Reviewerly/exHarmony huggingface dataset:
Fighting Filterbubbles with Adversarial BERT-Training for News-Recommendation

Recommender engines play a role in the emergence and reinforcement of filter bubbles. When these systems learn that a user prefers content from a particular site, the user will be less likely to be exposed to different sources or opinions and, ultimately, is more likely to develop extremist tendencies. We trace the roots of this phenomenon to the way the recommender engine represents news articles. The vectorial features modern systems extract from the plain text of news articles are already highly predictive of the associated news outlet. We propose a new training scheme based on adversarial machine learning to tackle this issue . Our experiments show that the features we can extract this way are significantly less predictive of the news outlet and thus offer the possibility to reduce the risk of manifestation of new filter bubbles. We validate our intuitions in a news recommendation task using a recent attention-based recommendation system.
Prevalence of Malaria in District Swat Khyber Pakhtunkhwa

The present study was conducted in year 2016 and 2017 recording all incidences of the infection from May 2016 to April 2017. A detailed description is given below. A cross-sectional survey was conducted from May 2016 to April 2017 in district Swat constituting of seven tehsils. In our study a total of 17,035 suspected cases of malaria were analyzed. Of the total cases 7.83% (1,334) were of Plasmodium vivax while 0.0% were of Plasmodium falciparum. Mixed infections were not seen in the present study not were any other species observed. Our results show that Plasmodium vivax is the dominant malarial parasite and throughout the year it remained prevalent. Seasonal variation was clearly noticed to be one of the factors in effecting the number of incidence, the highest incidence of malarial cases were recorded in the months of August to October i.e., 11.8% (721/6106) due to monsoon rainy season in the area. During the month of January and February the cases were at the lowest i.e., 2.52% (21/833) this can be due to the fact that the temperature is very low and does not provide suitable niche for the vector insect.
A Study of Fraud Types, Challenges and Detection Approaches in Telecommunication

Fraudulent activities have been rising globally resulting companies losing billions of dollars that can cause severe financial damages. Various approaches have been proposed by researchers in different applications. Studying these approaches can help us obtain a better understanding of the problem. The aim of this paper is to investigate different aspects of fraud prevention and detection in telecommunication. This study presents a review of different fraud categories in telecommunication, the challenges that hinder the detection process, and some proposed solutions to overcome them. Also, the performance of some of the state-of-the-art approaches is reported followed by our guideline and recommendation in choosing the best metrics.
Learning to Generate the Unknowns for Open-set Domain Adaptation

In many situations, the data one has access to at test time follows a different distribution from the training data. Over the years, this problem has been tackled by closed-set domain adaptation techniques. Recently, open-set domain adaptation has emerged to address the more realistic scenario where additional unknown classes are present in the target data. In this setting, existing techniques focus on the challenging task of isolating the unknown target samples, so as to avoid the negative transfer resulting from aligning the source feature distributions with the broader target one that encompasses the additional unknown classes. Here, we propose a simpler and more effective solution consisting of complementing the source data distribution and making it comparable to the target one by enabling the model to generate source samples corresponding to the unknown target classes. To this end, we attach a generative model to a standard domain adaptation network and augment the source data with the generated samples before matching the source distribution to the target one, thus avoiding negative transfer between the domains. We formulate this as a general module that can be incorporated into any existing closed-set approach and show that this strategy allows us to outperform the state of the art on standard open-set domain adaptation benchmark datasets.
Quantum-enhanced data classification with a variational entangled sensor network

Quantum machine-learning techniques speed up the task of classifying data delivered by a small network of quantum sensors.
‘Scarred for life too’: measuring girth and estimating ages of culturally modified trees using comparative examples from Wotjobaluk Country, Western Victoria

This paper was included in the ninth issue of Excavations, Surveys and Heritage Management in Victoria and was presented at the annual Victorian Archaeology Colloquium held at La Trobe University on 1 February 2020.
Gen Z Nursing Students' Usage, Perception and Satisfaction with Facebook for Educational Purposes: Tool for Learning or Distraction

Introduction: Gen Z has started to enter the portals of nursing classrooms. They are technology and socially-savvy consumers who grew up in the world of internet and smartphones. However, little is known about this generation, particularly among nursing students and how they use Facebook for academic purposes. The purpose of this study was to determine nursing students’ usage, perception, and satisfaction with Facebook for educational purposes Methods: A descriptive, cross-sectional research design was used. A total of 113 conveniently chosen nursing students in a Nursing College in the Philippines participated in the survey. Data were collected using an adopted questionnaire administered via online survey. Descriptive and inferential statistical tools were used to analyze the data. Results: Results indicated that majority of nursing students moderately (M=3.58) use Facebook for educational purposes to communicate, collaborate, and share academic or learning materials. They generally had a good perception of (M=4.36) and were highly satisfied (Mean=3.95) with using Facebook for educational purposes. The main challenge reported by 81.42% of nursing students in the use of Facebook was distraction from other Facebook contents. There was a significant positive relationship between usage and perception (p=.000) likewise between satisfaction and recommendation in the use of Facebook for educational purposes (p=.000). Conclusions: While Facebook showcases promising potential as a learning tool, challenges associated with its use in nursing education must be properly addressed. Careful consideration and thoughtful planning are necessary for nursing schools to maximize the advantages of Facebook as a supplemental tool for learning.
Corporate Governance System in Honda and Sony

In describing the corporate governance system in Japan, we focus mainly on two companies from two sectors, automobiles and consumers’ electronics, Honda and Sony.
seMLP: Self-evolving Multi-layer Perceptron in Stock Trading Decision Making

Abstract There is a growing interest in automatic crafting of neural network architectures as opposed to expert tuning to find the best architecture. On the other hand, the problem of stock trading is considered one of the most dynamic systems that heavily depends on complex trends of the individual company. This paper proposes a novel self-evolving neural network system called self-evolving Multi-Layer Perceptron (seMLP) which can abstract the data and produce an optimum neural network architecture without expert tuning. seMLP incorporates the human cognitive ability of concept abstraction into the architecture of the neural network. Genetic algorithm (GA) is used to determine the best neural network architecture that is capable of knowledge abstraction of the data. After determining the architecture of the neural network with the minimum width, seMLP prunes the network to remove the redundant neurons in the network, thus decreasing the density of the network and achieving conciseness. seMLP is evaluated on three stock market data sets. The optimized models obtained from seMLP are compared and benchmarked against state-of-the-art methods. The results show that seMLP can automatically choose best performing models.
IOT Connected with E-Learning

In the networking field, Internet of Things (IoT) can be referred to technological e-learning advancements. It is seen that through the internet, nowadays it becomes easier to be connected with the real world affairs by being acknowledges about the all-around happenings. Even everyone is aware about communicating with each other all over world. 'Things' can be specified as the objects which are connected through internet.Over the internet, the specific kind of interconnection of different things can serve its capability through the information which can be utilized in receiving and sending of evaluated data. It is said to be specialized in almost every field that can be determined in numerous manner for implementing wide range of applications format. Wide ranges can be mentioned as education, business, transportation, agriculture, healthcare and management. In a generalized manner, in this article specifically and mainly the discussion is being held over the Internet of Things (IoT). Specific emphasis on E-learning is said to be implemented as a source of information applied for its readers. By the utilization of smart learning as the IOT the smart techniques can also be represented shown by e-learning methods.
Multiple Fusion Strategies in Localization of Local Deformation Tampering

Tampering with images may involve the field of crime and also bring problems such as incorrect values to the public. Image local deformation is one of the most common image tampering methods, where the original texture features and the correlation between the pixels of an image are changed. Multiple fusion strategies based on first-order difference images and their texture feature is proposed to locate the tamper in local deformation image. Firstly, texture features using overlapping blocks on one color channel are extracted and fed into fuzzy c-means clustering method to generate a tamper probability map (TPM), and then several TPMs with different block sizes are fused in the first fusion. Secondly, different TPMs with different color channels and different texture features are respectively fused in the second and third fusion. The experimental results show that the proposed method can accurately detect the location of the local deformation of an image.
AAA launches fleet of roadside assistance vehicles

AAA is releasing 11 new roadside assistance vehicles, so when you get into a tough situation—AAA can now respond even faster.
Οι Νέες Τεχνολογίες στη διδακτική της Ιστορίας στο Δημοτικό Σχολείο

Nowadays, the exploitation of augmented reality in education is linked to a multitude of pedagogical subjects, including history, geography, natural sciences and arts. The extensive use of computers in the educational process in recent years, in addition to learners’ familiarity with the use of Internet and applications associated with its operation, have led to a search for creative methods, which will enhance interaction in the pedagogical approach. As a result, a digital learning environment has emerged in which trainees gain access to knowledge in an entertaining and interactive way by making use of innovations and gaining the ability to control their knowledge. The purpose of this thesis is to feature the role of new technologies in the educational process by studying the use of augmented reality applications in teaching history. Designing such applications requires direct involvement of the teacher and, as established by the case study, the benefits are extremely important; students acquire a particular interest in the learning object and achieve higher performance, as compared to conventional forms of teaching.
Увлажнитель дыхательных смесей: ПИД-регуляция с использованием метода Циглера – Никольса

Due to the ubiquitous spread of SARS-CoV-2 coronavirus infection, the demand for anaesthesia and respiratory devices has significantly increased since the beginning of 2020. In particular, artificial ventilation devices, inhalation anaesthesia devices, or oxygen inhalers. The respiratory support devices must include special medical devices designed to heat and increase the moisture content of the respiratory mixture supplied to the patient from the respiratory therapy apparatus. These medical devices are known to as humidifiers. The production of a humidifier for breathing mixtures “TEVLAR” – “UOMZ” according to TU 32.50.21-121-07539541-2018 with accessories was organized jn the territory of Joint Stock Company “Production Association “Urals Optical & Mechanical Plant” named after Mr. E. S. Yalamov”. The electronic measuring instruments unit of the device has been modified within the framework of the project for the modernization of the humidifier of breathing mixtures “TEVLAR” – “UOMZ”. In particular, in order to increase the accuracy of thermal stability of the heating element when heating the breathing mixtures to the target temperature, the software of the electronic measuring instruments unit was modernized by the Medical Devices Design Bureau, namely, the stable PID controller was implemented and tuned. Thus, this article provides an overview of the methods for tuning the PID controller, justifies the choice of PID tuning by the Ziegler-Nichols method and also provides the experimental results to confirm device operation stability. Lipchak D. A., Dushkina A. A., Chupov A. A. External humidifier for ventilator: PID control based on the Ziegler-Nichols method. Ural Radio Engineering Journal. 2020;4(4):376–317. DOI: 10.15826/ urej.2020.4.4.002.
Domain-Free Adversarial Splitting for Domain Generalization

Domain generalization is an approach that utilizes several source domains to train the learner to be generalizable to unseen target domain to tackle domain shift issue. It has drawn much attention in machine learning community. This paper aims to learn to generalize well to unseen target domain without relying on the knowledge of the number of source domains and domain labels. To achieve that goal, we unify adversarial training and meta-learning in a novel proposed Domain-Free Adversarial Splitting (DFAS) framework. In this framework, we model the domain generalization as a learning problem that enforces the learner to be able to generalize well for any train/val subsets splitting of the training dataset. This model can be further transformed to be a min-max optimization problem which can be solved by an iterative adversarial training process. In each iteration, it adversarially splits the training dataset into train/val subsets to maximize domain shift between them using current learner, and then updates the learner on this splitting to be able to generalize well from train-subset to val-subset using meta-learning approach. Extensive experiments on three benchmark datasets under three different settings on the source and target domains show that our method achieves state-of-the-art results and confirm the effectiveness of our method by ablation study. We also derive a generalization error bound for theoretical understanding of our method.
Artificial Neural Networks: Utilising Machine Learning for Equitable Breast Cancer Diagnosis

Breast cancer is the most commonly occurring cancer in women, and it is pivotal that it is diagnosed correctly and promptly. Artificial Intelligence (AI) is now widely used in diagnosis to produce more accurate results. Dr. Roy Jafari from the University of Redlands is training a type of AI called an Artificial Neural Network to make more equitable diagnosis decisions for patients. He hopes that focussing on decision-making will reduce stress on patients and create a better care experience.
Radiação Obscura: Fluxos energéticos sonificados no limiar da experiência sonora.

This essay analyze the impact of the sonification processes in the sound arts. This is achieved exploring the definition of their production methodologies, philosophical implications and conceptual significance taking as examples my artistic experiments with sonification of light and electromagnetic fields explored in my projects that are presented in this analyses. The sonification as an artistic practice consist of generating art works based in the data-flows. Originated a sound event outside the physic of sound as non-vibration force. That is associated in my argument as data-event-sound connected with a new ontology outside the forces that animate the understanding of sound as vibration. Opening the understanding of the work of art as a system of interdependent relations in digital-art. Generating new ways of understanding sound as mutation in which digital, culture and spiritual establish interconnections between the computer as a digital domain in a landscape of code, promoting complex regimes of laminar-perception.
English [V NP into V-ing] Construction: A Resultative Analysis

The purpose of this paper is to examine English [V NP into V-ing] constructions. This construction shares quite a few properties with causative sentences. For example, both are to express transitivity relationship such as [cause X to do Y] between the participants. However, corpus data suggest that this transitivity relationship may not be established in some cases (e.g., idiomatic expressions) simply because there is no X to be posited. As an alternative analysis, this paper proposes a resultative construction analysis. In this analysis, the participant X in the form of [cause X to do Y] does not pose any problem because what is important in this analysis is the end-point result. All cases of [V NP into V-ing] investigated in this paper fall out under the presented analysis. (Hallym University · Andong National University)
Newspapers, mock-ups and learning, oh my!

A newspaper article was published about us, the last mock-up has been signed off for design agreement, and Nikki is learning lots.
Coaching approach at a mathematics lesson in grade 3 in the educational structure “equal partner”

This article discusses a coaching approach in a mathematics lesson in grade 3 in the training structure “Equal partner”. Why can the implementation of a coaching approach in teaching schoolchildren be considered educational technology? This is a well-thought-out model of joint educational and pedagogical activities for the design, organization and conduct of the educational process with unconditional provision of comfortable conditions for students and teachers, which implies the implementation of the idea of complete controllability of the educational process. Educational coaching is an informal technology and the art of asking questions, the art of motivation.
Revealing the hidden capacity of artificial intelligence in nanoscience: physics-driven metric learning

We present a new approach for design of novel loss functions and introduce an optimal similarity-metric design for machine-learning-based design and knowledge discovery in nanophotonics. Machine-learning algorithms estimate the input-output relation in a photonic nanostructure by minimizing a loss function. We show that careful selection (from the available loss functions) or design of novel loss functions that are optimized for specific tasks can considerably improve the performance of machine-learning algorithms for design and knowledge discovery in photonic nanostructures. We also discuss the limitations and inefficacies of conventional loss functions that are currently being used for machine learning algorithms.
Structuring Framework for Early Validation of Product Ideas

The advancing digitalization leads to new challenges in the development of new product ideas. The systems, which need to be developed, are becoming increasingly complex. As complexity rises, so does the slowness of organizations. In order to remain innovative and be able to react quickly to changes in the market, validation approaches offer great potential. An essential focus is the early, customer-centric and continuous validation of development artefacts. This is the only way to cope with shorter development cycles, and develop products that address a real need. To plan a validation, engineers need to have an idea about the possibilities within a validation. This paper presents a structuring framework for early validation of product ideas, which contains the three tools of Validation Map, Building Block Cards and Validation Canvas. The objective is to enable easier planning of validation experiments.
Gluing resource proof-structures: inhabitation and inverting the Taylor expansion

A Multiplicative-Exponential Linear Logic (MELL) proof-structure can be expanded into a set of resource proof-structures: its Taylor expansion. We introduce a new criterion characterizing those sets of resource proof-structures that are part of the Taylor expansion of some MELL proof-structure, through a rewriting system acting both on resource and MELL proof-structures. As a consequence, we also prove semi-decidability of the type inhabitation problem for cut-free MELL proof-structures.
Three-photon discrete-energy-entangled W state in optical fiber

The tripartite W state exhibits maximal entanglement between three parties, represented as 1/&#115;qrt(3)(|001&gt;+|010&gt;+|100&gt;), and has interesting applications for quantum communication, fundamental tests of quantum mechanics, and in quantum sensing and quantum computing. We experimentally demonstrate the generation of a three-photon discrete-energy-entangled W state in optical fiber. The source relies on multiphoton-pair generation via spontaneous four-wave mixing, and post-selection. By taking advantage of constraints imposed by the SFWM process, post-selection, and the properties of the W state, we verify the state produced by this source without resorting to frequency conversion.
Technique Used In Developing Hots (Higher Order Thinking Skill) In Reading Class At The Second Grade Students Of SMK Muhammadiyah 01 Boyolali In 2019/2020 Academic Year

This study aims at describing the technique used by teacher in developinghigher order thinking skill in reading class at the second grade of SMKMuhammadiyah 01 Boyolali. Specifically, this study identifies the techniqueused by teacher to develop HOTS in teaching reading, the challenging faced byteacher in using HOTS in teaching reading, and the solution used by teacher inusing HOTS in teaching reading. The participants were an English teacher andthe second-grade students of SMK Muhammadiyah 01 Boyolali in 2019/2020academic year. The type of this research is descriptive qualitative. In this studythere are two ways to collect the data such as observation and interview, andanalyzed through three stages namely: data reduction, data display, andverification and drawing conclusion. The result showed the technique used byteacher in developing HOTS in teaching reading were: discussion, askingquestion, presentation technique, and giving feedback for students.