Reviewerly/exHarmony huggingface dataset:
Recurrent Neural Networks for Person Re-identification Revisited

The task of person re-identification has recently received rising attention due to the high performance achieved by new methods based on deep learning. In particular, in the context of video-based re-identification, many state-of-the-art works have explored the use of Recurrent Neural Networks (RNNs) to process input sequences. In this work, we revisit this tool by deriving an approximation which reveals the small effect of recurrent connections, leading to a much simpler feed-forward architecture. Using the same parameters as the recurrent version, our proposed feed-forward architecture obtains very similar accuracy. More importantly, our model can be combined with a new training process to significantly improve re-identification performance. Our experiments demonstrate that the proposed models converge substantially faster than recurrent ones, with accuracy improvements by up to 5% on two datasets. The performance achieved is better or on par with other RNN-based person re-identification techniques.
Garden balsam optimization algorithm

Summary This paper introduces a method called garden balsam optimization algorithm (GBO) for optimization problems. Garden balsam randomly ejects the seeds within a certain range by virtue of mechanical force originating from cracking of mature seed pods. The seeds scattered to suitable growth area will have greater reproductive capacity in the next generation, followed by iteration until the most suitable point for growth in a particular space is eventually found. Mimicking the transmission of garden balsam seeds, GBO generates the seeds by the mechanical transmission and second transmission operator to search the global optimum in the problem space. The convergence of GBO is tested in details through a set of benchmark multi‐dimensional functions. Secondly, the effect of tuning parameters on algorithm performance is studied. Finally, several typical problems were selected in the standard test set to test the performance of GBO. The experimental results show that the algorithm has advantages in optimization problems. In conclusion, the performance of GBO has a reasonable performance for all the test functions.
Investigating effects of interactive signage–based stimulation for promoting behavior change

Abstract In recent years, many types of research and developments on behavior change have been conducted. The purpose of behavior change is to improve people's lifestyle pattern or to maintain the improvement for a long time with the aim to achieve a goal such as promoting health condition improvement. To achieve the foundation of a new lifestyle, it is necessary to recognize the daily life patterns of users and give triggers for behavior change to users in their daily life. To realize this, in our research, we develop an interactive signage which is able to identify and actively talk to the passing user and try to induce behavior change by sending visual and auditory stimulation. Then, we record users' reactions and upload them to the server. In this paper, we report the investigation result on users' reactions and feelings to the developed interactive signage. As a survey experiment, we set up four interactive signs on a floor of our university and asked 15 participants to carry a name tag with a Bluetooth Low Energy beacon during their daily life. Five kinds of tasks based on dialogue scenarios are posted to the approaching participants. Participants can respond to these tasks through a touchscreen. The period of the experiment was three weeks. To get the data in an ideal environment, during the first week, we asked all the participants to respond to the utterance from the interactive signage whenever they hear the voice message. During the next two weeks, participants were not asked to respond to the task definitely to get the data in the real environment. The result of the experiment showed that our proposed interactive signage could induce behavior change effectively. Based on the result of experiment, we updated our interactive signage system by adding response time (the time passed from showing contents until user respond), record function, and voice feedback function. Furthermore, to collect the data of response time that is considered as a part of users' reactions, we conducted an additional experiment with the same participants in previous experiment (except for one missing participant) for one week after updating the system. In the additional experiment, the participants were not asked to respond to the utterance definitely. As a result, it is shown that the behavior change by the proposed signage is still effectively induced. We also analyzed the relationship between the day passed and the response rate of each task type. The result shows that the number of ignorance of personal task and check task does not rise even as the time passes.
A Literature Survey on Eye Corner Detection Techniques in Real-Life Scenarios

Accurate iris movement detection and tracking is an important and widely used step in many Human-computer interactive applications. Among the eye features, eye corners are considered as stable and reliable reference points to measure the relative iris motion. In real time scenarios, the presence of spectacles prohibit the current state-of-the-art methods to yield accurate detection as the appearance of eye corners changes considerably due to the glare and occlusion caused by them. We term this problem as the Spectacle problem. In this paper we review the available single and multiple image based spectacle problem removal techniques and highlight the pros and cons of the approaches. For this state-of-the-art report, we investigated research papers, patents and thesis presenting the basic definitions, terminologies and new directions for future researches.
Collaboration between SAML federations and OpenStack clouds

In this paper, we present a novel OpenStack module called regsite for enabling easy access for researchers to OpenStack research clouds. Many researchers have an account in an Academic AAI federation, such as national research and education federations or the eduGAIN SAML meta-federation. The software solution presented here makes it possible to use these institutional accounts together with so-called virtual organization managers for authenticating and authorizing in OpenStack instances in a clean and secure way. An analysis of earlier generations of OpenStack-related developments trying to tackle the same problem is given. Many aspects of this software integration can be generalized to serve as a template for federative research cloud access.
Using augmented reality for teaching students with mental disabilities

Mobile touch devices enable the use of augmented reality-based applications. Implementation of augmented reality into regular education has been adequately described. The paper discusses the specifics of using augmented reality for teaching students with mental disabilities. It has been proven that augmented reality is not as demanding in terms of students’ graphomotor skills and that it reduces cognitive load. The paper describes the use of the HP Reveal application to help students with abstracting things, terms and curriculum.
Distributive Laws via Admissibility

This paper concerns the problem of lifting a KZ doctrine P to the 2-category of pseudo T-algebras for some pseudomonad T. Here we show that this problem is equivalent to giving a pseudo-distributive law (meaning that the lifted pseudomonad is automatically KZ), and that such distributive laws may be simply described algebraically and are essentially unique [as known to be the case in the (co)KZ over KZ setting]. Moreover, we give a simple description of these distributive laws using Bunge and Funk’s notion of admissible morphisms for a KZ doctrine (the principal goal of this paper). We then go on to show that the 2-category of KZ doctrines on a 2-category is biequivalent to a poset. We will also discuss here the problem of lifting a locally fully faithful KZ doctrine, which we noted earlier enjoys most of the axioms of a Yoneda structure, and show that a bijection between oplax and lax structures is exhibited on the lifted “Yoneda structure” similar to Kelly’s doctrinal adjunction. We also briefly discuss how this bijection may be viewed as a coherence result for oplax functors out of the bicategories of spans and polynomials, but leave the details for a future paper.
Evolution of gold-bearing splays of crustal-scale fault zones of the south-central Archean Abitibi subprovince: Constraints from the Kirana deformation zone, Kirkland Lake, Ontario, Canada

We explored the effects of brittle-ductile deformation processes on the localization of strain and hydrothermal fluid flow throughout the formation and evolution of a fault zone. This was accomplished through detailed structural analysis of the Kirana deformation zone (Kdz), a splay of the Archean crustal-scale, orogenic gold-hosting Larder Lake-Cadillac deformation zone (LLCdz) in Ontario, Canada. Investigations included mapping, quantification of fault-related breccia by particle size distribution analysis, microstructural and petrographic characterization, and kinematic analysis of brittle-ductile structures. The Kdz records three principal evolutionary stages. Stage 1 involved seismogenic processes that resulted in the formation of a >50 m wide fault core and damage zone. Stage 2 is characterized by transpressional ductile shear localized along texturally favorable, mechanically weakened zones that formed during stage 1 and/or along zones where coeval fluid flow facilitated reaction weakening. Native gold is observed within the mylonitized fault core that is interpreted to have formed syn-to late-ductile shear. All structures are crosscut by small-scale faults and shear veins with disseminated alteration halos, defining stage 3. The Kdz demonstrates how early fault processes may control the spatial pattern and temporal progression of strain and hydrothermal fluid localization in orogenic gold-bearing fault splays.
SKFlow: Optical Flow Estimation Using Selective Kernel Networks

Leveraging on the recent developments in convolutional neural networks (CNNs), optical flow estimation from adjacent frames has been cast as a learning problem, with performance exceeding traditional approaches. The existing networks always use standard convolutional layers for extracting multi-level features with the fixed kernel size at each level. For enlarging the receptive field, some works introduce dilated convolution operation, which can capture more contextual information and can avoid the loss of motion details. However, these networks lack the ability to adaptively adjust its receptive field size and cannot aggregate multi-scale information with a selective mechanism. To address this problem, in this paper, we introduce selective kernel network into optical flow estimation, which can adaptively select different scale features and adjust their receptive field according to the global information. Specifically, we conduct the selective kernel mechanism on each level of pyramid, which can adaptively select multi-scale feature at each pyramidal level. The extensive analyses are conducted on MPI-Sintel and KITTI datasets to verify the effectiveness of the proposed approach. The experimental results show that our model achieves comparable results with the previous state-of-the-art networks while keeping a small model size.
Toward a semantic-based location tagging news feed system: Constructing a conceptual hierarchy on geographical hashtags

Online news and social networking sites have been significantly used in recent years. There has been a lot of efforts to provide appropriate contents for the end users; however, they proved not to be effective. We believe the semantic web (as the third generation of the web) is mature enough to undertake the responsibility of generating more user-centric content. One way to exploit the semantic web's capabilities for such purpose is to construct an ontology that establishes the relationships between hashtags. In this paper, we present the construction process of a news feed system based on the hierarchical relationships of geographic hashtag. Our experiments demonstrated that our proposed semantic-based hierarchical location tagging news feed system increases the quality of the user experience as well as the publication rate of the news while boosting the content match rate to the target audiences. The proposed system of this paper can be considered as a real step towards the realization of semantic web.
Back to basics: tackling security threats in an increasingly complex world

Something strange is happening to the world of IT. As technological innovation drives businesses to become more productive, innovative and agile, it's simultaneously driving those tasked with protecting these new networks and systems to breaking point. Complexity might be hidden from the end user, but it's making the job of the IT security function more challenging by the day. As technological innovation drives businesses to become more productive, innovative and agile, it's simultaneously driving those tasked with protecting these new networks and systems to breaking point. Complexity might be hidden from the end user, but it's making the job of the IT security function more challenging by the day. This can sometimes make it difficult for security practitioners to filter out the noise and remember what's really important. Organisations need to focus on the end user and adopt basic best practices to ensure their security is built on a solid foundation, argues Jon Fielding of Apricorn.
Asynchronous Approximation of a Single Component of the Solution to a Linear System

We present a distributed asynchronous algorithm for approximating a single component of the solution to a system of linear equations Ax = b, where A is a positive definite real matrix and b ∈ R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sup> . This can equivalently be formulated as solving for x <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</sub> in x = Gx + z for some G and z such that the spectral radius of G is less than 1. Our algorithm relies on the Neumann series characterization of the component xi, and is based on residual updates. We analyze our algorithm within the context of a cloud computation model motivated by frameworks, such as Apache Spark, in which the computation is split into small update tasks performed by small processors with shared access to a distributed file system. We prove a robust asymptotic convergence result when the spectral radius ρ(|G|) <; 1, regardless of the precise order and frequency in which the update tasks are performed. We provide convergence rate bounds that depend on the order of update tasks performed, analyzing both deterministic update rules via counting weighted random walks, as well as probabilistic update rules via concentration bounds. The probabilistic analysis requires analyzing the product of random matrices that are drawn from distributions that are time and path dependent. We specifically consider the setting where n is large, yet G is sparse, e.g., each row has at most d nonzero entries. This is motivated by applications in which G is derived from the edge structure of an underlying graph. Our results prove that if the local neighborhood of the graph does not grow too quickly as a function of n, our algorithm can provide significant reduction in computation cost as opposed to any algorithm that computes the global solution vector x. Our algorithm obtains an ∈||x|| <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> additive approximation for xi in constant time with respect to the size of the matrix when the maximum row sparsity d = O(1) and 1/(1 - ||G|| <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> ) = O(1), where ||G|| <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> is the induced matrix operator 2-norm.
On quantum stabilizer codes derived from local Frobenius rings

In this paper we consider stabilizer codes over local Frobenius rings. Firstly, we study the relative minimum distances of a stabilizer code and its reduction onto the residue field. We show that for various scenarios, a free stabilizer code over the ring does not underperform the according stabilizer code over the field. This leads us to conjecture that the same is true for all free stabilizer codes. Secondly, we focus on the isometries of stabilizer codes. We present some preliminary results and introduce some interesting open problems.
Disrupting the U.S. National Security Through Financial Cybercrimes

The U.S. financial sector is the bedrock of the economic health and strategic advancement. As a critical infrastructure, the financial sector continuously faces cyber-attacks and other nefarious activity. The financial sector is undergoing a technological explosion and forcing banks and financial institutions to implement cutting edge technologies. Even though technological breakthroughs are yielding competitive advantages; consequently, the same technologies are more prone to cyber-attacks stemming from technologically-induced vulnerabilities. The integrative and hyperconnected state of the financial industry and the domestic and global financial ecosystems are highly centralized and vulnerable to sophisticated cybersecurity threats, human factors, social engineering, credit card fraud, and online banking schemes. Any attempts to degrade, disrupt, or deny vital services and transactions in the financial industry could be conceived as an infringement and blockade of the U.S. global powers.
Improved XKX-Based AEAD Scheme: Removing the Birthday Terms

Naito [ToSC 2017, Issue 2] proposed $$\mathtt {XKX}$$ , a tweakable blockcipher (TBC) based on a blockcipher (BC). It offers efficient authenticated encryption with associated data (AEAD) schemes with beyond-birthday-bound (BBB) security, by combining with efficient TBC-based AEAD schemes such as $$\mathrm {\Theta CB3}$$ . In the resultant schemes, for each data block, a BC is called once. The security bound is roughly $$\ell ^2 q/2^n+ \sigma _{A}^2/2^n+ \sigma _\mathcal {D}^2/2^n$$ , where $$n$$ is the block size of the BC in bits, $$\ell $$ is the number of BC calls by a query, $$q$$ is the number of queries, $$\sigma _{A}$$ is the number of BC calls handing associated data by encryption queries, and $$\sigma _\mathcal {D}$$ is the number of BC calls by decryption queries. Hence, assuming $$\ell , \sigma _{A}, \sigma _\mathcal {D}\ll 2^{n/2}$$ , the AEAD schemes achieve BBB security. However, the birthday terms $$\sigma _{A}^2/2^n$$ , $$\sigma _\mathcal {D}^2/2^n$$ might become dominant, for example, when $$n$$ is small such as $$n=64$$ and when DoS attacks are performed. The birthday terms are introduced due to the modular proof via the $$\mathtt {XKX}$$ ’s security proof. In this paper, in order to remove the birthday terms, we slightly modify $$\mathrm {\Theta CB3}$$ called $$\mathrm {\Theta CB3}^\dagger $$ , and directly prove the security of $$\mathrm {\Theta CB3}^\dagger $$ with $$\mathtt {XKX}$$ . We show that the security bound becomes roughly $$\ell ^2 q/2^n$$ .
Non-factoid Question Answering in the Legal Domain

Non-factoid question answering in the legal domain must provide legally correct, jurisdictionally relevant, and conversationally responsive answers to user-entered questions. We present work done on a QA system that is entirely based on IR and NLP, and does not rely on a structured knowledge base. Our system retrieves concise one-sentence answers for basic questions about the law. It is not restricted in scope to particular topics or jurisdictions. The corpus of potential answers contains approximately 22M documents classified to over 120K legal topics.
Towards a Resource-aware Thing Composition Approach

This paper addresses the silo concern that undermines the participation of IoT-compliant things in composition scenarios. By analogy with composite Web services, each scenario is specified in terms of choreography and orchestration and at design-time and run-time. To define things’ execution behaviors during composition, a set of transactional properties known as pivot, retriable, and compensatable, are used allowing to decide when thing execution should be confirmed, rolledback, or stopped. Along with these properties, another set of availability properties known as limited, renewable, and nonshareable specify the resources that things consume at run-time. Not all resources are always available and hence, could impact the execution of thing composition scenarios. A case study related to Industry 4.0 is used to motivate thing composition.
Revisiting Skip-Gram Negative Sampling Model with Rectification

We revisit skip-gram negative sampling (SGNS), one of the most popular neural-network based approaches to learning distributed word representation. We first point out the ambiguity issue undermining the SGNS model, in the sense that the word vectors can be entirely distorted without changing the objective value. To resolve the issue, we investigate the intrinsic structures in solution that a good word embedding model should deliver. Motivated by this, we rectify the SGNS model with quadratic regularization, and show that this simple modification suffices to structure the solution in the desired manner. A theoretical justification is presented, which provides novel insights into quadratic regularization. Preliminary experiments are also conducted on Google’s analytical reasoning task to support the modified SGNS model.
Writer Characterization and Identification of Short Modern and Historical Documents

Handwriting is considered a unique "fingerprint" that characterizes a scribe (it is even used as evidence in modern forensics). In paleography (the study of ancient writing), it is presumed that each writer has a one prototype for each letter in the alphabet. Commonly, for ancient inscriptions, letters are organized into paleographic tables (where the rows are the alphabet letters, and the columns represent the examined inscriptions). These tables play a significant role in dating inscriptions based on their resemblance to columns in the table. In this paper, we argue that each scribe "fingerprint" is not represented by a single character prototype, but in fact by a distribution of characters. We introduce a framework for automatically identifying the writer style and constructing paleographic tables based on character histograms. Subsequently, we propose a method for comparing short documents utilizing letter distribution. We demonstrate the validity of the methods on two handwritten datasets: Modern and Ancient Hebrew pertaining to the First Temple period. Our methodology on the ancient dataset enables us to provide additional evidence concerning the level of literacy in the kingdom of Judah ca. 600 BCE.