Reviewerly/exHarmony huggingface dataset:
Research on collaborative filtering recommendation algorithm based on user interest for cloud computing

Aiming to resolve the mobile commerce scenario suggested problems, cloud computing technology and mobile user context are combined to propose a collaborative filtering model based on user interest in mobile scenarios. Through computing the scene similarity based on mobile users, we find similar scenarios constructed target user set current situation and then establish the item scoring scene and scoring matrix. Based on MapReduce, we propose a collaborative filtering recommendation method to realise parallel recommendation.
On Receding Horizon Chance Constraint Motion Planning for Uncertain Multi-Agent Systems

Abstract We propose and study a motion planning algorithm for multi-agent autonomous systems to navigate through uncertain and dynamic environments. We use a receding horizon chance constraint framework that allows for tuning the trade-off between the risk of collision and the infeasibility of paths. We consider sampling-based incremental planning algorithms and extend them to the case of multiple agents and dynamic and uncertain environments. The receding horizon control framework is used to incorporate sensor measurements at a fixed interval of time to reduce uncertainty about agents’ state and environment. Our presentation focuses on rapidly-exploring random trees (RRTs) and the assumption of Gaussian noise in the uncertainty model. Our algorithm is illustrated using several examples.
From Live Music to Electronic Offerings

Distribution of music via recordings and broadcasts has been a lively activity for well over a century. The value for music is immense, but this is a symbiotic process, where the musical demands spawned the invention of electronic amplifiers, microphones, speakers, and onward to all modern electronics. The original aim was to make a faithful recording of a performance. In reality, this is impossible because the conditions for listening are always different from the original performance. The musical data and reproduction are modified by every aspect of the electronics, and the way in which sound engineers and marketing companies handle the music. There may be advantages in that performance errors can be corrected, balance between instruments adjusted, or the pop music autotune which corrects the pitch. This chapter considers many aspects of current and future sound processing.
Artificial Neural Network (ANN) and Regression Model for Predicting the Albumin to Globulin (A/G) Ratio in a Serum Protein Electrophoresis Test

Multiple myeloma affects the several parts of bodies such as the spine, skull, pelvis and ribs. The cause of multiple myeloma is not known properly. The poor prognoses is associated with most cancers creates a sense of urgency for the brains behind healthcare Artificial Intelligence (AI) research. AI is able to detect cancer and other diseases earlier than possible through standard diagnostic methods, which could be lifesaving for future patients. The main objective of the research paper is to predict the Albumin to Globulin (A/G) ratio obtained by the electrophoresis test by developing regression model and Artificial Neural Network (ANN) model. The results obtained showed that the Mean Square Error (MSE) obtained by ANN model is less than the MSE obtained by the regression model.
Enhanced electromagnetic swarm yields better optimisation

Swarm intelligence has been one of the leading techniques used by researchers worldwide for optimisation. In this paper, the fine tuning of the update equations for the swarm are done based on linkage of particle motion with a electromagnetic field and also under the influence of strategic delays. The motion of a particle in a search space is confined to free space in general, however if restricted the solution under the envelope of a magnetic field, the algorithm better converges within a electromagnetic field. Simulation studies have been performed on the triple inverted pendulum case study which showed that stability was achieved with ease when compared to classical methods of control.
The impact of knowledge management on firm performance: direct impact vs. the mediating impact of strategic human resource practices: an empirical case study

The objective of this paper is to investigate the impact of knowledge management (KM) on firm performance both directly and via the mediating effect of strategic human resource practices in National Iranian Drilling Company (NIDC) as an empirical case study. Structural equation modelling (SEM) method is used to test the hypotheses on a sample of 256 employees at the NIDC. The results indicate that KM influences firm performance both directly and via the mediating effect of strategic human resource practices including staffing, training, participation, performance appraisal and compensation.
Theoretical-methodological bases of the creative thinking research: constructivist paradigm

Creative thinking is considered in the article as a process of a problem situation solving, and the means of its solving subject does not have, and he is forced to search for them outside of the given situation. It is stated that going beyond, forcing the subject to engage in a wider situation and to know it more deeply, serves as his creative thinking development incentive. Basing on the modern neoclassical theories of thinking analysis, it is proved that in the constructivist paradigm the mechanisms of creativity must be sought in the mental system structural components’ interconnections. In the context of this paradigm, each structural component of the mental system is regarded as being constructed, making significant changes within the system, created by its interconnections with other components. Each component of the mental system is constructed, including all the components of this system. It does not only change itself, but also determines the change of the whole mental system.This is proved in the article by the reference to the modern theories (O.Tikhomirov, D. Kahneman, Lisa F. Barrett), in which thinking is regarded as a systemic formation in which each of its components is constructed by interconnections with other mental formations.Creative thinking is also considered in the article as a subject-object relation, which includes understanding the content of the task (problem) by the subject; assessing the significance of the problem for the subject; its focus on finding new solutions of the task. In this regard, according to the traditions of native psychology, the following components in the model of creative thinking are distinguished: cognitive, affective and conative.The article presents a three-component structural-functional model of creative thinking, which focuses the analysis of the creativity of the subject on the identification of the composition and structure of the thinking system in order to clarify the specific content of the structural components included in this system, as well as to determine the hierarchy of mental phenomena that determine their configuration in a particular activity. Depending on the peculiarities of the mental system’s structural components composition and structure, we can observe and measure certain external manifestations of the subject's creativity in an activity.
Trajectory allocation algorithm for the positioning of multi-agent systems (MAS)

A multi-agent system, conformed by differential mobile robots, can execute many tasks. An example is the positioning of mobile robots in order to represent a 2D formation on the ground that represents a geometric shape. In this application, the mobile robots move to a position assigned by an algorithm. This algorithm assigns the 2D position that each mobile robot must achieve. This paper presents a methodology that defines seven criteria necessaries to compute a good 2D position assignation. Those criteria are based on the unweighted Euclidean distances between the robot’s location and the desired position. They are also evaluated in order to select the criterion that allows all robots in the multi-agent system to move the shortest distance when performing a geometric representation. This means a reduction in the length of the path required by each mobile robot to complete the assigned task.
Free-form surface measurement based on fringe reflection

This paper describes the principles and methods of free-form Surface measurement which is based on fringe reflection technique (PMD). This technique is based on incoherent imaging and phase-shfit. CCD camera was used to record images of sinusoid fringes pattern which is generated by computer monitor and reflected respectively by reflector tested. The phase of modulated fringes that test the mirror collected by CCD can be obtained through the phase-shifting algorithm, and the phase of the reference mirror can be calculated according to the structure, so the altitude difference between the two surface shape mentioned above can be obtained by the phase difference between them. The experiment fit the tested surface by 36 zernike polynomial and substitute the gradient data into equations to obtain the measured surface shaped by the least squares solution.
Generating Customizable Natural Language Descriptions

In the Natural Language Generation field, the task of Reference Expression Generation (REG) consists of selecting the semantic content that should compose the linguistic description of a discourse object, as in `the man in black' or `the boy in the centre'. REG algorithms tend to use predefined parameters to model qualitative and quantitative aspects of the description to be generated, and are often difficult to adapt to new domains or applications. In addition, obtaining linguistic examples in all possible reference situations is also often impracticable, which limits the use of machine learning approaches in this task. Based on these observations, this work proposes an extension of a standard REG algorithm, in which certain aspects of a reference strategy are customized without necessarily resorting to training data. The proposal was tested by making use of three REG domains, and its results compared favourably against a standard REG approach.
Strategic foresight and auditor's cognitive contribution: the study of cognitive mapping

This research allows acquiring a better understanding of the strategic prospective of the auditor in the accounting audit mission, in which the emphasis is placed on the auditor mind and forward thinking. The analysis of the cognitive approach and the prospective strategy of the auditor using the cognitive mapping allow identifying the factors that enable the auditors to reduce the cognitive problems in their strategy. This paper provides new insights into the cognitive role of the auditors and their strategic foresight. Practitioners and researchers can use the findings of this study to better understand the success audit factors. Moreover, auditing firms may use the findings of this study to improve their foresight audit strategy.
Implementation of an inbound corresponding smartphone application using markerless image processing augmented reality technology

We have developed an inbound corresponding smartphone application based on markerless image-processing augmented reality technology for use by zoo visitors and staff. On this application, we implemented an animal quiz distribution function and an animal character hunting function. We also implemented a web system on which the administrator can update the contents handled by these functions in real time. The proposed application negates the need for newly installing multilingual guide boards for foreign zoo visitors. Moreover, the web system enables the real-time updates of the contents used in smartphone applications. Here we confirmed the operability, relevance, readability, applicability, and effectiveness of the mobile application and content management web system in a questionnaire survey of 57 zoo visitors and 14 zoo staff. The survey results of all five measures revealed an overwhelmingly positive response to our mobile application and content management web application.
Florid or Virtuoso Études

Most of the music in <italic>The Classical Guitar Companion</italic> makes use of the same technique or musical texture throughout. High-level virtuoso playing requires that guitarists become adept at navigating ever-changing musical textures and the techniques required to produce them. Florid or virtuoso études present the challenges of combining and switching between various technical elements, such as arpeggios, scales, slurs, and shifts, at rapid <italic>tempi</italic>. Of special interest is the brief discussion of “latency” at high speeds, which is applicable to these studies, and how virtuoso players transcend the limits of the central nervous system when initiating a movement or series of movements that must occur in less time than it takes for the signal to move to get from the brain to the hands (100 milliseconds).
Formación Docente y TIC. Caracterización de los Estudiantes de Educación Primaria

This article presents and discuss the results achieved through a research process that seeks to characterize the students of a primary school teacher in the local context and their relationship with information and communication technologies in their daily life and in the academic training. Bearing in mind that a potential space for the professional practice of the teaching practice of these students is the province of Rio Negro, which stands out in the context of Argentina for its trajectory and development of policies for the inclusion of ICT in Education. In particular at the primary level, the Aulas Digitales Moviles program is being carried out, and in this sense we understand that it is of interest to know the characteristics of future teachers in relation to ICT training that allow the design of more related educational proposals. The results achieved allow defining a profile of a mostly young teacher training student with a predominance of female sex, self-perceived as good users of ICT in their daily work but not for the development of academic life. Thus, it is a challenge for those who assume the training of trainers to be able to advance in the design of educational proposals that promote in students the development of critical skills for the pedagogical integration of ICT in the classroom.
Salient Region Guided Deep Network for Violence Detection in Surveillance Systems

Abstract: It is significant to detect violent actions in video surveillance systems automatically, for example, bus stands, malls and railway stations. Though, the earlier detection techniques generally extract statistic features around the spatiotemporal interest points or extract descriptor in the regions where movement takes place, leading to limited abilities to successfully detect violence activities in video surveillance systems. To solve this problem, a new approach for the automatic detection of violence in video surveillance systems is proposed in this paper. Our proposed algorithm first extracts salient regions in the frames using PFT and Temporal PFT; salient regions may have a possible candidate region of violence. Then these salient region images are fed to the pre-trained deep networks to extract features and these extracted features are fed to the AdaBoost Support Vector Machine classifier for detection of whether the image contains any violent candidate or not. Experimental analysis on the two challenging standard datasets validates that the method proposed in this paper is better than the previous methods. Keywords: AdaBoost support vector machine, CNN, deep networks, PFT, Temporal-PFT Cite this Article: Gajendra Singh, Arun Khosla, Rajiv Kapoor. Salient Region Guided Deep Network for Violence Detection in Surveillance Systems. Journal of Computer Technology & Applications. 2019; 10(3): 19–28p.
A BRIEF UNDERSTANDING OF ORGANIZATIONAL AMBIDEXTERITY AND DYNAMIC MANAGERIAL CAPABILITIES, AND HOW THEY RELATE?

The concept of organizational ambidexterity and dynamic managerial capabilities have raised researchers’ interest. Based on previous studies, this paper aims to provide a simple understanding of those two concepts, so that everyone from diverse backgrounds can easily capture the ideas of these concepts. In addition, the clear explanation of the relationship between dynamic managerial capabilities and organizational ambidexterity also provided. In short, Ambidexterity is defined as the need for the firm to achieve a balance between explore and exploit (He and Wong, 2004; O’Reilly, 2013) and the responsibility to manage both lays on the TMTs. On the other hand, Dynamic managerial capabilities emphasize the important role of managers or leaders to sense, to seize, and to reconfigure organizational skills and resources to match with changing the environment (Eisenhardt and Martin, 2000; Teece et al., 1997). TMTs dynamic managerial capabilities influence their ability to sense opportunities for ambidexterity and seize them through combining, integrating and reconfiguring exploitative and explorative resources and capabilities. Several studies have provided several examples of these two concepts are related. For instance, TMTs’ human capital describe the knowledge, education, experience, and skills of the TMTs, then logically, the TMTs that have rich working experience will be able to manage the resources for exploitative and explorative activities in the better system (Heavey, 2010).
Positiv – Negativ

The motif “positive – negative” is virtually constitutive for musical and visual post-war art that took shape after 1950 within Europe and America and is exemplified here on the basis of compositions by Stockhausen, Cage, and Feldman, and for visual art by the artistic movement ZERO. Within the philosophical and aesthetic discussions surrounding such works, the defining common thread centered on what was missing, on what was not there. While silence primarily functions as the negative in music after 1950, the space that surrounds a tangible object, while also being the sole condition for its embodiment, serves this function for ZERO art. Thus, instances of nothingness itself become integral parts of these works of art.
Determinants of Firms Innovation and the role of R&amp;D Investment and Training: An Empirical evidence from Tunisian SMEs

The article aims to examine the determinants of firms' innovation in Tunisia. Following changes in the business world, companies over the world are increasingly including innovation as a strategy to ensure business expansion. Using the World Bank enterprise data-survey to test the correlation between two variables, the determinants of innovation and innovation were obtained, by applying a logit and probit regression approach. The findings showed that R&D investment with other firms, training, and sector variables are an important determinant of innovation. It was however established by the study that the firms' age, size and employee variables negatively affect the chances of innovation. Equally, it was found that the same factors (investing in R&D at home, formal training) were the significant determinants of product, process, organisational, marketing or logistic innovation. Thus, the policy implications of the results recommend that firms should make significant factors as the priorities to boost innovation.
Model-driven development of self-adaptive multi-agent systems with context-awareness

Self-adaptive systems are complex and operate in dynamic and heterogeneous environments. They have to dynamically modify their behaviour at run-time in response to different kinds of changes. This paper presents a methodology to develop context-aware self-adaptive systems by employing the model driven architecture (MDA) and agent-oriented technology advantages. The approach aims to combine these two promising technologies to overcome the complexity of developing such systems. The methodology focuses on the key issues in the analysis and design of self-adaptive multi-agent systems. Different abstraction levels based on MDA has been proposed and mappings between models in these levels provided. These mappings bridge the gap between the high-level models produced in computation independent (CIM) and platform independent models (PIM) as well as the low-level models based on specific implementation platform called SADE (Self-adaptation Development Environment). The proposed approach has been evaluated through a case study described in the paper.
Assessing Quality of Web User Interfaces Using Domain Ontology

User interface (UI) development sees the growing need for auto-assessment of UI quality attributes, such as usability, accessibility, HTML and CSS correctness, aesthetic attractiveness for target users, complexity and clutter, trustworthiness, etc. The two mainstream approaches in the field are analysis of HTML/CSS code and mining of webpage visual representation. The number of related algorithms and tools is already enormous and it continues to grow rapidly – so there's the need for structured representation of this dynamic domain. In the paper we design and implement OWL ontology of web UI quality assessment. First, we provide conceptualization of UI and the related concepts, based on the existing research works and standards, and classify them into groups. Then we design the ontology, whose core is the classes related to UI attributes, metrics, and existing services, which are used to calculate the metrics. Finally, we outline the process of building the ontology in OWL, and provide rationale for its feasibility in evaluating and improving modern web UIs.
Exploring Automation in Proofs of Attribute-based Encryption in the Standard Model

Motivated by the complexity of cryptographic proofs, we propose methods to automate the construction and verification of cryptographic proofs in the standard model. Proofs in the standard model (as opposed to the random oracle model) are the gold standard of cryptographic proofs, and most cryptographic protocols strive to achieve them. The burgeoning complexity of cryptographic proofs implies that such proofs are prone to errors, and are hard to write, much less verify. In this paper, we propose techniques to generate automated proofs for attribute-based encryption schemes in the standard model, building upon a prototype tool, AutoG&P due to Barthe et al. In doing so, we significantly expand the scope of AutoG&P to support a rich set of data types such as multi-dimensional arrays, and constructs commonly used in cryptographic protocols such as monotone-access structures, and linear secret-sharing schemes. We also provide support for a extended class of pairing-based assumptions. We demonstrate the usefulness of our extensions by giving automated proofs of the Lewko et al. attribute-based encryption scheme, and the Waters' ciphertext-policy attribute-based encryption scheme.