Reviewerly/exHarmony huggingface dataset:
Multiple Kernel Clustering Based on Self-Weighted Local Kernel Alignment

Multiple kernel clustering based on local kernel alignment has achieved outstanding clustering performance by applying local kernel alignment on each sample. However, we observe that most of existing works usually assume that each local kernel alignment has the equal contribution to clustering performance, while local kernel alignment on different sample actually has different contribution to clustering performance. Therefore this assumption could have a negative effective on clustering performance. To solve this issue, we design a multiple kernel clustering algorithm based on self-weighted local kernel alignment, which can learn a proper weight to clustering performance for each local kernel alignment. Specifically, we introduce a new optimization variable- weight-to denote the contribution of each local kernel alignment to clustering performance, and then, weight, kernel combination coefficients and cluster membership are alternately optimized under kernel alignment frame. In addition, we develop a three-step alternate iterative optimization algorithm to address the resultant optimization problem. Broad experiments on five benchmark data sets have been put into effect to evaluate the clustering performance of the proposed algorithm. The experimental results distinctly demonstrate that the proposed algorithm outperforms the typical multiple kernel clustering algorithms, which illustrates the effectiveness of the proposed algorithm.
Fault Tolerance in Reversible Logic Circuits and Quantum Cost Optimization

Energy dissipation is a prominent factor for the very large scale integrated circuit (VLSI). The reversible logic-based circuit was capable to compute the logic without energy dissipation. Accordingly, reversible circuits are an emerging domain of research based on the low value of energy dissipation. At nano-level design, the critical factor in the logic computing paradigm is the fault. The proposed methodology of fault coverage is powerful for testability. In this article, we target three factors such as fault tolerance, fault coverage and fault detection in the reversible KMD Gates. Our analysis provides good evidence that the minimum test vector covers the 100 % fault coverage and 50 % fault tolerance in KMD Gate. Further, we show a comparison between the quantum equivalent and controlled V and V+ gate in all the types of KMD Gates. The proposed methodology mentions that after controlled V and V+ gate based ALU, divider and Vedic multiplier have a significant reduction in quantum cost. The comparative results of designs such as Vedic multiplier, division unit and ALU are obtained and they are analyzed showing significant improvement in quantum cost.
Determinants of Capital Flight: New Panel Evidence from Sub-Saharan Africa (SSA)

This paper examines the determinants of capital flight in sub Saharan African countries (SSA) by introducing corruption as a focus variable in the model. The econometric analysis is based on data from 25 SSA countries over the period 1986-2010 using dynamic panel data estimation methods: Corruption, our focus variable retains its expected positive sign and is statistically significant across all the estimations. The relationship remains very strong even when other standard control variables are taken into account. These results confirm our hypothesis that the nature of corruption in SSA is such that it encourages and promotes capital flight. The empirical findings also indicate that the capital flight in SSA countries is driven mainly by corruption, lag capital flight, external debt, foreign direct investment, and macroeconomic uncertainty. Based on these results, the paper recommends that governments in the region should manage their external debt efficiently, and stabilize their monetary and macroeconomic policies in order to curtail capital flight. Finally, our results are also robust to different specifications, measures of corruption, and econometrics estimation techniques.
Facial profile preferences: Perception difference among Indian population

It is a prospective, in-vivo randomized cross sectional questionnaire based study to determine general esthetic preference of Indian population and to find out whether this preference was affected by sex, age, education, social status and geographic location.Toward these aims, 30 well balanced facial profiles are selected (15 males and 15 females) in the age group of 18-30 years.The most attractive facial profile of 1 male and 1 female subject is selected by three panel of Judges.Profile selected for each sex were morphed by an Adobe Photoshop version cs2 technique and then scored by 200 participants.Subjects were asked to rank the profiles in ascending order of attractiveness on scoring scale 1 to 10. Morphing is done in 2 dimensions Sagittal and Vertical.Profile digital photographs were altered by 2mm and 4mm increments to produce different combinations of mandibular sagittal positions and vertical facial heights and to assess whether interactions and magnitude of the sagittal and vertical facial dimensions influence perception of facial attractiveness.Analysis of variance (ANOVA) and independent sample t-tests were used to compare the preferences of the groups.The orthognathic profile and straight profile in both sexes was selected as the most preferred profile whereas the convex profile with a prognathic maxilla and a retrognathic mandible were the least preferred.The public also admired fuller and protrusive lips in females and retrusive lips in males.Sex, age, education, social status and geographic location were also shown to affect the public's profile preferences.
Blur-readable two-dimensional barcode based on blur-invariant shape and geometric features

In recent years, the application of two-dimensional (2D) barcode is more and more extensive and has been used as landmarks for robots to detect and peruse the information. However, it is hard to obtain a sharp 2D barcode image because of the moving robot, and the common solution is to deblur the blurry image before decoding the barcode. Image deblurring is an ill-posed problem, where ringing artifacts are commonly presented in the deblurred image, which causes the increase of decoding time and the limited improvement of decoding accuracy. In this article, a novel approach is proposed using blur-invariant shape and geometric features to make a blur-readable (BR) 2D barcode, which can be directly decoded even when seriously blurred. The finder patterns of BR code consist of two concentric rings and five disjoint disks, whose centroids form two triangles. The outer edges of the concentric rings can be regarded as blur-invariant shapes, which enable BR code to be quickly located even in a blurred image. The inner angles of the triangle are of blur-invariant geometric features, which can be used to store the format information of BR code. When suffering from severe defocus blur, the BR code can not only reduce the decoding time by skipping the deblurring process but also improve the decoding accuracy. With the defocus blur described by circular disk point-spread function, simulation results verify the performance of blur-invariant shape and the performance of BR code under blurred image situation.
Case Based Reasoning And Naive Bayes Implementation In Laptop Purchasing Recommender System

Purchasing a new laptop will be difficult if we do not know what the ideal laptop specification for our needs. Especially with a wide selection of laptops. From this problem, system that can give a recommendation to choose the right laptop based on purchaser’s specification choice is needed. This research using two method, Case Based Reasoning and Naive Bayes. The concept of Case Based Reasoning is the process of solving new problems based on the solutions of similar past problems, While Naive Bayes assumes that the presence of a particular feature in a class is unrelated to the presence of any other feature. Naive bayes will be implemented in retrive process of case based reasoning. The recommender system utilizing 7 feature, Kecepatan Processor, Kapasitas Ram, Tipe Grafis, Ukuran Layar, Ukuran Harddisk, Kecepatan Layar, and Harga. The percentage of respondents who said the system was successful in providing the right recommendations was 70 percent of the total respondents.
Technologies, Learning and Cognitive Models

The progressive increase in the use of multimedia and interactive platforms, including the world of social media, of mobile devices, which affects the new generations, must be considered.In particular, the prospect of integrating technologies into learning and teaching processes is not possible.In this paper, we intend to describe a research that has been done in this sense and develop the reflections it has aroused.In articulate this paper describes an experiment of introduction of software tools and technologies inspired by the principles of educational robotics to improve the learning level of middle school students.The research that is structured and implemented has as its central theme the use of technology to support learning-teaching processes.In particular, the central theme is how technological development strongly characterizes every section of people's lives.If technology enters the learning-teaching processes, it is certainly necessary to evaluate the problems and the potential to add value.In summary, the theme is to integrate technologies that are already pervading people's lives, in learning-teaching processes in formal teaching contexts.For the world of education in formal environments, we want to define how it is possible to establish a virtuous circle that begins with the training of teachers for the design and implementation of effective and virtuous processes from a cognitive point of view.The research has shown that the effective use of technologies in learning teaching processes is possible and that technology can be a transversal, technological and methodological competence.
Categorical Vector Space Semantics for Lambek Calculus with a Relevant Modality (Extended Abstract).

We develop a categorical compositional distributional semantics for Lambek Calculus with a Relevant Modality, which has a limited version of the contraction and permutation rules. The categorical part of the semantics is a monoidal biclosed category with a coalgebra modality as defined on Differential Categories. We instantiate this category to finite dimensional vector spaces and linear maps via quantisation functors and work with three concrete interpretations of the coalgebra modality. We apply the model to construct categorical and concrete semantic interpretations for the motivating example of this extended calculus: the derivation of a phrase with a parasitic gap. The effectiveness of the concrete interpretations are evaluated via a disambiguation task, on an extension of a sentence disambiguation dataset to parasitic gap phrases, using BERT, Word2Vec, and FastText vectors and Relational tensors
English Speaking Anxiety in Language Learning Classroom

English as a foreign language consists of four skills namely, listening, speaking, reading, and writing. These skills have a particular issue that happens differently for each student. For this reason, it's not easy to understand and master the four language skills effectively. Several issues need to overcome first to increase the effectiveness of each ability. Speaking is one of the skills that seem to represent the students' proficiency to speak English. Unfortunately, the majority of Indonesian students, in particular those at the university level, do not provide an appropriate way to speak English proficiently. Students in the 4.0 era are expected to have good communication skills and the ability to socialize with their community. Speaking also requires practice and a deep psychological pleasure that needs to be comfortable. A related study that improves the effectiveness of speaking in language teaching and learning is important. This study is a descriptive study that explains the importance of effective communication in English as a foreign language. This study also provides an opportunity to measure the effectiveness of teaching and learning English speaking skills earlier in the process, which can increase students' confidence and decrease students' anxiety in speaking skills.
Perancangan Pembuatan Aplikasi Pengenalan dan Penerjemah Bahasa Isyarat SIBI Menggunakan Leap Motion dengan Metode Hidden Markov Models

ABSTRACTSign language is a form of communication used by persons with disabilities who are deaf to communicate through movement. Every movement in sign language has a meaning that not everyone can understand. To be able to translate the meaning of each movement needed a pattern recognition method. The method used in designing this application is Hidden Markov Models.In designing this application using a Leap Motion camera that functions as a sensor to capture the movement of the skeleton in the hand. The sign language movement that is translated is SIBI sign language consisting of 5 words namely Brother, Sister, Eat, Patience and I.Based on the results of testing and analysis shows that the system as a whole has not been able to recognize movement well, with success reaching around 20%. This is because there are still errors in the learning process.
Developing of USDZ models for 3D digital analysis results visualization in augmented reality

The active development of augmented reality (AR) technologies in recent years leads to their increasing application in various fields of sciences.Especially the use of AR can be promising in areas where the results are represented in 3D, have complex shapes and it is often necessary to show them at different angles and zoom, such as digital rock analysis.One of the possible approaches is creating AR-models in the open format of Universal Scene Description Zipped (USDZ), developed jointly by Apple and Pixar and currently supported by a huge number of different mobile devices.This 3D format is distinguished by advanced texturing based on Physically Based Rendering (PBR), the ability to support high-poly models, 3D animation, sounds, creating complex scenes with the assignment of reactions to individual objects and ease sharing using emails, messengers, and websites.This work briefly describes the basics of USDZ models including file structure, meshing, UV mapping, and texturing.It also discusses the methodology for AR-models development based on the results of digital analysis using free software starting from CT-scanning and finishing with exporting.In addition, the information about the limitations of USDZ models and prospects for the development of using USDZ models were provided.The results can be used for native demonstration of 3D research output, quick access and exchange the visual information, for exhibitions in museums and educational purposes.AR models make it easy to share the 3D visual results with people, which can be integrated into websites and used for the support of the scientific publications or native demonstrations on conferences.
Active Environmental Monitoring and Anomaly Search System for Space Habitat With Markov Decision Process and Active Sensing

For future crewed missions that could last years with limited ground support, the environmental control and life support system (ECLSS) will likely evolve to meet new, more stringent reliability and autonomy requirements. In this work, we focus on improving the performance of the environmental monitoring and anomaly detection systems using Markov decision process and active sensing. We exploit actively moving sensors to develop a novel sensing architecture and supporting analytics, termed Active environmental Monitoring and Anomaly Search System (AMASS). We design a Dynamic Value Iteration policy to solve the path planning problem for the moving sensors in a dynamic environment. To test and validate AMASS, we developed a series of computational experiments for fire search, and we assessed the performance against three metrics: (1) anomaly detection time lag, (2) source location uncertainty, and (3) state estimation error. The results demonstrate that: AMASS provides 10~15 times better performance than the traditional fixed sensor monitoring and detection strategy; ventilation in the monitored environment affects the performance by 6~40 times for any monitoring architecture with fixed or moving sensors; the monitoring performance cannot be fully reflected in a monolithic, single metric, but should include different metrics for the timeliness and spatial resolution of the detection function.
Impact of Distance Measures in Shepards Interpolation Algorithm on Natural Images Corrupted by Outliers

The impact of Distance Measures in an Interpolation Algorithm on Natural images corrupted by Outliers is proposed. The Adaptive Inverse Distance Interpolation (Shepards algorithm) is modified with various distances for increasing distances. The Window size increases adaptively when three non noisy pixels does not exist in the current processing window. It was found that L1 Norm is robust than L2 Norm on Natural images corrupted by high density outliers noise. The algorithm requires a minimum of three non noisy pixels to perform L1 norm based Sheppard algorithm. Exhaustive testing were done on images of standard Database The use of L1 Norm based as distance measure between the processed pixel and non noisy pixel had a better impact on the performance of the algorithm in the presence of outliers with information preservation.
Boosting Education Through Mobile Technology in India - Study with Reference to Generation Z

Twenty-first century recognize the younger generation as Gen Z that is mobile first generation who live-in the virtual world in par with reality through extensive usage of smartphones & related gadgets. The usage of Mobile Technology in the education sector has become the need of the day. Students have started relying on mobiles for information, surfing the net, chatting, using applications and connecting to social media like WhatsApp, Facebook, Instagram, Twitter, Viber, etc. The usage of mobile technology depends on the emerging need for the advancement of education and student behavioural patterns. In the competitive era, the accomplishment of extensive learning goals is possible only by the adaptation of new teaching  pedagogies. The educational institutions have started encouraging teaching and learning pedagogies which are suitable to Gen Z along with regimented chalk and talk method. Schools have started using applications to compete with the current style of education. Information Technology has changed the world into Gen Z where people think, senses and use information through technology. This study aims to evaluate the utilization of mobile technology in classroom teaching, analyze the impact of technology towards enriching the learning abilities of the students, to explore new pedagogies suitable for learning and teaching. This paper suggests measures to teaching fraternity to improve the pattern of educational delivery by introducing innovative and advanced techniques of mobile technologies.
TEACHER MOTIVATION AND STIMULATION IN HIGHER EDUCATION INSTITUTIONS OF RUSSIA: CURRENT STATE, EXPERIENCE, PROBLEMS, SEARCH FOR NEW MODELS

The quality of education and its effectiveness are largely determined by the qualities of those who teach, the people who conduct the educational process. This article discusses the factors that determine the quality of teaching staff in higher education institutions. It analyzes the environmental conditions that determine teachers' attitudes and affect motivation in professional activity at present and further compares it with other historical periods when the conditions in the field were different from the current ones.
Perbandingan Pengelompokan K-Means dan K-Medoids Pada Data Potensi Kebakaran Hutan/Lahan Berdasarkan Persebaran Titik Panas

The cases of forest/land fires in Indonesia seem endless, almost every year in the dry season similar problems always occur. Some areas in Indonesia often occur in forest fires and result in losses of up to trillions of rupiah.  Various ways have been made to help the government in minimizing the potential for forest or land fires, one of them is by monitoring hot spots. In this study using data hot spots with parameters of latitude, longitude, brightness, fire radiation power and confidence by using the method of grouping K-Means and K-Medoids. The difference between these two methods is that the K-means method uses the mean as the center of the cluster, while K-Medoids uses representative objects (medoids) as the center of the cluster. This study aims to compare the results of the grouping of K-Means method with K-Medoids by using 42 data. The results of this study indicate that the K-Means method produces Silhouette Coefficient scores greater than K-Medoids. So that, K-Means can provide more accurate grouping results with a greater Silhouette Coefficient value.
Pengembangan Bahan Ajar Tematik Terpadu dengan Model Cooperative Script di Kelas IV Sekolah Dasar

Teachers are very instrumental in developing effective teaching materials to encourage the progress of students in learning. Meanwhile, the existing teaching materials still need improvements because there are several errors such as paragraphs in the reading text that are not aligned left-right, errors in capital letters. Therefore, to solve this roblem, it is necessary to find a solution in the form of developing integrated thematic teaching materials based on the cooperative script model for grade IV elementary school students. This study aims to produce valid teaching materials. This type of research is development research using the 4-D model (four D model). This model consists of four stages, namely define, design, develop and disseminate. The results showed that the integrated thematic teaching materials using the cooperative script model developed obtained the validity percentage of teaching materials was 87.5% (material) with a very valid category, 75% (language) with a valid category, and 81.8% (design) with very valid category.
Knowledge Incorporation in Requirements Traceability Recovery

The necessity of continuous change and adaptation in software systems makes maintenance tasks complex and difficult. One of the challenges in software maintenance is keeping requirements traceability up to date automatically. This problem can be considered as an optimization problem where the goal is to assign each requirement to one or many software artifacts (class, method, variable, etc.). However, some of the traceability links proposed using this approach do not necessarily make sense depending on the context and the semantic of the system under analysis. This paper proposes an approach that tackles this problem by adapting the Interactive Genetic Algorithm (IGA) which enables to interact with users and integrate their feedbacks into a classic GA. The proposed algorithm uses a fitness function that combines the recency of change, the frequency of change, and the semantic similarity between the description of the requirement and the software artifact, and the designers’ ratings of the traceability links proposed during execution of the classic GA. Experimentation with the approach yielded interesting and promising results.