Reviewerly/exHarmony huggingface dataset:
Towards Robust Video Instance Segmentation with Temporal-Aware Transformer

Most existing transformer based video instance segmentation methods extract per frame features independently, hence it is challenging to solve the appearance deformation problem. In this paper, we observe the temporal information is important as well and we propose TAFormer to aggregate spatio-temporal features both in transformer encoder and decoder. Specifically, in transformer encoder, we propose a novel spatio-temporal joint multi-scale deformable attention module which dynamically integrates the spatial and temporal information to obtain enriched spatio-temporal features. In transformer decoder, we introduce a temporal self-attention module to enhance the frame level box queries with the temporal relation. Moreover, TAFormer adopts an instance level contrastive loss to increase the discriminability of instance query embeddings. Therefore the tracking error caused by visually similar instances can be decreased. Experimental results show that TAFormer effectively leverages the spatial and temporal information to obtain context-aware feature representation and outperforms state-of-the-art methods.
Sliding Window String Indexing in Streams

Given a string $S$ over an alphabet $\Sigma$, the 'string indexing problem' is to preprocess $S$ to subsequently support efficient pattern matching queries, i.e., given a pattern string $P$ report all the occurrences of $P$ in $S$. In this paper we study the 'streaming sliding window string indexing problem'. Here the string $S$ arrives as a stream, one character at a time, and the goal is to maintain an index of the last $w$ characters, called the 'window', for a specified parameter $w$. At any point in time a pattern matching query for a pattern $P$ may arrive, also streamed one character at a time, and all occurrences of $P$ within the current window must be returned. The streaming sliding window string indexing problem naturally captures scenarios where we want to index the most recent data (i.e. the window) of a stream while supporting efficient pattern matching. Our main result is a simple $O(w)$ space data structure that uses $O(\log w)$ time with high probability to process each character from both the input string $S$ and the pattern string $P$. Reporting each occurrence from $P$ uses additional constant time per reported occurrence. Compared to previous work in similar scenarios this result is the first to achieve an efficient worst-case time per character from the input stream. We also consider a delayed variant of the problem, where a query may be answered at any point within the next $\delta$ characters that arrive from either stream. We present an $O(w + \delta)$ space data structure for this problem that improves the above time bounds to $O(\log(w/\delta))$. In particular, for a delay of $\delta = \epsilon w$ we obtain an $O(w)$ space data structure with constant time processing per character. The key idea to achieve our result is a novel and simple hierarchical structure of suffix trees of independent interest, inspired by the classic log-structured merge trees.
Characterizing Polarization in Social Networks using the Signed Relational Latent Distance Model

Graph representation learning has become a prominent tool for the characterization and understanding of the structure of networks in general and social networks in particular. Typically, these representation learning approaches embed the networks into a low-dimensional space in which the role of each individual can be characterized in terms of their latent position. A major current concern in social networks is the emergence of polarization and filter bubbles promoting a mindset of "us-versus-them" that may be defined by extreme positions believed to ultimately lead to political violence and the erosion of democracy. Such polarized networks are typically characterized in terms of signed links reflecting likes and dislikes. We propose the latent Signed relational Latent dIstance Model (SLIM) utilizing for the first time the Skellam distribution as a likelihood function for signed networks and extend the modeling to the characterization of distinct extreme positions by constraining the embedding space to polytopes. On four real social signed networks of polarization, we demonstrate that the model extracts low-dimensional characterizations that well predict friendships and animosity while providing interpretable visualizations defined by extreme positions when endowing the model with an embedding space restricted to polytopes.
SpArX: Sparse Argumentative Explanations for Neural Networks [Technical Report]

Neural networks (NNs) have various applications in AI, but explaining their decisions remains challenging. Existing approaches often focus on explaining how changing individual inputs affects NNs' outputs. However, an explanation that is consistent with the input-output behaviour of an NN is not necessarily faithful to the actual mechanics thereof. In this paper, we exploit relationships between multi-layer perceptrons (MLPs) and quantitative argumentation frameworks (QAFs) to create argumentative explanations for the mechanics of MLPs. Our SpArX method first sparsifies the MLP while maintaining as much of the original structure as possible. It then translates the sparse MLP into an equivalent QAF to shed light on the underlying decision process of the MLP, producing global and/or local explanations. We demonstrate experimentally that SpArX can give more faithful explanations than existing approaches, while simultaneously providing deeper insights into the actual reasoning process of MLPs.
OvarNet: Towards Open-vocabulary Object Attribute Recognition

In this paper, we consider the problem of simultaneously detecting objects and inferring their visual attributes in an image, even for those with no manual annotations provided at the training stage, resembling an open-vocabulary scenario. To achieve this goal, we make the following contributions: (i) we start with a naive two-stage approach for open-vocabulary object detection and attribute classification, termed CLIP-Attr. The candidate objects are first proposed with an offline RPN and later classified for semantic category and attributes; (ii) we combine all available datasets and train with a federated strategy to finetune the CLIP model, aligning the visual representation with attributes, additionally, we investigate the efficacy of leveraging freely available online image-caption pairs under weakly supervised learning; (iii) in pursuit of efficiency, we train a Faster-RCNN type model end-to-end with knowledge distillation, that performs class-agnostic object proposals and classification on semantic categories and attributes with classifiers generated from a text encoder; Finally, (iv) we conduct extensive experiments on VAW, MS-COCO, LSA, and OVAD datasets, and show that recognition of semantic category and attributes is complementary for visual scene understanding, i.e., jointly training object detection and attributes prediction largely outperform existing approaches that treat the two tasks independently, demonstrating strong generalization ability to novel attributes and categories.
HexPlane: A Fast Representation for Dynamic Scenes

Modeling and re-rendering dynamic 3D scenes is a challenging task in 3D vision. Prior approaches build on NeRF and rely on implicit representations. This is slow since it requires many MLP evaluations, constraining real-world applications. We show that dynamic 3D scenes can be explicitly represented by six planes of learned features, leading to an elegant solution we call HexPlane. A HexPlane computes features for points in spacetime by fusing vectors extracted from each plane, which is highly efficient. Pairing a HexPlane with a tiny MLP to regress output colors and training via volume rendering gives impressive results for novel view synthesis on dynamic scenes, matching the image quality of prior work but reducing training time by more than $100\times$. Extensive ablations confirm our HexPlane design and show that it is robust to different feature fusion mechanisms, coordinate systems, and decoding mechanisms. HexPlane is a simple and effective solution for representing 4D volumes, and we hope they can broadly contribute to modeling spacetime for dynamic 3D scenes.
Solving graph problems with single-photons and linear optics

An important challenge for current and near-term quantum devices is finding useful tasks that can be preformed on them. We first show how to efficiently encode a bounded $n \times n$ matrix $A$ into a linear optical circuit with $2n$ modes. We then apply this encoding to the case where $A$ is a matrix containing information about a graph $G$. We show that a photonic quantum processor consisting of single-photon sources, a linear optical circuit encoding $A$, and single-photon detectors can solve a range of graph problems including finding the number of perfect matchings of bipartite graphs, computing permanental polynomials, determining whether two graphs are isomorphic, and the $k$-densest subgraph problem. We also propose pre-processing methods to boost the probabilities of observing the relevant detection events and thus improve performance. Finally we present both numerical simulations and implementations on Quandela's Ascella photonic quantum processor to validate our findings.
A Comprehensive Review on Indian Sign Language Recognition System using Vision based Approaches

A sign language recognition system is a method in which a computer automatically recognizes the sign language motions and converts them into machine or human readable text or speech.Many researchers have proposed different algorithms for identifying the static and dynamic Indian sign language (ISL) gestures.This review presents a qualitative and a comprehensive study of the different approaches like digital image processing, machine learning and deep learning methods used for recognition of gestures.Research publications from the past 10 years have been collected from electronic databases like scopus, google scholar and researchgate for the review and the details of the publicly available dataset repositories are highlighted.This review helps the researchers, academicians and the technology oriented people to understand the importance of different technologies used to recognize the gestures automatically which in turn benefits the speech and hearing impaired people.The challenges present in ISL recognition, the short comings of the existing systems and the future research directions in order to improve the recognition rate is explained in this paper.
Performance Analysis of Six Chaos Cryptographic Algorithms for Image Encryption

The increase in cyber crimes such as theft and piracy adds to the vulnerability of storing and sending image data in cyberspace.To deal with the rampant crime in cyberspace, especially in image data, cryptography is implemented on images.Cryptography based on chaos theory was chosen because it has a random key generator value.Implementation of image cryptography based on chaos theory makes image cryptography more developed, chaos-based algorithms that have been implemented are the Algorithm Arnold Cat Map, Baker's Map, Ikeda Map, Tent Map, Logistic Map 3, Gauss Iterated Map, Henon Map, and Duffing Map Gingerbreadman Map.Of the many algorithms implemented previously in 2016 against the Logistic Map 3, Gauss Iterated Map, Henon Map, Duffing Map Gingerbreadman Map algorithms, comparisons and analysis of encryption time, decryption time, key sensitivity, histogram, lossy and lossless in the decrypted image have been carried out.In this study, the Tinkerbell Map algorithm was initiated to be implemented in image cryptography and compared to the Logistic Map 3 algorithm, Gauss Iterated Map, Henon Map, Duffing Map Gingerbreadman Map.Also added correlation coefficient analysis, MSE and PSNR analysis, to analyze the security of encrypted images.Based on testing of Logistic Map 3, Gauss Iterated Map, Henon Map, Duffing Map Gingerbreadman Map, Tinkerbell Map have different performance.The histogram analysis produces a very good spread of pixels, each algorithm has a different key sensitivity, the highest is the Tinkerbell Map.Henon Map is the best algorithm for correlation coefficient, MSE and PSNR.Time analysis found that the Tinkerbell Map algorithm has the longest process value, and the fastest is logistics map 3. General TermsThe increase in cyber crimes such as theft and piracy adds to the vulnerability of storing and sending data in cyberspace.Unknowingly, data and information that should be used for personal consumption are vulnerable to being exploited by irresponsible parties.In addition, there are many applications that can be used to manipulate data and information, especially data in the form of images.This is a concern for users about data and information security.The more complicated the method used, the better the resulting level of security.
L’inconscio al plurale: le città come modelli dello psichico

The City and the Unconscious in the Global Age. German Studies in Multidisciplinary Dialogue hosts many more questions than it is possible to state here and seeks answers that introduce an ethic of citizenship for the third millennium, where the goals of Agenda 2030 are not reduced to slogans and empty talks and where the grassroots activists do not risk to be hushed up or even taken in by the most powerful corporations, which pretend to operate in the acknowledgment of the differences that Otherness entails. The inspirers of the volume are German-speaking intellectuals, poets, artists, architects from various backgrounds. In particular, we started from the ideas and work of Bruno Taut to rethink through Sigmund Freud, F. G. Jünger, Paul Celan, Durs Grünbein and many others social bonding in the age of anthropological mutation and pandemic emergencies. ________________________________________________ List of chapters ________________________________________________
The Implementation of Financial System Information toward The Function of Regional Financial Supervision on Regional Financial Management in Bungo Regency

Utilization of today's technology is something that can't be avoided, because of the need for information very fast, and precisely becomes a necessity major in all aspects. One of the technologies that the most developed is the technology that web-based which is often referred to as Internet. This technology is already in use in various fields of business, government, health, education and so on. Internet technology that is now ingrained meat must be used optimally, the existence of technology is also expected to be the answer to generalize speed of service, an advancement if the government is starting to adopt the technology as the main infrastructure of public services. The application of SIMDA Financial application to the Bungo Regency Regional Financial is based on SIMDA elements such as adequate internet network access, basic infrastructure and applications, all infrastructure in the form of hardware, software, and brain ware is adequate as well as information management and processing organizations and electronic documents that are sufficient. So that, the SIMDA Financial Application has produced financial statement information and other financial information with excellent quality relevance, excellent accuracy, and very good timeliness as well.
Hubungan Perhatian Orang Tua dengan Hasil Belajar Siswa di Kelas VI SD Negeri 040530 Bunuraya Tahun Pelajaran 2021/2022

The success or failure of an educational process is strongly influenced by the ongoing learning. The learning process is composed of a number of components or elements that are interrelated. These elements are teachers (educators), students (students), materials/materials, methods/methods, teaching curricula, learning facilities, study time, and learning facilities and the role of people. old. This research is entitled The Relationship between Parental Attention and Student Learning Outcomes in Class VI of SD Negeri 040530 Bunuraya for the 2021/2022 Academic Year. The purpose of this study was to see the relationship between parental attention and student learning outcomes. The results showed that parents' attention to class VI children at SDN 040530 Bunuraya Tigapanah District for the 2021/2022 academic year obtained an average score of 67.4. The score was in the Less category. There is a significant relationship between parental attention and student learning outcomes in class VI at SDN 040530 Bunuraya Tigapanah district for the 2021/2022 academic year. it can be concluded that tcount&gt; from ttable (8.461 &gt; 2.080) means, According to the table, namely the results of U t (partial) indicate that the significance value of the relationship between parental attention (X) to student learning outcomes (Y) is 0.201 &gt; than 0.05 and t value is 8.461 &gt; at 2.080 then HO is accepted and Ha is rejected. This means that there is a significant influence of parental attention on student learning outcomes.
Pengukuran Pembelajaran E-Learning dengan Pendekatan Technology Acceptance Model

The purpose of discussing this research is to find out the measurement of learning using e-learning using the Technology Acceptance Model approach. This research is a quantitative research with a survey approach, with a population of 67 students at Pamulang University. The data analysis technique that the writer did was quantitative descriptive analysis. The analytical method uses SEMPLS with the help of SmartPLS. The results of this study concluded that the presence of PEoU has an influence on BI, PU, which means that the ease of using LMS or E-learning at Pamulang University is able to provide benefits in improving the quality of the learning process which also has an impact on students' desire to use LMS again. But inversely related to the benefits provided (PU) does not affect BI and student satisfaction in the learning process. This can happen because in the use of LMS activities are monotonous, it is necessary to have variations in learning activities using LMS.
Comparative Assessment between PD and Fuzzy Control for a Novel Unmanned Aerial Vehicle Inspired by Owls

This paper proposes a comparative assessment between PD and fuzzy controls applied to an autonomous aerial vehicle inspired by owls to accomplish a silent and stable flight. Firstly, the owls' flight is analysed to determine different components of a particular trirotor drone. Afterward a detailed study, the mathematical model is developed using kinematics and aerodynamics laws. Next, the theoretical model is employed to synthesize a control strategy based on PD and then on fuzzy concepts to stabilize the drone in a hovering situation with the adequate altitude and attitude. The fuzzy controller is compared to the PD to display its performances in terms of precision and trajectory tracking.
Peningkatan Hasil Belajar Siswa pada Pembelajaran Penjumlahan dan Pengurangan Bilangan Pecahan Menggunakan Model Problem Based Learning di Kelas V SDN 27 Anak Air Padang

Improving Learning Outcomes using the Problem Based Learning (PBL) Model in the Lesson of Addition and Subtraction of Fractions in Class V SDN 27 Air Children. This study aims to describe the improvement of student learning outcomes by using the Problem Based Learning in learning addition and subtraction of fractions in class V SDN 27 Anak Air. This research is a classroom action research with qualitative and quantitative approaches. The subjects of this study were the fifth grade students of SDN 27 Anak Air, totaling 27 people. The results of this article indicate that the application of the Problem Based Learning (PBL) model to improve student learning outcomes is as follows: Improved learning outcomes with an average score of 75.19% with the designation B (Good) for each meeting, namely 62.59%, 72.96% , and 90.00%. Thus, the application of the Problem Based Learning (PBL) learning model can improve mathematics learning outcomes in the matter of adding and subtracting fractions in class V at SDN 27 Anak Air.
Development of Android-Based Learning Media Using the CapCut Application in Integrated Thematic Learning in Grade IV Elementary School

This research is motivated by the limited use of interesting and easy-to-understand media that can stimulate students in learning. The purpose of this research is to determine the validity and practicality of media-based learning. android using the CapCut. This type of research is development research (R&amp;D) using a 4-D consisting of define, design, develop and disseminate. Given the limitations of space, time, and research costs, this research was only carried out until the develop. The subjects of this study were 3 experts and 1 fourth grade teacher and 14 fourth grade students at SDN 24 Parupuk Tabing, and 1 fourth grade teacher and 10 fourth grade students at SDN 09 Air Tawar Barat. The instruments used are expert validation sheets, teacher and student response questionnaires. The results of the study were stated to be very valid with the average value of material experts 96%, media experts 92.6% and linguists 95%. Based on the results of teacher and student responses at the research school, the percentage of the fourth grade teacher responses at SDN 24 Parupuk Tabing was 95% and the fourth grade teacher responses at SDN 09 Air Tawar Barat 90%. The percentage of student responses at SDN 24 Parupuk Tabing was 96% and student responses in grade IV at SDN 09 Air Tawar Barat were 93% and were stated to be very practical. &#x0D; Keywords: Learning media, CapCut, 4-D Model.
Pengembangan Media Pembelajaran Menggunakan Aplikasi Smart Apps Creator pada Pembelajaran Tematik Terpadu Kelas IV Sekolah Dasar

This study aims to determine the development of learning media using the Smarts Apps Creator application in integrated thematic learning for students in grade IV Elementary School that is valid and practical. The type of research, namely R&amp;D development research (Research and Development) using the ADDIE model, consists of five steps, namely: analysis (analysis), design (design), development (development), implementation (Implementation), evaluation (evaluation). The research subjects were fourth grade students at SDN 27 Anak Air. The data collection instruments used were expert validation sheets, teacher and student response questionnaires. The results in the study indicate that the learning media using the Smarts Apps Creator application is valid and practical to use in learning with a percentage of 89.1% validity and 90.6% practicality.
The Paleodepositional Environments in the Shendi Sub-Basin as part of the Atbara Basin, North Sudan

This study describes the lithofacies diagnoses and the depositional environments of the Shendi sub-basin (a part of Atbara Basin) in North Sudan.Several full body fossils were observed in the study area such as trilobites, conulariids, Gyrophyllites and Archaeocyathids, in addition a number of trace fossils such as Rhizocorallium, and skolithos were reported.These fossils indicate deposition in a range of marine environments from intertidal to deep water.Furthermore, Herringbone crossstratification is observed and it suggested a shallow water environment.Two formations can be identified in the Shendi sub-basin; the lower formation was deposited in a range of shallow to deep marine environments of probable Lower Cambrian age while the upper formation of the 'Nubian Sandstone' was most likely deposited in fluvial environments of the Upper Cretaceous age.The lower formation is composed of four facies form bottom to top as; shale facies, carbonate facies, siltstone, fine sandstone facies, and chert facies.This study reveals the presence of the Archaeocyathids of Cambrian age, the oldest formation of the Paleozoic marine sedimentary rock ever found in Sudan.