Reviewerly/exHarmony huggingface dataset:
Impact of usability on process lead-time in information systems: A case study

Technological advancements have started to demand the need for information systems to survive in the business world. There is an inherent need to be fast and efficient to conquer the market. In order to reduce time to market there is a need to shorten the lead-time in design and development process of products. Hence, lead-time is a significant performance metric for a product development organizations having information systems. It is important to explore the factors which affect the process lead-time in information systems. The objective of this study is to explore the impact that usability (one of the factors that may affect the process lead-time) has on process lead-time. This paper presents a case study involving qualitative and quantitate data from Volvo Group, which uses an information system called KOLA for their design and development process. Data was collected through 29 interviews, 17 think aloud sessions, 5 document studies, and 73 responses from a survey. This study identifies which usability factors and heuristics that have an impact on process lead-time. Moreover, the results show that the users level of experience determines the effective utilization of accelerators and thereby affecting the process lead-time. Finally, usability plays an important role in shortening the process lead-time in information systems.
Soft‐input bit‐flipping decoding of generalised concatenated codes for application in non‐volatile flash memories

Error correction coding based on soft-input decoding can significantly improve the reliability of non-volatile flash memories. This work proposes a soft-input decoder for generalised concatenated (GC) codes. GC codes are well suited for error correction in flash memories for high reliability data storage. The authors propose GC codes constructed from inner extended binary Bose–Chaudhuri–Hocquenghem (BCH) codes and outer Reed–Solomon (RS) codes. The extended BCH codes enable an efficient hard-input decoding. Furthermore, a low-complexity soft-input decoding method is proposed. This bit-flipping decoder uses a fixed number of test patterns and an algebraic decoder for soft-decoding. An acceptance criterion for the final candidate codeword is proposed. Combined with error and erasure decoding of the outer RS codes, this acceptance criterion can improve the decoding performance and reduce the decoding complexity. The presented simulation results show that the proposed bit-flipping decoder in combination with outer error and erasure decoding can outperform maximum-likelihood decoding of the inner codes.
Effective consistency management for large-scale product data

The research presented is aimed to develop and investigate an effective method for management of consistency of large-scale product data. Such data are usually driven by formal models in EXPRESS language being part of the STEP standard (ISO 10303). To be consistent and unambiguously interpretable by computer programs the data must satisfy syntactic and semantic rules defined by the standards. Although ACID principles (Atomicity, Consistency, Isolation, and Durability) are widely recognized and recommended for any information system, it is hard to guarantee the consistency of such complex data. Complete semantic validation requires extremely high costs, often exceeding the processing time of individual transactions. Periodic validation or validation on user demand is possible, but at a high risk of losing data that become useless in case of rule violation. In the paper an effective incremental method for semantic validation of product data is presented. It is guaranteed that the final data revision is consistent if only the original revision was consistent and the spot rules were not violated. Static analysis of the model specifications is applied and a dependency graph is formed. The dependency graph enables to identify the spot rules and the data that should be inspected against the rules. Computational experiments prove the effectiveness of the method in conformity to complex large-scale product data managed under an innovative platform PDMhub.
Contextual Information Based Quality Assessment for Contrast-Changed Images

In this letter, we propose the objective metric that can precisely predict the perceptual quality of contrast-changed images using inter-pixel contextual information. The metric consists of two parts. One is a two-dimensional (2-D) histogram-based contrast quality measure that utilizes the distribution of the gray-level differences between adjacent pixels. We design the desired 2-D histogram considering the characteristic of an adequately high contrast image and predict contrast quality by comparing the desired 2-D histogram with 2-D histograms of an original image and a contrast-changed image. The other is a spatial entropy based one that uses the information of spatial location distribution of gray-levels. A comparison is carried out with many IQA metrics on five contrast related databases. Experimental results show that the proposed metric provides a more accurate prediction of human perception of contrast change than other metrics.
Compact E-Cash with Efficient Coin-Tracing

Compact E-cash achieves an efficient system by withdrawing 2n coins within O(1) operations and storing the coins in O(n) bits. For preventing a double-spender from cheating again, it is necessary to trace his e-coins. So full-tracing in compact E-cash system means tracing double-spender and tracing his coins. However, the efficiency problem caused by coin-tracing without TTP (trusted third party) has not been solved. For solving this problem, we introduce a non-standard construction into zero-knowledge proof of payment protocol, which leaks coin information when double-spending but is proven to be perfect zero-knowledge to verifier when spending a coin only once. Therefore, it achieves tracing dishonest users' coins and preserving the anonymity of honest users. Comparing with the existing most efficient method of coin-tracing without TTP, we improve computational complexity from O(k) to O(1) with less storage space. In addition, to improve efficiency and practicality further, batch-spending (spending any number of coins in one operation) and compact-spending (spending all coins in one operation) had been proposed. Based on the non-standard zero-knowledge proof, our scheme provides more efficient batch/compact-spending. Moreover, we also make a comparison with Bitcoin and Bitcoin Lightning Network, which have attracted considerable attention.
Agile Lifecycle Processes and the Funnel Model of Agile UX

In this chapter, we discuss the many challenges with building systems. We talk about how change in the designer’s understanding of user needs, requirements, and even the overall vision of the design occur inevitably and how the ability of the team and the process to handle change will impact success of the project. We explain how the old waterfall process did not help manage change and why we now embrace an agile lifecycle process that treats change as a reality. We represent the concepts of scope and chunking (of deliverables) in an agile UX process in what we call the funnel model of agile UX. Early funnel activities include upfront analysis and design, while late funnel activities are devoted to syncing with the SE implementation sprints.
Counting local n-ary patterns

Despite the fact that image descriptors based on the statistical distribution of local patterns are very common tools, most of their mathematical underpinnings have been largely overlooked. Among them, the rigorous determination of the number of possible patterns that can arise from a given neighbourhood and kernel function – particularly when invariance under group actions (e.g., rotations and/or reflections) is taken into account – has received little or no attention in the literature. In this note we address the problem of counting local patterns in a rigorous way. We provide exact formulas for the number of the possible directional, rotation- and reflection-invariant patterns generated by neighbours of n points over alphabets of k symbols. Variations on this scheme such as rank and uniform patterns are considered, and direct applications to a number of common descriptors (e.g., Local Binary Patterns, Texture Spectrum and Full Ranking) are also presented.
Connecting Agile UX With Agile Software Development

Since our very early description of the agile UX funnel model, we have assumed an agile UX process. Now we discuss some details about how the agile UX process can connect to an agile SE process in real-world project environments. Agile software engineering (SE) approaches, now well-known and popularly used, are incremental, iterative, and a test-driven means of frequently delivering pieces of useful working software to customers. In the past, agile SE approaches have not taken UX into account. Because traditional UX processes have not fit well within agile SE environments, the UX side has struggled to adjust their methods to fit SE constraints. But, to be successful in developing usable systems, the entire team needs an overall approach that includes agile UX while retaining the basics of agile SE approaches. We begin by describing the basic goals, principles, and characteristics of agile SE, along with lifecycle aspects of agile SE, including planning and sprints. Then we look at the challenges of agile SE methods from the UX perspective. We conclude with a synthesized approach to integrating agile UX and agile SE, including integrating UX into planning and integrating UX into sprints—synchronizing the two agile work flows.
Our response to Devitt

It is argued that contraposition is valid for a class of natural language conditionals, if some modifications are allowed to preserve the meaning of the original conditional. In many cases, implicit temporal indices must be considered, making a change in verb tense necessary. A suitable contrapositive for implicative counterfactual conditionals can also usually be found. In some cases, the addition of certain words is necessary to preserve meaning that is present in the original sentence and would be lost or changed in the contrapositive without them. A distinction is made between adding new meaning and adding new words to preserve existing meaning. For concessive conditionals and relevance conditionals, however, no valid contrapositive can be found. They do not belong to the class of contraposable conditionals, which can be independently defined. Difficult cases are also discussed in which the contradictory of the consequent semantically entails the truth of the antecedent. In such cases the content of the antecedent is implicit in the meaning of the consequent. Contraposition becomes possible if what is implicit in the original consequent is made explicit in the contrapositive antecedent.
Precise Power Capping for Latency-Sensitive Applications in Datacenter

Power capping is widely used in cloud datacenters to mitigate power over-provisioning problem, thus improve datacenter capacity and cut off their operation cost. However, inappropriate or aggressive power capping may lead to performance degradation of applications (especially latency-sensitive ones), and there are few effective methods that can accurately evaluate and control such negative impact caused by aggressive power capping. In this paper, we propose <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Fine-Grained Differential Method</i> (FGD) to quantitatively analyze how inappropriate power capping degrades the performance of latency-sensitive applications. By using FGD, we can minimize the provisioned power for each server by setting a precise power budget according to application’s <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Service Level Agreement</i> (SLA). And we further propose <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Precise Power Capping</i> (PPCapping) which is designed to increase the datacenter capacity with a fixed power supply by means of FGD. Our research also provides an insight of precise tradeoff between applications’ SLAs and datacenter capacity. We verify FGD and PPCapping by using real world traces from Tencent’s datecenter with 25,328 servers. The experimental results show that FGD can accurately analyze the impact of power capping on the performance of latency-sensitive applications, and PPCapping can effectively increase datacenter capacity compared with the typical power provisioning strategy.
Detection Rate Optimization for Swerling Targets in Gaussian Noise

In this paper, we consider a pulse radar and study the tradeoff between integration time and scan rate for diverse target scattering models. At the design stage, we optimize the available degrees of freedom (namely, pulse train length and detection threshold) so as to maximize the detection rate, defined as the average number of detections from the target per unit of time, subject to a constraint on the false alarm rate, which is the average number of false alarms from the monitored area per unit of time. This objective function allows to carefully balance the contrasting needs for a large probability of detection (achievable through a large dwell time) and a short scan time. Closed-form solutions are provided for Swerling's Cases 1 and 3 target fluctuation and for the Marcum nonfluctuating model, while, for the Swerling's Cases 2 and 4, the solution is found with the aid of computer simulation. A thorough performance analysis is given to show the achievable tradeoffs among the principal system parameters under the different target models.
DeepImSeq: Deep image sequencing for unsynchronized cameras

Consider a set of n images of a dynamic scene captured using multiple hand-held devices. The order in which these images are captured is unknown. For n images, there can be n! possible arrangements, which makes this problem extremely challenging. In this work, we address the problem of sequencing such a set of unordered images in its temporal order. We propose an LSTM-based deep neural network which addresses this problem in an end-to-end manner. The network takes the set of images as input and outputs their order of capture. We formulate the problem as a sequence-to-sequence mapping task, in which each image is mapped to its position in the ordered sequence. We do not provide any other information to the network apart from the input images. We show that the proposed approach obtains the state-of-the-art results on the standard dataset. Further, we show through experimental results that the network learns better when the target sequence is reversed.
How Futures Trading Changed Bitcoin Prices

From Bitcoin?s inception in 2009 through mid-2017, its price remained under $4,000. In the second half of 2017, it climbed dramatically to nearly $20,000, but descended rapidly starting in mid-December. The peak price coincided with the introduction of bitcoin futures trading on the Chicago Mercantile Exchange. The rapid run-up and subsequent fall in the price after the introduction of futures does not appear to be a coincidence. Rather, it is consistent with trading behavior that typically accompanies the introduction of futures markets for an asset.
Multi-scale adaptive factors video acceleration magnification

The subtle variations in video may contain some significant information, and the variations may be tiny motion of objects or ones superimposed on large motion. Traditional video magnification methods can only amplify the single micro-motion. The state-of-the-art video acceleration magnification method can handle with linear large motions while still amplifying small changes. However, it still introduces some artifacts or blurring. In this work, we propose a method to mitigate this issue by adopting a magnification factor adaptive strategy, which is based on analyzing the limitation of magnification factor at different scales of the complex steerable pyramid. In this new approach, magnification factors at various scales are set according to the spatial representative wavelengths of each scale. Experiments have been carried out on both synthetic and real videos. Results demonstrate that our method is effective in amplifying tiny motions superimposed on large motion, getting sharper visual quality and mitigating artifacts or blurring.
Using 2048-like games as a pedagogical tool for reinforcement learning

2048-like games are games that have similar properties with 2048, a single-player stochastic sliding puzzle game. 2048-like games are highly suitable for educational purposes due to 2048’s relatively simple rules and its popularity. When using 2048-like games as a tool for machine learning educatio n, these games have the additional benefit of being a well-known topic of research. Numerous machine learning methods have been proposed in the past for 2048, which provides a good opportunity for students to gain first-hand experience in applying these techniques. This paper summarizes the experience of using the game 2584, a 2048-like game, as a pedagogical tool for teaching reinforcement learning and computer game algorithms in 2017. 2584 is similar to 2048, with the only difference being the tiles values are Fibonacci numbers instead of powers of two. A two-player variant was designed to further teach adversarial game techniques. With a class of 33 undergraduate and graduate students, the average win rate for the single-player version of the 2584 reached 96%.
Low Complexity Hierarchical Scheduling for Diverse Datacenter Jobs

Datacenter jobs in a private cloud are often generated by different departments or groups of a business or other organization. In order to reflect the organizational structures of datacenter workloads, it is desirable for the datacenter scheduler to support hierarchical scheduling. The state-of-the-art hierarchical scheduling scheme, hierarchical dominant resource fairness (H-DRF), however, is expensive to implement. Specifically, the worst-case time complexity of H-DRF is O(q <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ), where q is dominated by the number of jobs in the hierarchy, which is a large complexity in a practical large-scale datacenter. In this letter, we design a new online hierarchical fair scheduling scheme, multi-resource collapsed hierarchies (MCH), in the way of converting the hierarchy into a weighted flat tree. MCH takes at most O(q) time and is simple enough to implement in practice. Simulations driven by Google cluster traces show that MCH consumes a nearly sqrt of the total run time of H-DRF, improving significantly in saving the computation time.
Bregman inverse filter

An inverse problem in which the observed signal is produced by passing the original signal through a filter that is derived from a convex minimisation problem is dealt. The filter is available as a black box. It is shown that the Bregman iteration, which is a tool for convex optimisation, can be used to solve this inverse problem. This novel application of the Bregman iteration is demonstrated through successful restoration of the original image from images filtered by a low-pass filter. Theoretical analysis is conducted to explain the inversion process.
Enhancing Perceptual Attributes with Bayesian Style Generation

Deep learning has brought an unprecedented progress in computer vision and significant advances have been made in predicting subjective properties inherent to visual data (e.g., memorability, aesthetic quality, evoked emotions, etc.). Recently, some research works have even proposed deep learning approaches to modify images such as to appropriately alter these properties. Following this research line, this paper introduces a novel deep learning framework for synthesizing images in order to enhance a predefined perceptual attribute. Our approach takes as input a natural image and exploits recent models for deep style transfer and generative adversarial networks to change its style in order to modify a specific high-level attribute. Differently from previous works focusing on enhancing a specific property of a visual content, we propose a general framework and demonstrate its effectiveness in two use cases, i.e. increasing image memorability and generating scary pictures. We evaluate the proposed approach on publicly available benchmarks, demonstrating its advantages over state of the art methods.
The Impact of Electronic Human Resource Management (E-HRM) Strategies on Organizational Innovation by Knowledge Repository as Mediating Role

The current study is intended to provide analysis of the direct and indirect relationships between (E-HRM) strategies and organizational innovation through knowledge repository as a mediation construct. From various previous studies, five (E-HRM) strategies constructs were adopted for this study. These include E- recruitment, e- selection, e-training, e- performance appraisal, and e-compensations, and used the mediating role of a knowledge repository for these constructs to improve organizational innovation. The study applied the smart partial least square (PLS) software to analyse the underlying relationships amongst the most relevant constructs between (E-HRM) strategies, knowledge repositories, and organizational innovation with a total of seven constructs. The results are from top, middle managers (n = 94) working in the Royal Jordanian airline. It was found that there was a strong and statistically positive significant relationship between several (E-HRM) strategies and organizational innovation by using the knowledge repository as a mediation construct.
One-Bit Recursive Least-Squares Algorithm With Application to Distributed Target Localization

Adaptation and learning over low-cost wireless networks, meanwhile keeping an acceptable performance, are well motivated. This paper focuses on online parameter estimation over binary networks, which consist of noisy low-resolution sensors, each only giving coarsely one-bit quantized output observations and transmitting them to a fusion center. We develop a class of recursive least-squares (RLS) algorithms based on an expectation-maximization framework, which realizes adaptive parameter estimation from one-bit observations of the noisy output stream. The developed algorithms are, respectively, derived with and without prior knowledge of the noise variances, and their performances are theoretically and experimentally evaluated. Moreover, it is shown that, although the information contained in the one-bit observations is very limited, the proposed algorithms are comparable to the classical RLS algorithm using the original (nonquantized) observations. In addition, as a practical application, the proposed algorithm combined with array signal processing techniques is applied to bearing-only target localization over wireless sensor array networks, and its effectiveness is verified through simulation experiments.
Additive composition formulation of the iterative Grover algorithm

In the Grover-type quantum search process a search operator is iteratively applied, say, k times, on the initial uniform superposition database state. We present an additive decomposition scheme such that the iteration process is expressed, in the computational space, as a linear combination of k operators, each of which consists of a single Grover-search followed by an overall phase-rotation. The value of k and the rotation phase are the same as those determined in the framework of the search with certainty. We discuss how the additive form can be effectively utilized and we propose an alternative gate that realizes the same outcome as the iterative search.