Reviewerly/exHarmony huggingface dataset:
Synthetic Benchmarks for Scientific Research in Explainable Machine  Learning

As machine learning models grow more complex and their applications become more high-stakes, tools for explaining model predictions have become increasingly important. This has spurred a flurry of research in model explainability and has given rise to feature attribution methods such as LIME and SHAP. Despite their widespread use, evaluating and comparing different feature attribution methods remains challenging: evaluations ideally require human studies, and empirical evaluation metrics are often data-intensive or computationally prohibitive on real-world datasets. In this work, we address this issue by releasing XAI-Bench: a suite of synthetic datasets along with a library for benchmarking feature attribution algorithms. Unlike real-world datasets, synthetic datasets allow the efficient computation of conditional expected values that are needed to evaluate ground-truth Shapley values and other metrics. The synthetic datasets we release offer a wide variety of parameters that can be configured to simulate real-world data. We demonstrate the power of our library by benchmarking popular explainability techniques across several evaluation metrics and across a variety of settings. The versatility and efficiency of our library will help researchers bring their explainability methods from development to deployment. Our code is available at https://github.com/abacusai/xai-bench.
Programming design, education, innovation, exploration and practice based on students’ cognitive laws

This paper analyses the cognitive characteristics and cognitive laws of freshmen students in learning the C programming language. We have built a spirally ascending complete curriculum theory knowledge system and a practical teaching model of experience–verification–exploration. The knowledge system is established through programming thinking from the perspective of computer systems, designed according to the teaching structure of knowledge construction and trained based on the engineering literacy with a new engineering background. The implementation of the teaching reform has achieved the expected results. The curriculum theory knowledge system is complete, and the practical teaching content is novel and rich. It has stimulated students’ learning enthusiasm and innovative consciousness, cultivated students’ professional qualities and helped to cultivate talents that meet the needs of the industry.&#x0D; &#x0D; &#x0D; Keywords: Programming language, perspective, computer systems, knowledge construction.
Strategic Challenges to Internationalization in Higher Education in a Times of Crisis

The article analyzes the impact of the Covid crisis on the processes of internationalization in higher education institutions, the subsequent reactions and possible management approaches to restore the stability of international activities. The growing interest of European universities, including Bulgarian ones, in implementing an international dimension in higher education has led to a significant commitment of their missions to the concept of internationalization over the last 20 years. But after the beginning of the Covid crisis, there was a stagnation of almost all internationalization processes, especially the mobility of students for periods of study or obtaining a degree. Analyzing the causes and obstacles to mobility, it is clear that in the next few years the situation will be similar. The need for the right strategy and optimal allocation of resources to rebuild internationalization processes, along with all other changes related to the Covid crisis, is not an easy task for universities. They must not only strive to ensure high-quality teaching and learning, but also to develop innovative forms of teaching - motivating, effective, competitive, guaranteeing access to the labor market. This task will require a lot of imagination, creativity and ingenuity from the academic community and from decision makers. But universities need to put in the necessary effort and resources, as students' motivation has not changed - international exposure and education open up a variety of opportunities for young people; provide them with exciting experiences; encourage understanding, sharing of ideas; increase cultural competencies. And, ultimately, build them as stronger individuals and citizens of the world. At the moment, these values are even more important for the future.
Іmprovement of Images by Using Graduate Transformations of Their Furier Deciptions

The object of research is low-quality digital images. The presented work is devoted to the problem of digital processing of low quality images, which is one of the most important tasks of data science in the field of extracting useful information from a large data set. It is proposed to carry out the process of image enhancement by means of tonal processing of their Fourier images. The basis for this approach is the fact that Fourier images are described by brightness values in a wide range of values, which can be significantly reduced by gradation transformations. The work carried out the Fourier transform of the image with the separation of the amplitude and phase. The important role of the phase in the process of forming the image obtained after the implementation of the inverse Fourier transform is shown. Although the information about the signal amplitude is lost during the phase analysis, nevertheless all the main details correspond accurately to the initial image. This suggests that when modifying the Fourier spectra of images, it is necessary to take into account the effect on both the amplitude and the phase of the object under study.The effectiveness of the proposed method is demonstrated by the example of space images of the Earth's surface. It is shown that after the gradation logarithmic Fourier transform of the image and the inverse Fourier transform, an image is obtained that is more contrasting than the original one, will certainly facilitate the work with it in the process of visual analysis. To explain the results obtained, the schedule of the obtained gradation transformation into the Mercator series was carried out. It is shown that the resulting image consists of two parts. The first of them corresponds to the reproduction of the original image obtained by the inverse Fourier transform, and the second performs smoothing of its brightness, similar to the action of the combined method of spatial image enhancement. When using the proposed method, preprocessing is also necessary, which, as a rule, includes operations necessary for centering the Fourier image, as well as converting the original data into floating point format.
ACTIVITY-VALUE APPROACH IN THE APPLICATION OF ELECTRONIC EDUCATIONAL RESOURCES WHILE TEACHING AT A MILITARY UNIVERSITY

The pedagogical conditions for the use of the activity-value approach in teaching cadets of a military university, namely in the process of using electronic educational resources by teachers, have been investigated. The functions of the teacher and students are described in interactive cooperation, within the framework of using computer programs in the classroom in technical disciplines. Some aspects of the algorithm of the teacher's actions when using electronic resources in the classroom with cadets in technical subjects and difficulties in creating a database of computer programs used in practical training are revealed. The attention is paid to media content in educational resources used in training specialists, to the participation in the creation of a database of electronic educational resources for teachers, methodologists, programmers. The goals of the formation of cognitive and professional values of cadets, professional competencies, research abilities of students when working with computer programs in technical subjects are stated. The activity-based forms of teaching are revealed, which teachers use both in classroom and in extracurricular activities, aimed at conveying a holistic view of future professional activities, taking into account the self-reflection of the individual. The scientific novelty of the article lies in the description of computer programs implementation in technical disciplines based on the activity-value approach. As a result, the active use of the activity-value approach by university teachers when using electronic educational resources in the classroom has been substantiated. The article is of interest for novice university teachers, methodologists of departments, adjuncts and applicants.
Types of Elicitation on Students’ Engagement inLearning English

Elicitation technique is designed to drawinginformation from students, generally by asking questions. Thisresearch attempts to identify types of elicitation used by theEnglish teacher in learning English at SMA Plus Taruna AkterlisMedan. The teachers’ elicitation was aimed to know students’engagement in using elicitation technique. This research isconducted by applying descriptive qualitative method. Theparticipants of this study were two teachers and sixteen students.The theory that used is from Doff (1988) mentioned five types ofelicitation technique, namely asking questions, asking questionscombined with picture, asking questions combined with usinggames or activities, asking questions combined with using textsand dialogues, asking questions combined with using nonverballanguage. This study revealed that the frequency of askingquestions (40%), asking questions combined with picture (20%),combined with using games or activities (20%), combined withusing texts and dialogues (60%). The most frequent type ofelicitation used which reached is elicitation technique combinedwith using texts and dialogues;60%. This indicates that elicitationpromoting students’ engagement in learning English
Copyright Protection in Insecure Communication Channels Using a Robust Digital Picture Watermark

With the transition from analogue to digital technology, worries about the security and authenticity of digital material and data have grown. Owners of any type of digital material seek out and experiment with innovative copyright multimedia content protection solutions. In recent years, multimedia protection has become a challenge, and researchers are still looking for and testing new and more effective methods to solve the problem. This thesis project aims to improve the visibility and intensity of invisible watermarking in a typical aeroplane using multilayer Discrete Wavelet Transform (DWT) and embed two marks in the image for verification and copyright purposes. When unprotected digital material flows across an unsecured channel Based on five active locations and the usage of two marks, a new watermarking method has been suggested. Marketing pictures will be included in the assault test set, in addition to the extraction procedure. The test technique was used to evaluate the SNR, PNSR, MAE, and RMSE values in both visual modes and post-attack pictures, as well as the invisibility of watermarking before and after the assault. Our lab results demonstrate that our pictures are both SNR and PNSR valuable, with excellent durability and quality.
Joseph R. Skeen Library : Using Google Scholar and Skeen Library's Resources: Step 1: Configure Google Scholar

Google Scholar can be easily configured to show you which of the search results are available from Skeen Library. Once you've configured your browser with the steps below, just look for the Find full text at NMT link. Step-by-step instructions on configuring Google Scholar
ОСВІТА В РЕАЛІЯХ МЕДІА-ПРОСТОРУ: ФІЛОСОФСЬКЕ ОСМИСЛЕННЯ ПЕРСПЕКТИВ

The article analyzes the extent to which social reality can be considered as constructed. The main causes and consequences of the media's influence on the construction of social reality are analyzed. The main risks and benefits of the influence of the media on education are identified and the main directions of constructive interaction between the media and education are indicated.
New Sorting Algorithm—RevWay Sort

Saha, Swarna Sarkar, Soumyadip Patra, Rituparna Bhattacharjee, SubhasreeSorting provides a method of rearrangement of elements in ascending or descending order. In this paper, we are introducing a new sorting algorithm called RevWay sort in which the two consecutive numbers are compared from left and then from right. This process is repeated $$((n/2)+1)$$ times, where n is the total number of elements. We have compared running time of the proposed algorithm with other sorting algorithms. We run the algorithm starting from 10,000 to 50,000 elements. We found that the newly proposed RevWay sort yields lesser running time compared to bubble and selection sort. For 10,000 elements, RevWay sort takes 203.636 ms, whereas bubble sort takes 364.8243ms and selection sort consumes 337.5543 ms.
Deep Learning-Computer Aided Melanoma Detection Using Transfer Learning

Melanoma which is commonly known as skin cancer is classified under the deadliest cancer types for its form. Research suggests that it is a major cause of death in human beings which accounts for about 75% of fatalities from cancer-related causes. But research proves that if detected in time, this proactiveness may help in increasing the chances of survival of the patient. Computer aided diagnosis has proved its importance in achieving this goal of developing a melanoma detection model that is inexpensive, accurate and easy to use.
2D-to-3D Projection for Monocular and Multi-View 3D Object Detection in Outdoor Scenes

In this article, we introduce the task of multi-view RGB-based 3D object detection as an end-to-end optimization problem. In a multi-view formulation of the 3D object detection problem, several images of a static scene are used to detect objects in the scene. To address the 3D object detection problem in a multi-view formulation, we propose a novel 3D object detection method named ImVoxelNet. ImVoxelNet is based on a fully convolutional neural network. Unlike existing 3D object detection methods, ImVoxelNet works directly with 3D representations and does not mediate 3D object detection through 2D object detection. The proposed method accepts multi-view inputs. The number of monocular images in each multi-view input can vary during training and inference; actually, this number might be unique for each multi-view input. Moreover, we propose to treat a single RGB image as a special case of a multi-view input. Accordingly, the proposed method can also accept monocular inputs with no modifications. Through extensive evaluation, we demonstrate that the proposed method successfully handles a variety of outdoor scenes. Specifically, it achieves state-of-the-art results in car detection on KITTI (monocular) and nuScenes (multi-view) benchmarks among all methods that accept RGB images. The proposed method operates in real-time, which makes it possible to integrate it into the navigation systems of autonomous devices. The results of this study can be used to address tasks of navigation, path planning, and semantic scene mapping.
A Reliable Cloud Based Framework for Large Scale Urban Sensing Systems

The rising usage of smartphones and sensing models in today’s life induces the development of large scale urban sensing networks in communication concepts. With the efficient implementation of people centric mobility models, the personal communication devices of people are acting as the sensor nodes that are capable of sensing the human behaviours and participating in framing the smart protocol designs for smart cities. Without the involvement of mobile users or people, the new protocols for mobility management, traffic management, environmental sensing and other applications become futile. The proposed cloud based model improves the reliability and scalability of the system with its multiple cloud servers design. The single point of failure can be resisted since many cloud servers belonging to a provider is used. So the framework remains fault tolerant in the presence of any server attacks. A standard homomorphic based encryption scheme is used for providing data confidentiality and also data is transferred anonymously improving the privacy of the system. The data aggregation process is supported by the model protecting the user’s privacy. The performance analysis for the proposed framework is done in terms of design goal analysis and computation cost analysis.
Image Forgery Detection using Modified Adaptive Over-Segmentation and Feature Matching

With the emergence of digitisation of Visual Graphics it has been a constant need to extract typical features of Images. Forgery, on the other hand, is not something new to the world of Computer Graphics. In the past it was restricted to craftsmanship and writing and it didn’t affect human civilisation rather it was seen as an art for a few centuries. But, with the advent of the technology it has been noticed that by the use of computerised picture handling softwares and altering devices a picture can be easily changed and controlled. It is notably done nowadays to falsify and spread certain narratives through the Media and on the Internet. These alterations show that even graphical information is as vulnerable as any other information, questioning the credibility of digital images. This work is an improvement of an already existing Adaptive Over- Segmentation technique which has recently been used to detect forgery of a digital image by introducing a new feature of detection of forgery even if noise was introduced to the forged copy of the original image.
A Large-scale Study on Unsupervised Outlier Model Selection: Evaluating the Internal Model Evaluation Strategies

Given an unsupervised outlier detection task, how should one select adetection algorithm as well as its hyperparameters (jointly called a model)?Unsupervised model selection is notoriously difficult, in the absence ofhold-out validation data with ground-truth labels. Therefore, the problem isvastly understudied. In this work, we study the feasibility of employinginternal model evaluation strategies for selecting a model for outlierdetection. These so-called internal strategies solely rely on the input data(without labels) and the output (outlier scores) of the candidate models. Wesetup (and open-source) a large testbed with 39 detection tasks and 297candidate models comprised of 8 detectors and various hyperparameterconfigurations. We evaluate 7 different strategies on their ability todiscriminate between models w.r.t. detection performance, without using anylabels. Our study reveals room for progress -- we find that none would bepractically useful, as they select models only comparable to a state-of-the-artdetector (with random configuration).
Research on the Application of Augmented Reality Technology in the Transformation and Development of Cultural and Creative Industries

INTRODUCTION: In this paper, China Hainan "Li" national woven culture is used as an example, the status quo and problems of cultural creative in-dustry in Hainan are analyzed, and the new trend of the development of Hainan cultural creative industry is further clarified. OBJECTIVES: The in
Empirical Analysis of Cryptocurrencies in Global Financial Market

In this paper, the price fluctuation of Bitcoin under speculative environment is studied.The main objective of the present study is to understand the different types of crypto currency and to investigate bitcoin price drivers under speculative market behaviour. Over the course of the period from 2014 to 2018, the trend in price movements of bitcoin has proved to be strongly speculative. In that regard, investors might be curious about what drivers might be instrumental in these speculative price changes.
LibGuides: High Impact Practices (HIPS): Arts & Humanities

LibGuide to explain and illustrate the different HIPS programs at South Piedmont Community College
Development of Advisory Knowledge-Based Expert System to Identify and Mitigate Unintentional Insider Threats in Financial Institutions of Ethiopia

Security in financial institutions has become a crucial point to be considered, from design to deployment of the ICT systems, with proper care and follow-up. Today, most of the organizations have been transforming their professional activities towards end-to-end automation. Once the ICT systems or the data centers get connected via the internet, they are vulnerable or accessible to and threatened by malicious actors both from inside and outside the organization. Moreover, insiders cannot be easily detected, defended or quarantined because they are trusted insider employees. They do make innocent mistakes and sometimes erroneously pass on confidential customer records to outsiders. Their intention and coding conventions also cannot be easily traced, detected or disclosed. Hence, it is vital for the financial institutions to employ real-time surveillance to secure and protect organizational computing, communication and collaboration activities with data/information integrity. These kinds of issues and challenges are common in the financial institutions of Ethiopia. As a matter of fact, there is an acute shortage of cyber security specialists in Ethiopia who can provide adequate security awareness and training to the stakeholders. To address the aforementioned issues and challenges, the paper has designed and developed advisory knowledge-based expert system which can identify and mitigate unintentional insider threats in financial institutions of Ethiopia with a structured guideline for legitimate users. Prolog has been used to develop the prototype of knowledge-based expert system. The paper applies exploratory applied research using quantitative approach, and rule-based approach is used as knowledge representation technique.
Pengembangan Dashboard Bidang Kerja Sama, Bisnis dan Pemasaran Politeknik Caltex Riau Menggunakan Metode Prototype

Marketing, Cooperation and Alumni of Caltex Riau Polytechnic is a unit that works to handle Marketing, Cooperation and Tracer graduates of the Riau Catex Polytechnic (PCR). Based on the results of interviews with the deputy director and staff in the Field of Marketing, Cooperation and Alumni (PKA) of the Caltex Riau Polytechnic, information was obtained that the Caltex Riau Polytechnic had developed a dashboard, Business and Marketing (KBP) dashboard system used to make decisions. However, the system still needs to be developed in the visualization and data management section. The development in the Visualization section focuses on two features namely the Project and Alumni User Tracer features. With the condition of the dashboard system that still needs to be developed, resulting in tracer decision making for alumni and project users cannot be done. In addition, Marketing, Cooperation and Alumni staff use database access directly in managing their data. This makes it difficult for staff to manage their data. In addition, managing data directly accessing the database server can result in database damage if a human error occurs. Another problem, can be fatal if a data leak occurs. Therefore, the development of dashboard data visualization and data management is carried out on the KBP Dashboard system. The developed system will be implemented on the KBP Dashboard system. The results obtained after the development of data visualization on the KBP dashboard are able to assist the deputy director of Marketing, Cooperation and Alumni in decision making and dashboard data management that can be used to manage data in the Marketing, Cooperation and Alumni Field