Reviewerly/exHarmony huggingface dataset:
Human Activity Recognition Using Smartphone Sensor Data

The hot topic in recent times is recognition of human activities through a smartphone, smart home, remote monitoring and assisted healthcare. These fall under ambient intelligent services. This also includes recognition of simple activities like sitting, running and walking, and more research is being held for semi-complex activities such as moving upstairs and downstairs, running and jogging. Activity recognition is the problem of predicting the current action of a person by using the motion sensors worn on the body. This problem is approached by using supervised classification model where a model is trained from a known set of data, and a query is then resolved to a known activity label by using the learned model. The exigent issue here is whether how to feed this classification model with a set of features, where the input provided is a raw sensor data. In this study, three classification techniques are considered and their accuracy in predicting the correct activity. In addition to the systematic comparison of the results, a comprehensive evaluation of data collection and some preprocessing steps are provided such as filtering and feature generation. The results determine that feeding a support vector machine with an ensemble selection of most relevant features by using principal component analysis yields best results.
Research Guides: COVID-19 Educational Offers and Resources: University Libraries Resources

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Real-Time Robust and Cost-Efficient Hand Tracking in Colored Video Using Simple Camera

Dynamic hand gesture recognition field has high potential to change the interaction mechanism between human and machine. But user interfaces (UIs) working on hand movements are still a challenge because of the lack of cost-effective and robust hand tracking techniques. To avoid the challenges encountered in tracking, non-rigid and subtle object-Hand, researchers use advance cameras which overall increases the cost and complexity of any technique. In this paper, we have focused on two important stages of dynamic hand tracking, first is hand modeling and second is robust hand tracking. We have developed a prototype of hand tracking using graphical user interface (GUI) of MATLAB software, working on live videos captured using a normal camera. The proposed system is tested on videos in intelligent biometric group hand tracking (IBGHT) database.
Review of Various Two-Phase Authentication Mechanisms on Ease of Use and Security Enhancement Parameters

We are living in a digital era, where most of the critical information whether it is confidential, academic documents or chats and even money transaction is being done in digital format. Digital technology is progressing at its large because of its ease and speed. With this digital data advancement, responsibility and core need arises for its security arises. For protecting data, authentication mechanism plays a major role. Authentication mechanism assures security of data by allowing legitimate users to access it. Using single-phase authentication mechanism (UID and password) is the easiest and convenient mechanism to implement and use in past days. For preserving data from false access, there is a need to develop more protected authentication mechanism which cannot be easily penetrated. This gave birth to two-phase authentication mechanisms that are commonly known as two-factor authentication mechanisms. Two-phase authentication mechanisms provide additional security by adding one more factor for authentication in traditional single-phase authentication mechanisms. There are lots of two-phase authentication mechanisms that developed with technological advancement. In this paper, we will review various two-phase authentication mechanisms by considering security enhancement they provide and ease of use in their implementation.
LibGuides: Online resources and support: Trouble-shooting

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TArC: Incrementally and Semi-Automatically Collecting a Tunisian Arabish Corpus

This article describes the constitution process of the first morpho-syntactically annotated Tunisian Arabish Corpus (TArC). Arabish, also known as Arabizi, is a spontaneous coding of Arabic dialects in Latin characters and arithmographs (numbers used as letters). This code-system was developed by Arabic-speaking users of social media in order to facilitate the writing in the Computer-Mediated Communication (CMC) and text messaging informal frameworks. There is variety in the realization of Arabish amongst dialects, and each Arabish code-system is under-resourced, in the same way as most of the Arabic dialects. In the last few years, the focus on Arabic dialects in the NLP field has considerably increased. Taking this into consideration, TArC will be a useful support for different types of analyses, computational and linguistic, as well as for NLP tools training. In this article we will describe preliminary work on the TArC semi-automatic construction process and some of the first analyses we developed on TArC. In addition, in order to provide a complete overview of the challenges faced during the building process, we will present the main Tunisian dialect characteristics and their encoding in Tunisian Arabish.
Improving Calibration in Mixup-trained Deep Neural Networks through Confidence-Based Loss Functions.

Deep Neural Networks (DNN) represent the state of the art in many tasks. However, due to their overparameterization, their generalization capabilities are in doubt and are still under study. Consequently, DNN can overfit and assign overconfident predictions, as they tend to learn highly oscillating decision thresholds. This has been shown to affect the calibration of the confidences assigned to unseen data. Data Augmentation (DA) strategies have been proposed to overcome some of these limitations. One of the most popular is Mixup, which has shown a great ability to improve the accuracy of these models. Recent work has provided evidence that Mixup also improves the uncertainty quantification and calibration of DNN. In this work, we argue and provide empirical evidence that, due to its fundamentals, Mixup does not necessarily improve calibration. Based on our observations we propose a new loss function that improves the calibration, and also sometimes the accuracy. Our loss is inspired by Bayes decision theory and introduces a new training framework for designing losses for probabilistic modelling. We provide state-of-the-art accuracy with consistent improvements in calibration performance.
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An Advance Approach for Spam Document Detection Using QAP Rabin-Karp Algorithm

Document spam is the term which is related to the document copyright issue. It deals with the plagiarism of content from a genuine copy to another. Many researches are performed around the globe for the sake of improvement in different fields such as medical, technology, and agriculture The original content makes impact on the current scenario improvement. Many organization and individual make use of existing concepts to take credit of others’ work in their profile. Document spamming is not a legal activity, and thus, there are many algorithms are derived by the research authors to avoid such spamming. Challenges behind such approach are processing the data and finding accuracy over the similarity detection. In this paper, a novel QAP-based Rabin-Karp algorithm is proposed. This approach is a combination of score computation using QAP functions and finally similarity measure computation using Rabin-Karp algorithm. The execution of experimental algorithm is performed using Java library along with sample documents. Algorithm is compared with traditional approach which shows the performance of proposed technique in terms of similarity measure, computation time, and throughput as parameter. The application found improvement, and hence, it shows the effectiveness of proposed approach.
Teaching behind bars in Valparaiso

Situated on a hill in the seaport city of Valparaiso, on the Chilean coast, the Juan Luis Vives school was founded in 1999. Today it has 550 students. What makes it unique is that it is located inside the city’s prison. Every day, the teachers who work there are forced to cope with the challenges of the prison world – which include disparities in learning abilities, and emotions on edge. The school was awarded the UNESCO Confucius Prize for Literacy in 2015.
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Data Mapping and Finite Difference Learning

Restricted Boltzmann machine (RBM) is a two-layer neural network constructed as a probabilistic model and its training is to maximize a product of probabilities by the contrastive divergence (CD) scheme. In this paper a data mapping is proposed to describe the relationship between the visible and hidden layers and the training is to minimize a squared error on the visible layer by a finite difference learning. This paper presents three new properties in using the RBM: 1) nodes on the visible and hidden layers can take real-valued matrix data without a probabilistic interpretation; 2) the famous CD1 is a finite difference approximation of the gradient descent; 3) the activation can take non-sigmoid functions such as identity, relu and softsign. The data mapping provides a unified framework on the dimensionality reduction, the feature extraction and the data representation pioneered and developed by Hinton and his colleagues. As an approximation of the gradient descent, the finite difference learning is applicable to both directed and undirected graphs. Numerical experiments are performed to verify these new properties on the very low dimensionality reduction, the collinearity of timer series data and the use of flexible activations.
A Study on Teaching Method of Writing for the Creation of Sound Occupational View of University Students - Focused on Writing a Process-Based Self-Introduction Statement -

This study has applied how university students learn writing a process-based self-introduction statement as a teaching method of writing to help them have proper professionalism who need to be prepared for deciding their job. It is based on one of educational goals which writing a self-introduction statement can help the students hold positivity of intrinsic value of a job. The educational objectives of writing a self-introduction statement are to help the learners plan the present by themselves and put it into practice, and recognize professional values through having them search for themselves and discover their future roles as a member of society.BR Teaching how to write a self-introduction statement discussed in this research has been performed based on the process in order, from grown-up backgrounds, advantages and disadvantages of personality, motivation for application, to aspiration after entering a company, general items of a self-introduction statement, by being related to self-understanding, self-analysis, and creation of the occupational view. Through this process, the learners have got to know their current identity by analyzing grown-up backgrounds and characteristics of their personality through self-understanding and self-analysis. Moreover, they have also established their future identity through exploring what they want to do in the future by themselves and creating a roadmap for their life. In addition, they have thought about their positive roles in community through finding their role models and learning how they made their life valuable, and writting the meaning and value of the learners’ dream job.BR Despite the instructor’s intentional strategies for teaching the writing, most learners participated in the writing activity seriously. Hopefully, the learning experience of writing a process-based self-introduction statement can help the university students whose time to start their career is just around the corner, get into society smoothly, and have valuable and happy social life as responsible and independent ego.
TMPS: Ticket-Mediated Password Strengthening.

We introduce the notion of TMPS: Ticket-Mediated Password Strengthening, a technique for allowing users to derive keys from passwords while imposing a strict limit on the number of guesses of their password any attacker can make, and strongly protecting the users’ privacy. We describe the security requirements of TMPS, and then a set of efficient and practical protocols to implement a TMPS scheme, requiring only hash functions, CCA2-secure encryption, and blind signatures. We provide several variant protocols, including an offline symmetric-only protocol that uses a local trusted computing environment, and online variants that use group signatures or stronger trust assumptions instead of blind signatures. We formalize the security of our scheme by defining an ideal functionality in the Universal Composability (UC) framework, and by providing game-based definitions of security. We prove that our protocol realizes the ideal functionality in the random oracle model (ROM) under adaptive corruptions with erasures, and prove that security with respect to the ideal/real definition implies security with respect to the game-based definitions.
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Camera Orientation Determination Based on Copper Wire Spool Shape

A simple and inexpensive system but effective in performing required tasks is the most preferable in industry. In this study, a vision system is developed to solve the peg-in-hole problem of a robot-like forklift to pick up copper wire spool arranged side by side on a rack, without using any sensors, except a low-cost camera. Inspired by how human perceive an object orientation based on its shape, an algorithm is developed to determine robot orientation based on the shape of a copper wire spool relative to camera position and yaw angle. The center point of the spool (CPS) should be on the center line of camera FOV (CFOV) if the camera is perpendicular or 0° parallel to the spool. Thus, the coordinate of the CPS and the CFOV is same. Instead, when the camera is seeing the spool from the angle less or bigger than 0°, the CPS and CFOV will be different, and the difference shows the position and the yaw angle of the camera relative to the spool. A copper wire spool has three circles; the outer circle, the tapper part around its center hole and the center hole itself. The proposed system uses Circular Hough Transform (CHT), filtering, binary, morphology and Sobel edge detection of the sampled images from real-time video recording to determine the orientation of the camera related to the copper wire spool shape, in which the center coordinate of the three circles was determined. Results from the experiments that had been done show that the system is able to determine the orientation of the camera related to the spool.
New Discrete Logarithm Computation for the Medium Prime Case Using the Function Field Sieve.

The present work reports progress in discrete logarithm computation for the general medium prime case using the function field sieve algorithm. A new record discrete logarithm computation over a 1051-bit field having a 22-bit characteristic was performed. This computation builds on and implements previously known techniques. Analysis indicates that the relation collection and descent steps are within reach for fields with 32-bit characteristic and moderate extension degrees. It is the linear algebra step which will dominate the computation time for any discrete logarithm computation over such fields.
APPLICATION OF THE CONCEPTUAL UNDERSTANDING TO IMPROVE THE PERFORMANCE OF STUDENTS IN PHYSICS

Physics learning fundamentally requires conceptualization (conceptual understanding) and problem-solving processes. The first refers to specifying and interpreting the meaning of a concept in its entire range of validity. The second concerns the flexible application of the concepts and principles of physics to find the solution to a problem. However, students think that all they need to know are the equations, select them, apply them, and replace data according to the context of the problem.Therefore, the purpose of this study was to promote conceptual understanding to improve the performance of students from different engineering careers who are registered in a physics course offered by an Ecuadorian public university.The participants were 70 students, aged between 18 and 20, who took the subject of Physics offered to students of an Ecuadorian public university. The instructional unit was Kinematics of the particle in one and two dimensions. The texts used in the course were the time spent on his teaching lasted 16 hours. The instruments were an assessment related to the unit taught. The procedure followed in this study was as follows: (1) Explain the particle kinematics unit in one and two dimensions, both to the experimental and control group. (2) Presenting the teaching of conceptual understanding only to the experimental group, the control group received the class in a traditional way. (3) Administer the posttest test.In this study the independent variable is two-level teaching with conceptual understanding and no conceptual understanding; the dependent variable is student performance. The study consisted of two groups: the experimental group and the control group. The applied statistical analysis is the Gosset test used to compare the means of two samples of the population when the means are known and independent and the variances are different.The Gosset test indicates that there was a significant difference between the two groups (t x 3.07, df x 65 p x 0.0032). Therefore, the research hypothesis is accepted and the null hypothesis is rejected.This study proved that those students who receive the teaching with conceptual understanding perform better and the results obtained support this hypothesis. In addition, students demonstrated a better problem-solving ability than the students in the control group.This study has more practical value than theoretical and therefore its application in engineering career courses is recommended to emphasize conceptualization and problem solving. The most important part of this learning teaching strategy is that students learn how to solve problems by applying concepts and teachers improve their teaching because students better build knowledge by helping the process of self-regulation and the organization of knowledge.
La crisi del dibattito pubblico nell’Italia contemporanea: il discorso populista / The crisis of public debate in contemporary Italy: the populist discourse

In this paper I discuss the current state of the so called populist political discourse in Italy. In particular my purpose is to shed light on some features of this kind of discourse in order to show the relation between language and policy in the discourse of populism. In this perspective I will follow the eight key points that, according to Diamanti & Lazar (2018), identify the actual populist movements, in order to verify if – and, in that case, which – linguistic traits characterize their discourse.The analysis will be focused on the semantic and argumentative aspects of the discourse of some of the most important political actors in contemporary Italy.
PENGEMBANGAN SKENARIO PEMBELAJARAN TEKS NARASI DENGAN MODEL DISCOVERY LEARNING UNTUK SISWA SMP KELAS VII

The problem of this research is how to develop a learning scenario by usin discovery learning model to the seventh grade students of Junior High School. The method that is used in this reasearch is R and D (Reasearch and Development) which reffered to Borg and Gall. They states that the development procedures use five stages, namely collecting information, design design, design validity, design revision, and final product. The results of this research and development are in the form of narrative text learning scenarios using discovery learning models for seventh grade junior high school students who have been declared fit for use by material experts with a percentage of 78% with very feasible categories, the feasibility aspect of the presentation obtains a 75% percentage with the proper category and feasibility aspects language percentage of 75% with a decent category. Masalah dalam penelitian ini ialah bagaimanakah pengembangan  skenario pembelajaran menggunakan model discovery learning untuk siswa SMP kelas VII. Tujuan Penelitian ini ialah menghasilkan sebuah produk berupa skenario pembelajaran menggunakan model discovery learning untuk materi teks narasi di SMP. Metode dalam penelitian ini ialah  Research and Development (R&D) mengacu prosedur pengembangan Borg dan Gall dengan menggunakan lima tahap, yaitu pengumpulan informasi, perancangan desain, validitas desain, revisi desain, dan produk akhir.  Hasil penelitian dan pengembangan ini berupa sebuah skenario pembelajaran teks narasi menggunakan model discovery learning untuk siswa SMP kelas VII yang telah dinyatakan layak digunakan oleh ahli materi dengan presentase 78% dengan kategori sangat layak, aspek kelayakan penyajian memperoleh presentase 75% dengan kategori layak dan aspek kelayakan bahasa presentase 75% dengan kategori layak. Keywords:  narrative text learning scenarios, discovery learning models, SMP
Sustainable Corporate Social Responsibility Practices: An Indian Perspective:

Corporate Social responsibility (CSR) is the well-known term and accepted among various stakeholders of any organization in India. Our country is first in the world to make CSR activities mandatory as per the amendment made to the Companies Act, 2013 in April 2014 and any company that makes a minimum net profit of five crores need to spend 2% of their average net profits of three consecutive years on the CSR activities. CSR activities should be in line with the United Nations Sustainable Development Goals (SDGs) with its solid focus on achieving social performance. For the present study secondary data is taken from various company websites and other websites on CSR activities and amount spent by the Indian companies. This paper studies the analysis of CSR amount spent in the last five year that is from 2014 to 2019 and implementation of CSR sustainable practices by top four companies in India viz., Reliance Industries Limited, Tata Consultancy Services Ltd. Oil and Natural Gas Corporation Ltd. and Indian Oil Corporation Ltd. which are listed in BSE/NSE. From the study it was found that Reliance Industries Ltd. spent surplus amount consistently on the CSR activities from last five years when compared to other three industries.