On cross-domain social semantic learning

Approximately 2.4 billion people are now connected to the Internet, generating massive amounts of data through laptops, mobile phones, sensors and other electronic devices or gadgets. Not surprisingly then, ninety percent of the world's digital data was created in the last two years. This massive explosion of data provides tremendous opportunity to study, model and improve conceptual and physical systems from which the data is produced. It also permits scientists to test pre-existing hypotheses in various fields with large scale experimental evidence. Thus, developing computational algorithms that automatically explores this data is the holy grail of the current generation of computer scientists. Making sense of this data algorithmically can be a complex process, specifically due to two reasons. Firstly, the data is generated by different devices, capturing different aspects of information and resides in different web resources/ platforms on the Internet. Therefore, even if two pieces of data bear singular conceptual similarity, their generation, format and domain of existence on the web can make them seem considerably dissimilar. Secondly, since humans are social creatures, the data often possesses inherent but murky correlations, primarily caused by the causal nature of direct or indirect social interactions. This drastically alters what algorithms must now achieve, necessitating intelligent comprehension of the underlying social nature and semantic contexts within the disparate domain data and a quantifiable way of transferring knowledge gained from one domain to another. Finally, the data is often encountered as a stream and not as static pages on the Internet. Therefore, we must learn, and re-learn as the stream propagates. The main objective of this dissertation is to develop learning algorithms that can identify specific patterns in one domain of data which can consequently augment predictive performance in another domain. The research explores existence of specific data domains which can function in synergy with another and more importantly, proposes models to quantify the synergetic information transfer among such domains. We include large-scale data from various domains in our study: social media data from Twitter, multimedia video data from YouTube, video search query data from Bing Videos, Natural Language search queries from the web, Internet resources in form of web logs (blogs) and spatio-temporal social trends from Twitter. Our work presents a series of solutions to address the key challenges in cross-domain learning, particularly in the field of social and semantic data. We propose the concept of bridging media from disparate sources by building a common latent topic space, which represents one of the first attempts toward answering sociological problems using cross-domain (social) media. This allows information transfer between social and non-social domains, fostering real-time socially relevant applications. We also engineer a concept network from the semantic web, called semNet, that can assist in identifying concept relations and modeling information granularity for robust natural language search. Further, by studying spatio-temporal patterns in this data, we can discover categorical concepts that stimulate collective attention within user groups.Includes bibliographical references (pages 210-214)

Positive Outcomes of Human Resources Engagement and Impact on Motivation

For this study, I don’t intend to show teachers as victims of their school, nor that Human Resources is the only problem that needs to be fixed or that our education system is the issue. We only intended to question why teachers are always blamed, and their needs are ignored and always accused them of being demotivated. We mean to question how the education system functions with the lack of Human Resources practices and the methods and ideas that we can provide and help our teachers have a better future. We intend to discover what the best way to motivate and engage teachers through Human Resources practices is. What makes the admins dissatisfied with teachers’ performance, and is it the fault of the teachers. This study is a series of concerns and problems teachers (including ourselves) came across through our teaching years that nobody ever tried to see it from our point of view. This article is a group of chains and ideas that will give more value to teachers and encourage Human Resources to be more engaged and active in teachers lives through many methods and techniques. Furthermore, teachers’ demotivation and lack of engagement are causing burnouts and turnovers; we’ll try to show how Human Resources can help reduce these turnovers and burnouts through being more present and implement motivational systems and engagement models. This article will review previous literature related to Human Resources engagement and motivation positivity on teachers’ performance and productivity. It will discuss these demotivating factors and assess their impact on teachers’ performance and end with. This article will conclude by implementing more motivational and engagement systems and programs to enhance teachers performance, reduce turnovers, and make schools a better environment for students

Controller tuning by means of evolutionary multiobjective optimization: current trends and applications

Control engineering problems are generally multi-objective problems; meaning that there are several specifications and requirements that must be fulfilled. A traditional approach for calculating a solution with the desired trade-off is to define an optimisation statement. Multi-objective optimisation techniques deal with this problem from a particular perspective and search for a set of potentially preferable solutions; the designer may then analyse the trade-offs among them, and select the best solution according to his/her preferences. In this paper, this design procedure based on evolutionary multiobjective optimisation (EMO) is presented and significant applications on controller tuning are discussed. Throughout this paper it is noticeable that EMO research has been developing towards different optimisation statements, but these statements are not commonly used in controller tuning. Gaps between EMO research and EMO applications on controller tuning are therefore detected and suggested as potential trends for research.The first author is grateful for the hospitality and availability of the UTC at the University of Sheffield during his academic research stay at 2011; especially to Dr. P.J. Fleming for his valuable comments and insights in the development of this paper. This work was partially supported by Grant FPI-2010/19 and project PAID-2011/2732 from the Universitat Politecnica de Valencia and projects TIN2011-28082 and ENE2011-25900 from the Spanish Ministry of Economy and Competitiveness.Reynoso Meza, G.; Blasco Ferragud, FX.; Sanchís Saez, J.; Martínez Iranzo, MA. (2014). Controller tuning by means of evolutionary multiobjective optimization: current trends and applications. Control Engineering Practice. 28:58-73. https://doi.org/10.1016/j.conengprac.2014.03.003S58732

Dynamics of Hot QCD Matter -- Current Status and Developments

The discovery and characterization of hot and dense QCD matter, known as Quark Gluon Plasma (QGP), remains the most international collaborative effort and synergy between theorists and experimentalists in modern nuclear physics to date. The experimentalists around the world not only collect an unprecedented amount of data in heavy-ion collisions, at Relativistic Heavy Ion Collider (RHIC), at Brookhaven National Laboratory (BNL) in New York, USA, and the Large Hadron Collider (LHC), at CERN in Geneva, Switzerland but also analyze these data to unravel the mystery of this new phase of matter that filled a few microseconds old universe, just after the Big Bang. In the meantime, advancements in theoretical works and computing capability extend our wisdom about the hot-dense QCD matter and its dynamics through mathematical equations. The exchange of ideas between experimentalists and theoreticians is crucial for the progress of our knowledge. The motivation of this first conference named "HOT QCD Matter 2022" is to bring the community together to have a discourse on this topic. In this article, there are 36 sections discussing various topics in the field of relativistic heavy-ion collisions and related phenomena that cover a snapshot of the current experimental observations and theoretical progress. This article begins with the theoretical overview of relativistic spin-hydrodynamics in the presence of the external magnetic field, followed by the Lattice QCD results on heavy quarks in QGP, and finally, it ends with an overview of experiment results.Comment: Compilation of the contributions (148 pages) as presented in the `Hot QCD Matter 2022 conference', held from May 12 to 14, 2022, jointly organized by IIT Goa & Goa University, Goa, Indi

Social multimedia signals: a signal processing approach to social network phenomena

This book provides a comprehensive coverage of the state-of-the-art in understanding media popularity and trends in online social networks through social multimedia signals. With insights from the study of popularity and sharing patterns of online media, trend spread in social media, social network analysis for multimedia and visualizing diffusion of media in online social networks. In particular, the book will address the following important issues: Understanding social network phenomena from a signal processing point of view; The existence and popularity of multimedia as shared and social m

Design of Thinned Linear Antenna Array using Particle Swarm Optimization (PSO) Algorithm

This paper describes the unwanted side lobelevel reduction of thinned linear array antenna usingparticle swarm optimization (PSO) algorithm. InRADAR and satellite communication, very low sidelobe level is required. The purpose of this paper is toreduce side lobe level of linear antenna array usingoptimization technique. Thinning of an antenna arrayinvolves switching ‘ON’ some antenna elements andrest all the elements are switched ‘OFF’. Turning ‘OFF’some of the antenna elements do not degrade thesystem performance. The investigations presented inthis paper may be useful for Direct Broadcast Satellite(DBS) systems

Correction: Telomere length-dependent transcription and epigenetic modifications in promoters remote from telomere ends.

[This corrects the article DOI: 10.1371/journal.pgen.1007782.]

Telomere length-dependent transcription and epigenetic modifications in promoters remote from telomere ends.

Telomere-binding proteins constituting the shelterin complex have been studied primarily for telomeric functions. However, mounting evidence shows non-telomeric binding and gene regulation by shelterin factors. This raises a key question-do telomeres impact binding of shelterin proteins at distal non-telomeric sites? Here we show that binding of the telomere-repeat-binding-factor-2 (TRF2) at promoters ~60 Mb from telomeres depends on telomere length in human cells. Promoter TRF2 occupancy was depleted in cells with elongated telomeres resulting in altered TRF2-mediated transcription of distal genes. In addition, histone modifications-activation (H3K4me1 and H3K4me3) as well as silencing marks (H3K27me3)-at distal promoters were telomere length-dependent. These demonstrate that transcription, and the epigenetic state, of telomere-distal promoters can be influenced by telomere length. Molecular links between telomeres and the extra-telomeric genome, emerging from findings here, might have important implications in telomere-related physiology, particularly ageing and cancer