Reviewerly/exHarmony huggingface dataset:
Can we save near-dying games? An approach using advantage of initiative and game refinement measures

Games are attractive and engaging due to the complexity they pose to the player.Some games are complex enough which made them attractive to play.However, popular games would lose their attractiveness due to the large advantage of initiative.Highperformance AI like AlphaZero suggests from their actual games played that advantage of the first player would become larger as the performance level increases.This implies that games with a large advantage of the initiative would lose their attractiveness due to the unfairness.This paper explores an innovative way to make a game stay attractive.A link between the advantage of initiative and performance level is investigated while using Scrabble AI.Using two measures: the advantage of initiative and game refinement, possible treatments are considered.The experimental results with Scrabble AI suggest that reduction of search space from 15x15 to 13x13 board size is a possible enhancement.
A development of content-based video summarization system using machine-learning and its application to analysis of livestock behavior

In this work, we propose a static video summarization approach for the analysis of cattle's movement. An original digital video with a length of about 1 hour (58 minutes and 42 seconds) recording the daily behaviors of cattle in cattle barn was applied as the experimental object. In the approach, machine learning, statistics and color histogram are used to extract key-frames from the video. And it can be confirmed that this approach achieve the purpose of video summarization based on cattle's movement through analyzing the results of the experiment.
Clustering stability evaluation method based on SSIM

In the clustering validity analysis, three main methods including intra-class cohesion, inter-class separation, and artificial judgment index can be used to evaluate the clustering results. If the clustering result is efficient, it means that the clustering stability is better. However, when those methods are used, it is essential to provide the sample data or clustering algorithms in advance. This paper proposes a clustering stability evaluation method based on the Elliptic Fourier Descriptor structural similarity index (EFD-SSIM), which can evaluate the clustering stability only when the clustering result is available. Its mechanism is that cluster is mapped into 2D graphics, and the degree of intra-class cohesion is measured based on the structural similarity (SSIM) on the graphics. As shown by the experimental results, EFD-SSIM has a good evaluation effect and it is consistent with the existing effectiveness evaluation indices of the clustering algorithm.
A Scale-Insensitive Convolutional Neural Network for Fast Vehicle Detection

The Vision-based vehicle discovery methodologies make mind blowing progress as of late with the advancement of profound convolutional neural system (CNN). In any case, existing CNN based calculations experience the ill effects of the issue that the convolutional highlights are scale-touchy in item identification task however usually traffic pictures and recordings contain vehicles with a huge difference of scales. Precise vehicle identification or arrangement assumes a significant job in Intelligent Transportations Systems. Capacity to recognize vehicles in rush hour gridlock scenes permits breaking down drivers' conduct just as distinguishes traffic offenses and mishaps. Recognition and arrangement of vehicles is a difficult undertaking because of climate and light conditions and vehicle type decent variety. In any case, convolutional neural systems have demonstrated to be conceivably progressively successful. In this postulation, we present a convolutional neural system prepared to arrange and recognize vehicles. We present a scale-unfeeling convolutional neural system (SINet) for quick identifying vehicles with an enormous difference of scales. These lightweight strategies bring zero additional time intricacy yet unmistakable discovery precision improvement. The proposed systems can be outfitted with any profound system models and keep them prepared start to finish. Raspberry Pi is utilized.
A Quranic Dataset for Text Recognition

Any text recognition or Optical Character Recognition (OCR) system requires a dataset to learn how to recognize the text.Due to the lack of a standard benchmark, most of the studies in this field were conducted using private datasets without a fair comparison.In this work, we used the standard Mushaf al Madinah benchmark where there are some rules in writing style, for example, the page should start with the beginning of verse and end with the end of verse.Following these rules make the words vary in size and paragraphs on different pages.These characteristics making the recognition of the Quranic text more challenging than the normal Arabic text, where the state of the art systems fails to recognize the Quranic text.Therefore, Quranic OCR dataset is presented in this study.It contains 604 images on page level and 8927 images in text-line level.This dataset is public and free to use for the research community.The Quranic dataset would help the researchers in the field of Arabic OCR where the dataset produced in this study would be made public and free for the use of research purposes.
IMPROVING THE STUDENTS' READING COMPREHENSION OF ANALYTICAL EXPOSITION TEXT BY USING THINK-PAIR-SHARE (TPS)

This study aims to improve reading comprehension for the eleventh-grade students at SMA MATHLAUL ANWAR, consisting of 30 students in using the think-pair-share model. The researchers applied the think-pair-share model because this considered the model as one of the best teaching methods for teaching. Students use the think-pair-share model in learning activities to raise their reading comprehension, increase their enthusiasm, and become active in classroom learning. Besides, the benefits of using the Think-Pair-Share method in reading discussions will reveal opportunities to encourage students to be active in the learning process, such as discussing and helping each other solve problems or assignments. That will have a positive impact on students in accepted learning material provided by the teacher. In this study, the writer researched three cycles to achieve student improvement in reading comprehension. The results of the tests that have been done lead to the mean grade of students in each cycle as a follow-up pre-cycle is 68, while in the second cycle 71, and the last can be seen as a terrace in the third cycle 75. Based on the mean grade of two cycles above, we can prove that the think-pair-share technique has succeeded in increasing the students' ability to teach reading comprehension in analytical exposition texts.
Writer-independent Offline Handwritten Signature Verification using Novel Feature Extraction Techniques

Signature is critical for authentication and authorization in commercial, financial and legal transactions and fittingly, it is one of the most commonly used biometrics for authentication.Hence, an accurate and efficient signature verification system is required.The objective of signature verification is to discriminate the original signatures from the forged ones.It is a challenging task as even two signatures of the same person possess variations in different areas such as the starting and ending positions, the angle of inclination, relative spacing between letters, height, width etc. Offline signature verification is even more challenging as it is devoid of the dynamic information about the signing process.Although numerous research works have been done in the area of offline signature verification in last decades, it still remains an open research problem.There are three common phases in signature verification system: image preprocessing, feature extraction and verification.In this paper, two novel features have been presented that can be extracted from preprocessed signature images in the feature extraction phase.The proposed features are: i) Stroke angle and average intersected points ii) Pixel density of the signature nucleus.The goal of this research is to strengthen the feature set with the proposed features what will help to get more accurate verification of the signatures.
APPLICATION OF WORLDVIEW-3 DATA IN ALTERATION MINERAL MAPPING IN CHADORMALU AREA, CENTRAL IRAN

Abstract. WorldView-3 (WV-3), launched in August 2014, is a commercial imaging satellite with high spatial resolution that measures reflected radiation in VNIR-SWIR regions in 16 bands. The main objective of this study was to discriminate the alteration minerals in Chadormalu iron deposit area, central Iran, using band ratio techniques on the selected bands of this satellite. To identify the appropriate band ratios the spectral bands of WV-3 were investigated and assessed. Regarding to Fe3+, Fe2+, Al-OH, Fe-OH, Mg-OH and CO32− spectral absorption features, band ratios B5/B2, B13/B9, B13/B14 and B14/B16 were proposed for enhancement of ferrous and ferric iron bearing minerals, sericite, epidote, chlorite, and dolomite. Combination of field observations, geological map and high resolution spectra of rock samples were used to verify the results. Band ratio B5/B2, B13/B9, B13/B14 gray scale images respectively illustrated that Fe3+-rich minerals are occurring in granite, the Fe2+-rich minerals are enhanced in iron ore, green schist, and diorite units, and sericite is occurring in hydrothermally altered granite and iron ore. Since the Fe/Mg-OH vibrational mode in chlorite-epidote and spectral absorption feature of CO32− in dolomite occur in B16, the B14/B16 ratio highlighted chlorite-epidote-rich green schist, diorite and dolomitic marble. The false color composite image of B13/B14, B13/B9, and B14/B16 as RGB produced a large scale map which successfully discriminated the rock types and accompanying alteration minerals. This study demonstrated that WV-3 data have efficient spectral resolution to discriminate alteration minerals with Fe3+, Fe2+, Al-OH and Fe/Mg-OH or CO32− spectral absorption features.
Progressive Web App - The future of Web Development

Research support that 20% of app users are lost between user's initial contact with app and first experience. App can be downloaded and installed from app store. Progressive web app enables the user to instantly go through the app, thus skipping downloading and installation stages. And on returning to app they will be instigated to install the app and upgrade to a full screen experience. However, a native app has its own set of advantages. Mobile applications with push notification are able to sustain their users up to 3 times more than their equivalents. In addition, the end user would prefer mobile application over website, as mobile application consumes less data and is quicker as resources are saved on the device. Thus, a progressive web app has improved user withholding and performance and reduced complexity in up keeping a mobile application.
Fundamental limit and trade-off between security and secure key generation rate in quantum key distribution

Many researchers have contributed to creating Quantum Key Distribution (QKD) since the first protocol BB84 was proposed in 1984.One of the crucial problems in QKD is to guarantee its security with finite-key lengths by Privacy Amplification (PA).However, finite-key analyses show a trade-off between the security of BB84 and the secure key rates.This study analyses two examples to show concrete trade-offs.Furthermore, even though the QKD keys have been perceived to be arbitrarily secure, this study shows a fundamental limitation in the security of the keys by connecting Leftover Hash Lemma and Guessing Secrecy on the QKD keys.
Linear Discriminative Learning for Image Classification

In this paper, we propose a linear discriminative learning model called adaptive locality-based weighted collaborative representation (ALWCR) that formulates the image classification task as an optimization problem to reduce the reconstruction error between the query sample and its computed linear representation. The optimal linear representation for a query image is obtained by using the weighted regularized linear regression approach which incorporates intrinsic locality structure and feature variance between data into representation. The resultant representation increases the discrimination ability for correct classification. The proposed ALWCR method can be considered an extension of the collaborative representation- (CR-) based classification approach which is an alternative to the sparse representation- (SR-) based classification method. ALWCR improved the discriminant ability for classification as compared with CR original formulation and overcomes the limitations that arose due to a small training sample size and low feature dimension. Experimental results obtained using various feature dimensions on well-known publicly available face and digit datasets have verified the competitiveness of the proposed method against competing image classification methods.
Eigenspectrum Regularization on Grassmann Discriminant Analysis With Image Set Classification

Set-based image classification has become popular in recent years since it can provide a relatively large amount of within-set information that benefits classification. Grassmann Discriminant Analysis (GDA) models image sets as points (subspaces) on a Grassmann manifold and then explicitly maps them to a higher-dimensional Hilbert space, where Euclidean geometry applies, for Linear Discriminant Analysis (LDA). However, due to the noise disturbance and finite number of training samples in practice, the conventional problems of LDA, such as the singularity of the within-class scatter matrix and the instability of its inverse, also appear with GDA, which result in recognition performance deterioration. Inspired by eigenspectrum regularization techniques, we propose an eigenspectrum Regularized GDA (RGDA) method to alleviate the conventional problems of GDA in Grassmannian space. Moreover, we implement it with the graph embedded framework, three different eigenspectrum regularization models are incorporated into the proposed approach respectively. Extensive experimental results on set-based face recognition and object categorization tasks have confirmed the effectiveness of our approaches.
Expert System For Diagnosing Hemophilia In Children Using Case Based Reasoning

Many people who have children do not know about hemophilia, because this disease is one of the rare diseases. Hemophilia is a genetic disorder in the blood caused by a lack of blood clotting factors. Therefore there is a need for information for the public to be able to find out about this disease, so that when there is an unnatural bleeding, early treatment can be done properly.Therefore an expert system was designed to diagnose early hemophilia in children.The method used in this expert system is the Case Based Reasoning method. The Case Based Reasoning method is a method used to solve a new case by adapting the symptoms found in previous cases that are similar to the new case.This expert system can provide solutions / early prevention of the diagnostic process carried out. Expert system applications are designed based on websites using the PHP programming language.
Games as a Form of Career Guidance

The authors of the article analyzed the scientific research on the use of methods and gamification techniques in career guidance and concluded that it is necessary to work out career guidance games, make sure that elements of physical activity are included in career guidance games, since the board career guidance games do not take into account the “hyperactivity” of the modern generation. The article presents the results of the analysis of career guidance work in the monotown (Nizhnekamsk, The Republic of Tatarstan), identifies factors of its low efficiency: a formal approach to the development of career guidance activities, absence of innovative forms of work in practice, reluctance of managers of enterprises and organizations to cooperate with educational organizations using new forms of career guidance, a low number of highly-qualified and motivated professionals working with innovative methods of career guidance. The study made it possible to identify problems in the implementation of career guidance projects in the monotown. These included: actually no chance of conducting professional tests in real production conditions; provocative policy of the management of enterprises, expressed in the unwillingness to take responsibility for safety of participants in career guidance projects; the lack of personnel in organizations capable of organizing and conducting professional tests in production conditions; the lack of corporate personnel policies of city-forming enterprises in the field of career guidance for children and youth, corporate programs for conducting professional samples. The paper describes the proprietary methodology of conducting professional samples in the form of a quest game which allows acquainting school-age children with the professions of city-forming enterprises in the monotown. Besides, measures to systematize and increase the effectiveness of career guidance work in single-industry conditions are proposed.
Development of a Social Acceptance Scale for Inclusive Education

In this research, the development stages of the "Social Acceptance Scale for Inclusive Education" developed to measure the social acceptance levels of inclusive students were presented in detail.The research was conducted in 4 primary and 2 secondary schools located in Kayseri city center.A total of 488 students receiving education in 4th, 5th, 6th, 7th and 8th grades participated in the study.During the development phase of the test form, 48 students in 2 classes in an elementary school were asked 3 open-ended questions about inclusive education and asked to explain their feelings and thoughts.At the same time, the opinions of 5 teachers in these schools were also evaluated.A scale consisting of 56 items was prepared, and the number of items in the scale was reduced to 44 as a result of the expert opinions in the field.Students, who needed special education in their classrooms, who were affected by migration and terrorism, and who were under temporary protection, were reached by using criterion sampling method in the selection of sample.In order to provide evidence for the validity of the scale, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were applied to the measuring instrument within the scope of structural validity.The statistical calculations of the obtained data were performed in SPSS-21 and Lisrel 8.80 software.As a result of factor analysis, Cronbach's alpha reliability coefficient of the scale consisting of a single factor and 30 items was found as 0.94.As a result of the findings, it was determined that the scale measured the social acceptance level of the inclusive students in a valid and reliable way.
A Survey on Digital Immigrants’ Technology Usage and Practice in Teaching Digital Natives

The widespread use of digital technologies by digital natives has put a considerable amount of pressure on their educators, who are mostly digital immigrants, to recognize the relevance of digital connectivity, learn new ways of thinking and processing information of the digital natives, and integrate it into their teaching environments. The current study looks into these aspects while discussing the technology usage and practice of digital immigrant educators in higher education. A survey was conducted with a structured questionnaire on the technology usage and teaching strategies implemented by the digital immigrant educators to teach digital natives in higher education. The findings reported that digital immigrant educators must be accustomed to the a) diverse needs of digital native students and b) use and applications of digital technologies in order to create and practice interactive and collaborative teaching environments.
Constructing Two Classes of Boolean Functions With Good Cryptographic Properties

Wu et al. proposed a generalized Tu-Deng conjecture over <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathbb {F}_{2^{rm}}\times {\mathbb {F}_{2^{m}}}$ </tex-math></inline-formula> , and constructed Boolean functions with good properties. However the proof of the generalized conjecture is still open. Based on Wu’s work and assuming that the conjecture is true, we come up with a new class of balanced Boolean functions which has optimal algebraic degree, high nonlinearity and optimal algebraic immunity. The Boolean function also behaves well against fast algebraic attacks. Meanwhile we construct another class of Boolean functions by concatenation, which is 1-resilient and also has other good cryptographic properties.
P4‐389: CARE SUPPORT SYSTEM USING ONTOLOGICAL MODEL OF CARING PATIENT WITH DEMENTIA

Caregivers for Person with Dementia (PwD) have difficulties in choosing the appropriate care method because of the complex behavior and psychological symptoms of dementia. To alleviate such problems, interventions that use Web-based applications have been proposed. For example, some systems are designed to share care knowledge among different caregivers so that caregivers can make suitable care decisions for individual PwD. In this study, we introduce a dementia care support system equipped with an ontological model of caring PwD that could provide various care guidelines through personal computer system. We expanded the ontological model of caring PwD that was previously developed in the lab (Fig 1). In essence, we added more knowledges on activities of daily living, dementia symptoms and related care methods that are required to help PwD during daily living at home. To infer distinct care method for individual PwD with different symptoms, proposed system is equipped with contextual reasoners programmed in Semantic Web Rule Languages (SWRL) and Prolog. Figure 2 shows the overall architecture of the system consisting three different components: perception manager, knowledge system and application module. Contextual data from several sensors is processed by the perception manager. Recognition results and query for care method are transmitted to the knowledge system to retrieve possible care methods, which are provided through the robot platform or knowledge sharing platform in application module. Figure 3 illustrates an example of reasoning process when caregiver's task is to help PwD eat a meal. Through knowledge sharing platform, caregiver can not only provide patient assessment information but also obtain care guide for different task. For example, caregiver can find (1) necessary objects to be prepared for a task, (2) spatial information of objects, (3) temporal events related with current and future task and so on (Fig. 4).