Belayat Hossain^a, Takatoshi Morooka^b, Makiko Okuno^b, Manabu Nii^a, Shinichi Yoshiya^b, Syoji Kobashi^a

Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 105-115, 2019, DOI:10.31209/2018.100000034

Abstract This work aimed to predict postoperative knee functions of a new patient prior to total knee arthroplasty (TKA) surgery using machine learning, because such prediction is essential for surgical planning and for patients to better understand the TKA outcome. However, the main difficulty is to determine the relationships among individual varieties of preoperative and postoperative knee kinematics. The problem was solved by constructing predictive models from the knee kinematics data of 35 osteoarthritis patients, operated by posterior stabilized implant, based on generalized linear regression (GLR) analysis. Two prediction methods (without and with principal component analysis… More >

Yasir Mehmood, Waseem Shahzad

Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 91-103, 2019, DOI:10.31209/2018.100000017

Abstract Particle swarm optimization (PSO) algorithm is a global optimization technique that is used to find the optimal solution in multimodal problems. However, one of the limitation of PSO is its slow convergence rate along with a local trapping dilemma in complex multimodal problems. To address this issue, this paper provides an alternative technique known as ACPSO algorithm, which enables to adopt a new simplified velocity update rule to enhance the performance of PSO. As a result, the efficiency of convergence speed and solution accuracy can be maximized. The experimental results show that the ACPSO outperforms More >

Jiping Liu^a,b, Xiaochen Kang^a,*, Chun Dong^a, Fuhao Zhang^a

Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 65-77, 2019, DOI:10.31209/2018.100000013

Abstract To guarantee both the efficiency and accuracy of the transportation system, the real-time status should be analyzed to provide a reasonable plan for the near future. This paper proposes a model for simulating the real-world transportation networks by representing the irregular road networks with static and dynamic attributes, and the vehicles as moving agents constrained by the road networks. The all pairs shortest paths (APSP) for the networks are calculated in a real-time manner, and the ever-changing paths can be used for navigating the moving vehicles with real-time positioning devices. In addition, parallel computation is More >

Awais Qasim^a, Syed Asad Raza Kazmi^b

Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 49-63, 2019, DOI:10.31209/2018.100000012

Abstract The paradigm of multi-agent systems is very expressive to model distributed real-time systems. These real-time multi-agent systems by their working nature have temporal constraints as they need to operate in pervasive, dynamic and unpredictable environments. To achieve better fault-tolerance, they need to have the ability of self-adaptivity making them adaptable to the failures. Presently there is a lack of vocabulary for the formal modelling of real-time multi-agent systems with self-adaptive ability. In this research we proposed a framework named SMARTS for the formal modelling of self-adaptive real-time multi-agent systems. Our framework integrates MAPE-K interfaces, reflection More >

Yu-Cheng Chou¹, Wei-Chieh Liao², Yan-Liang Chen², Ming Chang², Po Ting Lin³

Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 79-90, 2019, DOI:10.31209/2018.100000011

Abstract This paper presents the Distributed Heterogeneous Inspection System (DHIS), which comprises two CUDA workstations and is equipped with CPU distributed computing, CPU concurrent computing, and GPU concurrent computing functions. Thirty-two grayscale images, each with 5,000× 12,288 pixels and simulated defect patterns, were created to evaluate the performances of three system configurations: (1) DHIS; (2) two CUDA workstations with CPU distributed computing and GPU concurrent computing; (3) one CUDA workstation with GPU concurrent computing. Experimental results indicated that: (1) only DHIS can satisfy the time limit, and the average turnaround time of DHIS is 37.65% of More >

Juan Li

Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 35-48, 2019, DOI:10.31209/2018.100000003

Abstract K-Nearest Neighbor algorithm (KNN) is a simple and mature classification method. However there are susceptible factors influencing the classification performance, such as k value determination, the overlarge search space, unbalanced and multi-class patterns, etc. To deal with the above problems, a new classification algorithm that absorbs tree structure, tree pruning and adaptive k value method was proposed. The proposed algorithm can overcome the shortcoming of KNN, improve the performance of multi-class and unbalanced classification, reduce the scale of dataset maintaining the comparable classification accuracy. The simulations are conducted and the proposed algorithm is compared with several existing More >

Alessia Callegari¹, Barbara Burkhardt¹, Christa Relly², Walter Knirsch¹, Martin Christmann¹

Congenital Heart Disease, Vol.14, No.4, pp. 671-677, 2019, DOI:10.1111/chd.12830

Abstract Background: Since routine clinical use of antibiotics as well as surgical and catheter‐ based closure of a patent arterial duct (PDA), PDA‐associated infective endarteritis (PDA‐IE) is rare but can still occur when the ductus is still open or as it closes. Thus, clinicians should maintain a high index of concern for patients with unexplained fever.
Methods: We report on a PDA‐IE in a young infant shortly after potentially delayed obliteration of a PDA. We discuss this case report by reviewing the literature in regard to the pathogenesis (infection primary or secondary to PDA thrombus formation), clinical (new… More >

Amy E. Delaney¹, Nina M. Dadlez², Audrey C. Marshall²

Congenital Heart Disease, Vol.14, No.4, pp. 665-670, 2019, DOI:10.1111/chd.12821

Abstract Background: In pediatric cardiac care, many centers participate in multiple, national, domain‐specific registries, as a major component of their quality assessment and im‐ provement efforts. Small cardiac programs, whose clinical activities and scale may not be well‐suited to this approach, need alternative methods to assess and track quality.
Methods: We conceived of and piloted a rapid‐approach cardiac quality assessment, intended to encompass multiple aspects of the service line, in a low‐volume program. The assessment incorporated previously identified measures, drawn from multiple sources, and ultimately relied on retrospective chart review.
Results: A collaborative, multidisciplinary team formed and came to… More >

Maria Fedchenko, Zacharias Mandalenakis, Helena Dellborg, Görel Hultsberg‐Olsson, Anna Björk, Peter Eriksson, Mikael Dellborg

Congenital Heart Disease, Vol.14, No.4, pp. 549-558, 2019, DOI:10.1111/chd.12785

Abstract Background: The aging patient with adult congenital heart disease (ACHD) faces the risk of developing atherosclerotic disease. Patients with coarctation of the aorta (CoA) are especially vulnerable because of an inherent high risk of developing hy‐ pertension. However, data on the prevalence of other cardiovascular risk factors are scarce. Therefore, this study aimed to describe the prevalence of traditional cardio‐ vascular risk factors (diabetes, hypertension, hyperlipidemia, smoking, obesity, and sedentary lifestyle) in adult patients with CoA.
Methods: Patients with CoA who were registered at the ACHD clinic in Gothenburg were asked to participate in a comprehensive cardiovascular… More >

Lisa X. Deng¹, Lacey P. Gleason², Katherine Awh², Abigail May Khan³, David Drajpuch^2,4, Stephanie Fuller⁵, Leah A. Goldberg², Christopher E. Mascio⁵, Sara L. Partington^2,4, Lynda Tobin^2,4, Adrienne H. Kovacs³, Yuli Y. Kim^2,4

Congenital Heart Disease, Vol.14, No.4, pp. 534-540, 2019, DOI:10.1111/chd.12778

Abstract Objective: To investigate the experiences and communication preferences of adult patients with congenital heart disease (CHD) in the domains of employment, insur‐ ance, and family planning.
Design: Patients ≥ 18 years of age completed a questionnaire about experiences and communication preferences regarding employment, health insurance, and family planning.
Results: Of 152 patients (median age = 33 years, 50% female, 35% with CHD of great complexity), one in four reported work‐related problems due to CHD and a quar‐ ter also recalled a previous gap in health insurance. Of females, 29% experienced an unplanned pregnancy. The median importance of discussion… More >