Reviewerly/exHarmony huggingface dataset:
Reshaping Crossroads Into a Design Square

The concluding chapter summarizes the culturally localized user engagement and empowerment (CLUE<sup>2</sup>) approach and calls for reshaping the crossroads of global social media design into a design square where a spectrum of thoughts, design traditions, discursive conventions, and epistemological orders converge and interact to spark new ideas. This chapter consists of two parts. The first part reviews the three keywords of the CLUE<sup>2</sup> approach—discursive affordances, technological genres, and local uptakes—and discusses how they serve as an agent for change and transformation in routinized everyday practices on a global cultural circuit. The second part highlights three design and research heuristics for this critical, global approach: articulating practice-based human–technology relations, piecing together fragmented experiences into global processes, and enabling and engaging cultural differences out of positionality and reflexivity. This critical social practice view of the CLUE<sup>2</sup> approach links design and innovation on the global cultural circuit and promotes a relational view of design, contributing to an uprising school for a relational approach of design that comes from multiple disciplines.
AI System Possibly Capable of Surpassing Human Experts in Breast Cancer Prediction

Researchers have yet to determine the optimal use of the AI system, though assessments in the clinical setting indicated that the technology could enhance screening results, potentially identifying breast cancer earlier than the standard of care.
PENGEMBANGAN APLIKASI WEB BERBASIS FLEXBOX UNTUK PENGELOLAAN JADWAL PRODUKSI DAN DOKUMEN DIGITAL MENGGUNAKAN FRAMEWORK BULMA DI PT. GRAMEDIA

PT. Gramedia is the largest printing service provider company in Indonesia. Besides in Jakarta, PT. Gramedia also opened several branches / sites in several regions, namely: Cikarang, Bandung, Surabaya, Medan, Bawen, Bali, Makassar and Palembang. The problem in this research is the process of delivering production schedule information and sending digital documents which are still carried out by production administration officers using fax machines, electronic mail (e-mail) and also messaging applications such as whatsapp. So that the production process at each site can run and well-coordinated applications are needed that can handle the production process and digital documents in PDF format that are needed as supporting information for centralized production. The application made consists of flexbox-based web applications and can be accessed by every user quickly and easily. The Bulma framework is needed so that the web application development process becomes faster and more efficient, because Bulma provides various libraries and web application components needed. The resulting web application can solve the problem of PT. Gramedia, easy to use, has a responsive display with an attractive layout and has compatibility with various mobile devices in use today.
: Scan and Deliver: Bringing the Library to your inbox

How to use the Library's Scan and Deliver service - get journal articles or 10% of a work sent straight to your email
Current Situation and Development Path of Liberal Arts Laboratory in Research Universities

How to construct a liberal arts laboratory in an efficient and orderly manner in research-based universities is of great significance for improving the level of liberal arts in colleges and universities and cultivating compound liberal arts talents. The liberal arts talents of research universities should be research-oriented senior talents with scientific research spirit and practical ability for production, study and research. In view of the current construction of liberal arts laboratories, the hardware level of experimental facilities and equipment is low, the operation mechanism needs to be further optimized, and the openness and utilization rate still need to be improved. The paper proposes the following measures of investing more in laboratories, intensifying the opening up of students, increasing the connotation of laboratories, and introducing the latest technological means, so as to continuously improve the construction and management level of laboratories, and to provide scientific research guarantee for research-based liberal arts talents.
The impact of Logistics Information Sharing and the Mediating Effect of Logistics Performance on Buyer Trust

The purpose of this study is to examine the effect of information sharing and the mediating effect of logistics performance in order accuracy and delivery timeliness on buyer trust. Arguing from social capital theory, logistics and supply chain management literature, seven hypotheses were developed. To test the proposed hypotheses, Smart PLS3 was used to estimate the partial least squares structural equation model (PLS-SEM) from 91 buyer-supplier relationships within the printing industry. The findings revealed that the sharing of logistics information has a positive influence on the accuracy of order, delivery timeliness and buyer trust. Moreover, order accuracy and delivery timeliness have a positive influence on the buyers’ trust in supplier competency. The mediating effect of logistics performance demonstrated that the effect of information sharing on buyer trust is partially mediated by order accuracy and delivery timeliness. Keywords : logistics information sharing, order accuracy, delivery timeliness, trust
Joint Learning of Dictionary and Convolutional Network for Pedestrian Attribute Recognition

Pedestrian attribute recognition is to predict the presence of a set of attributes from a given image, and it plays an important role in video surveillance applications. Most existing works model the task as a multi-label classification problem. Although effective, they ignore the existence of correlations among attributes. In this work, to learn multiple attributes jointly, the attributes are modeled as a subspace and a dictionary is introduced to represent the subspace. Furthermore, to extract the convolutional features which are more suitable for attribute prediction, the dictionary is modeled as a network layer which is learned jointly with the convolutional network. Finally, a novel learning algorithm is proposed to optimize the dictionary and the convolutional network corporately. Extensive experimental analyses and evaluations on two largest pedestrian attribute benchmarks PETA and PA-100K demonstrate that the proposed method achieves state-of-the-art performance.
State policy in the field of education: concept, goals, objectives and the principles

The article talks about state policy in the field of education, analyzes the regulatory framework of Russian education, clarifies the author's understanding of the concept of -state policy in educational activities‖, reveals the principles, goals and objectives of state educational policy in the education system.
Qualitativeness of Consciousness: Genesis of the Problem in Ancient Philosophy

Speaking about the philosophy of mind researchers address the concept of «qualia». In spite of the fact that this term entered the philosophical discourse at the beginning of the 20th century, the legitimacy of its use is still in question. The starting methodological point of the dispute is whether it is necessary to study the quality nature of consciousness separately or we can treat this problem as part of the language description of the functional activity of the brain. One of arguments in favor of the latter point of view is the novelty of the term. The author provides arguments that the problem field of qualia was formed in ancient philosophy. Rethought later as the problem of universals, the idea of the subjectivity of experience accompanies in the history of philosophy the questions related to human consciousness.
Here is the #edu106 syallbus for this ...

Here is the #edu106 syallbus for this semester @scsu: https://docs.google.com/document/d/18xB8YXcLV4oko4kF_LnpZAdNuQE6ztJl-G7zXHgVcyI/edit?usp=sharing wanna check out what students did last semester: https://edu106.jgregorymcverry.com/ looking forward to showing students value
Speaking into a Dead Man’s Ear

What Alexander Graham Bell considered his most important, if least known, invention, the ear phonautograph, was designed to “bring the deaf to speech.” This chapter links Derrida’s suggestion that invention has become production to Marx’s blurring of reproduction-production and to Bell’s eugenics initiatives designed to eliminate reproduction between deaf mutes who, like foreigners, suffered from “broken speech.”
Water-Bottom Video Coding Based on Coding- Oriented Reference Frame Generation

The video contents containing water scenes, such as seashore, water-sports, river-side, waving pool etc. are rich in sensation of presence. From the video coding point of view, those sequences are quite difficult to encode efficiently because of random movement and nonlinear deformation of the objects seen through waving water. This paper aims to tackle this problem by generating one additional frame from input video sequence. We additionally encode the frame and store as longterm reference frame and then encode the input sequence while referring to the additional frame. The key idea of it is to generate as good reference frame as possible in terms of motion compensation accuracy, and hence, in terms of coding efficiency. Our novel approach yielded BD-Rate reduction of 12 to 42% compared to VTM1.1 and 13 to 48% compared to VTM4.0, next generation video coding test model.
LibGuides: Academic Study Skills Offer: Referencing

A short guide to our in-class support sessions Resources and activities to support both APA and Harvard Referencing skills
Research on Education Resource Recommendation Algorithm Based on Implicit Feedback and Pairwise

In view of the problem of how to improve the accuracy of education resources recommendation in Internet era, a recommendation algorithm based on implicit feedback and pairwise education resources are proposed. Firstly, the feature extraction of learner-education resource is carried out, and the implicit features of learner-education resource are extracted by implicit semantic model, and the prediction results of factor decomposition are used as input to sorting learning algorithm. Converting sorting problems to classification problems uses the theory of ordering learning. Based on the experiment comparison with the traditional recommendation algorithm, it is compared with the comparison algorithm, which has better effect on the recommendation of educational resources. The algorithm increases by nearly 30% on metrics MAP, NDGG.
SISTEM PAKAR MENDIAGNOSA PENYAKIT HEWAN TERNAK KAMBING DENGAN MENGGUNAKAN METODE CERTAINTY FACTOR

Expert systems are systems that try to adopt human knowledge into computers, so that computers can solve problems as is usually done by experts. Expert system is a computer program that simulates the judgment and behavior of humans or organizations that have expert knowledge and experience in a particular field. In an expert system has many algorithms, one of which is the intelligence factor. Certainty Factor states trust in an event in accordance with the evidence and judgment of an expert. This method uses a value in assuming an expert's degree of confidence in the data. The design of goat disease diagnosis application is made to be useful for users / breeders, which is to make it easier to get information by using the application as a consultation media.
Towards optimize-ESA for text semantic similarity: A case study of biomedical text

Explicit Semantic Analysis (ESA) is an approach to measure the semantic relatedness between terms or documents based on similarities to documents of a references corpus usually Wikipedia. ESA usage has received tremendous attention in the field of natural language processing NLP and information retrieval. However, ESA utilizes a huge Wikipedia index matrix in its interpretation by multiplying a large matrix by a term vector to produce a high-dimensional vector. Consequently, the ESA process is too expensive in interpretation and similarity steps. Therefore, the efficiency of ESA will slow down because we lose a lot of time in unnecessary operations. This paper propose enhancements to ESA called optimize-ESA that reduce the dimension at the interpretation stage by computing the semantic similarity in a specific domain. The experimental results show clearly that our method correlates much better with human judgement than the full version ESA approach.
FAULT DATA DETECTION IN SOFTWARE USING A NOVEL FGRNN ALGORITHM

The use and dependence on software in various fields has been the reason why researchers for past decades have spent their efforts on finding better methods to predict software quality and reliability.Soft computing methods have been used to bring efficient improvement in prediction of software reliability.This study proposed a novel method called Fuzzy Greedy Recurrent Neural Network (FGRNN) to assess software reliability by detecting the faults in the software.A deep learning model based on the Recurrent Neural Network (RNN) has been used to predict the number of faults in software.The proposed model consists of four modules.The first module, attribute selection pre-processing, selects the relevant attributes and improves generalization that improves the prediction on unknown data.Second module called, Fuzzy conversion using membership function, smoothly collects the linear sub-dels, mo joined together to provide results.Next, Greedy selection deals with the attribute subset selection problem.Finally, RNN technique is used to predict software failure using previously recorded failure data.To attest the performance of the software, the popular NASA Metric Data Program datasets are used.Experimental results show that the proposed FGRNN model has better performance in reliability prediction compared with existing other parameter based and NN based models.
Simulation Study to Describe Bayesian Analysis of Nonlinear Structural Equation Modeling

Structural equation modeling (SEM) has widely used in many disciplines, such as economic, politic or health.Nonlinear structural equation modeling, as part of SEM, also has been developing analytically but still limited.In this method, the parameter models are estimated using conjugate prior in Bayesian approach.In nonlinear SEM, the models are specified including quadratic forms and/or interactions of latent variables.Posterior mean and posterior variance of the parameters are estimated using iteration approach since it is difficult to estimate those parameters model using analytical approach.The iteration approach used here is Markov Chain Monte Carlo (MCMC) method with Gibbs sampling.The simulation study is done to illustrate the proposed estimation methods for nonlinear model.A group of 300 data are generated to demonstrate the implementation of the proposed method.This study resulted that the proposed nonlinear SEM model could be accepted based on criteria of goodness of fit model.
Language processing and language acquisition through the lens of Relational Morphology

This chapter asks what is happening to linguistic representations during language use, and how representations are formed in the course of language acquisition. It is shown how Relational Morphology’s theory of representations can be directly embedded into models of processing and acquisition. Central is that the lexicon, complete with schemas and relational links, constitutes the long-term memory network that supports language production and comprehension. The chapter first discusses processing: the nature of working memory; promiscuous (opportunistic) processing; spreading activation; priming; probabilistic parsing; the balance between storage and computation in recognizing morphologically complex words; and the role of relational links and schemas in word retrieval. It then turns to acquisition, which is to be thought of as adding nodes and relational links to the lexical network. The general approach is based on the Propose but Verify procedure of Trueswell et al. (2013), plus conservative generalization, as in usage-based approaches.
THE POLITICAL DISCOURSE – AN INSTRUMENT OF THE POWER RELATION BETWEEN THE SPEAKER AND THE PUBLIC

The present paper is focused on the features of political discourse as a tool of power. Within it, we are interested in emphasizing the mechanisms that link the identitary component of the relation between the speaker and his public, on one hand, with the power relation emerged among the same communicators, on the other hand. Moreover, such mechanisms involve a certain attitude of the orator regarding the concept of truth, which in rhetorics is understood in a particular way which is centered on the concept of persuasion
Discovery Learning with Jigsaw II on Information Literacy and Cognitive Learning Outcomes of High School Students

Abstract : This study aimed to determine the effect of the discovery learning model combined with Jig-saw II on the students’ information literacy and cognitive learning outcomes. The study was a quasi-experimental with a non-equivalent control group design. The subjects were 134 high school students divided into one group given discovery learning model combined with Jigsaw II and 3 control groups given discovery learning, Jigsaw II, or conventional learning model. The experiment showed that the discovery learning model combined with Jigsaw II resulting in significant differences in students’ information literacy and cognitive learning outcomes with Fvalue = 13.935 (p < 0.05) on information literacy F value = 6.527 (p < 0.05) on cognitive learning outcomes. It can be concluded that the discovery learning model combined with Jigsaw II significantly improved students’ information literacy and cognitive learning outcomes. Key Words : discovery learning, jigsaw II, information literacy, cognitive learning outcomes Abstrak : Penelitian ini bertujuan untuk mengetahui pengaruh model pembelajaran discovery learning dipadu Jigsaw II terhadap literasi informasi dan hasil belajar kognitif. Penelitian merupakan penelitian eksperimen semu dengan desain nonequivalent control group design. Subjek yang digunakan yaitu siswa SMA sebanyak 134 siswa. Hasil penelitian menunjukkan nilai F sebesar 13,935 dan taraf signifikan sebesar 0,000<0,05 pada literasi informasi dan F sebesar 6,527 dan taraf signifikan sebesar 0,000<0,05 pada hasil belajar kognitif. Hal ini dapat disimpulkan bahwa ada perbedaan signifikan literasi informasi dan hasil belajar kognitif siswa yang menjalani model pembelajaran discovery learning dipadu Jigsaw II. Kata kunci : discovery learning, jigsaw II, literasi informasi, hasil belajar kognitif
The development of digital education in the Russian Federation

The article discusses the foreign and Russian experience of digitalization of education, shows approaches to creating a model of a digital educational platform, touches on the interaction of the digital economy and education.
Data Mining Techniques – A Study

Data mining is the technique of hidden, valid, and potentially useful patterns in huge data sets. Data Mining is all about discovering the previously unknown relationships amongst the data. It is a multi-disciplinary method that uses Machine Learning, Statistics, AI and Database Technologies. Data mining is also called as Knowledge Discovery, Knowledge Extraction, Data analysis, Information harvesting, etc. Data mining can able to handle the various types of data like Relational databases, Data warehouses, Object-Oriented and Object-Relational databases, Transactional and Spatial databases, Text mining and Web mining. This paper describes and discusses the various techniques associated with Data Mining Process.
Research Guides: AR/VR/MR Community of Practice: Research

This guide is a tool for locating educational resources and other general information to support the Community of Practice in AR/VR/MR at the University at Buffalo, SUNY. Citations of publications focusing on research in AR/VR/MR
On Chinese Cultural Subjectivity Regarding Exemplary and Narrative Language: Based on Ricoeur’s Research of Narrative

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A Preliminary Study on the Mixed Learning Mode of Public English in Higher Vocational Colleges under the Interactive English Platform

&lt;p&gt;In the past in the higher vocational education the entity class teaching mode is generally adopted in the process of public English teaching, in recent years due to the rapid development of Internet information technology and the emergence of multimedia teaching methods, to gradually change the traditional English teaching mode to entity class teaching and online mutual combination of Internet teaching. This new hybrid English teaching method has both the advantages of physical classroom teaching and the new advantages of online learning. It is a brand-new way of learning English. Interactive English platform is a new model of this new way of learning English. This paper will take this platform as an example and focus on the methods of learning public English in colleges and universities.&lt;/p&gt;
Identifying and Pruning Redundant Structures for Deep Neural Networks

Deep convolutional neural networks have achieved considerable success in the field of computer vision. However, it is difficult to deploy state-of-the-art models on resource-constrained platforms due to their high storage, memory bandwidth, and computational costs. In this paper, we propose a structured pruning method which employs a three-step process to reduce the resource consumption of neural networks. First, we train an initial network on the training set and evaluate it on the validation set. Next, we introduce an iterative pruning and fine-tuning algorithm to identify and prune redundant structures, which results in a pruned network with a compact architecture. Finally, we train the pruned network from scratch on both the training set and validation set to obtain the final accuracy on the test set. In the experiments, our pruning method significantly reduces the model size (by 87.2% on CIFAR-10), saves inference time (53.3% on CIFAR-10), and achieves better performance as compared to recent state-of-the-art methods.
Micro-blog User Profiling: A Supervised Clustering based Approach for Age and Gender Classification

User profiling is the process of tagging user attributes, such as gender, age, location and so on. Currently the popular way is to do classification by treating attributes as labels. In addition, ensemble classifications are used to future improve classification quality. However, the base classifier of traditional ensemble classification is trained by using random sampling, which cannot guarantee a constantly good classification performance. This paper proposes a supervised clustering of ensemble classification approach to tag micro-blog users with age and gender attributes. The proposed approach is to divide the training data with a same label into multiple clusters and then combine different clusters from training data with different labels into training data subsets. Each subset is used to train a base classifier. Experimental results show that the proposed approach can improve the gender and age classification accuracy classification by 1.79 % and 0.67 % respectively, compared with the traditional ensemble classification approach.