Reviewerly/exHarmony huggingface dataset:
Approximate Multiplication of Sparse Matrices with Limited Space

Approximate matrix multiplication with limited space has received ever-increasing attention due to the emergence of large-scale applications. Recently, based on a popular matrix sketching algorithm---frequent directions, previous work has introduced co-occuring directions (COD) to reduce the approximation error for this problem. Although it enjoys the space complexity of O((m_x+m_y)l) for two input matrices X∈ℝ^{m_x ╳ n} and Y∈ℝ^{m_y ╳ n} where l is the sketch size, its time complexity is O(n(m_x+m_y+l)l), which is still very high for large input matrices. In this paper, we propose to reduce the time complexity by exploiting the sparsity of the input matrices. The key idea is to employ an approximate singular value decomposition (SVD) method which can utilize the sparsity, to reduce the number of QR decompositions required by COD. In this way, we develop sparse co-occuring directions, which reduces the time complexity to Õ((nnz(X)+nnz(Y))l+nl^2) in expectation while keeps the same space complexity as O((m_x+m_y)l), where nnz(X) denotes the number of non-zero entries in X and the Õ notation hides constant factors as well as polylogarithmic factors. Theoretical analysis reveals that the approximation error of our algorithm is almost the same as that of COD. Furthermore, we empirically verify the efficiency and effectiveness of our algorithm.
The causality among e-money, manufacturing, services and money supply: an empirical evidence of ASEAN countries

The economic transition happened in ASEAN countries caused the increased growth of e-money use. This study was established to discover the causal relation between the growth in manufacturing and service sector and the e-money usage through causality panel approach. Furthermore, this study also focused on finding the causality among the economic growth in manufacturing and service sector, e-money and money supply during 2008-2018 period in the region. The result of the study showed that: (1) there was a one-way causality between the growth in service sector and e-money use, (2) there was no causality between e-money use and the growth in manufacturing sector (3) the growth of money supply provided causal effect on the increase of e-money use.
Hardware based cryptography: technological advances for applications in Colombia using embedded systems

To have totally independent systems that offer a sufficient security scheme has become a necessity in Colombia, this because of the proliferation of IoT type systems and similar; In general, it is required to make stand-alone systems totally independent and distributed to offer users a solution to this need, this work offers the analysis and comparison of two security schemes type digital signature and/or hardware security module (HSM) and its variations, made on embedded platforms type microcontroller software, which shows the strategy to provide information protection, In addition, it is analyzed how each implementation was executed, in which devices and metrics of interest, in the first application the cryptography schemes were made using a deep programming that describes the algorithms in C++ language and in the second implementation the use of the dedicated hardware that the embedded platform type microcontroller had is detailed; In both cases, solutions with an acceptable throughput were generated, allowing to obtain comparable solutions and the same style as those made in a PC or similar hardware. On the other hand, an exhaustive review of this type of solutions in the country-region was made, in order to have a reference as to the possible use of this type of applications.
Pengaruh Model Pembelajaran Kooperatif Tipe Time Token Terhadap Hasil Belajar Bahasa Indonesia Siswa SD

: This research to find out whether there is the influence of the cooperative to time token type learning model on the learning outcomes of Indonesian language speaking skills in fifth grade students of SD Negeri 1 Massepe. This research uses a quantitative approach to the type of experimental research and uses a Pre-Experimental design in the form of One Group Pre-test - Post-test Design. The sampling technique used in this study was purposive sampling technique with a sample of 15 students. The results of hypothesis testing using the One Sample T-Test test obtained a significance of 0.00 (0.00 &lt;0.05) the average score of the pretest was smaller than the average score of the posttest or µ1 ˂ µ2 indicating that H0 was rejected and Ha was accepted which means there are differences in the average results of speaking skills of fifth-grade students of SDN 1 Massepe on Indonesian language subjects between before and after the use of cooperative learning models of time token types. Based on these results it can be concluded that there is the influence of the cooperative to time token type learning model on the learning outcomes of Indonesian speaking skills in fifth grade students of SD Negeri 1 Massepe.
Improved Method of Searching the Associative Rules while Developing the Software

As the delivery of the good quality software in time is very important part of the software development process, it's very important task to organize this process very accurately. For this a new method of the searching associative rules where proposed. It is based on the classification of the all tasks on three different groups, depending on their difficulty, and after this, searching associative rules among them, which will help to define the time necessary to perform specific task by specific developer
Analisis Peluang Usaha Pembuatan Alat Permainan Edukatif Anak Selama Masa Pandemi Covid-19

This study aimed to determine the business opportunities for making educational game tools during the Covid-19 pandemic. This research was a qualitative research using literature study method. The data obtained were then analyzed descriptively. The development of children's abilities during this pandemic cannot be underestimated. Parents and teachers must work together to create an effective learning for children. In designing an interesting and effective learning, one must use learning media that can attract children's interest. Therefore educational play tools were a solution to the problems faced by most parents during this pandemic. Educational play tools become a medium for creating meaningful learning activities for children. Seeing the importance of this educational game tool, the public's demand for this media was increasing. This was one of the factors that made selling educational game tools a promising business opportunity. Several manufacturers that produce educational games have experienced an increase in the number of orders and this has resulted in an increase in sales turnover. Business opportunities in the sale of educational game tools based on market analysis will continue to increase. This was because parents' awareness of child development was increasing. Based on this, to start a business in this field a number of things that must be done are starting to become a reseller, expanding the sales network, increasing cooperation with foundations engaged in child education and looking for craftsmen partners to start producing their own.
Development Path Construction of the Community-Based Child Protection

With the continuous development of society, the emergence of new social problems makes children's growth and children's protection work face many new challenges.China's existing child protection mainly emphasizes family, school, social and judicial protection, and ignores an important environment for children to grow upthe community.This article proposes the establishment of a communitybased child protection system, and specifically discusses the feasibility and specific methods of this system.It is necessary to establish a community-based, multi-subjective, and cooperative approach to build a friendly environment for children.
SOCIETAL DIMENSION OF DOCTORAL EDUCATION IN THE EUROPEAN HIGHER EDUCATION AREA: PRIORITIES AND TRENDS

The article identifies trends in the societal dimension of doctoral training as a cycle of higher education in the EHEA. The use of the appropriate research methods allowed to characterise the essence of the societal dimension of higher education in the Bologna reform documents; to identify the specificity of the societal dimension of doctoral training within the framework of the Salzburg process, which outlines priorities for reforming doctoral training at the EHEA; to find out current trends in the development of the societal dimension of doctoral training in the EHEA and the ERA.It is shown that the most significant are the following trends in the development of the studied phenomenon: taking into account in the process of development and realisation of PhD programs the needs for productive employment of young scientists; intensification of cooperation of the University with a wide range of stakeholders in the formation of professional and transversal competences and personal qualities of PhD students; development of open educational and scientific spaces (inter-university, national, international), including educational, scientific and social resources, which not only give young scientists new opportunities to implement their own scientific projects, but also require qualified and competent participation in the further development of the content of such space; structural and cultural changes in approaches to the organisation of doctoral training (introduction of structured doctoral programs and collective guidance); transformation of the University into a friendly to PhD-students ecosystem, which implies their full participation in all spheres of the university life: educational, scientific, innovative, and social.
RA3D: Reputation-based Adaptive 3D Video Delivery in Heterogeneous Wireless Networks

The continuous innovations in both high-end mobile devices and wireless communication technologies, fueled by the growing interest of mobile device users, have driven the latest development of mobile 3D video services. One of the critical challenges for mobile 3D video delivery is the limited bandwidth provided by the wireless communications between mobile devices. Nowadays, network operators are trying to cope with significant increase of data traffic amount and adopt diverse solutions to expand their network capacity. Among long-term solutions is network convergence, which involves close interworking of existing 2.5G/3G/4G networks with the new generation networks in terms of handover, network selection and network integration with other networks (e.g., WLAN, terrestrial microwave network, satellite network, etc.). In this context, the diversification in mobile devices and heterogeneity of the wireless environment make provision of always best connectivity of mobile users a challenge for the service providers. This paper proposes RA3D, a reputation-based adaptive 3D video delivery solution in heterogeneous wireless networks, which supports Always Best Experience to the mobile users by making use of multipath content delivery technologies.
Implementing Agility in Large Software Development Projects

The present paper focuses on providing an in-depth understanding of the concept of agility and its uses in the software development projects. The paper also explains the key issues experienced by large companies while implementing agility practices and frameworks in the large-scale software development projects. The paper also develops key ideas about the procedure involved in implementing agility practices through extensive study of previous literature in this context. It also recommends certain methods in which the issues experienced during the implementation of agility in large scale software development projects can be minimized. The findings provide insights about the various challenges and reasons behinds such issues that are common in such large-scale software development projects drawing instances of international companies providing software development services.
A Trajectory Planning Algorithm for Medical Manipulators Based on Adaptive Particle Swarm Optimization and Fuzzy Neural Network

With the development of smart healthcare, surgical and rehabilitation robots have permeated into daily medical operations.This raises concerns over the trajectory planning of medical manipulators.Based on particle swarm optimization (PSO) algorithm and fuzzy neural network (FNN), this paper puts forward a trajectory planning algorithm for medical manipulators, which ensures that the target medical manipulator can suppress the residual jitter at the end, while meeting the requirements of high precision, flexible operation, and disturbance resistance.Specifically, a kinetic model was constructed for a medical manipulator of multi-degrees-of-freedoms (DOFs) through position and posture transforms, and used to construct an FNN for trajectory planning.To suppress the jitter at the end, an adaptive PSO algorithm was designed, and combined with the FNN into a trajectory planning algorithm called PSO neural network (PSONN) algorithm.Finally, the proposed algorithm was proved effective through experiments.The research results provide the reference for applying PSO algorithm and FNN in other fields.
Visual Browse and Exploration in Motion Capture Data with Phylogenetic Tree of Context-Aware Poses

Visual browse and exploration in motion capture data take resource acquisition as a human–computer interaction problem, and it is an essential approach for target motion search. This paper presents a progressive schema which starts from pose browse, then locates the interesting region and then switches to online relevant motion exploration. It mainly addresses three core issues. First, to alleviate the contradiction between the limited visual space and ever-increasing size of real-world database, it applies affinity propagation to numerical similarity measure of pose to perform data abstraction and obtains representative poses of clusters. Second, to construct a meaningful neighborhood for user browsing, it further merges logical similarity measures of pose with the weight quartets and casts the isolated representative poses into a structure of phylogenetic tree. Third, to support online motion exploration including motion ranking and clustering, a biLSTM-based auto-encoder is proposed to encode the high-dimensional pose context into compact latent space. Experimental results on CMU’s motion capture data verify the effectiveness of the proposed method.
Question formation strategies in Kunuz Nubian

This is an analytical and descriptive study that is based on a general theoretical framework which can be characterized as “basic linguistic theory”. It aims to study Kunuz Nubian interrogative pronouns and question markers. Previous studies failed to pay adequate attention to these features. It is an attempt to characterize the strategies used in question formation and to identify the question markers. I argue that the question markers in this Nubian dialect fall into three sets: (a) the set of question markers -yaa, -naa, and -waa are used with sentences (non-copular construction) involving the neural marker -r-. (b) the set of questions markers that are used if the neural marker –r- is in a copular construction: -yaa, -re, -waa. (c) another set of question markers are attached to a declarative sentence in which the verb or copular verb is accompanied with the past tense morpheme. The study has also provided a list of interrogative pronouns that can occur with or without the question markers. Moreover, it has been shown that both compound and complex sentences are turned into interrogatives via the same question strategies used in simple sentences.
Hubungan Antara Secure Attachment dan Kemandirian dengan Motivasi Berprestasi pada Remaja

The purpose this study was to determine the relationship between secure attachment with achievement motivation, the relationship between autonomy with achievement motivation, and the relationship between secure attachment and autonomy with achievement motivation in adolescents students. The population of this research was students of class X, XI and XII Madrasah Aliyah Negeri (MAN) Tebing Tinggi. The sample was 103 students were take by stratified random sampling technique. This study used secure attachment scale, autonomy scale, and achievement motivation scale. Double regression analysis showed FCOUNT 33, 482 with p = 0,000 (p0,005). The result indicate that there was significant correlation between secure attachment and autonomy with achievement. Patrially, there is a significant relationship secure attachment with achievement rxy = 0,365 with p 0,01 and there is a significant relationship between autonomy with achievement motivation rxy = 0,361 with p 0,01. R2 square value was 0, 527 it means that secure attachment and autonomy simultaneously contribute 52,7% toward achievement motivation.
Completion of Matrix Inversions Using Elementary Matrix Inverse Multiplication Method

Abstract.&#x0D; &#x0D; Given a matrix A is ordo . Elementary matrix inverse multiplication produces inverse matrix A which is where I is an identity matrix and is an inverse matrix A. The problem discussed in this research is to find a solution the ordo of matrices by using inverse elementary matrix inversion method with the steps given in solving by completing the smallest ordo matrix first up until the ordo matrix .&#x0D; &#x0D; Keywords: Matrix, Inverse Matrix, Multiplication of Elementary Matrix.
A Cramer-Rao Lower Bound for the Estimation of Bias with a Single Bearing-Only Sensor

This paper presents a metric for finding optimal sensor and target geometries that provide accurate estimates of bias during target tracking with a single sensor taking measurements of bearing. Since the bias cannot be measured directly, it is shown how to manipulate the equations of a Kalman filter to produce a pseudo measurement of bias and its associated measurement error covariance. These measurement error covariances are used to form a Cramer-Rao lower bound (CRLB) on the bias estimation variance as a function of sensor and target geometries. It is shown that highly accurate estimates of bias can be produced using a single sensor, even if the kinematic state estimate of the target is poor.
CatGCN: Graph Convolutional Networks With Categorical Node Features

Recent studies on Graph Convolutional Networks (GCNs) reveal that the initial node representations (i.e., the node representations before the first-time graph convolution) largely affect the final model performance. However, when learning the initial representation for a node, most existing work linearly combines the embeddings of node features, without considering the interactions among the features (or feature embeddings). We argue that when the node features are categorical, e.g., in many real-world applications like user profiling and recommender system, feature interactions usually carry important signals for predictive analytics. Ignoring them will result in suboptimal initial node representation and thus weaken the effectiveness of the follow-up graph convolution. In this paper, we propose a new GCN model named CatGCN, which is tailored for graph learning on categorical node features. Specifically, we integrate two ways of explicit interaction modeling into the learning of initial node representation, i.e., local interaction modeling on each pair of node features and global interaction modeling on an artificial feature graph. We then refine the enhanced initial node representations with the neighborhood aggregation-based graph convolution. We train CatGCN in an end-to-end fashion and demonstrate it on the task of node classification. Extensive experiments on three tasks of user profiling (the prediction of user age, city, and purchase level) from Tencent and Alibaba datasets validate the effectiveness of CatGCN, especially the positive effect of performing feature interaction modeling before graph convolution.
The Innovations and Entrepreneurship – Evidence from Kosovo’s SME Sector

The purpose of this research is to study the implication of R&D and Innovation in Entrepreneurship with particular meaning in the SME sector in Kosovo.The research is grounded on a review of the literature in this area and R&D applies and innovation actions of the SME development sector.This paper practices a variety of research methods to explore the development of Kosovo SMEs.In this research, we used a sample of BSCK (Business Support Centre Kosovo) last research, which tells us that most SME managers agreed that a number of activities undertaken are the result of efforts to apply R&D, or innovation occurs within the SME growth orientation.The results of the paper suggest that enterprise success and SME development are conditioned by SME ownership, financial sector conditions, internal and external business environments, and access to regional markets.The paper will also support most aspects of managers' needs to achieve business performance, as well as decision-makers at different levels in developing SME development procedures and regulations.
Hybrid Facial Features with Application in Person Identification

This paper presents the hybrid facial feature with identification and verification based on facial images. A query facial image had been taken under different conditions of the facial image of the same person (as the query). The query facial image database was constructed. We have used the technique of three-dimensional (3D) Dlib facial landmarks using a direct linear transform technique. A set of absolute affine invariance had been constructed from a series of the 3D landmark quadruplets, which make the facial identification robust to affine geometric transformation. These 3D facial features serve as a coarse feature depending on each individual facial structure. The construct of the 2D detail features represents the edge facial image confined between the 2D Dlib landmarks. The similarity of the 2D feature is achieved by aligning the 2D query edge image against that of the reference edge image. The geometric transformation matrix is estimated from the 2D Dlib landmarks, where correspondence is well established. An identification/verification cost function using a combination of local 2D facial features and global 3D facial features is utilized to verify and identify a query facial image against a candidate facial image(s). The performance of the algorithm yielding an area of 99.97% perfect classification is represented as a value under the receiver operating characteristic (ROC) curve.
Design of Website-Based Queue Retrieval Application on Andi Motor using Codeigniter Framework

Conventional queues have become a common polemic in society. The duration of the process and waiting time for the queue greatly disrupts daily activities. Queuing is not fun for many people, especially if the queue is long and irregular. To deal with irregular queues, an application is needed that helps to queue more fun and has certainty of time. In the workshop, the queue retrieval system and waiting for the queue are usually done on the spot, this will not be a problem if the queue is not long, but if the queue is too long it will cause various problems. This journal discusses the design of website-based queuing applications using framework codeIgniter, where features are made based on the wishes of customers, so that this application has the purpose of facilitating customers in queuing wherever and whenever and customers will have certainty of time to queue. The design of this application uses the MVC method contained in the codeigniter framework to separate data and display and how to process it.