bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multi-Auv Distributed Task Allocation Based on the Differential Evolution Quantum Bee Colony Optimization Algorithm
Authors: Li Jianjun , Zhang Ru Bo 
Published: November 2017

Abstract
The multi-autonomous underwater vehicle (AUV) distributed task allocation model of a contract net, which introduces an equilibrium coefficient, has been established to solve the multi-AUV distributed task allocation problem. A differential evolution quantum artificial bee colony (DEQABC) optimization algorithm is proposed to solve the multi-AUV optimal task allocation scheme. The algorithm is based on the quantum artificial bee colony algorithm, and it takes advantage of the characteristics of the differential evolution algorithm. This algorithm can remember the individual optimal solution in the population evolution and internal information sharing in groups and obtain the optimal solution through competition and cooperation among individuals in a population. Finally, a simulation experiment was performed to evaluate the distributed task allocation performance of the differential evolution quantum bee colony optimization algorithm. The simulation results demonstrate that the DEQABC algorithm converges faster than the QABC and ABC algorithms in terms of both iterations and running time. The DEQABC algorithm can effectively improve AUV distributed multi-tasking performance.
Experimental and Optimization Design of Offshore Drilling Seal
Authors: Zhang Yi , Zhang Xiaodong , Chang Xueping , Wu Qian 
Published: November 2017

Abstract
Three-cone bit is the key equipment in the exploration of the oil in offshore drilling and exploration, the bearing system and the seal system are the critical components for the bit. Especially in the offshore drilling environment, the seal design need to be carefully considered. A multi-objective optimization design including orthogonal design method and F-test with finite element analysis for a three-cone bit seal is proposed. Firstly, the calculation method of optimization targets are given, including the minimization of maximum contact pressure and leakage rate analyzed by ANSYS and MATLAB respectively, to maximize seal life and reliability. Then, an orthogonal experiment approach is used to investigate the effects of the eleven parameters on the seal performance, and the influence degrees of the seal factors on the optimization targets have been confirmed by F-test, and the reasonable factors can be determined by the trend of the targets. Finally, in order to validate the analysis results, a new seal was designed and tested on a seal tester compared to the previous seal. In this test, the seal maximum interface temperature that reflects the position of maximum contact pressure can be obtained by using three high precision thermocouples. Both the experiment results and the numerical analyses proved that the maximum contact pressure and leakage rate of the improved seal have been reduced compared to the previous.
A Deep Q-Learning Network for Ship Stowage Planning Problem
Authors: Shen Yifan , Zhao Ning , Xia Mengjue , Du Xueqiang 
Published: November 2017

Abstract
Ship stowage plan is the management connection of quae crane scheduling and yard crane scheduling. The quality of ship stowage plan affects the productivity greatly. Previous studies mainly focuses on solving stowage planning problem with online searching algorithm, efficiency of which is significantly affected by case size. In this study, a Deep Q-Learning Network (DQN) is proposed to solve ship stowage planning problem. With DQN, massive calculation and training is done in pre-training stage, while in application stage stowage plan can be made in seconds. To formulate network input, decision factors are analyzed to compose feature vector of stowage plan. States subject to constraints, available action and reward function of Q-value are designed. With these information and design, an 8-layer DQN is formulated with an evaluation function of mean square error is composed to learn stowage planning. At the end of this study, several production cases are solved with proposed DQN to validate the effectiveness and generalization ability. Result shows a good availability of DQN to solve ship stowage planning problem.
An Application of 24Model to Analyse Capsizing of the Eastern Star Ferry
Authors: Suo Xiao , Fu Gui , Wang Chunxue , Jia Qingsong 
Published: November 2017

Abstract
In the present study, the Eastern Star ferry accident was analyzed via 24Model. 24Model, as an accident causation model based on system thinking, holds that all causations of the accident are hazards and all hazards in the system need to be identified and comprehensively controlled in accident prevention. The result showed that five factors were the main causes of the accident. First, the direct causes: bad weather, the bad condition of the hull and the unsafe acts of the captain. Second, the indirect cause: the lack of safety awareness and safety knowledge of both the captain and the company’s senior management. Third, there were loopholes in safety management system, including the training, supervision and execution of the company. Forth, the root cause: the company didn’t establish a good safety culture. Last, the external causes: the severe market pressure, excessive regulatory authorities with puzzled relations and responsibilities-seriously hindered effective supervision. In order to prevent this kind of accident and to secure shipping system, the shipping companies and the relevant regulatory units should draw lessons from the five factors mentioned above, and take measures to identify and control those hazards.
Research on Intelligent Diagnosis Method for Large-Scale Ship Engine Fault in Non-Deterministic Environment
Authors: Feng Donghua , Li Yahong 
Published: November 2017

Abstract
Aiming at the problem of inaccurate and time-consuming of the fault diagnosis method for large-scale ship engine, an intelligent diagnosis method for large-scale ship engine fault in non-deterministic environment based on neural network is proposed. First, the possible fault of the engine was analyzed, and the downtime fault of large-scale ship engine and the main fault mode were identified. On this basis, the fault diagnosis model for large-scale ship engine based on neural network is established, and the intelligent diagnosis of engine fault is completed. The experiment proved that the proposed method has high diagnostic accuracy, engine fault diagnosis takes only about 3s, with a higher use value.
Treating malignant melanoma when a rare BRAF V600M mutation is present: case report and literature review
Authors: Popescu Andrei , Haidar Andrei , Anghel Rodica Maricela 
Published: November 2017

Abstract
Recent years have brought major advances in the treatment of malignant melanoma. One such an advance is the treatment with BRAF tyrosine-kinase inhibitors in metastatic malignant melanomas that harbor mutations in the BRAF gene. The trials that have been performed in this setting have demonstrated superior response rates and increased overall survival, however, they mostly included patients with melanomas carrying the more common V600E and V600K mutations, not being able to assess the benefit of these treatments in situations where more rare mutations of the BRAF gene are present. We present the evolution of a patient with malignant melanoma with a rare V600M mutation in the BRAF gene, that was eventually treated with vemurafenib. Also we present a brief review of the major phase III trials that showed benefit with tyrosine-kinase inhibitors in BRAF mutated melanoma, with respect to the BRAF mutations included.
Biological therapies in psoriasis - revisited
Authors: Sârbu Maria-Isabela , Georgescu Simona-Roxana , Tampa Mircea , Sârbu Alexandra-Elena , Simionescu Olga 
Published: November 2017

Abstract
Psoriasis is a chronic, immune mediated disorder affecting approximately 2% of the population. Even in our days, patients with psoriasis are confronted with stigmatization and social rejection. As a result, their quality of life is significantly impaired. Biological therapies have revolutionized the treatment of moderate to severe psoriasis. The aim of this paper is to look over the most important biological therapies available for the management of plaque-type psoriasis.
Evaluation of Alternatives to Integrate Special Transportation Services for People with Movement Disorders
Authors: Verseckiene Alina , Palsaitis Ramunas , Yatskiv Irina 
Published: November 2017

Abstract
Integrating the most appropriate special transportation service for people with movement disorders model may result in great economy efficiency and social benefit balance. However, most existing researches are based on improving the accessibility of public transport services or development of routing and scheduling under stochastic input data. The aim of this paper is to project the evaluation algorithm for the purpose of assessing the appropriate model of integration which would enable the employment of existing resources and filling the gap in assurance the mobility needs of people with mobility impairments. This paper identifies the evaluation indicators which are selected from international publications. Firstly the performance indicators of special transportation services were selected, further the sustainable development of public transport services evaluation indicators were selected, classified and adjusted to the goal of this paper. As a final result of indicators selection, a set of indicators classified into two groups - cost and benefit - was carried out. The decision making is based on Fuzzy Analytic Hierarchy Process and Fuzzy Technique for Order Preference by Similarity to Ideal Solution methods. A case study is provided to demonstrate the application of proposed evaluation algorithm.
Efficiency Increase Models of Two-Level Echelon Logistic Systems
Authors: Lukinskiy Valery , Lukinskiy Vladislav 
Published: November 2017

Abstract
In this article we deal with the approach to logistic systems efficiency increase on the basis of various forms of logistic integration development in supply chains, with modified variants of model of economic order quantity for the echelon two-level systems which allow considering the costs correlations at the different system levels, the different stock warehousing strategies, the multi-nomenclature of orders. The appropriate calculations have been done for the suggested modified models approbation.
An Unmanned Aerial Vehicles Company: A Stochastic Model of Resources Overbooking
Authors: Smurov Mihail , Sulima Nikolajs 
Published: November 2017

Abstract
In connection with the rapid development of commerce of unmanned aerial vehicles (UAV), the optimality of their use with UAV companies (UAVCo) is becoming increasingly important. The basis of such companies are mobile units (mobile units (MU)), which include UAV, means of their delivery to the place of rendering services and maintenance personnel. A problem of determining the optimal level of orders for the use of MU with UAVCo has been formulated and solved. The task is formulated as an overbooking task. The process under investigation is described as a discrete-time Markov chain corresponding to 24 hours. Based on a fixed number of MU and a fixed overbooking level, distributions for the number of orders on hand, the number of unfulfilled customs, and the average income with an MU usage fee and penalties for unfulfilled orders factored in have been calculated. The solution method has been tested on a particular model. For calculation used language and computer environment MathCAD.
Excitatory Synaptic Input to Hilar Mossy Cells under Basal and Hyperexcitable Conditions
Authors: Hedrick Tristan P. , Nobis William P. , Foote Kendall M. , Ishii Toshiyuki , Chetkovich Dane M. , Swanson Geoffrey T. 
Published: November 2017

AbstractHilar mossy cells (HMCs) in the hippocampus receive glutamatergic input from dentate granule cells (DGCs) via mossy fibers (MFs) and back-projections from CA3 pyramidal neuron collateral axons. Many fundamental features of these excitatory synapses have not been characterized in detail despite their potential relevance to hippocampal cognitive processing and epilepsy-induced adaptations in circuit excitability. In this study, we compared pre- and postsynaptic parameters between MF and CA3 inputs to HMCs in young and adult mice of either sex and determined the relative contributions of the respective excitatory inputs duringin vitroandin vivomodels of hippocampal hyperexcitability. The two types of excitatory synapses both exhibited a modest degree of short-term plasticity, with MF inputs to HMCs exhibiting lower paired-pulse (PP) and frequency facilitation than was described previously for MF–CA3 pyramidal cell synapses. MF–HMC synapses exhibited unitary excitatory synaptic currents (EPSCs) of larger amplitude, contained postsynaptic kainate receptors, and had a lower NMDA/AMPA receptor ratio compared to CA3–HMC synapses. Pharmacological induction of hippocampal hyperexcitabilityin vitrotransformed the abundant but relatively weak CA3–HMC connections to very large amplitude spontaneous bursts of compound EPSCs (cEPSCs) in young mice (∼P20) and, to a lesser degree, in adult mice (∼P70). CA3–HMC cEPSCs were also observed in slices prepared from mice with spontaneous seizures several weeks after intrahippocampal kainate injection. Strong excitation of HMCs during synchronous CA3 activity represents an avenue of significant excitatory network generation back to DGCs and might be important in generating epileptic networks.
Fever in pregnancy and its maternal and fetal outcomes
Authors: More Vibha S. 
Published: November 2017

Background: Contemporary obstetrics has witnessed improved maternal and fetal outcomes, owing to several advances. Any source of maternal hyperthermia that results in significant core temperature increase (>38.9°C), could potentially affect the fetus. Hence a study was planned to know the effect of fever on maternal and fetal outcome.Methods: This was a retrospective cohort analysis of case-records, of patients admitted in the Department of Obstetrics and Gynecology at tertiary care centre, Mumbai, between May 2007 and October 2009. The main parameters of assessment included incidence of fever in pregnancy, causes of fever, effect of episode(s) of fever on maternal and fetal outcomes, effect of specific infection on maternal and fetal outcomes, impact of fever on antepartum, intrapartum and postpartum phasesResults: The incidence of fever was 10.5%. the common cause of fever was malaria (15%), urinary tract infection (14%), viral (14%), respiratory tract infection (18%), and typhoid (7%). Seventy eight percent had fever in third trimester. The most common antenatal complication observed was preterm (13%), premature rupture of membrane (12%), oligohydramnios (8%), intrauterine growth retardation (26%). The rate of LSCS was 13% in study group and the most common indication was fetal distress and meconium stained amniotic fluid.Conclusions: In the present study on fever during pregnancy and its maternal and fetal outcomes, fever was associated with a definite impact on maternal and fetal outcomes. Preterm and IUGR were the most common fetal complications. Duration of fever was linearly associated with poor outcomes. Different causes of fever also had different impact on maternal and fetal outcome. Preterm IUGR, MSAF were more common with malaria and tuberculosis. Abortion was more commonly seen in first trimester fever, whereas preterm, PROM in the third trimester fever. Hence it is suggested that fever during pregnancy needs to be promptly investigated and treated to have a better outcome.
Efficient resource management for cost effective healthcare at Jinnah postgraduate medical centre
Authors: Jawed Shafaq , Tariq Syed Maaz 
Published: November 2017

Jinnah Post graduate medical Centre (JPMC) is on the biggest public hospitals of Pakistan, serves 1.2 million patients annually, 4,38,000 patients examined in the emergency department alone. Most of health services & treatments are low cost at JPMC and affordable for everyone. However, over the past few years the number of patients in emergency as well as Outpatient department has substantially increased causing stress on physical, human and financial resources. The number of patients has increased by two folds in the last decade. These number are continuously increasing and over burden to available infrastructure is a hindrance in the way of quality medical care. A study conducted in the department of chest medicine of JPMC revealed that among 120 tuberculosis patients, almost 50% (60) died during hospitalization. Delayed treatment, absence of smear records were among the major prognostic factors. Limited resources coupled with poor management results in compromised health care.
Analisis Karakteristik Input-Output dan Optimasi Biaya Pembangkitan Menggunakan Metode Quadratic Least Square Regression dan Metode Dynamic Genetic Algorithm
Authors: Anggraeni Rina , Setiawan Dedy Kurnia , Hardianto Triwahju 
Published: November 2017

Optimalisasi produksi listrik, khususnya pada pembangkit termal membutuhkan analisis karakteristik input-output dan pembebanan yang tepat agar beroperasi dengan baik. Karakteristik input-output akan mengawasi pergeseran yang terlihat dari kurva dan mendeteksi perlu adanya maintenance atau tidak pada sebuah pembangkit. Karakteristik input-output dapat dihitung dengan metode quadratic least square regression. Sedangkan pembebanan yang tepat, membuat produksi listrik sesuai maksimal beban yang diinginkan dengan biaya paling murah. Perhitungan pembebanan dilakukan dengan metode dynamic genetic algorithm. Metode ini diaplikasikan pada data PT. PJB UP Gresik bulan Juli 2015 didapatkan total biaya bahan bakar yang dihemat sebesar 3.162,9147 KNM3 dan biaya bahan bakar sebesar $22.773 dibandingkan PJB.
Kata Kunci: dynamic genetic algorithm, economic dispatch, karakteristik input-output, quadratic least square regression.
Lubag Syndrome (X-linked Dystonia Parkinsonism) Case Study of Mr G. Infante
Authors: Cheah Vincent 
Published: November 2017

Abstract
Sex-linked dystonia parkinsonism (XDP) also known as Lubag Syndrome is a rare sex-linked genetic progressive movement disorder affecting almost exclusively males from the province of Capiz in the Philippines and their descendants. At the Mater Centre for Neurosciences we have recently treated two patients with XDP utilising Deep Brain Stimulation (DBS) implants. Mr G. Infante was the second patient to be treated, the first being his uncle. Mr G. Infante’s case was brought to the attention of the Mater Centre for Neurosciences at South Brisbane after the success of his uncle’s treatment two years prior.
In the three years from when Mr G. Infante’s dystonia symptoms were first noticed, his condition progressively worsened until he was wheelchair bound. With severe chronic pain, unable to walk, difficulties talking and swallowing, Mr G’s quality of life was severely impacted by XDP.
XDP is a movement disorder considered a variation to Parkinson’s Disease. The difference being that the XDP starts with a long period of dystonia that eventually evolves into the tremor and associated symptoms typical of Parkinson’s Disease. Due to the similarity of the conditions the patient’s needs and treatment methods, both medical and surgical, are almost identical. Deep brain stimulation surgery involves implantation of electrodes into specific regions of the brain. The electrodes are then used to deliver finely tuned electrical currents in order to reduce the signs and symptoms of both neuropsychiatric and movement disorders such as Parkinson’s and XDP. The high frequency electrical charges sent to deep structures in the brain stimulate or shut down nerve cells around the electrode. The areas of the brain that the electrodes target are thought to participate in the circuitry involved and effectively disrupts these processes and reduces the symptoms of the disease.
This paper presents the journey of Mr G. Infante’s XDP and DBS and provides an explanation of how DBS works to improve the quality of life for patients who suffer from XDP.
Drain tube removal in the presence of anticoagulation in Spinal Surgery
Authors: Holland Christine , Smith Sarah 
Published: November 2017

Abstract
Venous thromboembolism (VTE), the collective term for Deep Vein Thrombosis (DVT) and Pulmonary Embolism (PE), remains a major cause of morbidity and a significant cause of mortality in hospitalised patients across Australia and internationally. It is important that adequate prophylaxis is provided for patients at risk. Measures including; anti-clotting medication, graduated compression stockings, adequate hydration and early mobilisation are known to be effective in reducing the incidence of VTE.
The prevention of VTE in acute care hospitals has been recognised worldwide as a priority patient safety issue because of the strong evidence base for preventive measures and high potential for improvements in patient outcomes.
With the introduction of risk assessment tools identifying patients of increased risk of VTE, more neurosurgical patients are now receiving VTE prophylaxis during their postoperative clinical course. This raises the question of the role and the impact of VTE anticoagulation when it comes to surgical drain tube removal and the risk of bleeding after spinal surgery. With multiple neurosurgeons and a variety of opinions, the clinical nursing team decided to review the role of anticoagulation and drain tube removal through evidence based research.
Imperialist Competitive Algorithm-Based Fuzzy Pid Control Methodology for Speed Tracking Enhancement of Stepper Motor
Authors: Yazdani Amir Mehdi , Ahmadi Ahmadreza , Buyamin Salinda , Rahmat Mohd Fua’ad , Davoudifar Farshad , Rahim Herlina Abd 
Published: November 2017

Abstract
Precise control of the stepper motor has always been a topic of interest and also a challenging issue among control engineering researchers due to the nonlinear nature of the motor dynamic. Abrupt influences of the uncertainties on the model’s dynamic and control performance, on the other hand, must be taken into account for providing a control methodology including the characteristics of adaption and flexibility. Lack of these items in most of the classic control approaches results in degradation of the control action. The main purpose of this paper is to provide an intelligent approach for improving the functionality of conventional PID controller in the problem of trajectory tracking in permanent magnet stepper motor (PMSM). Combination of a meta-heuristic algorithm called imperialist competitive algorithm (ICA) and fuzzy logic is employed for online tuning of PID controller. This, consequently, establishes an intelligent structure, fuzzy-PID controller (FPID), which is more flexible and accurate both in certain and uncertain situations. Using a systematic approach in designing the optimal fuzzy structure based on the ICA is our contribution here which leads to better performance of PMSM. Comparing the results of simulations, done in Matlab Simulink, between the suggested control strategy and performance of the PID, expresses the remarkable capability of FPID in overcoming the complexity of control of the nonlinear and uncertain systems.
An Enhanced Dynamic Token Protocol for Underwater Acoustic Sensor Networks
Authors: Fan Guangyu , Li Jian , Liu Wenhong , Zhao Yang 
Published: November 2017

Abstract
The properties of underwater acoustic channel are quite different from those of terrestrial wireless sensor networks. There are many challenges to design an efficient media access control (MAC) protocol for underwater acoustic sensor networks (UWASNs). In order to overcome the long propagation delay and low available bandwidth of UWASNs, an enhanced dynamic token protocol (EDTP), is proposed in the paper. It uses token passing queue (TPQ) and TPQ backup method to transfer the token packets dynamically and efficiently, leading to improving the channel efficiency of the networks. Simulation results show that compared with the existing protocols, the proposed protocol can achieve a high throughput, a low packet drop ratio, and a low transmission delay.