Reviewerly/exHarmony huggingface dataset:
Development of technique for face detection in image based on binarization, scaling and segmentation methods

A technique for face detection in the image is proposed, which is based on binarization, scaling, and segmentation of the image, followed by the determination of the largest connected component that matches the image of the face.Modern methods of binarization, scaling, and taxonomic image segmentation have one or more of the following disadvantages: they have a high computational complexity; require the determination of parameter values. Taxonomic image segmentation methods may have additional disadvantages: they do not allow noise and outliers selection; clusters can’t have different shapes and sizes, and their number is fixed.Due to this, to improve the efficiency of face detection techniques, the methods of binarization, scaling and taxonomic segmentation needs to be improved.A binarization method is proposed, the distinction of which is the use of the image background. This allows to simplify the process of scaling and segmentation (since all the pixels in the background are represented by the same color), non-uniform brightness of the face, and not to use the threshold settings and additional parameters.A binary image scaling method is proposed, the distinction of which is the use of an arithmetic mean filter with threshold processing and fast wavelet transform. This allows to speed up the image segmentation process by about P2 times, where P is the scaling parameter, and not to use the time-consuming procedure for determining.A binary scaled image segmentation method is proposed, the distinction of which is the use of density clustering. This allows to separate areas of the face of non-uniform brightness from the image background, noise and outliers. It also allows clusters to have different shapes and sizes, to not require setting the number of clusters and additional parameters.To determine the scaling parameter, numerous studies were conducted in this work, which concluded that the dependence of the segmentation time on the scaling parameter is close to exponential. It was also found that for small P, where P is the scaling parameter, the quality of face detection deteriorates slightly.The proposed technique for face detection in image based on binarization, scaling and segmentation can be used in intelligent computer systems for biometric identification of a person by the face image
FACE RECOGNITION USING WAVELET DECOMPOSITION TRANSFORMS AND REDUCTION RATE

The impact of the discrete Wavelet disintegration on the database which is utilized in biometric facial acknowledgment is the all out introduction of the paper. The individual distinguishing proof is such a lot of significant with regards to security. The recognizable proof of the face has become such a lot of significant nowadays. Since it is utilized in different parts like banking and financials which is of so much sense. The Olivetti and Oracle claim their facial acknowledgment preparing and testing. The Wavelet decay impacts of the information level were applied in testing and preparing which made the size of the database diminishing by 75% from their unique sizes. The primary part examination calculation is utilized to treat both the databases to get the impact on that on the facial acknowledgment rate. The primary segment investigation is biometric face acknowledgment. Subsequently, this diminished the face acknowledgment rate between the first and the decreased database is 2%. This strategy is progressively viable in the decrease databases and computational burden in providing for an adequate extent of acknowledgment rate.
AN EXPERIMENTAL APPROACH TO BUILD CONSUMER TRUST USING CLOUD TRUST LABEL

The lack of complete transparency in cloud related products has created a great sense of confusion and inefficiency among the consumers to choose the right product and make their buying decisions. As a result of this phenomenon the purchase or adoption of cloud computing has become even more difficult. This process of cloud trust labelling will provide relevant information to buyer to make the right decision/Choice thereby the decision making is made easier. This paper completely investigates the result of Cloud Trust labels and the consumers perception towards it to complete this research, a sample of 227 was used, all of business decision makers served as a sample. The data was collected before the exposure of cloud trust based label and after the exposure of the business trust label. And analysing the perceptions of each one before and after exposure and to examine and know the changes in perception too. The cloud trust labels that have Positive information contained has positive Perceptions and attitude. Correspondingly, negative perceptions had come when the Cloud Trust labels have negative information in them.
A Cell Potential and Motion Pattern Driven Multi-robot Coverage Path Planning Algorithm

This paper proposes an intelligent “Cell Potential and Motion Pattern driven Coverage (CPMPC)” algorithm to solve a cooperative coverage path planning problem for multiple robots in two-dimensional target environment. The target environment is divided into cell areas according to the detection range of robot, and the cell matrix is given correspondingly. The values in the cell matrix are defined as cell potential, which represents the number of times each cell is detected by robots. The priority of the robot’s neighbor cell is called the motion pattern. At different moments, robots can choose within different motion patterns. Genetic algorithm (GA) is used to optimize the combination of motion patterns. By taking account obstacle avoidance and collision avoidance into consideration, the CPMPC algorithm adopts a double-layer choice strategy driven by cell potential and motion pattern to generate the next waypoint. Furthermore, this algorithm contains two optimal strategies: avoiding collision and jumping out of the detected area. Compared with the pattern-based genetic algorithm, the results obtained by us show that the CPMPC algorithm could solve the multi-robot coverage path planning (MCPP) problem effectively with guarantee of complete coverage, and improved makespan.
Preface: The 3rd International Conference on Mathematics and Science Education (ICoMSE) 2019

First Page
Model-based calibration routine for a triangulation sensor for inner radius measurements of cylindrical components

None-tactile metrology systems for inner radius measurements of cylindrical objects with large diameters are often based on the triangulation principle, using a laser source as illumination unit and a camera as detection unit. Different approaches have been presented in the past in order to generate a complete profile section of the measurement object’s inner radius. A standard light-section sensor cannot provide a 360&deg; view of the radius without sensor rotation around the cylinder axis. The additional rotation axis needs to be calibrated and the captured point clouds registered in the same coordinate frame. To spare the necessity of a rotational axis, we developed a prototype sensor based on the hardware approach suggested by Yoshizawa et al.,<sup>1</sup> using a cylinder cone mirror and a laser illumination unit in order to generate a line circle projected onto the inner radius. In combination with a wide-angle camera, the laser line can be captured in one shot. Unlike the approach by Yoshizawa et al. , we present a model-based calibration routine for the triangulation sensor by mathematically describing the laser light path. The cone mirror expands the laser light into a disc (plane) or into a cone – depending on the incidence angle between laser and mirror. In our model, the light cone is parametrized by the right circular cone equation to reduce the number of unknowns in regression calculus. The necessary 3D support points to approximate the model parameter are gained by recording planar calibration pattern poses with and without laser line. The intersection calculation between the camera’s line-of-sight and the projected laser light geometry is derived, and the mathematical ambiguity in the line-cone intersection successfully solved. We present first experimental calibration and measurement data of a cylinder. By intentionally misaligning sensor and cylinder axes with arbitrarily chosen angles, the robustness of the suggested procedure is demonstrated.
Pre-Service Language Teachers' Autonomous Language Learning with Web 2.0 Tools and Mobile Applications.

Although the key role of utilizing Information and Communication Technology tools in foreign language learning and language teacher education is well-established in the literature, understanding the extent to which the student teachers of English are aware of and proficient in using ICT tools remains a key consideration. Therefore, this study was set out to investigate what Web 2.0 tools and mobile applications (henceforth apps) are used by student teachers in their personal and educational life. Consequently, this study, a) explored the familiarity of student teachers with available Web 2.0 tools and mobile apps, b) the frequency of the use of these tools, c) the aims of using these tools. The participants were 388 student teachers from two state universities in Turkey. The data were collected through a questionnaire with closed and open-ended questions. Descriptive statistics were used for the analysis of the questionnaire data and content analysis for the qualitative data. The findings revealed that most of the participants exhibited low degrees of familiarity and use towards the Web 2.0 tools and mobile apps. Results indicated that the most commonly used tools are the ones that contribute listening to and watching native and non-native English speakers. Moreover, student teachers do not know or use some technological tools such as corpus tools and virtual worlds, whose effects are well-established in the literature. One major implication of the results is that language teacher education programs offer a course on educational technology to student teachers of English.
A Study on the Future Society's Creative Convergence Education Program

급변하는 디지털환경과 4차 산업혁명 시대를 맞이하여 산업 패러다임의 변화가 빠르게 전개되고 있다. 빠르게 변화하는 사회에 대응하기 위하여 무엇보다도 먼저 준비해야 할 것은 미래시대에 미래세대를 위한 교육이다. 지금 초등학교에 입학 하는 아동이 사회에 나와 갖게 될 일자리의 거의 70퍼센트가 현재 존재하지도 않는 전혀 새로운 일자리가 될 것이라는 전문가들의 의견이 있다.1) 지금과 같이 정형화된 주입식 교육 내용과 방법으로는 다가오는 미래시대에 경쟁력 있는 주역으로 자리 잡는 것은 한계가 있을 것이다. 4차 산업혁명을 이끄는 동력으로는 인공지능, 로봇공학, 사물인터넷, 자율주행자동차, 3D프린팅, 나노기술, 생명공학, 재료공학, 에너지 저장 기술과 같은 과학기술이다. 과학기술이 가져온 변화의 시대에서 미래교육은 창의력과 융합적 사고력, 의사소통 능력, 공감력 등이 요구되며, 특히 동시대적 관심을 바탕으로 지식과 경험에 의한 아이디어를 도출하고 디자인적 사고력과 논리적 접근을 통한 문제해결능력 기반의 창의융합형 인재 육성의 필요성이 대두되고 있다. 학습자 스스로 비정형화된 문제해결과 비판적 사고, 소통, 협동 능력을 갖추고 창의력 있는 인재를 키우는 것을 상위 목표로 해야 하면서 외우는 공부보다는 현실적인 문제를 해결하며 만들어 보는 교육으로 바뀌어야 할 것이다. 본 연구에서는 4차 산업혁명의 미래사회를 주도 할 수 있는 문제해결능력과 공감과 소통을 기반으로 하는 디자인씽킹 사고에 중심을 둔 미래사회의 새로운 패러다임으로 디자인씽킹과 ic-pbl의 창의융합교육 프로그램을 제시하였다.With the rapidly changing digital environment and the era of the Fourth Industrial Revolution, changes in the industrial paradigm are rapidly developing. The first thing to prepare for is education for future generations in order to respond to a rapidly changing society. Experts say that nearly 70 percent of the jobs that children entering elementary schools will have in society will be new jobs that do not exist today. The content and methods of formalized infusion training will limit the future of Korea to become a competitive player. Powers leading the fourth industrial revolution are artificial intelligence, robotics, the Internet of Things, self-driving cars, 3D printing, nanotechnology, biotechnology, material engineering and energy storage technologies. In the era of change brought about by science and technology, future education requires creativity, convergence thinking skills, communication skills, empathy, etc. In particular, the need for fostering creative convergence talent based on design thinking skills and problem-solving skills based on contemporary interest is emerging. The goal should be to raise creative people with unformatted problem solving and critical thinking, communication and cooperation skills, while learning should be changed to education that addresses practical problems rather than studying. In this study, we presented design thinking and ic-pbl s creative convergence education programs as new paradigms for future society centered on design thinking thought based on empathy and communication, which can lead the future society of the fourth industrial revolution.
Better together: an ensemble learner for combining the results of ready-made entity linking systems

Entity linking (EL) is the task of automatically identifying entity mentions in text and resolving them to a corresponding entity in a reference knowledge base like Wikipedia. Throughout the past decade, a plethora of EL systems and pipelines have become available, where performance of individual systems varies heavily across corpora, languages or domains. Linking performance varies even between different mentions in the same text corpus, where, for instance, some EL approaches are better able to deal with short surface forms while others may perform better when more context information is available. To this end, we argue that performance may be optimised by exploiting results from distinct EL systems on the same corpus, thereby leveraging their individual strengths on a per-mention basis. In this paper, we introduce a supervised approach which exploits the output of multiple ready-made EL systems by predicting the correct link on a per-mention basis. Experimental results obtained on existing ground truth datasets and exploiting three state-of-the-art EL systems show the effectiveness of our approach and its capacity to significantly outperform the individual EL systems as well as a set of baseline methods.
Challenges in Context-Aware Mobile Applications Building Approaches

Context-aware mobile applications are immersed in our daily lives, allowing people to perform various tasks through the use of mobile devices. The complexity of designing these kinds of applications generate that different development tools have emerged to facilitate its creation. However, these development tools are often limited in the kind of applications that they derive which are generally based on the available APIs' sensors, such as GPS. From all the existing tools that could be allow to design and derive context-sensitive mobile applications, we are interested only in those that allow UML-based modeling. According to that, this paper analyzes different development tools to determine the variability of the kind of applications that can be generated with them. In order to carry out this analysis, we have taken into account the concepts proposed in a taxonomy of variability in building approaches for context-aware mobile applications. A discussion is presented in relation to the challenges involved to support variability in these tools.
Selection of Appliance Using Skeletal Tracking and 3D Face Tracking for Gesture Control Home Automation

This study implements 3d face tracking and skeletal tracking in Microsoft Kinect Xbox One. Once the user is detected by the sensor head point from skeletal tracking, and a computed point D from chin point and eyebrow midpoint from 3d face tracking will be used to create the Line of Sight vector. Also, appliance points are always specified by the location of the appliance in the room with respect to the Kinect. Different appliance vectors will be created through vector subtraction. Angles between the Line of Sight vector and each of the appliance vector were computed through scalar product and compared to obtain the smallest angle. Once the smallest angle was obtained it was compared to a 15-degree threshold. If it's within the threshold, then the appliance is selected.
REVIEW OF SALES AND INVENTORY ACCOUNTING INFORMATION SYSTEMS

The results of this study indicate that the sales and inventory accounting information system at the Chir Chir Fusion Chicken Factory Makassar still uses a manual system. The related functions in the sales and inventory accounting information system are waitrees, cooks, cashiers, financial admin, purchasing, cook, financial admin. The documents used in the sales and inventory accounting system are order notes, struck sales, purchase notes. The notes used in the sales and inventory accounting information system are sales records, and stock cards. The sales accounting information system procedure starts from the recording process of sales for inventory is a sales procedure that reduces inventory and purchases that add to the inventory.&#x0D; &#x0D; Keywords: Sales and Inventory Accounting Information Systems
Abstractive Text Summarization Using Enhanced Attention Model

Text summarization is the technique for generating a concise and precise summary of voluminous texts while focusing on the sections that convey useful information, and without losing the overall meaning. Although recent works are paying attentions in this domain, but still they have many limitations which need to be address.. This paper studies the attention model for abstractive text summarization and proposes three models named as Model 1, Model 2, and Model 3 which not only handle the limitations of the previous contemporary works but also strengthen the experimental results further. Empirical results on CNN/DailyMail dataset show that the proposed approach is promising.
Finding small solutions of the equation $ \mathit{{Bx-Ay = z}} $ and its applications to cryptanalysis of the RSA cryptosystem

<p style='text-indent:20px;'>In this paper, we study the condition of finding small solutions <inline-formula><tex-math id="M10">\begin{document}$ (x,y,z) = (x_0, y_0, z_0) $\end{document}</tex-math></inline-formula> of the equation <inline-formula><tex-math id="M11">\begin{document}$ Bx-Ay = z $\end{document}</tex-math></inline-formula>. The framework is derived from Wiener's small private exponent attack on RSA and May-Ritzenhofen's investigation about the implicit factorization problem, both of which can be generalized to solve the above equation. We show that these two methods, together with Coppersmith's method, are equivalent for solving <inline-formula><tex-math id="M12">\begin{document}$ Bx-Ay = z $\end{document}</tex-math></inline-formula> in the general case. Then based on Coppersmith's method, we present two improvements for solving <inline-formula><tex-math id="M13">\begin{document}$ Bx-Ay = z $\end{document}</tex-math></inline-formula> in some special cases. The first improvement pays attention to the case where either <inline-formula><tex-math id="M14">\begin{document}$ \gcd(x_0,z_0,A) $\end{document}</tex-math></inline-formula> or <inline-formula><tex-math id="M15">\begin{document}$ \gcd(y_0,z_0,B) $\end{document}</tex-math></inline-formula> is large enough. As the applications of this improvement, we propose some new cryptanalysis of RSA, such as new results about the generalized implicit factorization problem, attacks with known bits of the prime factor, and so on.
A Business Process Oriented Dynamic Cyber Threat Intelligence Model

Cyber threat intelligence (CTI) is a method for strengthening information security. CTI provides information on threats and the countermeasures. Businesses can benefit from the defensive knowledge if the relevant CTI is found. However, business environments involve miscellaneous dynamics of the business processes that can dynamically change the contexts. Correspondingly, threats associated with the contextual risk factors can change dynamically at the same time. Every time the contextual changes take place, CTI-based defensive strategies for businesses may not be useful and effective any more. However, the existing connection strategies between CTI and business risk contexts are still somewhat static. This paper proposes a business process oriented dynamic CTI model. The model can observe and capture the dynamics from the business environments. Every time the dynamics are captured, the model will then trigger adjustments of the connection strategies within the model. We use a case study to illustrate the use of the model and present how the model adjusts the connection strategies according to the dynamics. We then conclude the paper with future directions of the research.
Top-k Recommended Items: Applying Clustering Technique for Recommendation

This research proposes the Top-k Items Recommendation System which uses clustering techniques based on memory-based collaborative filtering technique. Currently, data sparsity and quantity of system are problems in memory-based collaborative filtering technique. We offer recommend or show some items set for user’s preference. In this research, we propose methods for recommended items set to user preference on data sparsity, movie lens datasets (1M) consisting of 671 users and 163,949 product items were used by determining the preference level between 1 and 5 and user satisfaction levels of all 98,903 items being build and test the models. Methods was divided into three parts included 1) Simple Agent Module 2) Neighbor Filtering and 3) Prediction and Recommend. Simple clustering was used to create a system to provide suggestions for sparsity data. Datasets obtained from clustering represented the sample agent of dataset to being create the recommendation system. Datasets were divided into two categories, 1) Traditional Data (TD) and 2) Statistic Data (SD), and each dataset clustered by k-means clustering. The experimental results demonstrated that the number of item types in the system were recommended in the TD and Euclidean (DIS). DIS was used to find the nearest value in TD for the item list recommendation to active users in the system with the a lot of number choice of recommendation system.
Continuous-Discrete Filtering and Smoothing on Submanifolds of Euclidean Space

In this paper the issue of filtering and smoothing in continuous discrete time is studied when the state variable evolves in some submanifold of Euclidean space, which may not have the usual Lebesgue measure. Formal expressions for prediction and smoothing problems are reviewed, which agree with the classical results except that the formal adjoint of the generator is different in general. These results are used to generalise the projection approach to filtering and smoothing to the case when the state variable evolves in some submanifold that lacks a Lebesgue measure. The approach is used to develop projection filters and smoothers based on the von Mises–Fisher distribution, which are shown to be outperform Gaussian estimators both in terms of estimation accuracy and computational speed in simulation experiments involving the tracking of a gravity vector.
A Cold Thinking on the Development of STEM Education

STEM Education is an interdisciplinary field that integrates science, technology, engineering and mathematics. It aims to cultivate students' creativity and problem-solving ability. STEM Education has been spread nationwide. This paper firstly introduces the meaning and development of STEM Education, reflects on its promotion and development process, then points out the problems and challenges in the promotion of STEM education. In addition, this paper offers some suggestions on how to promote STEM Education more effectively from the theoretical and practical level, expecting to provide useful reference for the launch of STEM Education in China.
Support to informal learning at work: a survey with the executive secretariat professionals of the Universidade Federal at Pará

The informal learning is a relevant strategy to improve the accomplishment of work assignments and to improve the performance of professionals.The support to informal learning is a construct to perceive how the institution, colleagues and managers incentive Suporte à aprendizagem informal no trabalho: uma investigação com os secretários executivos