CloudNeg: An autonomous multi issue negotiation system, with preference elicitation component, for trading cloud services

Cloud services provide its users with flexible resource provisioning. But in the current market, a user has to choose from a limited set of configurations at a fixed price. This paper presents an autonomous negotiation system termed CloudNeg for negotiating cloud services. CloudNeg provides buyers and sellers of cloud services with autonomous agents to negotiate on the specifications of a cloud instance, including price, on their behalf. These agents elicit their buyers’ time preferences and use them in negotiations. Further, this paper presents two artifacts: a negotiation algorithm and a prototype which together form CloudNeg

An e-ADR (elaborated Action Design Research) Approach Towards Game-based Learning in Cybersecurity Incident Detection and Handling

The growth of internet has significantly increased the cybersecurity threat instances. Therefore to equip people with skills to mitigate such attacks, this paper provides a Cybersecurity game-based learning artefact designed using the e-ADR approach. The artefact teaches the Incident Detection and Handling procedures that need to be undertaken in the event of a cybersecurity threat. As per NIST’s guide to malware incident prevention and handling, an incident response process has four major phases: preparation, detection and analysis, containment/eradication/recovery, and post-incident activity. Our gaming artefact delves into the detection and containment phase to design a game that teaches users to detect and then perform containment actions on the cybersecurity threat

Surgical management of basicervical fracture neck of femur with dynamic hip screw and de-rotation screw: a prospective study

Background: Basicervical region of femur is that part of femur which is intermediate between neck and intertrochanteric region. Fracture in this region carry substantially higher chances of failure due to greater fracture angle and are rotationally unstable. If treated inadequately they carry very high chances of fracture non-union and theoretically risk of osteonecrosis. The objective of the study was to analyse functional outcome of basicervical fracture neck of femur fixation with dynamic hip screw and de-rotation screw in a tertiary care hospital.Methods: 35 cases of basicervical fracture neck of femur admitted in Chigatteri General Hospital and Bapuji Hospital affiliated to JJM Medical College Davangere, in the period of October 2015 to October 2018. Functional outcome was assessed according to Modified Harris Hip Score after one year of follow up.Results: The fracture union was found in 100% cases, average time period for fracture union was 12.28±3.71 weeks (11-15 weeks range). The results according to Modified Harris hip score were excellent in 70%, good in 11.4%. Fair in 5.7% and poor in 2.8% at the end of one year. The correlation analysis with Pearson’s correlation coefficient (r) was 0.74 which show a highly positive correlation between the union of basicervical fracture neck of femur with dynamic hip screw and derotation screw.Conclusions: With the study of 35 cases of basicervical fracture neck femur we conclude that these are a unique type of fractures mid-way between neck and intertrochanteric fractures with rotational and axial instability, and also risk of osteonecrosis. DHS allows for controlled collapse of the fracture for uneventful healing, and de-rotation screw gives rotational stability

Microscopic modelling of adsorption and the generalised surface layer hypothesis

Two- and three-state models for the adsorption of organic compounds at the electrodelelectrolyte interface are proposed. Different size requirements, if any, for the neutral molecule and the adsorbing solvent are also considered. It is shown how the empirical, generalised surface layer (GSL) relationship (between the potential difference and the electrode charge) formulated by Damaskin et a / . can be understood at the molecular level

An Online Algorithm for Programmatic Advertisement Placement in Supply Side Platform of Mobile Advertisement

Smartphone applications are emerging as popular media for promoting one’s products through in-app advertisements. Today, there are a number of organizations, known as supply-side-platforms (SSP), who aggregate and auction these ad-spaces from different suppliers/publishers. Advertisers (or their intermediaries) place bid for these spaces based on different relevance criteria (e.g., the location and device of the app-user, the app’s IAB category etc.), the impression value, clickthrough value, and the conversion value. After the received ads are filtered based on relevance, the SSP is often still faced with a number of options for ad-placement, each having different revenues owing to differences in clickthrough rates etc. Moreover, the SSP has to decide on the ad-placement in real-time. In this paper, we consider the SSP’s ad-placement problem in the aforementioned situation. We propose an optimization model to maximize the SSP’s revenues. Based on computational experience with this model, we develop a rule-based online algorithm that appears to be viable as a real-time solution

Healthcare Analytics Adoption-Decision Model: A Case Study

Healthcare organizations (HCO) are under pressure to adopt emerging solutions with a view to improving the quality and efficiency of their operations, patient care and clinical decisions. In the literature, while recommendations have been put forth to follow an organizational approach to the adoption and implementation of analytics, there is a paucity of research into what specifically constitutes healthcare-analytics (HA), as well the antecedents that can explain and predict its adoption-decisions. In this paper, we fill this gap, by first proposing a typology for HA and an adoption-decision model that integrates the TOE framework with DeLone and McLean IS Success Model. We use a case study for the initial validation of the typology and the model. Our study reveals that the HCO studied has the same types of the data proposed in our typology, although the usage of the data and current/future adoption of analytics depends on many factors beyond simply technology

Collaborative Literature Search System: An Intelligence Amplification Method for Systematic Literature Search

In this paper, we present a method for systematic literature search based on the symbiotic partnership between the human researcher and intelligent agents. Using intelligence amplification, we leverage the calculation power of computers to quickly and thoroughly extract data, calculate measures, and visualize relationships between scientific documents with the ability of domain experts to perform qualitative analysis and creative reasoning. Thus, we create a foundation for a collaborative literature search system (CLSS) intended to aid researches in performing literature reviews, especially for interdisciplinary and evolving fields of science for which keyword-based literature searches result in large collections of documents beyond humans’ ability to process or the extensive use of filters to narrow the search output risks omitting relevant works. Within this article, we propose a method for CLSS and demonstrate its use on a concrete example of a literature search for a review of the literature on human-machine symbiosis