Reviewerly/exHarmony huggingface dataset:
Syntactical Development on Second Language Writing: A Case of L2 Child Learner on Immersion Experience Abroad

Development of child language is tremendously complex, remarkable and wondrous. In a second language acquisition context, a child can acquire his second language in either acquiring both languages at the same time or learning the second language after mastering the first one. This present research is concerned to describe the syntactical development particularly for second language writing of an eight-year old child who has experienced immersion abroad for one year in L2-speaking country. The participant is an eight-year old child from Jakarta Indonesia who has experienced immersion environment in Australia for one year. The research will be carried out qualitative naturalistic research design. Not less than 38 documents of participant’s paperwork during her school year were then collected, grouped and analysed. From the findings, it is known that morphological processes on L2 such as affixes and verb changes have emerged. Meanwhile, the findings also show the development on morphemic, phrasal and sentential level on acquiring L2. Some morphemes have been acquired such as the suffix, the changing of verb, the -ing form. Moreover, post-noun prepositional phrases are the most emerged phrases. On sentential level, active declarative sentences are the most frequently appeared. However, some errors and inconsistency also occur indicating the development of her second language.
Digitalization in the Romanian Higher Education in the Present Digital Era

The present challenge of the higher education system of Romania is the digital transformation, an action permanently preoccupying the government who is trying to find modern solutions to turn into practice the action domains foreseen by the National Strategy for the Digital Agenda, Romania 2020.Higher education digitalization is a transforming process influencing substantially all the higher education institutions' activities, from the development of new infrastructures, use of digital technologies for teaching and learning, research, support services, administration and communication, up to the students' and teaching personnel's need to develop new digital skills useful at present and future workplaces.In this context, the goal of this paper is to highlight by a theoretical approach the present situation of the Romanian higher education in the context of the digitalization phenomenon of the new digital era.
A 460 GOPS/W Improved Mnemonic Descent Method-Based Hardwired Accelerator for Face Alignment

The mnemonic descent method (MDM) algorithm is the first end-to-end recurrent convolutional system for high-accuracy face alignment. However, the heavy computational complexity and high memory access demands make it difficult to satisfy the requirements of real-time applications. To address this problem, an improved MDM (I-MDM) algorithm is proposed for efficient hardware implementation based on several hardware-oriented optimizations. First, a patch merging mechanism is introduced to dynamically cluster and eliminate redundant landmarks, which significantly reduces computational complexity with minimal accuracy loss. Second, a dedicated convolutional layer is inserted to halve the number of computations and memory access of the subsequent fully connected layer, yielding a 4.42% decrease in the failure rate. Third, a lightweight preprocessing method named dual regressors is proposed to reinitialize face images, which can greatly improve the overall accuracy. Moreover, compared with a similar method, the DR method can reduce computations and memory storage by nearly 99.9%. Overall and compared with the MDM algorithm, I-MDM not only reduces the number of computations by 23.5% but also decreases the failure rate by 17.9% on the 300 W test set. Based on the proposed I-MDM algorithm, an I-MDM-based hardwired accelerator is presented using the TSMC 65 nm CMOS process. First, compared with similar solutions, the gradient calculation operation is rearranged and loaded pixels are reused in the HoG feature extraction to eliminate all division operations and 25% off-chip memory access. Second, patch-independent central activations are used to enable patch-level pipelined operations, yielding a 2× acceleration in the overall process. This accelerator achieves 460 GOPS/W energy efficiency at 330 MHz, which is 38× higher than the most recent face alignment accelerator with the same process.
Three-Level Laser Coupled to Squeezed Vacuum Reservoir

We analyze the quantum properties of the light generated by a three-level laser with an open cavity and coupled to a two-mode squeezed vacuum reservoir via a single-port mirror.The three-level laser consists of three-level atoms available in an open cavity and pumped from the bottom to the top level by means of electron bombardment.Applying the large-time approximation scheme, we have obtained the steady-state solutions of the equations of evolution for the expectation values of the atomic operators and the quantum Langevin equations for the cavity mode operators.Using the resulting steady-state solutions, we have calculated the mean photon number, the variance of the photon number, and the quadrature variance for the two-mode cavity light.We have seen that the light generated by the three-level laser is in a squeezed state and the squeezing occurs in the plus quadrature.It so turns out that the maximum quadrature squeezing of the two-mode cavity light is 45.68% for M 0 = 0.59 and N 0 = 0.27 below the vacuum-state level.In addition, we have shown that the effect of the squeezed parameter is to increase the mean and variance of the photon number.
The Impact of Organizational Innovation on Financial Performance: A Perspective of Employees Within Dubai Ports World

Firms’ performance in terms of financial performance can be considered as an organizational innovation issue. For the reason being firms’ performance is considered as a result of product innovation, process innovation and administrative innovation in developing and implementing effective ideas, the performance is crucially depending on effective organizational innovation. This research aims to examine the impact of organizational innovation (product, process and administrative) on the financial performance of organizations within DP World in the UAE. A personally administered questionnaire being distributed by the researcher will be used to collect data from respondents within DP World in the UAE. Random sampling method was adopted to select the employees who use smart government services, and only 403 out of 700 respondents were achieved a response rate of 58%, which is considered as a healthier survey response rate, while 372 were analysed after removing missing data, outliers and suspicious responses. Partial least squares (PLS) structural equation modelling-variance based (SEM-VB) method was employed to assess the research model by utilizing the software SmartPLS 3.0. The proposed research model explained 58% of the organizational innovation (OI). Organizational innovation had a positive direct effect on the OI within DP world in the United Arab Emirates (UAE). The results of the current research have the potential to give further insights into the innovation of organizations strategies.
Functional/Semantic Gesture Design Factor Studies on Social Robot for User Experience Design

It is necessary to classify the design factors for the user experience design at a level that causes a difference in the aspect of the user experience.So in this research, the functional/semantic gesture design factors have been derived through case studies and a survey where they were amended to have the level values with which a significant difference was verified in the user experience.The organized functional/semantic gesture design factors from the research are the gestures for concept instruction, behavior description, behavior mimic, and functional performance.The concept instruction attribute has been suggested as 'item's sequential/quantity instructions', and 'directional instructions'.The behavior description attribute has been reorganized to 'usage/situational behavior description', and 'symbolic behavior description'.The behavior mimic attribute has been proposed and remained as 'prototype behavior mimic', 'biological behavior mimic', 'personality behavior mimic'.Lastly, the functional performance attribute has been presented as 'direct behavior performance' and 'proxy behavior performance.
[Design and analysis of two groups interrupt time series].

Interrupted time-series (ITS) is a quasi-experimental design which evaluates the effectiveness of an intervention based on time-series outcome variables. Compared with the single group of ITS, the two groups of ITS can better control the influence of pre-interventional confounding factors and evaluate the effectiveness of the intervention. This paper summarizes the principles and statistical methods of two groups of ITS by an example of evaluating vaccine effect on the incidence of a disease in two cities. The regression model is fitted by Prais-Winsten method and Newey-West method and the results are explained and compared in detail. When the intervention is performed with other confounding interventions at the same time, the two groups of ITS can be more effective to balance the existing trends before the intervention, and evaluate the effectiveness of intervention. The method of two groups of ITS has important practical significance, providing new insights in program evaluation.中断时间序列（ITS）是对具有时间序列特点的结果变量进行分析，评价干预措施是否有效的类实验设计方法。相对于单组ITS，两组ITS可以更好地控制干预前混杂因素的影响，评价干预措施的效果。本文阐述两组ITS的设计原理和统计方法，以两市疾病发病率为例，采用Prais-Winsten法和Newey-West法拟合线性回归模型，并对结果进行了详细的解释和比较。在干预实施的时间窗口中存在多个政策转变时，两组ITS可以更好地平衡序列干预前已存在的趋势，科学地估计干预措施有效性具有重要的现实意义，为项目效果评价提供一个新的思路。.
The impact of information technology on the design of distribution channels

The study aims to identify the impact of information technology on the distribution of services of tourist institutions in the city of Al-Kharj in the Kingdom of Saudi Arabia.The survey was concentrated on a number of institutions represented in hotels, restaurants and travel and tourism agencies.The results indicate that the information technology had no meaningful effect on the distribution of tourism services in Al-Kharj.A set of recommendations was also presented to tourism organizations represented in the image of using social media to distribute tourism services as well as using and activating the websites of tourist institutions themselves when making reservations for their services and the necessity of activating and using electronic payment methods..
Exploring Managerial Perspectives of Using Building Management System through TAM: An Empirical Study of Commercial Sector of Pakistan

A cursory review of the Building Management System (BMS) which optimizes building performance as a move towards smart cities has been presented in the present study. The extant study is an effort to distinguish and analyze the circumstances as if the underdeveloped economies are less likely to be benefitted by the contemporary trends of BMS as compare to the developed countries. Moreover, the current study identifies the factors which may cause to render the managerial acceptance for using BMS through the Technology Acceptance Model (TAM). TAM was used to measure four behaviors (latent factors) namely subjective norms, organization support, compatibility, and technology complexity. The data were statistically evaluated via multiple regression analysis using the Statistical Package for Social Sciences (SPSS). Results suggested that organization support and compatibility have a significant influence on managerial intentions to use BMS while subjective norms, technology complexity have no significant influence. The findings of this study may serve as guidelines for improvement in the acceptance process and using building management systems in commercial sectors of developing countries.
Motivation Measurement of an Augmented Reality Traditional Musical Instruments System

The popularity of traditional musical instruments in the eyes of children today has declined.That is due to the development of technology, gadgets, and the internet, which makes them spend more time on it.For this reason, an application that uses Augmented Reality is built to introduce traditional music instruments to them.With the use of technology, interest and motivation expect to get to know and learn conventional musical instruments to grow back.This study aims to measure the extent of the impact that applications have on children as users.Test measurement method uses several variables, namely motivation as a dependent variable.Ease of use, engaging, enjoyment, and usefulness are as independent variables.This study also looks for correlation relationships between the variables used.The results of this study in the form of a hypothesis variable ease of use and engaging have a significant influence on user motivation.Also, variable enjoyment and usefulness do not have a substantial effect on motivation.
Path Planning of Autonomous Parking Based on hp-adaptive Pseudospectral Method

Abstract：Aiming at the problem that the convergence rate is slow when solving the optimal control problem of autonomous parking path planning, a method of autonomous parking path planning based on hp-adaptive Gauss pseudospectral method is proposed.First, the vehicle kinematical model is established, then the collision avoidance constraints and the boundary constraints in autonomous parking processes are further considered, finally the problem of autonomous parking path planning is converted into the optimal control problem which takes the shortest parking time as the cost function.The optimal control problem is discretized by Gauss pseudospectral method, and solved by sequential quadratic programming, in which the number of mesh intervals and degree of the polynomial are adjusted dynamically improving the convergence rate.According to the actual scenario, four autonomous parking conditions are designed and path planning is simulated, and three pseudospectral methods are compared and analyzed.The simulation results show that the convergence rate of the optimal control problem of autonomous parking path planning is improved by the hp-adaptive Gauss pseudospectral method, and the proposed mothed can obtain the parking path in a narrow parking lot, the effectiveness of the proposed method for autonomous parking path planning is verified by real vehicle tests.
CACHE MEMORY LOACLITY OPTIMIZATION FOR IMPLEMENTATION OF COMPUTER VISION AND IMAGE PROCESSING ALGORITHMS

One of the main problems in developing fast image processing and computer vision systems is the memory speed. Memory speed represents the performance bottleneck due to the large gap between processor and memory speeds. Cache memory is very fast, but it is small to store all required data and instructions. In this paper , image processing and computer vision algorithms are optimized to enhance performance by increasing the cache memory utilization. This optimization increases the spatial locality and temporal locality and improves the system performance. The proposed optimization is applied on a set of image processing operations such as image intensity transformation, image filtering, geometric transformation, and CNN. The time analysis of the systems has shown a speed improvement of 30% to 70% compared with direct algorithm implementation. سرعة الذاکرة تمثل واحدة من أهم المشکلات التي تواجه عملية تطوير أنظمة سريعة لمعالجة الصور والرؤية بالحاسب. إن سرعة الذاکرة تمثل عنق الزجاجة في تحقيق أداء جيد نظرا للفجوة الکبيرة بين سرعة الذاکرة وسرعة المعالج. الذاکرة المخبأة هي ذاکرة سريعة جدا ولکنها صغيرة ولا يمکنها تخزين جميع البيانات والتعليمات المطلوبة. في هذا البحث يتم عمل تحسين لخوازميات الرؤية بالحاسب ومعالجة الصور من أجل تحسين الأداء عن طريق زيادة استغلال أفضل للذاکرة المخبأة. هذه الأمثلة تزيد من الترکيز المکاني والترکيز الوقتي لتحسين الأداء. الأمثلة المقترحة تم تطبيقها على العديد من عمليات معالجة الصور مثل تحويلات الوضوح و مرشحات الصور و التحويلات الهندسية و الشبکات العصبية. إن تحليلات الوقت لهذه الأنظمة أثبتت تحسينات في السرعة تصل من 30% إلى 70% مقارنة بالطرق المباشرة لتنفيذ هذه الخوارزميات.
Use of Gamification as A Means of Consulting Support for Continuous Professional Development of Teachers

The article presents the results of the research conducted on the pedagogical faculty of Baranovichi State University on the creation of the university consulting service as an internal service to assist university teachers in solving problems of their professional practice.Gamification is presented as a form of consulting support of the process of teacher professional development directly at the workplace.Game simulation interaction influences the formation of the teachers' need for constant reflexive estimation of their activities.An educator recognizes the need for innovative change, which requires the constant study of educational activities implementation.The usage of experimental model simulation as real phenomena in pedagogical activity creates optimal conditions and prerequisites for teachers research competencies formation.It helps to produce innovative solutions in problematic situations, which may arise in the particular teacher activities.In game simulation the process of participants' personal development is intensified.
Fight the Power! Games, Thermostats, and the Energy Patriarchy

Confronting issues of global climate change will require creative approaches to energy consumption across a range of human activities. This design case looks at the evolution of a physical/digital hybrid board game that we created to encourage families to reflect on household energy consumption and environmental sustainability. Design in this context was particularly challenging due to the nature of household heating and cooling systems, which tend to be opaque and difficult to understand. Our challenge was to employ game mechanics to help build up interest, awareness, and understanding of heating and cooling systems, while at the same time providing an enjoyable and engaging activity. Through many rounds of playtesting and interviews, we converged on the design presented here. We start with a conceptual framework describing modern energy practices, after which we describe the game design and reflect on its strengths and weaknesses.
Student’s Learning Strategies in English Speaking Class

Speaking is the most essential skill that must be learned in acquiring a new language. It is important for the students to find the best learning strategies in order help them in learning the materials. However, it is necessary for the students to realize that there are many kinds of learning strategies that they may use during English speaking class. Therefore, this study aimed to elaborate on the kinds of students’ learning strategies in the English speaking class and to identify the factors that caused students to choose that learning strategy. The participants of this research were the students of English Department in the fourth semesters. The data were collected by using questionnaire and interview. The result shows that the students of English Department applied almost the learning strategies which provide on the metacognitive, cognitive, and socio-affective strategies while learning speaking. The most strategy used by students was note taking (51, 4%) and the least strategy was a translation (19, 6%). On the other hand, the strategy used by male students was cooperation (16, 8%) and there were (27, 1) female students who used self-evaluation as their strategy in learning speaking. Those learning strategies may be chosen depending on the students’ occasion and learning objectives.
Public Opinion Detection in an Online Lending Forum: Sentiment Analysis and Data Visualization

Public opinion entails emotions, wishes, attitudes and ideas among individuals and various social groups in a certain historical stage and social space. This research aims to employ natural language processing (NLP), sentiment analysis and data mining technologies to build a public opinion analysis system to serve enterprises' need of online public opinion detection. By using the data set from an online pear-to-pear (P2P) lending forum with 4148 reviews, we analyzed the data with data visualization techniques.
Strategies for Module Teaching in Public English Teaching in Higher Vocational Colleges

The pace of vocational education reform is constantly accelerating. In addition, effective reforms at the level of curriculum setting and teaching management, innovation, adjustment and optimization in the teaching of specific disciplines are also an inevitable requirement for reform. There are many innovative choices in public English teaching in higher vocational colleges relatively and modular teaching can also become a basic innovative teaching choice. However, it must also be seen that whether the module teaching is carried out or the active role of the module teaching is not simple with resulted in the impact of relevant difficult factors cannot be underestimated. This article will specifically analyze on module teaching in public English teaching in higher vocational colleges and make reasonable suggestions on how to better implement the module teaching.
Modeling the Topology of Cerebral Microvessels Via Geometric Graph Contraction

Studying the topology of cerebral microvessels has been shown to be essential for understanding the mechanisms underlying neurovascular coupling and brain microphysiology. One can derive topological models of these microvessels after labeling them based on their raw acquisitions from two-photon microscopy (TPM). However, adequate 3D mapping of cerebral microvasculature from TPM remains difficult due to the uneven intensities and shadowing effects. In this paper, we present a novel 2D/3D skeletonization solution to generate topological graph models of microvessels regardless of the quality of their binary maps. Our scheme first constructs a random initial graph encapsulated within the boundary of a binary mask. The vertices of the initial model are then iteratively contracted toward the centerline of microvessels by local connectivity-encoded gravitational forces. At each iteration, the model is decimated through vertices clustering and connectivity surgery processes. Lastly, a refinement algorithm is applied to convert the final decimated model into a curve skeleton. Synthetic angiograms and real TPM datasets are used for evaluation. By comparing against other efficient graphing schemes, we demonstrate that our solution performs better when applied to extract topological information from cerebral microvessel labels.
Active Discriminative Cross-Domain Alignment for Low-Resolution Face Recognition

In real application scenarios, the face images captured by cameras often incur blur, illumination variation, occlusion, and low-resolution (LR), which leads to a challenging problem for many real-time face recognition systems due to a big distribution difference between the captured degraded images and the high-resolution (HR) gallery images.As widespread application of transfer learning in across-visual recognition, we propose a novel active discriminative cross-domain alignment (ADCDA) technique for LR face recognition method by jointly exploring both geometrical and statistical properties of the source domain and the target domain in a unique way.Specifically, the proposed ADCDA-based method contains three key components: 1) it simultaneously reduces the domain shift in both marginal distribution and conditional distribution between the source domain and the target domain; 2) it aligns the data of two domains in the common latent subspace by discriminant locality alignment (DLA); 3) it selects the representative and the diverse samples with an active learning strategy to further improve classification performance.Extensive experiments on six benchmark databases verify that the proposed method significantly outperforms other state-of-the-art predecessors.