Reviewerly/exHarmony huggingface dataset:
CPPM: a lightweight performance prediction middleware for cloud platforms

As more and more commercial clouds have been applied in various areas, how to evaluate the performance of a cloud platform has become an important issue that needs to be addressed. Furthermore, an effective performance prediction mechanism is of significant value for improving the current cloud services, such as resource allocation and task scheduling. In the paper, we present the design and prototype implementation of a performance prediction system, namely cloud performance prediction middleware (CPPM), which is aiming at providing a set of lightweight and flexible services on existing cloud infrastructure so as to allow cloud providers monitoring, estimating and predicting the runtime performance from various aspects. The CPPM enables cloud providers to make more efficient and fine-grained resource management and scheduling policies based on their short-term workload prediction mechanism; also it provides an application-level performance prediction service which uses skeleton approach to capture execution characteristics of the running applications so as to predict their actual runtime performance and efficiency. Extensive experiments are conducted to examine the effectiveness and efficiency of the CPPM.
Let’s Talk English book series improve non-major English learner’s speaking skills with the assistance of Artificial Intelligence (AI) and cloud-hosted

English speaking skill is considered one of crucial skills for language learners tointegrate into the globe. Hence, the students need to get enough assistance fromteacher to reach the competent level. With the emergence of Artificial Intelligence(AI) and cloud-hosting, it is believed that non-major English learners’ Englishspeaking skills will improve considerably through a varied exercises of Let’s TalkEnglish (LTE’s) book series such as pronunciation activities, self -recordingactivities. The LTE’s book is designed according to Common EuropeanFramework of Reference’s level, which is saved on cloud and gives studentsunlimited chances to practice English speaking skill after class. This paper is tointroduce a new approach to teach and learn speaking skills in Vietnam.
Dual And Plural Formation In Arabic: A Computational Study

The computational generation of dual and plural from a given singular noun base in Arabic language creates some problem for the learners of the other languages especially for the people who need to know about the way of generation and the way of the getting the dual and Plural from the singular Arabic nouns. In this paper we will describe the computational generation of dual and plural noun morphology from a given singular base noun in regular Arabic language, and also the classification of Arabic nouns. Using the computational technologies programs that including (Java - JSP – html – Net Beans) will ASSIST generate this method. This study develops and evaluates a linguistically natural computational method for generating dual and plural from a given singular noun base.
Generalized Linear Orthomorphisms

In this study, we generalize the conception of orthomorphisms and obtain a counting formula on the generalized linear orthomorphisms over the Galois field with the arbitrary prime number p as the characteristic. Thus the partial generation algorithm of generalized linear orthomorphisms is achieved. The counting formula of the linear orthomorphisms over the finite field with characteristic 2 is the special case in our results. Furthermore, the generalized linear orthomorphisms generated and discussed in this study can gain the maximum branch number when they are designed as P-permutations.
The development of a video retrieval system using a clinician-led approach

Patient video taken at home can provide valuable insights into the recovery progress during a programme of physical therapy, but is very time consuming for clinician review. Our work focussed on (i) enabling any patient to share information about progress at home, simply by sharing video and (ii) building intelligent systems to support Physical Therapists (PTs) in reviewing this video data and extracting the necessary detail. This paper reports the development of the system, appropriate for future clinical use without reliance on a technical team, and the clinician involvement in that development. We contribute an interactive content-based video retrieval system that significantly reduces the time taken for clinicians to review videos, using human head movement as an example. The system supports query-by-movement (clinicians move their own body to define search queries) and retrieves the essential fine-grained movements needed for clinical interpretation. This is done by comparing sequences of image-based pose estimates (here head rotations) through a distance metric (here Fréchet distance) and presenting a ranked list of similar movements to clinicians for review. In contrast to existing intelligent systems for retrospective review of human movement, the system supports a flexible analysis where clinicians can look for any movement that interests them. Evaluation by a group of PTs with expertise in training movement control showed that 96% of all relevant movements were identified with time savings of as much as 99.1% compared to reviewing target videos in full. The novelty of this contribution includes retrospective progress monitoring that preserves context through video, and content-based video retrieval that supports both fine-grained human actions and query-by-movement. Future research, including large clinician-led studies, will refine the technical aspects and explore the benefits in terms of patient outcomes, PT time, and financial savings over the course of a programme of therapy. It is anticipated that this clinician-led approach will mitigate the reported slow clinical uptake of technology with resulting patient benefit.
Decision making using lag synchronization of chaos in mutually-coupled semiconductor lasers

Photonic reinforcement learning and decision making has been used to solve multi-armed bandit problem. We propose a method of decision making using lag synchronization of chaos in mutually-coupled semiconductor lasers. We numerically investigate the performance of decision making by changing the sampling interval of chaotic temporal waveforms.
Heterogeneous Real-Time Multi-Channel Time-Domain Feature Extraction Using Parallel Sum Reduction on GPU.

Online BCI has become a fascinating field of research nowadays. One of the main challenges in this field is to reduce the latency caused by the computational complexity of the signal processing algorithms. This issue leads to difficulty in processing real-time data. Usually, a trade-off needs to be considered between the number of input samples and precision of the processing algorithms. In this paper, heterogeneous computing concept is investigated to alleviate the computational complexity occurred in real-time processing. An OpenCL was utilized to implement signal processing algorithms in parallel. Feature extraction methods including band power and statistical moments were selected to examine the power of heterogeneous computing using parallel sum reduction. As a result, varying the number of work-group sizes which is an essential parameter of parallel processing provided dissimilar computing times. Also, running at a higher sampling rate yielded a higher benchmark ratio between sequential and parallel. However, system optimization is still necessary when processing BCI in real time.
Fast and Accurate Bilingual Lexicon Induction via Matching Optimization

Most recent state-of-the-art approaches are proposed to utilize the pre-trained word embeddings for bilingual lexicon induction. However, the word embeddings introduce noises for both frequent and rare words. Especially in the case of rare words, embeddings of which are always not well learned due to their low occurrence in the training data. In order to alleviate the above problem, we propose BLIMO, a simple yet effective approach for automatic lexicon induction. It does not introduce word embeddings but converts the lexicon induction problem into a maximum weighted matching problem, which could be efficiently solved by the matching optimization with greedy search. Empirical experiments further demonstrate that our proposed method outperforms state-of-the-arts baselines greatly on two standard benchmarks.
Structural Relationships among Childcare Teachers’ Work-Life Balance, Job Stress, Job Satisfaction, Burnout, and Awareness of Infant Abuse : Focusing on the Group Differences by Marital Status

The purpose of this study was to explore the structural causal relationships among childcare teachers’ work-life balance, job stress, job satisfaction, burnout, and awareness of infant abuse focusing on the group differences by marital status. The participants were 700 childcare teachers in Jeollabuk-Do. The data were analyzed through structural equation modeling, multi group analysis.BR The results of this study are summarized as follows : First, work-life balance had a direct effect on childcare teacher’ job stress, job satisfaction, and burnout. Second, childcare teacher’ job stress had a direct effect on job satisfaction, burnout, and awareness of infant abuse. Third, burnout had a direct effect on awareness of infant abuse. Fourth, work-life balance had indirect effects on burnout through job stress and job satisfaction. Job stress had indirect effects on awareness of infant abuse through job satisfaction and burnout. job satisfaction had an indirect effect on awareness of infant abuse through burnout. Fifth It was found that the burnout of unmarried teachers was more influenced by job satisfaction and the burnout of married teachers was more influenced by the degree of work- life balance. These results can be used to develop infant abuse intervention programs for childcare teachers. Also, by improving childcare teachers’ work-life balance, it is possible to reduce infant abuse.
The Court’s Verdict and Political Implications of the March 1st Movement in Gyeonggi-Incheon Areas

Gyeong’gi·Incheon area was where the highest number of protests as well as protestors were reported to be joining the entire March 1st movement, and was where the protests were the most fierce and active. The Anseong-gun’s Weon’gok-myeon and Yangseong-myeon counties, and Su’weon-gun’s Jang’anmyeon and Wujeong-myeon counties were even considered by the Governor General office as prime cases upon which it contemplated on applying high treason charges. Such charge was initially deemed necessary as it was believed to be a prudent move in justifying the Japanese colonial authorities’ bloody suppression of the March 1st movement, yet in the end such charge was never actually applied in court.BR In fact, the Japanese government and the Joseon Governor General office never really intended to charge March 1st movement protesters with high treason. Such charge, once applied, would immediately and automatically be interpreted as Japan acknowledging the Joseon public’s rejection and refusal of Japan’s colonial rule of Joseon (which Japan did not want to admit). It would also be construed as the Japanese authorities’ apparent admission of their own failure in colonial ruling on the Korean peninsula. Japanese authorities were not at all ready for that, and that was why the Joseon Governor General office and the Japanese government defined the March 1st movement basically and merely as “disorder by malcontents’ commotions(不逞·騷擾·妄動事件),” and never recognized it as an Independence movement.BR This kind of stance led the colonial authorities to punish people who attacked the military police, other police forces or administrative facilities actually much more harsher than people who conceived and also personally led the March 1st movement demanding Korean independence. This kind of ironic approach was to prevent similar challenges against Japanese colonial authorities from occurring again in the future, and maintain the authority of the colonial rulers, while not recognizing the Korean resistance as an action demanding liberation from the Japanese.
Step 1: Getting Started in Python 3

In this chapter you will get a high-level overview about Python language and its core philosophy, how to set up the Python 3 development environment, and the key concepts around Python programming to get you started with basics. This chapter is an additional step or the prerequisite step for nonPython users. If you are already comfortable with Python, I would recommend you to quickly run through the contents to ensure you are aware of all the key concepts.
Transfer learning across human activities using a cascade neural network architecture.

Cascade Learning (CL) [20] is a new adaptive approach to train deep neural networks. It is particularly suited to transfer learning, as learning is achieved in a layerwise fashion, enabling the transfer of selected layers to optimize the quality of transferred features. In the domain of Human Activity Recognition (HAR), where the consideration of resource consumption is critical, CL is of particular interest as it has demonstrated the ability to achieve significant reductions in computational and memory costs with negligible performance loss. In this paper, we evaluate the use of CL and compare it to end to end (E2E) learning in various transfer learning experiments, all applied to HAR. We consider transfer learning across objectives, for example opening the door features transferred to opening the dishwasher. We additionally consider transfer across sensor locations on the body, as well as across datasets. Over all of our experiments, we find that CL achieves state of the art performance for transfer learning in comparison to previously published work, improving F1 scores by over 15%. In comparison to E2E learning, CL performs similarly considering F1 scores, with the additional advantage of requiring fewer parameters. Finally, the overall results considering HAR classification performance and memory requirements demonstrate that CL is a good approach for transfer learning.
Investigation of Pitch and Duration Range in Speech of Sindhi Adults for Prosody Generation Module

Prosody refers to structure of sound and rhythm and both are essential parts of speech processing applications.It comprises of tone, stress, intonation and rhythm.Pitch and duration are the core elements of acoustic and that information can make easy to design and development for application module.Through these two peculiarities, the prosody module can be validated.These two factors have been investigated using the sounds of Sindhi adults and presented in this paper.For the experiment and analysis, 245 male and female undergraduate students were selected as speakers belonging from five different districts of upper Sindh and categorized into groups according to their age.Particular sentences were given and recorded individually from the speakers.Afterward, these sentences segmented into words and stored in a database consisting of 1960 sounds.Thus, distance of the frequency in pitch was measured via Standard Deviation (SD).The lowest Mean SD accompanied 0.25Hz and 0.28Hz received from male and female group of district Sukkur.The highest Mean SD has measured with male and female group of district Ghotki along 0.42Hz and 0.49Hz.Generally, the pitch of female's speakers was found high in contrast to male's speaker by 0.072Hz variation.
THE RELATIONSHIP BETWEEN DEVOTIONAL SANGEETHAM OF SWAMI TYAGAYA, BRAIN-MIND DYNAMICS AND GOD SPOT

The rationale is that Saint Tyagaya’s devotional Sangeetham creates brain activity to contemplate on God and therefore God becomes neurologically real. This form of spiritual development and contemplative singing exercise could strengthen neurological circuits and manipulate a devotee’s emotion to produce love, empathy, compassion, benevolence and tolerance. The research is a validation of the psychometric assessment extending from Swami Tyagaya, devotional Sangeetham, God, neuro-psychology and spirituality. The methodology shows the development of a questionnaire survey with a grand total of Eighty two questions to measure five different types of subjects. The Questionnaire addresses the society’s knowledge, belief, devotion, attitudes and educational progress over the five subjects. The compilation of questionnaire was distributed to the Indian community in Malaysia. Four hundred and ten volunteers responded to tell their experiential views of Sangeetham, Swami Tyagaya, brain, devotion, God and spirituality. The Questionnaire data were analyzed using Pearson product-moment correlation coefficient. The result showed that there are strong positive correlation between Sangeetham, devotional reliance, God, brain Swami Tyagaya and spiritualism. These results conclusively indicate that Swami Tyagaya’s devotional Sangeetham strongly influences the spiritual experience of the Indian devotees in Malaysia.
Group-Constrained Embedding of Multi-fold Relations in Knowledge Bases

Representation learning of knowledge bases aims to embed both entities and relations into a continuous vector space. Most existing models such as TransE, DistMult, ANALOGY and ProjE consider only binary relations involved in knowledge bases, while multi-fold relations are converted to triplets and treated as instances of binary relations, resulting in a loss of structural information. M-TransH is a recently proposed direct modeling framework for multi-fold relations but ignores the relation-level information that certain facts belong to the same relation. This paper proposes a Group-constrained Embedding method which embeds entity nodes and fact nodes from entity space into relation space, restricting the embedded fact nodes related to the same relation to groups with Zero Constraint, Radius Constraint or Cosine Constraint. Using this method, a new model is provided, i.e. Gm-TransH. We evaluate our model on link prediction and instance classification tasks, experimental results show that Gm-TransH outperforms the previous multi-fold relation embedding methods significantly and achieves excellent performance.
Universal Learning Machine with Genetic Programming

This paper presents a proof of concept. It shows that Genetic Programming (GP) can be used as a “universal” machine learning method, that integrates several different algorithms, improving their accuracy. The system we propose, called Universal Genetic Programming (UGP) works by defining an initial population of programs, that contains the models produced by several different machine learning algorithms. The use of elitism allows UGP to return as a final solution the best initial model, in case it is not able to evolve a better one. The use of genetic operators driven by semantic awareness is likely to improve the initial models, by combining and mutating them. On three complex real-life problems, we present experimental evidence that UGP is actually able to improve the models produced by all the studied machine learning algorithms in isolation.
A Progressive Visual Analytics Tool for Incremental Experimental Evaluation.

This paper presents a visual tool, AVIATOR, that integrates the progressive visual analytics paradigm in the IR evaluation process. This tool serves to speed-up and facilitate the performance assessment of retrieval models enabling a result analysis through visual facilities. AVIATOR goes one step beyond the common compute wait visualize analytics paradigm, introducing a continuous evaluation mechanism that minimizes human and computational resource consumption.
An Image-Based Vocabulary Learning System Based on Multi-Agent System

Promoting and developing English language skills are essential for second language learners. This paper presents the design and development of a mobile application for promoting learners' experiences in learning the English vocabularies by formulating the compound words generated from images. The proposed system is based on the multi-agent system (MAS) covering three main agents: matching learners agent, combination vocabulary agent, and feedback agent. The innovation of the proposed approach is that many learners (matching learners agent) can formulate the new vocabulary that is formed from the combination algorithm (combination vocabulary agent) and learners can experience new vocabulary represented by using the image results (feedback agent). The two experiments of the system performance evaluation are reported. The experimental results show that the performance of the vocabularies' detection and the sub processes execution were achieved the high accuracy.
Membaca Kritis dan Kemampuan Mengungkapkan Makna Tersirat Teks Cerpen Siswa SMP

This study aims to: (1) describe the ability of student to uncover the implicit meaning of short stories before applying critical reading strategies in grade VII student of Marioriawa State Middle School 3 Soppeng Regency; (2) describe the ability of student to uncover the implicit meaning of short stories after applying critical reading strategies in grade VII student of Marioriawa State Middle School 3 Soppeng Regency; and (3) knowing the effect of critical reading strategies on the ability to uncover the implicit meanings of short story texts in class VII students of Marioriawa 3 Public Middle School, Soppeng District. This type of research is quantitative research with a pre-experimental design using test techniques namely the initial test (pretest) and the final test (posttest). The sample of this study was the seventh grade students of Marioriawa State Middle School 3 Soppeng Regency, amounting to 45 people. The data collection technique used is the test technique. The results showed that there was a significant effect of critical reading on the ability to express the implicit meaning of short stories.
Geometrical correction for surrounded projection by simplifying a shape of a measured indoor space

Recently, image projection attracted a lot of attention, and it is used in various situations. So, the system that realizes image projection simply in any wide areas becomes necessary. Therefore, in this research, we proposed a geometrical correction method for surrounded projection combining a standard lens camera with a fish-eye lens camera and realize simple construction of image projection space in any indoor spaces. By capturing the same pattern images from two types of cameras, two types of cameras are corresponded without external parameters of cameras and projectors, and simplifying obtained data makes the correspondences highly accurate. In this research, we evaluated our geometrical correction method in accuracy, and projected image projection with multiple projectors in the wide indoor space.
Prospects and challenges of virtual reality adoption for destination marketing

Virtual Reality (VR) is a cutting-edge technology that has been widely adopted for promotional purposes. In tourism industry, VR is favored due to its interactivity characteristics on delivering experience of tourist destination. The objective of this research is to explore the prospects and challenges of VR adoption for destination marketing. This study is a qualitative research in which the data are collected through observation and in-depth interview with 3 informants, i.e. a virtual reality maker, an advertising agency, and a traveler. The result indicates that VR as destination promotional tools is evolving in number and types of virtual reality formats that have been used, e.g. 3D image, application and 360° video. It offers different visualization and effectiveness in capturing users’ attention. However, VR as promotional tools faces several challenges in terms of cost, system development, visualization, and creativity as a package of tourist destination marketing.