Reviewerly/exHarmony huggingface dataset:
Situational Criminogenic: The Financial Crime’s Collaborative Factors in Indonesia

Financial crimes in Indonesia from 2014-2018 were classified as quite dynamic with a total of 241,367 cases. In 2018 the legal unit area of Polda Metro Jaya had the highest number of cases of 5,526 cases of financial crimes. This study seeks to examine the determinant aspects of financial crime in Indonesia. I used the illustration of the case of First Travel and the Koperasi Simpan Pinjam (KSP) Pandawa that occurred in Indonesia with a total loss of up to IDR 1 trillion. Discussions in this paper begin from the point of view of white collar crime that elaborated with criminaloid and organizational criminogenic aspects. This study uses a grounded theory method through in-depth interviews of actors. The result is that on the criminaloid aspect, the perpetrators have a tendency to easily confess, have certain social and cultural status, has moral sensitivity and intelligence, and has skills, but hesitates in acting. Meanwhile, in the organizational criminogenic aspect, it was found that the perpetrators were in an environment with profit-oriented ambitions, had certain business perceptions, had a loyal attitude towards their group and their human resources tended to be homogeneous. The results of this study found that a supportive situation is needed in financial crime based on the illustrations of the cases used. Situational criminogenic aspects in research in the form of business that utilize religious sentiments, use a cooperative system and manage funds with a Ponzi scheme. This research will enrich criminology studies, especially in the field of white collar crime. Other than that, hopefully can be useful in the formulation of policies for stakeholders.
Prediction of the Optimal Umbrella Shape of Insulators Based on Data Mining Technology

Abstract The insulator flashover process is affected by many factors. In order to better study the factors that affect the insulator flashover voltage, and then accurately predict the insulator flashover voltage. In this paper, 11 different types of composite insulators are studied through artificial pollution tests. Data mining technology has been widely used now. In order to better apply data mining in the prediction of insulation flashover voltage, this paper adopts the BP neural network in data mining technology to predict the flashover voltage of different umbrella-shaped insulators. In addition, in order to further improve the prediction accuracy of the model, this paper uses the global search capability of genetic algorithm to optimize the initial weights and thresholds of the BP neural network, and optimizes the BP neural network prediction model, and established an optimization model based on genetic algorithm to optimize BP neural network. Through this method, the flashover voltage of the insulator can be predicted in time, which is of great significance for maintaining the safe and stable operation of the power system.
Topological drone navigation in uncertain environment

Purpose With the increasing demand for surveillance and smart transportation, drone technology has become the center of attraction for robotics researchers. This study aims to introduce a new path planning approach to drone navigation based on topology in an uncertain environment. The main objective of this study is to use the Ricci flow evolution equation of metric and curvature tensor over angular Riemannian metric, and manifold for achieving navigational goals such as path length optimization at the minimum required time, collision-free obstacle avoidance in static and dynamic environments and reaching to the static and dynamic goals. The proposed navigational controller performs linearly and nonlinearly both with reduced error-based objective function by Riemannian metric and scalar curvature, respectively. Design/methodology/approach Topology and manifolds application-based methodology establishes the resultant drone. The trajectory planning and its optimization are controlled by the system of evolution equation over Ricci flow entropy. The navigation follows the Riemannian metric-based optimal path with an angular trajectory in the range from 0° to 360°. The obstacle avoidance in static and dynamic environments is controlled by the metric tensor and curvature tensor, respectively. The in-house drone is developed and coded using C++. For comparison of the real-time results and simulation results in static and dynamic environments, the simulation study has been conducted using MATLAB software. The proposed controller follows the topological programming constituted with manifold-based objective function and Riemannian metric, and scalar curvature-based constraints for linear and nonlinear navigation, respectively. Findings This proposed study demonstrates the possibility to develop the new topology-based efficient path planning approach for navigation of drone and provides a unique way to develop an innovative system having characteristics of static and dynamic obstacle avoidance and moving goal chasing in an uncertain environment. From the results obtained in the simulation and real-time environments, satisfactory agreements have been seen in terms of navigational parameters with the minimum error that justifies the significant working of the proposed controller. Additionally, the comparison of the proposed navigational controller with the other artificial intelligent controllers reveals performance improvement. Originality/value In this study, a new topological controller has been proposed for drone navigation. The topological drone navigation comprises the effective speed control and collision-free decisions corresponding to the Ricci flow equation and Ricci curvature over the Riemannian metric, respectively.
Research on Time Bank’s Mutual-support Old-aged Care Mode Based on Blockchain Technology

With the development trend of aging and low fertility in China, disability and dementia increase year by year in the elderly population. The demand of long-term life care service for the elderly with disability and dementia brings great challenges to the service supply and funds of the traditional endowment insurance model. However, with the application of blockchain technology, the Time Bank’s mutual-support old-aged care mode can better solve the above problems. First, the author uses SWOT analysis to comprehensively analyze the advantages, difficulties, opportunities and challenges of the Time Bank’s Mutual-support for the Aged mode in China, then the blockchain technology is applied to this mode, finally the corresponding optimization scheme and suggestions are put forward.
Stufflebeam's Model Application of Education Management Information Systems (EMIS) in Improving the Quality of Learning Services

Advances in science and information technology have changed the perspective and lifestyle of the Indonesian people in carrying out their activities, including in the world of education. The application of the Education Management Information System (Emis) today is a must for every educational institution. In learning, the application of Emis is expected to improve the quality of learning services which in turn will improve the quality of teachers and students, especially in the field of Information Technology. The four basic management functions put forward by Terry are Planning, Organizing, Actuating and Controlling (POAC), the dimensions of service quality created by Haksever et al., As well as the program evaluation model developed by Stufflebeam (Stufflebeam's Model) or CIPP Model, Becomes theoretical basis as an analysis knife or the framework of ideas used to analyze, synthesize and provide solutions for the application of Emis in SMA and SMK Ma'arif Banyuresmi Garut in improving the quality of learning services. The implementation of Emis in SMA and SMK Ma'arif starts with the creation of a strategic plan for learning Emis, the formation of an IT team and a letter of assignment, budget provision, preparation and procurement of learning media for Emis, preparation of Standard Operating Procedures (SOP), socialization and training on the use of Learning Emis, Implementation of Learning Emis, Evaluation of the application of Learning Emis and the impact of the application of Learning Emis on the quality of learning services and on the quality of teacher human resources and the quality of student human resources
A multi-level visualization method for IT system structure

This article is to solve the problems of disordered and complex architectural relationships in IT in the multi-level visualization of the IT system structure, and the relationship is not transparent and intuitive.3D visualization has its unique display advantages. By integrating the visualization concept into the IT architecture management process, Establish a multi-level visualization model of IT system structure, covering from the IT infrastructure level to the system application and business logic level, analyze location attributes, node types, rule attributes and relationship attributes, and present them in a three-dimensional visualization form to make IT internal structural relationships And the relationship between nodes is clear and intuitive.This article uses different layout algorithms such as hierarchical layout algorithm, circular distribution algorithm, star layout algorithm, etc.According to the different characteristics of the number of IT system nodes and node relationships, matching the corresponding layout algorithm makes the multi-level IT system visualization architecture more flexible.The experimental results show that the method proposed in this paper can show the IT system structure simply and clearly, and match various complex business relationships more flexibly.
Exploiting Home Infrastructure Data for the Good: Emergency Detection by Reusing Existing Data Sources

Monitoring people within their residence can enable elderly to live a self-determined life in their own home environment for a longer period of time.
Deep neural network based approach for robust aerial surveillance

Aerial object detection is one of the most important applications in computer vision. We propose a deep learning strategy for detection and classification of objects on the pipeline right of ways by analyzing aerial images captured by flying aircrafts or drones. Due to the limitation of sufficient aerial datasets for accurately training the deep learning systems, it is necessary to create an efficient methodology for object data augmentation of the training dataset to achieve robust performance in various environmental conditions. Another limitation is the computing hardware that could be installed on the aircraft, especially when it is a drone. Hence a balance between the effectiveness and efficiency of object detector needs to be considered. We propose an efficient weighted IOU NMS (intersection over union non-maxima suppression) method to speed up the post-processing time that satisfies the onboard processing requirement. Weighted IOU NMS utilizes confidence scores of all proposed bounding boxes to regenerate a mean box in parallel. It processes the bounding box score at the same instant without removing the bounding box or decreasing the bounding box score. We perform both quantitative and qualitative evaluations of our network architecture on multiple aerial datasets. The experimental results show that our proposed framework achieves better accuracy than the state-of-the-art methods for aerial object detection in various environmental conditions.
On-Device Text Representations Robust To Misspellings via Projections

Recently, there has been a strong interest in developing natural language applications that live on personal devices such as mobile phones, watches and IoT with the objective to preserve user privacy and have low memory.Advances in Locality-Sensitive Hashing (LSH)-based projection networks have demonstrated state-of-the-art performance in various classification tasks without explicit word (or word-piece) embedding lookup tables by computing on-the-fly text representations.In this paper, we show that the projection based neural classifiers are inherently robust to misspellings and perturbations of the input text.We empirically demonstrate that the LSH projection based classifiers are more robust to common misspellings compared to BiL-STMs (with both word-piece & word-only tokenization) and fine-tuned BERT based methods.When subject to misspelling attacks, LSH projection based classifiers had a small average accuracy drop of 2.94% across multiple classifications tasks, while the fine-tuned BERT model accuracy had a significant drop of 11.44%.
PELATIHAN FOTOGRAFI DASAR SEBAGAI MEDIA VISUAL PROMOSI WISATA INDONESIA TIMUR

Photography is an activity cherised by many people of all age as hobby. In an era with easy access to internet and social media, photography also enjoys an increase in popularity. Young adult age group is the one who benefits the most from those technology advancements. It’s as if they compete to create images on social media to be liked by other people. However, sometimes people lacking in technological knowledge buy cameras without knowing the full technical functions and differences in image quality produced by them. The lack of knowledge in photography basic techniques and aesthetical composition may cause picture quality to suffer. This Program Pengabdian kepada Masyarakat (PkM) with the theme of Photography Basic Training aims to grow basic photography skills as a tool to produce interesting stock photos. Therefore, participants will have the capability to capture the exoticism of East Indonesia, where they come from. Tourist promotion with easthetically pleasing photos is believed to be positively impacting visitor numbers. It’s true that informations about photography basic techniques are prevalent online, but people who are only beginning to learn still need face-to-face guidance to assure transfer of informations occur the right way. After engaging in this PkM program, their knowledge and skill of basic photography techniques will improve. They will be more knowing of how to make more interesting pictures.
On estimation and feedback control of spin-1/2 systems with unknown initial states

In this paper, we consider stochastic master equations describing the evolutions of quantum systems interacting with electromagnetic fields undergoing continuous-time measurements. In particular, we study feedback control of quantum spin1/2 systems in the case of unawareness of initial states and in presence of measurement imperfections. We prove that the fidelity between the true quantum filter and its estimation (with arbitrary initial state) converges to one under appropriate assumption on the feedback controller. This shows the asymptotic convergence of such filters. In the more general case of spin-J systems, we discuss heuristically the asymptotic behavior of the true quantum filter and the associated estimation, and the possibility of exponentially stabilizing such systems towards an eigenvector of the measurement operator by an appropriate feedback.
How do people interact with biased text prediction models while writing

Recent studies have shown that a bias in thetext suggestions system can percolate in theuser’s writing. In this pilot study, we ask thequestion: How do people interact with text pre-diction models, in an inline next phrase sugges-tion interface and how does introducing senti-ment bias in the text prediction model affecttheir writing? We present a pilot study as afirst step to answer this question.
VIEWERS’ LANGUAGE STYLES ON GOLD DIGGER: A MULTIMODAL ANALYSIS

This paper undertakes viewers' languages style on gold digger using a multimodal analysis. This paper aims to depict the language style of viewer comments on Gold Digger prank in YouTube channel content. Comments on the contents of YouTube channel may differ from active viewers, and the language style they utilized shows the culture, the background, or class where they are from. Therefore center on language style constitutes the main point of this study. The corpus was achieved by viewers' comments on the gold digger prank as one of the YouTube channel contents. The study employed a descriptive qualitative research approach and the content or viewers comments on YouTube as the form of data. The study will focus on the viewers' style language in commenting on the prank content called Gold Digger in the YouTube channel and the style language that the viewers mostly utilized multimodal analysis. Casual style is the dominant style conveyed by the viewers. The viewers' language style varies on the bases of the intimacy, the social interaction and the community from which they come, and the media in which they share their thoughts.
Attitude of Students towards Cooperative Skills in Learning Kadazandusun Language in Malaysia

The purpose of this research is to identify the attitude of students towards cooperative skills in the learning of Kadazandusun language in a few secondary schools around Sabah state, Malaysia. The respondents consist of 265 Form 2 students from eight secondary schools, who is learning Kadazandusun language. The 5 point Likert scale is used in the questionnaire. There are ten items each with the attitude and cooperative skills section. To analyse the data obtained, descriptive analysis and Spearman’s Rhohave been used. The descriptive result shows a mean score for attitude is between 3.04 to 4.31, and 4.07 to 4.57 for cooperative skills. Correlation analysis shows a significant positive and medium strength of relationship between the attitude of students with cooperative skills in learning Kadazandusun language,(rs=0.533, p&lt;0.01). This research implicates the importance of cooperative skills in learning Kadazandusun language in the 21st century in line with the need of industrial revolution 4.0.
AR.Drone 2.0 state estimation using Dynamic Expectation Maximization: Bringing brain perception theory to practice

Recent developments in neuroscience research, mainly introduced by neuroscientist Karl J. Friston, have resulted in a concept called the Free Energy Principle (FEP). The FEP is a brain theory unifying action, perception and learning. An important observation is that autonomous robots have to perform similar tasks to the human brain. Therefore, these developments are very interesting from a control engineering perspective. A lot of research is going on in the direction of Active Inference (AI), which includes the perception and action parts of the FEP used for filtering and control on physical systems. However, a research gap exists for the theory describing the complex mathematical backbone of perception and learning, called Dynamic Expectation Maximization (DEM). DEM is a parameter estimation algorithm that can be used to perform filtering as well as system identification. This thesis is part of the research aiming to evaluate the performance of DEM as a filtering as well as system identification technique. To be more specific, this thesis considers the filtering part. In general, a filter is meant to derive the states of a system using a system model and sensor measurements. The system model is often not perfect, resulting in process noise, and the sensors provide noisy data, resulting in measurement noise. Many existing filtering techniques, including the conventional Kalman filter, assume these noises to be white. However, the process noise contains unmodelled system dynamics that introduce correlation. Therefore, by definition, the process noise is not white, but coloured. The main advantage of using the DEM filter is the ability to extract information from the correlation in the measurements and the noises to construct a better state estimate. Simulation results in previous work indicated the potential of DEM as a filter. The next step is to prove the usefulness of the DEM filter on a physical system. In order to do so, this thesis describes the design of an experimental setup with a quadrotor Unmanned Aerial Vehicle (UAV) used to evaluate the performance of the DEM filter. The recorded flight data is used to analyze the process and measurement noises. Furthermore, the DEM filter is compared with the conventional Kalman filter. It turns out that for a relatively big subspace of DEM tuning parameters, the DEM filter is able to outperform the Kalman filter, which proves the potential of this filtering algorithm in a practical robotics setting.
Online Technologies As an Innovative Form of Working with Applicants

This article offers an analysis of the system of professional orientation of modern students. The main problems of pre-university training arising from the digitalization and informatization of education are disclosed. The main ideas of applying social networks and online services in career guidance activities are substantiated. Significant advantages of online career guidance services over traditional methods are shown.
DNA Based Criminal Identification Using Block Chain

The emergence of the internet has made it possible for all the users to be connected with each other regardless of the physical distance. The ever-increasing use of internet comes with its own risks and cyber security is always an active issue when it comes to the internet. It is common to hear people’s emails and other sensitive information to be hacked and stolen, compromising their data integrity and various others threats. With the increase in the number of attacks that are occurring digitally, cyber security has become one of the most crucial parts of this modern society. This paper demonstrates the implementation of block chain to show how it decreases the risk associated with sharing sensitive information over the internet, in this case DNA data of criminals which needs to be accessed from different places by different agencies in order to identify the criminal using their DNA information.
The Effects of the Havruta Discussion Program on Critical Thinking Ability and Communication Ability of the Gifted

본 연구는 하브루타 토론 프로그램이 영재의 비판적 사고력과 의사소통능력에 미치는 효과를 알아보고, 하브루타 토론, 소집단 토론, 프로젝트 교수법간의 효과 차이를 알아보고자 하였다. 이를 위해 하브루타 토론 교수법을 적용한 프로그램을 15차시 과정으로 개발하였고, 레이븐 지능검사 결과 백분위 90이상의 수행결과를 보인 중등 영재교육대상자 38명을 하브루타 토론 10명, 소집단토론 10명, 프로젝트 18명으로 분류하여 실시하였다. 본 연구의 결과는 다음과 같다. 첫째, 하브루타 토론 프로그램을 적용한 집단의 비판적 사고력과 의사소통능력의 하위요인별 효과를 분석한 결과 유의한 향상 결과를 나타냈다. 둘째, 하브루타 토론 프로그램을 적용한 집단은 비판적 사고력과 의사소통능력에서 소집단 토론 및 프로젝트 수업을 적용한 집단과 유의한 차이를 나타냈으며, 검정결과 하브루타 토론 프로그램이 비판적 사고력과 의사소통 능력을 향상시키는데 효과적인 것으로 나타났다. 따라서 본 연구를 위해 개발한 하브루타 토론 프로그램은 영재의 비판적 사고력과 의사소통능력을 향상시키는데 효과적이며, 영재교육을 위한 교수법으로 하브루타 토론 방법을 제안하고자 한다.The purpose of this study was to find out the effect of the Havruta discussion program on the critical thinking and communication ability of the gifted, and to find out the difference between the Havruta discussion, the debate, and the project teaching method. To this end, the program that applied the Havruta discussion method was developed into a 15th period, and 38 students who were eligible for secondary education were classified into 10 Havruta discussions, 10 debate, and 18 projects, where the Raven intelligence test was applied; the results showing that the students performed at more than the 90 percentile. The results of this study are as follows: First, the groups applying the Havruta discussion method showed significant differences from those applying the debate and project method group in critical thinking and communication skills. Second, the effects of the group’s critical thinking and communication skills using the Havruta discussion program methods were analyzed showing both effective and significant improvement. Therefore, the Havruta discussion program developed for this study is effective in improving the critical thinking and communication skills of the gifted and thus we propose a method of Havruta discussion as a teaching method for gifted education.