《人体解剖组织学》基于学的实验教学设计

"授之以鱼不如授之以渔"已被大部分职业学校老师达成共识,但课堂教学中教师"一统天下"的情况还屡见不鲜。学生在课堂上被动执行教师的"指令",缺乏实质性的参与,学生在课堂学习中的主体地位没有真正体现。改变这种现状,教师要转变教学理念,从教学设计着手,将"基于教"转向"基于学"。基于学的教学设计,老师是组织者、引导者,学生是学习活动的主体,学校要为基于学的教学设计提供良好的环境,使学生成为真正的学习主宰者。

卫生职业学校教学管理从“基于教”向“基于学”转变的策略

教学管理从"基于教"向"基于学"转变是新时期赋予卫生职业学校课程改革的重任,对教师、学生和学校提出了更高要求。教师要成为"基于教"向"基于学"转变的设计者与实践者;学生要具备适应"基于教"向"基于学"转变的基本素养;学校要创造良好的"基于教"向"基于学"转变的教学环境,努力为医疗卫生单位培养发展型、复合型和创新型卫生技术专门人才。

“基于学”的五年制高职数学教学实施策略

新课程的核心理念就是一切为了学生的学习和发展,在五年制高职数学教学中,坚持采用'基于学'的教学方法,以五年制高职生的职业发展为导向,结合学生学情,合理设计教学内容和教学环节,是提升五年制高职数学教学效果的有效途径。

“基于学”为中心的初中物理课堂教学模式实践分析

文章主要分析了“基于学”模式的教学概念，同时阐述了“基于学”模式下初中教学的具体开展，最后总结了“基于学”模式主要存在的问题，旨在加强新模式的推广和应用，改变当前学生学习兴趣低下的问题，全面提高初中物理的学习质量。

以常规催化学习,用习题激发思维

教学是一个统一体,教是为了学,学会是目的,常规是一种手段。因此,在课堂教学中,落实学、改进教;立足学,多磨题;基于学,研究考;面向学,优作业是当下课堂常规改革的重要环节。教师做到眼中有学生、心中有学生,就会多一份神圣感,多一份责任感,多一份创造感,多一份幸福感。所以,在日常常规教学中,每一位科学教师都力求对习题能有更深刻理解与拓展、能掌握更多适合科学课的的教学方法。

IMPROVED AERODYNAMIC APPROXIMATION MODEL WITH CASE-BASED REASONING TECHNIQUE FOR MDO OF AIRCRAFT

To increase the efficiency of the multidisciplinary optimization of aircraft, an aerodynamic approximation model is improved. Based on the study of aerodynamic approximation model constructed by the scaling correction model, case-based reasoning technique is introduced to improve the approximation model for optimization. The aircraft case model is constructed by utilizing the plane parameters related to aerodynamic characteristics as attributes of cases, and the formula of case retrieving is improved. Finally, the aerodynamic approximation model for optimization is improved by reusing the correction factors of the most similar aircraft to the current one. The multidisciplinary optimization of a civil aircraft concept is carried out with the improved aerodynamic approximation model. The results demonstrate that the precision and the efficiency of the optimization can be improved by utilizing the improved aerodynamic approximation model with ease-based reasoning technique.

Active learning based on maximizing information gain for content-based image retrieval

This paper describes a new method for active learning in content-based image retrieval. The proposed method firstly uses support vector machine (SVM) classifiers to learn an initial query concept. Then the proposed active learning scheme employs similarity measure to check the current version space and selects images with maximum expected information gain to solicit user's label. Finally, the learned query is refined based on the user's further feedback. With the combination of SVM classifier and similarity measure, the proposed method can alleviate model bias existing in each of them. Our experiments on several query concepts show that the proposed method can learn the user's query concept quickly and effectively only with several iterations.

EVALUATION OF ELECTROMAGNETIC SCATTERING OF TWO DIMENSIONAL CONDUCTING OBJECTS--TE CASE

A hybrid technique is developed for the evaluation of two dimensional electromagnetic scattering from electrically large conducting bodies with cracks on their surfaces (TE case). The edge based finite element method (FEM) is employed to compute the scattering from the cracks. Physical optics (PO) and physical theory of diffraction (PTD) are utilized to evaluate the scattering from the large bodies with the cracks filled with perfect conductors. These two methods are combined by an efficient coupling scheme. Some of numerical results are presented. It is shown that the hybrid technique has some advantages over other methods in regard to saving computer memory units and CPU time.

ID-based Key-insulated Authenticated Key Agreement Protocol

The basic idea behind an ID-based cryptosystem is that end user's public key can be determined by his identity information.Comparing with the traditional certificate-based cryptography,identity-based cryptography can eliminate much of the overhead associated with the deployment and management of certificate.However,exposure of private keys can be the most devastating attack on a public key based cryptosystem since such that all security guarantees are lost.In this paper,an ID-based authenticated key agreement protocol was presented.For solving the problem of key exposure of the basic scheme,the technique of key insulation was applied and a key insulated version is developed.

Characteristics and outcomes of cholangiocarcinoma by region in Thailand: A nationwide study

AIM To identify the potential risk factors of cholangiocarcinoma, we determined the characteristics of cholangiocarcinoma patients among 5 different regions of Thailand. METHODS All patients diagnosed with cholangiocarcinoma between 2008 and 2013 were identified using the Nationwide Hospital Admission Data registry(n = 39421). Baseline characteristics, comorbidities and survival were abstracted. RESULTS The annual incidence during the study period was stable in all regions. Most patients lived in the Northeast(62.8%), followed by the North(16.9%), Central(12.3%), Bangkok(5.4%), and South(n = 2.6%) regions(P < 0.0001). Significantly more cholangiocarcinoma patients had diabetes, cirrhosis, and chronic viral hepatitis B/C infection than noncholangiocarcinoma participants(diabetes: 11.42% vs 5.28%; cirrhosis: 4.81% vs 0.92%; hepatitis B: 0.74% vs 0.12%; and hepatitis C: 0.50% vs 0.10%, P < 0.0001 for all, respectively). The overall 1-year mortality rate was 81.7%, with a stable trend over time. CONCLUSION Diabetes and chronic liver diseases may be associated with cholangiocarcinoma in the Thai population.

An Approach to Underwater Image Enhancement Based on Image Structural Decomposition

Underwater imaging posts a challenge due to the degradation by the absorption and scattering occurred during light propagation as well as poor lighting conditions in water medium Although image filtering techniques are utilized to improve image quality effectively, problems of the distortion of image details and the bias of color correction still exist in output images due to the complexity of image texture distribution. This paper proposes a new underwater image enhancement method based on image struc- tural decomposition. By introducing a curvature factor into the Mumford_Shah_G decomposition algorithm, image details and struc- ture components are better preserved without the gradient effect. Thus, histogram equalization and Retinex algorithms are applied in the decomposed structure component for global image enhancement and non-uniform brightness correction for gray level and the color images, then the optical absorption spectrum in water medium is incorporate to improve the color correction. Finally, the en- hauced structure and preserved detail component are re.composed to generate the output. Experiments with real underwater images verify the image improvement by the proposed method in image contrast, brightness and color fidelity.

Content-based Instruction in Foreign Language Learning

Abstract. In recent years content-based instruction has become increasingly popular as a means of developing linguistic ability. It has strong connections to project work, task-based learning and a holistic approach to language instruction and has become particularly popular within the state school secondary （11 - 16 years old） education sector. This paper discusses about the definition, types, ways to create a CBI lesson, advantages and the problems of CBI, as well as the assessment of CBI.

Object detection of artifact threaded hole based on Faster R-CNN

In order to improve the accuracy of threaded hole object detection,combining a dual camera vision system with the Hough transform circle detection,we propose an object detection method of artifact threaded hole based on Faster region-ased convolutional neural network(Faster R-CNN).First,a dual camera image acquisition system is established.One industrial camera placed at a high position is responsible for collecting the whole image of the workpiece,and the suspected screw hole position on the workpiece can be preliminarily selected by Hough transform detection algorithm.Then,the other industrial camera is responsible for collecting the local images of the suspected screw holes that have been detected by Hough transform one by one.After that,ResNet50-based Faster R-CNN object detection model is trained on the self-built screw hole data set.Finally,the local image of the threaded hole is input into the trained Faster R-CNN object detection model for further identification and location.The experimental results show that the proposed method can effectively avoid small object detection of threaded holes,and compared with the method that only uses Hough transform or Faster RCNN object detection alone,it has high recognition and positioning accuracy.

Fuzzy-second order sliding mode control optimized by genetic algorithm applied in direct torque control of dual star induction motor

The direct torque control of the dual star induction motor(DTC-DSIM) using conventional PI controllers is characterized by unsatisfactory performance, such as high ripples of torque and flux, and sensitivity to parametric variations. Among the most evoked control strategies adopted in this field to overcome these drawbacks presented in classical drive, it is worth mentioning the use of the second order sliding mode control(SOSMC) based on the super twisting algorithm(STA) combined with the fuzzy logic control(FSOSMC). In order to realize the optimal control performance, the FSOSMC parameters are adjusted using an optimization algorithm based on the genetic algorithm(GA). The performances of the envisaged control scheme, called G-FSOSMC, are investigated against G-SOSMC, G-PI and BBO-FSOSMC algorithms. The proposed controller scheme is efficient in reducing the torque and flux ripples, and successfully suppresses chattering. The effects of parametric uncertainties do not affect system performance.

Coupling of an Individual-Based Model of Anchovy with Lower Trophic Level and Hydrodynamic Models

Anchovy （Engraulis aponicus）, a small pelagic fish and food of other economic fishes, is a key species in the Yellow Sea ecosystem. Understanding the mechanisms of its recruitment and biomass variation is important for the prediction and management of fishery resources. Coupled with a hydrodynamic model （POM） and a lower trophic level ecosystem model （NEMURO）, an individual-based model of anchovy is developed to study the influence of physical environment on anchovy＇s biomass variation, Seasonal variations of circulation, water temperature and mix-layer depth from POM are used as external forcing for NEMURO and the anchovy model. Biomasses of large zooplankton and predatory zooplankton which anchovy feeds on are output from NEMURO and are controlled by the consumption of anchovy on them. Survival fitness theory related to temperature and food is used to determine the swimming action of anchovy in the model. The simulation results agree well with observations and elucidate the influence of temperature in over-wintering migration and food in feeding migration.

General and robust voxel feature learning with Transformer for 3D object detection

The self-attention networks and Transformer have dominated machine translation and natural language processing fields,and shown great potential in image vision tasks such as image classification and object detection.Inspired by the great progress of Transformer,we propose a novel general and robust voxel feature encoder for 3D object detection based on the traditional Transformer.We first investigate the permutation invariance of sequence data of the self-attention and apply it to point cloud processing.Then we construct a voxel feature layer based on the self-attention to adaptively learn local and robust context of a voxel according to the spatial relationship and context information exchanging between all points within the voxel.Lastly,we construct a general voxel feature learning framework with the voxel feature layer as the core for 3D object detection.The voxel feature with Transformer(VFT)can be plugged into any other voxel-based 3D object detection framework easily,and serves as the backbone for voxel feature extractor.Experiments results on the KITTI dataset demonstrate that our method achieves the state-of-the-art performance on 3D object detection.

Object-based Classification of Baltic Sea Ice Extent and Concentration in Winter 2011

The Baltic Sea is a brackish, mediterranean sea located in the middle latitudes of Europe. It is seasonally covered with ice. The ice covered areas during a typical winter are the Bothnian Bay, the Gulf of Finnland and the Gulf of Riga. Sea ice plays an important role in dynamic and thermodynamic processes and also has a strong impact on the heat budget of the sea. Also a large part of transport goes by sea, and there is a need to create ice charts to make the marine transport safe. Because of high cloudiness in winter season and small amount of light in the northern part of the Baltic Sea, radar data are the most important remote sensing source of sea ice information. The main goal of the following studies is classification of the Baltic sea ice cover using radar data. The ENVISAT ASAR （Advanced Synthetic Aperture Radar） acquires data in five different modes. In the following studies ASAR Wide Swath Mode data were used. The Wide Swath Mode, using the ScanSAR technique provides medium resolution images （150 m） over a swath of 405 kin, at HH or VV polarization. In following work data from February 13th, February 24th and April 6th, 2011, representing three different sea ice situations were chosen. OBIA （object-based image analysis） methods and texture parameters were used to create sea ice extent and sea ice concentration charts. Based on object-based methods, it can separate single sea ice floes within the ice pack and calculate more accurately sea ice concentration.

The Use of PBL （Problem-Based Learning） in Improving the Student Performance in Navigation 3 （Terrestrial and Coastal Navigation）

This quasi-experimental study aimed at looking into the effectiveness of PBL （problem-based learning） in improving the performance in Navigation 3 （terrestrial and coastal navigation） of BSMT （Bachelor of Science in Marine Transportation） second year students at JBLFMU-Arevalo during the first semester of school year 2016-2017. The respondents of this research were the two sections comparable with each other who was enrolled in the subject Navigation 3. There were 60 student respondents composed of 30 in the experimental group and 30 in the control group. A validated three item teacher-made problem solving test with 10 points for each correct answer was used as an instrument. The dependent variable was the scores in Navigation 3 and independent variable was the PBL approach. The statistical tools used were mean, standard deviation, Mann-Whitney test, and Wilcoxon-Signed ranks test set at 0.05 level of significance. The effect size was computed to determine the effectiveness of the PBL approach in terms of students＇ performance in Navigation 3. Results showed that in the pretest, though the experimental group had a higher mean than the control group, the Mann-Whitney test showed that the mean scores of the two groups were comparable because the significant value was greater than 0.05. When the treatment was introduced, findings showed that there were significant differences in the Navigation 3 performance in the pretest and posttest of experimental and control groups as well as in the posttests of both groups. It could be inferred that the better performance of the experimental group could be attributed to the intervention where the students were actively involved in the learning process.

Using Icons in a Knowledge Based System for Traditional Medicine

MedTrad＋ is an expert system for African Traditional Medicine where actors are often illiterate. Its originality lies in the use of icons instead of textual content of facts. It has been created by GExpert＋ which is An Expert system Generator based on the use of icons in a Web environment. With its iconic interface GExpert＋ allows any user to overcome any intermediary for the management and the use of its knowledge base. Traditional healers from Yamoussoukro region are working toward its validation.

PRINCIPLE, CONSTRUCTION AND KINEMATIC ANALYSIS FOR THE OMNIDIRECTIONAL MOBILE ROBOT——ICE-SKATER ROBOT

Three main basic types of locomotion for a mobile robot were introduced and the advantages and disadvantages of a legged mobile robot, a wheeled mobile robot and an articulated mobile robot were also discussed. A new type of leg wheeled mobile robot was introduced which combines the adaptability of legged robot with the stability of wheeled robot. On the basis of the structure of the wheels, the paper described the principle of the ice skater robot developed from Roller walker and ALDURO and its construction. The paper also established an inertia coordinate system and a wheel coordinate system, and analyzed the configuration or the posture and the related kinematic constraints of the robot according to some assumptions. Based on the motion principle, a logic based coordinated control system and corresponded flowchart were designed. At last, taking the ice skater robot as an example the paper expounded its application and the actual experiment proved its feasibility.