Identify the Object’s Shape using Augmented Reality Marker-based Technique.

At present, new technology affects daily life in both direct and indirect ways. Internet technology can connect people around the world through social networks. It can facilitate online shopping or e-commerce, which is the popular culture of today business. Contents provided in the online shopping must be in the form that customer can interact with, i.e., it must be converted from analog data to digital information. For apparel or clothing business, only picture and information of the dresses, such as size, color, etc., may not be enough, since the customer did not know whether it will fit their bodies or not. To make sure that the dress they wanted to buy fit their body, the body size of the customers must be known. With the known body size, generating the 3D model of the customer to try on the 3D virtual model of the dress is possible, and the decision to buy is possible. There are many ways to find the exact body size and generate a 3D model of the customers i.e. using 3D scanner, using Photogrammetry technique (merging many photographs of the customers’ bodies to create the 3d model) or generating 3D model with known information using 3d computer graphic software such as Autodesk Maya, 3D max. The techniques mentioned above have some drawback because it required either an expensive device or expert to create a 3D model which may take a long time. Therefore in this research, we present the technique using marker-based Augmented Reality to acquire the shape of the objects. By wrapping the markers around the surface of the object that we want to measure, each marker’s position can be identified, and when combined, the shape and sizes of the object can be created. This technique takes a shorter time than other method and does not require any sophisticated device but still give good results. We separate the experiment into three groups, group one, testing the concept with five objects with different sizes and shapes with one row markers and group two, testing cylindrical objects with four row markers, and group three, testing with a mannequin to find the shape of human’s body. we have found that the shape and size of the objects that we have created are very close to the real one with the maximum error of less than 5%. It possible to generate the whole 3D object which can be adjusted to support virtual fitting room

Interactive Marker-based Augmented Reality for CPR Training

CPR, or Cardiopulmonary Resuscitation, is a lifesaving technique useful for the case in which someone’s heartbeat or breathing has stopped due to heart attack. Without proper CPR, nine out of ten patients die. The American Heart Association recommends CPR with chest compressions in the event of witnessing such an incident. For proper CPR training, taking a class with a CPR instructor is usually the best choice, but it is not practical and costly for mass training, especially in schools and universities. There are many new techniques available that can replace traditional CPR training and Augmented Reality (AR) is one of them. AR is the technology that integrates virtual objects or environments, created by digital technology, with the real world. Augmented Reality using marker-based technique is a good option, since a trainee can have a realistic look at the patient, know the position of the hand on the chest, identify the number of chest compressions per minute, and also know the pressure that he or she puts on the chest. Besides that, the status of the operation can be displayed along with a recording system for analysis. In this research, we chose marker-based AR due to its precision in distance measurement. For measuring the pressure on the chest, we use a marker-marker interaction technique. Unity 3D cross-platform game engine and Qualcomm's Vuforia—an augmented reality software development kit (SDK) for mobile devices that enables the creation of augmented reality applications—are required. The results from our experiment with a group of people with non-CPR training confirm that the configuration increases the speed and accuracy of CPR training

Effect of Term Weighting on Keyword Extraction in Hierarchical Category Structure

While there have been several studies related to the effect of term weighting on classification accuracy, relatively few works have been conducted on how term weighting affects the quality of keywords extracted for characterizing a document or a category (i.e., document collection). Moreover, many tasks require more complicated category structure, such as hierarchical and network category structure, rather than a flat category structure. This paper presents a qualitative and quantitative study on how term weighting affects keyword extraction in the hierarchical category structure, in comparison to the flat category structure. A hierarchical structure triggers special characteristic in assigning a set of keywords or tags to represent a document or a document collection, with support of statistics in a hierarchy, including category itself, its parent category, its child categories, and sibling categories. An enhancement of term weighting is proposed particularly in the form of a series of modified TFIDF's, for improving keyword extraction. A text collection of public-hearing opinions is used to evaluate variant TFs and IDFs to identify which types of information in hierarchical category structure are useful. By experiments, we found that the most effective IDF family, namely TF-IDFr, is identity>sibling>child>parent in order. The TF-IDFr outperforms the vanilla version of TFIDF with a centroid-based classifier

Game elements from literature review of gamification in healthcare context

Gamification is a conceptual framework to apply game elements and techniques to improve the interesting process in non-game context. Gamification offers the motivation approach to motivate the player to handle the challenge tasks with game mechanics, game dynamics, and components. Nowadays, To discover the set of game elements and techniques from evaluating the existing related research is more opportunity for success in the exciting process. The core objective of this paper is to review the literature by using descriptive statistics of game elements with the review methodology and evaluate the model with multi-label classification with a dataset from this literature examined. The reviewed literature was first coded author-centrally. After each paper was scrutinized for the analysis, the perspective was pivoted, and further analyses were conducted concept-centrally. A systematic review has been conducted that proves the wide variety of game elements, being retrieved a total of fifteen terms of game elements from twenty-two selected papers that were screened from a total of eighty-two documents. Only a few terms are used: points, feedback, levels, leaderboards, challenges, badges,  avatars, competition, and cooperation. However, only some can be considered actual elements mechanics and that have not a similar abstraction level. Additionally, the authors examined the relationship between game elements and STD: Competence, Autonomy, and Relatedness with a Data mining technique, Multi-label classification to discovery knowledge of game elements. The results indicated that rFerns algorithm provides the lowest Hamming Loss with 4.17%. Furthermore, It shows that Multi-label Rain Forest (rfsrc) in Algorithm adaptation method and Rain Forest (RF) in Problem transformation method provide the same Hamming Loss with 29.17%. Moreover, rFerns algorithm provides the highest accuracy with 87.5% for Competence, and 100% for Autonomy and Relatedness. Furthermore, It shows that Multi-label Rain Forest (rfsrc) in Algorithm adaptation method and Rain Forest (RF) in Problem transformation method provide the same Accuracy with 87.5% for Competence, and 62.5% for Autonomy and Relatedness. The results from this study will be used to design a gamified system in a healthcare context to promote physical activity

A systematic review of the effects of prolonged cow-calf contact on behavior, welfare, and productivity

Separation of calves from cows within hours or days of birth is common on dairy farms. Stakeholders have conflicting perspectives on whether this is harmful or beneficial for the animals’ welfare and production. Our objective was to critically evaluate the scientific evidence for both acute and long-term effects of early separation versus an extended period of cow-calf contact. The outcomes investigated were the behavior, welfare (excluding physical health) and performance (milk yield and growth, respectively) of dairy cows and calves. Primary research papers were found through targeted Web of Science searches, the reference lists of recent reviews for each topic, and the reference lists of papers identified from these sources. Studies were included if they were published in English, the full text was accessible, and they compared treatments with and without contact between dairy cows and calves for a specified period. Early separation (within 24 h post-partum) was found to reduce acute distress responses of cows and calves. However, longer cow-calf contact typically had positive longer-term effects on calves, promoting more normal social behavior, reducing abnormal behavior and sometimes reducing responses to stressors. In terms of productivity, allowing cows to nurse calves generally decreased the volume of milk available for sale during the nursing period, but there was no consistent evidence of reduced milk production over a longer period. Allowing a prolonged period of nursing increased calf weight gains during the milk-feeding period. In summary, extended cow-calf contact aggravates the acute distress responses and reduces the amount of saleable milk while the calves are suckling, but can have positive effects on behaviors relevant to welfare in the longer term and benefit calf growth. The strength of these conclusions is limited, however, given that relatively few studies address most of these effects and that experimental design including timing of contact and observations are often inconsistent across studies. Few studies presented indicators of long-term welfare effects other than abnormal and social behavior of the calves