Anonymous Authentication and Key Agreement Scheme Combining the Group Key for Vehicular Ad Hoc Networks by Mei Sun, Yuyan Guo, Dongbing Zhang, MingMing Jiang

“…Many existing schemes suffer from high computational cost by using bilinear pairing operation or need the assistance of the trust authorities (TAs) during the authentication process or rely on an ideal tamper-proof device (TPD), which requires very strong security assumption. …”
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Music as a (Science as a) Liberal Art at Princeton by Aaron Girard

“…The literature on this subject has suffered from several flaws: an over-emphasis on Milton Babbitt at the expense of his colleagues; a conflation of distinct paradigms of scientific research; a near-total absence of documentary research; and a disquieting elision of the polemical with the historiographical. …”
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Effectiveness of health promotion utilizing word puzzle games in enhancing older adults' knowledge and attitudes regarding hypertension management by Mia Fatma Ekasari, Aan Nurhasanah, Eros Siti Suryati, Puspita Hanggit Lestari, Siti Badriah, Ahmad Jubaedi

“…However, the result has not shown an optimal reduction in the number of hypertension sufferers. An effective health promotion, such as word puzzle games, needs to be developed. …”
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Perception of Gender Issues among Surgical Residents and their Supervisors by Syed Inamullah Shah, Muzna Iftikhar, Sajida Shah, Muhammad Salman Shafique, Mahvish Noor, Jamil Ahmad Shah

“…Conclusion: Gender is not felt as a discriminatory factor by residents during training. Female residents suffer during training due to family obligations, pregnancy and parenthood. …”
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Dynamic Peak Threshold Estimation Method for Noise Mitigation in Hybrid PLC/VLC Systems by Irvine Mapfumo, Thokozani Shongwe

“…Most communication systems suffer from signal distortions as a result of noise interference. …”
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Purinergic Receptors in Ocular Inflammation by Ana Guzman-Aranguez, Xavier Gasull, Yolanda Diebold, Jesús Pintor

“…In summary, adenosine and nucleotides can activate receptors in ocular structures susceptible to suffer from inflammatory processes. This involvement suggests the possible use of purinergic agonists and antagonists as therapeutic targets for ocular inflammation.…”
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Characterization of patients with clinical suspicion of dengue and warning signs. Pediatric Hospital. Cienfuegos, 2019 by Delfín Rodríguez Buergo, Hilda María Delgado Acosta, Diana Rosa Rodríguez Delgado, Roxana Gutiérrez Morán, Lisset María Martínez González

“…<br /><strong>Results</strong>: female sex and preschool ages predominated, as well as normal weight (95.1%). 26.8% suffered from chronic diseases. Patients admitted more than 48 hours after the beginning of symptoms predominated. …”
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Energy Efficiency Analysis of Antenna Selection Techniques in Massive MIMO-OFDM System with Hardware Impairments by Anuj Singal, Deepak Kedia

“…However, as the hardware degradation effect increases, the EE of the bulk antenna selection scheme suffers more degradation as compared to the Per-subcarrier antenna selection scheme. …”
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An Enhanced Slime Mould Algorithm and Its Application for Digital IIR Filter Design by Xiaodan Liang, Dong Wu, Yang Liu, Maowei He, Liling Sun

“…It can effectively obtain a promising global optimal solution. However, it still suffers some shortcomings such as the unstable convergence speed, the imprecise search accuracy, and incapability of identifying a local optimal solution when faced with complicated optimization problems. …”
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Neuronal Plasticity Associated with Burn Injury and Its Relevance for Perception and Management of Pain in Burn Patients by Terence J Coderre, Manon Choinière

“…The present paper examines these two very important issues in an effort to understand better the mechanisms that underlie the pain suffered by burn patients. The physiological responses to burn injury involve many different mediators and mechanisms, all of which contribute to pain perception and development of neuronal plasticity underlying short and long term changes in pain sensitivity. …”
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Prospective of climate change impact on water resources and sugar beet yield in the Urmia Lake basin by Somayeh Naderi, Bohloul Alijani, Zahra Hedjazizadeh, Hasan Heidari, Karim Abbaspour

“…This means that sugar beet may suffer from climate change impacts, and the production of this plant will change over the next period in this region. …”
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MSCD-YOLO: A Lightweight Dense Pedestrian Detection Model with Finer-Grained Feature Information Interaction by Qiang Liu, Zhongmin Li, Lei Zhang, Jin Deng

“…As a crucial direction in pedestrian detection, dense pedestrian detection still faces many unresolved challenges. Existing methods suffer from low detection accuracy, high miss rates, large model parameters, and poor robustness. …”
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Seismic Performance of Offshore Piers under Wave Impact and Chloride Ion Corrosion Environment by Yin Gu, Anhua Yu, Xiaolong Zhang

“…Offshore bridges may suffer from chloride ion corrosion, tsunami wave impact, and earthquake. …”
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Dynamic Pricing under Cost Reduction in the Presence of Myopic and Strategic Consumers by Guangning Liu, Zhenzhong Guan, Hua Wang

“…After release, a product usually suffers cost reductions during its whole lifespan. …”
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CAT-RFE: ensemble detection framework for click fraud by Yixiang LU, Guanggang GENG, Zhiwei YAN, Xiaomin ZHU, Xinchang ZHANG

“…Click fraud is one of the most common methods of cybercrime in recent years, and the Internet advertising industry suffers huge losses every year because of click fraud.In order to effectively detect fraudulent clicks within massive clicks, a variety of features that fully combine the relationship between advertising clicks and time attributes were constructed.Besides, an ensemble learning framework for click fraud detection was proposed, namely CAT-RFE ensemble learning framework.The CAT-RFE ensemble learning framework consisted of three parts: base classifier, recursive feature elimination (RFE) and voting ensemble learning.Among them, the gradient boosting model suitable for category features-CatBoost was used as the base classifier.RFE was a feature selection method based on greedy strategy, which can select a better feature combination from multiple sets of features.Voting ensemble learning was a learning method that combined the results of multiple base classifiers by voting.The framework obtained multiple sets of optimal feature combinations in the feature space through CatBoost and RFE, and then integrated the training results under these feature combinations through voting to obtain integrated click fraud detection results.The framework adopted the same base classifier and ensemble learning method, which not only overcame the problem of unsatisfactory integrated results due to the mutual constraints of different classifiers, but also overcame the tendency of RFE to fall into a local optimal solution when selecting features, so that it had better detection ability.The performance evaluation and comparative experimental results on the actual Internet click fraud dataset show that the click fraud detection ability of the CAT-RFE ensemble learning framework exceeds that of the CatBoost method, the combined method of CatBoost and RFE, and other machine learning methods, proving that the framework has good competitiveness.The proposed framework provides a feasible solution for Internet advertising click fraud detection.…”
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Self-adaptive bare-bones differential evolution based on bi-mutation strategy by Hui-yu LIU, Ji-hong HAN, Lin YUAN, Bo YU

“…Bare-bones differentia1 evo1ution（BBDE）can e1egant1y so1ve the se1ection prob1em of contro1 parameters and mutation strategy in differentia1 evo1ution（DE）.MGBDE is a c1assica1 BBDE based on bi-mutation strategy.However，it random1y assigns a mutation strategy to each individua1，not considering their differences during evo1ution process，meanwhi1e it may suffer from premature convergence.To overcome these drawbacks，a modified a1gorithm based on MGBDE was proposed.A mutation strategy choice factor that guided the individua1 to choose a preferab1e mutation strategy at each mutation operation was introduced，avoiding the evo1ution b1indness brought by the random se1ection of mutation strategy.To retain the a1most parameter-free characteristic of bare-bones a1gorithm，the tuning of choice factor to be adapted was invo1ved in the individua1 evo1ution，inspired by the concept of se1f-adaptive DE.The a1gorithm a1so inc1uded a we11-designed stagnation perturbation mechanism to reduce the risk of trapping into the 1oca1 optima1.Experimenta1 resu1ts on 18 benchmark functions show that the proposed a1gorithm genera11y achieves better performance than state-of-the-art BBDE variants and severa1 we11-known DE a1gorithms in terms of convergence and robustness.…”
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Deep learning vulnerability detection method based on optimized inter-procedural semantics of programs by Yan LI, Weizhong QIANG, Zhen LI, Deqing ZOU, Hai JIN

“…In recent years, software vulnerabilities have been causing a multitude of security incidents, and the early discovery and patching of vulnerabilities can effectively reduce losses.Traditional rule-based vulnerability detection methods, relying upon rules defined by experts, suffer from a high false negative rate.Deep learning-based methods have the capability to automatically learn potential features of vulnerable programs.However, as software complexity increases, the precision of these methods decreases.On one hand, current methods mostly operate at the function level, thus unable to handle inter-procedural vulnerability samples.On the other hand, models such as BGRU and BLSTM exhibit performance degradation when confronted with long input sequences, and are not adept at capturing long-term dependencies in program statements.To address the aforementioned issues, the existing program slicing method has been optimized, enabling a comprehensive contextual analysis of vulnerabilities triggered across functions through the combination of intra-procedural and inter-procedural slicing.This facilitated the capture of the complete causal relationship of vulnerability triggers.Furthermore, a vulnerability detection task was conducted using a Transformer neural network architecture equipped with a multi-head attention mechanism.This architecture collectively focused on information from different representation subspaces, allowing for the extraction of deep features from nodes.Unlike recurrent neural networks, this approach resolved the issue of information decay and effectively learned the syntax and semantic information of the source program.Experimental results demonstrate that this method achieves an F1 score of 73.4% on a real software dataset.Compared to the comparative methods, it shows an improvement of 13.6% to 40.8%.Furthermore, it successfully detects several vulnerabilities in open-source software, confirming its effectiveness and applicability.…”
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Behavior modeling for a new flexure-based mechanism by Hunger Game Search and physics-guided artificial neural network by Hieu Giang Le, Thanh-Phong Dao, Minh Phung Dang, Thao Nguyen-Trang

“…However, modeling the compliant mechanism behavior has suffered from many challenges, such as unstable results, and the limitation of training data set. …”
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A retrospective analysis of two tertiary care dizziness clinics: a multidisciplinary chronic dizziness clinic and an acute dizziness clinic by Phillip Staibano, Daniel Lelli, Darren Tse

“…Moreover, 12% of patients with functional dizziness also suffered from comorbid severe anxiety and depression. …”
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Spatiotemporal Exploration and Hazard Mapping of Tropical Cyclones along the Coastline of China by Shaobo Zhong, Chaolin Wang, Zhichen Yu, Yongsheng Yang, Quanyi Huang

“…Guangdong, Guangxi, Fujian, and Zhejiang provinces in particular suffered severely from the destructive TCs.…”
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