Reviewerly/exHarmony huggingface dataset:
Visual decision aids: Improving laypeople’s understanding of forensic science evidence

Forensic science plays an important role in the criminal justice system, however research and miscarriages of justice have demonstrated that laypeople can easily misunderstand the results of forensic tests. Given the importance of these test results, interdisciplinary oversight groups have called for clearer expression of forensic tests’ corresponding error rates. Meanwhile, a large body of research in the medical domain suggests that visual decision aids can improve understanding of statistical information. Seeking to apply decision aids to the forensic domain, we present three preregistered experiments (N = 879) demonstrating that visual decision aids may indeed improve understanding of forensic science evidence. A mini meta-analysis across the three experiments comparing control conditions to visual aids demonstrated a medium effect size of g = 0.35. Therefore, decision aids represent a promising, easy-to-implement way to improve laypeople’s understanding of forensic science evidence, thereby potentially preventing associated miscarriages of justice.
SOSIALISASI PROSPEK KARIR DI INDUSTRI IT BAGI SISWA SMK DI JAKARTA SELATAN

For vocational students, determining the choice of college majors according to their talents, interests, and abilities, which can determine future careers is a problem that is quite confusing and often occurs even until the time for college entrance selection arrives. Meanwhile, rapid technological innovation creates an IT industry that promises enormous career opportunities. Thus, vocational students need to know information about career prospects in the IT industry. This community service activity is carried out in the form of a webinar to provide information about careers in the IT industry and promising prospects in the future. The method used is the presentation of material online through the Zoom Meeting application to webinar participants who are vocational students in South Jakarta. The steps carried out in this activity are observation, data collection, literature review, material creation, implementation, and evaluation. The result of this activity is that vocational students get useful references and insights regarding career prospects in the IT industry.&#x0D;
Chaotic dynamics model based on field-programmable analog array technology

Engineering applications in secure communications and encryption based on chaotic signals have attracted a lot of attention in the past decade. This paper presents an extensive study of the chaotic dynamics model of the Van Der Pol oscillator via MATLAB/Simulink simulation and its practical implementation using field-programmable analog matrix techniques. The obtained results show the ease of changing the frequency of the oscillator signal once it is retrieved, creating the required changes, and loading it again according to the required changes. An unlimited number of signals can be generated, allowing them to be used as a chaotic signal oscillator used in many transceiver systems, which require the generation of an unlimited number of such a signal. These research results confirmed that the AN231E04 field-programmable analog array (FPAA) device could be an interesting choice for analog circuit designers, it has the advantage of the ease of use in introducing design changes and testing many critical design solutions.
Effectuating Blockchain Network Compromise by Orchestrating a Daisy - Chain Architecture

As the surface of blockchains is increasing over the years, several vulnerabilities and attacks have been identified in the network, and several of those are currently being exploited without proper remediation from the providers. Circumstantially, the security of vendors and users is at stake from this. Investigation: This paper demonstrates a simulated daisy-chain attack on a victim who is a user of the ETH blockchain. The attack involves the participation of other exploitation techniques used to jeopardize the victim's wallet and insecurely transfer funds across the network. Method: The daisy-chain attack uses privilege escalation to first compromise the machine as an administrator, then misusing the privilege, installing multiple miners, and performing an eclipse attack into the blockchain. Later, transferring funds using a double-signing attack. Principle Result:The simulated attack was successful, and funds were transferred to another wallet through the simulated blockchain.The reverse shell remained persistent, and the ETW (Event Tracer for Windows) was disabled successfully so no traces could be found.However, a multitudinous amount of broadcast packets was needed to efficaciously perform the eclipse attack.
Digital marketing as a competitive differential in sales of a lingerie store in Sergipe

With the COVID-19 pandemic, companies needed to innovate to stay in the market, and digital marketing was a means to contribute to improving sales and increasing the visibility of organizations in the market. Therefore, this research aims to analyze how digital marketing can boost sales in a lingerie store. Regarding the methodology, the research is classified as exploratory quantitative, being applied a questionnaire with closed questions to a non-probabilistic sample of customers and potential customers of the company under study. After analyzing the results found, it can be observed that most respondents highlighted that the most used means of communication to find new stores is Instagram and that they buy in the store due to the variety of products and the good price or quality. The data indicate that the store achieves greater visibility through digital means and that the use of digital marketing contributes to increased sales of products, with customers saying that the quality of the photo of the products totally interferes with the choice. Therefore, the importance of investing in digital marketing is emphasized, seeking to improve the relationship between company and customer, and consequently increase the organization's position in the current competitive market.
Leveraging Machine Learning and Model-Agnostic Explanations to Understand Automated Diagnosis of Cardiovascular Disease

Abstract The pervasiveness of cardiovascular disease and physician misdiagnosis creates the urgent need for artificial intelligence models to improve diagnosis accuracy. The first objective of this study was to train machine learning models on publicly available data sets containing simple medical information of patients to diagnose cardiovascular disease. The Multilayer Perceptron (MLP) assembled for this task performed optimally with an F1 score of 0.8968. This prompted the creation of an open-source, automated cardiovascular disease diagnosis tool, powered by the MLP. The second objective of this study was to employ a meta-learning methodology called Local Interpretable Model-Agnostic Explanations (LIME) to understand the impact of different features on the model's diagnosis in the form of marginal probabilities. K-Means Clustering was employed to segment the data into ten clusters, after which each data example was passed through LIME. The resulting histograms depict the complex relationship between feature, cluster, and impact on diagnosis. A series of P-values with contrasting orders of magnitude shows the nuances in the MLP's understanding of patients from different clusters. The results of meta-learning analysis reveal that the most important features for cardiovascular disease diagnosis are fasting blood sugar, type of chest pain, and slope of the ST segment on an electrocardiogram. Future experiments should replicate the novel methodology introduced in this study on data sets containing more specialized medical features in order to gain practical medical insights about different types of cardiovascular disease represented by each cluster. Finally, feature engineering pathways should be explored with consideration of these results to create versatile diagnosis models not only for cardiovascular disease, but adaptable to other diseases as well.
PERANCANGAN SISTEM KEAMANAN BRANKAS DENGAN VERIFIKASI PASSWORD DAN SIDIK JARI BERBASIS IOT

The safe box is one of the targets of theft crimes. With today's technological advances, the parts of our bodies can be used as unique identities so that they can be used as system access. This method is quite good because the security system can immediately recognize the physical characteristics of the owner when opening the safe. In this case the authors make a safe box security system with passwords and fingerprints verification based on IoT. This system uses a combination interlock where the fingerprint scanner cannot perform a fingerprint scan without entering a password. Then the alarm will sound, and the system will send a telegram message notification to the safe owner's cell phone if there is an error more than three times when entering the password or during fingerprint scanning, as well as when the safe door is open and when the safe lose of primary power supply to avoid the possibility of the safe moving when there is a theft. Keypad and fingerprint scanner to open the safe door. NodeMcu V3 as a medium for sending data from the microcontroller system to the safe owner's cell phone to provide information to the safe owner in the event of an attempt to break into the safe by someone else. LCD screen as a guide in the process of opening the safe door. From the manufacture of this tool, it is hoped that if someone who wants to break into a safe will be easily identified and maintain more security.
Sistem Informasi Distribusi Rekam Medis ( Studi Kasus : RSAU Lanud Sulaiman )

Sulaiman Air Force Base Hospital is a hospital that organizes service activities for members of the Indonesian Air Force and family members, as well as serving the general public, especially in terms of health. The medical record distribution information system is needed to support services to patients and assist the process of searching and monitoring medical records out and back from the patient's destination polyclinic. The distribution of medical records at the Sulaiman Air Base Hospital has not been computerized in terms of recording and reporting. Thus, the purpose of this research is to design a medical record distribution information system that facilitates the process of recording reports and searching for medical records as well as monitoring the distribution of medical records. The research method using a qualitative descriptive approach, as well as data collection based on field observation techniques, also uses library research techniques by analyzing several references. The system development method uses the waterfall, as well as the stages of system design with Data Flow Diagrams programming language VB.NET . It is hoped that the medical record distribution information system designed in this study can help the medical record distribution process so that it can run well and efficiently.&#x0D; Keywords: DFD, Distribution, Medical Records, Information System
The impact of corporate social responsibility on customer loyalty and employee satisfaction in Bosnia And Herzegovina

The aim of the study is to investigate consumer attitudes towards specific Customer Social Responsibility Activities in Bosnia and Herzegovina. In order to support this research, a case study method, combined with qualitative and quantitative research methods (referenced survey) was used. To get an insight into the companies’ perspective, when it comes to an engagement in the employment practices, as an integral part of Corporate Social Responsibility, data regarding “The Most Desirable Employer” project- “Najpoželjniji poslodavac”, organized by Kolektiv d.o.o.-MojPosao.ba, for years 2020, 2019 and 2018 will be analyzed. The study should illustrate the exact scenario of customer loyalty in Bosnia and Herzegovina to the companies included in CSR activities and contribute to an advancement of overall knowledge in the field of CSR in Bosnia and Herzegovina. The directing outcome uncovers those corporate capacities have a critical part in fortifying the relationship between corporate social responsibility drives and customer trust in Bosnia and Herzegovina, in light of the fact that high corporate capacities with professional corporate social responsibility actions lead to high faithfulness of customers. The examination features the meaning of the corporate social responsibility activities, which are obligatory for authoritative achievement and guides the policymakers of companies, supervisors, and researchers.
The Community of Inquiry Instructional Strategies Impact on Student Satisfaction on Remote Learning

The COVID-19 restrictions compelled institutions worldwide to transition into the remote teaching-learning modality abruptly. Studies evaluating the effectiveness of remote teaching and learning strategies are scant. With the recent shift to this new learning mode, little is known about the fulfillment of learning outcomes and student satisfaction. This research examines the impact of the teaching-learning course design and instructional strategies as implemented by this faculty researcher last school year 2020-2021. It intends to provide practical guidance for teachers aiming to evaluate the effectiveness of their remote teaching/strategies. The research is both quantitative (causal) and qualitative design. A total of 104 management students from a Philippine state university participated in an online survey. The quantitative investigation assessed the influence of the independent variables – the Community of Inquiry (CoI) presence strategies, course design, and instructional strategies on students’ perceived learning and satisfaction, utilizing the CoI framework and adopting scales from online teaching.
Path Planning Algorithm Based on Visual Image Feature Extraction for Mobile Robots

When autonomous mobile robots plan their own movements properly, they first need to perceive the surrounding environment and then make comprehensive decisions based on the surrounding environment information, that is, path planning. Vision can provide abundant and complete environmental information for robots, and it can significantly improve the effect of path planning when it is introduced into the path planning of autonomous robots. In this article, we take the autonomous mobile robot AS-R as the research object and use the multisensors such as a gimbal camera and ultrasonic sensor attached to the robot to study the navigation line information perceived by machine vision, the obstacle information sensed by range sensor, and the fusion of multisensor information to solve the image processing, path recognition, information fusion, decision control, and other related problems of the mobile robot to realize the autonomous mobile robot.
The Design and Implementation of Campus informatization in Chinese Universities: A Conceptual Framework

Abstract With the deepening of educational informatization and the integration of information technology into education, a new form of teaching and management has been emerged. Digital campus is one of the educational reform results, and it shall be established to support the development of intelligent education. This paper aims to explore an overall situation of implementing progress of campus informatization in Chinese universities, and design a conceptual framework of the digital campus, then find out the practical results of Chinese universities which applied the conceptual framework. The advanced technology applied in Chinese campus informatization was analyzed, the main characteristics of the digital campus were put forwarded, and a conceptual framework of digital campus in universities was designed. For this article, we've chosen the one-stop service platform of southwest university as a case study, the practical results of the digital campus include IC card services, integration services, one-stop services, wireless networks, and the implementation of the data center.
Using the Theory of Motivated Information Management to Understand Direct Information Seeking on COVID-19 from Close Contacts

INTRODUCTION: As the COVID-19 pandemic spread like wildfire in 2020, initially, little was known about the pandemic. Various parties including local governments, health agencies, medical researchers, and frontliners made concerted efforts to ensure the accuracy, timeliness, and reliability of the information released to the public. Accordingly, a major focus of this study is to examine the factors influencing COVID-19 direction information seeking from close contacts as determined by the theory of motivated information management (TMIM). MATERIALS AND METHODS: A cross-sectional survey using Google form was distributed to undergraduate students pursuing communication courses at public universities in Malaysia. RESULTS: Out of six hypotheses, only two are not supported. Consistent with TMIM, outcome expectancy and target efficacy predict direct information seeking on COVID-19 from close contacts. Further, target efficacy mediates the relationship between outcome expectancy and direct information seeking. CONCLUSION: Overall, the study found empirical support for TMIM as a useful framework for understanding COVID-19 information management. The repercussions of these findings on TMIM as well as key factors that may influence decision-making on information seeking during a global health pandemic are also discussed.
Mining in extremely imbalanced data: a case study for predicting personnel fraud in a bank

Abstract One of the rare departments that data scientists have not deal with yet is the Internal Audit department where they inspect and try to find out the bank personnel who might have been committing fraud. The main reason of this is the too few known fraudulent cases and thus an extremely imbalanced data between fraudulent and legitimate transactions. On the other hand, the work of the auditors is too complicated as they touch almost all banking system. In this study, we, for the first time in the literature, apply data analytics tools in a novel framework to help the auditors. The aim is to indicate which transactions, or personnel should the auditors inspect in the first place so that they can figure out problems with a higher chance. To overcome the difficulties related with the extreme imbalance of the data, we suggested and compared two different ideas. First one is making use of descriptive techniques together with the predictive tools. The second one is using a genuine technique to oversample the minority class. The models developed are shown to perform good on past data.
Mitigating the Supply Chain Wastages Using Blockchain Technology

Supply chains are crucial for the overall well-being of any business. The present systems of supply chain management are antiquated and need to be revamped. Different kinds of unnecessary wastages are generated across the supply chain, which reduces the performance as well as the responsiveness of the entire supply chain. For a supply chain management system to be efficient, it must maintain a network which is transparent, cost-effective, efficient, responsive, robust, and there is proper end-to-end communication. The present study aims to apprehend the effect of blockchain technology in reducing the different wastages produced in the supply chain. This study into the mitigation of the various supply chain generated wastages first highlights the various features of blockchain. It then tries to understand how these characteristics can aid in reducing the different supply chain wastages generated across the diverse domains of the supply chain thereby resulting in improved product tracking and visibility, reduced overhead costs, removal of intermediaries and better forecasting data for inventory demand.
Matriculation students’ usages and its driving factors in mobile learning for Chemistry

&lt;span lang="EN-US"&gt;The study identified how Malaysian matriculation students employ mobile devices for learning Chemistry, and the driving factors that influence their use of mobile devices for learning Chemistry. A qualitative case study approach was adopted in this study, in which interviews and student journals were the main instruments used for the data collection process. The study was conducted in a matriculation college, and all students were invited to participate in the study voluntarily. A total of 17 students who were actively using mobile devices to learn Chemistry were selected for individual and face-to-face interviews. The data were analyzed in a three-stage process to inductively identify the themes. The analysis revealed that matriculation students used mobile devices for referential and collaborative learning activities. They preferred to search the relevant learning resources on the web, and learn collaboratively with their peers or lecturers. Meanwhile, the driving factors of these mobile learning practices were primarily due the ability of mobile learning to overcome their learning difficulties, convenience, as well as the ability to provide a better user experience in the digital age. The findings of this study suggest that the mobile device is a viable social constructivism pedagogical tool for learning Chemistry. The lecturers and management of matriculation colleges can use the findings of this study as a basis to promote the adoption of mobile learning for Chemistry in the digital age.&lt;/span&gt;
When Does Group Invariant Learning Survive Spurious Correlations?

By inferring latent groups in the training data, recent works introduce invariant learning to the case where environment annotations are unavailable. Typically, learning group invariance under a majority/minority split is empirically shown to be effective in improving out-of-distribution generalization on many datasets. However, theoretical guarantee for these methods on learning invariant mechanisms is lacking. In this paper, we reveal the insufficiency of existing group invariant learning methods in preventing classifiers from depending on spurious correlations in the training set. Specifically, we propose two criteria on judging such sufficiency. Theoretically and empirically, we show that existing methods can violate both criteria and thus fail in generalizing to spurious correlation shifts. Motivated by this, we design a new group invariant learning method, which constructs groups with statistical independence tests, and reweights samples by group label proportion to meet the criteria. Experiments on both synthetic and real data demonstrate that the new method significantly outperforms existing group invariant learning methods in generalizing to spurious correlation shifts.
Applying the Project Portfolio Management Maturity Level Selection Method to an Organization

The purpose of the paper is to create and apply a method for selecting the maturity level of an organization in the field of project portfolio management. A method for assessing the maturity level of an organization in the field of project portfolio management is proposed. The method is based on assessing the application of principles, functions, life cycle, specialized organizational structure, prescribed roles, and responsibilities for their implementation in managing a portfolio of projects. A distinctive feature of the method is that the evaluation uses a generalized table of project portfolio management processes. The functions performed should be reflected in this table. A method is proposed for choosing the maturity level of an organization’s project portfolio management based on the optimization of the maturity level and costs of project portfolio management. The method is applied to select a rational level of maturity of project portfolio management for a technical university.