Reviewerly/exHarmony huggingface dataset:
Identifikasi Bukti Forensik Jaringan Virtual Router Menggunakan Metode NIST

The evolution information technology has led to the growth of virtualization technology. Router OS is the operating system of the Mikrotik Router, which supports virtualization. Router Os virtualization technique which is easy to run is a metarouter. Metarouter provides benefits such as, building virtual servers, virtual machines, network topology and savings cost. As an object of research, Metarouter introduces challenges to digital forensic investigations, both practitioners and academics. Investigators need to use methodology and tools in order to prove the perpetrators of crimes. This study uses the Windump forensic tool as a means of recording network traffic activity. Network Miner and Wireshark as an analytical tool for identifying digital evidence. The use of the National Institute of Standard and Technology (NIST) method which collection, examination, analysis and reporting, can be repeated and maintained with the same data. Based on experiments with virtual router network traffic testing, the system built has succeeded in obtaining digital evidence, either by direct or indirectly. The system scenario that has been planned succeeded recording 220494 packages, but by the Windump, it is automatically divided into 9 (nine) parts of the package which are Buktidigital0 to Buktidigital8. The inspection stage produces evidence that has been verified by Wireshark and Network Miner. The analysis stage proves that there were attacks carried out by addresses 192.168.10.10 and 192.168.234.10. Based on the results of forensic testing, the use of the NIST method on a forensic system that has been built with a virtual router object can be used by investigators to identify evidence of cyber-attacks.&#x0D;
Organization and methods of corporate personnel training in the aerospace industry

The key principles of the formation of a training system for personnel of aerospace industry organizations are considered. Particular attention is paid to taking into account the influence of the human factor, which leads to the need to use a developing learning model based on the andragogical approach (adult education). Increased attention to the human factor contributes to the provision of motivation and the introduction of new approaches to corporate training of personnel based on the principles of andragogy, i.e. in relation to the features of adult education. Due to the high emotional involvement of participants in the implementation of long-term science-intensive programs, the requirements for conflict resolution competence of managers and specialists of the respective industries are significantly increased. Other needs for staff development include improving communication skills, the ability to effectively conduct presentations, and opposing manipulation at various levels. The key personalities of the practical implementation of this andragogical model are a business trainer or, depending on the nature of the training, a tutor, the range of necessary competencies of which is significantly expanded compared to a traditional teacher. The conditions for ensuring the effectiveness of this model, the organizational and methodological principles of the interaction of its participants, and the components of support and development of the educational process are considered. A particular example of evaluating the economic effect of corporate training is given.
KORELASI KETERAMPILAN MENYIMAK WAWANCARA DENGAN KETERAMPILAN MENULIS TEKS BERITA SISWA KELAS VIII SMP NEGERI 23 PADANG

ABSTRACT The purpose of this study is three. First, describe the listening skills of class VIII interview at SMP Negeri 23 Padang. Second, describing the news text writing skills of class VIII students of SMP Negeri 23 Padang. Third, describe the correlation of listening skills to interviews with news text writing skills of class VIII students of SMP Negeri 23 Padang. This type of research is a quantitative descriptive method. The design used in this study is correlational design. The population of this study was Class VIII of SMP Negeri 23 Padang. The sample in this study was determined by proportional random sampling of 25% of the population, namely 51 students. The research data were test scores on interview listening skills and news text writing skills test scores. The research instrument was an objective test to measure interview listening skills and performance tests to measure news text writing skills. The results of this study are three. First, the writing text skills of class VIII students of SMP Negeri 23 Padang are in more than enough qualifications. Secondly, listening to interview skills is more than adequate. Third, listening skills interviewed were correlated at 7,41 with news text writing skills of class VIII students of SMP Negeri 23 Padang. Kata Kunci: Korelasi, Keterampilan Menyimak Wawancara, Keterampilan Menulis Teks Berita
Concept and implementation of the educational program of the International School of information technologies "Data Science" at Dubna State University

The article presents the concept of organization and the International school of nformation technologies "Data Science" functioning. IT-school was created in Dubna State University together with the Laboratory of information technology of the Joint Institute for Nuclear Research. The educational program of the IT-school is detailed and describes the educational environment, which includes services for working with students and an ecosystem for conducting practical classes. The main principle of working with students — learning through research is revealed
Towards certifying ℓ∞ robustness using Neural networks with ℓ∞-dist Neurons

It is well-known that standard neural networks, even with a high classification accuracy, are vulnerable to small l∞ perturbations. Many attempts have been tried to learn a network that can resist such adversarial attacks. However, most previous works either can only provide empirical verification of the defense to a particular attack method or can only develop a theoretical guarantee of the model robustness in limited scenarios. In this paper, we develop a theoretically principled neural network that inherently resists l∞ perturbations. In particular, we design a novel neuron that uses l∞ distance as its basic operation, which we call l∞-dist neuron. We show that the l∞-dist neuron is naturally a 1-Lipschitz function with respect to the l∞ norm, and the neural networks constructed with l∞-dist neuron (l∞-dist Nets) enjoy the same property. This directly provides a theoretical guarantee of the certified robustness based on the margin of the prediction outputs. We further prove that the l∞-dist Nets have enough expressiveness power to approximate any 1-Lipschitz function, and can generalize well as the robust test error can be upper-bounded by the performance of a large margin classifier on the training data. Preliminary experiments show that even without the help of adversarial training, the learned networks with high classification accuracy are already provably robust.
JITTER ANALYSIS OF ETHERCAT MASTER OPEN LIBRARIES IN INDUSTRIAL ROBOT CONTROL SYSTEM

This paper presents the comparison of efficiency of control systems based on industrial PC using different open source EtherCAT libraries to communicate with motion control units.The aim of this study is to measure the jitter level in hard realtime application based on Xenomai realtime operating system and application running in user space.Main goal of this research is to find the best solution for positioning six axis manipulator utilized in sorting and packing processes.
Klasifikasi Data Nasabah Asuransi Dengan Menggunakan Metode Naive Bayes

Classification is the logical grouping of objects according to the characteristics of their similarities. Naive Bayes is a method for predicting future opportunities based on past experiences. This study discusses the classification of insurance customer data of PT. Prudential Life Branch of Samarinda in 2017. With the aim to know whether the method of Naive Bayes can classify data of insurance customers of PT. Prudential Life in 2017 using the R program and to determine the accuracy of the results of data testing I and data testing II. As a result, Naive Bayes method can classify data of insurance customers of PT. Prudential Life with 80% accuracy for 25 data testing I and 74.67% for 75 data testing II.
EDUCATION SYSTEM IN THE REPUBLIC OF SERBIA UNDER COVID-19 CONDITIONS: CHATBOT- ACADIMIC DIGITAL ASSISTANT OF THE BELGRADE BUSINESS AND ARTS ACADEMY OF APPLIED STUDIES

In the Republic of Serbia, the COVID-19 pandemic has created the largest disruption of educational systems in history so far, having a universal impact on the entire country and all levels of education from pre-school education, through secondary schools, technical and vocational education and training, to colleges, universities and institutions for adult education or a skills development institution. As the health crisis developed, causing widespread socio-economic disruptions, the Serbian government reacted quickly to ensure continuity of education and protect students and educational actors. Due to the closure of schools, the domestic education system is turning to greater application of information and communication technologies in all educational subsectors, and teachers are required to switch to the delivery of educational content online and online interaction with their students. The paper especially analyzes the experiences of the Belgrade Business and Arts Academy of Applied Studies in dealing with new challenges in the implementation of teaching and its overall functioning in the conditions of the COVID-19 pandemic. Despite improvement, modernization and digitalization are the basis of the Academy's business strategy, the new working conditions required a quick adjustment of work in order to provide students with the highest quality educational service. In addition to new versions of the student information service application, E-employee application, new versions of the website, the Belgrade Academy began in 2020 to develop chatbot technology using the Weaver platform of the company Saga to provide its students with improved service during studies. Namely, the function of chatbot is based on understanding the requirements regardless of the language or structure of the sentence that is written or spoken. Based on the processing of the sentence with the help of natural language understanding (NLU), and with the application of the appropriate algorithm, the chatbot comes to an adequate answer which is forwarded to the student. The ADA (Academic Digital Assistant) chatbot project is the first project of its kind in the Balkans in the field of education that provides better communication, time savings, faster and more efficient implementation of educational services.
Adoption of Blockchain in Retail Logistics: A Future Imperative

e use and adoption of blockchain in the logistics industry is in nascent stage. There are numerous concerns on adoption of blockchain, but the benefits derived are already leading towards the solution of adopting blockchain as contemporary technology. The Smart Contracts, a unique feature of blockchain, is the answer to many problems faced by the logistics industry. The present study attempts to offer a view on how blockchain has the latency to bring about a greater change in logistics management by bringing in more cost-effective solutions. The study further gives a brief description of the blockchain technology, its evolution, and benefits associated around it. This study depicts how blockchain technology may be applied in the logistics industry to lead to cost-savings and enhanced profitability.Keywords-Blockchain; Technology; Logistics; Smart Contracts; Challenges
Category‐wise feature extractor based on ADL method for weak‐supervised object localisation

Fully supervised object detection needs to use the data set with object category annotation and location annotation to train the model. In contrast, weak supervised object localisation only needs to use the data set with object category annotation to train the model, but it can complete the classification task and object localisation task at the same time. Inspired by the attention-based dropout layer (ADL) method, this study designs a category-wise feature extractor (CFE), which can explicitly obtain the localisation map used to indicate the object location, and it is directly related to the category output of the classification task. Although its amount of calculation is slightly larger than that of the ADL method, the performance is better than ADL in some tasks. In addition to the standard CFE method mentioned above, this study also designs a lightweight CFE-tiny method, which adopts split-attention mechanism, and the calculation amount of this method is much smaller than that of ADL method.
Application and Practice Research of QR Code Technology in the Prevention and Control of COVID-19 Epidemic

In order to effectively protect the employees′ heath, therefore, resolutely prevent the spread of the epidemic, strength control the flowing of the returning staff and fully monitor the temperature are the first priority of the epidemic prevention and control work. By studying the implementation process and system test of QR Code technology, combining with the specific situation of the enterprise, QR Code technology is applied in the functional modules of entry and exit registration of returning staff, records of daily health, disinfection records of public facilities, etc. The adoption of QR Code scanning registration method can put the basic personal information and travel status information into system, which can shorten the contact time of personnel and reduce the risk of cross-infection, thus greatly improve the work efficiencies. Also, it ensure that the people are flowing in a closed loop, therefore, it has improved the effectiveness of epidemic prevention and control.
Secure Gestures—Case Study 4

chapter Share on Secure Gestures—Case Study 4 Authors: Can Liu Search about this author , Janne Lindqvist Search about this author Authors Info & Claims Intelligent Computing for Interactive System Design: Statistics, Digital Signal Processing, and Machine Learning in PracticeFebruary 2021 Pages 323–338https://doi.org/10.1145/3447404.3447422Online:23 February 2021Publication History 0citation1DownloadsMetricsTotal Citations0Total Downloads1Last 12 Months1Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
[CT image quality assessment based on prior information of pre-restored images].

Objective We propose a CT IQA strategy based on the prior information of pre-restored images (PR-IQA) to improve the performance of IQA models. Objective We propose a CNN-based no-reference CT IQA strategy using the prior information of image quality features in the image restoration algorithm, which is combined with the original distorted image information into the two CNNs through the pre-restored image and the residual image. Multi-information fusion was used to improve the feature extraction ability and prediction performance of CNN. We built a CT IQA dataset based on spiral CT data published by Mayo Clinic. The performance of PR- IQA was evaluated by calculating the quantitative metrics and statistical tests. The influence of different hyperparameter settings for PR-IQA was analyzed. We then compared PR-IQA with the BASELINE model based on the single CNN to evaluate the original distorted image without reference image and other eight IQA algorithms. Objective The comparative experiment results showed that the PR-IQA model based on the prior information of 3 different image restoration algorithms (BF, NLM and BM3D) was better than all the tested IQA algorithms. Compared with the BASELINE method, the proposed method showed significantly improved performance, and the mean PLCC was increased by 12.56% and SROCC by 19.95%, and RMSE was decreased by 22.77%. Objective The proposed PR-IQA method can make full use of the prior information of the image restoration algorithm to effectively predict the quality of CT images.
Reducing the number of neurons of Deep ReLU Networks based on the current theory of Regularization

We introduce a new Reduction Algorithm which makes use of the properties of ReLU neurons to reduce significantly the number of neurons in a trained Deep Neural Network. This algorithm is based on the recent theory of implicit and explicit regularization in Deep ReLU Networks from (Maennel et al, 2018) and the authors. We discuss two experiments which illustrate the efficiency of the algorithm to reduce the number of neurons significantly with provably almost no change of the learned function within the training data (and therefore almost no loss in accuracy).
Divide-and-Conquer Monte Carlo Tree Search

Standard planners for sequential decision making (including Monte Carlo planning, tree search, dynamic programming, etc.) are constrained by an implicit sequential planning assumption: The order in which a plan is constructed is the same in which it is executed. We consider alternatives to this assumption for the class of goal-directed Reinforcement Learning (RL) problems. Instead of an environment transition model, we assume an imperfect, goal-directed policy. This low-level policy can be improved by a plan, consisting of an appropriate sequence of sub-goals that guide it from the start to the goal state. We propose a planning algorithm, Divide-and-Conquer Monte Carlo Tree Search (DC-MCTS), for approximating the optimal plan by means of proposing intermediate sub-goals which hierarchically partition the initial tasks into simpler ones that are then solved independently and recursively. The algorithm critically makes use of a learned sub-goal proposal for finding appropriate partitions trees of new tasks based on prior experience. Different strategies for learning sub-goal proposals give rise to different planning strategies that strictly generalize sequential planning. We show that this algorithmic flexibility over planning order leads to improved results in navigation tasks in grid-worlds as well as in challenging continuous control environments.
Exploration on Establishment of Off-campus Training Base for Civil Engineering Professional Master

The training of civil engineering professional master focuses on cultivating practical talents and its training method is different from that of academic masters. This paper proposes the establishment of off-campus training bases to train masters of civil engineering in order to establish a leadership group based on school-enterprise joint work and make full use of teacher’s resources. Not only work on projects, but also select better training base according to complementary advantages. In this paper, a new idea was provided that improved the establishment of off-campus training bases for civil engineering masters training.
Dynamics and Information Processing in Recurrent Networks

Author(s): Kuczala, Alexander Phillip | Advisor(s): Sharpee, Tatyana O; Vergassola, Massimo | Abstract: Random recurrent networks facilitate the tractable analysis of large networks. The spectrum of the connectivity matrix, determined analytically by random matrix techniques, determines the network’s linear dynamics as well as the stability of the nonlinear dynamics. Knowledge of the onset of chaos helps determine the networks computational capabilities and memory capacity. However, fully homogeneous random networks lack the non-trivial structures found in real world networks, such as cell-types and plasticity induced correlations in neural networks. We address this deficiency by investigating the impact of correlations between forward and reverse connections, which may depend on the neuronal type. Using random matrix theory, we derive a formula that efficiently computes the eigenvalue spectrum of large random matrices with block-structured correlations. The inclusion of structured correlations distorts the eigenvalue distribution in a nontrivial way; the distribution is neither a circle nor an ellipse. We find that layered networks with strong interlayer correlations have gapped spectra. For antisymmetric layered networks, oscillatory modes dominate the linear dynamics.We analyze the effect of structured correlations on the nonlinear dynamics of rate networks by developing a set of dynamical mean field equations applicable for large system sizes. We find that the power spectrum of strongly antisymmetric bipartite networks peaks at nonzero frequency, miming the gap present in the eigenvalue distribution. Heterogeneous connection statistics facilitate the presence of strongly feed-forward connections in addition to recurrent ones, both of which promote signal amplification. We investigate the role of feed-forward amplification in i.i.d. block-structured networks by computing the Fisher information of past input perturbations. We apply this result to find the optimal architecture for information retention in two populations, under energy constraints. We find that this architecture is both strongly feed-forward and recurrent, with the respective strengths of these connections depending on the available synaptic gain. Finally, we assess the ability of rate networks to dynamically approximate the dominant mode of a random symmetric matrix. Given an initial estimate of the eigenvector as input, we find that there is an optimal processing time and synaptic gain strength depending on the dimensionality and quality of the initial estimate.
The Shield and the Sword: The Press Between the Public Interest and the Illegal Interception of Private Communications

Journalism is not only under the attack of fake news and post-truth politics. Its main enemy comes from within. Malpractices of journalism such as the fabrication of sources, fake stories, and illegal intrusion in people’s privacy, are part of the equation that leads to people’s distrust in news organization.This article addresses two very related topics that, nevertheless, have not been sufficiently studied as part of the same phenomenon: The reporter’s privilege to protect his sources’ identity and its connection with a journalist’s involvement in the illegal hacking or interception of private communications.After reviewing the most relevant case law from the federal and state level, and all states that have enacted a Shield Law, the author recommends an exception to the reporter’s privilege when there is probable cause that the journalist participated in illegal gathering activities of secluded information. With this proposal, the purpose is to reconcile two of the most emblematic legal precedents for freedom of the press by the U.S. Supreme Court: Branzburg and Bartnicki.