Reviewerly/exHarmony huggingface dataset:
Optimizing the Cost of Executing Mixed Interactive and Batch Workloads on Transient VMs

Container Orchestration Platforms (COPs), such as Kubernetes, are increasingly used to manage large-scale clusters by automating resource allocation between applications encapsulated in containers. Increasingly, the resources underlying COPs are virtual machines (VMs) dynamically acquired from cloud platforms. COPs may choose from many different types of VMs offered by cloud platforms, which differ in their cost, performance, and availability. While transient VMs cost significantly less than on-demand VMs, platforms may revoke them at any time, causing them to become unavailable. While transient VMs' price is attractive, their unreliability is a problem for COPs designed to support mixed workloads composed of, not only delay-tolerant batch jobs, but also long-lived interactive services with high availability requirements. To address the problem,we design TR-Kubernetes, a COP that optimizes the cost of executing mixed interactive and batch workloads on cloud platforms using transient VMs. To do so, TR-Kubernetes enforces arbitrary availability requirements specified by interactive services despite transient VM unavailability by acquiring many more transient VMs than necessary most of the time, which it then leverages to opportunistically execute batch jobs when excess resources are available. When cloud platforms revoke transient VMs, TR-Kubernetes relies on existing Kubernetes functions to internally revoke resources from batch jobs to maintain interactive services' availability requirements. We show that TR-Kubernetes requires minimal extensions to Kubernetes, and is capable of lowering the cost (by 53%) and improving the availability (99.999%) of a representative interactive/batch workload on Amazon EC2 when using transient compared to on-demand VMs.
Learning to Solve Multi-Robot Task Allocation with a Covariant-Attention based Neural Architecture

This paper presents a new graph neural network architecture over which reinforcement learning can be performed to yield online policies for an important class of multi-robot task allocation (MRTA) problems, one that involves tasks with deadlines, and robots with ferry range and payload constraints and multi-tour capability. While drawing motivation from recent graph learning methods that learn to solve combinatorial optimization problems of the mTSP/VRP type, this paper seeks to provide better convergence and generalizability specifically for MRTA problems. The proposed neural architecture, called Covariant Attention-based Model or CAM, includes three main components: 1) an encoder: a covariant compositional node-based embedding is used to represent each task as a learnable feature vector in manner that preserves the local structure of the task graph while being invariant to the ordering of graph nodes; 2) context: a vector representation of the mission time and state of the concerned robot and its peers; and 2) a decoder: builds upon the attention mechanism to facilitate a sequential output. In order to train the CAM model, a policy-gradient method based on REINFORCE is used. While the new architecture can solve the broad class of MRTA problems stated above, to demonstrate real-world applicability we use a multi-unmanned aerial vehicle or multi-UAV-based flood response problem for evaluation purposes. For comparison, the well-known attention-based approach (designed to solve mTSP/VRP problems) is extended and applied to the MRTA problem, as a baseline. The results show that the proposed CAM method is not only superior to the baseline AM method in terms of the cost function (over training and unseen test scenarios), but also provide significantly faster convergence and yields learnt policies that can be executed within 2.4ms/robot, thereby allowing real-time application.
Fooling a Complete Neural Network Verifier

The efficient and accurate characterization of the robustness of neural networks to input perturbation is an important open problem. Many approaches exist including heuristic and exact (or complete) methods. Complete methods are expensive but their mathematical formulation guarantees that they provide exact robustness metrics. However, this guarantee is valid only if we assume that the verified network applies arbitrary-precision arithmetic and the verifier is reliable. In practice, however, both the networks and the verifiers apply limited-precision floating point arithmetic. In this paper, we show that numerical roundoff errors can be exploited to craft adversarial networks, in which the actual robustness and the robustness computed by a state-of-the-art complete verifier radically differ. We also show that such adversarial networks can be used to insert a backdoor into any network in such a way that the backdoor is completely missed by the verifier. The attack is easy to detect in its naive form but, as we show, the adversarial network can be transformed to make its detection less trivial. We offer a simple defense against our particular attack based on adding a very small perturbation to the network weights. However, our conjecture is that other numerical attacks are possible, and exact verification has to take into account all the details of the computation executed by the verified networks, which makes the problem significantly harder.
Virtual Training on Digital School Library Management(A Role Model for Community Service in the Covid-19 Pandemic Era)

Ongoing Covid-19 pandemic has not discouraged lecturers from working on Tridharma The same matter is the case with community service activity using online or virtual as a role model From the problems of analyzing partner problems regarding school libraries, making virtual training in managing school libraries digitally is a preferred solution during the Corona outbreak The usefulness response of the training was responded well by the respondents The teachers, students, and library staff of the MA Nurussalam School Semarang were the respondents of this paper The data obtained using questionnaires and interviews were analyzed using quantitative research method The result of this research shows that this virtual training can provide a solution to upgrade knowledge during a pandemic by using technology in school libraries In addition, the existence of virtual community service leads to confidence in using technology Digitalization by implementing the SLiMS application provides convenience and time efficiency in managing school libraries The existence of digital school library management also makes environmental sustainability, namely the reduced use of paper from trees
Smart Contracts to Support the Advancement of Blockchain Technology in the Security Integrity

The development of technology today is used as a benchmark in the advancement of the industrial world where the development of technology has influenced various aspects in the life of today's society. Smart contracts as one form of blockchain technology that resembles a conventional contract can be used to bind agreements between one party and another. One difference between a smart contract and a conventional contract is the smart contract that is stored in the blockchain. With the presence of smart contracts on the blockchain has become one of the most sought-after technologies, because the number of users is high enough for each transaction within the company. In this case various features of smart contracts applications in various worlds, ranging from financial services, life sciences, energy resources and media voting. Smart contracts still pose a lot of challenges that overwhelm the interaction of some Parties, such as users, developers, and organizations built on smart contracts. Smart contracts are essentially a very effective source of problem solvers, where smart contracts on the blockchain make it easy to maintain data security, and save costs and time. In addition, in the absence of third parties strongly minimizes the fraud that is often done by irresponsible parties, this prevents conflicts between parties. Prone to cases of loss of a document is generated because there is no secure storage media. The advent of smart contracts on the blockchain is expected to be a solution to tackle most of the world's commercial and bureaucratic systems.&#x0D;
Multidisciplinary Approaches to the Rise of Cybersecurity Research

This research note focuses on trends in the publication of research on cybersecurity and in whether multidisciplinary approaches to this research have become more prominent. Through the lens of the Web of Science, there has been a dramatic rise in research on cybersecurity. However, there is little evidence of a significant growth of multidisciplinary approaches to this research. While more detailed research needs to be done, the paper offers several thoughts on what factors are braking the move of more researchers into this area, given the critical role cybersecurity could play in the future of the Internet.
"What's in the box?!": Deflecting Adversarial Attacks by Randomly Deploying Adversarially-Disjoint Models

Machine learning models are now widely deployed in real-world applications. However, the existence of adversarial examples has been long considered a real threat to such models. While numerous defenses aiming to improve the robustness have been proposed, many have been shown ineffective. As these vulnerabilities are still nowhere near being eliminated, we propose an alternative deployment-based defense paradigm that goes beyond the traditional white-box and black-box threat models. Instead of training a single partially-robust model, one could train a set of same-functionality, yet, adversarially-disjoint models with minimal in-between attack transferability. These models could then be randomly and individually deployed, such that accessing one of them minimally affects the others. Our experiments on CIFAR-10 and a wide range of attacks show that we achieve a significantly lower attack transferability across our disjoint models compared to a baseline of ensemble diversity. In addition, compared to an adversarially trained set, we achieve a higher average robust accuracy while maintaining the accuracy of clean examples.
he Effectiveness of Two Stay Two Stray combine with Think Talk Write Method to Improve Students’ Writing Skill.

Siti Julaeha, 14230160, 2018, The Effectiveness of Two Stay Two Stray combine with Think Talk Write Method to Improve Students’ Writing Skill.This research investigates the use of two stay two stray combine with think talk write to improve students’ writing skill on students at MTs Negeri 1 Serang. The aims of the research are 1) to find out the students’ writing skill, 2) to know the use of teaching two stay two stray combine with think talk write method to improve students’ writing skill. The method that used for this research is experimental with two classes, called experiment and control class using pre-test and post-test technique. The writer collects the data from 71 students’ spread two classes, one class as the experiment class and another class as control class. The population is the third grade of MTs Negeri 1 Serang, class IX-A 1 as experiment class which consist of 36 students and IX-B 2 as control class which consist of 35 students. The writer uses quasi experiment method which the data gathered through pre-test and post-test. Based on result, the average score of experiment class in Pre- Test is 75,72 and 80,91. While, the average score of control class is 72,68 in Pre- Test and 77, 8 in Post- Test. The result shows that the hypothesis value of to 〖(t〗_observation) is higher than tt (ttable); 2,25 > 1,995. Ha:to > tt : it means that two stay two stray method has significant effect on students’ writing skill, so the null hypothesis (H0) is rejected and alternative hypothesis (Ha) is accepted. Based on the findings, it can be concluded that the use of two stay two stray technique is effective for learning process writing text, especially at the third grade of MTs Negeri 1 Serang.
OPTIMASI CLUSTER K-MEANS MENGGUNAKAN METODE ELBOW PADA DATA PENGGUNA NARKOBA DENGAN PEMROGRAMAN PYTHON

As we know, drugs are very illegal in Indonesia because drug abuse can have very dangerous effects. Drugs are substances that have side effects such as hallucinations, reduced awareness and arousal of the user. Technological advances continue to change over time so that information needs are very much needed in life. Currently, data on drug users is very extensive, so that adequate information presentation techniques are needed so that the information received is very accurate and in accordance with the user's needs. Therefore, it is necessary to carry out a data mining process on drug user data to obtain useful information for users. This study aims to prove Elbow's performance to produce optimal clusters of drug user data using the K-Means algorithm as a data grouping method. Cluster optimization is obtained from the Elbow method, which is executed with Google Collaboratory using the Python programming language. The test results show that the Elbow method works very well in producing the optimal cluster, which is found at k = 3 with the SSE difference value of 1257.862 with k test = 5.
Supporting the Statistical Analysis of Variability Models by Processing Binary Decision Diagrams

When one of the main aims of the Software Engineering is saving costs and time, the software product lines play an essential role. In this eld, the key lies in identifying reusable components or features that can be applied in future projects. Much research is being done to provide customizable solutions that match specic problems and thus satisfy a variety of non-functional requirements, such as runtime eciency, computer memory consumption, security level, etc. Customization is often accomplished through a conguration process where the desired features are selected. The space of possible congurations is usually constrained to avoid features incompatibilities, and guaranteeing that feature inter-dependencies are satised. There are many questions of interest inside this restricted space: Are all congurations free of errors? Is there any dead code that cannot be activated because of the inter-feature constraints? What is the component reusability range? What is the typical size of a nal product in terms of components? Etc. The conguration space may potentially be 2n for n features. Hence, processing the complete set of solutions is impossible except for the most trivial cases. After removing the invalid congurations that do not satisfy the inter-feature constraints, the solution space is reduced substantially. Nevertheless, it is usually still large enough to be suitable to work with it. One strategy to address these diculties is selecting a representative sample of the space and, once the computation is done, extrapolating the conclusions to the whole problem. At this point, the problem turns into the way of obtaining a reliable random sample to avoid wrong interpretations. This thesis presents a set of algorithms that support both (i) working with the whole population of valid congurations by using a highly-optimized Boolean structure known as Binary Decision Diagrams, and (ii) generating random samples from the conguration space. Moreover, a whole infrastructure in two programming languages (C++ and R) is provided to incorporate new algorithms on Binary Decision Diagrams effortlessly. Finally, this thesis reports the empirical validation of our algorithms and framework on a benchmark composed of real variability models, whose number of features ranges from 45 to 17 365.
Improving E-Health Governance through Syndromic Surveillance Systems and Data Mining in KSA

Recently, the KSA has witnessed significant technical advances in the health sector, where local hospitals are using high-quality systems and technologies to serve patients. However, even with this great progress in healthcare systems, communication is still limited with other decision-makers in different sectors who need to access some health-related information to take the best decisions for serving patients. Therefore, this project aims to utilise the concept of electronic health governance (e-health governance) to build an automated system, which will help the health sector to know which common diseases are currently prevalent and facilitate the decision-making process by providing them with the necessary health information to help them provide the best service for patients in various fields. To do that this research will apply classification data mining techniques through using naïve Bayes classification algorithm; where this project aims to build a common diseases prediction system (CDPS) to work as syndromic surveillance system.
ANALISA MODEL POHON DAN GRAF PADA GAME PERFECT WORLD 2 ONLINE

The implementation of graphs and trees in the Perfect World Online Game is one example of the application of discrete mathematics in human activities, especially the world of entertainment. The internet is currently causing the development of online games to increase rapidly, as seen from the emergence of many online games with various genres such as Adventure, Action, Strategy, RPG, MMORPG and many more. MMORPG was chosen as the type of game to be discussed because in the game model and features many apply trees and graphs. With the help of graph and tree theory, we can further explore all the features that are fast in an online game.
텍스트마이닝을 이용한 보수와 진보 언론의 ‘국가안보’ 프레임 분석

In principle, the media should be balanced and objective in reporting non-biased. This is because reports that have lost fairness and objectivity cause conflicts and divisions in society. Today, Korean journalism tends to see a noticeable increase in news reports that have lost their realism, objectivity and neutrality. The reality is that conservative and progressive media are pouring out biased reports of their own subjective and overemphasizing one side.Regardless of conservatives and progressives, national security must be prepared and responded with one mind. This is because it is an important matter for the entire nation. Nevertheless, the reality is that the frame of conservatism and progressivism shows different positions and opinions.This study was intended to collect articles that reported major national security issues using BigKines, extract keywords from press releases with text mining, one of the big data analysis techniques, and analyze them with network techniques to compare and analyze the media’s conservative and progressive frames on national security.When the results of the study were analyzed by comparison, even if the reports of conservative and progressive media were the same issue, they could see that the frame of the report frame. Citing the shooting of government officials in the West Sea as an example, conservative media viewed it as a frame in which the government failed to respond properly, while progressive media focused on fact-finding reports on what North Korea reported.Second, in the analysis of key words, conservatism is analyzed as the most important keyword in Korean security, with its representative keyword “North Korea,” while progress expresses that “president” is the most important keyword in national security and has expectations and hopes for the president. According to an analysis by WordCloud, the North Korean keyword of conservatism was the “America” with high frequency but high centrality, and “America” also proved that both conservatives and progressives play a central role in South Korea’s security.Finally, as a result of CONCOR analysis, which determines the sidewalk frame, it can be seen that remuneration and progress deal with national security with very different frames.Through this study, we can see that in reporting the important issue of national security, there is a window of reporting of conservatism and progress, and that the frame of national security is viewed from different angles. Freedom of speech is guaranteed, but at least until the day when the windows to look at the task of national security with national survival come straight to each other, we need to practice thinking and conscious together.
Penerapan Data Mining Klasifikasi Tingkat Kepuasan Mahasiswa Terhadap Pelayanan Sistem Informasi di Program Studi Sistem Informasi

The purpose of this study was to determine the effect of Academic Information System services on student satisfaction so that students who are academics do not feel disappointed with services related to Academic Information Systems. Measurement of Student satisfaction related to campus Information System services is rarely done so that the level of student satisfaction is unknown. By knowing the level of student satisfaction, the College can improve the service if it is not good and further improve the service if the level of satisfaction is good. This study measures the level of student satisfaction with the services of the Academic section at STIKOM Tunas Bangsa. The method used in this study is C4.5 Algorithm, where the data source used uses a questionnaire / questionnaire technique that is given to students randomly in the STIKOM Tunas Bangsa Pematangsiantar environment. Data validity is done with internal validity. The variables used include (1) System Quality, (2) Information Quality, (3) Service Quality, and (4) Performance Expectations. It is expected that the results of this research can be applied to improve the Academic Information System service so that the existing system can run better
OFR20-01, Minnesota Data Preservation Report for 2019/2020: Updated Data Inventory, Preservation of Pillsbury Hall Rock Collections and Documentation, Assembly of Mineral Potential Related Information

UPDATED DATA INVENTORY, PRESERVATION OF PILLSBURY HALL ROCK COLLECTIONS AND DOCUMENTATION, ASSEMBLY OF MINERAL POTENTIAL RELATED INFORMATION
COMPUTATIONAL THINKING DAN ALICE 3: Prodi/Jurusan D4 Teknik Informatika Politeknik Pos Indonesia

Digital technology is developing so rapidly this can be seen in the era of the industrial revolution 4.0, the need to make solutions in the form of software is becoming a common thing. The ability to communicate with hardware via software is a must. Programming languages begin to be taught from the basic level with a certain depth. Industry needs reliable personnel to be able to work through software solutions. The computational thinking method with Alice 3 is used to improve students' decomposition and abstraction programming abilities. The test results show that the application of computational thinking by developing the source code that has been given has a better impact than if tudents code programs from scratch.
Research on Optimization Technology of Radix-4 FFT in FPGA Implementation

Fast Fourier Transform (FFT) is one of the core algorithms in digital signal processing. The traditional FFT processing method can no longer meet the data processing requirements, so the implementation and optimization of the better performance radix-4 FFT algorithm has very important research value. Based on FPGA technology, this paper proposes a design scheme of radix-4 FFT algorithm processing system. By optimizing the butterfly processing unit, the system realizes a high-performance FFT algorithm processing system with characteristics of faster operation speed, higher calculation accuracy, easy hardware implementation and large capacity compared with the traditional FFT processing method. It is well suited for scientific computing, image processing and other fields.