Reviewerly/exHarmony huggingface dataset:
Strategi Peningkatan Keterampilan Bahasa Inggris Pelaku Wisata Di Desa Wisata Tista, Kerambitan, Tabanan

English communication is a problem faced by the human resources involved in the tourism activities in Desa Wisata Tista, Kerambitan Subdistrict, Tabanan Regency, Bali. However, there had been no research that identified English problems. Then, this research was done to (1) identify the problem faced by the human resources involved in tourism activities in Desa Wisata Tista, Kerambitan Subdistrict, Tabanan Regency, Bali and (2) finding out the proper and suitable English learning strategies to improve the English mastery of the human resources involved in the tourism activities in Desa Wisata Tista, Kerambitan Subdistrict, Tabanan Regency, Bali. The data used in this research were gained through interviews, observation, and literature studies. The data were analyzed qualitatively. The results of the analysis reveal that (1) the numbers of the human resources who can speak English is limited, (2) the lack of speaking skills using English, (3) the lack of English vocabulary they have, and (4) low level of self-confidence to communicate in English. These problems can be overcome by implementing several strategies, namely (1) memory strategy, (2) cognitive strategy, (3) affective strategy and (4) social strategy. Based on the identification, the managers can conduct English course for the community. Keywords: English Communication, English Learning Strategies, English Communication Problems, English for Tourism Workers
Detection, Recognition and Tracking Cars from UAV Based implementation of MobileNet- Single Shot Detection deep neural network on the embedded system By Using Remote Sensing Techniques

Tracking targets from the ground is difficult due to natural and artificial barriers, and in some cases, such as car detection, is dangerous, therefore, identifying targets using remote sensing is obvious. To achieve the purpose, the desired camera is installed on the unmanned aerial vehicle (UAV). with images processing on captured images from the camera, the system has used can identify the vehicle using aerial images and follow it if it is necessary. An important issue to this matt
Brian Lennon <i>Passwords: Philology, Security, Authentication</i>. Cambridge, Mass.: Harvard University Press, 2018. 229 pp.

Previous article No AccessThe CI ReviewBrian Lennon Passwords: Philology, Security, Authentication. Cambridge, Mass.: Harvard University Press, 2018. 229 pp.Avery SlaterAvery Slater Search for more articles by this author PDFPDF PLUSFull Text Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinkedInRedditEmail SectionsMoreDetailsFiguresReferencesCited by Critical Inquiry Volume 47, Number 2Winter 2021 Article DOIhttps://doi.org/10.1086/712124 Views: 119Total views on this site For permission to reuse, contact [email protected]PDF download Crossref reports no articles citing this article.
The Effect of Catalisting Strategy OnStudents‟ Writing Skill At Madrasah Aliyah Laboratorium UINSU Medan

The objective of this research is to improve students‟ ability to write effectively.Writing is a basic thing that‟s important to learn. It was done by using catalisting strategy indescriptive text. The classes studied were two classes, namely class XI MIA-1 and class XIMIA-2. The number of each students are 30 students. This research was conducted at MALUINSU. This study is aimed at the effectiveness of catalisting strategies on students‟ abilityto write descriptive text through the scores. Based on the result, using quantitative research.The student‟s achievement in writing descriptive text in experimental group showed thelowest score of pre-test was 60, and the highest score of pre-test was 92 and the mean of pre-test was 77.2. Furthermore, the lowest score of post-test was 65, and the highest score ofpost-test was 95 and the mean of post-test was 80. Based on the table above, the student‟sscore in writing descriptive text in control group showed the lowest score of pre-test was 60,and the highest score of pre-test was 85 and the mean of pre-test was 69.5. Furthermore, thelowest score of post-test was 60, and the highest score of post-test was 80 and the mean ofpost-test was 71.4. Based on the result of posttest of experiment class and control class, it can befound that the tobserved = 0.995> ttable = 0.910 in the significance level of 0.05 (5%) and the Sign. (2-tailed) is 0.000 ttable and the Sign. (2-tailed) < 0.05, it means that Hα isaccepted. So, the researcher can conclude that the students‟ writing skill can be done effectively bycatalisting strategy on student achievement in writing.
AKTUALISASI PELAYANAN PENDIDIKAN MELALUI BUDAYALITERASI PAGI DI SMPN 1 LATAMBAGA (BEST PRACTICE)

To realize the objectives of National Education in its entirety, the government has issued Permendikbud No. 23 of 2015 concerning the Development of Ethical Characteristics which contains a structured and planned learning activity realized through the School Literacy Movement (GLS). The Permendikbud is an effort to foster students' character that aims to have students have a culture of reading and writing so as to create a learning culture that can last a lifetime. GLS activities have been carried out since 2015 at SMP Negeri 1 Latambaga. The stages of GLS conducted at SMP Negeri 1 Latambaga include: 1) the stages of understanding; 2) the stage of habituation; 3) stages of learning. To support the implementation of the School Literacy Movement activities several efforts were made at Latambaga 1 Public Middle School, including: 1) Making an expression stage; and 2) Installation of internet networks to facilitate the procurement of wifi in the online learning process. The real impact felt by the existence of the School Literacy Movement is that it can improve students' insights and knowledge, increase vocabulary, improve memory quality, practice skills for thinking and analyzing, increase focus and concentration, can help prevent cognitive decline, can increase one's empathy , and can help students connect with the outside world as a manifestation of the vision of a local school with global culture.
Eye Tracking Simulation for a Magnetic-based Contact Lens System

In this paper, we present a simulation of an eye motion tracking system. The system consists of a moving magnet and three static magnetic sensors, which implies the magnet embedded in a contact lens and sensors fixed on the spectacles in the application scenario. When the eye is moving, the changing relative position between sensors and magnet will result in different sensory outputs that encodes eye movement information. The simulation of eye movements and corresponding magnetic fields was carried out in MATLAB MathWorks software. After collecting the sensory output, artificial neural network was used to decode the signal and classify the direction of gaze. In total 30 different configurations were tested to determine which one gives the highest accuracy. The network prior to each configuration was trained and the output was compared to the actual position of the eye. It was found that the lens misplacement may cause a lot of issues and requires further investigation to lower its impact on the results. This could be fixed by introducing a calibration step. For all of the configurations, usually, the confusion occurred on the neighbouring classes. This could be due to poor design of the classes, where borders of the regions do not overlap, and cause a sudden change. Based on this simulation, better tracking method can be derived.
Mike Kestemont en Dirk Van Hulle (red.), ‘Theorie en de digitale geesteswetenschappen’, Tijdschrift voor Nederlandse Taal- en Letterkunde

Amsterdam University Press is a leading publisher of academic books, journals and textbooks in the Humanities and Social Sciences. Our aim is to make current research available to scholars, students, innovators, and the general public. AUP stands for scholarly excellence, global presence, and engagement with the international academic community.
Justification of the Fragmentation: Lev Shestov’s “All Things are Possible (The Apotheosis of Groundlessness)” (1905)

In All Things are Possible (Apotheosis of Groundlessness, 1905) – one of the key works of the beginning of the 20th century – Lev Shestov suggests the principles of fragmentation, which make it possible to more clearly represent many phenomena not only in philosophy, but also in literature and art, including those emerging much later. The search for new forms of thought took place in the new practices of narration and new representation of images (what became a key issue for the entire 20th century) of wandering in a labyrinth, lonely existence, insight, fragmentation of the universe. The images were inherent in the literature of the 19th century, but at the beginning of the 20th century they acquired new qualities and accounted for a new reality, in which the fragmentary is fundamentally incomplete, is not included in the system of thought, but forms new connections, exists without a unifying plan. This type of thinking is largely prepared by Lev Shestov’s practice of rereading, which creates a new type of thinking in all his works.
Visual servoing based control methods for non-holonomic mobile robot

In this paper, we utilized two vision-based go-to-goal robot control approaches and compare them to the non-holonomic indoor mobile robot. In the proposed methods, an overhead camera image data is used as the input parameters when the robot wheel speeds are determined. The main purpose of this system is to minimize the complexity of conventional robot control kinematics and to provide an efficient control approach when controlling the wheel speeds and the robot orientation angle of the mobile robot. In addition to reducing the complexity of robot control kinematics, it is also intended to reduce systematic and non-systematic errors. Our proposed method is divided into three phases; the first phase is that the calibration of the overhead camera and working environment. At this phase, target and labels placed on the robot were detected and robot position information was extracted. The second phase is tracking the robot motion and extracts the control inputs’ such as position and orientation based on visual feature information. The third phase is controlled loop by using Graph and Angle based control approaches merged with Gaussian and Decision tree algorithms. We have briefly described these control approaches as follows. Graph-based decision tree control as (GDTC), Graph-based Gaussian control as (GGC), Angle-based decision tree as (ADTC) and Angle based Gaussian control as (AGC). Experiments have been performed for the non-holonomic mobile robot with the eye-out-device camera configuration in real-time. Our experimental results are presented to emphasize the efficiency of the methods in the presence of kinematic disturbances and without using any extra sensors, only overhead camera.
OMEGA : A probabilistic approach to referring expression generation in a virtual environment

In recent years, referring expression genera- tion algorithms were inspired by game theory and probability theory. In this paper, an al- gorithm is designed for the generation of re- ferring expressions (REG) that base on both models by integrating maximization of utilities into the content determination process. It im- plements cognitive models for assessing visual salience of objects and additional features. In order to evaluate the algorithm properly and validate the applicability of existing models and evaluative information criteria, both, pro- duction and comprehension studies, are con- ducted using a complex domain of objects, pro- viding new directions of approaching the eval- uation of REG algorithms.
Silicon-based Optical Neural Network Chip Based on Coherent Detection

We design a silicon-based optical neural network (ONN) chip based on coherent detection. Nonnegative neural networks are trained and tested on three different datasets and test accuracies are 96.67%, 97.22% and 96.16% respectively.
Instructional Design of Data Modeling for Informal Statistical Inference of Elementary School Students

The purpose of this article is to present the design principles of data modeling activities for the development of informal statistical inference of elementary school students, and systematically illuminate the design process based on it. The details are as follows. First, through the analysis of previous research, we draw the data modeling process and the norm of task design for the development of informal statistical inference of elementary school students. Second, based on the design principles, we developed a data modeling task and lessons, and after expert evaluation, a teaching experiment was conducted for actual elementary school students. The implications of this study are the following. First, through exploring the appropriate design principles and methods to apply each principle to the student level, we confirmed the usability of data modeling activities for the development of informal statistical inference. Second, When using technology in data modeling activities, it is necessary to select a tool that suits the student's level and the context of the class. Third, when designing lesson sequences for the development of informal statistical inference, special care of the integration of contextual knowledge is needed.
Optimization of Search Algorithm using Regular Expressions and Finite Automata

In the world of computer science, algorithms and data structures are an important part of any programming task. There are many ways of implementing an algorithm to perform a certain task, but only ...
Advances in Statistical and Machine Learning Methods for Image Data, with Application to Alzheimer's Disease

The revolutionary development of neuroimage technology allows for the generation of large-scale neuroimage data in modern medical studies. For example, structural magnetic resonance imaging (sMRI) is widely used in segmenting neurodegenerative regions in the brain and positron-emission tomography (PET) is commonly used by clinicians and researchers to quantify the severity of Alzheimer's disease. In the first part of this dissertation, we build “OASIS-AD”, which is a supervised learning model based on a well-validated automated segmentation tool “OASIS” in multiple sclerosis (MS). OASIS-AD considers the specific challenges raised by WMH in Alzheimer's Disease (AD) to reduce false discoveries. We show that OASIS-AD performs better than several existing automated white matter hyperintensity segmentation approaches. In the second part of this dissertation, we develop an interpretable penalized multivariate high-dimensional method for image-on-scalar regression that can be used for association studies between high-dimensional PET images and patients' scalar measures. This method overcomes the lack of interpretability in regularized regression after reduced-rank decomposition through a novel encoder-decoder based penalty to regularize interpretable image characteristics. Empirical properties of the proposed approach are examined and compared to existing methods in simulation studies and in the analysis of PET images from subjects in a study of Alzheimer's Disease. In the third part of this dissertation, we developed ACU-Net, an efficient convolutional network for medical image segmentation. The proposed deep learning network overcomes the small sample size problem of training a deep neural network when used for medical image segmentation. It also decreases computation cost by increasing the effective degrees of freedom through data augmentation and the novel use of convolutional layers blocks to compress the model. We show that ACU-Net can achieve competitive performance while dramatically decreases the computation cost compared with modern CNNs. Public health significance: This dissertation proposes new statistical and machine learning methods for two aging-related problems: (1) automatically segmenting white matter hyperintensity (WMH), a biomarker of neurodegenerative pathology, and (2) estimating the association between neurodegeneration pathology and vascular measures, which are important to aging population living quality and can be studied by clinical neuroimage data.
Best k-Layer Neural Network Approximations

We show that the empirical risk minimization (ERM) problem for neural networks has no solution in general. Given a training set $$s_1, \ldots , s_n \in {\mathbb {R}}^p$$ with corresponding responses $$t_1,\ldots ,t_n \in {\mathbb {R}}^q$$ , fitting a k-layer neural network $$\nu _\theta : {\mathbb {R}}^p \rightarrow {\mathbb {R}}^q$$ involves estimation of the weights $$\theta \in {\mathbb {R}}^m$$ via an ERM: $$\begin{aligned} \inf _{\theta \in {\mathbb {R}}^m} \ \sum _{i=1}^n \Vert t_i - \nu _\theta (s_i) \Vert _2^2. \end{aligned}$$ We show that even for $$k = 2$$ , this infimum is not attainable in general for common activations like ReLU, hyperbolic tangent, and sigmoid functions. In addition, we deduce that if one attempts to minimize such a loss function in the event when its infimum is not attainable, it necessarily results in values of $$\theta $$ diverging to $$\pm \infty $$ . We will show that for smooth activations $$\sigma (x)= 1/\bigl (1 + \exp (-x)\bigr )$$ and $$\sigma (x)=\tanh (x)$$ , such failure to attain an infimum can happen on a positive-measured subset of responses. For the ReLU activation $$\sigma (x)=\max (0,x)$$ , we completely classify cases where the ERM for a best two-layer neural network approximation attains its infimum. In recent applications of neural networks, where overfitting is commonplace, the failure to attain an infimum is avoided by ensuring that the system of equations $$t_i = \nu _\theta (s_i)$$ , $$i =1,\ldots ,n$$ , has a solution. For a two-layer ReLU-activated network, we will show when such a system of equations has a solution generically, i.e., when can such a neural network be fitted perfectly with probability one.
Quantum Subsystems and Properties

This chapter covers quantum subsystems and their properties. Single and multiple quantum bit systems are discussed in detail. Quantum states, protocols, operations, and transformations are also presented in this chapter.
4차 산업혁명과 환경 친화적 교통 산업 발전 전략과 정책

The purpose of this paper is to review and study policy and strategy for 4th industrial revolution and eco-friendly transportation.First, meaning and definition of the 4th industrial revolution are studied and reviewed. And then, the current and upcoming revolutions in transportations in the era of the 4th industrial revolution are deeply investigated and researched.How system dynamics approach can be used and utilized in the study of the 4th industrial revolution and eco-friendly transportation are main purpose of this research. This study reviews important and significant related researches that have employed system dynamics approach in investigating the 4th industrial revolution and related innovations and developments in eco-friendly transportation and whole transportation sector. Especially, the study focuses on development strategy and policy to nurture new transportation industries based on 4th industrial revolution.As results, this study shows usefulness and current and potential contributions of the system dynamics approach in investigating upcoming huge technological innovations, those are the 4th industrial revolution, and the related innovations in many important sectors such as transportations and eco-friendly industries.
Assessing the impact of regional scientific environment on the performance of scientific organizations: the example of Russia

The goal of the study is to determine the impact of the regional scientific environment on the performance of scientific organizations. The indicators of a regional scientific environment, which were used as predictors in a regression model built to assess the dependence of the effectiveness of scientific organizations has been identified during the study. In the model, the category of scientific organizations was assigned as a dependent variable, according to the results of the federal monitoring conducted in 2016 for 541 scientific organizations located in 65 Russian regions. The study showed that there were no significant differences between regions when comparing factors determining the regional scientific environment and the performance of scientific organizations.
LibGuides: Intro to Poetry: Home

A guide to introduce high school students to some of the basic skills used for reading and analyzing poetry..
SOFTWARE QUALITY TESTING ON THE E-SIM APPLICATION BASED ON ISO 9126

Sidoarjo City Resort Police is one of the police stations that provides driving license making and driving license extension services for all Indonesian citizens. Sidoarjo City Resort Police have implemented a mobile-based e-sim application that can make it easier for applicants to make or extend their driving license at the Sidoarjo City Resort Police. This e-sim application has never been tested for software quality so the purpose of this study is to measure the quality of the e-sim application based on ISO 9126 and provide recommendations for the e-sim application based on the results of software quality testing that has been done. The method that used in this research is quantitative methods that using a questionnaire as a research instrument. The results of this research are software quality measurement results based on 6 aspects of ISO 9126 which is: usability variable is 72%, efficiency variable is 74%, functionality variable is 82%, reliability variable is 80%, maintainability variable is 87% and the variable portability is 73%. Through these results, an average feasibility of an e-sim application is obtained by 78% with an interpretation of Enough so that it can be stated that the Sidoarjo City Resort Police e-sim application has met ISO 9126 standards.
Mama/Papa, Is this Text for Me?

Children have less linguistic skills than adults, which makes it more difficult for them to understand some texts, for instance when browsing the Internet. In this context, we present a novel method which predicts the minimal age from which a text can be understood. This method analyses each sentence of a text using a recurrent neural network, and then aggregates this information to provide the text-level prediction. Different approaches are proposed and compared to baseline models, at sentence and text levels. Experiments are carried out on a corpus of 1, 500 texts and 160K sentences. Our best model, based on LSTMs, outperforms state-of-the-art results and achieves mean absolute errors of 1.86 and 2.28, at sentence and text levels, respectively.