Reviewerly/exHarmony huggingface dataset:
Connected ambient assistance : achievements, current status and future prospects

Connected ambient assistance systems support elderly people - or people in need of care - for a self-determined, healthy and safe living in their familiar home until very old age. The systems typically communicate with nursing relatives or remote professional caregiving providers. The basic functions of stationary assistance systems include the detection of a) falls and b) deviant behavior indicating a health hazard. These kernel tasks of assistance have been amended in the course of time by a plenitude of more general assistant functions. Wearable devices, like programmable smartwatches, extend the reach of stationary assistance beyond the spatial boundaries of the familiar home. They extend the scope of wellbeing monitoring by analyzing the wearer’s heart rate in relation to the current physical activity and can also verify sufficient liquid ingestion, drinking, thus compensating the diminishing natural sensation of thirst at increasing age. Home robots also extend the scope of wellbeing monitoring within the home and relieve from the necessity of a comprehensive sensoric instrumentation of the home. So far, ambient assistant systems can primarily provide assistance only in the physiological dimension. Cognitive ambient assistance, which allows the participation in the social communication on an equal footing, today is beyond their abilities. The advances in artificial intelligence are about to change the picture. From an economic point of view, the dissemination and success of assistance systems has been slowed down within the last decade by lacking wide-spread interaction standards as well as the shortage of necessary multivalent utility of such systems. In contrast, the smart home concept offering increased comfort and sustainability has gained a lot of attractivity in the same time. Therefore, commercially successful assistance systems must provide their utility in all three dimensions: assistance, but also simultaneously in comfort/safety and sustainability.
Computer mathematical statistics optimization of conversion between blockchain integral and Token

Block chain in recent years is a new technology for the development of faster, it is mainly based on the principle behind the underlying distributed network structure, and based on the distributed, not tampered with, the nature of the traceability chain blocks in recent years has gradually become the financial and monetary financial attributes such as very strong support, therefore block chain in the extremely rich in recent years. Object of this paper is aimed at token chain integration or the block chain between trade and exchange rate problems, these problems can be described as two token between how to automatically by means of the chain of integral exchange and trading, and solve the middle block chain will appear black swans, slippage is too large, the problem of liquidity dried up.
A Study of Case Database Building of MTI Courses in Guizhou Normal University

This paper introduces the database building of MTI courses in Guizhou Normal University. The case database contains plenty of translation theories and practice cases, and integrates a variety of translation theories and practice materials. The construction of the case database will be devoted to solving the problems existing in the teaching and research of MTI courses.
Poster: An Efficient Permissioned Blockchain with Provable Reputation Mechanism

Permissioned blockchains take more reliability on participants than permissionless ones. In this poster, we focus on a hierarchical scenario of permissioned blockchains, which includes three types of participants: providers, collectors, and governors. Such a scenario has many applications in the field of IoT data collection, horizontal strategic alliances, etc. Our object is to reduce the cost of the governor's transaction verification. For this purpose, we propose a reputation protocol to help the governor measure the reliability of collectors. Based on the measurement of collectors' reputations, governors can pack high-quality transactions from reliable collectors into blocks, and thus the cost of verifying transactions can be decreased effectively. Through theoretical analysis, our protocol dramatically reduces the verification loss of governors.
A Study on ‘Hara’ Style Endings in the Korean Language Education Textbooks

This paper examined how ‘hara style endings were suggested as target grammatical items in Korean language education textbooks and suggested some basic directions for improvement. ‘Hara style endings are sentence-final endings which are used typically in written texts in which a specific addressee is not assumed. Data sources were from six series of Korean language education textbooks which are published by well-known Korean language education institutes since 2015. The findings of data analysis showed that ‘hara style endings have seldom been suggested as target grammatical items. Only two series of the textbooks suggested declarative forms as target items, and only one series suggested interrogative forms as target items. Neither imperative form nor suggestive form has been suggested as a target item in any textbooks. This paper also suggested some basic directions for improvement. First, every types of ‘hara style endings need to be suggested as target items. Second, they need to be suggested in separation from sentence-final endings of same forms which are used in spoken language. Third, information on text genre in which each ending is used needed to be offered besides information on media. Finally, information on different usages of each interrogative form is need to be offered for distinction.
SISTEM ANALISIS BUTIR SOAL PADA CBT DENGAN METODE TEORI RESPON BUTIR

Analysis of the quality of the items is carried out so that the questions made actually consist of quality items in order to measure learning outcomes. Currently, there are still many teachers who have not analyzed the questions they made because they think that analyzing the questions takes a long time and takes a lot of energy. As a result, many items used cannot produce correct data about student learning outcomes. Therefore, a Question Item Analysis System was made using the Website-based Item Response Theory method to determine the quality of the items presented. In this study, a website-based item analysis system was developed using the item response theory method with a 3PL approach model. This system is made one package with CBT. Responses from participants to analyze the items are obtained automatically when participants take the CBT test
Ergonomic Wheelchair with Enhanced Independency to Alight

There are many causes that leads to lower limb disabilities. Accidents, injuries, congenital defects, sprains, etc. are some of themost common reasons. The patients with such disabilities usually prefer the wheelchair as the most common augmentative optionbecause of easy availability and user friendliness. Although there has been great advancements in the wheelchair design, (e.g.stair-climbing, standing, sports), there are certain areas in which developments has not been considered. One such area is themovement of the patient to the bed. The project aims to improve the self-sufficiency of the user to move to the bed by them. Thewheelchair design involves four steps that aids in efficiently moving the user to the bed. The in depth study and work of theadjustable wheelchair will be discussed further in this paper
Experimental deterministic correction of qubit loss [1]

The successful operation of quantum computers relies on protecting qubits from decoherence and noise, which - if uncorrectet - will lead to erroneous results. Because these errors accumulate during an algorithm, correcting them becomes a key requirement for large-scale and fault-tolerant quantum information processors. Besides computational errors, which can be addressed by quantum error correction [2] – [8] , the carrier of the information can also be completely lost or the information can leak out of the computational space [9] – [13] .
FireBERT: Hardening BERT Classifiers Against Adversarial Attack

We present FireBERT, a set of three proof-of-concept NLP classifiers hardened against TextFooler-style word-perturbation by producing diverse alternatives to original samples. In one approach, we co-tune BERT against the training data and synthetic adversarial samples. In a second approach, we generate the synthetic samples at evaluation time through substitution of words and perturbation of embedding vectors. The diversified evaluation results are then combined by voting. A third approach replaces evaluation-time word substitution with perturbation of embedding vectors. We evaluate FireBERT for MNLI and IMDB Movie Review datasets, in the original and on adversarial examples generated by TextFooler. We also test whether TextFooler is less successful in creating new adversarial samples when manipulating FireBERT, compared to working on unhardened classifiers. We show that it is possible to improve the accuracy of BERT-based models in the face of adversarial attacks without significantly reducing the accuracy for regular benchmark samples. We present co-tuning with a synthetic data generator as a highly effective method to protect against 95% of pre-manufactured adversarial samples while maintaining 98% of original benchmark performance. We also demonstrate evaluation-time perturbation as a promising direction for further research, restoring accuracy up to 75% of benchmark performance for pre-made adversarials, and up to 65% (from a baseline of 75% orig./12% attack) under active attack by TextFooler.
Automatic Data Warehouse Generation Model from BI Requirements in Natural Language

The rise of Business Intelligence projects allowed to consolidate and consolidate the existing methodologies for the creation of Data Warehouse. Data Science and Natural Language research provided tools to solve problems that are generated in the different stages of these methodologies. The great dynamics in the management of organizations generate information needs to undergo changes or adaptations in very short periods of time. The processes of creating a Data Warehouse are characterized mainly by being long and expensive. This highlights a problem with respect to the ability of the Data Warehouse to adapt to changes in requirements. This work proposes a conceptual model that allows automating certain stages of the generation process to improve the absorption of changes in requirements.
Robustness and Generalization via Generative Adversarial Training

While deep neural networks have achieved remarkable success in various computer vision tasks, they often fail to generalize to new domains and subtle variations of input images. Several defenses have been proposed to improve the robustness against these variations. However, current defenses can only withstand the specific attack used in training, and the models often remain vulnerable to other input variations. Moreover, these methods often degrade performance of the model on clean images and do not generalize to out-of-domain samples. In this paper we present Generative Adversarial Training, an approach to simultaneously improve the model's generalization to the test set and out-of-domain samples as well as its robustness to unseen adversarial attacks. Instead of altering a low-level pre-defined aspect of images, we generate a spectrum of low-level, mid-level and high-level changes using generative models with a disentangled latent space. Adversarial training with these examples enable the model to withstand a wide range of attacks by observing a variety of input alterations during training. We show that our approach not only improves performance of the model on clean images and out-of-domain samples but also makes it robust against unforeseen attacks and outperforms prior work. We validate effectiveness of our method by demonstrating results on various tasks such as classification, segmentation and object detection.
Sentiment Analysis of Imran Khan’s Tweets

In the recent past, sentiment analysis has been an area of interests of psychologists, sociologists, neurologists, computer scientists, and linguists including corpus linguists and computational linguists. Interdisciplinary approaches to researching various issues especially the analysis of social media websites such as Facebook, Twitter, and Instagram are becoming popular nowadays. The availability of data on social media has made it easier to analyse the opinion or sentiments of its users. Analysis of these sentiments could reveal the face of users and it could help in various decision-making processes. Sentiment analysis is a system of knowing polarity (positive, negative, and neutral) in discourse. Moreover, sentiments can enable and disable certain functions of discourse and can divert the attention of the audience from important to a less important issue or otherwise, hence, there is a need to analyse the sentiments. In this research, sentiments (Polarity) of Imran Khan’s tweets are analysed with the help of R studio. Data for this study is collected from Imran Khan’s one-year’s tweets, tweeted from 1st January 2018 to 20th November 2018. Later we saved the data in. csv files. The results of the polarity check revealed that he has used all three types of sentiments that is positive, negative, and neutral. However, he mostly used neutral or free polarity items (FPIs) that is 67.41% in his tweets. Among positive and negative polarity items the number of negative polarity items (NPIs) is higher that is 23.21% as compared to positive polarity items (PPIs) which are only 9.40%. The manual analysis of results revealed that only software is not enough and there is a need to check the accuracy of the results manually. The use of negative polarity/negative face reveals that he tries to be independent and autonomous in his decisions (Goffman, 1967). The use of positive polarity items shows he tries to show his positive face to others. Moreover, sentiment analysis demonstrates the presence of themes propagated through the use of various lexical items.
Aran Literasi Baca Tulis Pegon pada Santri Baru di Pondok Pesantren Putri Al-Ma’ruf Juranguluh Mojo Kediri

In our literacy in the pesantren environment, we must also know literacy in Arabic reading-writing pegon. Because the learner pesantren can not be separated from the name of the Arabic reading-writing pegon. Pegon Arabic is an Arabic script or letter with no symbol, punctuation or sound. According to M. Dahlan that the meaning of is bald Arabic script, or Arabic script used to write Javanese. In the Javanese-Indonesian dictionary, means unable to pronounce. Another word pegon means bald or plain while the Arabic letter is used to write translations or meanings expressed in the yellow book using a certain language. While the yellow book in Pesantren literature is the classic religious books of Islam in Arabic, Malay, Javanese or other regional languages using Arabic writing written by jawi scholars printed or written on yellow paper. This report uses theories from Nur Ahmad, Amin Sholekhah Rahayu Ningsih, and Darmadi. The data sources of this report are words and actions, the rest are additional data such as documents and others relating to this type of written data, photos, and statistics. The result of this report is to introduce a change from the Indonesian alphabet, hoping that the new santri can find out the change from the Indonesian alphabet from A-Z and also understand how to cooperate or know how to write the alphabet.Keywords: Pegon, Santri, and Pondok Pesantren
Ten Artificial Human Optimization Algorithms

The term “Artificial Human Optimization” was first coined by the corresponding author of this work in December 2016 when he published a paper titled “Entrepreneur : Artificial Human Optimization” at Transactions on Machine Learning and Artificial Intelligence (TMLAI) Volume 4, No 6 (December 2016). According to that paper published in 2016, Artificial Human Optimization Field is defined as the collection of all those optimization algorithms which were proposed based on Artificial Humans. In real world we (Humans) solve the problems. In the same way Artificial Humans imitate real Humans in the search space and solve the optimization problems. In Particle Swarm Optimization (PSO) the basic entities in the solution space are Artificial Birds where as in Artificial Human Optimization the basic entities in search space are Artificial Humans. Each Artificial Human corresponds to a point in the solution space. Ten Artificial Human Optimization methods titled “Human Bhagavad Gita Particle Swarm Optimization (HBGPSO)”, “Human Poverty Particle Swarm Optimization (HPPSO)”, “Human Dedication Particle Swarm Optimization (HuDePSO)”, “Human Selection Particle Swarm Optimization (HuSePSO)”, “Human Safety Particle Swarm Optimization (HuSaPSO)”, “Human Kindness Particle Swarm Optimization (HKPSO)”, “Human Relaxation Particle Swarm Optimization (HRPSO)”, “Multiple Strategy Human Particle Swarm Optimization (MSHPSO)”, “Human Thinking Particle Swarm Optimization (HTPSO)”, “Human Disease Particle Swarm Optimization (HDPSO)” are applied on various benchmark functions and results obtained are shown in this work.
Establishing Efficient IT Operations Management through Efficient Monitoring, Process Optimization, and Effective IT Policies

Every organization is becoming increasingly reliant on IT that is available, dependable, secure, and high-performing. The ability of an IT team to run its operations efficiently is directly and completely contingent on its ability to deliver resilient IT. The IT team must be able to identify, prioritize, execute, and manage the processes that drive operational tasks and activities in particular. IT teams may reach such goals more efficiently and consistently with the help of effective IT Operation Management processes and solutions. This research attempts how efficiency can be attained. More specifically, we focus on three broad components of efficient IT Operation management: 1) efficient monitoring 2) process optimization 3) and effective IT policies. IT infrastructure monitoring enables the detection of security threats and the resolution of operational issues before they cause harm to clients. We find that there are three significant practices to achieve efficient monitoring. They are: Organizing and Prioritizing Alerts, Providing Processed Data in a Dashboard, and Selecting a Trustworthy Vendor Partner. We also find that there are four challenges in IT infrastructure monitoring: It is sometimes necessary to take a proactive approach; after all, that's what monitoring is all about. Here are some of the most typical monitoring difficulties that businesses, in general, and IT departments, in particular, face: Being beyond monitoring capacity, the ineffectiveness of outdated monitoring applications, increasing prices, and data capacity. IT process optimization technique identifies the most appropriate ways of satisfying an organization's technological and informational needs on a proactive (and non-responsive) basis, with the main goal of supporting it in the long-term development of value. This research also explains discusses forming efficient IT policies such as policies for IT emergency intervention and disaster recovery, Security policies for IT infrastructure.  Efficient IT policies provide information technology transparency for individuals in a business. IT policies assist to counter risks and manage risk while assuring that operations are efficient, effective, and consistent.
Appetite for Disruption: Designing Human-Centred Augmentations to an Online Food Ordering Platform

Online food ordering platforms have changed how many of us purchase takeaway food.They have centralised and streamlined access, providing an opportunity for population-level dietary impact.However, they are currently not human-centred: typically providing limited functionality in support of users' values and dietary considerations; and focused on the provision of food that is broadly characterised as unhealthy.In this paper we explore a redesign of portions of Just Eat, an online takeaway food aggregator, building upon theoretical perspectives from public health.We conducted workshops in 2018 and 2019 to identify user behaviours and motivations then designed a human-centric web augmentation template that could disrupt platform provider behaviours and increase functionality to support users' desires and well-being.We provide a template for lightweight end-user appropriations of food ordering platforms that would enable researchers to explore how health information features could improve individual health and satisfaction, and design guidance for disruptively augmenting existing food ordering platforms (or designing new ones) to enable transparency, personalisation, and self-monitoring to empower users and improve their well-being.
Citizenship and COVID-19: Syndemic effects

This article studies the impact of the COVID-19 pandemic in the domain of citizenship. It highlights how the pandemic enhances existing vulnerabilities and inequalities and thus undermines ideas, concepts and practices of membership, especially for some individuals and groups, and suggests areas where strengthening citizenship may also be a strategy for effective recovery after the pandemic. The article combines reflections on the pandemic, which has triggered crises of governance, public health and economic wellbeing, with an articulation of the idea and ideal of constitutional citizenship, as a place where the symbolism of (in)equality is rife. The urgency of the analysis is driven by the significance that citizenship, as membership, can take on in the context of crisis, especially when it becomes a strong marker of entitlement and belonging. Furthermore, citizenship is not only a legal and socio-economic issue, but also a proxy for political questions about legitimate responses to both a public health emergency and its longer term societal and economic consequences. While the approach is not strictly comparative, the article draws on examples to be found in many different countries, reflecting the global nature of the pandemic.
Adversity and Emotional Quotients of Public Elementary School Heads Amidst the COVID-19

This study aimed to identify the relationship of adversity quotient and emotional quotient amongst public elementary school heads. The study employed a descriptive-correlation research design with the online survey as primary data collection tool. The respondents came from the 25 elementary schools in a Schools Division Office in Central Luzon. 25 elementary school heads participated in the online survey using universal sampling technique. Adapted questionnaires were used to gather data. For the statistical treatment of the study, mean was used for the responses of the school heads; for the relationship, the study used Pearson-r. This paper concluded that the school heads’ Adversity Quotient (AQ) score falls within “above average,” which indicates above normal capacity for challenges, difficulties, setbacks, and demands. In terms of emotional quotient, all factors involved in emotional intelligence like self-awareness, managing emotions, motivating oneself, empathy, and social skill all “apply” to school heads. In addition, there exists a significant relationship between adversity quotient and emotional quotient of public elementary school heads. Based on the aforementioned results, the researcher provided some important recommendations for the study.