Reviewerly/exHarmony huggingface dataset:
Four research pathways for understanding the role of smart technologies in accounting

Purpose This paper aims to study the role of smart technologies (e.g., artificial intelligence, Internet of Things, blockchain and analytics, among others) in the accounting environment (AE). In this context, the nuances of innovation generated by such technologies allow for tracing the merging trends in accounting research. Design/methodology/approach This paper uses an integrated qualitative methodology composed of structured literature analysis and systematic literature analysis to study scientific papers published and stored in prominent databases from 2000 to 2020. This paper collected a data set sharing topics related to smart technologies and innovation in the AE. Findings The primary findings reveal four research paths of innovation, impact, implication and intelligence in accounting research as follows: smart technologies as innovations to be managed; smart technologies as impacting tools affecting the AE in certain circumstances; smart technologies as a source generating relevant implications; and smart technologies as factors requiring new and updated knowledge, skills and abilities of actors. Originality/value The joint investigation of the AE and smart technologies poses a milestone for future academic and professional accounting research. This paper proposes a new framework (SMATECHacc Framework) consisting of four pathways research that can be used by future researchers to consider and construct their own research designs.
Considerations for implementing electronic laboratory notebooks in an academic research environment

As research becomes predominantly digitalized, scientists have the option of using electronic laboratory notebooks to record and access entries. These systems can more readily meet volume, complexity, accessibility and preservation requirements than paper notebooks. Although the technology can yield many benefits, these can be realized only by choosing a system that properly fulfills the requirements of a given context. This review explores the factors that should be considered when introducing electronic laboratory notebooks to an academically focused research group. We cite pertinent studies and discuss our own experience implementing a system within a multidisciplinary research environment. We also consider how the required financial and time investment is shared between individuals and institutions. Finally, we discuss how electronic laboratory notebooks fit into the broader context of research data management. This article is not a product review; it provides a framework for both the initial consideration of an electronic laboratory notebook and the evaluation of specific software packages. This review explores factors to consider when introducing electronic laboratory notebooks, including discussion of integration with research data management and the functionalities to compare when evaluating specific software packages.
A systematic review of homomorphic encryption and its contributions in healthcare industry

Abstract Cloud computing and cloud storage have contributed to a big shift in data processing and its use. Availability and accessibility of resources with the reduction of substantial work is one of the main reasons for the cloud revolution. With this cloud computing revolution, outsourcing applications are in great demand. The client uses the service by uploading their data to the cloud and finally gets the result by processing it. It benefits users greatly, but it also exposes sensitive data to third-party service providers. In the healthcare industry, patient health records are digital records of a patient’s medical history kept by hospitals or health care providers. Patient health records are stored in data centers for storage and processing. Before doing computations on data, traditional encryption techniques decrypt the data in their original form. As a result, sensitive medical information is lost. Homomorphic encryption can protect sensitive information by allowing data to be processed in an encrypted form such that only encrypted data is accessible to service providers. In this paper, an attempt is made to present a systematic review of homomorphic cryptosystems with its categorization and evolution over time. In addition, this paper also includes a review of homomorphic cryptosystem contributions in healthcare.
Adaptive cognitive fit: Artificial intelligence augmented management of information facets and representations

Explosive growth in big data technologies and artificial intelligence [AI] applications have led to increasing pervasiveness of information facets and a rapidly growing array of information representations. Information facets, such as equivocality and veracity, can dominate and significantly influence human perceptions of information and consequently affect human performance. Extant research in cognitive fit, which preceded the big data and AI era, focused on the effects of aligning information representation and task on performance, without sufficient consideration to information facets and attendant cognitive challenges. Therefore, there is a compelling need to understand the interplay of these dominant information facets with information representations and tasks, and their influence on human performance. We suggest that artificially intelligent technologies that can adapt information representations to overcome cognitive limitations are necessary for these complex information environments. To this end, we propose and test a novel *Adaptive Cognitive Fit* [ACF] framework that explains the influence of information facets and AI-augmented information representations on human performance. We draw on information processing theory and cognitive dissonance theory to advance the ACF framework and a set of propositions. We empirically validate the ACF propositions with an economic experiment that demonstrates the influence of information facets, and a machine learning simulation that establishes the viability of using AI to improve human performance.
A critical analysis of the integration of blockchain and artificial intelligence for supply chain

The integration between blockchain and artificial intelligence (AI) has gained a lot of attention in recent years, especially since such integration can improve security, efficiency, and productivity of applications in business environments characterised by volatility, uncertainty, complexity, and ambiguity. In particular, supply chain is one of the areas that have been shown to benefit tremendously from blockchain and AI, by enhancing information and process resilience, enabling faster and more cost-efficient delivery of products, and augmenting products' traceability, among others. This paper performs a state-of-the-art review of blockchain and AI in the field of supply chains. More specifically, we sought to answer the following three principal questions: Q1-What are the current studies on the integration of blockchain and AI in supply chain?, Q2-What are the current blockchain and AI use cases in supply chain?, and Q3-What are the potential research directions for future studies involving the integration of blockchain and AI? The analysis performed in this paper has identified relevant research studies that have contributed both conceptually and empirically to the expansion and accumulation of intellectual wealth in the supply chain discipline through the integration of blockchain and AI.
Electronic speckle pattern interferometry in long wave infrared: a new technique for combining temperature and displacement measurements: application in thermo-mechanical assessment of structures

Holographic and speckle based techniques are well known for measuring full-field displacements and performing non destructive testing on solid objects [1]. The measurement range and accuracy of these techniques are related to the wavelength of the laser. In visible light they are often not well suited for field applications or for large displacement measurement due to the short wavelength used, which imposes high stability constraints. One way to decrease this sensitivity is to use a longer wavelength. Our purpose is to investigate holography in the Long Wave InfraRed (LWIR) range and more specifically at 10 μm with CO2 lasers. This provides a typical 20 factor of decrease of the stability requirements; meantime the range of measurement is increased by the same factor. We present here advanced results obtained within the FANTOM FP7 project. Besides the lower sensitivity to external perturbations, another interesting feature that is put forward in this project is the possibility to develop a sensor which combines displacement by holography/speckle and thermography measurements. Here we take advantage to the fact that the necessary observation device for the holographic signal is a thermographic camera. This has an interest in various applications such as analysis of thermo-mechanical behaviour of structures or non destructive testing, where often displacements and temperature fields need to be observed and correlated one to another. We already presented preliminary results on out-of-plane and in-plane ESPI at 10.6 μm, and also on digital holographic interferometry [2], however without combining thermography. Recently we presented an improved digital holographic interferometry set-up [2], and a study of the scattering problems arising when working at such long wavelengths [3]. In this paper we present for the first time to our knowledge the combination of full-field temperature and displacements, with a single sensor.
A GALS Pipeline DES Architecture to Increase Robustness against CPA and CEMA Attacks

Side channels attacks (SCAs) are very effective and low cost methods to extract secret information from supposedly secure cryptosystems.The traditional synchronous design flow used to create such systems favors the leakage of information, which enables attackers to draw correlations between data processes and circuit power consumption, electromagnetic radiation or other sources of leakage. By using well known analysis techniques, these correlations may allow that an attacker retrieves secret cryptographic keys. Differential Power Analysis (DPA) and Differential Electromagnetic Analysis (DEMA) are among the most cited attack types. More accurate types of attacks have been proposed, including Correlation Power Analysis (CPA) that associates power quantities with a specific power model. In recent years, several countermeasures against SCAs have been proposed. Fully asynchronous and globally asynchronous locally synchronous (GALS) design methods appear as alternatives to design tamper resistant cryptosystems. However, according to previous works they use to achieve this with significant area, throughput, latency and power penalties and are not absolutely secure. This paper proposes a new GALS pipeline architecture for the Data Encryption Standard (DES) that explores the trade-off between circuit area and robustness to SCAs. Robustness is enhanced by replicating the DES hardware structure in asynchronously communicating module instances, coupled with self-varying operating frequencies. Designs prototyped on FPGAs with the proposed technique presented promising robustness against attacks, after submitted to differential and correlation analyses. This is true for both power and electromagnetic channels. Additionally the proposed architecture displays throughput superior to previously reported results.
Logic-Oriented Methods for Structuring in the Context of Lawmaking

With the transition from a text culture to a machine culture, the language changes, too. The language of the machine culture is the formal logic that is adequate for the machine, but not in the same way for people in their everyday language usage. In the mainstream of greater rationalisation, logic is increasingly used in legislation, especially allowing only correct interpretations. However, logic is not the only instrument which can be used to shape and improve legislative rationality. In the neighbourhood of logic there are further methods which can find application in structuring legislative texts. We propose to supplement legislative documents ex ante with explicit logic-oriented information which is relevant to ontologies and taxonomies. This information in a form of a mini-thesaurus can already be used in ex ante legislative procedure, and should not be added only in the ex post analysis of legal documentation.
The Limitations of Optimization from Samples

In this article, we consider the following question: Can we optimize objective functions from the training data we use to learn them? We formalize this question through a novel framework we call optimization from samples ( OPS ). In OPS , we are given sampled values of a function drawn from some distribution and the objective is to optimize the function under some constraint. While there are interesting classes of functions that can be optimized from samples, our main result is an impossibility. We show that there are classes of functions that are statistically learnable and optimizable, but for which no reasonable approximation for optimization from samples is achievable. In particular, our main result shows that there is no constant factor approximation for maximizing coverage functions under a cardinality constraint using polynomially-many samples drawn from any distribution. We also show tight approximation guarantees for maximization under a cardinality constraint of several interesting classes of functions including unit-demand, additive, and general monotone submodular functions, as well as a constant factor approximation for monotone submodular functions with bounded curvature.
Unconditionally secure quantum coin flipping

Quantum coin flipping (QCF) is an essential primitive for quantum cryptography. Unconditionally secure strong QCF with an arbitrarily small bias was widely believed to be impossible. But basing on a problem which cannot be solved without quantum algorithm, here we propose such a QCF protocol, and show how it manages to evade all existing no-go proofs on QCF.
What role can the Internet play in the development of democracy in Africa?

This article explores the recent trends in information technology, specifically the Internet,and what role it can play in the development and sustainability of democracy in Africa.It examines what role it can play in revitalising the public sphere and how it can influencepolitical decisions in the continent. However, I argue that even though the Internet hashad profound effects on people’s lives, contributing significantly to communication andinformation sharing, its real potential is yet to be realised in Africa. This means in effect,that although it might have contributed to various sociological phenomena, it couldpotentially be dangerous to the growth of democracy in Africa because it is still in thehands of a few, especially those in power.120 Communicare 23(1) - July 2004George
Modelling a Complex Human Centre Queuing System for Enhancing the Capability of Agent Based Simulation

Agent Based Simulation (ABS) is a simulation technique that emerged after Discrete Event Simulation (DES). The design of ABS is based on artificial intelligence using the concept of robotics and multi-agent systems (MAS). The agent based model consists of a set of interacting active objects that reflect objects and relationships in the real world. Technically, every agent has its own thread of execution to represent its own histories, intentions, desires, individual properties, and complex relationships. ABS is found suitable to model people centric systems as compared to traditional DES. People centric systems are systems that involve with many human interactions and where the actors work with some degree of autonomy. However due to the MAS structure, agents in ABS are decentralized. As such, modeling people centric system’s features such as people queuing in ABS is found difficult. Addressing the aforementioned issue, we propose to enhance the capability of ABS for modelling human centric queuing system by combining DES approach in ABS model called hybrid ABS/DES model.
Pixel-Vernier: A General Image-Based Approach For Particle Size Distribution Estimation

Particle size distribution estimation (PSDE) is a fundamental task for heterogeneous materials characterization and modeling. This paper presents a general image-based approach for PSDE, which is called collectively “Pixel-Vernier” or PV for short. Meaningful image segmentation is the main problem to be solved for image-based PSDE. To this end, the proposed approach combines markers-controlled watershed segmentation with a clustering algorithm to solve the delineation of the boundaries of the particles. The combined approach is embedded in a coarse-to-fine strategy using a one training parameter to adapt the algorithm to the underlying distributions of the particle size. This training parameter is restricted to the size of an averaging filter. PV decomposes the image into separate particle regions. The final results of these regions are used to compute several geometric attributes for particles such as the semi-major axis, the semi-minor axis, and the equivalent diameter. Then, the geometric attributes of all the particles are used to estimate size distribution and relevant statistics. PV can be used in a laboratory as well as in a field setting. It is tested successfully on a diverse set of images that represent materials like soils, texture, rocks, and Mars surface geology.
Vocativo slavo e formazione di alterati: casi di reinterpretazione categoriale e convergenza formale

In the Slavic languages, in which the vocative case is an unstable category (Polish, Serbian-Croatian, Macedonian, Bulgarian), the explicit vocative mark is better preserved with altered nouns, like diminutives and pejoratives. Taking this as the starting point, the paper aims at verifying whether the semantic and functional “attraction” between vocative and diminutives/pejoratives affects the formal level too, i.e. whether there are points of contact between case morphology and word formation strategies. The analysis of Polish and Bulgarian vocative forms has revealed that these two domains intersect as follows: 1) vocative case endings are reinterpreted as lexical formants; 2) the formation strategies of vocative case endings and altered nouns tend to converge.
On the Commutativity of States in von Neumann Algebras

Abstract The notion of commutativity of two normal states on a von Neumann algebra was defined some time ago by means of the Pedersen–Takesaki theorem. In this note, we aim at generalising this notion to an arbitrary number of states, and obtaining some results on so defined joint commutativity. Also relations between commutativity and broadcastability of states are investigated.
Streamlined Workflow for 3D Modeling with Animated Characters

With the proliferation of computer graphics and multimedia technology, there are abundant choices of three-dimensional (3D) modeling and character animation professional software in the market. However, authoring using different software products collectively still remains a difficult task considering the distinct features of proprietary software artifacts. The main purpose of this paper is to propose a streamlined workflow aiming at performing the 3D modeling construction with animated characters. As the concept of Wikinomics emerges, open source based software and products are utilized to provide the maximum collective throughput potential. The proposed SketchUp and MikumikuDance workflow (SUMD) introduces the novel method for plentiful of potential applications in light of the augmented capabilities of the integrated process. The goal is to assist professional users associated with different domains and sustain their high enthusiasm levels during the modeling process. Rather than manipulating more than one software products with incompatible properties, the workflow users will be guided through the challenging process to complete their 3D construction with animated characters in the proposed SUMD workflow to create potentials for more future application use.
Non-parametric Latent Modeling and Network Clustering

The paper exposes a non-parametric approach to latent and co-latent modeling of bivariate data, based upon alternating minimization of the Kullback–Leibler divergence (EM algorithm) for complete models. For categorical data, the iterative algorithm generates a soft clustering of both rows and columns of the contingency table. Well-known results are revisited, and new procedures are presented. In particular, the consideration of square contingency tables induces a clustering algorithm for weighted networks, differing from spectral clustering or modularity maximization techniques. Also, we present a novel co-clustering algorithm, distinct from the Baum–Welch algorithm, applicable to HMM models for unrestricted bigrams counts. Three case studies illustrate the theory.
The Extended Bag of Words Model for Visual Recognition and Categorization

With the development of science and technology, more and more images need to be recognized and categorized. Although the classical Bag of Words (BoW) model has played a great role in the past, there are still many limitations about it, i.e. low precision and accuracy, high complexity of computation, etc. In this paper, it is improved and extended from four ways. Firstly, the features filtered from the background are sampled to reduce the influence of background noise. Secondly, the spatial relationship among all features is integrated with the classical BoW vector to improve the accuracy of recognition and categorization. Thirdly, vocabulary tree is constructed by applying hierarchical K mean value, in order to obtain more reasonable vocabulary list and greatly reduce the clustering time. Fourthly, a weighted visual word histogram is considered, in order to stand out the essential difference among images. At last, some experiments are conducted to show the advantage of the proposed method.
The Relationship Between Pupillary Changes and Subjective Indices to the Content of Television Programs

It is possible to evaluate the viewer’s interest in visual information using pupillary changes caused by mental activity. This paper examines the possibility of estimating viewer’s interest and enjoyment of TV programs by measuring dynamic pupillary changes, blinking, and subjective interest responses. The primary factors for pupillary changes are derived from the evaluation of images of TV programs, using questionnaires that are based on the SD method. The results show, during dynamic evaluation, that there is a relationship between pupillary changes and subjective interest response. In evaluating images from TV programs, there is a significant difference in pupil size between the two groups with higher and the lower factor scores for “Potency, and a difference in the rate of blinking between these two groups with higher and the lower factor scores for “Activity. There is also a significant correlation between subjective interest response and all three factors.
JRIF: Reactive Information Flow Control for Java

A reactive information flow (RIF) automaton for a value v specifies (i) restrictions on uses for v and (ii) the RIF automaton for any value that might be derived from v. RIF automata thus specify how transforming a value alters restrictions for the result. As labels, RIF automata are both expressive and intuitive vehicles for describing allowed information flows. JRIF is a dialect of Java that uses RIF automata for specifying information flow control policies. The implementation of JRIF involved replacing the information flow type system of the Jif language by a RIF-based type system. JRIF demonstrates (i) the practicality and utility of RIF automata, and (ii) the ease with which an existing information flow control system can be modified to support the expressive power of RIF automata.