Reviewerly/exHarmony huggingface dataset:
Validación del Approaches and Study Skills Inventory for Students (ASSIST) en Universitarios de Buenos Aires, Argentina

espanolLos enfoques de aprendizaje permiten conocer las preferencias que manifiestan las personas para enfrentar una tarea de aprendizaje especifica. Una de las herramientas mas difundidas para evaluar los enfoques de aprendizaje es el Approaches and Study Skills Inventory for Students (ASSIST), que en su version abreviada permite valorar mediante 18 items tres enfoques de aprendizaje (Profundo, Superficial, Estrategico). Dada la importancia que este instrumento tiene para evaluar los enfoques de aprendizaje en estudiantes universitarios, el objetivo de esta investigacion es validar la version espanola para el contexto argentino. Para ello se adecuo primero linguisticamente el inventario a los modismos locales, para luego examinar evidencias de validez de constructo (analisis factorial exploratorio, confirmatorio, e invarianza factorial) y evidencias de validez concurrente. Tambien se estudio la confiabilidad del instrumento mediante el analisis de consistencia interna. Se obtuvo una herramienta compuesta de 14 reactivos que posibilita evaluar los enfoques de aprendizaje Profundo, Superficial y Estrategico propuestos por la teoria. El modelo resultante de los procedimientos exploratorio y confirmatorio exhibio una adecuada invarianza factorial, y las dimensiones del inventario presentaron indices de consistencia interna superiores a .80. Ademas se obtuvieron evidencias de validez concurrente coherentes con la teoria y con resultados empiricos previos. EnglishThe study of approaches to learning enables the description of preferences manifested when facing a specific learning task. One of the most widespread instruments for assessing learning approaches is the Approaches and Study Skills Inventory for Students (ASSIST). In its short version of 18 items, the ASSIST measures three learning approaches (Deep, Surface and Strategic). Given that the availability of this instrument would be of great value and needed to research learning approaches in college students, the objective of this research was to develop an Argentinean version. To meet this end, the inventory underwent an initial linguistic adaptation to the local forms of expression and idioms. Then, construct validity was examined (exploratory and confirmatory factorial analysis, and factorial invariance) together with analyses of concurrent validity. Reliability was examined by means of analyses of internal consistency. The resulting 14-item instrument may be used to describe approaches to learning as proposed by the theory: Deep, Superficial and Strategic. The measure obtained by exploratory and confirmatory procedures showed an adequate factorial invariance. The dimensions of the inventory had internal consistency indexes greater than .80. Finally, evidences of concurrent validity were coherent with the theory and with previous empirical results.
Veriﬁable Data Streaming via Noncryptographic Approach

We propose a novel solution for veriﬁable data streaming via noncryptographic approach (NAVDS). Our proposed NAVDS is featured by its execution performance, compared to the existing solutions with signiﬁcant computation burden on both client and server sides.
A descrição de marginália em obras especiais e raras

It presents findings of the research on how Brazilian libraries record marginalia, or handwritten notes, contained in special and rare works, in their online public access catalogs (OPACs). It is applied research, with qualitative approach and exploratory objectives. It discusses the importance of bibliological analysis in this context and reveals that there is no standard for recording in the 14 OPACs investigated. In general, as libraries do not describe the attributes of this type of notes, as well as annotator identification, note type, publication location, brand type, quantity, among other details that help to qualify information in a bibliographic record.
The important of typography in publication / Nur Eirza Khairunnisa Mohd Rezan

Typography plays an integral part in design and publication. In the modern era. the audience is aware of typography. design and others. Typography is used as a more extensive conversation to global visual culture, and the audience starts to increasingly aware of the effects of visual design. Typography is used as letter design in print or digital media. Also bring definition to giving text form and its sense of wonder, (Danielle, 2014). The unique font would add character and relate to the body text, and the reader may notice the typeface faster. Typography is often used to attract the reader. Usually. the reader is quickly drawn to something new, unique and not commonly seen. The typeface was category under typography. There is a different type of typeface and typeface gives a fresh font and a new look. In education publication, typography is essential to attract the reader to continue reading and also grab reader attention so that the reader will not be bored. Typography is essential to keep the reader being interested in learning education publication. There are six different typeface sorting, that is a serif, San-serif - mono spaced, cursive, fantasy, and script. The most commonly used is serif and San-serif. Education publication can be more interested in having an exciting info graphic and fonts (Nathan, 2014)
Free Speech and the Embodied Self

Democratic theories of free speech hold that the right to free speech is grounded in the nature of collective self-governance. The legitimacy of imposing laws on those who disagree with them depends on giving all citizens an equal right to participate in the lawmaking process, including the right to express their opposition. Ronald Dworkin argues that views of this kind are in tension with hate speech regulation. If we forbid the expression of prejudice, we undermine the legitimacy of laws protecting minority groups. The aim in this chapter is to diffuse the tension Dworkin sees between a democratic justification of the right to free speech and hate speech regulation. This is done by developing an account of how our bodily rights constrain the right to free speech.
ACTION RECOGNITION FROM TIME SERIES GEOMETRIC JOINT FEATURES ON LSTM NETWORK

Convolutional neural networks (CNN) have shown evidences of reliability on action recognition tasks. However, their ability has been limited to correctly decoding spatial data. Moreover, the action data exhibits a spatio temporal characteristics in real time. To this effect, recurrent neural networks (RNNs) had been successful in reconstructing temporal data from action sequences. Despite their strong reputation, RNNs fall short in decoding long sequences of data, which are part of real actions. Consequently, this problem is effectively solvable by Long Short-Term Memory (LSTM) networks. In this work, LSTMs are used to measure the relatively between action sequences that can impact positively in recognition. Specifically, we select geometric patterns drawn from skeletal time series data for experimentation on 3-layer LSTM network and achieved better results than CNNs and RNNs. We demonstrate this on skeletal data by using four challenging benchmark skeletal action datasets.
Study on the Selection of Words in College English Writing

Selection of words is an important part in college English writing. A perfect writing largely depends on the right choice of words. By means of a writing test and a questionnaire, a survey was carried out upon 100 freshmen with non-English majors from two classes to investigate the challenges of the selection of words in writing. The findings indicate that students have major difficulties in spelling, meaning conveying, concise expressing, style of words, and so on. Thus, the study puts forward some effective methods in lexical, grammatical and stylistic aspects to improve the selection of words. Furthermore, the researcher attains valuable reflection on the teaching of college English writing. The reflection includes the cultivation of students’ writing accomplishment and writing interest, the adoption of flexible teaching methods in writing class, and effective use of online writing platforms. Finally, an interview with 35 respondents has proved the teaching effect. So the study can be implemented by students and teachers to enhance the learning and teaching of English writing.
An Enhanced Content Based Image Retrieval in Cloud Computing with Privacy Towards EMD

Content Based Image Retrieval (CBIR) aims the system to compel the recovery of pictures from a very large store of collected pictures. The recovered picture approaches shading, color, texture and size. In this paper, a privacy saving substance based on picture recovery computes by utilizing Earth Moveable Distance (EMD) which is proposed because of the administrations of information proprietor to reappropriate picture from the database that is powerfully accessible in the cloud without extracting the entire substance from the database that should be given to the client's precise query. The proposed scheme supports the neighborhood highlight based CBIR with EMD as closeness metric. The EMD matches perceptual similarity for substance based picture recovery. It is additionally dependent on transportation issue from straight improvement, for which proficient calculations are accessible and to get comparability metric effectively. The sensitive (LSH) Local Sensitive Hash is improved for search efficiency. We look at the recovery execution of EMD and examine the protection and security of pictures dependent on client query.
Personal README Files: User Manuals for Library Staff

Presentation given at the Designing for Digital Conference in Austin, Texas, on Monday, March 9, 2020.
A Lightweight Fully Homomorphic Encryption Scheme for Cloud Security

A decade ago, fully homomorphic encryption mechanism came as a great breakthrough in security. In homomorphic encryption, ciphertext (data in encrypted format) should be sent to the cloud, the computations are made on the ciphertext, and the result of this computation is a ciphertext form itself. If the result of the computation is decrypted, then the correct plaintext result must be obtained. Maintaining the secrecy and privacy of data, generally in cloud scenario, has become an intense challenge for present day's practical applications. However, transferring private data to any third party consists of large amount risks of disclosure of private data while computation. This problem can be addressed by performing computations on encrypted data without decrypting it. In this paper, we propose a fully homomorphic encryption framework which is lightweight in nature and utilising symmetric key. Analysis of the scheme confirms that our proposed system is efficient and practical to adopt it in various cloud computation applications. Further, to prove the novelty, we present the implementation results and given the comparative analysis of our scheme with significant state-of-the-art.
On the Metrics and Adaptation Methods for Domain Divergences of sEMG-based Gesture Recognition

We propose a new metric to measure domain divergence and a new domain adaptation method for time-series classification. The metric belongs to the class of probability distributions-based metrics, is transductive, and does not assume the presence of source data samples. The 2-stage method utilizes an improved autoregressive, RNN-based architecture with deep/non-linear transformation. We assess our metric and the performance of our model in the context of sEMG/EMG-based gesture recognition under inter-session and inter-subject domain shifts.
Introducing Scene Understanding to Person Re-Identification using a Spatio-Temporal Multi-Camera Model

In this paper, we investigate person re-identification (re-ID) in a multi-camera network for surveillance applications. To this end, we create a Spatio-Temporal Multi-Camera model (ST-MC model), which exploits statistical data on a person&#x2019;s entry/exit points in the multi-camera network, to predict in which camera view a person will re-appear. The created ST-MC model is used as a novel extension to the Multiple Granularity Network (MGN) [1], which is the current state of the art in person re-ID. Compared to existing approaches that are solely based on Convolutional Neural Networks (CNNs), our approach helps to improve the re-ID performance by considering not only appearance-based features of a person from a CNN, but also contextual information. The latter serves as scene understanding information complimentary to person re-ID. Experimental results show that for the DukeMTMC-reID dataset [2][3], introduction of our ST-MC model substantially increases the mean Average Precision (mAP) and Rank-1 score from 77.2% to 84.1%, and from 88.6% to 96.2%, respectively.
Environmental-Based Illiteracy Eradication in Owata Village, Bone Bolango Regence, Gorontalo Province

The program of Student Community Service -Community Empowerment (henceforth called as KKN-PPM) aims to eradicate illiteracy through the environment as a learning source in Owata Village, BulangoUludistrict, Bone BolangoRegency, Gorontalo Province.The environment as a learning source due to the consideration of potential and local wisdom in Owata Village towards the environment as stated in the vision of this village that emphasizes the economic strengthening throughgreen human resources.The target to be achieved from this activity is that the illiterates can read and write based on their observation to the surrounding area as well as to reduce the illiteracy rate in Owata Village.This activity is carried out by providing socialization, training, and observation to the environment as a source of vocabulary and sentence acquisition for reading and writing purposes.In addition, the training will involve the supervisors and students in motivating and developing the community to recognize and understand letters, syllables, and sentences so that it can be implemented in writing the discourse about their surrounding area.The results of this KKN-PPM program are the decreased illiteracy rate and the increased knowledge and skills of Owata Village community in writing and reading based on their environment so that it can be a means in emerging their love and awareness of environmental conservation.
Quantum key distribution beyond the repeaterless rate-loss limit (Conference Presentation)

Quantum key distribution (QKD) allows users to generate shared encryption keys that are guaranteed to be theoretically secure by the laws of quantum mechanics. Most implementations use light pulses that are attenuated by the propagation medium. This leads to a fundamental rate-distance limit in QKD that was thought to be impossible to overcome with current technology. The recent proposal of "Twin-Field QKD", however, changed this belief and showed how to overcome this limit and perform long-distance QKD with present-day technology. In my talk I will review the most significant theoretical and experimental results in this emerging and rapidly growing research area.
PERANCANGAN WEB PARIWISATA PADA DINAS KEBUDAYAN DAN PARIWISATA KABUPATEN PASAMAN BARAT DENGAN BAHASA PEMROGRAMAN PHP DAN DATABASE MYSQL

In connection with the research conducted at the Culture and Tourism Office of West Pasaman Regency, particularly on the development and introduction of culture and tourism, several key points that need to be discussed and become a major concern in the process of developing and introducing culture and tourism are creating a website that contains culture and tourism. tourism that is packaged attractively so as to attract the interest of the community to visit West Pasaman Regency. This culture and tourism website is designed so that it can become a media of promotion and education so that it has a use value for the community. West.
Our Introduction to the Learn Something module in #edu106 @scsu using a #connectedlearning lens in our #literacies class

We began class with a check-in. Every class begins with an entrance slip where students blog about their writing. I use this technique to take
Analisis Kerawanan Longsor Dan Penentuan Jalur Evakuasi Potensial Kecamatan Poncol Kabupaten Magetan Tahun 2017

This study aims to analyze the level of longosr vulnerability and potential evacuation routes, which can minimize losses and make it easier for self-rescue. To achieve this goal researchers conducted a survey to determine the causes of landslides, which can be divided into factors such as slope, trigger factors (dynamic) in the form of rainfall and land use, and trigger factors (static) in the form of rock weathering, soil depth, bed structure , and soil texture, all parameters are weighted and multiplied by constants. This sampling is based on the unit map of the terrain unit, thus recognizing the extent of the avalanche and the affected area. Determination of the evacuation route by determining the starting point and end point in the form of a potential shelter, the starting point is used as a safe point and a gathering point before the evacuation process by volunteers. Whereas the potential shleter is the final point for temporary settlement, which is determined based on the availability of public kitchen capacity and MCK. Evacuation routes are obtained from field surveys and weighting of parameters in the form of landslides, road widths, road conditions, road surface material, position locations and road directions processed using the least cost path. The results showed 6 villages that entered into the level of high landslide vulnerability namely the villages of Alastuwo, Genilangit, Gonggang, Plangkrongan, Poncol and Sombo, because the village was on a flat slope while the landslide vulnerability was very high on the slope slope with sloping level very advanced rock weathering and poor rock bed structure. That way, 16 potential shelters were obtained in the form of public facilities that have a capacity of over 100 people, and 7 gathering points and 16 evacuation routes that can be traversed using four-wheeled vehicles with asphalt road conditions and no bridge.
An Improved Subspace Clustering Algorithm Based on Sparse Representation

Subspace clustering is an effective algorithm refer to the problem which separate the data lying on a union of subspaces. Usually the algorithm consists of two steps. First, an affinity matrix is calculated from the self-representation of the data. Second, spectral clustering is used to cluster the data by the affinity matrix. The paper introduces a new method based on the sparse subspace clustering. The new method used a new objective which considered both the sparseness and grouping effect. And the affinity matrix which is calculated from the self-representation of the data is furthered optimized. It proved to be more efficient than existing subspace clustering methods.
Topics in the mean-field type approach to pedestrian crowd modeling and conventions

This thesis consists of five appended papers, primarily addressingtopics in pedestrian crowd modeling and the formation of conventions.The first paper generalizes a pedestrian crowd model for compe ...
Classification of Hand Movement in EEG using ERD/ERS and Multilayer Perceptron

Continuous EEG activity in the measured subjects includes different patterns depending on what activity the subject performed. ERD and ERS are examples of such patterns related to movement, for example of a hand, ﬁnger or foot. This article deals with the detection of motion based on the ERD/ERS patterns. By linking ERD/ERS, feature vectors which are later classiﬁed by neural network are created. The resulting neural network consists of one input and one output layer and two hidden layers. The ﬁrst hidden layer contains 3,000 neurons and the second one 1,500 neurons. A training set of feature vectors is used for the training of this neural network and the back-propagation algorithm is used for the subsequent adjustment of the weights. With this setting and training, the neural network is able to classify motion in an EEG record with an average accuracy of 79.92%.
Sieve: Internationalized Email

This document defines an extension to the Sieve language called eaiwhich adds full support for internationalized email.
Incorporating Improvisation in a Theory Class on Contemporary Music

I begin with one example of structured improvisation used in theory class, the “Indeterminate Jam.” It consists of five boxes that contain instructions on what kinds of sounds to make. One student acts as conductor, who makes decisions on which box(es) to execute, and when. I follow this with a table of weekly improvisation activities – based on the topic for each week – and explain three of them. The purpose of the jams is to allow students to work (play) with the materials, while developing their ensemble skills and creativity. I end by discussing the purposes and benefits of incorporating improvisation into the classroom.
Procure Data Veracity and Seclusion Preservation in Testimony Emporium

Data contribution  is the announcing of your Firms receivable data, which is thought about the business credit reports of your clients. Data  is wherever right now. Indeed, the measure of advanced data  that exists is developing at a fast rate, multiplying like clockwork, and changing the manner in which we live. As indicated by IBM, 2.5 billion gigabytes (GB) of data  was produced each day, an article by Forbes states that Data is becoming quicker than at any other time and continuously 2020, about 1.7 megabytes of new data will be made each second for each person on the planet. Which makes it critical to know the nuts and bolts of the field at any rate. Right now benefactors need to transfer their data's. Data 's are have been gathered and store it as bytes and administrator need to endorse the transferred documents by their transferred record name, if any various names are have been transferred by data  patrons Admin will erase their transferred records and acknowledged records will be obvious to the data  purchasers and they can download their documents, while downloading to check data  customer is a substantial individual or not an OTP will be naturally send to their enlisted Mail ID and if the OTP matches the record will be downloaded for their future undertakings.
Creating a Personalised Experience for Libraries’ Visitors

Great value can be given to any old-school organization by providing its users with personalised experience. The present study aims at the use of innovative technology in libraries to enable the study and understanding of the libraries’ frequent visitors to better support them through the provision of enriched personalised experience. To support this goal, modern technologies such as recommendation systems, gamification and indoor localization techniques such as beacons will be used. Recommendation systems are the basis for providing personalised user experience since their task is to exploit user information (demographic information, habits, actions, likes and dislikes) to get to know each and every one of the users by building a profile for them. Gamification will also support the concept by enriching the user experience with game-like attributes to boost user engagement like rewarding the user with experience points for each library visit or for each book they check out. Finally, indoor localization techniques will be used to help the libraries manage the on-premises crowd to avoid congestion and to also help the libraries’ visitors have fruitful interactions with each other. The combined application of the aforementioned techniques can help the libraries grow alongside the technological advancements by exploiting them for the modernisation of their model.