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  • Open Access

    ARTICLE

    Single-port robotic laparoscopic ureterocalicostomy: surgical technique and clinical outcomes

    Alex J. Xu1, Jeffery S. Lin1, Po Yen Chen2, Samuel Carbunaru1, Yeonsoo S. Lee3, Lee C. Zhao1

    Canadian Journal of Urology, Vol.31, No.6, pp. 12072-12076, 2024

    Abstract Introduction: We describe a method of robotic ureterocalicostomy (RALUC) with the Da Vinci Single Port (SP) platform and present clinical outcomes in our cohort of patients.
    Materials and methods: We retrospectively reviewed all patients undergoing RALUC with the SP platform in a single-institution, IRB-approved database between 2020 2023. Demographics, preoperative, intraoperative, and postoperative outcomes were collated. Surgical success was defined as freedom from hardware, avoidance of additional surgical reconstruction, and no obstruction on follow up imaging/ureteroscopy.
    An incision is made 1/3rd the distance from anterior superior iliac spine to the umbilicus. The retroperitoneal space is entered and SP… More >

  • Open Access

    ARTICLE

    Enhancing Software Cost Estimation Using Feature Selection and Machine Learning Techniques

    Fizza Mansoor1, Muhammad Affan Alim2,5,*, Muhammad Taha Jilani3, Muhammad Monsoor Alam4,5, Mazliham Mohd Su’ud5

    CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4603-4624, 2024, DOI:10.32604/cmc.2024.057979 - 19 December 2024

    Abstract Software cost estimation is a crucial aspect of software project management, significantly impacting productivity and planning. This research investigates the impact of various feature selection techniques on software cost estimation accuracy using the CoCoMo NASA dataset, which comprises data from 93 unique software projects with 24 attributes. By applying multiple machine learning algorithms alongside three feature selection methods, this study aims to reduce data redundancy and enhance model accuracy. Our findings reveal that the principal component analysis (PCA)-based feature selection technique achieved the highest performance, underscoring the importance of optimal feature selection in improving software More >

  • Open Access

    ARTICLE

    Energy-Efficient and Cost-Effective Approaches through Energy Modeling for Hotel Building

    Alya Penta Agharid1, Indra Permana2, Nitesh Singh1, Fujen Wang2,*, Susan Gustiyana2

    Energy Engineering, Vol.121, No.12, pp. 3549-3571, 2024, DOI:10.32604/ee.2024.056398 - 22 November 2024

    Abstract Hotel buildings are currently among the largest energy consumers in the world. Heating, ventilation, and air conditioning are the most energy-intensive building systems, accounting for more than half of total energy consumption. An energy audit is used to predict the weak points of a building’s energy use system. Various factors influence building energy consumption, which can be modified to achieve more energy-efficient strategies. In this study, an existing hotel building in Central Taiwan is evaluated by simulating several scenarios using energy modeling over a year. Energy modeling is conducted by using Autodesk Revit 2025. It… More >

  • Open Access

    ARTICLE

    Production of Light Fraction-Based Pyrolytic Fuel from Spirulina platensis Microalgae Using Various Low-Cost Natural Catalysts and Insertion

    Indra Mamad Gandidi1,2,*, Sukarni Sukarni3,4, Avita Ayu Permanasari3, Purnami Purnami5, Tuan Amran Tuan Abdullah6, Anwar Johari6, Nugroho Agung Pambudi7,*

    Energy Engineering, Vol.121, No.12, pp. 3635-3648, 2024, DOI:10.32604/ee.2024.054943 - 22 November 2024

    Abstract The use of catalysts has significantly enhanced the yield and quality of in-situ pyrolysis products. However, there is a lack of understanding regarding pyrolysis approaches that utilize several low-cost natural catalysts (LCC) and their placement within the reactor. Therefore, this study aims to examine the effects of various LCC on the in-situ pyrolysis of spirulina platensis microalgae (SPM) and investigate the impact of different types of catalysts. We employed LCC such as zeolite, dolomite, kaolin, and activated carbon, with both layered and uniformly mixed LCC-SPM placements. Each experiment was conducted at a constant temperature of 500°C… More > Graphic Abstract

    Production of Light Fraction-Based Pyrolytic Fuel from <i>Spirulina platensis</i> Microalgae Using Various Low-Cost Natural Catalysts and Insertion

  • Open Access

    ARTICLE

    Software Cost Estimation Using Social Group Optimization

    Sagiraju Srinadhraju*, Samaresh Mishra, Suresh Chandra Satapathy

    Computer Systems Science and Engineering, Vol.48, No.6, pp. 1641-1668, 2024, DOI:10.32604/csse.2024.055612 - 22 November 2024

    Abstract This paper introduces the integration of the Social Group Optimization (SGO) algorithm to enhance the accuracy of software cost estimation using the Constructive Cost Model (COCOMO). COCOMO’s fixed coefficients often limit its adaptability, as they don’t account for variations across organizations. By fine-tuning these parameters with SGO, we aim to improve estimation accuracy. We train and validate our SGO-enhanced model using historical project data, evaluating its performance with metrics like the mean magnitude of relative error (MMRE) and Manhattan distance (MD). Experimental results show that SGO optimization significantly improves the predictive accuracy of software cost More >

  • Open Access

    ARTICLE

    Efficient and Cost-Effective Vehicle Detection in Foggy Weather for Edge/Fog-Enabled Traffic Surveillance and Collision Avoidance Systems

    Naeem Raza1, Muhammad Asif Habib1, Mudassar Ahmad1, Qaisar Abbas2,*, Mutlaq B. Aldajani2, Muhammad Ahsan Latif3

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 911-931, 2024, DOI:10.32604/cmc.2024.055049 - 15 October 2024

    Abstract Vision-based vehicle detection in adverse weather conditions such as fog, haze, and mist is a challenging research area in the fields of autonomous vehicles, collision avoidance, and Internet of Things (IoT)-enabled edge/fog computing traffic surveillance and monitoring systems. Efficient and cost-effective vehicle detection at high accuracy and speed in foggy weather is essential to avoiding road traffic collisions in real-time. To evaluate vision-based vehicle detection performance in foggy weather conditions, state-of-the-art Vehicle Detection in Adverse Weather Nature (DAWN) and Foggy Driving (FD) datasets are self-annotated using the YOLO LABEL tool and customized to four vehicle… More >

  • Open Access

    ARTICLE

    Unknown Environment Measurement Mapping by Unmanned Aerial Vehicle Using Kalman Filter-Based Low-Cost Estimated Parallel 8-Beam LIDAR

    Mohamed Rabik Mohamed Ismail1, Muthuramalingam Thangaraj1,*, Khaja Moiduddin2,*, Zeyad Almutairi2,3, Mustufa Haider Abidi2

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4263-4279, 2024, DOI:10.32604/cmc.2024.055271 - 12 September 2024

    Abstract The measurement and mapping of objects in the outer environment have traditionally been conducted using ground-based monitoring systems, as well as satellites. More recently, unmanned aerial vehicles have also been employed for this purpose. The accurate detection and mapping of a target such as buildings, trees, and terrains are of utmost importance in various applications of unmanned aerial vehicles (UAVs), including search and rescue operations, object transportation, object detection, inspection tasks, and mapping activities. However, the rapid measurement and mapping of the object are not currently achievable due to factors such as the object’s size,… More >

  • Open Access

    ARTICLE

    Enhancing Unsupervised Domain Adaptation for Person Re-Identification with the Minimal Transfer Cost Framework

    Sheng Xu1, Shixiong Xiang2, Feiyu Meng1, Qiang Wu1,*

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4197-4218, 2024, DOI:10.32604/cmc.2024.055157 - 12 September 2024

    Abstract In Unsupervised Domain Adaptation (UDA) for person re-identification (re-ID), the primary challenge is reducing the distribution discrepancy between the source and target domains. This can be achieved by implicitly or explicitly constructing an appropriate intermediate domain to enhance recognition capability on the target domain. Implicit construction is difficult due to the absence of intermediate state supervision, making smooth knowledge transfer from the source to the target domain a challenge. To explicitly construct the most suitable intermediate domain for the model to gradually adapt to the feature distribution changes from the source to the target domain,… More >

  • Open Access

    ARTICLE

    Cost-Sensitive Dual-Stream Residual Networks for Imbalanced Classification

    Congcong Ma1,2, Jiaqi Mi1, Wanlin Gao1,2, Sha Tao1,2,*

    CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4243-4261, 2024, DOI:10.32604/cmc.2024.054506 - 12 September 2024

    Abstract Imbalanced data classification is the task of classifying datasets where there is a significant disparity in the number of samples between different classes. This task is prevalent in practical scenarios such as industrial fault diagnosis, network intrusion detection, cancer detection, etc. In imbalanced classification tasks, the focus is typically on achieving high recognition accuracy for the minority class. However, due to the challenges presented by imbalanced multi-class datasets, such as the scarcity of samples in minority classes and complex inter-class relationships with overlapping boundaries, existing methods often do not perform well in multi-class imbalanced data… More >

  • Open Access

    ARTICLE

    Carbon Abatement Cost-Sharing Strategy for Electric Power Sector Based on Incentive and Subsidy Mechanisms

    Hui Wang, Wen Wang*, Wenhui Zhao

    Energy Engineering, Vol.121, No.10, pp. 2907-2935, 2024, DOI:10.32604/ee.2024.052665 - 11 September 2024

    Abstract The green and low carbon transition and development of the electricity industry is the most crucial task in realizing the “dual-carbon target”, and it is urgent to explore the incentive and subsidy mechanism to promote green electricity consumption and the cost-sharing strategy of carbon reduction, to alleviate the pressure of carbon abatement cost of each subject of the electricity supply chain. Against this background, this paper takes into account the low-carbon subsidies provided by the government and the incentive subsidies for users, and studies the optimal decision-making of each subject in the electricity supply chain,… More >

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