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Nowadays the use of ultrasound (US) is mandatory in order to reduce the number of complications and to increase the safety and quality of central venous catheter (CVC) placement. For clinical practice, a systematic approach for US-guided central venous access placement is recommended. It includes maintaining the absolute sterility of the surgical field and of the whole instrumentation, assessing the target vein (anatomy and vessel localization, vessel patency), using US guidance for puncture of the vein, and confirming the correct needle, wire, and catheter position in the vein. Small linear array probes with high-frequency transducers allowing 2D high-resolution imaging are required. Static and real-time US can be used to visualize the anatomy and patency of the target vein. US-guided needle advancement can be performed in an “out-of-plane” and an “in-plane” technique depending on the operator level of experience and the complexity of the anatomical relation between the vein and the artery. In summary, the knowledge from anatomic landmark techniques and the knowledge from US-guided CVC placement need to be combined and integrated in order to achieve the best skill level for CVC placement.

Of the three skills needed to play esports, Mechanical Skills, Awareness Skills and Cognitive Skills, this paper focusses on Cognitive Skills. This paper examines how the Cognitive Skills needed by esports player to move from intermediate player to expert player can be improved by exercise. It takes lessons learned from pro players and recognises a need for grassroots player to start good habits around exercise early. It outlines a study done with 109 12–18 year old students to establish once incentivised by the knowledge that exercise improves cognitive skills which improves player skill level, what sort of exercise would encourage them to overcome the barriers they have to taking exercise after every 30 min of play. The paper then goes on to propose how grassroots esports can be supported in the endeavour to encourage exercise breaks as a standard grassroots activity in much the same way as other grassroots sports do in weekend or after school training.

This paper carries out the design and development of digital music teaching assistant system based on computer application technology. The system analyzes students’ video, audio, physiology and other related information in detail, and stores the specific training status to the database in an all-round way to test the real-time changes of skill level. It has been proved by practice that this system can not only provide more visual information and all parameters for teaching and training, but also transform the theory and method of skills into vivid image data information. It can also significantly improve the rationality of music skill training and the efficiency of skill learning, which is worth promoting and applying.

Many universities have started to adopt online programming tools to support students’ programming practice, yet the services currently offered by the existing tools are somewhat passive with respect to considering a student’s programming skill level and providing appropriate code questions. To enhance students’ learning experience and improve their programming skills, it would be helpful to examine students’ programming abilities and provide them with the most suitable code questions and guidelines. Machine learning can play a role in modeling the level of students’ programming skills as well as the difficulty of questions by taking the students’ programming experience and code submissions into account. This paper presents a study on the development of machine learning models to classify the levels of students’ programming skills and those of programming questions, based on the data of students’ code submissions. We extracted a total of 197 features of code quality, code readability and system time. We used those features to build classification models. The model for the student level (four classes) and the question level (five classes) yielded 0.60 and 0.82 F1-scores, respectively, showing reasonable classification performance. We discuss our study highlights and their implications, such as group and question matching based on code submissions and user experience improvement.

The Australian food industry is vast in its operations and opportunities. It is an industry that can cater to the career or employment needs of almost any person, with almost any skill level and capability. It offers opportunities for unskilled workers as well as for those highly skilled and highly educated. This industry is therefore uniquely placed for the opportunities it offers for the wide range of communities it services.

The lead author has in this decade been studying the processes of creating and transferring multinational IT service knowledge among the headquarters of a global IT Service firm in Japan and the firm’s local subsidiaries in China and APAC regions. Key findings of the preceding studies are, (1) the average of Project Managers’ skill level in China and APAC regions has already reached to the global average determined in the standardized PM skill assessment within the global firm. (2) IT service project managers’ value systems are highly influenced by those of organization the PMs belong to, and the value systems vary not only by nations but also by industries. (3) To transfer knowledge from HQ to overseas subsidiaries in China and APAC regions, especially in the case that the knowledge to be transferred is extremely new and unfamiliar to the knowledge transferees (i.e., local PMs), it is better for the knowledge transferrers from HQs to consider the differences between the value systems of the transferrer and the transferee.

Programming is increasingly introduced in secondary schools, both as a stand-alone subject or integrated into other subjects, leading to growing attention to the training of in-service teachers. Teachers need to learn both (a) how to program and (b) how to teach programming, often in the context of different disciplines. The paper explores the impact of a university-level training program offered to in-service teachers, with a focus on teachers’ self-efficacy in teaching programming. The paper reports the interviews with ten teachers after about one year they have completed the program. The results indicate that the training has improved teachers’ self-efficacy, and the impact is lasting in time. Also, some teachers expressed concerns about their skill level in programming, but this does not necessarily associate with lower self-efficacy in teaching programming. The paper presents the results from the study and some implications for the design of training of in-service programming teachers.

Ultrasound-guided needle insertion is a difficult skill to learn and, in the context of competency-based medical education, requires continual monitoring of trainees’ performance. This work investigates two standard neural network architectures, temporal convolutional networks and long short-term memory networks, for automated classification of skill level based on kinematics data. It examines which data representations are optimal for skills assessment using the proposed architectures in low data scenarios. The data representation had significant effect on the computed results. But given the optimal data representation, the proposed architectures achieve skills classification on two simulated ultrasound-guided needle insertion tasks with better performance than summary statistics. Thus, neural networks can be an effective tool for skills assessment in ultrasound-guided interventions; however, it is recommended to search over the space of data representations when limited data is available.

The paper considers the main problems of introduction of digital economy technologies to activities of companies in order to create their sustainable competitive advantage. Technologies and tools of the digital economy compel companies to reconceive customary standards of doing business and traditional business processes. Digital ecosystems and innovative business models are coming to the forefront. In a number of industries and scopes of activities, including the company’s retail network, modern consumers value convenience and environmental friendliness. They demand personalized approach and seek to save their time. The need for being aware of the latest technological trends and using every opportunity to make their businesses more efficient and competitive forces retailers to develop their own competence in the field of designing and introduction of the digital economy solutions. The choice of digital economy technologies in network retail is defined by financial capabilities of companies, the expected effect of the solution introduced, the level of technological development in the industry (country), the skill level of personnel, the process of organizing of introduction. The scientific article discusses the main changes and characteristics of the competitive environment of modern companies in the context of the digital economy. The paper provides the main solutions and objectives of the introduction of digital economy technologies in the company of network retail, as well as recommendations for their development in order to improve competitiveness and meet the needs of consumers of network companies.

Introduction: Surgeons’ cognitive workload should be controlled during a surgical intervention for a successful and safe performance. Eye tracking technologies could be used for cognitive workload monitoring by analyzing the pupil size and blink frequency of surgeons. This work aims to study the surgeons’ cognitive workload watching an advanced laparoscopic video. Methods: 16 surgeons (5 experts, 11 novices) participated in the study watching a colectomy video consisting of eight steps with introductory titles. Surgeons’ gaze was recorded with eye tracking glasses while visualizing the video, from which pupil size and blink frequency were analyzed. Results: Pupil diameter of surgeons increased during the visualization of steps and decreased during the titles. Two specific steps of the intervention produced the highest pupil diameter of surgeons. When the pupil diameter increased the blink frequency decreased. Pupil diameter tended to decrease as the video is watched, which is mainly due to expert surgeons, who had a lower pupil diameter than novices. Conclusions: Eye tracking technologies allow monitoring the cognitive workload of surgeons in surgical procedures. Larger pupil size and shorter blink frequency means greater cognitive workload. Such metrics could be used to objectively label the difficult tasks within the surgical procedure. Surgical videos used for training of surgeons should be short, according to micro-learning, since cognitive workload decreases over time while visualizing them. Based on proposed metrics, eye tracking technologies could be used to distinguish the level of experience of surgeons, since cognitive workload is sensitive to the skill level of surgeons.

Many resources exist on how to optimize IUD service delivery and guide clinics in developing IUD programs and training providers. Implementing IUD services will go more smoothly if all stakeholders are involved and all clinic staff members are operating at their highest skill level. Clinics can streamline access to adolescents’ and young adults’ preferred method by optimizing clinic-wide training in IUD counseling, skills, and clinic flow. Having a standardized approach to IUD insertion and removal procedures, which takes into account both the behavioral components and cognitive reasoning for these, helps providers to improve standard IUD provision for adolescents and young adults, and to work through complications if they arise. This chapter will help readers to identify initial steps to establish readiness for introducing IUD services into an adolescent and young adult practice, as well as how to access proctoring supervision in order to successfully insert and remove IUDs. Detailed steps for IUD set-up, placement, and removal are outlined, along with guidelines on compiling supplies and materials necessary for IUD procedures.

Part 6: Wearable and Tangible Interaction; International audience; The same dance can give different impressions depending on the way the dancers convey their own emotions and personality through their interpretation of the dance. Beginner dancers who are teaching themselves often search for dance videos online that match their own personality in order to practice and mimic them, but it is not easy to find a dance that suits their own personality and skill level. In this work, we examined hip-hop dance to determine whether it is possible to identify one’s own dance from skeleton information acquired by Kinect and whether it is possible to mechanically extract information representing the individuality of dance. Experimental results showed that rich experienced dancers could distinguish their own dances by only skeleton information, and it was also possible to distinguish from averaged skeletal information. Furthermore, we generated features from the skeletal information of dance and clarified that individual dance can be distinguished accurately by machine learning.

Using highly interactive systems like computer games requires a lot of visual activity and eye movements. Eye movements are best characterized by visual fixation – periods of time when the eyes stay relatively still over an object. We analyzed the distributions of fixation duration of professional athletes, amateur and newbie players. We show that the analysis of fixation durations can be used to deduce the skill level in computer game players. Highly skilled gaming performance is characterized by more variability in fixation durations and by bimodal fixation duration distributions suggesting the presence of two fixation types in high skill gamers. These fixation types were identified as ambient (automatic spatial processing) and focal (conscious visual processing). The analysis of computer gamers’ skill level via the analysis of fixation durations may be used in developing adaptive interfaces and in interface design.

Continuing the discussion of the interviewees’ accounts, this chapter looks at issues relating to the workplace in Armenia and abroad, including the challenge of finding work that is commensurate to education and skill level. This can be a difficult transition, different and arguably more arduous compared to moving from education-to-work in other countries. For those who remain in Armenia, there may be limited opportunities for professional development, while moving abroad brings with it risk and uncertainty. The interviewees provide illustrations of different aspects of transitions-to-work at home and abroad, including managing expectations when seeking employment in Armenia, and while the idea of moving abroad to work is popular, relatively few of our interviews have encountered success after leaving.

One of the most challenging goals in the game industry is to design games which are difficult enough to be a fun challenge but not so hard to provoke frustration among a wide range of different types of players. Dynamic difficulty adjustment (DDA) is a set of techniques used to customize the difficulty of a game according to the skill level of the player so that the game can keep the player “flowing”.

Crowdsourcing platforms are frequently employed to collect answers from numerous participants on the Internet, e.g., Amazon Mechanical Turk. Different participants may have different answers for the same question. This cause unexpected aggregated answers. The accuracy of aggregated answers depends on answer quality. Answer quality varies by skill level of participants. In crowdsourcing, participants are defined as workers. Existing studies always characterize worker quality with their skills. However, the personality features of individual persons may have significant impact on the quality of their answers, e.g. worker emotion and worker intent. To this end, aggregating answers without taking into account the personality characteristics of persons may lead to unexpected results. To fill the gap this paper employs an improved EM-based approach for answer aggregation based on the answer data of workers and considering personality characteristics. The approach not only aggregates answers but also simultaneously estimates the skill level of each worker, worker emotion, worker intent and the difficulty of the task. Last but not least, the verification is conducted on real-world datasets Affect Text and simulation datasets.

The trend in education is not to focus on the knowledge, but on the skills, which are essential for every pupil. There are a lot of various skills; some of them are to be developed primarily in science education. Science education has the common feature—the experiment that can also be used for the pupils’ skills development. The integral part of improving the skill is the measurement of progress and the skill level development. The aim of the paper is to present the development and the pilot testing of a measurement tool for selected skills that is suitable for the lower secondary education (the age of the target group is 10–15). The skills are: making predictions, following directions and working with data tables. We assume the skills are suitable for the lower secondary education, and they can be easily improved in the physics classrooms via hands-on activities and experiments. After selecting the skill, levels of each skill were defined. The level of enhancement was determined according to the literature and our teaching experiences. At first, we analysed the physics textbook from the view of selected skills, so we can assume the skills could be developed in the physics education. Also, teachers had to be trained for such an action. Teachers stated they wanted more activities focused on the skills fostering. However, there is also a need for the feedback and the measurement tool of the efficiency of the teaching method. To test the efficiency of the method, we created the measurement tool that is focused on the selected skills. It has a form of the test for pupils. Several tests of integrated process skills were used as a basis and the inspiration for tasks. The tasks, as well as the whole test, were prepared in a playful and informal way, so the pupils felt comfortable when they were solving the worksheet. The test items have a form of the application of the skills in real life situations. The pilot testing was conducted at the selected lower secondary schools in Slovakia. The results from the pilot testing were used to specify the skill levels more precisely. From the evaluation, we can also see the current level of the skills and determine the prospective norm for following tests of skill development.

The key principles and tactics of addressing severely wounded persons in battle are delineated in Tactical Combat Casualty Care (TCCC). However, whereas the military setting affords a mostly homogenous group of patients within a very unique care environment, the civilian sector is comprised of a wide array of patient demographics with disparate mechanisms of injury. Thus, the principles of TCCC have been translated for the civilian sector as delineated in the Tactical Emergency Casualty Care (TECC) guidelines. TECC takes into account the skill level of the provider – ranging from the bystander to the surgeon – the environment of care, and threat level associated with it and addresses all causes of potentially preventable death, including hemorrhage, pneumothorax, and loss of airway. It stresses that the greatest opportunity to mitigate preventable death is rapid extrication of the wounded to a facility able to provide definitive care.

Reconstruction of full face or total cheek burns is a difficult task for a surgeon of any skill level. Lack of adequate healthy local tissue, significant differences in skin texture, color, and thickness of distal transplants, and the complex anatomical composition of the face lead surgeons to constantly search for new surgical methods to improve surgical outcomes. Many strategies have been implemented over the years allowing us to compare the outcomes of various techniques and to perform the most effective operations. For total deformed cheek restoration, the flap should be large, thin, sensate, and pliable, and should match the color of the surrounding healthy skin. Neck skin fits all of these criteria better than any other sources. It usually takes two stages to cover a total cheek burn. A step-by-step approach is described in this chapter.

Current research on performance awareness evaluates approaches primarily for their functional correctness but does not assess to what extent developers are supported in improving software implementations. This article presents the evaluation of an existing approach for supporting developers of Java Enterprise Edition (EE) applications with response time estimations based on a controlled human-oriented experiment. The main goal of the experiment is to quantify the effectiveness of employing the approach while optimizing the response time of an implementation. Subjects’ optimizations are quantified by the amount of fixed performance bugs. Having employed the approach, subjects fixed on average over three times more performance bugs. The results further indicate that in the absence of a performance awareness aid, the success of optimizing a previously unknown implementation is far less dependent of the behavior and skill level of the developer.

For the ideal functioning of an intelligent tutoring system it is essential to be able to estimate the level of skill of the students according to complex learning objectives. We propose an architecture for the evaluation of the student’s skill level, based on the multi-attribute utility theory, using as aggregation operator the Choquet integral. The method takes into account the learning objectives raised by the decision maker (academics, school teachers, heads of institutions, etc.) represented by complex relationships that can be found among the criteria considered for the evaluation.

A 67-year-old female is undergoing an elective hepatic resection for a massive left-sided hepatocellular carcinoma. During the challenging outflow dissection, an injury to the main trunk of the left/middle hepatic veins occurs. The bleeding is audible and non-remitting.

Scheduling in manufacturing systems is one of the most important and complex combinatorial optimization problems, where it can have a major impact on the productivity of a production process. Moreover, most of manufacturing scheduling models fall into the class of NP-hard combinatorial problems. In a real world manufacturing system, a plurality of worker who operates the machine exists, depending on the skill level by the workers for each machine and working time is different even if same work on the same machine in job-shop scheduling problem (JSP). Therefore, it is taking to account for differences in working time by the worker is scheduling problem with worker allocation. In this paper, in order to approach the more realistic model by dividing into several class workers and to determine the skill level for each machine for each class worker, we propose a new model that introduced the concept of class-type skill and demonstrate the effectiveness of the computational result by Hybrid Genetic Algorithm.

Recent developments in technology have permitted an increased use of autonomy. To work best with humans, autonomy should have the qualities of a good team member. But how can these qualities be measured? One way is to use similar measures to those used to measure good teams with human members. For example, the Non-Technical Skills (NOTECHS) framework measures Crew Resource Management (CRM) skills that allow pilots to work together as a team. The framework consists of skill categories, elements of those categories, and behavioral markers that demonstrate good or poor performance in the elements. This paper introduces CMSD (Cooperation/Management/Situation Awareness/Decision Making), a measurement system based on NOTECHS and other widely-used skill level systems, which provides quantitative measures of Human-Autonomy Teaming (HAT).

A slalom ski racer’s center-of-mass (CoM) has a negative acceleration during a turn. Some of this change in acceleration can be attributed to the physical contact with the pole, and possibly physiological and/or psychological factors of the ski racer. One factor may be the type/size of poles (gates) used to define the race line (route prescribed by competition rules) in slalom. Poles come in a variety of sizes and styles. This study utilized five differing pole types with 12-year-old male and female racers. As a general conclusion, they were faster on the small/shorter poles. They also felt faster, more aggressive, higher level of confidence, and thought their race line was superior on the shorter poles. When looking at the acceleration component, we divided the skiers into “skilled” and “less skilled.” The two groups differed on direction of acceleration. The discussion lays out mechanical, physiological, psychological, and technique ramifications to interpret this acceleration paradox.

The purpose of the present study is to reveal the fundamental skills for slacklining. A slackline is a flat belt tightly spanned between two anchor points. Because it bounces and swings in all directions, maintaining balance on it is difficult. In the practical field of slackline training, instructors share their skills based on personal experience. In a basic slackline course, they begin by teaching a fundamental skill, such as single-leg standing on a slackline, by explaining how they do it. However, such first-person perspectives on slacklining skills have not been scientifically investigated. According to instructors’ knowledge based on personal experience, we hypothesize the skills for single-leg standing on the slackline. The present study examines current hypotheses by comparing performances at different skill level (i.e., experienced vs. novice). This article introduces our pilot study, including current hypotheses and data from preliminary experiment, and discusses them.

The speed before the accident is a necessary data to understand the injury mechanisms and to evaluate means of protection. In order to interpret the reported speed of a skier in an accident survey, this study aims to identify the governing factors of skiing speed and to propose ranges of speed combining the identified factors and the skiers’ perception of their speed. Travelling speed of 1399 skiers and snowboarders was measured with a radar speed gun. Gender, sport, helmet use, skill level, difficulty, and preparation of the slope were recorded. 170 recorded skiers were interviewed about their age, their skill level, their perceived speed (“slow to medium,” “high,” or “too high”), and their estimated speed (km/h). Linear regression models were used to evaluate the effect of each factor on skiing speed. The mean recorded speed was 43.4 (±15.2) km/h. It was 37.5 (±9.8) km/h when the perceived speed was “low to medium” and 49.0 (±14.6) km/h when the perceived speed was “high.” The factors best explaining skiing speed were the skill level (η2 = 0.26) and the slope difficulty (η2 = 0.19). Gender, age, sport, and slope preparation were found to have a small but significant effect (η2 < 0.1; p < 0.05). Those factors also influenced the speed perception: for the same perceived speed, “less skilled” skiers and skiers on easy slope tended to go on average 6 km/h and 8 km/h slower than the “more skilled” and those on medium slope, respectively. Finally, skiers estimated their measured speed fairly (r: 0.53). They tended to overestimate the speed when they went slower than 35 km/h but underestimated it at higher speed. Ranges of speed were obtained regarding perceived speed, skill level, and difficulty of the slope. This should be considered when interpreting skiers’ evaluation of their speed in accidents reports.

Randomization of study participants avoids potential bias in assigning treatment, balances assignments by treatment group on measured prognostic factors and tends to do the same for unmeasured factors, and assures that statistical tests of significance are valid. There are two classes of randomization, and each has several different methods: fixed allocation randomization (simple, blocked, and stratified) and adaptive randomization (baseline adaptive, minimization, response adaptive). The pros and cons of each method and recommendations for their use are summarized in Table 15.2. Regardless of the method used, randomization will not be successful unless it is done properly (e.g., blinding to assignment is maintained; the number of ineligible participants randomized in error is small), and it is important to randomize as closely as possible to the start of treatment to minimize the number of participants withdrawn from the study. Some potential issues in invasive studies that are not of concern or are less problematic in drug studies include differences across sites in the skill level and experience of the interventionalist/surgeon and how those affect the participant’s response, the invasive technique may continue to develop and change while the study is ongoing, and the degree to which the interventionalist/surgeon follows the protocol may vary.

In this paper we suggest the first systematic review and compare performance of most frequently used machine learning algorithms for prediction of the match winner from the teams’ drafts in Dota 2 computer game. Although previous research attempted this task with simple models, weve made several improvements in our approach aiming to take into account interactions among heroes in the draft. For that purpose we’ve tested the following machine learning algorithms: Naive Bayes classifier, Logistic Regression and Gradient Boosted Decision Trees. We also introduced Factorization Machines for that task and got our best results from them. Besides that, we found that model’s prediction accuracy depends on skill level of the players. We’ve prepared publicly available dataset which takes into account shortcomings of data used in previous research and can be used further for algorithms development, testing and benchmarking.

In the past chapters we have seen that the decision to migrate of Mexican migrants in Australia was less driven by supply of labour and more driven by post-material values such as quality of life. This mirrors the motivation of other middle-class migrants. Now we turn to the outcome of this decision, particularly in the sphere of work. Is there a profile of respondents’ occupational structure and income? Are they satisfied with their job? What are the main difficulties encountered? Through this chapter it will be shown that overall, and particularly in terms of employment, Mexicans in Australia are a successful group compared to similar Latin American migrants in Australia. Of course, not all respondents were doing well, and many had struggled initially. The interview material was particularly revealing in that the employment transition from Mexico to Australia was difficult for many migrants; I found that a significant number of people were forced to take jobs below their skill level, particularly when they first joined the Australian labour market. Yet, it appears that there is a high level of work satisfaction among survey respondents.

According to the estimation of US Census Bureau, the age demographic will change from 13 percent of the population aged 65 and older in 2010 to 19 percent in 2030 [1]. With the fast growing number of elderly population, designers may be driven by market to consider an aging-centered design. However, the real challenge of aging-centered design may not only be the preference or interest by age difference but also the technology gap of using computer.

We present a method of analyzing the relationships between driver characteristics and driving behaviors on the basis of fusing heterogeneous datasources with large-scale vehicle recorder data. It can be used, for example, by fleet managers to classify drivers by their skill level, safety, physical/mental fatigue, aggressiveness, and so on. Previous studies relied on precise data obtained in only critical driving situations and did not consider their circumstances, such as road width and weather. In contrast, our approach takes into account not only a large-scale (over 100 fleet drivers) and long-term (one year’s worth) records of driving operations, but also their circumstances. In this study, we focused on classifying drivers by their accident history and examined the correlation between having an accident and driving behavior. Our method was able to reliably predict whether a driver had recently experienced an accident (f-measure \(=\) 72%) by taking into account both circumstantial information and velocity at the same time. This level of performance cannot be achieved using only the drivers’ demographic information or kinematic variables of operation records.

This chapter examines the post-2007 Southern European migration to Germany, arguing that this highly recruited and sought after migration has served to consolidate Germany’s status as an immigration country. This migration flow has some parallels to the post-war recruitment of Gastarbeiter, or guest workers, although it differs strongly in skill level – today’s migration is more highly-skilled than the post-war migration. The recruitment is both top-down and bottom-up, with the Federal Employment Agency, regional offices, trade associations and employers themselves all recruiting skilled Southern Europeans. The migration is seen in Germany as solving the current Fachkräftemangel, or lack of skilled workers, resulting from the emerging demographic challenges. Unlike post-war recruitment, which was intended to be temporary, Germany hopes that today’s migrants will remain.

Aboriginal or Indigenous student achievement is multidimensional and complex in Canada and in an international context. Although successes are experienced by Aboriginal students, there continue to be barriers and challenges (e.g., socio-cultural factors, school and community perceptions that determine policy and practice) that have negative implications. Statistically, Aboriginal student graduation rates in Canada continue to be disproportional when compared to non-Aboriginal students (a reflection of academic achievement), and Aboriginal students continue to be over-represented in terms of requiring special education programs and services and under-represented in the gifted and talented categories. Since academic achievement and the allocation of Aboriginal students to special education programs are influenced and/or determined by assessment practices implemented by teachers and educational psychologists, the validity and effectiveness (this including the cultural relevance; the knowledge and skill level, and affective orientation of teachers and educational psychologists) of the assessment practices should be critically examined and improved on a regular basis. Disproportionality in special education becomes an issue when it perpetuates the deficit view of Aboriginal students and/or when the precursors or outcomes of special education are biased or inadequate.

In this paper, we propose an efficient English vocabulary learning system using repetitive learning and the rate-matching rule. The proposed system provides a learning method based on the user's learning skill. By using the proposed system, users can solve exam-style questions wherever and whenever they choose. Efficient repetition learning is provided by using repetition periods based on the forgetting curve for long-term memory. The answered questions are then evaluated to update the user's learning skill and the question difficulty. Due to this adaptive difficulty adjustment, users almost always receive questions that are appropriate for their skill level. If users answer questions correctly or learn more than the defined amount, then the proposed system provides them with encouraging feedback imagery. This is very similar to being rewarded for an achievable challenge in a game, and it can encourage users to study consistently.

Cooperative learning facilitates the design of effective group work; but effective group work is more complex than attending to the research on cooperative learning. This chapter illustrates some of the missing thinks in the application of effective group work and how leadership at the school and district levels positively impacts instructional change. Key to effective group work is understanding how different cooperative learning methods might intersect with each other, as well as with other instructional methods outside of cooperative learning. For example, intersecting the Johnsons’ five basic elements as students do an Academic Controversy or intersecting Think Pair Share and Place Mat to complete phase two of Concept Attainment. That intersection of multiple methods allows teachers to combine the effect sizes of those innovations; by combining innovations we impact learning and assessment. The idea of how effectively teachers apply aspects of cooperative learning is also explored through the research on Levels of Use on an innovation that emerged from the work of Gene Hall and Shirley Hord on the Concerns Based Adoption Model (CBAM). Here teachers are reminded that until they and their students are skilled at implementing effective group work, they need to understand that student learning is going to be minimal. Obviously, we must consider the teachers’ and students’ skill level with all instructional innovations before making ‘assessment’ decisions about student learning.

Glass fiber is well known as a reinforced material with low costs and excellent mechanical properties advantages and it has been extensively exploited over the past few years. In this paper, glass fiber was selected and used to fabricate composite with unsaturated polyester resin by hand lay-up method. However, the issue that it is difficulty for quality of product to control was caused by this method. At recent research, the effect of the worker’s skill levels on the quality of product has hardly been investigated. Therefore, it mainly focuses on worker’s skill level influence on the mechanical performance of molded product in this paper. To achieve this purpose, Subjects (Subject A, B, C, D, E had 25, 18, 15, 4, 1 year of experience, respectively.) were allowed to choose their familiar molding tools to produce product which were made of the same materials and met the requirements of volume friction. The thickness of laminates was measured especially in the corner before the test. In addition, bending properties and low cycle bending fatigue (LCBF) were also discussed and investigated. After the test, the fracture cross sectional observations was implemented on the selected test specimens by using a scanning electron microscope (SEM), with a focus on the fracture morphologies.

The shamisen is a traditional Japanese folk musical instrument. It is regarded as a valuable cultural asset that might attract people into moving into unpopulated districts of the country. We focus on the Mutsumi-ryu style of shamisen, a famous playing style originating in Akita a prefecture in northern Japan. Mutsumi-ryu has a characteristic action called the uchi, where a plectrum is struck down to the body and strings of the shamisen. In this paper, we propose a self-learning system for the uchi for students of the Mutsumi-ryu playing style by using Virtual Reality VR. The system captures a student's actions during uchi using a motion capture system, evaluates the student's actions, and interactively represents the movements of an expert performing the uchi in a VR environment. Experimental results showed that using our system, students can acquire a skill level comparable to that of those who learn directly from human experts.

Attacks on organisations today explore many different layers, including buildings infrastructure, IT infrastructure, and human factor – the physical, virtual, and social layer. Identifying possible attacks, understanding their impact, and attributing their origin and contributing factors is difficult. Recently, system models have been used for automatically identifying possible attacks on the modelled organisation. The generated attacks consider all three layers, making the contribution of building infrastructure, computer infrastructure, and humans (insiders and outsiders) explicit. However, this contribution is only visible in the attack trees as part of the performed steps; it cannot be mapped back to the model directly since the actions usually involve several elements (attacker and targeted actor or asset). Especially for large attack trees, understanding the relations between several model components quickly results in a large quantity of interrelations, which are hard to grasp. In this work we present several approaches for visualising attributes of attacks such as likelihood of success, impact, and required time or skill level. The resulting visualisations provide a link between attacks on an organisations and the contribution of parts of an organisation to the attack and its impact.

Games are boring when they are too easy and frustrating when they are too hard. A game in which the challenge level matches the skill of the human player has the greatest entertainment value. In this paper a simple and fast method for adjusting a difficulty level of a computer opponent is introduced. An empirical investigation of the method when playing a FPS game is conducted. Different kinds of players are analyzed. The results show that proposed method matches the difficulty level of an opponent to a player’s skill level even without full information about player’s abilities.

In this research, “Maki-e” technique was focused. Maki-e technique is a decoration technique of Urushi crafts technique. There is a polishing process in the Maki-e making process. Maki-e surface is polished by a charcoal and whetstone in the polishing process. Time-served technique is needed for this process. Because this process affects a finish of Urushi crafts work, this research aimed to clarify a relationship between a skill level difference of craftspeople and a finish of Urushi crafts work in the polishing process by using charcoal. Characteristics of the finish Urushi crafts work and how to use a body of craftspeople was analyzed. As the results of this research, it was confirmed that; 1. The expert’s Maki-e specimen was more brightness and yellow than the non-expert. 2. There was not much difference about the gloss and surface roughness between the expert and the non-expert. 3. The expert took the rhythmic activity in each muscle. Therefore it seemed that the finish of the work became more beautiful. These results suggest that how to use the body affects the finish of the Urushi crafts work in the polishing process. The non-expert can improve the finish of the work and the level of polishing skill by training the body position and motion like the expert.