the Root Mean Squared Error (RMSE) is reported at 3.806, demonstrating the model's ability to approximate the true energy consumption values. Furthermore, the Random Forest model exhibits enhanced predictive accuracy, as reflected by a lower RMSE of 1.392. …”
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Uncertainty Quantification and Sensitivity Analysis of Concrete Structure Using Multi-Linear Regression Technique by Abdelhamid Hebbouche, Salim Bennoud, Ayoub Zeroual

“…However, it is necessary to take haphazard or random phenomena as crucial considerations when assessing the security of these structures or planning new ones. …”
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Optimizing hypertension prediction using ensemble learning approaches. by Isteaq Kabir Sifat, Md Kaderi Kibria

“…A multi-faceted feature selection approach was employed, incorporating Boruta, Lasso Regression, Forward and Backward Selection, and Random Forest feature importance, and found 13 common features that were considered for prediction. …”
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Penerapan MODEL SAS (Struktural Analitik Sintetik) Bahasa Kaili Da’a dalam Pembelajaran Baca dan Tulis KAT (Komunitas Adat Terpencil) Anak Suku Bunggu Dusun Salurayya by Intan Nurcahayani

“…Teknik pengumpulan data yang digunakan adalah cluster random sampling atau simple random sampling untuk menentukan kelas yang diberi perlakuan dan kelas yang tidak diberi perlakuan. …”
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Advancements in Predictive Analytics: Machine Learning Approaches to Estimating Length of Stay and Mortality in Sepsis by Houssem Ben Khalfallah, Mariem Jelassi, Jacques Demongeot, Narjès Bellamine Ben Saoud

“…After rigorous preprocessing to address missing data and ensure consistency, multiple classifiers, including Random Forest, Extra Trees, and Gradient Boosting, were trained and validated. …”
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Noise Reduction for Modal Parameter Identification of the Measured FRFs Using the Modal Peak-Based Hankel-SVD Method by Tianxu Zhu, Chaoping Zang, Gengbei Zhang

“…A simulation of the FRF of a flat plate artificially contaminated with the random Gaussian noise and the random harmonic noise is implemented to verify the proposed method. …”
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The Performance of Multiple Imputation in Social Surveys with Missing Data from Planned Missingness and Item Nonresponse by Julian B. Axenfeld, Christian Bruch, Christof Wolf, Annelies G. Blom

“…This entails a complex imputation task with amounts of missing data larger than initially planned and a potentially non-random, heterogeneous mechanism. Yet, it remains to be studied whether accurate multiple-imputation estimates can be obtained in practice with planned missingness and item nonresponse. …”
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Bifid Mandibular Canal: A Proportional Meta-Analysis of Computed Tomography Studies by Nyan Min Aung, Kyaw Kyaw Myint

“…Joanna Briggs Institute (JBI) critical appraisal tool for prevalence studies was used to assess methodological quality of all included studies. Random effect meta-analyses for proportion of bifid mandibular canal were done. …”
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Adaptive Bi-Directional RRT Algorithm for Three-Dimensional Path Planning of Unmanned Aerial Vehicles in Complex Environments by Nan Li, Sang Ik Han

“…This paper proposes an Adaptive Bi-directional Rapidly-exploring Random Tree (ABi-RRT) algorithm with the objective of addressing challenges in three-dimensional path planning of unmanned aerial vehicle (UAV) operating in complex environments. …”
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Design and Analysis of a Multiple and Wide Nulling Collaborative Beamforming Scheme in the Domain of 3-Dimensional Wireless Sensor Networks by Robert Macharia Maina, Philip Kibet Langat, Peter Kamita Kihato

“…A new multiple and wide null steering scheme applicable to CB in WSNs is presented in this work (from the perspective of a 3-dimensional random arrangement of static sensor nodes). It is assumed that desired nulling directions are implicitly known at a CB cluster head. …”
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AMEND 2.0: module identification and multi-omic data integration with multiplex-heterogeneous graphs by Samuel S. Boyd, Chad Slawson, Jeffrey A. Thompson

“…Results We present AMEND 2.0, an updated active module identification method which can analyze multiplex and/or heterogeneous networks integrated with multi-omic data in a highly generalizable framework, in contrast to existing methods, which are mostly appropriate for at most two specific omic types. It is powered by Random Walk with Restart for multiplex-heterogeneous networks, with additional capabilities including degree bias adjustment and biased random walk for multi-objective module identification. …”
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A meta-analysis of the effects of nitrogen fertilizer application on maize (Zea mays L.) yield in Northwest China by Yuanbo Jiang, Haiyan Li, Wenqiong Ma, Wenjing Yu, Junxian Chen, Yalin Gao, Guangping Qi, Minhua Yin, Yanxia Kang, Yanlin Ma, Jinghai Wang, Liting Xu

“…In this study, a meta-analysis was used to quantify the yield effects of nitrogen addition on maize, and meta-regression analysis and a random forest model were used to study the main factors affecting the yield effects of nitrogen addition on maize. …”
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A Hybrid Approach Integrating Multiple ICEEMDANs, WOA, and RVFL Networks for Economic and Financial Time Series Forecasting by Jiang Wu, Tengfei Zhou, Taiyong Li

“…First, we employ ICEEMDAN with random parameters to separate the original time series into a group of comparatively simple subseries multiple times. …”
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The application of machine learning approaches to classify and predict fertility rate in Ethiopia  by Ewunate Assaye Kassaw, Biruk Beletew Abate, Bekele Mulat Enyew, Ashenafi Kibret Sendekie

“…The best ML models to classify and predict fertility rates were random forest, one-dimensional convolutional neural network, logistic regression, and gradient boost classifier. …”
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