Reviewerly/exHarmony huggingface dataset:
Gendering Algorithms in Social Media

Social media platforms employ inferential analytics methods to guess user preferences and may include sensitive attributes such as race, gender, sexual orientation, and political opinions. These methods are often opaque, but they can have significant effects such as predicting behaviors for marketing purposes, influencing behavior for profit, serving attention economics, and reinforcing existing biases such as gender stereotyping. Although two international human rights treaties include express obligations relating to harmful and wrongful stereotyping, these stereotypes persist both online and offline, and platforms often appear to fail to understand that gender is not merely a binary of being a 'man' or a 'woman,' but is socially constructed. Our study investigates the impact of algorithmic bias on inadvertent privacy violations and the reinforcement of social prejudices of gender and sexuality through a multidisciplinary perspective including legal, computer science, and queer media viewpoints. We conducted an online survey to understand whether and how Twitter inferred the gender of users. Beyond Twitter's binary understanding of gender and the inevitability of the gender inference as part of Twitter's personalization trade-off, the results show that Twitter misgendered users in nearly 20% of the cases (N=109). Although not apparently correlated, only 8% of the straight male respondents were misgendered, compared to 25% of gay men and 16% of straight women. Our contribution shows how the lack of attention to gender in gender classifiers exacerbates existing biases and affects marginalized communities. With our paper, we hope to promote the online account for privacy, diversity, and inclusion and advocate for the freedom of identity that everyone should have online and offline.
SISTEM INFORMASI PASIEN POSYANDU PADA POSKESDES KALIMAS

The Kalimas poskesdes is one of the government agencies engaged in health, the Kalimas poskesdes are under the auspices or working areas of the Snapper river puskesmas, one of the health services routinely carried out by the Kalimas poskesdes is the Posyandu activities which are conducted every month. Data from each posyandu is managed solely by the poskesdes kalimas and then reported to the snapper river puskesmas, baby and toddler data collection still uses bookkeeping while making reports using Microsoft excle is still fairly simple, so it requires a lot of time in making reports due to repeated data recording. To help the data collection process, the Posyandu Patient Information System was created. Posyandu Patient Information System At Kalimas Poskesdes is a web-based information system. Help provide and present information about infants and toddlers patients who do posyandu in the work area of the poskesdes kalimas. Making this information system using the waterfall software development method and the way to collect data is by observing the Kalkesas poskesdes, interviewing staff working at the Kalimas poskesdes, a literature study that supports the theory of problem solving. The software used in making the Posyandu Patient Information System in Kalimas Posasdes Web-Based is XAMPP as a server, MySQL as a database, Sublime Text as a text editor, Chrome as a browser. While the languages used in making this posyandu patient information system are, PHP, HTML, CSS, JavaScript. And to facilitate the creation of the website also uses a codeigniter framework.
Technology Entrepreneurship : Comb Sprayer / Ameerah Mansor ...[et al.]

Hair care is an overall term for hair treatment involving the process of brushing hair and the usage of hair serum or oil which responsible for maintaining the heath and beauty of hair. Hair care services are offered in salons, barbershop and day spas, and the products are also available commercially for home use. The beauty centre like salon needs the product that can help them to make their work easy and efficient. Therefore, the A's company has produced the comb sprayer in order to solve their problem. However, this product has to complete to the other company that have the same feature of the product. Therefore, the comb spray has come with variety of designs and also functions to attract more consumers. There are also a few problem with the current products in the market in a few aspects. The price and functions is mostly people pointing out as the issue. Comb sprayer with manual function of course comes with affordable price but the function is too simple yet far from being convenient. The one with automatic function, on the other hand, is quite expensive. So most of the people cannot afford it even though the system is really efficient. Comb sprayer has been buit to cater with the problem as it offers an affordable price, convenient and most importantly, it is simple to use.
LibGuides: Research Help: 6. Research it!

Use this guide to help you learn about research and perform research yourself for both academic and leisurely activities.
Exploratory Data Analysis and Data Summarization

Abstract The third chapter introduces the dataset that readers will work with for the remainder of the book: the RxP data. Students are taught how to import the data and how to use indexing and packages like dplyr to navigate this large, real, and somewhat messy set of ecological data. Basic plotting is introduced as a tool for exploratory data analysis. Lastly, students are taught how to summarize a dataset quickly and efficiently.
Anomaly Detection Method for Spacecraft System Based on High Dimensional Space Mapping

Abstract Spacecraft system, as a typical complex system, is also a high-risk field. Even small faults in local links may bring huge losses or disasters. Analyzing the system level associated anomaly detection method caused by the interaction of multiple telemetry parameters can provide technical means for the rapid and accurate detection of system level in orbit associated faults. In this paper, firstly, a system anomaly detection method based on high-dimensional space mapping is proposed. Secondly, based on the preprocessing of telemetry data, the division of telemetry subsystem is realized. Thirdly, Based on the dimension reduction of subsystem space, the system anomaly detection method is given, and the technical process of the method is given. Finally, through the verification of on orbit actual data, it shows that the system anomaly detection result is accurate.
Contact Tracing Tool of COVID -19 for India and Ethiopia using Blue-trace Protocol in Android Mobile

Contact tracing is an important tool for reducing the spread of infectious diseases. Its goal is to reduce a disease’s effective reproductive number (R) by identifying people who have been exposed to the virus through an infected person and contacting them to provide early detection, tailored guidance, and timely treatment. By stopping virus transmission chains, contact tracing helps “flatten the curve” and reduces the peak burden of a disease on the health-care system. Contact tracing forms an essential part of Ethiopia and India response to the COVID-19 pandemic. This proposed technical specification for a new privacy-preserving Bluetooth protocol is used to support Contact Tracing and makes it possible to combat the spread of the COVID-19 virus by alerting participants of possible exposure to someone who they have recently been in contact with, and who has subsequently been positively diagnosed as having the virus. The Contact Detection Service is the medium for contact tracking and uses the Bluetooth LE (Low Energy) for nearby smart-phone proximity detection and data sharing mechanisms. Technology (BLE), which has been available in today's smart phones for many years, has proven to be the only way to determine the proximity to other smart phones. In our proposed model, firstly we developed the tracing cloud function and android app which is a privacy-preserving protocol for community-driven contact tracing across borders. It allows participating devices to log Bluetooth encounters with each other, in order to facilitate epidemiological contact tracing while protecting users’ personal data and privacy, finally We developed Tracing calibration data and trial methodologies for testing implementations of Bluetrace protocol.
A Hybrid Recommender System Using Bio Inspired Clustering Technique For Top N Item Recommendation

Now, we all are living in the information rich world, people depend on technologiesfor their everyday activities. The technologies and its massive growth give rich set ofbenefits and services to the users. The entire world is running towards digitization. Thepeople, company, organizations and institutions are making their everyday activities in digitalform. The growth of digitization gives better solution for information search.But, on the other end, people struggle with information overloaded. We are finding difficultto get the desired information from the internet. Sometimes it is a great challengeto get the wished data from the internet. This is the reason behind the research inrecommendation and invention of recommender systems. A smart recommendersystem provides better solution for information search and its related issues. Manyrecommender systems and tools are widely used by the e-commerce applications, but theaccuracy of the tools still needs improvement. The previous research in thearea of recommendation comes under collaborative filtering, user content searchand by combining the best of the above mentioned. The proposed work focuses on thecombination of the first two methods which are mentioned earlier. This research attemptsto utilize the possible features of the two clustering techniques to achieve the user interestprediction. The item ratings are the major parameters taken for evaluating theefficiency of the proposed work. The data set are taken from Imdb database(www.imdb.com) and MovieLens dataset to test the accuracy of the proposed system.
Enhancing Retention of Water Pollution using Computer Tutorial and Drill Practice among First Year Science Education Students of University of Uyo, Nigeria

Students need supportive, empowering and enabling technology-driven environment to make learning interesting and retentive. Water pollution is a major threat to the environment and students' knowledge of the hazards is crucial to their management of the environment using digital devices effectively. Computer tutorial and drill practice were employed to investigate learners' retention of water pollution. Three research questions and three hypotheses guided the study. The study was quasi-experimental of non-randomized pretest, posttest control group design with students in intact classes. Population and sample size of the study was all 210 first year science education students of university of Uyo, 2018/2019 session using purposive sampling technique. Retention Test was the instrument used to collect data for the study. Instrument validation was done by three lecturers of test, measurement and evaluation in Science Education Department. Reliability index was .81 obtained using Kuder-Richardson Formulae-21. Data was analyzed using mean and standard deviation to answer research questions and Analysis of Covariance for hypotheses formulated at .05 level of significance. Findings showed that students taught water pollution using computer tutorial achieved and retained higher than students taught using computer drill-practice and lecture strategies. Gender was not a significant determinant of students' retention, though female students retained slightly higher in their mean retention scores than male students using drill-practice strategy. Based on the findings, it is concluded that computer tutorial is the most effective strategy in enhancing students' retention on water pollution. It is recommended amongst others that science teachers adopt computer tutorial as well as computer drill-practice strategies in teaching science concepts.  Keywords: computer tutorials, drill-practice, water pollution, retention, enhancing
Design of Management Information Systems Inventory at School Computer Laboratory Web-Based with Waterfall Methods

Currently, many schools have used computer technology; one of the goals of computer technology is to help increase effectiveness by producing information systems. An inventory inspection information system is very suitable for schools because it makes it easier for computer laboratory officers to manage the available inventory. Computer laboratory officers are expected to quickly and accurately obtain information related to available inventory. Students will no longer experience disappointment when they want to use the available computers because, with this inventory inspection information system, computer laboratory officers can easily check available items. This type is applied research with a qualitative approach. The waterfall method obtains its title from the rung-step fashion by which deployed events ongoing from one phase to another. The final results are: the resulting system is an inventory management information system in a web-based computer laboratory using PHP, HTML, and CSS programming languages. For databases using MySQL with the creation of this system, the authors hope to help computer laboratory staff and schools manage inventory in computer laboratories.
Blockchain, GDPR, and Fantasies of Data Sovereignty

Like the European Union’s General Data Protection Regulation (GDPR), the broader, mainstream emergence of blockchain technology in the present moment of, what I call, data dysphoria is no accident. It is in part reaction to data dysphoria, and in part exploitation of it, a duality underpinned by the tantalising promise of the prosumer ‘taking control’ of their data and establishing sovereignty over it. Blockchain and GDPR alike aim to resolve ‘problem’/’solution’ matrices with deep roots in a wide variety of global economic, political, social, legal and cultural contexts. This article explores the problem of achieving resolution based on innovation and technology by offering an account of the rise of blockchain and implementation of GDPR within a psycho-political framework, one in which fantasies of taking control are predominant yet highly contestable actualities in the lives of technology users.
AN ANALYSIS OF DIRECT AND INDIRECT SPEECH ACTS ON TWEETS NCT (NEO CULTURE TECHNOLOGY) TWITTER ACCOUNT

Nirmala, Anindita. 2020. An Analysis Of Direct And Indirect Speech Act On Tweets NCT (Neo Culture Technology) Twitter Account. A Graduating Paper, English Education Department, Teacher Training and Education Faculty, State Institute for Islamic Studies Salatiga. Counselor: Mrs. Sari Famularsih, S. Pd. I., M. A.This research was conducted in order to find out speech act that used on tweets NCT (Neo Culture Technology) twitter account. The first objective of this research is finding out the type of speech act are produced on tweets NCT (Neo Culture Technology) twitter account and the second objective is finding out the dominant type of the speech act especially direct speech act and indirect speech act on tweets NCT (Neo Culture Technology) twitter account. The method of this research was a qualitative approach with descriptive-analytical. The data were analysed using several theories, namely the theory of direct and indirect speech acts study, and classic theory of speech acts. The object of this study were direct and indirect speech acts on the tweets NCT (Neo Culture Technology) which hastag #Beyond_the_Dream_Show.The result of the research is the researcher took 12 tweets according the hastag #Beyond_the_Dream_Show where the 7 tweets were a thread which contains direct and indirect speech acts. Totally the researcher found 17 direct speech act, and 4 indirect speech act. Keywords: Direct-Indirect Speech Acts, Neo Culture Technology, Twitter Tweets.
Copyright Protection for Artificial Intelligence Output - Considerations de lege lata and de lege ferenda under Swiss law

The aim of this thesis is to examine whether paintings, music or texts produced by Artificial Intelli- gence (AI output) are protected under Swiss copyright law de lege lata and whether these should be protected de lege ferenda. Firstly, the basics of AI generated output are examined and classified under Swiss copyright law. Secondly, the classification is analyzed on a comparative legal basis. Thirdly, different lines of argument for and against the protection of AI output are discussed and different im- plementation options are considered. The result of these analyses shows that AI output de lege lata does not enjoy copyright protection in Switzerland because AI output does not have sufficient human input and therefore the definition of a work is not met. There are various arguments for and against the copyright protection of AI output, as well as ways in which a protection could be implemented. For Switzerland de lege ferenda there is a good argument for granting copyright protection to AI output based on incentives and practicability arguments, even if this is associated with a paradigm shift away from the human centricity of Swiss copyright law. Furthermore, it is argued here that the best solution is to assign the copyright to the user of the AI.
Continuous-variable error correction for general Gaussian noises

We design continuous-variable error correction codes for general correlated and heterogeneous Gaussian noises, based on Gottesman, Kiteav and Preskill states and Gaussian operations, and numerically verify the codes’ performance on random samples.
Bootstrapping a Data-Set and Model for Question-Answering in Portuguese (Short Paper)

Question answering systems are mainly concerned with fulfilling an information query written in natural language, given a collection of documents with relevant information. They are key elements in many popular application systems as personal assistants, chat-bots, or even FAQ-based online support systems.This paper describes an exploratory work carried out to come up with a state-of-the-art model for question-answering tasks, for the Portuguese language, based on deep neural networks. We also describe the automatic construction of a data-set for training and testing the model.The final model is not trained in any specific topic or context, and is able to handle generic documents, achieving 50% accuracy in the testing data-set. While the results are not exceptional, this work can support further development in the area, as both the data-set and model are publicly available.
Heeding the Call for Objective Investigation into Blockchain Adoption: An Empirical Analysis of the Partial Open vs. Completely Open Blockchain Tension

The empirical framework exists to test the proposition, “Does the extent of blockchain openness positively affect the willingness to adopt a platform?” We can compare a partially open blockchain like EOS with a more open platform like Ethereum. Both fund-raised by issuing cryptocurrencies through ICO’s (Initial Coin Offerings). We collect extensive longitudinal data to determine the impact of blockchain openness on an objective performance measure — the price of the relevant cryptocurrency and several blockchain performance measures (e.g. scalability, security, throughput, etc.) Given that likelihood of widespread platform adoption is closely correlated with relative cryptocurrency price out-performance (Zhang 2019), this measure is not an unreasonable aggregate measure of adoption willingness by organizations (or individual users). We aim to use robust econometric causal inference designs to offer more granular insights as well, namely when a blockchain platform undergoes a regime change from completely open to partially open, or vice versa, how does that impact adoption willingness. We believe that our research will help inform these decisions for practitioners and break new theoretical grounds for IS research’s longstanding interest in the open vs close tension in digital platforms.
Emerging from the shadows: survey evidence of shadow it use from blissfully ignorant employees

Current research dealt with various aspects of Shadow IT. However, we still do not have an evidence of how much the phenomenon is widespread in organizations. Are employees really using Shadow IT and how much? We conducted an online survey of 450 employees in 5 organizations to understand how much Shadow IT is used by employees. Our research found that Shadow IT phenomenon is widespread in the organizational context. We found that 52% of “Blissfully ignorant” employees, despite their 75% awareness of information security policy, do use Shadow IT to satisfy their job needs, increase their productivity and efficiency. These illegal activities are conducted as employees miss clarity on the proper compliance behaviors regarding Shadow IT but also because they believe that IT department cannot meet their needs in terms of the approval speed. Our study has several important insights for practitioners and offers some future directions for researchers.
Efficient Hamming Code Encoder & Decoder Using True Random Number Generator

In this paper, True random number generator (TRNG) based Hamming code encoder and decoder circuit is designed based on Gate Diffusion Input (GDI) logic to achieve error free transmission and reception in digital data communication. It is better to generate the random numbers by using the TRNG frameworks. In the existing, several works are focused on implementation of TRNG by using CMOS technology.  But they consume the greater number of transistors, thus area, power consumption and delay were increasing. To overcome this problem, the TRNG based Hamming Encoder-Decoder is developed with the GDI technology.  The GDI-TRNG will be functioned based on the switchable ring oscillators (SCRO. The simulations are implemented by using the H-spice software, the quantitative analysis of area, power and delay shows the GDI outperforms compared to the state of art approaches.
Energy efficient and robust reservoir computing system using ultrathin (3.5 nm) ferroelectric tunneling junctions for temporal data learning

Reservoir computing (RC) can compute temporal data with low training cost. To enhance data processing capability, high dimensionality of reservoir is required, which poses a significant challenge on RC hardware implementation using Si-friendly devices. In this work, for the first time, we use ultra-thin (3.5 nm) ferroelectric tunneling junctions (FTJs) with transient depolarization property as physical nonlinear virtual nodes to address this challenge. By constructing an FTJ-based dynamic reservoir and combining it with RRAM-based binarized readout layer, the high energy efficiency (35 pJ), processing speed (500 ns), and recognition accuracy (92.3%) have been demonstrated for digital sequence classification.
Novel Method to Achieve Data Integrity Auditing In Cloud Server

In current day’s cloud computing has become one of the fascinating domains which are used by almost all MNC and IT companies.Using cloud storage services, users can store their data in the cloud to avoid the expenditure of local data storage and maintenance. To ensure the integrity of the data stored in the cloud, many data integrity auditing schemes have been proposed. In most, if not all, of the existing schemes, a user needs to employ his private key to generate the data authenticators for realizing the data integrity auditing. They require a physical device to authenticate the identity by using third party devices like smart card or some token generators. If this token generator or smart card is lost or this password is forgotten, most of the current data integrity auditing schemes would be unable to work. In order to overcome this problem, we propose a new paradigm called data integrity auditing without private key storage and design such a scheme. In this scheme, we use biometric data (e.g. iris scan, fingerprint) as the user’s fuzzy private key to avoid using the hardware token. The security proof and the performance analysis show that our proposed scheme achieves desirable security and efficiency.