Reviewerly/exHarmony huggingface dataset:
A Review on the Applications and Challenges of Active Silicon Ring Resonators

Integrate photonic devices show promise not only for short-range optical interconnects, but also as a platform for non-von Neumann or "neuromorphic" computing [1]-[5]. Among other devices, silicon ring resonators provide a platform for the interaction of photons, phonons and free carriers using Kerr and free-carrier nonlinearities [5]-[7]. This interesting platform has been proposed for several applications, like the realization of free carrier oscillators, bistable behaviour, nonlinear thresholder, and spike generators [5]-[10]. Compared to other CMOS-compatible materials, silicon waveguides have a low threshold for Kerr nonlinearity in telecom wavelengths. However, in this regime, two-photon absorption results in the generation of carriers. These carriers accumulate and increase the waveguide loss due to free-carrier absorption.
An Analysis of How to Improve the Effect of Task-based Teaching Method in Tertiary School English Teaching

The paper analyzes the concept of task-based teaching method and its advantages in tertiary school English teaching, and focuses on how to effectively improve the English teaching effect of tertiary school through task-based teaching method for reference.
Exploring the LASSO as a Pruning Method

In this study, the efficiency of various pruning algorithms were investigated, with an emphasis on regularization methods. Pruning is a method which aims to remove excess objects from a neural network. In particular, this included the LASSO (Least Asbolute Shrinkage and Selection Operator) and the extensions derived from it, which were compared with other methods, including optimal brain damage and the elastic net. Initially, this was implemented for MLPs, but the same methods were extended to CNNs with some alterations for increased computational efficiency. Pruning was then implemented on the level of weights, neurons as well as filters. It was concluded that the LASSO tends to yield a superior sparsity on the level of weights, but the group LASSO's ability to select variables simultaneously is a worthwhile addition. Also, optimal results can be obtained by combining both while regularizing the cost function.
Research Guides: Films & Video @ ATU Libraries: Recommend A Video

Everything you wanted to know about physical and streaming collections of films and video for classroom use.
Enumeration of Self-Dual Codes of Length 6 over ℤp

The purpose of this paper is to classify and enumerate self-dual codes of length 6 over finite field &#x0D; &#x0D; &#x0D; &#x0D; Z&#x0D; p&#x0D; &#x0D; &#x0D; &#x0D; . First, we classify these codes into three cases: decomposable, indecomposable non-MDS and MDS codes. Then, we complete the classification of non-MDS self-dual codes of length 6 over &#x0D; &#x0D; &#x0D; &#x0D; Z&#x0D; p&#x0D; &#x0D; &#x0D; &#x0D; for all primes p in terms of their automorphism group. We obtain all inequivalent classes and find the necessary and sufficient conditions for the existence of each class. Finally, we obtain the number of MDS self-dual codes of length 6.
Perceptually motivated algorithm for grouping objects in complex scenes

Region proposal algorithms are beneficial for enhancing the performance of object detection and recognition methods. We present a method for grouping region proposals based on perceptual grouping principles. The grouping principles are simulated to extract image features, and the region proposals are segmented by solving a sequence of parametric maxflow problems. In order to extract complex objects from natural images, the element connectedness cue is introduced in the parametric energy functions. This newly introduced cue is propitious to group objects with diversified patterns. To effectively fuse the grouping principles, a multiclassify-based learning algorithm is proposed to optimize an ensemble of binary segmentation models. The training samples are first divided into groups to pretrain each individual model, and the algorithm adaptively adjusts the sample groups in the iteration procedure to learn an optimal set of models. We conduct the experiments on the PASCAL Visual Object Classes Challenge 2012 segmentation dataset but also in the context of region proposals in optical remote sensing images, and the results show that the proposed method can achieve a favorable performance compared to the existing algorithms.
Discussion on the Role of Information Disciplines in the Construction of New Engineering

New engineering has some new features such as new educational concepts, crossing disciplines and industry-university cooperation and education, and is closely related to the new generation of information technology. This paper discusses the construction of new engineering and the new educational concepts, new features, new models and new methods of talent training, explores the need of information talent training, the crossing innovation of specialties, the model reform of talent training and the construction of education system, and puts forward some viewpoints and suggestions on the role of information disciplines in the construction of new engineering.
Conspiracy Theories, Misinformation, Romance Scamming, White Nationalism, Twitter, and YouTube

Trigger warning: this post discusses misinformation related to the suicide of a person implicated in sex trafficking of minors. While it does not go into
PENGEMBANGAN MODEL PEMBELAJARAN BERBASIS MASALAH BERBATUAN MULTIMEDIA DALAM PEMBELAJARAN MENULIS TEKS EKSPOSISI SISWA KELAS VIII SMP

The current learning in schools is use to learning models that have generally been used from time to time or traditional ways. This requires innovation by utilizing existing technological developments. The purpose of this research is to explore the application of a model of learning based on problems and use multimedia in learning exposition text. The type of study is development research. The research design in this study was pretes-postest group design. The sample in this study was 8th-grade junior high school students amounting to 183 students. The result showed that the students’ writing skill improved much better with the application of learning model based on problems aided by the presence of technology by multimedia in supporting the process of observing students in gathering material in writing exposition text. Based on the results of the pretest and postest, it was done showing an increase in the value of students in writing exposition text about environmental problems observed around them. With this study, learning, it can be concluded that students ability two write exposition text with the existence of problem-based on the learning model is at a level very good.
Consensual aggregation of clusters based on Bregman divergences to improve predictive models

A new procedure to construct predictive models in supervised learning problems by paying attention to the clustering structure of the input data is introduced. We are interested in situations where the input data consists of more than one unknown cluster, and where there exist different underlying models on these clusters. Thus, instead of constructing a single predictive model on the whole dataset, we propose to use a K-means clustering algorithm with different options of Bregman divergences, to recover the clustering structure of the input data. Then one dedicated predictive model is fit per cluster. For each divergence, we construct a simple local predictor on each observed cluster. We obtain one estimator, the collection of the K simple local predictors, per divergence, and we propose to combine them in a smart way based on a consensus idea. Several versions of consensual aggregation in both classification and regression problems are considered. A comparison of the performances of all constructed estimators on different simulated and real data assesses the excellent performance of our method. In a large variety of prediction problems, the consensual aggregation procedure outperforms all the other models.
Large-scale neural dissociations between views of objects, scenes, and reachable spaces

Space-related processing recruits a network of brain regions separate from those recruited in object-related processing. This dissociation has largely been explored using views of navigable-scale spaces compared to singleton objects. However, in naturalistic visual experience, we encounter spaces intermediate to these extremes, like the tops of desks and kitchen counters, which are not navigable but typically contain multiple objects. How are such intermediate “reachspaces” represented in the brain? Human participants underwent functional neuroimaging in which brain responses to reachspaces were compared with responses to scene and object views (Experiment 1, N=12). We found evidence for at least two regions that prefer reachspaces to both scenes and objects: one in ventral visual cortex (11/12 participants), one in occipito-parietal cortex (10/12 participants), with a potential third region in superior parietal cortex. Reachspace preferences were maintained in these regions even when all images were equalized in luminance, contrast and spatial frequency (Experiment 2a, N=12), indicating that low-level differences alone cannot account for these activation differences. Furthermore, these regions respond more strongly to views of multiple objects on blank backgrounds than to empty near-scale spaces (Experiment 2b), pointing to a role for multi-object processing. Finally, reachspaces elicited activity in both scene- and object-selective ROIs, driving each of these regions to an intermediate degree. Taken together, these results provide evidence for a neural distinction between reachspaces, full-scale scenes, and singleton object views. Broadly, the current evidence suggests that visual representations of reachable environments may draw on object-based and space- based computations, as well as recruiting additional regions to support multi-object processing.
InfoGuides: Spanish Language Proficiency Resources for Social Services: Dictionaries & Vocabulary

Resources to assist with Spanish language proficiency for social services staff (social workers, vocational rehabilitation, self sufficiency, etc.)
Towards Explainability for a Civilian UAV Fleet Management using an Agent-based Approach.

This paper presents an initial design concept and specification of a civilian Unmanned Aerial Vehicle (UAV) management simulation system that focuses on explainability for the human-in-the-loop control of semi-autonomous UAVs. The goal of the system is to facilitate the operator intervention in critical scenarios (e.g. avoid safety issues or financial risks). Explainability is supported via user-friendly abstractions on Belief-Desire-Intention agents. To evaluate the effectiveness of the system, a human-computer interaction study is proposed.
Pemanfaatan Augmented Reality sebagai Media Pembelajaran Kerangka Manusia di SMP Negeri 2 Kartasura

SMP Negeri 2 Kartasura is the First Middle School located on Jl. A. Yani No. 320, Banaran, Pabelan, Sukoharjo, Central Java. In the learning process of SMP Negeri 2 Kartasura using the 2013 curriculum. In biology subjects, especially material on the human skeleton, the learning process still uses manual methods from books and continues the information from the teacher which makes students easily bored. In this day and age people of all ages have an Android smartphone that is not only used for communication, but also for information and learning. Therefore, with android applications and augmented reality technology students can find out human skeletons in 3D. The purpose of this study is to display the 3D shape of a human skeleton to facilitate students in understanding the lesson. In this study the authors used several software namely Blender, Unity 3D, and Adobe Photoshop. The method used in this study is SDLC with Waterfall modeling. The results obtained 2 by the author are an android application with augmented reality technology that uses markers in the form of a QR Code to display the 3D shape of a human skeleton. The author tests to get the results of applications that can run well, using the black box testing method. The marker test showed that the marker could not be read when lighting was dark, and when the marker was squeezed. At the last stage the author conducted tests on students and teachers at SMP Negeri 2 Kartasura by means of a questionnaire and the results were obtained with a good indicator of 81.72%. From this study it can be concluded that this application is feasible to be used in the learning of SMP Negeri 2 Kartasura.
Research Guides: Films & Video @ ATU Libraries: Academic Video Online

Everything you wanted to know about physical and streaming collections of films and video for classroom use.
A study of the direction in the methodology of action research through analyzing the action research studies in English education

This paper analyzes 46 theses and 13 journal articles that have used action research methodology in the study of elementary and secondary English education in Korea for the last 18 years (2001-2019). Three criteria have been applied to the analysis of the selected action research studies: the teacher as a practitioner of action research, the spiraling cycles of the research process, and the teacher learning community to share research results. The findings are as follows. While teachers as the main researcher participated in the research in most of the studies, their action research basically did not start from figuring out the problems inherent in their teaching practices but from applying the existing instructional theories to their teaching practices. As a result, 83.05% of the studies left out the process of analyzing the problems inherent in the teaching practices. Also, only 23.73% of researchers shared the research results without forming the teacher learning community. This study shows that many studies have been conducted under the name of action research, but there are not many in its true sense. It is necessary to comply with the aforementioned criteria to be proper action research.
I see what you did there: Deep learning algorithms can classify cognitive tasks from images of eye tracking data

Since Yarbus (1967) wrote the book on examining eye movements, researchers have tracked eye movements associated with various tasks and mindsets. This line of research has consistently shown that eye movements can be indicative of the task at hand (Einhauser et al., 2008; Yarbus, 1967). Recently, theoretically informed computational models have been able to categorize eye movements at levels significantly above chance (e.g., MacInnes et al., 2018). The purpose of the present study was to design a neural network alternative to the previously implemented eye tracking models by categorizing eye movements using a simple deep learning model that was not guided by theoretical assumptions. In the current study, participants were presented with color images of scenes (interior and exterior locations, no images of people) while performing either a search task, a memory task, or an image preference task. Each image was viewed for several seconds, during which an eye tracker sampling at 1000 Hz was used to record eye movements. During data processing, each trial was converted into an image that represented the full path of the eye movements throughout the trial, but without any explicit notation of saccades, fixations, dwell times, or other traditional eye tracking variables. The DeLINEATE deep learning toolbox (http://delineate.it) was used to classify these images. The classifier consisted of a convolutional neural network that decoded the image into search, memory, or preference tasks. The deep learning model classified the eye movement images with accuracy that was well above chance, commensurate to contemporary results using explicit cognitive models. This suggests that deep learning models are capable of extracting a surprising amount of useful information out of nearly-raw eye tracking data with minimal human guidance as to what the relevant features are in the data.
Jämförelse av NoSQL-databas och SQL-baserad relationsdatabas : En förklarande studie för när NoSQL kan vara att föredra framför en relationsdatabas

With the explosive development of the mobile world, web applications and Big Data, new requirements for storage capacity and speed of database systems have arisen. The traditional relational databa ...
Who will surf for science? Understanding motivations to engage surfers in citizen science with Smartfin.

Author(s): Scott, Vanessa | Abstract: Coastal zones provide significant social and economic benefits to society and are home to the majority of the global population. While highly desirable, these areas are also some of the most affected by climate change and population growth. As climate change continues to progress and severe weather events become increasingly unpredictable, it is crucial to expand the collection of real time data that can improve forecasting, contribute to scientific research and provide information to assist with mitigation and planning efforts in coastal regions. Smartfin, a surfboard fin with a sensor that records sea surface temperature (SST) and GPS data, is a cost effective tool that enables surfers to contribute important oceanographic information to fill the data gaps and support scientific research while doing the activity they love. The purpose of this Capstone project is to find out what groups within the surf community would surf for science, what would motivate them to take part in citizen science and how much would they be willing to pay to participate. To answer these questions, a survey was designed exploring the habits, preferences, environmental views and use of technology among surfers. Using Qualtrics software, the survey was distributed to the surf community through social media. The results confirm the hypothesis that there are groups within surf community motivated to participate in citizen science and pay for a Smartfin.
Current Use of Childcare Service and Reform Tasks for More Effective Service System

Early Childhood Education and Care(ECEC) remains high on the policy agenda in many OECD countries. They all have recently tried to have high quality services for children under 6, and effectively support the families in need of service as one of the work-family reconciliation policy programmes. Since both Lee MyungBak government enacted a cash system for family care at home, and Park GeunHye government introduced no-fee policy system into childcare policy, Korea s childcare service has completely lost it s focus. This paper attempts to review current pattern of use of childcare service based on several policy principles, and highlights the differences between Korean policy frame and OECD countries overall which reveals a quite stark contrast. Since Korean childcare policy has been inconsistent, it is urgent to build up clarity of this policy s purpose as well as main target population, and to stop no-fee policy in order to better invest in staff side before it is too late which is surely expected to boost up the service quality.
High-rate measurement device-independent quantum key distribution system

Measurement device-independent quantum key distribution (MDI-QKD) system is significant for exploring the future communication system because of its outstanding performance in security. In this paper, the key rate of single-photon source and WCP source with common wavelength under ideal infinite-decoy case is analyzed in order to outline the relationship between the key rate and the optimization of light intensity. The performance of the key rate under the simplest situation of finite decoy-state (two decoy-state) is compared. The result may provide important parameters for the practical application of QKD system.
Literasi Digital Dalam Mewujudkan Guru Berkualifikasi Ulul Albab di SD Muhammadiyah Program Khusus Kottabarat Surakarta

The purpose of this study is to describe: 1. Teachers 'understanding of digital literacy, 2. Digital literacy programs in realizing qualified teachers of Ulul Albab, 3. Teacher inhibiting factors in improving digital literacy skills, 4. Teachers' efforts to minimize barriers to improve a digital literacy skills in Muhammadiyah Elementary School Special Program of Kottabarat Surakarta. This research is a qualitative research with phenomenology design. Data collection techniques using interviews, observation, and documentation. Data analysis using interactive models. The validity of the data uses source and technique of triangulation. The results of the study show that literacy is important for teachers, the interpretation of the definition of digital literacy is good. The digital literacy competency in searching information on the internet is classified as good, evaluation of information content is classified as lacking, and compilation of knowledge is classified as good. Digital literacy programs in the form of self-development are classified as good, scientific publications are quite sufficient, and innovative works are classified as lacking. The inhibiting factors of digital literacy are from internal and external teachers. Teachers' efforts to minimize obstacles in digital literacy by participating in self-development activities more optimally such as workshops, peer tutors, clusters, managing time proportionally and collaborating with colleagues, maintaining body stamina, increasing school infrastructure facilities to support the use of digital literacy, and better budgeting.
Optimalisasi Perkembangan Bahasa melalui Kegiatan Esksplorasi Lingkungan Menggunakan Media Kaca Pembesar pada Anak Kelompok Tk B di PAUD Surya Alam 'Aisyiyah, Sawit, Boyolali Tahun Ajaran 2018/2019 Tahun Ajaran 2018/2019

This research aims to improve language development through environmentexploration using magnifying glass as a learning media on pupils of Grade BKindergarten in PAUD/KB Surya Alam Aisyiyah Sawit Boyolali academic year2018/2019. This research uses class action research conducted in three cycles, suchas cycle I, cycle II, and cycle III with 2 meeting in each cycle. There are 4 stages inthis research consisting of action planning, implementation of action planning,observation or data collection and reflection. The research subjects are 14 students.Data collection method uses are observation, interview and documentation. Theresults of pracycle stage show 37,24%. Furthermore, the results of cycle I show63,51% and in cycle II increase to 77,03%. To reach the goal of the research, theresearcher conducted cycle III which increases to 90,55%. The results achievedexceed the target. In conclusion, environment exploration using magnifying glass asa learning media on pupils of Grade B Kindergarten in PAUD/KB Surya AlamAisyiyah Sawit Boyolali academic year 2018/2019 can improve the languagedevelopment.
Long-Term Robot Navigation in Indoor Environments Estimating Patterns in Traversability Changes

Nowadays, mobile robots are deployed in many indoor environments, such as offices or hospitals. These environments are subject to changes in the traversability that often happen by following repeating patterns. In this paper, we investigate the problem of navigating in such environments over extended periods of time by capturing these patterns and exploiting this knowledge to make informed decisions. Our approach incrementally estimates a model of the traversability changes from robot's observations and uses a probabilistic graphical model to make predictions at currently unobserved locations. In the belief space defined by the predictions, we plan paths that trade off the risk to encounter obstacles and the information gain of visiting unknown locations. We implemented our approach and tested it in different indoor environments. The experiments suggest that in the long run, our approach leads to navigation along shorter paths compared to following a greedy shortest path policy.