Reviewerly/exHarmony huggingface dataset:
Klasifikasi Transaksi Penipuan Pada Kartu Kredit Menggunakan Metode Resampling Dan Pembelajaran Mesin

The high number of credit card fraud causes a lot of losses for both users and credit service providers. Because the rate of credit card transactions is very fast, it is necessary to detect credit card fraud as early as possible. However, another challenge that is no less important is the amount of data that is imbalanced between valid and invalid transactions. One solution to the problem of data imbalance is to use a resampling method that can improve the quantity of data so that the accuracy results are good. In this study, three types of resampling methods were implemented, SMOTE, bootstrap, and jackknife. Furthermore, to validate the success of the resampling method, three types of machine learning methods were used. The machine learning methods are SVM, ANN, and random forest. From the test results, it was found that the combination of resampling SMOTE and random forest methods produced the best performance with values of accuracy, precision, recall and F1-score of 99.95%, 81.63%, 90.91% and 86.02%, respectively.
PSYCHOLOGICAL FEATURES OF SELF-ORGANIZATION OF HIGHER EDUCATION SEEKERS AS A FACTOR OF SUCCESSFUL LEARNING ACTIVITY

Theoretical analysis of psychological peculiarities of self-organization of a personality has been made in the article. Self-organization is a principle of personal work organization, which is based on the necessity of using rational techniques in everyday work, methods of planning and working hours distribution. Personalality self-organization of a student in educational activity represents an orderly set of goals and motives of self-development. The effectiveness of educational process is ensured by many factors, determinant among them is a student’s ability to self-dependent acquisition of new knowledge on different stages of professional development, etc. The interrelation between the ability to self-organization and success of students educational activity has been empirically studied. It has been determined, that ability to self-organization and level of students volitional efforts are associated with success indicators of educational activity: those students with higher level of success of educational activity have more developed volitional abilities, are more purposeful, assertive and self-organized than those students who have an average and low level of success.
The importance of habits in student life: results and consequences

The relevance of the research topic lies in the daily practical component of the stated problem. The topic of habits, particularly in student life, is important, because this component affects the professional development of a future specialist. Currently, time management is one of the promising areas of scientific research in recent years. Multi-functionality in the modern world has become a basic requirement for an employee with the massive emergence of information technologies in the era of digitalization. Since the work efficiency of any employee depends on previously acquired skills, it makes sense to investigate the peculiarities of becoming a specialist during the student period. In particular, this concerns the issue of habit formation. The research presents the results of the author’s questionnaire. In particular, a chart of respondents’ answers regarding their age, type of activity, gender, etc. general personality parameters. Based on the respondents’ answers, it was determined whether, in their opinion, habits are an important part of life. Reflections on whether habits can significantly improve or worsen life, and whether they are capable of forming a person’s character, are highlighted. Particular attention is focused on whether habits can be an important factor in student life, as well as on what type of habits prevail in their lives. Currently, a certain number of students do not fully understand the importance of habits with all their consequences. Therefore, it is important to investigate how these habits can affect life and in what way. The results and consequences of the student’s habits have meaning, depending on their beneficial or negative impact. Much depends on the ability to acquire and get rid of various habits. That is why the outline of the problems of the importance of habits in student life and the definition of the accepted connotation for the people of the XXI century. is an actual scientific direction. The article focuses on the definition of types of habits and their impact on a student’s life. The methods of acquiring, losing and consolidating habits in student life have been studied. The main categories on the path to successful habit formation are highlighted, including purpose, simplicity, attractiveness, visibility and satisfaction, and the need to monitor the progress of habits.
Parallel Data Augmentation for Text-based Person Re-identification

Given textual descriptions, text-based person reidentification aims at retrieving the matched target person in a large-scale image pool. In contrast to the traditional person re-identification (Re-ID) task, text-based person Re-ID requires extra extracted discriminative textual representations and then aligns two modal features to narrow down the semantic gap between linguistic domain and visual domain. A majority of previous works design complex network structures and concatenate multi-branch features while failing to pay much attention to problems with the dataset, which requires more parameters learning and might lead to over-fitting. Hence, in this paper, we propose a Parallel Data Augmentation method (PDA) to reduce over-fitting and make the model occlusion resistant without increasing the number of training parameters. Specifically, prior to the training, for an image, we randomly choose a rectangular region of variable size and erase the region with a constant value. Similar to image processing, we randomly add a mask of random length words to a sentence, then the processed data is sent to the TIPCB framework for training. Extensive experimentations on the large-scale CUHK-PEDES dataset show the effectiveness of our method and verify that our method exceeds the state-of-the-art methods.
Practical Analysis of Wechat Service in University Library Management

Wechat as the social software with the highest frequency of use and the largest number of users, has comprehensive functions and humanized design.Applying the built-in functions of wechat to the management and service of university libraries can improve efficiency, improve service quality and provide students with convenient and simple operations to a certain extent.However, how to use wechat functions scientifically and reasonably without making students feel cumbersome processes requires managers to deeply study the advantages and disadvantages of built-in functions, and develop new uses of functions in combination with the actual situation of library management and services.This paper analyzes the feasibility of the application of wechat in the management and service of university libraries, explores new ideas of time, and promotes the high-quality development of university library management.
On the Reformulation of Discretised PDDL+ to Numeric Planning (Extended Abstract)

PDDL+ is an expressive planning formalism that enables the modelling of hybrid discrete-continuous domains. The resulting models are notoriously difficult to cope with, and few planning engines are natively supporting PDDL+. To foster the use of PDDL+, this paper revisits a set of recently proposed translations allowing to reformulate a PDDL+ task into a PDDL2.1 one. Such translations permit the use of a wider set of engines to solve complex hybrid problems.
Dual-Rank Attention Module for Fine-Grained Vehicle Model Recognition

Vehicle fine-grained recognition is an important task in the field of intelligent transportation. However, due to the subtle differences between different vehicle models, and the tremendous difference caused by the different pose of the same vehicle model, the effect of vehicle recognition is less successful and still require further research. In this paper, we propose a dual-rank attention module (DRAM), which can reduce visual interference caused by vehicle multi-pose. In addition, combined with the attention mechanism, our method can not only mine the discriminative features of the vehicle model but also increase the feature richness and improve the accuracy of vehicle model recognition. In this paper, in the initial stage of the network, the STN is used to transform the vehicle pose, meanwhile, the whole image is weighted by the global attention to mine the subtle discriminant features. At the high part of the network, after fusing multi-level feature maps top-down, we designed a fused channel attention module to enhance the feature response of the current category. It achieves 94.1% and 96.9% top-1 accuracy on the Stanford Cars and CompCars datasets, which is more than 2.1% higher than the original baseline network VGG19 but only adds a few parameters. Experimental results show that the DRAM can effectively improve the accuracy of vehicle fine-grained recognition.
Intercultural curriculum design in early childhood education

The I.ECEC+ Project 2018-1-HU01-KA201-047763 (2018-2021) aims at strengthening collaboration among different European institutions working within (or in relation to) early childhood education (ECEC) settings. The general objectives of the project are to contribute to the integration of disadvantaged children and improve the quality of institutional education and care in early childhood. The immediate goal of the project was to learn about the intercultural competencies of professionals working in the field and to assess their training needs in the areas of early childhood education. The Italian, Spanish, Belgian, and Hungarian early childhood educators involved in the projects have gained experiences that can be incorporated into an inclusive early childhood education environment. Based on these experiences, a pilot training was designed and tested for improving early childhood educators’ attitudes towards intercultural and inclusive practices. The effect of the pilot training was monitored by means of observational data. The I.ECEC project also aimed to study and make available successful experiences, good practices and innovative solutions.
A Lightweight Model with Separable CNN and LSTM for Video Prediction

Future frame prediction is an emerging, yet challenging task in the deep learning field due to its inherent uncertainty and complex spatiotemporal dynamics. The state-of-the-art methods achieve significant accuracy at the expense of complex, computationally intensive deep neural networks, which makes it difficult to deploy in mobile devices. In the light of recent wide popularity of Green AI which aims for efficient environment friendly solutions alongside accuracy, we propose a lightweight model using 3D separable convolutions, which can predict future video frames with reduced model size and reasonable accuracy-complexity tradeoffs as compared to the state-of-the-art methods.
On the Foundations of Cycles in Bayesian Networks

Bayesian networks (BNs) are a probabilistic graphical model widely used for representing expert knowledge and reasoning under uncertainty. Traditionally, they are based on directed acyclic graphs that capture dependencies between random variables. However, directed cycles can naturally arise when cross-dependencies between random variables exist, e.g., for modeling feedback loops. Existing methods to deal with such cross-dependencies usually rely on reductions to BNs without cycles. These approaches are fragile to generalize, since their justifications are intermingled with additional knowledge about the application context. In this paper, we present a foundational study regarding semantics for cyclic BNs that are generic and conservatively extend the cycle-free setting. First, we propose constraint-based semantics that specify requirements for full joint distributions over a BN to be consistent with the local conditional probabilities and independencies. Second, two kinds of limit semantics that formalize infinite unfolding approaches are introduced and shown to be computable by a Markov chain construction.
Underwater Image Enhancement Using Image Formation Model and GAN

Underwater vision has played an important role in robotic operations, exploration of seabed resources, sea life monitoring and underwater fishing. However, raw underwater images, which suffer from color distortion and poor image quality, make underwater vision more challengeable than open air vision. To address the mentioned problems, a novel model for underwater image color correction is proposed in this paper. Firstly, a synthetic underwater image generating network is proposed to address the lack of effective underwater training data problem. The model combines a background color prior with an underwater imaging model to generate synthetic underwater images by using in-air images data. By the benefit of the color prior and imaging model, the generating model can be with fewer number of parameters and more effective. Meanwhile, a simple yet effective model is proposed to train on the in-air images and corresponding rendered synthetic underwater images for color correction. Different from other image restoration models with multiple substructure or complicated construction, the proposed method has only few convolution layers. Finally, the enhanced results demonstrate the superiority of the proposed method, which performs favorably against the existing stage-of-the-art methods in both effectiveness and model size aspects.
LITHO-STRUCTURAL MAPPING USING REMOTE SENSING AND FIELD WORK TECHNIQUES: A CASE STUDY FROM CENTRAL SALT RANGE, DISTRICT KHUSHAB PUNJAB PAKISTAN

Litho-structural mapping in an inaccessible rugged and mountainous region like the Central Salt range has frequently been a great challenge and importance for geologists. For this purpose, in the present study, litho-structural mapping was carried out based on enhancement and interpretation of Landsat 8 USGS data by the application of remote sensing and GIS technology and further verified by the data which was collected in field work to the study area. Different band combinations of the image are applied for visual image interpretation to digitize the rock boundaries while as Sobel and Laplacian filtering techniques are utilized for lineament mapping. The purpose of our field work was a comprehensive mapping of Geology and related structural aspects of Kufri, Jhalar, Chamnaki, Surraki, Khura and Naushehra area, Central Salt Range, district Khushab Punjab Pakistan in the Central Salt Range Pakistan. It includes Litho-structural Mapping at scale of 1:10,000. The results and conclusion of this study demonstrate that the processing and interpretation of Satellite data set can be employed as a powerful tool to improve lithological discrimination and enhance the overall mapping performance in the rugged and hilly terrain like Salt range.
In conversation with a (highly passionate) temporal logician

If you have 100 socks in a drawer, 50 of which are red and 50 black, how many will you have to pull out to guarantee you have a pair?We will give you a second to think about it… Okay, time is up.Let us work through this logically.You pull out one sock and it is red.Now, the next sock could be red, making two socks to make a pair.However, you could pick out a black sock, meaning you do not have a pair.Regardless, the next sock you pick will be either a red or a black sock, which would guarantee you have a pair.The answer is three.That gives us a simple logic puzzle we can all understand, but somebody who understands logic to a far greater degree is Dr Kristin
TOWARD A POSTCLASSICAL PARADIGM FOR THE EDUCATION OF THE FUTURE

The authors of the article analyze the implementation of post-classical education at the present stage of society development and forecast its future. The researchers define the concept of classical and post-classical education, highlight the factors of a crisis situation in the educational environment, highlight the demands of modernity on human skills and competences. The main legacy of the study is to offer solutions to crisis situations and predict the future based on the fall environment as an institution and as a set of techniques, methodologies, and learning principles (e.g., STEAM education, flipped classroom, electronic portfolio, active work in pairs or group, preparation of presentations, the involvement of technology in learning, etc.). The authors of this study used the following methods: comparative-historical, systematic and inductive. The future of education lies in the constant rethinking of being and transformation under the demands of the twentieth century. But for now, the future is in the vein of “freedom and dignity of the child”. This work is theoretical, but its insights are useful for state structures in education and educational institutions to recall and give impetus to greater implementation of the newest systems and methods of education, so that the next generations no longer face severe crises, have quick adaptation, and be modern people.
نظام خبير وأهميته للجامعات اليمنية الخاصة في تحقيق الميزة التنافسية

يهدف البحث إلى معرفة نظام خبير وأهميته للجامعات اليمنية الخاصة في تحقيق الميزة التنافسية، ولتحقيق ذلك اعتمدت الدراسة على تحليل المحتوى، وبخصوص أدوات جمع البيانات اعتمدت على الأبحاث والدراسات والتقارير الحديثة.&#x0D; وخلصت الدراسة إلى أن الميزة التنافسية ظاهرة أفرزتها العولمة؛ لذا فإن لنظام خبير أهمية في تمكين الجامعات الخاصة من الوصول إلى الميزة التنافسية في عملياتها وأنشطتها كافة، إلا أن الجامعات اليمنية الخاصة ما تزال بعيدة عنه؛ لهذا توصي الدراسة بضرورة تبني الجامعات لأساليب فعالة ومرنة، لا سيما من خلال تبني الفكر المعرفي في تنفيذ آلياتها التنافسية.&#x0D; الكلمات المفتاحية: نظام خبير – الميزة التنافسية – الجامعات اليمنية الخاصة.&#x0D; &#x0D; Abstract:&#x0D; Research aims to identify the important of an expert system in achieving the competitive advantage of Yemeni private universities. By identifying the concept of an expert system, as well as the concept of competitive advantage; and the reality of its performance. To achieve the objective of the research, the study used descriptive through content analysis approach. As related to data collection, the researcher collected through analysis of recent literature on research subject, research and reports. The study concluded that the competitive advantage is a phenomenon produced by globalization and its variables. Therefore, the expert system may have a role in enabling private universities to reach a competitive advantage in all their activities and operations. However, Yemeni private universities are still far from full application of the system. For this reason, the study recommends that universities should adopt effective and flexible methods, especially through the adoption of cognitive thinking in implementing their competitive mechanisms. &#x0D; Kay words: Artificial intelligence - Competitive Advantage – Private Yamani Universities
WEB 3.0: Emergence of a Decentralized Network

Web is known to be the best futuristic and implicit way of communication in the present day of the connected world. It was hypothesized in the early development of the internet that the web would greatly affect the working of the internet. Web 2.0, and now Web 3.0, may bring immense prosperity to the Internet sector in such a short time. For almost a decade, the transition from Web1.0 to Web 2.0 has been completed. In any case, not long after Web 2.0, another Web 3.0 arose, raising fervor as well as many inquiries among pioneers, users, and regulators. Is it actually necessary at this point, what could be the driving forces, and how does it vary from Web 2.0?
Design and Application of Current Situation Network Survey System for Female Science and Technology Workers Based on J2EE

J2EE is an industry development standard based on Java language. On the basis of maintaining the independence of Java language platform, it solves the system interface compatibility between programs, reduces the coupling degree between modules, and makes the software development process more clear and concise. In J2EE layered architecture, Web browser and Applet access the presentation layer, application client access the business logic layer, J2EE application server and enterprise information system layer access based on the unified interface. This paper designs the network survey content, which consists of 8 categories, and each category includes 3 specific questions. Questionnaire survey program is designed. Users can choose to answer questions with their real names or anonymously. The research results of this paper, provide the complete solution for the development of the network investigation system of the current situation of female scientific and technological workers.
L3: Accelerator-Friendly Lossless Image Format for High-Resolution, High-Throughput DNN Training

The training process of deep neural networks (DNNs) is usually pipelined with stages for data preparation on CPUs followed by gradient computation on accelerators like GPUs. In an ideal pipeline, the end-to-end training throughput is eventually limited by the throughput of the accelerator, not by that of data preparation. In the past, the DNN training pipeline achieved a near-optimal throughput by utilizing datasets encoded with a lightweight, lossy image format like JPEG. However, as high-resolution, losslessly-encoded datasets become more popular for applications requiring high accuracy, a performance problem arises in the data preparation stage due to low-throughput image decoding on the CPU. Thus, we propose L3, a custom lightweight, lossless image format for high-resolution, high-throughput DNN training. The decoding process of L3 is effectively parallelized on the accelerator, thus minimizing CPU intervention for data preparation during DNN training. L3 achieves a 9.29 $$\times $$ higher data preparation throughput than PNG, the most popular lossless image format, for the Cityscapes dataset on NVIDIA A100 GPU, which leads to 1.71 $$\times $$ higher end-to-end training throughput. Compared to JPEG and WebP, two popular lossy image formats, L3 provides up to 1.77 $$\times $$ and 2.87 $$\times $$ higher end-to-end training throughput for ImageNet, respectively, at equivalent metric performance.
Perbandingan Karakteristik Infused Water (Apel + Jeruk + Kiwi) Berdasarkan Suhu dan Waktu

&lt;em&gt;&lt;span&gt;Infused water is a healthy drink that contains minerals and vitamins obtained from a mixture of ingredients in infused water, such as fruit and spices. Infused water can be used as an alternative for people who have difficulty consuming only mineral water. Infused water has a variety of additional flavors in mineral water so that people who consume it do not get bored with the taste of mineral water.&lt;/span&gt;&lt;span&gt;The purpose of this study was to compare the characteristics of infused water stored at room temperature (31&lt;sup&gt;0&lt;/sup&gt;C) and refrigerator temperature (4&lt;sup&gt;0&lt;/sup&gt;C) and how long the infused water can last at room temperature and refrigerator temperature. This research method is experimental, with temperature and storage time factors consisting of 6, 12, 24, 48, and 72 hours, then organoleptic tests are carried out. The results obtained based on a good temperature and time to make infused water are 48 hours or two days at a refrigerator temperature of 4&lt;sup&gt;0&lt;/sup&gt;C and 12 hours at a temperature of 31&lt;sup&gt;0&lt;/sup&gt;C and 4&lt;sup&gt;0&lt;/sup&gt;C, for the taste and aroma of good quality infused water is at a temperature of 4&lt;sup&gt;0&lt;/sup&gt;C. Suggestions in making infused water, the longest storage is 2 days without refill, if there is a refill, you should use infused 12 hours&lt;/span&gt;&lt;/em&gt;