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  • Open Access

    ARTICLE

    Emotion Exploration in Autistic Children as an Early Biomarker through R-CNN

    S. P. Abirami1,*, G. Kousalya1, R. Karthick2

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 595-607, 2023, DOI:10.32604/iasc.2023.027562

    Abstract Autism Spectrum Disorder (ASD) is found to be a major concern among various occupational therapists. The foremost challenge of this neurodevelopmental disorder lies in the fact of analyzing and exploring various symptoms of the children at their early stage of development. Such early identification could prop up the therapists and clinicians to provide proper assistive support to make the children lead an independent life. Facial expressions and emotions perceived by the children could contribute to such early intervention of autism. In this regard, the paper implements in identifying basic facial expression and exploring their emotions upon a time-variant factor. The… More >

  • Open Access

    ARTICLE

    Exploration of Combinational Therapeutic Strategies for HCC Based on TCGA HCC Database

    Dong Yan1,#, Chunxiao Li2,#, Yantong Zhou2, Xue Yan1, Weihua Zhi1, Haili Qian2,*, Yue Han1,*

    Oncologie, Vol.24, No.1, pp. 101-111, 2022, DOI:10.32604/oncologie.2022.020357

    Abstract Hepatocellular carcinoma (HCC) is one of the most deadly types of cancer. Sorafenib is currently the only available first-line molecular targeted drug approved by the FDA for HCC. However, primary and secondary resistance is often encountered with treatment with sorafenib. Genomic alterations found in HCC represent potential targets to develop new drugs or new combinational strategies against this type of cancer. Here we analyzed genomic alterations from the TCGA database of HCC samples and the corresponding targeted drugs available to the clinic to identify candidate drugs that might hold promise when used in combination with sorafenib. Our results revealed that… More >

  • Open Access

    ARTICLE

    Exploration of IoT Nodes Communication Using LoRaWAN in Forest Environment

    Anshul Sharma1, Divneet Singh Kapoor1, Anand Nayyar2,3,*, Basit Qureshi4, Kiran Jot Singh1, Khushal Thakur1

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6239-6256, 2022, DOI:10.32604/cmc.2022.024639

    Abstract The simultaneous advances in the Internet of Things (IoT), Artificial intelligence (AI) and Robotics is going to revolutionize our world in the near future. In recent years, LoRa (Long Range) wireless powered by LoRaWAN (LoRa Wide Area Network) protocol has attracted the attention of researchers for numerous applications in the IoT domain. LoRa is a low power, unlicensed Industrial, Scientific, and Medical (ISM) band-equipped wireless technology that utilizes a wide area network protocol, i.e., LoRaWAN, to incorporate itself into the network infrastructure. In this paper, we have evaluated the LoRaWAN communication protocol for the implementation of the IoT (Internet of Things)… More >

  • Open Access

    ARTICLE

    Autonomous Exploration Based on Multi-Criteria Decision-Making and Using D* Lite Algorithm

    Novak Zagradjanin1,*, Dragan Pamucar2, Kosta Jovanovic1, Nikola Knezevic1, Bojan Pavkovic3

    Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1369-1386, 2022, DOI:10.32604/iasc.2022.021979

    Abstract An autonomous robot is often in a situation to perform tasks or missions in an initially unknown environment. A logical approach to doing this implies discovering the environment by the incremental principle defined by the applied exploration strategy. A large number of exploration strategies apply the technique of selecting the next robot position between candidate locations on the frontier between the unknown and the known parts of the environment using the function that combines different criteria. The exploration strategies based on Multi-Criteria Decision-Making (MCDM) using the standard SAW, COPRAS and TOPSIS methods are presented in the paper. Their performances are… More >

  • Open Access

    ARTICLE

    A New Reward System Based on Human Demonstrations for Hard Exploration Games

    Wadhah Zeyad Tareq*, Mehmet Fatih Amasyali

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2401-2414, 2022, DOI:10.32604/cmc.2022.020036

    Abstract The main idea of reinforcement learning is evaluating the chosen action depending on the current reward. According to this concept, many algorithms achieved proper performance on classic Atari 2600 games. The main challenge is when the reward is sparse or missing. Such environments are complex exploration environments like Montezuma’s Revenge, Pitfall, and Private Eye games. Approaches built to deal with such challenges were very demanding. This work introduced a different reward system that enables the simple classical algorithm to learn fast and achieve high performance in hard exploration environments. Moreover, we added some simple enhancements to several hyperparameters, such as… More >

  • Open Access

    ARTICLE

    Applying Non-Local Means Filter on Seismic Exploration

    Mustafa Youldash1, Saleh Al-Dossary2,*, Lama AlDaej1, Farah AlOtaibi1, Asma AlDubaikil1, Noora AlBinali1, Maha AlGhamdi1

    Computer Systems Science and Engineering, Vol.40, No.2, pp. 619-628, 2022, DOI:10.32604/csse.2022.017733

    Abstract The seismic reflection method is one of the most important methods in geophysical exploration. There are three stages in a seismic exploration survey: acquisition, processing, and interpretation. This paper focuses on a pre-processing tool, the Non-Local Means (NLM) filter algorithm, which is a powerful technique that can significantly suppress noise in seismic data. However, the domain of the NLM algorithm is the whole dataset and 3D seismic data being very large, often exceeding one terabyte (TB), it is impossible to store all the data in Random Access Memory (RAM). Furthermore, the NLM filter would require a considerably long runtime. These… More >

  • Open Access

    ARTICLE

    Tour Planning Design for Mobile Robots Using Pruned Adaptive Resonance Theory Networks

    S. Palani Murugan1,*, M. Chinnadurai1, S. Manikandan2

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 181-194, 2022, DOI:10.32604/cmc.2022.016152

    Abstract The development of intelligent algorithms for controlling autonom- ous mobile robots in real-time activities has increased dramatically in recent years. However, conventional intelligent algorithms currently fail to accurately predict unexpected obstacles involved in tour paths and thereby suffer from inefficient tour trajectories. The present study addresses these issues by proposing a potential field integrated pruned adaptive resonance theory (PPART) neural network for effectively managing the touring process of autonomous mobile robots in real-time. The proposed system is implemented using the AlphaBot platform, and the performance of the system is evaluated according to the obstacle prediction accuracy, path detection accuracy, time-lapse,… More >

  • Open Access

    ARTICLE

    Exploration on the Load Balancing Technique for Platform of Internet of Things

    Donglei Lu1, Dongjie Zhu2,*, Yundong Sun3, Haiwen Du3, Xiaofang Li4, Rongning Qu4, Yansong Wang3, Ning Cao1, Helen Min Zhou5

    Computer Systems Science and Engineering, Vol.38, No.3, pp. 339-350, 2021, DOI:10.32604/csse.2021.016683

    Abstract In recent years, the Internet of Things technology has developed rapidly, and smart Internet of Things devices have also been widely popularized. A large amount of data is generated every moment. Now we are in the era of big data in the Internet of Things. The rapid growth of massive data has brought great challenges to storage technology, which cannot be well coped with by traditional storage technology. The demand for massive data storage has given birth to cloud storage technology. Load balancing technology plays an important role in improving the performance and resource utilization of cloud storage systems. Therefore,… More >

  • Open Access

    ARTICLE

    L’exploration axillaire en pratique quotidienne dans le parcours diagnostique d’un cancer du sein
    Axillary staging in daily practice in the diagnosis of breast cancer

    J. Boudier, G. Oldrini, C. Barlier, A. Lesur

    Oncologie, Vol.21, No.1, pp. 11-16, 2019, DOI:10.3166/onco-2019-0034

    Abstract When a breast cancer is diagnosed, the quality of the evaluation before treatment is essential to guide the therapeutic decision. The staging axillary is necessary because it estimates the regional extension of the disease, which makes it a paramount prognosis factor. Some different preoperative medical imaging can reveal metastasis axillary nodes. However, the axillary ultrasound remains the reference imaging and it also leads the biopsies too. Since theACOSOG-Z0011 trial, we are facing a therapeutic deescalation in the axillary surgery. According to recent results, we can note that the position of the axillary imaging is more and more important. The purpose… More >

  • Open Access

    ARTICLE

    L’exploration axillaire : un standard du bilan préthérapeutique
    Axillary Evaluation: a Standard in Pretreatment Staging

    S. Dejust

    Oncologie, Vol.21, No.1, pp. 5-10, 2019, DOI:10.3166/onco-2019-0031

    Abstract Axillary evaluation is a major step in the initial staging of breast cancer. Ultrasound guided biopsy is currently recommended in first-line. MRI and 18FDG PET/CT are useful in axillary lymph node evaluation. Imaging sensitivities and specificities are globally identical and their combination allows obtaining the best performances. Currently, sentinel node technique is essential in case of T1-T2 N0 mammary tumors and in case of suspected lymph node adenopathy with negative cytopuncture or microbiopsy.


    Résumé
    L’exploration préthérapeutique axillaire est une étape majeure du bilan initial du cancer du sein. L’échographie associée à un prélèvement est actuellement recommandée en première intention. L’IRM et la… More >

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