Reviewerly/exHarmony huggingface dataset:
Beyond photon pairs: Nanophotonic photon number difference squeezing

We demonstrate over 1 dB of photon number difference correlations from two-mode squeezed states having mean photon number above 5, generated with a silicon nitride ring resonator and measured using photon number-resolving transition edge sensors. © 2019 The Author(s)
LibGuides: Human Library Event: 2020 Event "Books"

Everything you need to know about the human library! Find information about what a human library is, what human books are, and how to participate as a reader.
High-Speed Photodetection and Microwave Generation in a Sub-100 mK Environment

We perform microwave generation via high-speed photodetection at a temperature of 20 mK. Shot noise-limited detection with high linearity was obtained, compatible with continued scaling of the control and readout of superconducting quantum information systems.© 2019 The Author(s)
Data Breach Impacts on Companies and Their Consumers.

This paper will describe a data breach and how they impact the company and consumers involved. Statistics will be provided on the financial impact of a data breach to a company. Three recent data breach examples will be given along with a description of what personal identifiable information was compromised. I will also describe steps companies and consumers can take to mitigate the risk involved related to personal identifiable information.
LibGuides: Beaver Basics: Google Docs

Jump start your academic success with mini workshops and consultations for doc, presentation, and spreadsheet tips
JURNALISME GAME DAN MEMBAURNYA KARAKTER KONTEN MEDIA Studi Kasus the Lazy Monday, Gamebrott dan Playverse

Game journalism develops along with the development of the gaming industry, increasingly sophisticated information and communication technology, as well as increasingly convergent institutionalization of new media. The purpose of this research is to understand game specialist journalism and blend the study of content production. The research method used is a case study with a constructionist perspective. Data collected through interview, content review, and literature review related to journalism, games, and the media industry. The mixed character of the media content in game news is, among others, reviewed through media institutions, media practices, namely: planning, management, production and distribution, and through dimensions in journalism. To cite this article (7th APA style): Adiputra, W. M. (2018). Jurnalisme Game dan Membaurnya Konten Media: Studi Kasus the Lazy Monday, Gamebrott dan Playverse [Game Journalism and the Immersion of the Media Content Character]. Journal Communication Spectrum, 8(2), 166-189. http://dx.doi.org/10.36782/jcs.v8i2.1853
Defining and Prioritizing Software Requirement Using gIBIS and AHP Method

Requirement engineering is an important process in a software development project.During the process there are two activities that are very significant that determine the success of the software development: requirement definition and requirement prioritization.Through this process we can set the scope of the software product and the limitations of product features for each released version.Defining and prioritizing requirements can be done using same approach.gIBIS (graphical Issue-Based Information System) is a proposed approach for the design rationale to describe the reasoning process for the solution that is chosen in order to answer a problem or issue.The graphical representation of the reasoning process using gIBIS can be supported by tools such as Compendium.This paper proposes the implementation of the gIBIS approach in defining software requirements by assigning a score for each alternative and selecting the highest score as a solution.The approach is combined with AHP (Analytical Hierarchical Process) method to set the priority and as the result we can determine the software requirements and also rank the requirements based on its priority.The criteria used in setting the priority include cost, risk, difficulty and stability.The proposed approach (combining of gIBIS and AHP) is demonstrated with a case study of prioritizing requirements for a website development of "IndoSoccerSchool".The result show that the proposed approach can help us generate a list of requirements and give them a score based on priority and the list can give a reference for developing the software based on credible priorities and then manage the software release.
Analysis on a multimodal text

This paper analyzes the contribution of factors other than language such as images, font size and shape, colors, layout, etc, in understanding four features: 1) the information genre, 2) the experiential meaning on science topic, 3) the interpersonal meaning associated with the subjective and objective relationship between the author and readers, and 4) the textual meaning on the logical meaning of the text. For this analysis, a scientific information text (one of the multimodal texts) describing the sun is used. The analysis shows that the multimodal text contributes to the readability of the text through harmonization - i.e., harmonizing the language with the use of semiotic resources aside from the language itself. This paper is meaningful in that it analyzed how semiotic elements can be in harmony with language to increase readability in the situation where the research on the multimodal text has hardly been conducted. (Jeju National University)
Steganography Based Asymmetric Key Cryptosystem Using Trellis Coded Genetic Algorithm Random Key Generator

Steganography Based Asymmetric Key Cryptosystem Using Trellis Coded Genetic Algorithm Random Key Generator
Dissecting Graph Neural Networks on Graph Classification

Graph Neural Nets (GNNs) have received increasing attentions, partially due to their superior performance in many node and graph classification tasks. However, there is a lack of understanding on what they are learning and how sophisticated the learned graph functions are. In this work, we propose a dissection of GNNs on graph classification into two parts: 1) the graph filtering, where graph-based neighbor aggregations are performed, and 2) the set function, where a set of hidden node features are composed for prediction. To study the importance of both parts, we propose to linearize them separately. We first linearize the graph filtering function, resulting Graph Feature Network (GFN), which is a simple lightweight neural net defined on a \textit{set} of graph augmented features. Further linearization of GFN's set function results in Graph Linear Network (GLN), which is a linear function. Empirically we perform evaluations on common graph classification benchmarks. To our surprise, we find that, despite the simplification, GFN could match or exceed the best accuracies produced by recently proposed GNNs (with a fraction of computation cost), while GLN underperforms significantly. Our results demonstrate the importance of non-linear set function, and suggest that linear graph filtering with non-linear set function is an efficient and powerful scheme for modeling existing graph classification benchmarks.
An Analysis Of PQRST Strategy in Reading Comprehension on Descriptive Text in Fifth Semester Students at English Department of UIN Antasari Banjarmasin

PQRST Strategy is the kind of strategies for teaching reading. PQRST Strategy stands for Previewing, Questioning, Read, Summarizing and Test. The Research questions of this research are: How the implementaion of PQRST strategy in reading comprehension on descriptive text in fifth semester students at English Department of UIN Antasari Banjarmasin, what are students’ opinion PQRST strategy. This research is field research which the data is analyzed qualitatively. The subject of this research is 30 students from English Department of UIN Antasari Banjarmasin who was taken from 5 classes. In each class the researrcher took 6 students. To collect the data, the researcher uses some techniques such as observation, test and interview. The result of this research showed that the implementation of PQRST strategy is helpful for students in finding main idea, referent, synonym and antonym on descriptive text. The students’ opinion of PQRST strategy is 99% said the PQRST strategy is good used by lecturer and students in Reading Comprehension class, because PQRST strategy has the steps that can help students in Reading class and 1% said the strategy is not good used by lecturer and students, because PQRST strategy is not appropriate used by students who have weak in reading skill.
How Nature Computes: Reconciliation with Standard Model (Part 2)

Physicists reduce data, discover fundamentals and write computer models but to understand nature we must understand how it produces itself. Many believe that everything consists of wave functions. Are they producing nature similar to the way computers use information to produce a result? This paper explores how the neutron and proton compute information about energy. The Standard model is accepted as a summary of nature’s particles and fields but the purpose of its variations need explanation. I believe the neutron/proton models are the source of nature’s laws and their Schrodinger based wave functions produce quantum entities underlying the Standard model’s color forces and quarks. Sub-components of neutron/proton field wave functions define dimensions, space, time, gravity and other properties. The possibility that algorithms in the wave functions allow nature to produce other features was examined. For example, can they compute fusion binding energy or expansion of the universe? Part 2 of this two-part article includes: Measured properties of Neutron and Protons; Summary; and Appendices.
Contrast Enhancement of Digital Image using Artificial Bee Colony Optimization

Image contrast enhancement is aim to enhance the contrast level of images, which are degraded during acquisition process. In this paper the contrast enhancement of image has been taken as an optimization problem and artificial bee colony (ABC) algorithm has been used here to solve the optimization problem. The work has been done in two phase, in the 1st phase a fitness function has been proposed to evaluate the quality of the enhanced image where as in the 2nd phase is to generate new pixel intensities for the enhanced image from the original input image. Artificial bee colony technique is used to optimized the searching parameter. Experimental analysis has been drawn and the result has been presented to support the proposed method.
An Assessment of the Language Learning Attitudes, Learning Strategies, Language Proficiency of First Year College Students

This descriptive-correlational research described the Language Learning Attitudes (LLA), Language Learning Strategies (LLS) and Language Proficiency (LP) of 120 college students from 4 courses. It employed Lunsford's Standardized LLA Questionnaire, Oxford's (1994) Strategy Inventory of Language Learning (SILL); and Reading Proficiency Test. It used mean, standard deviation, Pearson r, Multiple Regressions, t-Test of significant difference, and One-Way ANOVA for treatment of data. This study found out that students are Average in LLA; "Somewhat true of me" in LLS and Poor in reading proficiency. No significant relationship between respondents' LLA and reading proficiency; Very low correlation between respondents' LLS and reading proficiency; Sex and course do not affect students' LLA and do not influence the latter's contribution on reading proficiency except for the inferential level; and Sex does not influence respondents' LLS and reading proficiency except course. This study hardly provides empirical data to support the theories in LLA and LLS which are supposed to have a significant role in affecting students' reading proficiency. It also denies the role of schema theory in reading by activating learners' prior knowledge to process meaning and concepts from the reading selections. Variable course may seem to provide empirical support to the extension of the theories in LLS as well as schema theory in reading.
Faktor-faktor yang Mempengaruhi Upaya Penanganan Pra Bencana Kebakaran di Tingkat Komunitas Studi Kasus pada Masyarakat RW 02, Kelurahan Karang Anyar, Kecamatan Sawah Besar, Jakarta Pusat

This research discusses about a pre-fire disaster reinforcement effort which is held by the community of RW 02 at Kelurahan Karang Anyar as a vulnerable community in fire disaster. The Pre-Fire Disaster Reinforcement Effort which is discussed in this research are mitigation and preparedness. This research uses descriptive approach and qualitative method of a case study type. The research result shows that an effort in pre-fire disaster reinforcement are continuously conducted by kelurahan governance, fire department, informal leaders, and community itself. The effort are consist of a risk reduction either structural or non structural and improvement of the alert with the influences from economic factor, social, cultural, and physic. Every factors give a different influence to each stakeholder which is participate in it
Wireless Ultrasonic Auto Navigation Robot for Agriculture

At present, the machinery and their effortlessness are incredibly essential things that compose our lives full of expediency.They can also be enhanced for employ in sensitive sites that cause a threat to the human being.In general a group of people who are involved in agricultural.There are various difficulties they face throughout their works.Naturally, the agriculture land is very complex to reach some of the places we are in.This study makes it easy to use a Wireless Ultrasonic Auto Navigation Robot (Wireless UAN Robot) to diminish the risk of injuries that might occur while walking or by car.The modern robot consists of a custom-made structure with a circular shape that is competent to navigate easily in most hazardous places and rotate in rigid spaces.
Ethical things: designing ethical technologies

We are researching how developers of connected technologies make ethical decisions during their product design and development processes.
Enriching folksonomy for online videos

We propose a method that enriches folksonomy by using user comments on online videos. Folksonomy is a process in which users tag videos so that they can be searched for easily. On some videos, users can post tags and comments. A tag corresponds to folksonomy. One such online sharing website is Nico Nico Douga; however, users cannot post more than 12 tags on a video. Therefore, there are some important tags that could be posted but are sometimes not. We present a method for acquiring some of these missing tags by choosing new tags that score well in a scoring method developed by us. The method is based on information theory and a novel algorithm for estimating new tags by using distributed databases constructed by us.
Reduksi Kadar Besi Dalam Air Sumur di Lingkungan Universitas Muhammadiyah Surakarta dengan Filter

Iron was silvery white, clay, and can be formed. it was usually obtained as hematite in nature. Iron was a chemical element that could be found in almost all places on the face of the earth, in all parts of the geological layer, and all bodies of water. In surface water, Fe was rarely found more than 1 mg / L, but in the water, Fe content could be much higher. When it accumulated in the body, iron could cause health problems, such as skin irritation, respiratory problems, and cause cancer in a long time. This study aims to determine the reduction of iron content in well water at the Universitas Muhammadiyah Surakarta (UMS) using the Spectrophotometry method with phenanthroline reagents. The samples were taken as many as five points in three different regions, namely Tanuragan (near the river), Menco and Nilasari (dense settlements), and Gonilan (near the rice fields) showed positive results containing iron with the highest levels in the sample without filtering at 9,478 ppm. These levels decreased after filtration using four filters, namely filters made of carbon, cotton, foam, carbon three layers in each sample. The iron content reduction was best to use cotton filters with 100% reduction in percent.
Big Data Platform Access Control Rule Generation Method Based on Data Mining

The access control problem of big data platform is related to personal privacy, corporate interests and national security. In the context of big data platform, the fine-grained permission relationship between users and resources is difficult to be explored through the experience of administrators, and the permission granularity is difficult to be refined. In this paper, we propose an access control rule generation method based on data mining. By selecting appropriate data preprocessing, clustering analysis, association analysis algorithms and improving them, we dig out the normal access behavior rules of users from the user logs and attributes, and generate fine-grained control rules based on these rules, and improve the accuracy through negative feedback regulation. The experiment results verify the effectiveness and practicability of the method which can provide accurate access control for the big data platform.
PENGEMBAGAN MEDIA PEMBELAJARAN SEJARAH APLIKASI ANDROID BERBASIS ANDROMO UNTUK MENINGKATKAN MOTIVASI BELAJAR SISWA KELAS XI APL I SMK MUHAMMADIYAH 3 SINGOSARI

RINGKASAN This study aims to overcome the problems of student motivation in the XI APL I class of Muhammadiyah 3 Singosari, in this study the researchers made products in the form of historical learning media on andromo-based android applications, which will be used to overcome students' motivational problems, for data used in this research is qualitative data from interview results and quantative data from the results of the product feasibility questionnaire. From this study, it was found that the use of historical learning media with andromo-based android applications can overcome students' motivation problems in class XI APL I of Muhammadiyah 3 singosari, Normal 0 false false false IN X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable{mso-style-name:Table Normal;mso-tstyle-rowband-size:0;mso-tstyle-colband-size:0;mso-style-noshow:yes;mso-style-priority:99;mso-style-qformat:yes;mso-style-parent:;mso-padding-alt:0cm 5.4pt 0cm 5.4pt;mso-para-margin-top:0cm;mso-para-margin-right:0cm;mso-para-margin-bottom:10.0pt;mso-para-margin-left:0cm;line-height:115%;mso-pagination:widow-orphan;font-size:11.0pt;font-family:Calibri,sans-serif;mso-ascii-font-family:Calibri;mso-ascii-theme-font:minor-latin;mso-fareast-font-family:Times New Roman;mso-fareast-theme-font:minor-fareast;mso-hansi-font-family:Calibri;mso-hansi-theme-font:minor-latin;mso-bidi-font-family:Times New Roman;mso-bidi-theme-font:minor-bidi;}
Evaluation of Deep Clustering for Diarization of Aphasic Speech.

Speaker attribution and labeling of single channel, multi speaker audio files is an area of active research, since the underlying problems have not been solved satisfactorily yet. This especially holds true for non-standard voices and speech, such as children and impaired speakers. Being able to perform speaker labelling of pathological speech would potentially enable the development of computer assisted diagnosis and treatment systems and is thus a desirable research goal. In this manuscript we investigate on the applicability of embeddings of audio signals, in the form of time and frequency-band based segments, into arbitrary vector spaces on diarization of pathological speech. We focus on modifying an existing embedding estimator such that it can be used for diarization. This is mainly done via clustering the time and frequency band dependant vectors and subsequently performing a majority vote procedure on all frequency dependent vectors of the same time segment to assign a speaker label. The result is evaluated on recordings of interviews of aphasia patients and language therapists. We demonstrate general applicability, with error rates that are close to what has been previously achieved in diarizing children's speech. Additionally, we propose to enhance the processing pipelines with smoothing and a more sophisticated, energy based, voting scheme.
Enriching User Representation in Neural Matrix Factorization

Personalized recommendation is a crucial problem in the era of information overload. One of the most prominent methods addressing this problem is collaborative filtering (CF). Recently, NeuMF [1] has employed Deep Neural Network to facilitate traditional CF methods. Although NeuMF achieved the state-of-the-art performance, it is expected that predictive accuracy can be improved by enriching user representation. In this paper, we propose a neural network incorporating latent features and personalized information of users, namely Feature based Neural Matrix Factorization (FeaNMF). In FeaNMF, personalized information can be considered as auxiliary features which are generated by associating past behavior of users (e.g, purchase history, browsing activity, watching habits) with item categories. By explicitly modeling personalized information in the metric of item categories, the major advantages of FeaNMF are: (1) it enriches user representation and thus enhances the predictive capability, (2) it inherits the advantages of NeuMF to model the latent features in a more comprehensive approach, rather than applying a simple linear function as existing methods (e.g. Matrix Factorization), and (3) it is easy to extend FeaNMF for employing a large amount of external sources to construct user preferences. Experiments show that our model significantly improves predictive accuracy compared to the three previous approaches including NeuMF.
On the Research and Construction Path of Informationization Teaching Mode of College English

The purpose of the current research was to emphasis the importance of informationization teaching mode of college English. Based on the basic principles of constructivism, the challenges for traditional English teaching mode, relationship between teacher and leaners as well as the curriculum and evaluation methods are discussed. The paper presents two typical informationization teaching modes of college English which are successfully motivate the effectiveness of teaching and learning as well as cultivate the intellectual potential to improve the comprehensive quality levels of students with various teaching contents and vivid teaching modes.
Kontribusi Motivasi Belajar, Bahan Ajar dan Lingkungan Belajar Terhadap Hasil Belajar Matematika Siswa Kelas VIII SMP N 2 Karangmalang Tahun Ajaran 2018/2019

AbstrackThe purpose of research to 1) examine the contribution of learning motivation to mathematics learning outcomes, 2) examine the contribution of teaching materials to mathematics learning outcomes, 3) examine the contribution of the learning environment to mathematics learning outcomes, 4) examine the contribution of learning motivation, teaching materials and learning environment to mathematics learning outcomes. This type of research is quantitative with a correlational research design. The population in this research were all VIII grade students of SMP N 2 Karangmalang with a sample of 152 students. Data collection in this research uses questionnaires and documentation. Data analysis techniques using regression tests. The results of this study indicate that 1) learning motivation contributes directly to learning outcomes, 2) instructional materials contribute directly to learning outcomes, 3) learning environments contribute directly to learning outcomes, 4) motivation to learn, teaching materials and learning environments simultaneously contribute directly to learning outcomes. Keywords: learning motivation, teaching materials, learning environment, learning outcomes