Subtle skills: Using objective structured clinical examinations to assess gastroenterology fellow performance in system based practice milestones

BACKGROUND System based practice(SBP) milestones require trainees to effectively navigate the larger health care system for optimal patient care. In gastroenterology training programs, the assessment of SBP is difficult due to high volume, high acuity inpatient care, as well as inconsistent direct supervision. Nevertheless,structured assessment is required for training programs. We hypothesized that objective structured clinical examination(OSCE) would be an effective tool for assessment of SBP.AIM To develop a novel method for SBP milestone assessment of gastroenterology fellows using the OSCE.METHODS For this observational study, we created 4 OSCE stations: Counseling an impaired colleague, handoff after overnight call, a feeding tube placement discussion, and giving feedback to a medical student on a progress note. Twentysix first year fellows from 7 programs participated. All fellows encountered identical case presentations. Checklists were completed by trained standardized patients who interacted with each fellow participant. A report with individual and composite scores was generated and forwarded to program directors to utilize in formative assessment. Fellows also received immediate feedback from a faculty observer and completed a post-session program evaluation survey.RESULTS Survey response rate was 100%. The average composite score across SBP milestones for all cases were 6.22(SBP1), 4.34(SBP2), 3.35(SBP3), and 6.42(SBP4)out of 9. The lowest composite score was in SBP 3, which asks fellows to advocate for cost effective care. This highest score was in patient care 2, which asks fellows to develop comprehensive management plans. Discrepancies were identified between the fellows’ perceived performance in their self-assessments and Standardized Patient checklist evaluations for each case. Eighty-seven percent of fellows agreed that OSCEs are an important component of their clinical training,and 83% stated that the cases were similar to actual clinical encounters. All participating fellows stated that the immediate feedback was "very useful." One hundred percent of the fellows stated they would incorporate OSCE learning into their clinical practice.CONCLUSION OSCEs may be used for standardized evaluation of SBP milestones. Trainees scored lower on SBP milestones than other more concrete milestones. Training programs should consider OSCEs for assessment of SBP.

SOMS: A Subway Operation and Maintenance System Based on Planned Maintenance Model with Train State

This paper aims to propose a modeling framework for subway operation and maintenance system (SOMS), which analyzes the train condition data based on both train sensor network data and basis train maintenance plan. The system is formulated into five function modules, and the research problem is to determine one auxiliary maintains plan, including the time allocation and frequency of maintenance. The case of Guangzhou metro is conducted to illustrate the applicability of SOMS, and the results reveal a number of interesting insights into subway maintenance system, i.e., the worksheet can reduce duplication of redundant maintenance work, the repair cost, and the damage caused by frequent disassembly.

An E-Commerce Recommender System Based on Content-Based Filtering

Content-based filtering E-commerce recommender system was discussed fully in this paper. Users＇ unique features can be explored by means of vector space model firstly. Then based on the qualitative value of products informa tion, the recommender lists were obtained. Since the system can adapt to the users＇ feedback automatically, its performance were enhanced comprehensively. Finally the evaluation of the system and the experimental results were presented.

Design and Strategy of Series-Parallel Hybrid System Based on BSFC

In this paper,a drive control strategy is developed based on the characteristics of series-parallel plug-in hybrid system.Energy management strategies in various modes are established with the basis on the minimum brake specific fuel consumption(BSFC)curve of engine.The control strategy,which is based on rules and system efficiency,is adopted to determine the entry/exit mechanisms of various modes according to battery state of charge(SOC),required power and required speed.The vehicle test results verify that the proposed control strategy can improve vehicle economy efficiently and makes a good effect on engine control.

ESKD-A New Structure of Expert System Based on Knowledge Discovery

A new structure of ESKD (expert system based on knowledge discovery system KD (D&K)) is first presented on the basis of KD (D&K)-a synthesized knowledge discovery system based on double-base (database and knowledge base) cooperating mechanism. With all new features, ESKD may form a new research direction and provide a great probability for solving the wealth of knowledge in the knowledge base. The general structural frame of ESKD and some sub-systems among ESKD have been described, and the dynamic knowledge base based on double-base cooperating mechanism has been emphased on. According to the result of demonstrative experi- ment, the structure of ESKD is effective and feasible.

V–L decomposition of a novel full-waveform lidar system based on virtual instrument technique

A novel three-dimensional（3D） imaging lidar system which is based on a virtual instrument technique is introduced in this paper. The main characteristics of the system include： the capability of modeling a 3D object in accordance with the actual one by connecting to a geographic information system（GIS）, and building the scene for the lidar experiment including the simulation environment. The simulation environment consists of four parts： laser pulse, atmospheric transport,target interaction, and receiving unit. Besides, the system provides an interface for the on-site experiment. In order to process the full waveform, we adopt the combination of pulse accumulation and wavelet denoising for signal enhancement.We also propose an optimized algorithm for data decomposition： the V-L decomposition method, which combines Vondrak smoothing and laser-template based fitting. Compared with conventional Gaussian decomposition, the new method brings an improvement in both precision and resolution of data decomposition. After applying V-L decomposition to the lidar system, we present the 3D reconstructed model to demonstrate the decomposition method.

Model-Based Systems Engineering Approach to Design a Human Settlement to Better Serve Displaced People

The challenge of transitioning from temporary humanitarian settlements to more sustainable human settlements is due to a significant increase in the number of forcibly displaced people over recent decades, difficulties in providing social services that meet the required standards, and the prolongation of emergencies. Despite this challenging context, short-term considerations continue to guide their planning and management rather than more integrated, longer-term perspectives, thus preventing viable, sustainable development. Over the years, the design of humanitarian settlements has not been adapted to local contexts and perspectives, nor to the dynamics of urbanization and population growth and data. In addition, the current approach to temporary settlement harms the environment and can strain limited resources. Inefficient land use and ad hoc development models have compounded difficulties and generated new challenges. As a result, living conditions in settlements have deteriorated over the last few decades and continue to pose new challenges. The stakes are such that major shortcomings have emerged along the way, leading to disruption, budget overruns in a context marked by a steady decline in funding. However, some attempts have been made to shift towards more sustainable approaches, but these have mainly focused on vague, sector-oriented themes, failing to consider systematic and integration views. This study is a contribution in addressing these shortcomings by designing a model-driving solution, emphasizing an integrated system conceptualized as a system of systems. This paper proposes a new methodology for designing an integrated and sustainable human settlement model, based on Model-Based Systems Engineering and a Systems Modeling Language to provide valuable insights toward sustainable solutions for displaced populations aligning with the United Nations 2030 agenda for sustainable development.

A Conceptual and Computational Framework for Aspect-Based Collaborative Filtering Recommender Systems

Many datasets in E-commerce have rich information about items and users who purchase or rate them. This information can enable advanced machine learning algorithms to extract and assign user sentiments to various aspects of the items thus leading to more sophisticated and justifiable recommendations. However, most Collaborative Filtering (CF) techniques rely mainly on the overall preferences of users toward items only. And there is lack of conceptual and computational framework that enables an understandable aspect-based AI approach to recommending items to users. In this paper, we propose concepts and computational tools that can sharpen the logic of recommendations and that rely on users’ sentiments along various aspects of items. These concepts include: The sentiment of a user towards a specific aspect of a specific item, the emphasis that a given user places on a specific aspect in general, the popularity and controversy of an aspect among groups of users, clusters of users emphasizing a given aspect, clusters of items that are popular among a group of users and so forth. The framework introduced in this study is developed in terms of user emphasis, aspect popularity, aspect controversy, and users and items similarity. Towards this end, we introduce the Aspect-Based Collaborative Filtering Toolbox (ABCFT), where the tools are all developed based on the three-index sentiment tensor with the indices being the user, item, and aspect. The toolbox computes solutions to the questions alluded to above. We illustrate the methodology using a hotel review dataset having around 6000 users, 400 hotels and 6 aspects.

Telematics as a Transformative Agent for the Zimbabwean Auto Insurance Ecosystem

Zimbabwe has witnessed the evolution of Information Communication Technology (ICT). The vehicle population soared to above 1.2 million hence rendering the Transport and Insurance domains complex. Therefore, there is a need to look at ways that can augment conventional Vehicular Management Information Systems (VMIS) in transforming business processes through Telematics. This paper aims to contextualise the role that telematics can play in transforming the Insurance Ecosystem in Zimbabwe. The main objective was to investigate the integration of Usage-Based Insurance (UBI) with vehicle tracking solutions provided by technology companies like Econet Wireless in Zimbabwe, aiming to align customer billing with individual risk profiles and enhance the synergy between technology and insurance service providers in the motor insurance ecosystem. A triangulation through structured interviews, questionnaires, and literature review, supported by Information Systems Analysis and Design techniques was conducted. The study adopted a case study approach, qualitatively analyzing the complexities of the Telematics insurance ecosystem in Zimbabwe, informed by the TOGAF framework. A case-study approach was applied to derive themes whilst applying within and cross-case analysis. Data was collected using questionnaires, and interviews. The findings of the research clearly show the importance of Telematics in modern-day insurance and the positive relationship between technology and insurance business performance. The study, therefore revealed how UBI can incentivize positive driver behavior, potentially reducing insurance premiums for safe drivers and lowering the incidence of claims against insurance companies. Future work can be done on studying the role of Telematics in combating highway crime and corruption.

Preliminary Study on the Effect of Different Ecological Cultivation Modes on the Water Stability of Soil Aggregates in Rubber Based Agroforestry Systems

Rubber trees (Hevea brasiliensis Müll. Arg.) have been commercially cultivated for a century and a half in Asia, particularly in China, and they constitute a common element of plantation ecosystems in tropical regions. Soil health is fundamental to the sustainable development of rubber plantations. The objective of the study is to explore the influence of different complex ecological cultivation modes on the stability of soil aggregates in rubber based agroforestry systems. In this study, the ecological cultivation mode of rubber—Alpinia oxyphylla plantation, the ecological cultivation mode of rubber—Phrynium hainanense plantations, the ecological cultivation mode of rubber—Homalium ceylanicum plantations and monoculture rubber plantations were selected, and the particle size distribution of soil aggregates and their water stability characteristics were analyzed. The soil depth of 0 - 20 cm and 20 - 40 cm was collected for four cultivation modes. Soil was divided into 6 particle levels > 20 cm. soil was divided into 6 particle levels > 5 mm, 2 - 5 mm, 1 - 2 mm, 0.5 - 1 mm, 0.25 - 0.5 mm, and 0.053 - 0.25 mm according to the wet sieve method. The particle size proportion and water stability of soil aggregates were determined by the wet sieve method. The particle size proportion and water stability of soil aggregates under different ecological cultivation modes were analyzed. The results showed that under different ecological cultivation modes in the shallow soil layer (0 - 20 cm), the rubber—Alpinia oxyphylla plantation and the rubber—Phrynium hainanense plantation promoted the development of dominant soil aggregates towards larger size classes, whereas the situation is the opposite for rubber—Homalium ceylanicum plantation. In soil layer (20 - 40 cm), the ecological cultivation mode of rubber—Phrynium hainanense plantation developed the dominant radial level of soil aggregates to the diameter level of large aggregates. Rubber—Alpinia oxyphylla plantation and rubber—Homalium ceylanicum plantation, three indicators, including the water-stable aggregate content R0.25 (>0.25 mm water-stable aggregates), mean weight diameter (MWD), and geometric mean diameter (GMD), were all lower than those in the rubber monoculture mode. However, in the rubber—Phrynium hainanense plantation, the water-stable aggregate content R0.25, mean weight diameter, and geometric mean diameter were higher than in the rubber monoculture mode, although these differences did not reach statistical significance.

A Systems Approach to Assessing Sustainability Capacity in Kalobeyei Refugee Settlement in Turkana County, Kenya

Refugee settlements face several challenges in transitioning from a temporary planning approach to more sustainable settlements. This is mainly due to an increase in the number of forcibly displaced people over the last few decades, and the difficulties of sustainably providing social services that meet the required standards. The development of refugee settlements assumed that forcibly displaced people would return to their places or countries of origin. Unfortunately, displacement situations are prolonged indefinitely, forcing these people to spend most of their lives in conditions that are often deplorable and substandard, and therefore unsustainable. In most cases, the establishment of refugee settlements is triggered by an emergency caused by an influx of forcibly displaced people, who need to be accommodated urgently and provided with some form of international assistance and protection. This leaves little or no time for proper planning for long-term development as required. In addition, the current approach to temporary settlement harms the environment and can strain limited resources with ad hoc development models that have exacerbated difficulties. As a result, living conditions in refugee settlements have deteriorated over the last few decades and continue to pose challenges as to how best to design, plan, and sustain settlements over time. To contribute to addressing these challenges, this study proposes a new methodology supported by Model-Based Systems Engineering (MBSE) and a Systems Modeling Language (SysML) to develop a typical sustainable human settlement system model, which has functionally and operationally executed using a Systems Engineering (SE) approach. To assess the sustainability capacity of the proposed system, this work applies a matrix of crossed impact multiplication through a case study by conducting a system capacity interdependence analysis (SCIA) using the MICMAC methodology (Cross-impact matrix multiplication applied to classification) to assess the interdependency that exist between the sub-systems categories to deliver services at the system level. The sustainability analysis results based on capacity variables influence and dependency models shows that development activities in the settlement are unstable and, therefore, unsustainable since there is no apparent difference between the influential and dependent data used for the assessment. These results illustrate that an integrated system could improve human settlements’ sustainability and that capacity building in service delivery is beneficial and necessary.

An immune system based differential evolution algorithm using near-neighbor effect in dynamic environments

Many real-world problems are dynamic, requiring optimization algorithms being able to continuously track changing optima （optimum） over time. This paper proposes an improved differential evolutionary algorithm using the notion of the near-neighbor effect to determine one individuals neighborhoods, for tracking multiple optima in the dynamic environment. A new mutation strategy using the near-neighbor effect is also presented. It creates individuals by utilizing the stored memory point in its neighborhood, and utilizing the differential vector produced by the ＇near- neighbor-superior＇ and ＇near-neighbor-inferior＇. Taking inspirations from the biological immune system, an immune system based scheme is presented for rapidly detecting and responding to the environmental changes. In addition, a difference- related multidirectional amplification scheme is presented to integrate valuable information from different dimensions for effectively and rapidly finding the promising optimum in the search space. Experiments on dynamic scenarios created by the typical dynamic test instance--moving peak problem, have demonstrated that the near-neighbor and immune system based differential evolution algorithm （NIDE） is effective in dealing with dynamic optimization functions.

Algorithm for Calculating Torque Base in Vehicle Traction Control System

Existing research on the traction control system（TCS） mainly focuses on control methods, such as the PID control, fuzzy logic control, etc, aiming at achieving an ideal slip rate of the drive wheel over long control periods. The initial output of the TCS （referred to as the torque base in this paper）, which has a great impact on the driving performance of the vehicle in early cycles, remains to be investigated. In order to improve the control performance of the TCS in the first several cycles, an algorithm is proposed to determine the torque base. First, torque bases are calculated by two different methods, one based on states judgment and the other based on the vehicle dynamics. The confidence level of the torque base calculated based on the vehicle dynamics is also obtained. The final torque base is then determined based on the two torque bases and the confidence level. Hardware-in-the-loop（HIL） simulation and vehicle tests emulating sudden start on low friction roads have been conducted to verify the proposed algorithm. The control performance of a PID-controlled TCS with and without the proposed torque base algorithm is compared, showing that the proposed algorithm improves the performance of the TCS over the first several cycles and enhances about 5% vehicle speed by contrast. The proposed research provides a more proper initial value for TCS control, and improves the performance of the first several control cycles of the TCS.

Reliability Analysis of Controller Area Network Based Systems—A Review

This paper reviews the research work done on the Reliability Analysis of Controller Area Network (CAN) based systems. During the last couple of decades, real-time researchers have extended schedulability analysis to a mature technique which for nontrivial systems can be used to determine whether a set of tasks executing on a single CPU or in a distributed system will meet their deadlines or not [1-3]. The main focus of the real-time research community is on hard real-time systems, and the essence of analyzing such systems is to investigate if deadlines are met in a worst case scenario. Whether this worst case actually will occur during execution, or if it is likely to occur, is not normally considered. Reliability modeling, on the other hand, involves study of fault models, characterization of distribution functions of faults and development of methods and tools for composing these distributions and models in estimating an overall reliability figure for the system [4]. This paper presents the research work done on reliability analysis developed with a focus on Controller-Area-Network-based automotive systems.

Innovative Artificial Neural Networks-Based Decision Support System for Heart Diseases Diagnosis

Heart diagnosis is not always possible at every medical center, especially in the rural areas where less support and care, due to lack of advanced heart diagnosis equipment. Also, physician intuition and experience are not always sufficient to achieve high quality medical procedures results. Therefore, medical errors and undesirable results are reasons for a need for unconventional computer-based diagnosis systems, which in turns reduce medical fatal errors, increasing the patient safety and save lives. The proposed solution, which is based on an Artificial Neural Networks (ANNs), provides a decision support system to identify three main heart diseases: mitral stenosis, aortic stenosis and ventricular septal defect. Furthermore, the system deals with an encouraging opportunity to develop an operational screening and testing device for heart disease diagnosis and can deliver great assistance for clinicians to make advanced heart diagnosis. Using real medical data, series of experiments have been conducted to examine the performance and accuracy of the proposed solution. Compared results revealed that the system performance and accuracy are acceptable, with a heart diseases classification accuracy of 92%.

Educational Advisor System Implemented by Web-Based Fuzzy Expert Systems

Using of the Internet technology and the field of Fuzzy expert systems has proposed new branches of sharing and distributing knowledge. However, there has been a general lack of investigation in the area of web-based Fuzzy expert systems (FES). In this paper the issues associated with the design, development, and use of web-based FES from a standpoint of the benefits and challenges of developing and using them. The original theory and concepts in conventional FES were reviewed and a knowledge engineering framework for developing them was revisited. Student in an educational place need an educational advisor for solve problems. Some of educational circulars order changing because advisor must update information away. The student's request is linguistic and crisp Expert System cannot solve problems completely. In my approach we build Web-Based Fuzzy Expert System for Student Education Advisor (FES-SEA) and stays in university portal. This system implemented with ASP.NET, SQL-SERVER 2008.

Effect of Heat-Treatment Process on Properties of Rare Earth Mg-Based System Hydrogen Storage Alloys with AB_3-Type

The effect of heat-treatment process on the properties of Mm0.8Mg0.2(NiCoAlMn)3.5 hydrogen storage alloy was discussed . The electrochemical properties such as cycling stability, activation property, and the plateau voltage of the alloy which was heat-treated in various temperatures and times had different changes during the cycle process, the optimum heat-treatment conditions of this alloy were determined by this work.

A Partial Parallel Airport Gate Assignment Supported by a Knowledge－based System Combined with Mathematical Programming

The gate assignment at an airport is one of the major activities in airport operations.With the increase of passenger traffic volumes and the number of flights, the complexity of this task and the factors to be considered have increased significantly, and an efficient gate utilizationhas received considerable attention. For overcoming the shortcomings of previous gate assignmentapproaches, this paper presents a partial parallel gate assignment approach, by which more factorsconcerning aircraft and gates can be collsidered at the same time. This paper also presents themethod of using a knowledge-based system combined with a mathematical programming method forgetting an optimized feasible assignment solution. By this way, it is more easily to get the solutionthat satisfies both the static and dynamic situations,and thus it may adapt well to meet the needsof actual use to rea-time operations. An experimental prototype has been implemented, and a casestudy is presented at the end of the paper.

Personalized Service System Based on Hybrid Filtering for Digital Library

Personalized service systems are an effective way to help users obtain recommendations for unseen items, within the enormous volume of information available based on their preferences. The most commonly used personalized service system methods are collaborative filtering, content-based filtering, and hybrid filtering. Unfortunately, each method has its drawbacks. This paper proposes a new method which unified partition-based collaborative filtering and meta-information filtering. In partition-based collaborative filtering the user-item rating matrix can be partitioned into low-dimensional dense matrices using a matrix clustering algorithm. Recommendations are generated based on these low-dimensional matrices. Additionally, the very low ratings problem can be solved using meta-information filtering. The unified method is applied to a digital resource management system. The experimental results show the high efficiency and good performance of the new approach.