Reviewerly/exHarmony huggingface dataset:
Research on the Application of Micro lecture in the Gymnastics Teaching in Colleges and Universities

With the development of the times and the technological progress, the microlecture has entered into our life in various forms. In the current gymnastics teaching of colleges and universities, most of the colleges and universities still continuously use the single traditional class teaching mode. The old teaching mode and single teaching method hardly stimulate the students’ enthusiasm. In addition, not all the students can fully understand and comprehend what the teachers teach in class after one class. Not only the microlecture can be used as an effective complement to the traditional class teaching, but also its teaching mode is more in line with the age characteristics of the college students and stimulates their learning interest more easily.
An Empirical Study of Intelligence Teaching in University English Based on the Output-Driven Hypothesis

Cultivating students' higher English application ability is a new requirement for university English teaching in the transition from local undergraduate colleges to applied technology universities. The theory-based teaching model of integrating two wings into one aims to form an output-driven, piecewise-focused teaching content system for university English, so as to improve students' English application ability. Based on the output-driven hypothesis theory, this paper analyzes how foreign language teaching uses the theory of hypothesis to promote the reform of university English reading, which provides an important teaching reference value for university English reading classroom teaching.
A New Method for Encryption of Color Images based on Combination of Chaotic Systems

This paper presents a new method for encryption of color images based on a combination of chaotic systems, which makes the image encryption more efficient and robust. The proposed algorithm generated three series of data, ranged between 0 and 255, using a chaotic Chen system. Another Chen system was then started with different initial values, which were converted to three series of numbers from 0 to 10. The three red, green, and blue values were combined with three values of the first Chen system to encrypt pixel 1 of the image while values of the second Chen system were used to distort the combination order of the values of the first Chen system with the pixels of the image. The process was repeated until all pixels of the image were encrypted. The innovative aspect of this method was in combination of the two chaotic systems, which makes the encryption process more complicated. Tests performed on standard images (USC datasets) indicated effectiveness and robustness of this encryption method
The origin of the spooky behavior of quantum particles: Time reversal

In this paper, we study the origin of the quantum particle entanglement. Particles will have one mixed wave function as soon as they are created, which are called quantum particle entanglement. Electron spin states are used as an example to discuss this topic. When two electrons are created simultaneously, they have two different mixed quantum spin states. Before the measurement of its spin, we cannot determine its spin state. However, as soon as the spin of one of the electrons is determined (measured), the spin of the other will definitely be in the opposite state, regardless of how far they are away from each other. This paper uses the mechanism that the wave packet spreads as soon as they are created and then the wave packet shrinks when it undergoes a measurement to interpret this spooky phenomenon mentioned above.
Issues & Challenges in Urdu OCR

Optical character recognition is a technique that is used to recognized printed and handwritten text into editable text format. There has been a lot of work done through this technology in identifying characters of different languages with variety of scripts. In which Latin scripts with isolated characters (non-cursive) like English are easy to recognize and significant advances have been made in the recognition; whereas, Arabic and its related cursive languages like Urdu have more complicated and intermingled scripts, are not much worked. This paper discusses a detail of various scripts of Urdu language also discuss issues and challenges regarding Urdu OCR. due to its cursive nature which include cursiveness, more characters dots, large set of characters for recognition, more base shape group characters, placement of dots, ambiguity between the characters and ligatures with very slight difference, context sensitive shapes, ligatures, noise, skew and fonts in Urdu OCR. This paper provides a better understanding toward all the possible engendering dilemmas related to Urdu character recognition.
HEMEI

In this new era of intelligent industry, Human-Machine Interfaces (HMI) must allow employees to use all their knowledge and skills to exploit the possibilities offered by new technologies. In this situation, User Experience (UX) is presented as a key factor. However, there is a great lack of UX methods oriented to the design and development of industrial interfaces. Therefore, the HEMEI tool has been created, a new evaluation method that allows evaluating the pragmatic and experiential aspects of HMIs from the expert perspective of the designer or developer. To validate this new tool, we conducted a case study with a manufacturing company. The study concluded that the tool has allowed all participants to identify a significant number of aspects to be improved in the evaluated interface. This evaluation and subsequent redesign of the HMI, in addition to increasing the efficiency of production processes, generates experiences that increase the autonomy, competence, closeness, safety and stimulation of employees.
Research on the Extraction Method of Explicit Attribute-View Pairs in Product Review

Abstract The fine-grained affective analysis of product reviews is a fine-grained mining of the content of reviews, which has important research significance. The explicit attribute-viewpoint extraction is one of its key research issues. Due to the complex structure and colloquial features of online product reviews, traditional models are not ideal for the extraction of explicit attribute-views pairs. To solve this problem, this paper proposes an extraction method based on deep learning and integrating positional relationship information. By using the Bi-directional Long Short-Term Memory Network to overcome the problem of long distance dependence, the author makes full use of the context, combines the attention mechanism to reduce the noise weight of sentence-level informal text, and integrates the feature of position relation to enrich the feature information. The experimental results show that compared with other models, the network model proposed in this paper has improved the call rate and F1 value.
Phrasal Criteria for Authorship, with Consideration of Negative Checks

Researchers have proposed that phrases (collocations and n-grams) may be successfully used as evidence of authorship. This note utilizes the large body of phrases from over 500 Early Modern plays m...
Study on core essential elements for O2O business model with value net theory

The O2O business model concept was given based on literature review. The O2O business model framework was established and the most basic seven major elements were identified in our research with value net theory as follow: customer, telecom operator, content provider, service provider, software provider, third-party payment platform and offline business entity. Then, we identified eight secondary elements and 22 three-level elements of O2O business model with Delphi, and the O2O business model core essential elements evaluation model was also established. We analysed the model systematically and figured out top ten core elements with analytic network process as follow: network speed and stability, mining the customer subject requirements, insight to customer demand, control the trading risk, the core technology research and development, the life service payment platform, after payment platform, financial services platform development, outburst requirements fulfilment and maintenance of direct correlation among enterprises. The top ten elements mainly concentrated in four dimensions as follow: customer, telecom operators, third-party payment platform, and software providers. We hope that the research can provide enlightenment to O2O business model essence and insight to O2O future trends.
Contrast determination in phase-shifting algorithms for interferograms with arbitrary steps and additive noise

Phase-shifting (PS) is a well-established technique for phase retrieval in interferometry that requires a series of intensity measurements with known or unknown phase-steps. Contrast information is useful for evaluating the quality of the collected data. The objective of this work is determinate an algorithm to calculate the contrast function in the case of arbitrarily spaced phase steps.
The Moderating Effects of Learning Goal Orientation on the Influence of Education Service Quality on Learning Transfer : Focused on Vocational Training Institute Students Major of Culinary

The aim of this study was to test the effect of education service quality Perceived by vocational training institute students major of culinary on learning transfer, and moderating effect of learning goal orientation in the above causal relationship. The findings of this study are as follows. First, this study conducted a multi-variate regression analysis to examine the effect of education service quality on learning transfer, and found that both of the three sub-variables of education service of lecture program, educational environment and educational service significant and positive (+) effects on learning transfer. Second, as the result of verifying the moderating effect of learning goal orientation in the relationship between education service quality and learning transfer, it was found that learning goal orientation did effect of moderator. The result from the analysis provides practical implications for learning transfer for student.
3D Digital Grid Map Initialization and Path Planning for Autonomous Robot Navigation

This paper presents a novel approach to process 3D point cloud data to create a 3D grid evaluation map for path planning algorithm. In particular, it is aimed at solving the 3D navigation problem by using raw point cloud as path algorithm's input. After data processing, the gained 3D grid map is able to be implemented to path planning algorithms and allowing planning a safe and optimal path in it via repeated computation of nearby nodes. The proposed approach will integrate environment survey, environment reconstruction, and path planning as a completed task, which involves learning and planning. A competed simulation of the environment topology acquisition and route planning process is documented in this paper.
To study the correlation between stature and facial parameters of human adults in North Indian population

Introduction: Stature is defined as natural height of human being in standing position. Each and every part are related with each other i.e. face, trunk, head and extremities. Stature estimation is important parameter when human remain such as mutilated body or facial remain of skull is brought for medicolegal examination for person’s identity. This correlation will also be helpful in anthropological and geographical research. Our study aimed to determine the stature from facial parameters that were morphological facial length, upper facial length, and lower facial length. Materials and Methods: The study was conducted in department of Anatomy, SN Medical College, Agra, on 300 medical students aged between 18yrs to 25yrs out of which 164 are males & 136 are females. Stature of person was measured by anthropometric rod & morphological facial length, upper facial length and lower facial length were measured by digital Vernier caliper. The mean, standard deviation, regression equation, were calculated. Result: We observed correlation between stature &facial parameter and developed regression equation for it. The morphological facial length, upper facial length and lower facial length was found to be significantly higher in males compared to females. Keywords: Stature, Morphological facial length, Upper facial length, Lower facial length, Digital vernier calliper, Anthropometric rod.
Physics and Dynamics of the Atmosphere

This chapter describes the basic physics and thermodynamics of the atmosphere, starting from the ideal gas law and the hydrostatic equation, from which the lapse rate in the troposphere is derived. The effect of atmospheric moisture on the lapse rate is identified and the Clausius–Clapeyron equation giving the saturated humidity is derived. The effect of moisture on adiabatic vertical transport is shown. Then, the three-dimensional equations of motion are derived in vector form. From these, geostrophic balance and the thermal wind equations are derived. This, with the Coriolis force, gives the physical description of the atmospheric circulation. The driving force behind circulation is identified as the energy difference between the tropics and the extratropics. This is driven by radiation differences, including, at large geological scale, the Milankovitch cycles. Finally, circulation as a three-cell system per hemisphere, and the development of weather systems such as cyclones, are described.
Service recommendation using conditional restricted Boltzmann machines

We propose methods based on the conditional restricted Boltzmann machine (CRBM) for the service recommendation. First, we construct a CRBM model, the individualised characteristics of customers and indexes of satisfaction have been encoded into its conditional units, and the using status of services has been encoded into its visible units. Next, a method for dynamically adjusting learning rates is proposed to improve the training process of the CRBM. Finally, we develop a neighbourhood-based approach to further boost recommendation results. The evaluation on a dataset extracted from a manufacturing company, validates that the above-proposed methods have highly practical relevance to the service recommendation problem in real world business.
An Intelligence Security Alarming System With Fall Detection Algorithm

Falls endanger the health of the elderly seriously. Fall detection and emergency alarm is very necessary. At present, the alarm system has the problems of low fall detection accuracy, high power consumption, poor user experience and slow feedback. We designed a low-power wearable smart device with fall detection and touch alarm based on nRF51-DK low-power MCU, which can last for 5 days and can be triggered without pressing. Its detection sensitivity reached 94.05%, and its feedback time is shorter than three seconds.
Analysis of Common Errors Made by Second Year English Language Department Students in Writing Academic Paragraph: The Case of Gilgel Beles CTE

The purpose of this study was to explore and analyze the common errors of second year English department students in writing paragraph with reference to Gilgel Beles CTE.The students wrote paragraphs (about causes of environmental pollution) with the range of 150 to 200 words approximately.They also completed the questionnaires that were adapted from Korbel (2001) regarding their views toward writing skills.The instructors completed the questionnaire and replied for opened-ended question.The study was a survey method using 4-point Likert Scale questionnaire.Systematic sampling technique was implemented to select 10 students in each section from the total population of 196 students.Though the total numbers of the students were 196, only 50 students had responded to the questionnaire.Among 50 sample sizes, only forty-five students completed the questionnaire formally.Two students completed the questionnaire wrongly whereas three students were absent during data gathering.Comprehensive (available) sampling technique was used to select instructors.Among the seven English instructors, six instructors completed the questionnaire formally and returned to the researcher.This study employed a mixed method design which includes both quantitative and qualitative research analysis methods.In general, there were different types of errors; grammatical errors in particular, were made by the students.These were passive voice, verb form, subject-verb agreement, word order, prepositions, articles, plurality and auxiliaries.Especially, words spelling and the lack of sense of sentences/paragraphs/ are the most problems.This incomprehensibility of grammar rules has negative effect on student compositions.After analyzing students' and teachers' questionnaire, it has been found out that the students made grammatical errors due to many reasons: the lack of practices daily, lack of motivation, problem of teaching methods, lack of writing activities, teachers escape writing lesson, school text book is not conducive (it focuses more on speaking) and the lack of opportunities to practice writing skills.
Монументализм: фактор «больших идей» в самоорганизации сетевого пространства

The authors aim to comprehend the socio-cultural essence of the communicative changes occurring in social networks. The methods of reducing the «network» information in the public consciousness are analysed from the viewpoint of their culture effectiveness. The scholars put forward the idea of monumentalism and consider it as a factor of «big ideas» useful for self-organization of chaotic network space, disintegrated by the multiplicity of views. Anthropocosmism is proposed as the most culturally productive communicative paradigm for an effective socio-network interaction.
A Hybrid Model for Optimal Pseudorandom Bit Sequence Generation

Chaotic map gained its importance in the field of cryptography, due to its properties like, randomness, unpredictability, sensitivity on initial condition, aperiodicity, which is used to generate pseudorandom bit streams. In this paper the optimal values of chaos parameters are generated through Real Coded Genetic Algorithm (RCGA), which is optimal, unpredictable, and optimally sensitive. Here, a non-deterministic RCGA based optimal pseudo-random bit sequence generator based on Chaotic maps, such as Logistic Chaotic map, Skew Tent Chaotic map, Cross Coupled Logistic Chaotic map, Cross Coupled Skew Tent Chaotic map is proposed. A real coded crossover and mutation technique is proposed for RCGA. Seed values for chaotic map have been optimized by using all sub-functions of GA (RCGA). These seed values are used to generate optimal pseudorandom bit stream of finite length. The randomness of the bit stream is tested by using NIST statistical test suit.
QoS-Aware Agent Capabilities Composition in HARMS Multi-agent Systems

With the increasing adoption of Internet of Things (IoT) technologies, the number of agents offering equivalent capabilities is increasing more and more. The services of these capability equivalent agents may have different Quality of Service (QoS) levels. Therefore, the selection of the most appropriate services that best match some given requirements becomes a challenging issue in the HARMS (Human, Agent, Robot, Machine, Sensor) multi-agent systems. In this paper, a Social Group optimization-based QoS-aware agents services Composition Algorithm (SG-QCA) is proposed to enable HARMS interaction layer with the capability of composing agents services in large-scale IoT services environments. The simulation results show that for both randomly generated and real datasets, the proposed approach is scalable and achieves a near-to-optimal composition in a reduced composition time compared to other services composition approaches.
Pattern Matching in Sequential Data Using Reservoir Projections

A relevant problem on data science is to define an efficient and reliable algorithm for finding specific patterns in a given signal. This type of problems often appears in medical applications, biophysical systems, complex systems, financial analysis, and several other domains. Here, we introduce a new model based in the ability of Recurrent Neural Networks (RNNs) for modelling time series. The technique encodes temporal information of the reference signal and the given query in a feature space. This encoding is done using a RNN. In the feature space, we apply similarity techniques for analysing differences among the projected points. The proposed method presents advantages with respect of state of art, it can produce good results using less computational costs. We discuss the proposal over three benchmark datasets.
Knowing, Believing and Thinking We Know

Beliefs are not knowledge, knowledge should be absolute, unconditionally true like day and night alternate or are mortals. Beliefs generate convictions. Convictions are the origin of what we think we know. Convictions and knowledge generate opinions. This rises an important question: how much our actions are determined by beliefs and how much by knowledge? And accordingly, how are convictions generated and what can make them change? We know that education and social media are mainly responsible in forming our convictions. Printed matter was for centuries the main tool to educate people but today school, family and society are heavily dependent on internet, since this tool offers something that books will never do: interactivity and universality which help people find answers to almost any question. This paper tries to investigate what are the important consequences of the internet on forming convictions and how modern education should use this tool to improve performance and avoid willful or not misconducts.
WHELS Aims to Create Conscious Women Leaders

Women in Higher EducationVolume 28, Issue 7 p. 8-15 WIHE Interview WHELS Aims to Create Conscious Women Leaders Kelly J. Baker, Kelly J. BakerSearch for more papers by this author Kelly J. Baker, Kelly J. BakerSearch for more papers by this author First published: 02 July 2019 https://doi.org/10.1002/whe.20730Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume28, Issue7July 2019Pages 8-15 RelatedInformation
DSP Design With Hardware Accelerator For Convolutional Neural Networks

Convolutional Neural Networks impressed the world in 2012 by reaching state-of-the-art accuracy levels in the ImageNet Large Scale Visual Recognition Challenge. The era of machine learning has arrived and with it countless applications varying from autonomous driving to unstructured robotic manipulation. Computational complexity in the past years has grown exponentially, requiring highly efficient low power new hardware architectures, capable of executing those.In this work, we have performed optimization in three levels of hardware design: from algorithmic, to system, and accelerator level. The design of a DSP with Tensilica and the integration of Xenergic dual port SRAMs, for direct memory access of a convolution hardware accelerator, lead to four orders speed-up on the initial identified bottleneck, causing an estimated three times final speed-up of a single handwritten classification image compared to the pure software implementation. Higher speed-up is expected for deeper convolutional architectures and larger image dimensions, due to the linear time complexity scaling of the convolution hardware accelerator in comparison to conventional non-linear software-based approaches.