Reviewerly/exHarmony huggingface dataset:
Virtual machine allocation strategy in energy-efficient cloud data centres

Energy consumption is significant in cloud data centres even when some virtual machines (VMs) are idle. Taking into account both the energy efficiency and the response performance, we propose a VM allocation strategy with speed switch and VM consolidation in the cloud data centre. When the traffic is lighter, the processing speed of VMs in baseline module will be switched between a low speed and a high speed. When the traffic is much heavier, the VMs in reserved module will be consolidated with the VMs in baseline module, and operates at a high speed. We establish a two-dimensional Markov chain to mathematically estimate the energy-saving degree and the response performance. Numerical experiments with analysis and simulation show that our proposed VM allocation strategy can effectively reduce the energy consumption as well as guarantee the response performance.
Routing for RPL Leaves

This specification leverages 6LoWPAN ND to provide a unicast andmulticast routing service in a RPL domain to 6LNs that do notparticipate to RPL.
Automatic Classifiers as Scientific Instruments: One Step Further Away from Ground-Truth

Automatic machine learning-based detectors of various psychological and social phenomena (e.g., emotion, stress, engagement) have great potential to advance basic science. However, when a detector $d$ is trained to approximate an existing measurement tool (e.g., a questionnaire, observation protocol), then care must be taken when interpreting measurements collected using $d$ since they are one step further removed from the underlying construct. We examine how the accuracy of $d$, as quantified by the correlation $q$ of $d$'s outputs with the ground-truth construct $U$, impacts the estimated correlation between $U$ (e.g., stress) and some other phenomenon $V$ (e.g., academic performance). In particular: (1) We show that if the true correlation between $U$ and $V$ is $r$, then the expected sample correlation, over all vectors $\mathcal{T}^n$ whose correlation with $U$ is $q$, is $qr$. (2) We derive a formula for the probability that the sample correlation (over $n$ subjects) using $d$ is positive given that the true correlation is negative (and vice-versa); this probability can be substantial (around $20-30\%$) for values of $n$ and $q$ that have been used in recent affective computing studies. %We also show that this probability decreases monotonically in $n$ and in $q$. (3) With the goal to reduce the variance of correlations estimated by an automatic detector, we show that training multiple neural networks $d^{(1)},\ldots,d^{(m)}$ using different training architectures and hyperparameters for the same detection task provides only limited ``coverage'' of $\mathcal{T}^n$.
Efficient learning of smooth probability functions from Bernoulli tests with guarantees

We study the fundamental problem of learning an unknown, smooth probability function via pointwise Bernoulli tests. We provide a scalable algorithm for efficiently solving this problem with rigorous guarantees. In particular, we prove the convergence rate of our posterior update rule to the true probability function in L2-norm. Moreover, we allow the Bernoulli tests to depend on contextual features and provide a modified inference engine with provable guarantees for this novel setting. Numerical results show that the empirical convergence rates match the theory, and illustrate the superiority of our approach in handling contextual features over the state-of-the-art.
Ornamental Variety of Garuda and Wilmana on Padmasana Architecture at Kahyangan Jagat Temple in Bali, Indonesia

Garuda was known in prehistoric India, where his paintings were found in the Harappa (Sindhu River valley), then spread to all corners of the world affected by Indian civilization. Its head, beak and claws are eagles, the light of the gods shining from its body. While Wilmana as a picture of a space vehicle that moves beyond the speed of thought. Wilmana is also a worldwide character, presented in the world of the internet, film and games. Padmasana architecture is a sacred building as a place/position of God, on the back is often carved by the two kinds of decoration. This research about ornamental variety is research in the context of traditional architecture, as an exploration of building concepts that have been developed in the past and are useful to apply to contemporary architecture. This study aims to re-express the meaning of Garuda and Wilmana and how they are placed on Padmasana architecture. The steps taken are to record the Padmasana in the Kahyangan Jagat Temple in Bali, followed by comparing the use of these two types of decoration on each Padmasana. The next step is to interpret the meaning by connecting the object with its past (expanding the horizon of the researcher). The results of the study show that the use of Garuda and Wilmana decoration in the Padmasana architecture is not a necessity. The use of Garuda points to the message that humans must try to free themselves from the bondage of worldly passions. While the use of Wilmana refers to the sky vehicle that carries passengers, both Giant and Dewata to the place they want. Both are symbolic decoration types, have the same position, placed on the body behind the padmasana. The position of the two becomes different if applied together, Garuda is placed in a position above Wilmana, because only a soul that has been freed from worldly slavery can ride Garuda.
RESTful Web Services Development With a Model-Driven Engineering Approach

A RESTful web service implementation requires following the constrains inherent to REST architectural style, which, being a non-trivial task, often leads to solutions that do not fulfill those requirements properly. Model-driven techniques have been proposed to improve the development of complex applications. In model-driven software development, software is not implemented manually based on informal descriptions but partially or completely generated from formal models derived from metamodels. A model-driven approach, materialized in a domain specific language that integrates the OpenAPI specification, an emerging standard for describing REST services, allows developers to use a design first approach in the web service development process, focusing in the definition of resources and their relationships, leaving the repetitive code production process to the automation provided by model-driven engineering techniques. The code generation process covers the entire web-service flow from the description and exposure of the endpoints to the definition of database tables.
A journal with real impact: responsive, reliable, and thought-provoking

Paige J. Novak summarizes recent news from <italic>Environmental Science: Water Research &amp; Technology</italic> and looks forward to further developments in 2019.
Growing Security and Privacy Threats Inspire New Approaches: Signal Processing Is Playing a Crucial Role in the Development of Next-Generation Protection Technologies [Special Reports]

As threats to data security and privacy multiply, researchers worldwide are investigating novel approaches to protect critical assets, including financial accounts, medical histories, and personal identities. In this effort, signal processing is playing an important role across virtually all security technologies, helping to make new protection tools function efficiently and flawlessly.
Active ingredient: dance

Despite its name, Placebo, the latest performance by award-winning artistic company Clod Ensemble, does have an active ingredient: dance. As seven dancers feel their way through 13 experiments, initially directed by a disembodied, electronic speaker, the supposedly controlled environment onstage begins to, captivatingly, lose control.
Exact completion and type-theoretic structures

This thesis consists of four papers and is a contribution to the study of representations of extensional properties in intensional type theories using, mainly, the language and tools from category ...
The ALI Architecture Description Language

Architecture Description Languages (ADLs) have emerged over the past two decades as a means to abstract details of large-scale systems in order to enable better intellectual control over the complete systems. Recently, there has been an explosion in the number of ADLs created in the research community. However, industrial adoption of these ADLs has been rather limited. This has been attributed to various reasons, including the lack of support of some ADLs for: variability management, requirements traceability, architectural artefact reusability and multiple architectural views. To overcome these limitations, this paper is a report on ALI, an ADL that was designed to complement existing work by adding mechanisms to address the aforementioned limitations. The ALI design principles, concepts, notations and formal semantics are presented in this paper. The notation is illustrated using two distinct case studies, one from the information systems domain " an Asset Management System (AMS); and another from the embedded systems domain - a Wheel Brake System (WBS).
Catalog of Optimization Strategies and Realizations for Composed Integration Patterns.

The discipline of Enterprise Application Integration (EAI) is the centrepiece of current on-premise, cloud and device integration scenarios. However, the building blocks of integration scenarios, i.e., essentially a composition of Enterprise Integration Patterns (EIPs), are only informally described, and thus their composition takes place in an informal, ad-hoc manner. This leads to several issues including a currently missing optimization of application integration scenarios. In this work, we collect and briefly explain the usage of process optimizations from the literature for integration scenario processes as catalog.
ANALYSIS OF SHORT STORY WRITING SKILL BY USING INTERACTIVE MULTIMEDIA BASED ON THE RELIGIOUS CHARACTER OF STUDENTS PRIMARY SCHOOL GRADE 6

Interactive multimedia here is a learning medium that combines text, amber, audio. Interactive multimedia based on religious characters here is an interactive multimedia which contains the value of religious characters. The purpose of this study is to determine the ability to write short stories using interactive multimedia based on religious characters of grade 6 elementary school students. This research was a qualitative descriptive study. Verbal data in this study are the results of recording short story writing using interactive multimedia based on religious characters and nonverbal data, namely the value of the evaluation results of the ability to write short stories of grade 6 students using interactive multimedia based on religious characters. Subjects in this study were students of grade 6 Kawedanan 2 State Elementary School, totaling 39 people. This study uses data collection techniques, namely (a) observation, (b) interviews, and (c) tests. Data in this study will be analyzed with interactive data analysis techniques, namely data reduction, data presentation, and conclusion drawing. Based on the results of the evaluation given, students' short story writing skills are good. All students have achieved the Minimum Completion Criteria that has been set, namely 75. In learning to write short stories, the average grade is 82.18% of the total 39 students. The lowest value is 75 and the highest value is 90.
Properties modelling as design by contract for cyber-physical systems: an example in the smart grid domain

The development of a cyber-physical system (CPS) is strongly related to the requirements elicitation and their fulfilment. Requirements represent the agreement, among the actors involved in the development process of a system (e.g., stakeholders, engineers), of what it is expected to be delivered. As they are neither computable nor verifiable, because typically expressed textually, their misunderstanding could lead to delay or even the failure of the overall system development. In this context, the exploitation of the properties modelling (PM) approach combined with the simulation is proposed to enable assessable requirements. In particular, PM is adopted for expressing requirements as computable and verifiable components, whereas simulation techniques are exploited for supporting their automatic verification and to evaluate their level of fulfilment. The simulation model along with the results gathered from the properties' evaluation represent the contract (design-by-contract) on which the actors can agree before the realisation of an actual CPS. The proposal is tested in the smart grid domain.
INTEGRATING STANDARD SCRM KNOWLEDGE INTO CONVENTIONAL ACADEMIC CURRICULA AN EXAMINATION OF THE CURRENT STATE OF THINGS

The assurance of effective information and communication technology supply chain risk management is a national priority due to the potential impact of supply chain failures on our national infrastructure. Given education’s role in facilitating social change, it is imperative that information and communication technology (ICT-SCRM) supply chain risk management topics are embedded in our present computer curricula. The existence of a well-defined and standard body of knowledge for ICT supply chain risk management offers a validated point of departure for defining and then amalgamating supply chain risk management topics into conventional higher education teaching. This article presents an analysis that explores the specific ways that ICT-SCRM could be disseminated into various computer curricula based on the standards of the traditional societies for those areas (Association for Computing Machinery, Institute of Electrical and Electronics Engineers, Association for Information Systems). This analysis found that it was possible to incorporate secure acquisition and ICT–SCRM best practices into higher education teaching. This can be demonstrated down to the course level.
Universal Grammar and Consciousness

The orthodox interpretation of quantum theory treats the subject and the object on an equal footing. It has been suggested that the cyclical-time process, which resolves self-reference in consciousness, interconnects the observed universe and the mind of the subject. Based on the analogy between cryptography and language, the concept of the common innate structure of language, also known as universal grammar, may be associated with the continuity in consciousness. Extending this connection, Levi-Strauss's proposal on universal culture may be considered as a shared structure of continuity among the consciousness of multiple subjects.
Reachability and Differential based Heuristics for Solving Markov Decision Processes

The solution convergence of Markov Decision Processes (MDPs) can be accelerated by prioritized sweeping of states ranked by their potential impacts to other states. In this paper, we present new heuristics to speed up the solution convergence of MDPs. First, we quantify the level of reachability of every state using the Mean First Passage Time (MFPT) and show that such reachability characterization very well assesses the importance of states which is used for effective state prioritization. Then, we introduce the notion of backup differentials as an extension to the prioritized sweeping mechanism, in order to evaluate the impacts of states at an even finer scale. Finally, we extend the state prioritization to the temporal process, where only partial sweeping can be performed during certain intermediate value iteration stages. To validate our design, we have performed numerical evaluations by comparing the proposed new heuristics with corresponding classic baseline mechanisms. The evaluation results showed that our reachability based framework and its differential variants have outperformed the state-of-the-art solutions in terms of both practical runtime and number of iterations.
Modified 1D Multilevel DWT Segmented ANN Algorithm to Reduce Edge Distortion

In spite of the ability of Artiﬁcial Neural Network (ANN) to handle nonlinear relationships in data, there are instances where ANNs have not been able to predict accurately in the presence of non-stationarity. A novel algorithm that has the ability to treat the nonstationary and nonlinearity in a time series had been presented in [1]. This paper presents a modification done to the algorithm via addressing the edge distortion that arises in the real time execution. The proposed algorithm in [1] was named as “1D Multilevel DWT Segmented ANN Algorithm” where the modified algorithm presented in this paper will be called as “Denoised 1D Multilevel DWT Segmented ANN Algorithm”.
A Study on Preprocessing Techniques for Ultrasound Images of Carotid Artery

Ultrasound imaging has been widely used in the diagnosis of atherosclerosis. To precisely diagnose the carotid plaque, the affected region should be segmented from the ultrasonic image of carotid artery. Many techniques have been used to identify the plaque in ultrasound images. Image enhancement and restoration are the important processes to acquire high-quality images from the noisy images. When the artery images are captured, noise occurs due to high-frequency rate. To acquire a high-quality image, preprocessing is the first step to be done. The quality of the image is improved in this process. The techniques involved in preprocessing are dealt in this paper. Preprocessing involves filtering the image and removing the noise by various filtering techniques. Salt-and-pepper and Gaussian noise in ultrasound images can be filtered using techniques like mean, median and Wiener filters. Salt-and-pepper noise is multiplicative in nature and it is introduced by the image acquisition mechanism. The quality of the input sensor is reflected by the Gaussian noise. In this paper, the performance of image enhancement techniques on ultrasound images are evaluated using quality metrics, namely Mean Square Error (MSE) and Peak Signal–to-Noise Ratio (PSNR).
The Influence of IT-Based Learning Media toward Attitude, Self-Efficacy, and Motivation of MSMEs in Developing Its Business

IT-based learning media is required today for creative MSMEs since it has a strategic role in developing the business. The purpose of this research is to test and analyze the influence of Information Technology (IT)-based learning media for creative Micro Small Medium Entreprises (MSMEs) in increasing attitude, self-efficacy, and motivation of the owner/manager of creative MSMEs in Sleman Regency in developing their business by utilizing IT. The respondent of this research is most of the creative MSMEs in Sleman Regency who have join business and entrepreneur training in which the trainer used the learning media such as audio visual, film, and games by computer with the number of 120 people. The type of the data is using filled out questionnaire and interview with some of the owner/manager of the MSMEs. The result proved that IT-based learning media for creative MSMEs can increase attitude, self-efficacy, and motivation of the owner/manager of creative MSMEs in Sleman Regency in developing their business.
Characterizing Long-Running Political Phenomena on Social Media.

Social media provides many opportunities to monitor and evaluate political phenomena such as referendums and elections. In this study, we propose a set of approaches to analyze long-running political events on social media with a real-world experiment: the debate about Brexit, i.e., the process through which the United Kingdom activated the option of leaving the European Union. We address the following research questions: Could Twitter-based stance classification be used to demonstrate public stance with respect to political events? What is the most efficient and comprehensive approach to measuring the impact of politicians on social media? Which of the polarized sides of the debate is more responsive to politician messages and the main issues of the Brexit process? What is the share of bot accounts in the Brexit discussion and which side are they for? By combining the user stance classification, topic discovery, sentiment analysis, and bot detection, we show that it is possible to obtain useful insights about political phenomena from social media data. We are able to detect relevant topics in the discussions, such as the demand for a new referendum, and to understand the position of social media users with respect to the different topics in the debate. Our comparative and temporal analysis of political accounts can detect the critical periods of the Brexit process and the impact they have on the debate.
Handwritten Indic Character Recognition using Capsule Networks

Convolutional neural networks(CNNs) has become one of the primary algorithms for various computer vision tasks. Handwritten character recognition is a typical example of such task that has also attracted attention. CNN architectures such as LeNet and AlexNet have become very prominent over the last two decades however the spatial invariance of the different kernels has been a prominent issue till now. With the introduction of capsule networks, kernels can work together in consensus with one another with the help of dynamic routing, that combines individual opinions of multiple groups of kernels called capsules to employ equivariance among kernels. In the current work, we have implemented capsule network on handwritten Indic digits and character datasets to show its superiority over networks like LeNet. Furthermore, it has also been shown that they can boost the performance of other networks like LeNet and AlexNet.
Evaluating gender-based mobile shopping application using eye-tracking technology

The mobile applications (apps) development has been gaining popularity for the past few years. Some mobile apps have been failing in its popularity because of the unattractive user interface and bad interaction with the apps. This was proven by previous researchers who have stated that the interaction between a user of mobile application and a graphical user interface could lead to some misunderstandings, errors and frustration from an inability to achieve a goal and could lead to failure of the mobile application. Most of the mobile application developers have been facing proper graphical user interface design recently. There is a noticeable lack of studies and research in the area of mobile application design compared to web application user interface (UI) design. Therefore, this research was done to evaluate the different gender on the mobile shopping application using eye-tracking technology. This research had proposed guidelines based on gender for mobile shopping application. These proposed guidelines can be preferred in the designing process of a mobile shopping application as it could provide a better user interaction and would prevent failure in its popularity by providing fast and user friendly interface.
MEAN-FIELD ANALYSIS OF BATCH NORMALIZATION

Batch Normalization (BatchNorm) is an extremely useful component of modern neural network architectures, enabling optimization using higher learning rates and achieving faster convergence. In this paper, we use mean-field theory to analytically quantify the impact of BatchNorm on the geometry of the loss landscape for multi-layer networks consisting of fully-connected and convolutional layers. We show that it has a flattening effect on the loss landscape, as quantified by the maximum eigenvalue of the Fisher Information Matrix. These findings are then used to justify the use of larger learning rates for networks that use BatchNorm, and we provide quantitative characterization of the maximal allowable learning rate to ensure convergence. Experiments support our theoretically predicted maximum learning rate, and furthermore suggest that networks with smaller values of the BatchNorm parameter achieve lower loss after the same number of epochs of training.