Reviewerly/exHarmony huggingface dataset:
An approach for unsupervised contextual anomaly detection and characterization

Outlier detection has been widely explored and applied to different real-world problems. However, outlier characterization that consists in finding and understanding the outlying aspects of the anomalous observations is still challenging. In this paper, we present a new approach to simultaneously detect subspace outliers and characterize them. We introduce the Dimension-wise Local Outlier Factor (DLOF) function to quantify the degree of outlierness of the data points in each feature dimension. The obtained DLOFs are used in an outlier ensemble so as to detect and rank the anomalous points. Subsequently, the same DLOFs are analyzed in order to characterize the detected outliers with their relevant subspace and their same-type anomalies. Experiments on various datasets show the efficacy of our method. Indeed, we demonstrate through an experimental evaluation that the proposed approach is competitive compared to the existing solutions in terms of both detection and characterization accuracy.
Automatic association method of knowledge points about karst landform VR panoramic teaching resources

VR panoramic teaching resources can create an immersive teaching situation for teachers and students. Aiming at the problems of tedious manual annotation and easy omission of VR panoramic teaching resources during the course preparation of karst landform teaching teachers, this paper designs an automatic association method for knowledge points of VR panoramic teaching resources to construct the training set of karst landform sample images based on Convolution Neural Network(CNN), which can extract the karst landform teaching objects in the panoramic images, and associates and locates the knowledge points stored in the object relational database in the VR panoramic space. Finally, a prototype system of "Geographical Karst" teaching course of senior high school geography published by People’s Education Press is constructed. The experimental results show that this method can realize the automatic correlation of VR panoramic teaching resource knowledge points.
Simulation study of frequency hopping/Multi-levelFrequencyShifKeying (FH/MFSK) system

Frequency hopping communication as one of the most important branches of extended frequency communication, has a strong anti-search, interception, anti-interference ability, can improve the short wave communication performance, this paper using Simulink simulation platform in MATLAB communication F H/MFSK system for simple modeling simulation, to prove that frequency hopping communication technology can indeed improve short wave communication performance.
The Blockchain-Based Digital Certificate for the Transport of Dangerous Goods

The transport of dangerous goods consists of the carriage of goods presenting potential risks to the people, living organisms, the environment, and materials (public or private property) and therefore necessitates dedicated and specially reinforced security measures. According to global statistics, dangerous goods may constitute about fifty percent of global transportation in the following years, whether by road, railway, air, or seas. Compared to traditional transportation e.g., general supply chains, the TDG is a particular class of transportation that is subject to specific requirements among which the human and environmental safety. It also incorporates rigorous information immutability and the traceability of the DG movement [2], as indicated in the “Agreement concerning the International Carriage of Dangerous Goods by Road” [3] applicable since 1 January 2021. In this context, this chapter aims to propose a platform to support the verification of the stakeholders’ identity, the history of transportation, including environmental data, and the location overtime of the dangerous good employing the blockchain-based digital certificate. Using blockchain technology (jointly use) of two concepts/technologies such as blockchain and digital certificate has for purpose to ensure transaction transparency, easy access to the transportation information, less paperwork, and strong stakeholder identification. Finally, besides proposing a blockchain-based digital certificate for the TDG, our approach also analyzes the extent to which the blockchain may be specified to integrate and be compatible with the Internet of Things (IoT) technology and specifications.
Joint Optimization of Topology and Hyperparameters of Hybrid DNNs for Sentence Classification

Deep Neural Networks (DNN) require specifically tuned architectures and hyperparameters when being applied to any given task. Nature-inspired algorithms have been successfully applied for optimising various hyperparameters in different types of DNNs such as convolutional and recurrent for sentence classification. Hybrid networks, which contain multiple types of neural architectures have more recently been used for sentence classification in order to achieve better performance. However, the inclusion of hybrid architectures creates numerous possibilities of designing the network and those sub-networks also need fine-tuning. At present these hybrid networks are designed manually and various organisation attempts are noticed. In order to understand the benefit and the best design principle of such hybrid DNNs for sentence classification, in this work we used an Evolutionary Algorithm (EA) to optimise the topology and various hyperparameters in different types of layers within the network. In our experiments, the proposed EA designed the hybrid networks by using a single dataset and evaluated the evolved networks on multiple other datasets to validate their generalisation capability. We compared the EA-designed hybrid networks with human-designed hybrid networks in addition to other EA-optimised and expert-designed non-hybrid architectures.
Portrayal of Pakistan Electronic Crimes Act in Leading Liberal Dailies of Pakistan

The content analysis is used to quantitatively analyze the portrayal of the Pakistan Electronic Crimes Act (PECA) in leading English language dailies of Pakistan, Dawn, The News International and Express Tribune, for three (3) months, from 22 February 2022 to 22 May 2022. The News International seems to portray Pakistan Electronic Crimes Act (PECA) more when compared with Dawn and Express Tribune. All three newspapers emphasize freedom of expression, and no newspaper adopts the-stance toward censorship or regulation of media. However, The Expression Tribune does hint at the need for censorship in one news article. The Dawn newspaper also emphasizes the voice of opposition and legal proceedings.The study is likely to have implications for the socially responsible role of mass media in contexts of factual news and the emerging issue of fake news by the inclusion of diverse voices. Unfortunately, the selected newspapers did not show cultural pluralism.
Preventing Reverse Engineering of Critical Industrial Data with DIOD

Business analytics augmented by artificial intelligence and machine learning (AI/ML) have revolutionized the role of data in the modern world. In recent years, businesses have incorporated data into their decision-making process for better prediction, risk assessment, content creation, etc. While such businesses often seek to leverage the full use of their data through third-party AI/ML services, they are often hampered by the risks of data leaks, reverse engineering, stolen technology, etc., that often have disastrous consequences for businesses and their stakeholders alike. This is especially relevant to the nuclear industry where proprietors are reluctant to share nuclear data for fear of misuse despite their willingness to integrate the additional insight provided by AI/ML applications and remain competitive. Thus, there arises a need for data masking prior to its transmission that obfuscates proprietary information while preserving the information relevant for AI/ML applications. In order to meet the needs of industrial data that are significantly different from those of data warehouses, previous work proposed an efficient time and space-scalable data masking paradigm known as the deceptive infusion of data (DIOD) methodology. The present work expands upon this work by leveraging existing reverse-engineering capabilities to facilitate the decomposition of industrial data into its proprietary and AI/ML-relevant parts, referred to as fundamental and inference metadata, respectively. Both sets of metadata are further obfuscated in accordance with the DIOD methodology to create the DIOD rendition of the industrial data, which is rendered immune to reverse engineering by discarding proprietary information and preserving only AI/ML–relevant information. Additionally, constraints of the original DIOD paper are relaxed using mutual information by configuring the methodology to the target AI/ML application to unlock the full potential of the DIOD methodology. Since the present work focuses on the nuclear industry, data from a nuclear reactor is transformed into that from a nonlinear spring-mass system with different levels of data masking as required by the generic system and the target AI/ML application.
Research and Design of the Intelligent Bulk Transfer Laboratory Interconnection

Offline operation and manual operation are common in laboratory business. There are problems such as low detection efficiency, data isolation and lack of supervision. The digital transformation of business is an important part to realize the intelligence of laboratory. The interconnection of experimental equipment is the basic guarantee of business digitalization. In order to solve the above problems, an intelligent laboratory interconnection system architecture was built. This project included downlink data collection and uplink data interconnection scheme design. Combined with the development and design of intelligent laboratory platform, the vertical connection, fusion and sharing of laboratory resources and data and demonstration application are finally realized.
An Analysis of Financial Product Purchase Behavior Based K-means on Hadoop Platform

This text discusses the use of map/reduce processing mechanism based on the hadoop platform to analyze the purchasing behavior data of high-net-worth customers in the commercial bank database system and find out the influence and preference of major fund companies in the high-net-worth customer groups of commercial banks. Then we uses the K-means (KM) clustering algorithm to analyze group characteristics of customer which is used to facilitate commercial banks to formulate precise marketing strategies.
AGRIBUZZ (Agriculture Website)

The agricultural website provides its users and researches to get online information about, the crop, statistical details and new tendencies. The trends of the crops act so that these will be pretty important to the users who access these via the Internet. The main features of the information system include information retrieval facilities for users from anywhere in the form of obtaining statistical information about fertilizer, research institutes and researches, suitable soil concentration for the corresponding crops, information about exports and etc. In addition, this provides individual information about Intercrops related to main crops. The system allows the retrieving facilities but also the updating facilities to the authorized persons in the corresponding institutes. PHP, HTML, CSS was used to create the front end for the system and MY SQL Server was used for the back end.
Palekh artist I. I. Golikov and his design of the book "The Word about Igor's Regiment": on the issue of Creative Borrowings

The subject of the study is the analysis of illustrations created by the Palekh artist Ivan Ivanovich Golikov for the "Words about Igor's Regiment" – the largest monument of book graphics of Palekh art. The background, the reasons for giving I. I. Golikov an order to illustrate the book by the publishing house "Academia", the progress of I. I. Golikov's work on its implementation, as well as the impression that this publication made on customers and Soviet society are revealed in detail. The purpose of the article is, in addition to showing the possibility of fruitful work of a miniature artist in the field of art that is not related to the traditional lacquer miniature for Palekh, to analyze the creative method of I. I. Golikov when working on the illustration of this publication. Using the method of comparative analysis, as well as historical-systemic and iconographic research methods, the author at the same time focuses on the qualities of I. I. Golikov as an innovator and experimenter in art, which predetermined both the order for the illustration of the "Word" to this particular Palekh master, and the grandiose success that fell to the share of this book edition. It is in the study of these innovative qualities of I. I. Golikov, who is trying to "get away" from the stylistics of the lacquer miniature in his work on the publication "Words", that the scientific novelty of the study consists. The main conclusion of the article is the statement about the universality of I. I. Golikov as an artist, which allowed him to illustrate the publication "Words about Igor's Regiment", which immediately after its release became a universally recognized masterpiece of the art of Soviet book graphics.
Implementation of E-Voting in The Election of The OSIS Chairman of Smkn 2 Rancaekek

In a school organization called OSIS, in general, there must always be a leader or can be called the chairman of the organization, there is an OSIS organization chairman, which aims to promote and prosper the organization in junior high schools and vocational schools, they also must have leadership structures and when We need a leader who deserves to be elected. Therefore This study aims to implement E- VOTING in the selection of student council leaders at SMKN 2 RANCAEKEK because some of the schools are still elected directly or can also be called by voting using paper. To support the research, we use the waterfall method of software development. The sequence in the waterfall method is very serial starting from the planning process of analysis, design, and implementation of the system. results show that election chairman OSIS this use Besides Fulfill principles, we must follow development technology Information as well as speed up the results of the vote recapitulation. Electronic voting or E-Voting is something from collection voice which normally used election general using electronic media. E-Voting also makes elections easierfor example: no eat the cost, speeds up recapitulation voice, honest, fair, happening transparency, and reduces fraud. Because that paper, discusses the application of E- Voting if it is applied to the field of school organization, namely in schools Vocational High School 2 RANCAEKEK.
Game Design For an Environmental-themed 2D Adventure Mobile Game

Game is a game based on technology media, which is currently one of the entertainments today. The development of games has become a technology that can be felt, through computers to cellphones. One of the game media, namely mobile games, is an attraction for gamers (people who play games) now. Game makers are competing to make games interesting and useful for game lovers. The genres presented are also diverse, such as RPG, Open World, Horror, Puzzle, Sport, and others. At this time the design of the mobile game focuses on the slide type game, where the camera in the game moves right and left, and the illustrations presented are 2D. This game takes the topic of the environment, which through the game tries to invite players to preserve, learn, and understand about the environment, presented with the spices of RPG (Role Playing Game) games as well as a strong story presentation
User Profiling Using Keystroke Dynamics and Rotation Forest

The anonymity that users can maintain when connecting to the internet, in addition to the positive effects, such as being able to express their views and ideas freely without fear of retaliation, also carries some risks, such as the fact that it is a significant advantage for malicious users. In order to remove the complete anonymity of internet users, so as to protect unsuspecting users, this work attempts to identify some of their characteristics, namely gender, age, and handedness, using data coming from typing. For this purpose, the rotation forest is used as a classifier, and keystroke dynamics features are selected based on the chi-square feature selection procedure. The final results show that user profiling can be achieved with an accuracy of 88.9% in gender prediction, 86.3% in age prediction, and 94.3% in handedness prediction.
Bi-level Optimization Method for Automatic Reward Shaping of Reinforcement Learning

The key to lowering the threshold of the application of reinforcement learning is the simplicity and convenience of reward function design. At present, reinforcement learning with good performance mostly adopts complex rewards of artificial trial and error, or adopts supervised learning to track the artificial trajectory, but these methods increase the workload. Assuming that the basic mathematical elements (operators, operands) can be used to automatically accomplish the combinatorial search process, it is possible to search for a compact, concise and informative reward model. Starting from this idea, this paper explores the reward function of reinforcement learning, which can find the optimal or suboptimal solution that can meet the multi-optimization index through operator search without clear prior knowledge. Based on AutoML-zero, the automatic search method of operator-level reward function based on evolutionary search is realized, and the reward function algorithm which can satisfy the constraint conditions is found to be equal to or better than human design.
Wasserstein dropout

Abstract Despite of its importance for safe machine learning, uncertainty quantification for neural networks is far from being solved. State-of-the-art approaches to estimate neural uncertainties are often hybrid, combining parametric models with explicit or implicit (dropout-based) ensembling. We take another pathway and propose a novel approach to uncertainty quantification for regression tasks, Wasserstein dropout , that is purely non-parametric. Technically, it captures aleatoric uncertainty by means of dropout-based sub-network distributions. This is accomplished by a new objective which minimizes the Wasserstein distance between the label distribution and the model distribution. An extensive empirical analysis shows that Wasserstein dropout outperforms state-of-the-art methods, on vanilla test data as well as under distributional shift in terms of producing more accurate and stable uncertainty estimates.
Council on Foundations workshop on policy advocacy

Nonprofit Business AdvisorVolume 2022, Issue 397 p. 4-4 Conferences & Events Council on Foundations workshop on policy advocacy First published: 07 September 2022 https://doi.org/10.1002/nba.31312Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume2022, Issue397October 2022Pages 4-4 RelatedInformation
CNN-BASED CONTINUOUS AUTHENTICATION OF SMARTPHONES USING MOBILE SENSORS

With the advancement of technology, the smartphone has become a reliable source to store private details, personal photos, credentials, and confidential information. However, smartphones are easily stolen and it has become a suitable target for attackers. Usually, smartphones require only initial explicit authentication, once the initial login is passed all the information can be accessed easily. Hence, this paper proposes an efficient implicit, continuous authentication of the smartphone based on the user’s behavioral characteristics. We propose architecture to differentiate legitimate smartphone owners from intruders. Our model relies on the smartphone’s built-in sensors like an accelerometer, gyroscope, and GPS. The sensors respond according to the user’s behavior which is recorded by the smartphone. We have used the rest filter model to separate motion data from rest since the rest data does not contain much information about the user’s behavior. We have used Xgboost and Convolutional Neural Network as our rest filter and legitimate-intruder classifier respectively. Our system can predict legitimate and intruders in a few seconds. Our proposed CNN model has an achieved average accuracy of 95.79% in our custom dataset, which has further improved after integrating GPS data.
EFEKTIFITAS PEMBELAJARAN DARING DENGAN E-MODUL TERINTEGRASI GOOGLE EDUCATION PADA MATA PELAJARAN MATEMATIKA KELAS VIII

Student interest in class VII SMP NAMIRA Kota Probolinggo on subject Mathematics is classified as low, especially when the subject mathematics fells like it’s always being skipped. This is an accordance with the results of diagnostic Assesment and learning interest of 60 students, the percentage of high interest in learning Mathematics subject, only 30 %. Mathematics is a subject that is considered difficult. It is a challenge to present on pandemic or daring of learn it in an must attractive, easy and fun away. Solution to overcome this problem is through the implementation of google education integrated e-book. The purpose os this study was to determine effectivity of implementation of google education integrated e-book on class VII SMP NAMIRA Kota Probolinggo. The research method used is Mathematics Realistic integrated discovery learning that present on e book. E-book that created with Bookcreator application mix google education. Data collection techniques used were test of students understanding, attitude assessment, observation (quisoner), reflection learning of Mathematics. The results showed that the implementation of google education integrated e book is effective with interest Matematics subject increasing 55,6% on the first meet, the second meet to be 83% . Students learning outcomes describe student interest to follow learning of Mathematics, it is shown assignment collection and result show 10 % under KKM Mathematics subject.&#x0D; Keywords: e-book, Bookcreator, Google Education, FAAST
Movie Recommender System Using Content-based and Collaborative Filtering

One of the most effective and widely used applications of machine learning technologies in business is recommender systems. Machine learning algorithms from the field of artificial intelligence have recently been used in these systems. Many varieties of movies have become increasingly diverse as technology and entertainment development have advanced, leaving users perplexed as to how to choose amongst them. The main aim of a movie recommendation system is to deal with a recommender approach using data clustering and computational intelligence. This recommender system’s goal is to acquire insights based on the user ‘s choices and to achieve customer satisfaction by presenting effective findings and optimizing the time a user spends on the website or platform.