Reviewerly/exHarmony huggingface dataset:
An Empirical Evaluation of Predicted Outcomes as Explanations in Human-AI Decision-Making

In this work, we empirically examine human-AI decision-making in the presence of explanations based on predicted outcomes. This type of explanation provides a human decision-maker with expected consequences for each decision alternative at inference time - where the predicted outcomes are typically measured in a problem-specific unit (e.g., profit in U.S. dollars). We conducted a pilot study in the context of peer-to-peer lending to assess the effects of providing predicted outcomes as explanations to lay study participants. Our preliminary findings suggest that people's reliance on AI recommendations increases compared to cases where no explanation or feature-based explanations are provided, especially when the AI recommendations are incorrect. This results in a hampered ability to distinguish correct from incorrect AI recommendations, which can ultimately affect decision quality in a negative way.
Accurate and Real-time 3D Pedestrian Detection Using an Efficient Attentive Pillar Network

Efficiently and accurately detecting people from 3D point cloud data is of great importance in many robotic and autonomous driving applications. This fundamental perception task is still very challenging due to (i) significant deformations of human body pose and gesture over time and (ii) point cloud sparsity and scarcity for pedestrian class objects. Recent efficient 3D object detection approaches rely on pillar features to detect objects from point cloud data. However, these pillar features do not carry sufficient expressive representations to deal with all the aforementioned challenges in detecting people. To address this shortcoming, we first introduce a stackable Pillar Aware Attention (PAA) module for enhanced pillar features extraction while suppressing noises in the point clouds. By integrating multi-point-channel-pooling, point-wise, channel-wise, and task-aware attention into a simple module, the representation capabilities are boosted while requiring little additional computing resources. We also present Mini-BiFPN, a small yet effective feature network that creates bidirectional information flow and multi-level cross-scale feature fusion to better integrate multi-resolution features. Our proposed framework, namely PiFeNet, has been evaluated on three popular large-scale datasets for 3D pedestrian Detection, i.e. KITTI, JRDB, and nuScenes achieving state-of-the-art (SOTA) performance on KITTI Bird-eye-view (BEV) and JRDB and very competitive performance on nuScenes. Our approach has inference speed of 26 frame-per-second (FPS), making it a real-time detector. The code for our PiFeNet is available at https://github.com/ldtho/PiFeNet.
TAG: Task-based Accumulated Gradients for Lifelong learning

When an agent encounters a continual stream of new tasks in the lifelong learning setting, it leverages the knowledge it gained from the earlier tasks to help learn the new tasks better. In such a scenario, identifying an efficient knowledge representation becomes a challenging problem. Most research works propose to either store a subset of examples from the past tasks in a replay buffer, dedicate a separate set of parameters to each task or penalize excessive updates over parameters by introducing a regularization term. While existing methods employ the general task-agnostic stochastic gradient descent update rule, we propose a task-aware optimizer that adapts the learning rate based on the relatedness among tasks. We utilize the directions taken by the parameters during the updates by accumulating the gradients specific to each task. These task-based accumulated gradients act as a knowledge base that is maintained and updated throughout the stream. We empirically show that our proposed adaptive learning rate not only accounts for catastrophic forgetting but also allows positive backward transfer. We also show that our method performs better than several state-of-the-art methods in lifelong learning on complex datasets with a large number of tasks.
MapTR: Structured Modeling and Learning for Online Vectorized HD Map Construction

High-definition (HD) map provides abundant and precise environmental information of the driving scene, serving as a fundamental and indispensable component for planning in autonomous driving system. We present MapTR, a structured end-to-end Transformer for efficient online vectorized HD map construction. We propose a unified permutation-equivalent modeling approach, i.e., modeling map element as a point set with a group of equivalent permutations, which accurately describes the shape of map element and stabilizes the learning process. We design a hierarchical query embedding scheme to flexibly encode structured map information and perform hierarchical bipartite matching for map element learning. MapTR achieves the best performance and efficiency with only camera input among existing vectorized map construction approaches on nuScenes dataset. In particular, MapTR-nano runs at real-time inference speed ($25.1$ FPS) on RTX 3090, $8\times$ faster than the existing state-of-the-art camera-based method while achieving $5.0$ higher mAP. Even compared with the existing state-of-the-art multi-modality method, MapTR-nano achieves $0.7$ higher mAP, and MapTR-tiny achieves $13.5$ higher mAP and $3\times$ faster inference speed. Abundant qualitative results show that MapTR maintains stable and robust map construction quality in complex and various driving scenes. MapTR is of great application value in autonomous driving. Code and more demos are available at \url{https://github.com/hustvl/MapTR}.
PENGGUNAAN MEDIA SALINDIA INTERAKTIF UNTUK MENARIK MINAT BELAJAR SISWA SEKOLAH DASAR DALAM PEMBELAJARAN DARING

THE USE OF INTERACTIVE POWERPOINT TO INCREASING ELEMENTARY SCHOOL STUDENTS LEARNING INTEREST IN ONLINE LEARNINGThe purpose of this research is to describe the effectiveness of PowerPoint to engage primary students especially in the online learning setting. Method that have been using for this research was qualitative descriptive with the instruments are lesson plan, observation log, and teacher’s mentor feedback. The result show that the use of PowerPoint was effective to engage students in learning because there are many features that support teacher to teach. The features is use to add pictures, video, and particularly hyperlink features that help user to made nonlinear presentation, so the teacher can design an interactive quizzes. PowerPoint also support students to learn individually at home in this kind of online learning setting. It can be conclude that PowerPoint is effective to engage primary student in online learning. Therefore the researcher suggest that the PowerPoint can be validated by the expert so that it can use for teaching primary students in online learning around Indonesia.
IMPLEMENTASI GAME ONLINE TERHADAP MOTIVASI BELAJAR PESERTA DIDIK DI SEKOLAH DASAR

ONLINE GAME IMPLEMENTATION TOWARDS STUDENTS 'LEARNING MOTIVATION IN PRIMARY SCHOOLSThis study aims to determine the use of online games in students, and to determine the use of online games in motivating students' learning, as well as to determine the positive and negative impacts of using online games on students. This research uses descriptive qualitative. Data was collected through interviews, observation and documentation. This study uses data analysis techniques, which consist of the stages of data collection, data reduction, data presentation, and drawing conclusions. The results showed that the use of online games in students had disciplinary rules at school, online games were used as a learning resource and means or media, the positive impact of using online games for students could support a fun learning process to facilitate the learning process, while the negative impact of using online games, causing students to become addicted or addicted. So that the decrease in the learning motivation of students. The conclusion of this study is the use of online games is expected to be a source of learning and learning media in the learning process so that students are motivated to learn.
ANALISIS PENGGUNAAN KOHESI GRAMATIKAL PADA TEKS EKSPLANASI SISWA KELAS VIII SMP NEGERI 5 BOGOR

ANALYSIS OF THE USE OF GRAMMATICAL COHESION IN THE EXPLANATION TEXT OF CLASS VIII SMP NEGERI 5 BOGORThe aim of this research is to describe the use of grammatical cohesion of references and substitutions in students' explanatory texts. The focus of this research is the use of grammatical cohesion tools in the form of references and substitutions in students' explanatory texts. The method used in this research is qualitative descriptive, meaning that the data found in the form of sentences and will be described descriptively. Data sources used in this research are 29 explanatory texts for students of class VIII H of SMP Negeri 5 Bogor, using literature study data collection techniques. Grammatical cohesion tools analyzed in the explanatory text are references and substitutions. From the results of this analysis found the use of reference grammatical cohesion and substitution tools of 80 data findings. The most findings are the use of references as much as 67 data (84%). References usually relate to elements that are referring and referenced. The references are inside and outside the text with the most findings being personal and demonstrative references. Then the use of substitution grammatical cohesion only found 13 data findings (16%). This substitution is related to the substitution of a language element with other language elements. Grammatical cohesion of substitution is very little used by students in explanatory texts. This happens because of the lack of understanding of students in writing texts in accordance with good linguistic rules and the lack of vocabulary that students have. However, from this amount it can be concluded, this explanatory text of eighth grade students of SMP Negeri 5 Bogor has many uses of grammatical cohesion. The results of this research give a positive thing on learning Indonesian, especially aspects of language in school.
PENERAPAN MODEL PEMBELAJARAN COOPERATIF TYPE JIGSAW UNTUK MENINGKATKAN HASIL BELAJAR SISWA TENTANG TEKS INTERAKSI INTERPERSONAL LISAN DAN TULIS PADA MATA PELAJARAN BAHASA INGGRIS

APPLICATION OF THE JIGSAW COOPERATIVE LEARNING MODEL TO IMPROVE STUDENT LEARNING OUTCOMES ABOUT INTERPERSONAL INTERPERSONAL INTERACTION TEXTS AND WRITING IN ENGLISH SUBJECTSThis research is a Classroom Action Research by providing action on research subjects in two learning cycles. This study aims to determine the application of the Type Jigsaw cooperative learning model can improve student learning outcomes in English subjects about oral and written interpersonal interaction texts in Class IX Junior High School (SMP Negeri 5 Kota Bogor) Odd Semester 2019/2020 Academic Year. Another goal is to describe the process of improving student learning outcomes about oral and written interpersonal interaction texts in English subjects after using the Jigsaw Type Cooperative Learning Model. To measure the magnitude of the increase in student learning outcomes about oral and written interpersonal interaction texts in English subjects after using the Jigsaw Type Cooperative Learning Model in. The results of this study indicate that before using the cooperative learning model Type Jigsaw, the learning outcomes of students only reached an average value of 66.32 then an increase occurred after using the Make A Match cooperative learning model to 73.53 in cycle 1 and 81.03 in cycle. 2. By using the cooperative learning model Type Jigsaw can be a fun variation of learning for students so that it is proven to improve student learning outcomes in Class IX semester 1 Junior High School (SMP Negeri 5 Kota Bogor).
ANALISIS LITERASI DIGITAL CALON GURU SD DALAM PEMBELAJARAN BERBASIS VIRTUAL CLASSROOM

ANALYSIS OF DIGITAL LITERACY FOR ELEMENTARY SCHOOL TEACHER CANDIDATES IN VIRTUAL CLASSROOM BASED LEARNINGAbstract. Self-directed learning is a process in which individuals learn without the help of others supported by digital and cellular technology, technology applications are developed to take advantage of the concept of independent learning. By implementing online learning strategies, digital literacy skills are absolutely needed by students. This is because it is impossible to implement online learning without being supported by high digital literacy. This study aims to describe the digital literacy of elementary school teacher education students in virtual classroom-based learning. The method used is descriptive qualitative research with a sample of 74 PGSD students. The results showed that most students had basic internet skills, PGSD students were able to find and retrieve information from the internet, and use it effectively.
PENGARUH PENGUASAAN KOSAKATA TERHADAP KETERAMPILAN MENULIS KARANGAN DESKRIPSI

THE EFFECT OF VOCABULARY MASTERY ON ESSAY WRITING SKILLS DESCRIPTIONThe purpose of this study was to determine the effect of vocabulary mastery on description essay writing skills. The method used is a quantitative method with a causal technique. The data of this study were obtained by using multiple choice tests for vocabulary mastery variables and description tests for variable description writing skills. The population in this study were students of grade IV 03 Karangtengah State Elementary School, Babakanmadang, Bogor Regency, totaling 66 students. The sample used was 40 students, obtained by calculation using the Taro Yamane formula. Simple regression analysis and correlation techniques produce a relationship model that is expressed in the form of a regression equation that is Ŷ = (49 + 0.4X), with a price of 38.808 greater than the real level of 0.05 at 4.01 and contributions based on research results of 90%. Based on the results of these studies, it can be concluded that there is a positive and significant influence between vocabulary mastery of the writing essay skills in students.
PENGARUH PENGUASAAN STRUKTUR KALIMAT TERHADAP KEMAMPUAN MENULIS EKSPOSISI PADA MURID KELAS V SEKOLAH DASAR INPRES TAMABONGONG

THE EFFECT OF SENTENCE STRUCTURE MASTERING ON EXPOSITION WRITING ABILITY IN CLASS V ELEMENTARY SCHOOL STUDENTS TAMABONGONG INPRESThe purpose of the study was the effect of mastery of sentence structure on the ability to write exposition in fifth grade students of Inpres Tamabongong Elementary School. This type of research is quasi-experimental because in this study no specific treatment was given, but only revealed the symptoms that had existed when this research was conducted, so there was no direct control over the independent variables. The sample in quantitative research is part of the population in a study. The number of samples in this study were 15 students. Data collection methods used are learning outcomes tests and documentation. The data analysis technique used is the first by using a descriptive statistical approach and linear regression. The results showed that 1) The mastery of sentence structure was based on the results of the categorization of mastery of sentence structure in students, it was found that they were still in the category of scores of 14-20, scores of 26-30, and at scores of 14-20 whose mastery of sentence structure had not increased like the others. While in the posttest, 14 people were found to be moderate and there was 1 person whose mastery of sentence structure got better who was in the high category. 2) The results of data analysis obtained a probability value (p-value) of 0.042. Because the probability value (p-value) is less than 0.050, it means that the regression model in this study can be said that X (mastery of sentence structure) is dependent on Y (ability to write expository essays).
Revising Anthropocentrism of Technics in the Light of the 21st Century New Anthropological Models

Purpose. To substantiate the definition of technics as the attributive characteristics of a human being and the necessity of its orientation towards human flourishing in the context of new anthropological models of the 21st century. Theoretical basis. Correlation between technics, technology and the human essence is examined. The role of technics is traced at different historical stages of human development. Negative and positive effects of digital technology development upon a contemporary human being is analysed in the light of new anthropological models: homo technologicus, homo digitalis and homo eudaimonicus. The content of a new worldview-value paradigm of defining goals of technology is outlined. Originality. Transformation of the role of technics correlates with value and worldview shifts in person’s understanding of his/her purpose in both natural and social worlds. Nowadays, philosophical analysis of anthropological dimension of technics and technology opens a horizon for seeking effective solutions in the face of the contemporary challenges and anti-utopian threats by means of focusing on the fact that, indeed, technological development is subordinate to the humanist goal that is flourishing, wellbeing and comprehensive development of a human being. Conclusions. The essence of technology reveals not through its functional but anthropogenic definitions in a sense of a source of institutionalization and in a sense of a source of realization of a human way of self-identification and self-objectification of human subjectivity. Technics/technology is the attributive characteristics of human essence and being: a human being is as much human as much he/she is a creator of technics. The purpose of technics is not to master the nature and to transform the world; technics is, above all, a tool of human self-improvement and self-creation through broadening the horizon of human capacities. The analysis of new modern anthropological models shows that it is the orientation of technology/technology towards human flourishing that is, on the one hand, a response to the existential demands of modern man, and on the other hand, a way of preventing future threats related to technological development.
Search Algorithm of the Number of Unfixed Points of Permutations from Sylow 2-subgroups Syl2(S2n) of Symmetric Groups S2n

The Symmetric permutation group S2n is a classical algebraic object that is also used in Computer science, Coding theory, Statistics, etc. In particular, the coding theory considers codes defined on the symmetric group Sn or its subgroups. The research of permutation codes has been started from 1970s. These codes can be obtained with using different distances: Hamming, Ulam, Cailey, Levenshtein. The finding distance on permutations depends on their number of fixed or unfixed points. Therefore, it is natural to count the number of unfixed points in a certain group of permutations.In this paper, we consider the number of unfixed points of permutations that are elements of the Sylow 2-subgroup Syl2(S2n) of symmetric groups S2n. Leo Kaluzhnin used tables to represent the elements of these groups [8]. Volodymyr Nekrashevych represented permutations by their portraits [9]. We use algorithms that describe the connection between the permutation group Syl2(S2n) and the group of labeled binary rooted trees [10].An algorithm for finding the number of unfixed points for permutations of the Sylow 2-subgroup Syl2(S2n) of the symmetric group S2n is proposed in the article. An isomorphism between the group Syl2(S2n) and a group of labeled binary root trees was used to construct this algorithm. It is proved, that the algorithm of searching the number of unfixed point for permutations of the Sylow 2-subgroup Syl2(S2n) of the symmetric group S2n has complexity O(2n). In addition, the average number of steps of the algorithm for the Sylow 2-subgroup of the symmetric group S2n is found. The result for small n (n = 2, 3, 4) was verified with a program, that is written in the language of the computer algebra Sage. At the end of the article we find the number of permutations from Syl2(S2n ) that have a maximumnumber of unfixed points. The number of such permutations in the symmetric group S2n is well known.Obviously that this number is smaller for the Sylow 2-subgroup of the symmetric group Syl2(S2n ). Inthis case, we calculate the maximum number of unfixed points using a recursive formula.
BTP: automatic identification and prediction of tasks in data center networks

Abstract Modern data centers have widely deployed lots of cluster computing applications such as MapReduce and Spark. Since the coflow/task abstraction can exactly express the requirements of cluster computing applications, various task-based solutions have been proposed to improve application-level performance. However, most of solutions require modification of the applications to obtain task information, making them impractical in many scenarios. In this paper, we propose a Bayesian decision-based Task Prediction mechanism named BTP to identify task and predict the task-size category. First, we design an automatic identification mechanism to identify tasks without manually modifying the applications. Then we leverage bayesian decision to predict the task-size category. Through a series of large-scale NS2 simulations, we demonstrate that BTP can accurately identify task and predict the task-size category. More specifically, BTP achieves 96% precision and 92% recall while obtaining accuracy by up to 98%.
The Effects of the Innovative Decisions on Firms’ Innovative Performance of Nigerian Industry

Firms have to keep innovating if they want to maintain competitive advantage; hence, this study investigates the innovation activities in Nigerian firms considering the role Nigeria plays in the African economy. Specifically, the objectives of this study are to (1) to determine the factors that affect firms’ innovative activities and (2) to evaluate the impact of the innovative decision on innovation performance or product of firms. 2014 Enterprise survey data conducted by the World Bank is used, and CDM-model is adopted as the method of analysis. The results showed that improved supporting activities by firms has a significant positive relationship with firms’ innovative performance, and giving employees time to develop new idea has a positive impact on innovation performance. Finally, the study recommends that firms should embark on the job training of staff because it will help them be more efficient by improving the working process.
Object Detection and Ship Classification Using YOLOv5

Using a public dataset of images of maritime vessels provided by Analytics Vidhya, manual annotations were made on a subsample of images with Roboflow using the ground truth classifications provided by the dataset. YOLOv5, a prominent open source family of object detection models that comes with an out-of-the-box pre-training on the Common Objects in Context (COCO) dataset, was used to train on annotations of subclassifications of maritime vessels. YOLOv5 provides significant results in detecting a boat. The training, validation, and test set of images trained YOLOv5 in the cloud using Google Colab. Three of our five subclasses, namely, cruise ships, ROROs (Roll On Roll Off, typically car carriers), and military ships, have very distinct shapes and features and yielded positive results. Two of our subclasses, namely, the tanker and cargo ship, have similar characteristics when the cargo ship is unloaded and not carrying any cargo containers. This yielded interesting misclassifications that could be improved in future work. Our trained model resulted in the validation metric of mean Average Precision (mAP@.5) of 0.932 across all subclassification of ships.