Miniaturized and flexible FSS-based EM shields for conformal applications

This article reports on very efficient and highly miniaturized wideband polygon-shaped frequency selective surface (PFSS) shields for the planar and conformal applications in the X-band. These shields have been analyzed for both lossy as well as for low-loss substrates. The conformal configurations of PFSS are particularly investigated for inward, outward, and double-curved profiles useful for a variety of applications. The conformal designs have been tested for two different radii of curvatures. The models have been simulated using a hybrid simulation approach for electrically large geometries. The equivalent circuit model as well as the analytical model are determined. The proposed PFSS designs offer stable angular response up to 60° for planar and all conformal geometries on both lossy and low-loss prototypes. Shielding effectiveness of at least 55 dB and 48 dB has been measured for flat/nonconformal and conformal configurations, respectively

How to Evaluate a Conflict Minimizing Task Scheduler through a User Study

Workspace awareness tools facilitate coordination among developers in a team by informing them of emerging conflicts due to parallel development. Several such tools have been introduced recently. However, evaluating such (collaborative) tools through user studies is nontrivial because it depends on the group dynamics and their development behavior. In this paper, we present the challenges in evaluating a collaboration tool geared towards minimizing conflicts by scheduling (independent) development tasks. We present the research questions that a user evaluation should answer along with the foreseen challenges in answering these questions. We would like to use the workshop to exchange opinions and feedback to refine the design of our user study and start a conversation on the challenges and methods for evaluating a collaborative development tools

Cassandra: Proactive Conflict Minimization through Optimized Task Scheduling

Software conflicts arising because of conflicting changes are a regular occurrence and delay projects. The main precept of workspace awareness tools has been to identify potential conflicts early, while changes are still small and easier to resolve. However, in this approach conflicts still occur and require developer time and effort to resolve. We present a novel conflict minimization technique that proactively identifies potential conflicts, encodes them as constraints, and solves the constraint space to recommend a set of conflict-minimal development paths for the team. Here we present a study of four open source projects to characterize the distribution of conflicts and their resolution efforts. We then explain our conflict minimization technique and the design and implementation of this technique in our prototype, Cassandra. We show that Cassandra would have successfully avoided a majority of conflicts in the four open source test subjects. We demonstrate the efficiency of our approach by applying the technique to a simulated set of scenarios with higher than normal incidence of conflicts

A Degree of Conflict Model for Workspace Awareness

Workspace awareness solutions provide ongoing change information at the level of files. This makes the user responsible for identifying how current changes affect their tasks and provides no guidance for planning their (future) tasks. Here, we present our approach to task-based awareness that calculates a degree-of-conflict for tasks and recommends an optimum set of tasks that minimizes the risk of conflicts. Specifically, we present three novel research ideas: (1) transition from the current file-based awareness systems to task-based awareness, (2) transition from reactive conflict detection to proactive conflict prediction, and (3) a degree-of-conflict model that models conflicts per task per workspace, which can be used to recommend an optimum task list for a developer

Minimizing software conflicts through proactive detection of conflicts and task scheduling

Distributed software development has become a norm in today’s large-scale software development. While the use of distributed version control systems helps facilitate peer-to-peer collaboration by enabling developers to work independently in local repositories, software conflicts that arise because of coordination failures are still a regular occurrence. In a study of four popular open-source projects we found conflicts to occur frequently (ranging from 34% to 54% of all merges) taking substantial amounts of time (about 1-14 days (median)) to fix the conflicts. The state-of-the art has focused on conflict mitigation and aims to notify developers of emerging conflicts. A key type of conflict mitigation technique is embodied in workspace awareness tools. These tools monitor developers’ workspace activities to facilitate coordination among developers, by identifying potential conflicts early, while changes are still small and easier to resolve. However, in this approach conflicts still occur and require developer time and effort to resolve. We propose a novel conflict minimization technique that is designed to avoid conflicts to the extent possible. Our approach proactively identifies potential conflicts among developers’ tasks, encodes them as constraints, and solves the constraint space to recommend a set of conflict-minimal development paths for the team. This research is the first work towards conflict minimization in software development. In this dissertation, we motivate the study of conflict minimization by conducting an empirical evaluation of four open source projects to characterize the distribution of conflicts and their resolution efforts. We propose a hybrid approach that leverages different data preprocessing heuristics and techniques in natural language processing, machine learning, and information retrieval to predict a priori the set of files that will change for a task–a key input to identifying conflicts among tasks. We introduce and illustrate the generality of our task context identification approach using three popular OSS projects. We implemented our approach in a tool, Cassandra, which extends the Eclipse Mylyn plugin. We evaluated Cassandra, and thereby our approach through several studies, each focusing on a specific aspect of the approach. Our results indicate Cassandra is effective at minimizing conflicts. We evaluated the efficiency of Cassandra by using a simulated set of scenarios with higher than normal incidence of conflicts. Finally, we evaluated the robustness of our approach by evaluating Cassandra’s sensitivity to imprecise information using simulated data with induced errors in the task context

An Intelligent and Smart Environment Monitoring System for Healthcare

Skin wound healing is influenced by two kinds of environment i.e., exterior environment that is nearby to wound surface and interior environment that is the environment of the adjacent part under wound surface. Both types of environment play a vital role in wound healing, which may contribute to continuous or impaired wound healing. Although, different previous studies provided wound care solutions, but they focused on single environmental factors either wound moisture level, pH value or healing enzymes. Practically, it is insignificant to consider environmental effect by determination of single factors or two, as both types of environment contain a lot of other factors which must be part of investigation e.g., smoke, air pollution, air humidity, temperature, hydrogen gases etc. Also, previous studies didn’t classify overall healing either as continuous or impaired based on exterior environment effect. In current research work, we proposed an effective wound care solution based on exterior environment monitoring system integrated with Neural Network Model to consider exterior environment effect on wound healing process, either as continuous or impaired. Current research facilitates patients by providing them intelligent wound care solution to monitor and control wound healing at their home