Miracle-dz/UniFAR-FTUs huggingface dataset:
Interactive Object Segmentation With Inside-Outside Guidance

This article explores how to harvest precise object segmentation masks while minimizing the human interaction cost. To achieve this, we propose a simple yet effective interaction scheme, named Inside-Outside Guidance (IOG). Concretely, we leverage an inside point that is clicked near the object center and two outside points at the symmetrical corner locations (top-left and bottom-right or top-right and bottom-left) of an almost-tight bounding box that encloses the target object. The interaction results in a total of one foreground click and four background clicks for segmentation. The advantages of our IOG are four-fold: 1) the two outside points can help remove distractions from other objects or background; 2) the inside point can help eliminate the unrelated regions inside the bounding box; 3) the inside and outside points are easily identified, reducing the confusion raised by the state-of-the-art DEXTR Maninis et al. 2018, in labeling some extreme samples; 4) it naturally supports additional click annotations for further correction. Despite its simplicity, our IOG not only achieves state-of-the-art performance on several popular benchmarks such as GrabCut Rother et al. 2004, PASCAL Everingham et al. 2010 and MS COCO Russakovsky et al. 2015, but also demonstrates strong generalization capability across different domains such as street scenes (Cityscapes Cordts et al. 2016), aerial imagery (Rooftop Sun et al. 2014 and Agriculture-Vision Chiu et al. 2020) and medical images (ssTEM Gerhard et al. 2013). Code is available at https://github.com/shiyinzhang/Inside-Outside-Guidancehttps://github.com/shiyinzhang/Inside-Outside-Guidance.
Fault Tolerant Quantum Clock Synchronization

Secure fault-tolerant clock synchronization can be received using Byzantine agreement. Classically this can reach a fault-tolerance of less than a third faulty processors or complicated signatures, in which case all fault rates. The Byzantine Agreement problem have successfully been solved for three players using quantum information and thereby decreasing the complexity of the protocol. This paper develops the three players quantum solution of the Byzantine Agreement problem for use on clock synchronization with positive results. Further, quantum enhanced protocols for more than three players both for Byzantine Agreement and clock synchronization are discussed.
Brain–Computer Interfaces Handbook Technological and Theoretical Advances

The great improvements in brain–computer interface (BCI) performance that are brought upon by merging brain activity from multiple users have made this a popular strategy that allows even for human augmentation. These multi-mind BCIs have contributed in changing the role of BCIs from assistive technologies for people with disabilities into tools for human enhancement. This chapter reviews the history of multi-mind BCIs that have their root in the hyperscanning technique; the collaborative and competitive approaches; and the different ways that exist to integrate the brain signals from multiple people and optimally form groups to maximize performance. The main applications of multi-mind BCIs, including control of external devices, entertainment
Price Asymmetric Evaluation on the Cocoa Market as an Effort to Increase Economic and Bargaining Position of Cocoa Farmers in Pidie, Aceh

The price transmission process on agricultural commodities especially at the smallholder level generally occurs imperfectly as price asymmetric. This study aims to evaluate and identify the occurrence of price asymmetric in the cocoa commodity market in the Pidie Regency. This study also aims to look at the causes and obstacles faced by cocoa farmers in the price issue and how the solutions strengthen their bargaining position against the power of wholesalers in the cocoa market. Thus, a solution will be found to reduce the gap between cocoa farmers and traders. Increasing the bargaining position of farmers is of course one of the efforts to increase. This study uses the Vector Error Correction Model (VECM) method. The data used are secondary data in the form of monthly average data for 2018-2020. There is a long-term and short-term price transmission relationship between the price of cocoa at the farm level and the price of cocoa at the collected trader’s level in the Pidie Regency. The causes of the price transmission relationship are the lack of information availability, the low quality of cocoa produced by farmers, less supportive agribusiness institutions such as the inactive cocoa farmer associations or cooperatives and limited transportation. For this reason, an efficient marketing channel is needed, for example by establishing farmers cocoa association, and drying the processing practices that comply with the desired moisture standard.
Faktor Pendorong Keputusan Pembelian Virtual Item Pada Mobile Commerce (Studi Kasus: Game Mobile Legends)

- MOBA or Multiplayer Online Battle Arena or commonly called action real-time strategy (ARTS) is part of real-time strategy (RTS). One type of Multiplayer Online Battle Arena (MOBA) action game on mobile devices is Mobile Legend. The game was created and developed by a game development company from Shanghai, China called Moonton. This game already has millions of players in the world. It is evident from a play store application market with the number of downloads in April 2021 reaching more than 100 million. It can be concluded that more than 100 million smartphone devices have installed this game since the global launch for the Android platform on July 11
Difficulties Faced and Applications of Machine Learning in Cyber-Security

Over time, internet technologies like social networks, cloud computing and web technologies have shown remarkable progress therefore the need for securing these platforms has also intensified. Machine learning has displayed eminence over the conventional rule-based algorithms. This paper is a literature survey of scrutinizing security attributes of protocols and replacing the first level of security analysis with superior machine learning algorithms. Although Machine Learning is one of the most promising answers against cyber-crimes and contemporary research is being undertaken by the use of machine learning techniques, the effectiveness of machine learning in cybersecurity must be evaluated. This paper is an attempt to identify the hindrances faced in applying these machine learning techniques practically.
New Organizational Environment Types Based on Garvin and Quinn – the Case of Slovakian Small and Medium Enterprises

– The aim of the study was to examine what common characteristics can be observed in companies based on Garvin’s learning organization and the Quinn’s organizational culture. Both of the trends are considered a fundamental factor of modern management. Studying the international scientific literature, it is clear that examining the overlaps between the two approaches is highly incomplete. The issue was approached from the perspective of employees, as they show high willingness to express their opinion. A questionnaire survey was used as a part of our research. 549 responses were included in the analysis, during which we applied a cluster analysis. Based on the results, three different types of organizational environment can be defined: supporting, neutral and distancing
Noisy Riemannian Gradient Descent for Eigenvalue Computation with Application to Inexact Stochastic Recursive Gradient Algorithm

We provide a robust convergence analysis of the Riemannian gradient descent algorithm for computing the leading eigenvector of a real symmetric matrix. Our result characterizes the convergence behavior of the algorithm under the noisy updates, where noises can be generated by a stochastic process or could be chosen adversarially. The noisy Riemannian gradient descent has a broad range of applications in machine learning and statistics, e.g., streaming principal component analysis or privacy-preserving spectral analysis. In particular, we demonstrate the usefulness of our convergence bound with a new eigengap-dependent sample complexity of the inexact Riemannian stochastic recursive gradient al-gorithm, which utilizes mini-batch gradients instead of full gradients in outer loops. Our robust convergence paradigm strictly improves the state-of-the-art sample complexity in terms of the gap dependence.
Rango de identidad académica y su relación con la orientación de meta de logro Christopher

Introduction . Two constructs that have received a great deal of attention in Educational Psychology research are Achievement Orientation and Identity Status. However, the relationship between these two constructs has not received the attention that the current researcher feel is warranted. The impetus for the current study is the paucity of research in this area. Method . The current study employed a self-report measure of academic identity status founded in Marcia’s theory of identity states. A second measure adopted from Elliot’s trichotomous framework of goal orientation was used to capture students’ achievement goal orientation. Data collected from 407 undergraduate students was submitted to correlational and path analyses to examine the relationship between the two constructs. Results . Results indicated that the specific academic identity status of a student is related to the type of academic goals one adopts. Discussion or Conclusion . The results of our analysis support our hypothesis that a relationship exists between a student’s academic identity status and the types of goals a student will adopt. Implications for educators and research are discussed.
Comparative study on the levels of phytochemicals present in n-hexane, ethanol, aqueous, ethylacetate and methanol extracts of Uvaria chamae stem

A comparative phytochemical analysis was conducted to determine the levels of the phytochemicals present in n-hexane, ethanol, aqueous, ethylacetate and methanol extracts of Uvaria chamae stem. The qualitative phytochemical screening showed the presence of phenols, alkaloids, flavonoids, tannins, saponins, steroids, and glycosides in U. chamae stem. The result of the quantitative estimations of the concentrations of the various phytochemicals in the different solvent extracts recorded variations, with some showing higher concentration than others. Ethanolic extract of the plant showed significantly ( p ˂0.05) higher concentrations of saponins, (602.00 ± 1.00 µg/ml) and phenols (82.00 ± 2.00 µg/ml) than in other solvent extracts. The concentrations of alkaloids in ethanolic and aqueous extracts (708.00 ± 1.00 µg/ml) were higher than in other extracts. Also, aqueous extracts showed significantly ( p ˂0.05) higher concentrations in flavonoids, (0.82 ± 0.02 mg/ml), glycosides (10.30 ± 0.10 µM) and tannins (0.19.00 ± 0.15 mg/ml) than in other extracts. The concentrations of steroids were found to be significantly ( p ˂0.05) higher in the methanolic extract (107.00 ± 2.00 µg/ml) than in other extracts. Therefore, the study showed that Uvaria chamae stem contains appreciable amounts of medicinally important phytochemicals, with solubilities (extraction powers) differing in different solvents. Hence, the various solvents with higher yield can be exploited to get higher concentrations of the required phytochemical.
The Effect of Exchange Rate, Inflation, Gross Domestic Bruto, Return on Assets, and Debt to Equity Ratio on Stock Return in LQ45 Company

: This study aims to determine the effect of exchange rates, inflation, Gross Domestic Product, Return On Assets, and Debt to Equity Ratio on stock returns.The study uses secondary data in a period of 4 years from 2015-2018 in companies that listed in LQ45 Index. The sampling technique used a purposive sampling and the total sample of this research are 26 companies. The analysis method used in this research is multiple linear regression.The result of this study are (1) Exchange rate has a negative and significant effect on stock returns, (2) Inflation has a negative and not significant effect on stock returns, (3) Gross Domestic Product has a negative and not significant effect on stock returns, (4) Return on Assets has a positive and not significant effect on stock returns, (5) Debt to Equity Ratio has a negative and not significant effect on stock returns
Evidence for base-driven alternation in Tgdaya Seediq

Standard morphophonological analysis allows composite URs, which “cobble” together information from multiple slots of a paradigm (Kenstowicz & Kisseberth, 1977). In contrast, under the single surface base hypothesis (Albright 2002 et seq. ), the input to morphophonology must be a single slot in a paradigm. In this paper, I compare the two approaches by examining verb paradigms in Tgdaya Seediq. In a corpus study of the Seediq lexicon, I find that isolation stems are much more informative than suffixed forms. This asymmetry is argued to support the surface-base approach. Results are further supported in an experiment, where speakers productively extended alternations from the isolation stem to novel suffixed forms. Interestingly, speakers over-generalised certain patterns instead of matching lexical statistics in the experiment. I propose that this non-viridical learning is the result of a complexity bias, which cannot be accounted for in existing surface-base models of morphophonological learning. Instead, I propose a constraint-based analysis of Seediq alternations, with a complexity learning bias.
Supplementary Materials: Robust Trajectory Prediction against Adversarial Attacks

where d is a distance function (e.g., L2 norm). However, latent attack and context attack are effective due to two reasons. First, they are exploiting the vulnerability of a partial model. For example, latent attack only exploits the posterior estimation qφ(Z|X,Y) and context attack only exploits the conditional encoder f(X). Second, these attacks aim for a different goal. For the latent attack and context attack, the objectives are set for finding adversarial perturbations that maximize the difference of generated posterior distribution/context given X and X + δ, due to lacking ground truth for intermediate latent variables. However, for the sample attack, the objective is directly set for maximizing the prediction errors from the ground truth (future trajectories), which is more effective.
Perturbed, Genus One Scherk Surfaces and their limits

Perturbed Genus One Scherk Surfaces and Their Limits by Casey Douglas The singly periodic, genus one helicoid is conjectured to be the limit of a one parameter family of doubly periodic minimal surfaces referred to as Perturbed Genus One Scherk Surfaces. Using elementary elliptic function theory, we show such surfaces exist, solving a two-dimensional period problem by perturbing a one-dimensional problem. Using flat structures associated to these minimal surfaces, we then verify the conjecture.
Improved MCMC method and its application

A multi-chain sampling method based on Metropolis-Hastings algorithm was used to improve the Markov Chain Monte Carlo(MCMC) method in order to prevent from trapped into the local optimal solutions that often occur to probability inversion by using current MCMC algorithm.The improved MCMC method can adjust the number of chains according to the feedback results from sampling process in real time,so that it can search out the non-unique solutions as much as possible while saving the time of multi-chain search.As an example an inverse problem of groundwater flow was solved by using the improved MCMC algorithm.The computational results indicate the improved method performs well in solving inverse problems with non-unique solutions.
Finding Hierarchical and Overlapping Dense Subgraphs using Nucleus Decompositions

Finding dense substructures in a graph is a fundamental graph mining operation, with applications in bioinformatics, social networks, and visualization to name a few. Yet most standard formulations of this problem (like clique, quasi-clique, k-densest subgraph) are NP-hard. Furthermore, the goal is rarely to ﬁnd the “true optimum”, but to identify many (if not all) dense substructures, understand their distribution in the graph, and ideally determine a hierarchical structure among them. Current dense subgraph ﬁnding algorithms usually optimize some objective, and only ﬁnd a few such subgraphs without providing any hierarchy. It is also not clear how to account for overlaps in dense substructures. We deﬁne the nucleus decomposition of a graph, which represents the graph as a forest of nuclei . Each nucleus is a subgraph where smaller cliques are present in many larger cliques. The forest of nuclei is a hierarchy by containment, where the edge density increases as we proceed towards leaf nuclei. Sibling nuclei can have limited intersections, which allows for discovery of overlapping dense subgraphs. With the right parameters, the nuclear decomposition generalizes the classic notions of k -cores and k -trusses. We give provable eﬃcient algorithms for nuclear decompositions, and empirically evaluate their behavior in a variety of real graphs. The tree of nuclei consistently gives a global, hierarchical snapshot of dense substructures, and outputs dense subgraphs of higher quality than other state-of-the-art solutions. Our algorithm can process graphs with tens of millions of edges in less than an hour.
Facial feature extraction based on curvature and texture

To compensate for the limitation of the 3D facial feature extraction that is sensitive to the expressions,a new method of 3D facial extraction based on curvature and texture is proposed.This method uses the characteristics that the surface curvature describes the facial shape and the texture will not be affected by expressions.The experimental results show that this method which uses the range image of 3D face is not sensitive to expression and pose,and has high veracity and good robustness.
Swiss-cheese action on the totalization of action-operads

We prove that if a pair of semi-cosimplicial spaces (X,Y) arise from a coloured operad then the semi-totalization sTot(Y) has the homotopy type of a relative double loop space and the pair (sTot(X),sTot(Y)) is weakly equivalent to an explicit algebra over the two dimensional Swiss-cheese operad.
Blood Vessel Enhancement by Directed Diffusion

In this paper, a blood vessel in an angiographic image, which plays an importance role in the diagnose diseases including in the eyes, brain and heart, is enhanced by using a directed diffusion technique. A fundamental component of the angiographic analysis is vessel segmentation that the proposed method provides a preprocessing of the image into a form suitable for human analysis, or more importantly, for machine analysis such the segmentation. Vessel enhancement is a challenging problem due to the complex nature of vascular trees and to imaging imperfections. Some parts of the inherent imperfections in angiography are the intensity inhomogeneity between the larger and smaller vessels, and another imperfection is the leakage of contrast agent into the background tissue that provides to low contrast between vessels and tissue. In the proposed scheme, the directed diffusion solves the problem by formulating a local geometric structure, which consists of direction and scale of the blood vessels. The diffusion process uses the local structure to enhance by a diffusivity tensor. The proposed algorithm can be applied to maintain sharpness and coherence-smooth the intra-regions into homogeneity better than traditional diffusion methods, which are Gaussian regulation and coherence enhancing diffusion.
Participatory Conspiracy Culture

The popularization and normalization of conspiracy theories over the last decade are accompanied by concerns over conspiracy theories as irrational beliefs, on the one hand; and their advocates as radical and extremist believers on the other hand. Building on studies emphasizing that such accounts are one-sided at best, and pars pro toto stigmatizations at worst; we propose to study what we call “ participatory conspiracy culture ” — the everyday, mundane online debates about conspiracy theories. Based on a 6-month ethnography on Reddit ’ s r/conspiracy subreddit, an analysis of 242 selected discussions, and supported by digital methods tool 4CAT, this article addresses the question of how people participate in online conspiracy culture. It shows that among the plethora of conspiracy theories discussed online, discussions are heterogeneous, and their participants relate to each other primarily through con ﬂ ict. Three epistemological positions occur: belief (particularly leading to constant discreditation of others ’ beliefs), doubt (particularly as opposed to belief), and play (particularly with the fun of entertaining conspiracy theories without taking them too seriously). We conclude that the participatory conspiracy culture of r/conspiracy is not a homogenous echo chamber of radical belief, but a heterogeneous participatory culture in which belief is fundamentally contested, rather than embraced.
A Review of Sustainable Supplier Selection and Evaluation Using Topic Modelling

The study provides a review of sustainable supplier selection (SSS), which has proceed to emerge and expand along with greater speed over the last decades. This research aims to identify and explore the use of machine learning and text mining methods to automatically identify relevant core topics in sustainable supplier selection. The traditional approach by personal judgments with predetermined categories, cannot adequately take latent topics from large volumes of research data. Therefore, this study selects the topic modelling approach, which automatically identify topics that extend a large and unstructured collection of documents to uncover research topics in sustainable supplier selection research. The papers for the literature review were collected from SCOPUS database. The model with 20 topics was selected through the Latent Dirichlet Allocation (LDA) model from selected articles published from 2010 to 2020 in associated with various journals, and the top 5 most popular topics in sustainable supplier selection research are reviewed in a nutshell. We then explore topic trends by considering the transformation over different topics of sustainable supplier selection research over the last few decades. For each of the top 10 journals, the areas of subspecialty and the effects of editor changes on the topic portfolios are also investigated. The findings of this study are expected to provide implications for researchers, journal editors, and policy makers in the field of sustainable supplier selection.
A NEW WIRESCANNER CONTROL UNIT

Wires scanners are standard instruments for beam size measurements in storage rings: A wire is crossing the beam at a given speed and the secondary emission current of the wire and/or the photomultiplier signals produced from Bremsstrahlung or particles scattered at the wire are recorded together with the wire positions. The control unit described here is based on a previous CERN design [1]. It now has additional features: �� Triggered fast scans (1m/s) with a trigger uncertainty below ± 30µs (mechanics + electronics) used at the TTF Linac and at the proton synchrotron DESY III, �� Slow scans (e.g. 50µm/s) for the TTF Linac, �� Positioning of the wire within ± 3µm for tail scans at the storage rings PETRA and HERA, �� A 10.5MHz data acquisition rate for bunch-by-bunch acquisitions in the accelerators at DESY. Another important design goal was the compatibility with CERN scanners; it is foreseen to operate them at LHC with the new control unit. First measurements with the new control unit at TTF and HERA will be presented.