Reviewerly/exHarmony huggingface dataset:
Creating AR models for challenging sizes

Augmented and Virtual Reality is being evermore adopted in various sectors with the process of creating augmentable mostly focusing on laser scanning and photogrammetry. This research presents cost-effective solutions of creating augmentable models for artefacts of various sizes, more specifically the challenging sizes of the scale of large vehicles. After testing a number of solutions in a controlled environment the ideal solution was adopted in an aviation museum and used on various objects such as a tractor and aeroplane engine. We proceeded to create a prototype for the museum, integrating the augmentable and letting a number of individuals use it so to gather feedback. After presenting the solution and overall positive user feedback to the director of the museum an interview was held to gather qualitative feedback addressing the business aspect of this solution. We are confident that our proposed approach can be adopted by young entrepreneurs willing to offer such a cost-effective solution to entities with a limited budget, yet still delivering a professional product.
About counterexamples for generalized Zariski cancellation problem

We investigate principal Ga-bundles over pre-varieties which play an important role for the moduli of counter examples for Generalized Zariski Cancelation Problem. In this paper we give three important theorem for this problem; a criterion for a principal Ga-bundle over a pre-variety of a certain type to be affine, a criterion for two principal Ga-bundles to be isomorphic, and the uniqueness of the base schemes of principal Ga-bundle structures in the case that there exists a base scheme having a dominant morphism to a variety of nonnegative logarithmic Kodaira dimension.
AI rethinks mass extinctions

Machine learning sheds new light on the history of life on Earth
CAPSTONE DESIGN PROJECTS WITH INDUSTRY PARTNERS: A 6-YEAR EXPERIENCE REPORT

Since 2013, the fourth-year capstone design courses for the electrical and computer engineering programs at UBC are working only with projects defined by industrial partners. These capstone courses run over two terms (September to April) and are worth 10 credits. The projects involves teams of five students, which follow a common timeline, produce a common set of deliverables, and have a common evaluation scheme –with some latitude for variation based on the nature of the project and the type of partner. A key objective is to include non-technical graduate attributes, the so-called “soft skills”, in our learning outcomes. In this paper, we describe our current course framework, our constraints and design choices, and we report lessons learned and improvements implemented over 6 years.&#x0D;
ID Card Detection Using Histograms of Oriented Gradients

ID card location innovation assumes a significant job in the present society to recognize the data database in different areas. Histogram of Oriented Gradients is the most broadly perceived part descriptors in picture planning and PC vision and is used for article ID. High-security ID check is an extremely intense activity. Present day object distinguishing proof and acknowledgment has progressively transformed into a critical issue in various on-going applications like security frameworks and government oversaw reserve funds systems. The ID card can be definitely perceived by utilizing an institutionalized scanner, for example, a standardized tag scanner. The specific customer honestly takes a gander at the given information on the ID card and after that thinks about it to the information effectively given to check whether it matches. This sort of ID is used precisely to strikingly separate customers faster and is dynamically powerful to give unmistakable access control courses of action. The trial results led show that this technique can be utilized to get the careful data of an individual and the required information.
GRNet: An Efficient Group Ranking Network for Face Attribute Recognition

Face attribute recognition methods have been far from real-world applications despite remarkable progress in recent years. Most of these methods fail to mine attribute relationships with traditional cross entropy loss and hold considerable computational complexity. In this work, we propose a group ranking network (GRNet) to investigate substantial relationships among face attributes. First, an attribute grouping manner is designed to capture interactions among spatially related attributes and enhance computational efficiency. Second, a new supervision signal is presented to model attribute ranking relationships. Under the supervision of ranking loss, GRNet learns intra-attribute and inter-attribute ranking features to intensify the representational capability of attribute models. We evaluate our approach on aligned and unaligned CelebA datasets. Results show that the performance of the proposed approach is superior to other start-of-the-art methods on attribute recognition.
Keterlambatan Berbicara pada Anak Usia 4 Tahun

This paper focuses on the language disorder in the form of speech delay, which happens to five-year-old children. This research was conducted with the aim to describe: 1) Factors that influence speech delay in children, 2) The treatment given by parents and environment in response to the problem of speech delay (speech delay) in children. Data retrieval is done by listening and recording data from a YouTube video. In data analysis techniques, researchers used qualitative methods. Technique of presentation of result of data analysis used is method of informal presentation because its data is speech. Based on the results of data analysis, it can be concluded that there are many inhibiting factors in children's speaking ability, among which are (1) hearing impediment, (2) developmental obstacles in the brain mastering oral-motor, (3) heredity problems, (4) learning problems and communication with parents, and (5) Media factors in this case television. Therefore, the role of parents, teachers, and the environment is very important in improving the ability to speak at early childhood. Then special treatment needs to be done by parents and the surrounding environment by changing the language used when talking to the child.
A Class of Negacyclic Codes and Their Application to Quantum Codes

In this paper, the properties of $q^{2}$ -ary cyclotomic cosets modulo $2n$ are investigated in detail, where $n=\frac{q^{2m}-1}{m(q-1)},q\equiv\pm 1\mathrm{mod} m$ or $q^{2}\equiv-1\mathrm{mod} m$ when $m$ is even and $q$ is an odd power prime when $m$ is power of 2. Then, non-narrow-sense negacyclic Bose-Chaudhuri-Hocquenghem (BCH) codes of length $n$ that contain their Hermitian duals are determined. By the Hermitian construction, series of quantum codes are obtained from such negacyclic BCH codes. Compared with quantum codes in the [6], [10], [12], our constructed ones have better parameters.
PMI-IR Based Sentiment Analysis Over Social Media Platform for Analysing Client Review

Social media is an emerging platform where people share their opinion about any national or global issue. This opinion attract marketing and research team to analysis people sentiment over social media for their marketing of their product. The reviews of end user over social media play an important role to show the quality of products. This paper discus the analysis and the evaluation of the sentiment based on the customer review s that are available in the online for presenting the sentiment based review for the products by using point wise mutual information of opinion word. The Results shows that using modified approach gives improved efficiency on feature-based sentiment analysis.
FLOUTING MAXIMS IN HITAM PUTIH TALK SHOW

Communication between speakers and hearer should fulfil maxims in order to have an effective communication and to avoid misunderstanding. In fact, sometimes people blatantly flout the maxims but people mostly have reasons behind that and whenever a maxim is flouted there must be an implicature to save the utterance from simply appearing to be a faulty contribution to a conversation. The importantance of the research is about finding out the dominant flouting of maxims during the conversation between the participants in Hitam Putih talkshow. Besides, the purposes of why flouting the maxim was also displayed as to make this research become more comprehensive. Why a certain dominant maxim was flouted but not another maxim. In analyzing the data, the writer uses Grice's theory on maxim. The data were collected by searching, listening and making the transcripts, watching the record for many times, grouping the conversation, deciding which maxims are flouted based on the criteria, finding the reasons of the flouting. As the result, the writer found that the first most flouted maxim is the Maxim of Quality. The reasons of flouting this maxim are to make a joke and to give a clearer information. In making a joke, a speaker can pretend not to know something, pretend not being honest, and this pretendings are clearly flouting the quality maxim. That is why the quality maxim is flouted to make a joke. Another flouted maxims are also found from the data which are flouting the quantity maxim to give clearer information, to stress something, to avoid unpleasant situation. The relation maxim is also flouted as being polite, and the last the manner maxim is flouted as to make a joke. The characteristic of Indonesian speaker with long winded and not to the point, has in fact influence the flouting the maxim.
OUTLOOK FUNDAMENTALS OF THE TERM “SPIRITUALITY” INTERPRETATION BY THE UKRAINIAN EDUCATORS (THE SECOND HALF OF THE XIX CENTURY)

The article deals with the ideological principles of interpretation of the term “spirituality” by Ukrainian educators of the second half of the nineteenth century. Particular attention is paid to the fundamental concepts of “spirituality” in pedagogy. The article reveals the peculiarities of the national definition of the term “spirituality”.
An Analysis of Kite’s Symbolic Meaning in The Kite Runner

Marc Forster adapted the novel The Kite Runner for a movie which had won an Oscar nomination in 2008. The Kite Runner tells a story of two Afghan boys Amir and Hassan. Kite is regarded as a symbolic object throughout the movie. For sure, it plays a significant role to drive the plot. There is something more profound hidden below the surface of story strand. This paper aims to figure out the symbolic meanings of the kite at the social background, interpersonal relationship and humanity level. This way, audience can have a better understanding of this movie.
Neural Networks from Scratch

Artificial neural networks consist of distributed information processing units. In this chapter, we define the components of such networks. We will first introduce the elementary unit: the formal neuron proposed by McCulloch and Pitts. Further we will explain how such units can be assembled to design simple neural networks.
Teacher use of Augmented Reality in classes, a question of Perceived Enjoyment?

The ARTEfac project aims to develop a web solution for teachers and trainers to design flexible teaching scenario including Augmented Reality (AR). This solution, developed by researchers and engineers from Aix-Marseille University and a private company, is composed of a Backoffice for scenarios' designers and a mobile user application. This paper is focused on the possible factors influencing the teachers' behavioural intention to use AR models in their own classes. Based on the TAM (Technology Acceptance Model), the survey tool is a questionnaire assessing the Behaviour Intention of use, the Perceived Usefulness, the Perceived Ease of Use, the Perceived Enjoyment, the Attitudes towards the use and the Aesthetic aspect. Thirty-six pre-service teachers investigated earth seasons through an AR scenario during a science training session at university. The scenario included an interactive AR model representing the earth revolution around the sun using 3D objects. The users had the possibility to interact with the model like stopping the revolution and rotation, changing the earth inclination, etc. One of the pedagogical objectives was to make them aware that the seasons are explained by the earth inclination (and not by the earth distance from the sun which is a very common misconception). A multiple regression analysis, including the different factors tested by the questionnaire, shows that there is a significant link between the Perceived enjoyment and the Behaviour Intention to use AR models in their classes. In contrast to earlier findings in different field of technologies, no significant influence of other TAM factors such as Perceived Usefulness, Perceived Ease of Use, Attitudes towards the use, Aesthetic aspects of the AR model was found. External factors such as gender, or their speciality (science, literature, etc.) do not influence significantly their intention to use. All these results will be discussed according to their limitations and the previous studies done in the same field.
Super-resolution Image Reconstruction Utilizing High-Precision Skin Color for Face Images

In recent years, opportunities to deal with digital images on the Internet have increased due to the information society, there is a great demand for techniques such as super-resolution processing to make images more beautiful. When super-resolution processing is performed on natural images such as scenery, edges are emphasized to obtain clear images. However, when super-resolution processing is applied to a facial image, the wrinkle and stains of the skin as well as the emphasis of hair and eyes are emphasized, so super-resolution processing on the skin part is not suitable. Therefore, in the previous study, we proposed a method to perform facial correction using non-linear filter on skin part, and tried to solve this problem. This method is composed of super-resolution processing and facial correction processing, and it was possible to realize a super-resolution processing with a sharp sense for facial images. However, we also confirmed that there was a problem that the image quality deteriorated according to the skin color detection accuracy at the time of image synthesis of each processed image. Therefore, in this paper, we study the skin color detection method and try to improve the image quality.
Large-Scale Image Action Recognition Depends on Deep Learning

In the field of computer vision, research on action recognition in still images has begun to attract people's attention. However, the single action image contains limited information and is difficult to identify. Therefore, the action recognition of still images still faces the enormous challenges. In order to solve this problem, this paper uses the 34-layers residual convolutional neural network to construct recognition model. By extracting the features of the last fully connected layer from this CNN model, we forward the features to the classical models such as Decision Tree, Random Forest, Bayes, and SVM. Experimental results on our images datasets show that our method achieves better performance than a single CNN and other traditional classifiers, especially when combined our residual network with SVM, the recognition accuracy is over 80%. It confirms the effectiveness of our method.
Metric Entrainment and the Problem(s) of Perception

Chapter 11 discusses the limits and mechanisms of our perceptual faculties for auditory rhythm. Perhaps more than vision, a consideration of auditory perception, and our auditory perception of rhythm in particular, reminds us that the perceptual process is not a linear chain of information from the external world to the mind, but an active interplay between mind and world. But while considering our senses as perceptual systems—as cross-modal—solves some problems of perception, it creates other, perhaps deeper ones, the author argues. In the case of musical rhythm, our rhythmic percepts are often non-veridical, as we add accents, beats, and grouping structure to otherwise undifferentiated stimuli.
Resource Scheduling Using Modified FCM and PSO Algorithm in Cloud Environment

Cloud computing is a growing environment in the IT industry. Many of the users are interested to outsource their data in cloud. However, load balancing in cloud is still at risk. Resource allocation plays a major role in load balancing. In this scheduling problem, independent tasks in cloud computing can allocate resources by the use of fuzzy c means algorithm (FCM). To allocate tasks to their corresponding resources, particle swarm optimization algorithm (PSO) is used. This paper proposes a hybridization of the FCM and PSO algorithm which is called H-FCPSO algorithm. FCM uses Euclidean distances and PSO optimizes the cluster centers. FCM requires the number of clusters used in advance and thus PSO comes into action to find the number of best clusters. Hence, H-FCPSO identifies the number of clusters and enhances the load balancing. Since our proposed system selects resources based on parallel execution kit reduces the load imbalance in cloud. When compared to Genetic algorithm (GA), Ant Colony Optimization algorithm (ACO), PSO algorithm showed better results in terms of memory. Similarly, FCM was compared with k-means clustering algorithm, Hierarchial algorithm and it showed outputs with better accuracy. The proposed system evaluated data sets and proved to overcome the issues in load balancing and load scheduling which is proved by its precision in the outputs.
Early Childhood Metacognitive Learning among Students of Early Childhood Teacher Education

The purpose of this research is to describe the ability of Early Childhood Teacher Education students to carry out Early Childhood metacognitive learning.By using the developmental research method that refers to the Dick and Carey's model, the following research results are obtained: Based on the teaching of thinking, teaching for thinking and teaching about thinking, early childhood metacognitive learning is planned so that the method and media used are clear, to train students' thinking ability. The implementation of early childhood metacognitive learning is assessed from the teacher's perception, namely students of Early Childhood Education as prospective teachers and from children's perceptions. From the teacher's perception it is believed that early childhood metacognitive learning can start at the age of 2 years old. From the children's perception, early childhood metacognitive learning occurs because of the process of habituation and imitation.
The applications of GPS in gauges of current and tide

GPS is widely applied in ocean measuring for its function of all-weather and real-time precise positioning. The theory of gauging currents and tides by using GPS was introduced and summarized the developments of various gauging methods, the advantages and disadvantages were discussed as well. With the rapid development of GPS satellite positioning technology, the inversion of ocean dynamic parameters has become a popular issue in recent years. Research on this area is still far from completing.
Image Montage Summarization

Describing an image’s content automatically is a basic issue in artificial intelligence that links computer vision and processing of natural language. Recently, however, less attention has been given to extracting summaries from a set of associated pictures that can provide much better data. This paper presents an abstractive summary model with an Encoder-Decoder hierarchy that simultaneously sums up a gallery of pictures and matches phrases and pictures in summaries. The model is designed in order to enhance the probability of the destination identification sentence given the teaching picture. The precision of the model and the fluency of the language learned so only from image descriptions are demonstrated in experiments on various datasets. Our model is often quite precise and we check it in qualitative and quantitative terms. A recent study on neural summarization shows the power of the encoder-decoder model for picture and document overview. Experiments demonstrate that our model is better than neural abstraction and extraction techniques by producing better informative summaries of the collection of images.
Development of path planning of line follower robot with obstacles avoidance based on particle swarm optimization

Research on robot path planning based on the PSO (Particle Swarm Optimization) method has been widely developed. PSO is one of optimization algorithm that aims to provide the best solution on the finding of shortest route by utilizing particle population movements. In this paper, we developed a line follower robot with obstacle avoidance based on PSO. The PSO is embedded into Arduino microcontroller to control the navigation as well as avoid the obstacles. The robot is programmed a start point on coordinate (1,1) and a destination point on coordinate (5,5). The robot performances to avoid the obstacles were tested by robot goes to destination point while obstacles were added to the route. The computation time and the shortest route distance of the robot to reach the destination point with and without obstacles have been compared.
Hand Gestures Detection, Tracking and Classification Using Convolutional Neural Network

The article describes a software pipeline for detecting, tracking and classification of static hand gestures of the Russian Sign Language in a video stream using computer vision and deep learning techniques. The dataset used for this task is original, includes 10 classes and consists of more than 2000 unique images. The solution includes a hand detection module that uses a color mask, a gesture tracking module, a static gestures classification module in the detected region of the image based on convolutional neural network, as well as an auxiliary image preprocessing module and dataset augmentation module.
Improving open-set person re-identification by statistics-driven gallery refinement

Person re-identification (re-ID) is a valuable tool for multi-camera tracking of persons. Up till now, research on person re-ID has mainly focused on the closed-set case, where a given query is assumed to always have a correct match in the gallery set, which does not hold for practical scenarios. In this study, we explore the open-set person re-ID problem with queries not always included in the gallery set. First, we convert the popular closed-set person re-ID datasets into the open-set scenario. Second, we compare the performances of six state-of-the-art closed-set person re-ID methods under open-set conditions. Third, we investigate the impact of a simple and fast statistics-driven gallery refinement approach on the open-set person re-ID performance. Extensive experimental evaluations show that, gallery refinement increases the performance of existing methods in the low false-accept rate (FAR) region, while simultaneously reducing the computational demands of retrieval. Results show an average detection and identification rate (DIR) increase of 7.91% and 3.31% on the DukeMTMC-reID and Market1501 datasets, respectively, for an FAR of 1%.
String Similarity Based on Phonetic in the Gujarati Language Using Gujsim Algorithm

Searching using top 10 search engine1 to find “ગ ાધીજી” or “ગ નધીજી” and surprised to see the result which far differs from one to another. As in the Gujarati language, both strings are correct. Therefore, String similarity algorithm is useful for text mining applications while we generate index – saving space and time, both. Basically, string similarity compares each character from both strings but it may not give the accurate result on highly rich Gujarati language due to different kinds of writing styles which depend on matras, reph, vatu, and diacritics on simple and compound alphabets. GUJSIM (GUJarati SIMilarity) algorithm is the hybrid approach to do strings similarity for the Gujarati language. Here, the author compares 70 strings pairs and GUJSIM algorithm which gives optimum percentage result. This algorithm also helps to reduce the percentage of index based on the unique string.