Article
Engineering, Biomedical
Feng Chen, Chunyan Yang, Mohammad Khishe
Summary: This paper presents the use of deep convolutional neural networks (DCNNs) and the chimp optimization algorithm (ChOA) to recognize disordered speech. Several advancements using ChOA are proposed to optimize the DCNN structure. Experimental results show that the proposed model accurately diagnoses abnormal speech signals from patients with Parkinson's disease and cleft lip and palate.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2022)
Article
Chemistry, Multidisciplinary
Mohammad Khursheed Alam, Ahmed Ali Alfawzan, Fatema Akhter, Haytham Jamil Alswairki, Prabhat Kumar Chaudhari
Summary: This study investigated the variation between non-syndromic cleft lip and/or palate (NSCLP) and non-cleft (NC) subjects in relation to lip morphology (LM) and nasolabial angle (NLA). The results showed significant disparities in LM-1 and NLA between NSCLP and NC individuals.
APPLIED SCIENCES-BASEL
(2022)
Review
Dentistry, Oral Surgery & Medicine
Robert Frederick, Amy Claire Hogan, Natalie Seabolt, Rose Mary S. Stocks
Summary: This article emphasizes the benefits of a multidisciplinary team approach in the systemic management of patients with cleft lip and cleft palate, and suggests the addition of a registered dietitian to the care team. An ideal cleft palate care team should focus on a comprehensive, collaborative, and family-centered approach. While care teams may vary depending on context and location, there are still some key principles.
Article
Chemistry, Multidisciplinary
Natalia Kaczorowska, Marcin Mikulewicz
Summary: This paper examines cephalometric parameters in patients with cleft lip and palate and cleft lip, and compares the differences between these patient groups. The results show that cleft palate surgery has an effect on the forward growth of the maxilla.
APPLIED SCIENCES-BASEL
(2022)
Article
Cell Biology
Xiaofeng Li, Yu Tian, Ling Qiu, Shu Lou, Guirong Zhu, Yue Gao, Lan Ma, Yongchu Pan
Summary: This study utilized an expression quantitative trait locus (eQTL) dataset to identify multiple associations with the risk of non-syndromic cleft lip with or without cleft palate (NSCL/P). Functional annotation analysis showed that these risk loci were significantly enriched in transcription regulation and chromatin open regions on the genome. Additionally, these susceptible genes were closely related to cell fate determination, the pluripotency of stem cells, and Wnt signaling pathways.
Review
Genetics & Heredity
Arwa Babai, Melita Irving
Summary: Orofacial clefting is a common birth defect worldwide, presenting as cleft lip only, isolated cleft palate or cleft lip and palate. It has a diverse genetic background influenced by gene-gene and gene-environment interaction, resulting in syndromic and nonsyndromic orofacial clefts. Orofacial clefts cause significant physiological difficulties, impacting feeding, speech and language development, and other developmental aspects, leading to increased social and financial burden. The management of orofacial clefts requires a multidisciplinary team approach.
Article
Surgery
Amy S. Xue, Edward P. Buchanan, Larry H. Hollier
Summary: This article provides an overview of characteristics of unilateral cleft lip and nasal deformity, as well as its management options including presurgical orthopedics, operative techniques, and postsurgical care. Specific surgical techniques such as rotation-advancement and straightline repairs are discussed in detail, along with current concepts in primary cleft nose repair.
PLASTIC AND RECONSTRUCTIVE SURGERY
(2021)
Article
Pediatrics
Kristina Klinto, Marie Eriksson, Avni Abdiu, Karin Brunnegard, Jenny Cajander, Emilie Hagberg, Malin Hakelius, Christina Havstam, Hans Mark, Asa Okhiria, Petra Peterson, Kristina Svensson, Magnus Becker
Summary: The aim of this study was to compare data from the Swedish cleft lip and palate registry (CLP registry) among six treatment centers regarding surgery and speech outcomes at 5 years old. The results showed that at one center, more children underwent a higher number of surgeries and achieved poorer speech outcomes. It was also found that performing the last primary palatal surgery after 25 months of age increased the risk of negative speech results.
Article
Health Care Sciences & Services
Chin-Han Chang, Chi-Hua Chang, Jui-Pin Lai, Shiu-Shiung Lin, Yu-Jen Chang
Summary: This study investigated the prevalence of tooth agenesis, tooth malformation, and eruption patterns of upper canines/first premolars in Taiwanese children. The results suggest a strong correlation between the patterns of dental anomalies and the cleft sites in cleft lip and cleft palate patients.
JOURNAL OF PERSONALIZED MEDICINE
(2022)
Review
Biochemistry & Molecular Biology
Chihiro Iwaya, Akiko Suzuki, Junichi Iwata
Summary: Cleft lip and palate is a common congenital birth defect with varied causes. Recent studies suggest that non-coding RNAs, specifically microRNAs, may play a role in the development of cleft lip and palate. This review examines the potential of microRNAs as causative mechanisms in humans and mice.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Otorhinolaryngology
David O'Neil Danis, Kevin Bachrach, Jacquelyn Piraquive, Alexander P. Marston, Jessica R. Levi
Summary: The study found an association between neonatal abstinence syndrome (NAS) and cleft lip and/or cleft palate (CLP), specifically isolated cleft palate, suggesting that prenatal exposure to opioids may be an environmental risk factor in the development of CLP.
OTOLARYNGOLOGY-HEAD AND NECK SURGERY
(2021)
Article
Pediatrics
Kristina Klinto, Maria Sporre, Magnus Becker
Summary: This study evaluated the speech outcomes of 5-year-old children with cleft palate with or without cleft lip, finding relatively good speech overall but poorer speech in children with more extensive clefts. Children in the CP/L+ group were more likely to have incompetent velopharyngeal competence, but no significant differences were observed in speech outcomes between CP/L+ and CP/L- groups.
Article
Genetics & Heredity
Benjamin L. Green, Grace-Ann Fasaye, Sarah G. Samaranayake, Anna Duemler, Lauren A. Gamble, Jeremy L. Davis
Summary: Pathogenic and likely pathogenic variants in the CDH1 gene are associated with increased risk of gastric and breast cancers, as well as hereditary cleft lip and palate (CLP). This study aimed to determine the prevalence of CLP in families with these variants. The results showed a high prevalence of CLP in families carrying CDH1 variants, with no clear genotype-phenotype pattern. Genetic testing for CDH1 should be considered in families with CLP and a history of gastric or lobular breast cancer.
FRONTIERS IN GENETICS
(2022)
Article
Surgery
Amy S. Xue, Edward P. Buchanan, Larry H. Hollier
Summary: This article describes the characteristics and management of bilateral cleft lip and nasal deformity, including presurgical orthopedics, operative techniques, and postsurgical care.
PLASTIC AND RECONSTRUCTIVE SURGERY
(2022)
Article
Medicine, General & Internal
Andrzej Brudnicki, Elzbieta Radkowska, Ewa Sawicka, Piotr Stanislaw Fudalej
Summary: This study compared speech outcomes of cleft lip and palate patients who underwent various surgical interventions. The results showed that speech abnormalities were relatively infrequent and not highly severe, suggesting that the primary repair method effectively reduced the need for further surgical interventions, leading to positive speech outcomes.
JOURNAL OF CLINICAL MEDICINE
(2023)
Article
Computer Science, Artificial Intelligence
Chao Wu, Mohammad Khishe, Mokhtar Mohammadi, Sarkhel H. Taher Karim, Tarik A. Rashid
Summary: This paper proposes a method for diagnosing COVID19 patients using Extreme Learning Machine (ELM). By adjusting the parameters of ELM using the sine-cosine algorithm, the reliability of the network is improved. In the experiment, the proposed approach performs well on the COVID-Xray-5k dataset, achieving an accuracy of 98.83% and reducing relative error by 2.33% compared to a canonical deep CNN.
Correction
Computer Science, Interdisciplinary Applications
Bestan B. Maaroof, Tarik A. Rashid, Jaza M. Abdulla, Bryar A. Hassan, Abeer Alsadoon, Mokhtar Mohammadi, Mohammad Khishe, Seyedali Mirjalili
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Qiuyu Bo, Wuqun Cheng, Mohammad Khishe
Summary: This paper presents an evolved chimp optimization algorithm (ChOA) that uses greedy search and opposition-based learning to improve exploration and exploitation capabilities. The algorithm is evaluated on benchmark functions, real practical engineering-constrained problems, and other optimization techniques. The evaluation shows that the GSOBL-ChOA outperforms other benchmarks in several scenarios.
APPLIED SOFT COMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Mohammad Khishe
Summary: This paper proposes a modified Chimp Optimization Algorithm (ChOA) that improves the exploration and exploitation capabilities of the original algorithm. The performance of the modified algorithm, called OBLChOA, is evaluated on various benchmark functions, IEEE CEC06-2019 tests, random landscapes, and real-world engineering challenges. The results show that OBLChOA and CMA-ES perform the best among the tested algorithms in terms of mathematical test functions and engineering challenges.
ARTIFICIAL INTELLIGENCE REVIEW
(2023)
Article
Engineering, Electrical & Electronic
Ye Tian, Mohammad Khishe, Rasoul Karimi, Esmail Hashemzadeh, Omid Pakdel Azar
Summary: Radial basis function (RBF) neural network is a practical tool for underwater image processing. The deficiencies of RBF neural networks, such as low accuracy and slow convergence rate, are addressed using the chimp optimization algorithm (ChOA). Experimental results show that the proposed RBF-ChOA detector outperforms previous RBF-based recognizers and achieves a 1.91% improvement in recognizing underwater items compared to the top benchmark model.
CIRCUITS SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Computer Science, Artificial Intelligence
M. Khishe, N. Orouji, M. R. Mosavi
Summary: The Multi-Objective Chimp Optimization Algorithm (MOChOA) is developed in this research to address multi-objective optimization issues in various engineering problems. By utilizing a memory structure, leader selection strategy, and grid mechanism, MOChOA provides competitive results and outperforms other intelligent algorithms in terms of performance.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Maryam Kamalipour, Hamed Agahi, Mohammad Khishe, Azar Mahmoodzadeh
Summary: This study proposes a novel deep convolutional-recurrent autoencoder with a compound cepstral lifter to address the issues caused by varying ship noise, multi-path propagation effect, and time-varying underwater channels. Experimental results show that the designed model outperforms other benchmark models in terms of accuracy and complexity.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Mohammad Khishe, Mokhtar Mohammadi, Ali Ramezani Varkani
Summary: A four-phase deep learning approach is proposed for real-time underwater backscatter classification. It utilizes a deep convolutional neural network for feature extraction, replaces the fully connected layer with an extreme learning machine to reduce processing time, addresses uncertainty and unreliability using hunger games search, and balances exploration and exploitation using fuzzy systems.
NEURAL PROCESSING LETTERS
(2023)
Article
Computer Science, Artificial Intelligence
Chengfeng Cai, Bingchen Gou, Mohammad Khishe, Mokhtar Mohammadi, Shima Rashidi, Reza Moradpour, Seyedali Mirjalili
Summary: This paper introduces the application of deep learning in radiological images for COVID-19 detection. The Chimp Optimization Algorithm (ChOA) is used to train the fully connected layers of the deep convolutional neural networks (DCNN) and a fast COVID-19 detector is developed. Results from comparative experiments show that the proposed detector outperforms other similar detectors. Additionally, the Class Activation Map (CAM) is used to identify probable COVID-19-infected areas, which is validated by experts.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Imaging Science & Photographic Technology
Mohammad Khishe
Summary: This study proposes using a novel Trigonometric Function (TF) for training fully connected layers to improve the overall accuracy of the COVID-19 detection model. The designed model achieves competitive results on the COVID-Xray-5k dataset and utilizes the class activation map theory to detect potentially infected areas by the Covid-19 virus.
IMAGING SCIENCE JOURNAL
(2023)
Article
Computer Science, Information Systems
Mohammad Khishe, Omid Pakdel Azar, Esmaeil Hashemzadeh
Summary: This study proposes an improved version of the Chimp Optimization Algorithm (ChOA) to automatically find the optimal architecture of deep Conventional Conv neural networks (DCNNs). The proposed method achieves the best performance on the Fashion dataset with an error percentage of 5.08% and outperforms other benchmarks in terms of classification accuracy in 87 out of 95 investigations.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Retraction
Computer Science, Artificial Intelligence
Chao Wu, Mohammad Khishe, Mokhtar Mohammadi, Sarkhel H. Taher Karim, Tarik A. A. Rashid
Article
Automation & Control Systems
Seyed Majid Hasani Azhdari, Azar Mahmoodzadeh, Mohammad Khishe, Hamed Agahi
Summary: This paper proposes a novel approach to recognize PRIM patterns through a four-phase process, using a deep convolutional neural network (DCNN) as a feature extractor and extreme learning machines (ELMs) for real-time recognition. The biogeography-based optimizer (BBO) is employed to enhance the network's robustness by optimizing the connection weights and biases through an optimized variable-length internet protocol-based BBO (VBBO).
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Computer Science, Information Systems
Shukun He, Qinlin Li, Mohammad Khishe, Amin Salih Mohammed, Hassan Mohammadi, Mokhtar Mohammadi
Summary: This paper proposes an energy-efficient clustering and multi-hop routing protocol using a metaheuristic-based algorithm to increase energy efficiency in underwater wireless sensor networks (UWSNs) and lengthen the network life.
Article
Construction & Building Technology
Shouhua Liu, Jianfeng Li, Hamidreza Aghajanirefah, Mohammad Khishe, Abbas Khishe, Arsalan Mahmoodzadeh, Banar Fareed Ibrahim
Summary: This paper contrasts conventional seismic design with a design incorporating buckling-restrained bracing in three-dimensional reinforced concrete buildings. By improving the optimization algorithm and introducing new computational techniques, the design efficiency and performance are enhanced, and building costs are reduced. Additionally, a new method is proposed for calculating seismic and dead loads. Therefore, this research is significant for structural design.
STEEL AND COMPOSITE STRUCTURES
(2023)
Article
Acoustics
Cailiang Zhang, Zhihui Lai, Zhisheng Tu, Hanqiu Liu, Yong Chen, Ronghua Zhu
Summary: This paper proposes two single-parameter-adjusting SR models to optimize the output performance of SR systems. The effects of the proposed models on SR output under different parameters and signals are investigated through numerical simulations, and their feasibility is verified through experimental results. The research results are of great significance for guiding the design of tri-stable SR models and the application of SR-based signal processing in the context of big data.
Article
Acoustics
Shaoqiong Yang, Hao Chang, Yanhui Wang, Ming Yang, Tongshuai Sun
Summary: In this study, a suspension system based on phononic crystals is designed for vibration isolation of acoustic loads in underwater gliders. The vibration properties of the phononic crystals and the effects of physical parameters on the underwater attenuation zones are investigated. Vibration tests show that the phononic crystal suspension system has a stable vibration isolation effect in the frequency range of 120-5000 Hz.
Article
Acoustics
Xuebin Zhang, Jun Zhang, Tao Liu, Ning Hu
Summary: This study proposes a tunable metamaterial beam to isolate flexural waves. A genetic algorithm-based size optimization is used to obtain a broad low-frequency bandgap. The tunability of the beam is achieved by attaching different numbers of permanent magnets to change the mass of the resonators. Additionally, ultra-broadband flexural wave attenuation is achieved by forming a gradient metamaterial beam based on the rainbow effect. Numerical and experimental results confirm the good flexural wave attenuation ability of the proposed beam.
Article
Acoustics
Luca Rapino, Francesco Ripamonti, Samanta Dallasta, Simone Baro, Roberto Corradi
Summary: This paper presents a method for simulating tyre/road noise using equivalent monopoles, including the synthesis of monopoles through an inverse problem approach and the use of an ISO 10844 road replica for laboratory testing. The method combines acoustic finite element models and numerical simulations of vehicles, and the results are validated by comparing them with measured data.
Article
Acoustics
Xiaoyan Zhu, Tin Oberman, Francesco Aletta
Summary: This paper explores the definition of acoustical heritage and proposes a multidimensional definition based on interviews with experts and detailed analysis of the data.
Article
Acoustics
Faeez Masurkar, Saurabh Aggarwal, Zi Wen Tham, Lei Zhang, Feng Yang, Fangsen Cui
Summary: This research focuses on estimating the elastic constants of orthotropic laminates using ultrasonic guided waves and inverse machine learning models. The results show that this approach has the potential to accurately predict the elastic constants of a material and reduce computational time.
Article
Acoustics
Feng Xiao, Haiquan Liu, Jia Lu
Summary: Diagnostic methods for cardiovascular disease based on heart sound classification have been widely studied due to their noninvasiveness, low-cost, and high efficiency. However, existing research often faces challenges such as the nonstationarity and complexity of heart sound signals, leading to limited capability of neural networks to extract discriminative features. To address these issues, this study proposes a novel convolutional neural network that combines 1D convolution and 2D convolution, and introduces an attention mechanism to enhance feature extraction capability. The study also explores the advantages and disadvantages of combining deep learning features with manual features, and adopts an evolving fuzzy system for decision-making interpretability.
Article
Acoustics
Hong Xu, Zhengyao He, Qiang Shi, Yushi Wang, Bo Zhang
Summary: This paper presents the development of a directional segmented ring transmitting transducer that can radiate sound waves in any horizontal region. The study focuses on the structure of the segmented ring transducer, its radiation sound field characteristics, and the beam pattern control method based on modal synthesis. The authors propose orthogonal beam pattern functions for adjusting steering angles and establish a three-dimensional finite element model to simulate the transmitting beam patterns. Experimental measurements and tests validate the effectiveness of the proposed transducer, showcasing its ability to steer the beam patterns to different directions.
Article
Acoustics
Jirui Yang, Shefeng Yan, Di Zeng, Gang Tan
Summary: This paper proposes an improved domain adaptation framework, self-supervised learning minimax entropy, to enhance the recognition performance of underwater target recognition models. The experimental results demonstrate that applying domain adaptation methods can effectively improve the recognition accuracy of the models under various marine conditions.
Article
Acoustics
Zonghan Sun, Jie Tian, Yuhang Zheng, Xiaocheng Zhu, Zhaohui Du, Hua Ouyang
Summary: This paper analyzes the noise reduction method of installing a sinusoidal-shaped inlet duct on a cooling fan through theoretical and experimental analysis of the acoustic mode modulation. The study establishes the correlation between the free field noise and acoustic mode of the fan rotor and the unsteady forces on the rotor blade surface. The results show that the sinusoidal-shaped inlet duct achieves greater noise reduction compared to a straight duct, especially at the blade passing frequency and its first harmonic.
Article
Acoustics
Min Li, Rumei Han, Hui Xie, Ruining Zhang, Haochen Guo, Yuan Zhang, Jian Kang
Summary: This study is part of a global collaboration to translate and standardise soundscape research. A reliable questionnaire for soundscape characterisation in Mandarin Chinese was developed and validated. The study found that salient sound sources become the focus of attention for individuals in urban open spaces, and the perception is also influenced by the acoustic characteristics of the soundscape. Certain types of sound sources play a more important role in soundscape perception.
Article
Acoustics
Arezoo Talebzadeh, Dick Botteldooren, Timothy Van Renterghem, Pieter Thomas, Dominique Van de Velde, Patricia De Vriendt, Tara Vander Mynsbrugge, Yuanbo Hou, Paul Devos
Summary: This study proposes a sound selection methodology to enhance the soundscape in nursing homes and reduce BPSD by analyzing sound characteristics and recognition methods. The results highlight the sound characteristics that lead to positive responses, while also pointing out the need for further studies to understand which sounds are most suitable for people with dementia.
Article
Acoustics
Yang Yang, Yongxin Yang, Zhigang Chu
Summary: This paper introduces a grid-free compressive beamforming method compatible with arbitrary linear microphone arrays, and demonstrates the correctness and superiority of the proposed method through examples. Monte Carlo simulations are performed to reveal the effects of source coherence, source separation, noise, and number of snapshots.
Article
Acoustics
Sukru Selim Calik, Ayhan Kucukmanisa, Zeynep Hilal Kilimci
Summary: Computer-Aided Language Learning (CALL) is growing rapidly due to the importance of acquiring proficiency in multiple languages for effective communication. In the field of CALL, the detection of mispronunciations is vital for non-native speakers. This research introduces a novel framework using audio-centric transformer models to detect mispronunciations in Arabic phonemes. The results demonstrate that the UNI-SPEECH transformer model yields notable classification outcomes in Arabic phoneme mispronunciation detection. The comprehensive comparison of these transformer models provides valuable insights and guidance for future investigations in this domain.
Article
Acoustics
Yi-Yang Ni, Fei-Yun Wu, Hui-Zhong Yang, Kunde Yang
Summary: This paper proposes an improved method for compressive sensing by introducing a self training dictionary scheme and a CS reconstruction method based on A*OLS, which enhances the sparse representation performance of propeller signals.