Entity Personalized Talent Search Models with Tree Interaction Features

Talent Search systems aim to recommend potential candidates who are a good match to the hiring needs of a recruiter expressed in terms of the recruiter's search query or job posting. Past work in this domain has focused on linear and nonlinear models which lack preference personalization in the user-level due to being trained only with globally collected recruiter activity data. In this paper, we propose an entity-personalized Talent Search model which utilizes a combination of generalized linear mixed (GLMix) models and gradient boosted decision tree (GBDT) models, and provides personalized talent recommendations using nonlinear tree interaction features generated by the GBDT. We also present the offline and online system architecture for the productionization of this hybrid model approach in our Talent Search systems. Finally, we provide offline and online experiment results benchmarking our entity-personalized model with tree interaction features, which demonstrate significant improvements in our precision metrics compared to globally trained non-personalized models.Comment: This paper has been accepted for publication at ACM WWW 201

Heart Rate Variability in Children with Tricyclic Antidepressant Intoxication

The aim of this study was to evaluate HRV in children requiring intensive care unit stays due to TCA poisoning between March 2009 and July 2010. In the time-domain nonspectral evaluation, the SDNN (P<0.001), SDNNi (P<0.05), RMSDD (P<0.01), and pNN50 (P<0.01) were found to be significantly lower in the TCA intoxication group. The spectral analysis of the data recorded during the first 5 minutes after intensive care unit admission showed that the values of the nLF (P<0.05) and the LF/HF ratio (P=0.001) were significantly higher in the TCA intoxication group, while the nHF (P=0.001) values were significantly lower. The frequency-domain spectral analysis of the data recorded during the last 5 minutes showed a lower nHF (P=0.001) in the TCA intoxication group than in the controls, and the LF/HF ratio was significantly higher (P<0.05) in the intoxication group. The LF/HF ratio was higher in the seven children with seizures (P<0.001). These findings provided us with a starting point for the value of HRV analysis in determining the risk of arrhythmia and convulsion in TCA poisoning patients. HRV can be used as a noninvasive testing method in determining the treatment and prognosis of TCA poisoning patients

A survey on smart grid potential applications and communication requirements

Information and communication technologies (ICT) represent a fundamental element in the growth and performance of smart grids. A sophisticated, reliable and fast communication infrastructure is, in fact, necessary for the connection among the huge amount of distributed elements, such as generators, substations, energy storage systems and users, enabling a real time exchange of data and information necessary for the management of the system and for ensuring improvements in terms of efficiency, reliability, flexibility and investment return for all those involved in a smart grid: producers, operators and customers. This paper overviews the issues related to the smart grid architecture from the perspective of potential applications and the communications requirements needed for ensuring performance, flexible operation, reliability and economics.http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=9424hb2016Electrical, Electronic and Computer Engineerin

Smart grid technologies : communication technologies and standards

For 100 years, there has been no change in the basic structure of the electrical power grid. Experiences have shown that the hierarchical, centrally controlled grid of the 20th Century is ill-suited to the needs of the 21st Century. To address the challenges of the existing power grid, the new concept of smart grid has emerged. The smart grid can be considered as a modern electric power grid infrastructure for enhanced efficiency and reliability through automated control, high-power converters, modern communications infrastructure, sensing and metering technologies, and modern energy management techniques based on the optimization of demand, energy and network availability, and so on. While current power systems are based on a solid information and communication infrastructure, the new smart grid needs a different and much more complex one, as its dimension is much larger. This paper addresses critical issues on smart grid technologies primarily in terms of information and communication technology (ICT) issues and opportunities. The main objective of this paper is to provide a contemporary look at the current state of the art in smart grid communications as well as to discuss the still-open research issues in this field. It is expected that this paper will provide a better understanding of the technologies, potential advantages and research challenges of the smart grid and provoke interest among the research community to further explore this promising research area.http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=942

Do popular apps have issues regarding energy efficiency?

Mobile apps have become essential components of our daily lives, seamlessly integrating into routines to fulfill communication, productivity, entertainment, and commerce needs, with their diverse range categorized within app stores for easy user navigation and selection. User reviews and ratings play a crucial role in app selection, significantly influencing user decisions through the interplay between feedback and quantified satisfaction. The emphasis on energy efficiency in apps, driven by the limited battery lifespan of mobile devices, impacts app ratings by potentially prompting users to assign low scores, thereby influencing the choices of others. In this study, the presence of energy consumption issues within widely-used popular apps that have high app ratings and user interaction has been investigated through the analysis of user reviews. It is anticipated that popular apps, with high ratings, are less problematic than other apps. User reviews were collected from 32 apps across 16 diverse categories and subsequently filtered based on specific keywords. From the resulting pool of 14,064 user reviews, 8,007 reviews were manually identified as specifically addressing the app’s energy consumption. The results of the study demonstrate that all 32 popular apps under consideration exhibit issues related to energy consumption. While the frequency of energy-related issues may vary, it is evident that users are concerned about app energy consumption, as evidenced by the reception of complaint reviews regarding their energy usage. App energy efficiency is important to users, including popular apps with diverse features, necessitating developers to address expectations and optimize for energy efficiency. Improving the energy efficiency of apps has the potential to enhance user satisfaction and, consequently, contribute to the overall success of the app

Empirically investigating energy impacts of software engineering decisions

Clause, JamesPollock, Lori L.Software energy efficiency has become an important objective in a broad range of environments where reducing energy consumption is a high-priority goal (e.g., embedded systems in devices, mobile phones and tablets, laptops, and large data centers). Historically, software engineers were unconcerned with energy efficiency; instead they focused on quality attributes such as correctness, performance, reliability, and maintainability. Although the task of improving energy efficiency was left for compiler writers, operating system designers, and hardware engineers, software developers can further reduce the energy usage of the applications that they write beyond what can be achieved at lower system levels. Unfortunately, lack of information about how software engineering decisions impact energy consumption of applications and incorrect assumptions about the underlying causes of energy impacts prevent software developers fulfilling their role in reducing energy consumption. ☐ In addition to reducing the energy consumption of an application, it is also important to maintain the application’s energy efficiency. Therefore, developers need to test their applications for energy consumption and energy issues while evolving them. However, the high costs of energy testing can adversely impact the planning process of application evolution since developers must anticipate performing energy testing in response to code changes. ☐ The research in this dissertation aims to enable and support software engineers in developing and maintaining energy-efficient applications in two ways. First, we have conducted empirical studies that examine the software engineering decisions to improve developers’ understanding of how the decisions they make potentially impact the energy consumption of their applications. Second, we have developed a technique that predicts energy testing requirements of proposed code changes to help developers in making informed decisions and creating an effective timeline during the planning process of application evolution.University of Delaware, Department of Computer and Information SciencesPh.D

PlayStoreData

Collected reviews from 32 popular apps considered from 16 different app categories in Google Play Store</p

Designing a Distributed Multi-agent System for Compiler Optimization

This paper explores the run time performance improvements using different GCC optimization flags in program compilation. As multi-core microprocessor systems replacing legacy single-core ones, tremendous effort is needed to address to optimize the associated compilers for newly designed architectures in order to suit them for running parallel programming on multiple cores. Therefore, the aim of this paper is to address this challenge by designing an optimum distributed multi-agent system to perform compiler optimization. A multi-agent framework is adopted to utilize random and genetic algorithm-based search algorithm to find the best GCC optimization flags for a given program. The framework is highly scalable and can be extended with distributed system concept to perform code compilation in parallel to find the best-optimized code sequence in a short amount of time. The initial performance results have promising indicators which clearly show that the performance improvement is achieved