Reviewerly/exHarmony huggingface dataset:
Attacking and Defending Multiple Valuable Secrets in a Big Data World

This paper studies the attack-and-defence game between a web user and a whole set of players over this user’s ‘valuable secrets.’ The number and type of these valuable secrets are the user’s private information. Attempts to tap information as well as privacy protection are costly. The multiplicity of secrets is of strategic value for the holders of these secrets. Users with few secrets keep their secrets private with some probability, even though they do not protect them. Users with many secrets protect their secrets at a cost that is smaller than the value of the secrets protected. The analysis also accounts for multiple redundant information channels with cost asymmetries, relating the analysis to attack-and-defence games with a weakest link.
Precision improvement of gaze estimation based on deep learning

Various gaze estimation methods have been proposed, but they have not been evaluated well in random environment, and their estimation accuracy are not sufficient. We developed a gaze estimation method using convolutional neural network based on left and right eye images. In addition, we evaluated the present method with a cross-dataset evaluation using MPIIGaze and performed cross-validation using a dataset of eye images obtained in unrestricted daily settings. The results of this study are summarized as followings. First, we created a learning machine model that estimates the gaze direction of each of the left and right eyes from both eyes images, using a convolutional neural network. The accuracy was 10.3°, which was equal to or greater than the previous excellent gaze estimation method. Second, we compared the model with the input of both eyes and the model with the input of one eye. As a result, it was found that the accuracy of the model using both eyes images was 54.2% better than the accuracy of the model using one eye image. Furthermore, it was found that the accuracy especially in the horizontal direction was improved. Finally, in the cross-dataset evaluation, the accuracy in the vertical direction is better than the horizontal direction, which is different from the result that the horizontal direction is generally better than the vertical direction. On the other hand, the within-dataset evaluation showed the opposite result. It is indicated that the vertical estimation in the proposed method is more flexible to environmental variations than the horizontal estimation.
The Variation of the Atomic Radius with the Universal Density of Potential Energy

After learning that ρ (Universal Density of Potential Energy), varies from one place to another, causing a change in the time measured in the clocks, inversely proportional to the square root of the value of ρ, Ref. [1], and that in expanding universe, locally, Universal Density of Potential Energy will decrease in the inverse proportion of that expansion. This decrease increases the G value indicating that the less the Universal Density of Potential Energy, the better the gravitational radiation occurs, thus causing its increase in the direct proportion of the expansion of the Universe, Ref. Following the same principle, the Magnetic Permeability of the Vacuum should also increase, allowing a better propagation of electromagnetic waves. The increase in this permeability will allow greater action by the nuclei of the atoms on the electrons. Applying the expression of the atomic ray through quantum mechanics, we conclude that the size of the atoms will decrease with the expansion of the Universe, that is, it will vary in the inverse proportion of that expansion. This finding also implies that the stars are shrinking, which requires a New approach to the removal of the Moon from the Earth. The age of the Universe. Hubble Constant, Ref. [1].
Mobile Learning via Educational Apps: An Interpretative Study

This research explains the rationale behind the utilisation of mobile learning technologies. It involves a qualitative study among children to better understand their opinions and perceptions toward the use of educational applications (apps) that are available on their mobile devices, including smartphones and tablets. The researchers organised semi-structured, face-to-face interview sessions with primary school students who were using mobile technologies at their institution. The students reported that their engagement with the educational apps has improved their competencies. They acquired relational and communicative skills as they collaborated together in teams. On the other hand, there were a few students who were not perceiving the usefulness and the ease of use of the educational apps on their mobile device. This study indicates that the research participants had different skill-sets as they exhibited different learning abilities. In conclusion, this contribution opens-up avenues for future research in this promising field of study.
A Development Method of Web System Combining Service Oriented Architecture with Multi-Software Product Line

As software systems become more complex and larger, software systems require a way to reuse software components or modules to provide new functionality. This paper designed a development method of web system combining SOA(Service Oriented Architecture) with MPSL(Multi-Software Product Line). According to provides SOA and MPSL, this paper suggested to service providers and service users to provide and reuse variable services. From the viewpoint of service provider, the suggested method identifies and implements reusable variable services as features by syntax-based, functional-based, and behavior-based methods applying feature identification guidelines and manages them as reuse assets. From the user's point of view, it is possible to develop a web system by constructing a service by workflow model as a method of structure and reconfigure services. As a result of measuring the reuse of the web system constructed in this paper by the function point, the cost reduction effect was verified by applying it to the similar project with the increase of reuse.
Similarity Analyses of Modal Auxiliaries using Distributional Representation

This paper attempts to measure the similarity of frequently occurring modal auxiliaries in both L1 and L2 writings. The modal auxiliaries are known to be difficult areas of study for both L1 and L2, due to the overlapping in their use. A subset of TOEFL11 corpus and a subset of PTB(Penn Treebank) corpus were used to capture the similarities among modal auxiliaries within L1 and L2, respectively, and also across L1 and L2. Based on the hypothesis of distributional representation, similarities of modal auxiliaries were computed by applying cosine similarity and mutual information to every pair of words in the corpus, and then finally reducing dimensions with Singular Value Decomposition. The results show that the modals are found to be similar to other modals, and the distribution of modals in the reduced dimensions show that the modals in L1 and those in L2 exhibits different patters of similarities, while the distance among the modals in L1 is further away than the distance among those L2 modals.
Constructivist Teaching Experiment: Constructivist Research and Constructivist Teaching

The aim of the discussion is twofold: first, we formulate and present examples of the creative bisociativity inherent in teaching-research TR/NYCity model (Section 1). Second, we bring the creative model of teaching-research as the precise solution to the difficulties experienced by Common Curriculum Standards in Mathematics (CCSM). Section 2 analyzes the reason for extraordinary difficulties in successful introduction of the curriculum into practice, which manifest themselves among others, by the necessity of scripted lessons telling teachers exactly what to do in all different moments of the lesson time. The root reason for the contemporary difficulties is the absence of teachers involvement in the design process It is in contradiction with the irreducible presence of teaching within the central constructivist instrument of research- constructivist teaching experiment of Cobb and Steffe (1983).
GLUECode: A Benchmark for Source Code Machine Learning Models

A multitude of machine learning models for source code have been proposed in the recent years capturing various aspects of the inherent rich structure and semantics of code. However, these models are commonly designed to perform well on a single task, failing to capture code's multifaceted nature. To address this, we present GLUECode, Global and Local Understanding Evaluation of Code, a benchmark of diverse tasks to evaluate machine learning models of source code. Crucially, GLUECode accounts for the distinct characteristics of source code: (1) source code is highly structured and (2) source code is often composed of multiple interacting entities. Existing tasks incentivize researchers to create models and code representations that perform well on a single task - commonly focusing on local reasoning. GLUECode aims to allow researchers to experiment with multiple local and global source code representations, and evaluate these models on their ability to capture the diverse characteristics of source code, thus driving the community towards building robust source code models incorporating global reasoning. We present results for several baselines. The GLUECode tasks are challenging for the evaluated baselines; no model achieves convincing performance across all tasks. This indicates that there is ample room for progress on GLUECode.
IMPLEMENTASI SISTEM INFORMASI PEMESANAN MAKANAN BERBASIS WEB

In recording food and beverage transactions, Pizza Ala Piazza has not separated general transactions from online ordering transactions, so it is difficult to create reports. So the research conducted at Pizza Ala Piazza aims to be able to provide clear information about the Transaction process data and ensure the smooth running of reports that can support work activities at Pizza Ala Piazza. In conducting research, a development method is used with a system or waterfall life cycle development model in order to produce a food ordering information system at Pizza Ala Piazza. So it can be concluded that with this web-based food ordering information system, it can produce sophisticated technology, it is easy to prepare reports that are faster and more accurate, data storage is more accurate, data storage is a lot and produces information that is more accurate, relevant and easy to retrieve. decision.
Quantitative analysis of the kowangan resonator

This paper presents a quantitative analysis of the kowangan, a shield-shaped resonator used in the bunden- gan, a bamboo-based musical instrument from Indonesia. The kowangan resonator is made from a woven lattice of bamboo splits, covered with layers of bamboo sheaths, and then secured with palm sugar fibers. To gain insight into how this resonator works, it is required to first determine the shape of the resonator. Previously, we have developed a computational model of the resonator shape, where the distribution of curvatures in the resonator surface is driven by the minimization of potential bending energy in the woven lattice of bamboo splits. In the present study, we report the latest development in this work, where we have designed and built an optical imaging setup to measure the actual shape of a real kowangan resonator. Our measurement data allows for further improvements on our computational model, and consequently a deeper insight into the physics of the kowangan. The ultimate aim of this study is to build a full virtual prototype, not only of the kowangan resonator, but also of the whole bundengan instrument, which will be useful for the conservation and documentation of this endangered cultural heritage.
Sensorless Direct Torque Control of an Induction Motor Using Fuzzy Controller.(Dept.E)

In this paper direct torque control DTC of an induction motor is developed. A new technique for DTC based ou fuzzy logic concept is proposed, where fast torque response with low ripple in the stator lux and torque of induction motor can be achieved. In comparison with the conventional DTC şimulation results clearly demonstrate a better dynamic and steady state performance with the fuzzy logic DTC. The two approaches are explained in clear details, which are designed using SIMULINK under Matlab Ver.6 software package. Also, MATLAB/FUZZY toolbox is used to implement the fuzzy logic controller. Both systems are simulated under the same conditions.
Fear the Reaper: How Content Moderation Rules are Enforced on Social Media

This paper investigates the enforcement stage of the content moderation process on social media platforms. It argues that the current approach adopted by most platforms is underdeveloped, poses serious human rights issues, and would benefit from a number of reforms. The enforcement stage is arguably the most important stage in the moderation process because it has the most impact on what content is available and how the platform is governed. The enforcement stage is also where the concerns over private companies regulating the exercise of free expression online are at their more pronounced. This will be a central theme throughout the paper as it is a troubling situation despite laws like the Network Enforcement Act in Germany and decisions such as Google Spain requiring platforms to take on an increasing number of legal assessments. This paper will first explain what the role of the moderator entails and how the enforcement process occurs at social media platforms. The investigation will then turn to the enforcement process itself and identify a number of problems in how content rules are generally enforced. It will consider bias in decision-making, a problem that exists for both human and algorithmic moderators. This paper will use the example of blood and how menstrual blood is treated by platforms as infinitely more objectionable than blood resulting from graphic violence or serious accidents (despite it being a normal aspect of women’s health). This differential treatment stems from the rules created by a male-dominated Silicon Valley, which embodies a particular form of cultural bias. Then the paper will examine over-reliance on efficiency as a solution, where platforms respond to controversies by offering solutions that promise enhanced speed or technical effectiveness without addressing the underlying issues. For example, platforms often fixate on how fast content can be removed after it is posted, a narrative that this paper will argue has also influenced political discussions around social media. The paper will move on to investigate the inconsistent enforcement of terms and conditions, which increases user uncertainty and raises concerns that some narratives are being privileged over others. For example, the Facebook Files leak featured multiple slides prohibiting any positive statements about the Irish Republican Army (the IRA) but no accompanying slides indicating that the same treatment should be applied to other para-military groups from Northern Ireland. Finally, it will provide a number of suggestions for reform such as the adoption of a body of precedents as a tool for accountability and empowerment of users. This should be publicly accessible and would contain anonymised case-studies to help users understand what is and is not acceptable. It will also recommend moving away from the efficiency narrative to consider larger issues in enforcement (which are not so easily solved) such as human rights and rule of law issues, and more emphasis on trouble-shooting problems before they become major scandals.
SENTIMENT ANALYSIS OVER TWITTER BIGDATA USING MODIFIED MEANSHIFT CLUSTERING ALGORITHM

The amount of digital data that exists is growing at a rapid rate, doubling e very two years. A huge repository of terabytes of data is generated each day and analysis of these massive data requires a lot of efforts to extract knowledge for decision making. This means we need to have the technical tools, algorithms, and models to clean, process, and understand the available data in its different forms for decision-making purposes. The aim of this work is to develop a clustering technique to extract relevant information from unstructured Bigdata. Twitter is one of the important and popular social media where people may express their views/opinions or emotions freely. Thus, twitter is some of the central source of Bigdata and taken as the dataset. Cluster based techniques on sentiment analysis is a novel approach for analyzing sentiments expressed in social media sites. This paper presents the analysis of twitter feeds by implementing the algorithms Bisecting K Means, basic Meanshift algorithm and its modified form Gaussian mixture model based Meanshift and a comparison is made with these methods based on metrics namely accuracy, precision, recall and F1 score. For analyzing thedata, Python programming and PySpark DataFrame was used. The experiments perform on big data of tweets from a dataset of one lakh and show that the work provides an accuracy of 87% on detecting whether a tweet is ―positive‖, ―negative‖, or ―neutral‖.
Political Institutions and Corporate Transparency in Emerging Economies

Corporate transparency is essential to reducing investor uncertainty and attracting foreign investment. Although firms operating in emerging economies vary widely in the degree of their corporate transparency, existing theories have difficulty accounting for this. We argue that whether a country possesses a legislature with multiple political parties will influence the level of corporate transparency for firms operating in that country. We predict that firms located in political regimes which lack legislatures (non-competitive authoritarian regimes) will have a lower level of transparency than those in regimes with semi-competitive legislative elections (semi-competitive authoritarian regimes), and these in turn will have lower transparency than firms located in countries with competitive elections (democracies). We further predict corporate transparency will vary among semi-competitive authoritarian regimes depending on whether the ruling party is weakly or strongly dominant. Results from a sample of 226,088 firm-level observations from 81 countries over the period 1990–2014 support our hypotheses.
Analog environment vs. digital communications

In this article, I discuss problems associated with new technologies, digital communications and the future of analog interaction models. I also analyze the development possibilities of artificial intelligence and neural networks based on analog computhttping systems. The transformation today, involves a radical change in existing models and the rediscovery of the benefits of some traditional approaches, which in another context can be much more effective than existing information and digital tools. In this case, it is the analog approaches of quantum computing in combination with new technologies that lead to better results, development of society and the creation of a more human environment.
Development of a Mobile Learning Application of Malay Vocabulary for Lower Secondary School Level

Modern technology has become an integral part of education field. Undeniably, the use of multimedia technology has a major impact on teaching and learning (T&amp;L) process of the new generation. This article focuses on designing and developing a mobile learning application of Malay vocabulary for lower secondary school level. The design and development of the application called “Kuasa Kosa Kata” (3K henceforth) was based on a novel entitled “Sejambak Bakti”. The context of this study is closely related to game-based learning (GBL) method in the 3K application that encourages independent learning among the targeted students. Designing the 3K application was based on a storyboard for the idea and story-making whilst the development of it was done using Adobe Flash. The data on participants’ comments and opinions on the learning application were qualitatively gathered from semi-structured interviews. As conclusion, focus is on the importance of game-based learning implementation in the development of mobile learning application. It is hoped that use of 3K application as teaching material will boost the mastery of Malay Language vocabulary among lower secondary school students.
Mining Developer Questions about Major NoSQL Databases

NoSQL databases are quickly becoming more and more popular among developers.While RDBMS is still the most popular, the NoSQL camp is closing in the gap.To bridge this gap, we aim to carry out the first empirical software engineering research on NoSQL databases using Stack Overflow posts.Being one of the leading question-answering sites available, Stack Overflow has become a helpful resource in numerous software engineering research.In this paper, we chose five NoSQL databases, MongoDB, Cassandra, Redis, Neo4j, and HBase, based on their popularity and the increasing number of posts on Stack Overflow.We extracted the relevant questions and investigated different challenges and issues faced by the developers of NoSQL databases and the various domains the NoSQL databases are used by mining questions asked on Stack Overflow.We sorted the issues by popularity and difficulty metrics and observed the different nature of difficulty and popularity.We found that connection issues and integration are the most common difficult issues the developer of NoSQL databases faced.We also found that Cassandra, HBase, and Neo4j are very popular among Java developers, MongoDB and Redis are very popular among node.jsdevelopers, and Cassandra and HBase are very popular for big data systems.Our findings will help better understand the challenges, requirements, and specific applications of the NoSQL databases.
LibGuides: Kentucky Christian University's Young Library Great Lakes Lighthouses Virtual Vacation: Day 1 - All About the Coast Guard

A virtual trip in the Great Lakes area where you go on virtual tours of lighthouses and museums, read fiction and non-fiction materials about the area, explore local area favorite recipes, and watch movies about lighthouses. Travel day - Start to prepare by learning more about the US Coast Guard
La Dimensión Socioemocional de la Competencia Digital en el marco de la Ciudadanía Global

The accelerated advance of digital technologies has generated the transmutation from being citizens of a nation to being citizens of the world. In the educational field, this global citizenship has a significant expression in virtual learning environments, as interactive spaces that require collaboration and communication between the actors of the educational process to achieve relevant learning. For this, the development of digital competence is required from a perspective that transcends the technical or operational use of technologies, and places emphasis on socio-emotional aspects that stimulate the teaching-learning process mediated by ICT. In this sense, the study present is specified in a documentary research that reveals the importance of empathy and conflict resolution as essential aspects of the socio-emotional dimension of digital competence in the framework of global citizenship, and its impact on the achievement of relevant learning in virtual environments, dynamized by multiple training alternatives that are identified and systematized, with the intention of offering it as a tool to the educational community.