Unanticipated Context Awareness for Software Configuration Access Using the getenv API

Method for rapidly generating urban damage scenarios under non-uniform ground motion input based on matching algorithms and time history analyses

The authors discuss the evaluation of highly interactive and novel context-aware system with a methodology based on a TREC-like benchmark. We take as a case study an application for Web content perusal by means of context-aware mobile devices, named Context-Aware Browser. In this application, starting from the representation of the user’s current context, queries are automatically constructed and used to retrieve the most relevant Web contents. Since several alternatives for query construction exist, it is important to compare their effectiveness, and to this aim we developed a TREC-like benchmark. We present our approach to early stage evaluation, describing our aims and the techniques we apply. The authors underline how, for the evaluation of context-aware retrieval systems, the benchmark methodology adopted can be an extensible and reliable tool.

In this paper we present the latest CMS open data release published on the CERN Oopen Data portal. Samples of collision and simulated datasets were released together with detailed information about the data provenance. The associated data production chains cover the necessary computing environments, the configuration files and the computational procedures used in each data production step. We describe data curation techniques used to obtain and publish the data provenance information and we study the possibility of reproducing parts of the released data using the publicly available information. The present work demonstrates the usefulness of releasing selected samples of raw and primary data in order to fully ensure the completeness of information about the data production chain for the attention of general data scientists and other non-specialists interested in using particle physics data for education or research purposes.

In this paper, we describe a case study to improve performance through the load testing of multi-tired system for financial accounts before the system opening. The load test was conducted after the data collection tools(Performance Monitor, DB PSSDiag) were installed. By analyzing the collected log, we were able to identify the main sector requiring performance improvements among the presentation tier, web tier, business logic tier and data tier. The ASP.NET server-down on the web tier could be improved by modifying the parameter values in the configuration file. Some server downs occurred on the business logic tier when a large number of users access at the same time, were more difficult to be solved. By analyzing the hang-dump at the server-down time, we were able to find a process that caused the problem. and we had to modify the relevant codes. For major performance improvements of the data-tier, indices of some queries was optimized by using the built-in DBMS query analyzer, after analyzing the log of long-response-time queries. The problems and solutions considered in this case study will be a reference for the performance improvement of a multi-layer system with the similar structure.

This research intends to offer an original contribution by studying how fashion and luxury companies have redefined both their marketing (in terms of price, product, promotion and placement) and operations actions (in terms of the relationship between supply network partners, types of integration, location of production, outsourcing and network objectives) to challenge contextual dynamic changes. The study adopts the multiple case study method. Evidence from 11 Italian companies highlights different areas under exploration to better respond to dynamic business contexts. Findings show how contextual changes significantly compel a growing alignment between marketing and supply network activities. Case studies indicate that closer partnerships and collaborations among companies within the entire value chain are crucial to realizing new collections, with compressed lead times and improved quality content. Finally, this study identifies two new production strategies (pronto-programmato and focused-programmato) adopted by fashion and luxury companies to improve competitiveness in changing business conditions.

Understanding the work context of future system users is essential in requirements engineering. It is particularly crucial when developing ubiquitous systems that react on context changes. This paper discusses the need for in-situ requirements elicitation approaches to build mobile and context-aware systems. We identify three different levels of support: The first level covers contextual techniques without tool support. Second level support is based on existing RE approaches and mobile tools. Third level support utilizes context-aware tools receiving context-specific information to guide analysts in the field. These tools enhance requirements gathering for ubiquitous systems. We present a context-aware tool prototype for on-site scenario walkthroughs and discuss how the underlying scenario-based approach needs to be adapted. Our tool-based approach was tested in an initial evaluation study. Finally, the paper presents requirements for RE approaches supporting ubiquitous system development based on lessons learned from using level II and III tools.

The vision of ubiquitous computing is about numerous devices embedded in our every-day environment, designed to serve humans in a non-obtrusive manner while minimizing the required user attention. These devices are expected to seamlessly monitor context changes and adapt their behavior and functionality to maximize the user benefit. However, designing the self-adaptive logic of such systems is far from trivial. This paper discusses a utility function-based approach for specifying the adaptive behavior of component-based context-aware systems. Although this approach allows for completely autonomous self-adaptive behavior, it also leverages potential user feedback by adjusting and optimizing its behavior. It is argued that this approach provides significant improvement to the adaptive behavior of a system while maintaining the required user attention to a minimum. At the same time, it keeps the complexity involved in the development of such context-aware, self-adaptive applications to a reasonably low level.

• Workspace design in a hybrid working setup • A flexible co-working space in London as the case study • Geo-spatial association between spatial and environmental design metrics and occupants’ space preferences • Data-driven machine-learning-based seat occupancy prediction model • Space with high spatial connectivity and large visual field is preferred • Seats with a relatively higher temperature and daylight level have a higher occupancy level. The evolving landscape of hybrid working necessitates a corresponding change in workspace design, yet the understanding of the spatial and environmental design of flexible workspaces remains relatively limited. This study investigates the association between workspace design and occupants’ behaviour and preferences and builds a data-driven model to predict seat occupancy based on design features. Case study data collection process spans over a year in a hybrid co-working space in London, forming a multi-domain integrated dataset including sensor-detected occupancy, on-site measured and simulated environmental variables, computed spatial metrics and human-voted preferences. The combined effects of thermal comfort (temperature and humidity), visual comfort (artificial light and daylight exposure) and spatial metrics (connectivity and isovist field) are analysed to understand their collective impacts on space occupancy and user preferences. Geo-spatial regression and autocorrelation models are employed to explore associations at a grid level. Through cluster analysis, 61 seats are categorised to four levels based on their occupancy and utilisation rates, and a supervised classification model predicts occupancy levels using design variables. The study aims to present a data-driven analytical framework for evaluating flexible workspace utilisation and demonstrate predictive capabilities by identifying associations between environmental and spatial variables and occupancy patterns, offering a tool to guide evidence-based design and management of flexible workspaces. The analysis underscores the significance of spatial and environmental metrics, revealing that areas or seats with high spatial connectivity and larger visual fields tend to attract more occupants. Additionally, environmental variables, such as temperature and daylight level, exhibit positive effects on increased occupancy.

Charitable trust is a combination of charity and trust industry. The development of charitable trust started earlier in foreign countries and has been widely used. Charitable trust in China is still in its infancy, lacking legal support and a complete operation system. Problems such as unclear boundaries and imperfect tax preference system, and a complete public trust system has not yet been formed. But from a development point of view, charitable trust in China's poverty alleviation, pension and other fields have a high application value and development prospects. In this paper, the development status of charitable trust in China is summarized and considered.

Measurement and reporting of dynamic behavior of a target application is a pressing issue in the Trusted Computing paradigm. Remote attestation is a part of trusted computing, which allows monitoring and verification of a complete operating system or a specific application by a remote party. Several static remote attestation techniques have been proposed in the past but most of the feasible ones are static in nature. However, such techniques cannot cater to dynamic attacks such as the infamous Heartbleed bug. Dynamic attestation offers a solution to this issue but is impractical due to the infeasibility of measurement and reporting of enormous runtime data. To an extent, it is possible to measure and report the dynamic behavior of a single application but not the complete operating system. The contribution of this paper is to provide the design and implementation of a scalable dynamic remote attestation mechanism that can measure and report multiple applications from different stakeholders simultaneously while ensuring privacy of each stakeholder. We have implemented our reference monitor and tested on Linux Kernel. We show through empirical results that this design is high scalable and feasible for a large number of stakeholders.

PurposeThis paper aims to explore the key risk factors affecting the Personnel Localization Management of international construction projects under the major public emergencies represented by the novel coronavirus pneumonia pandemic (hereinafter COVID-19) and how the public emergency affected the Personnel Localization Management from three levels: staff turnover rate, the number of different personnel, the salary and performance of workers. The paper also helps to enhance the construction enterprises' response capacity of major public emergencies and provides a comprehensive framework of optimization strategies for the Personnel Localization Management of international construction projects (hereinafter projects).Design/methodology/approachThe main research method of this paper is the case study, and ten representative international construction projects are selected for case study in China construction enterprises (hereinafter CCE). And this study used the failure mode and effects analysis (FMEA) and comparative analysis to find out all potential risk factors under the COVID-19 and analyze how the epidemic affects the Personnel Localization Management of projects which based on the primary data from 10 projects obtained through in-depth interviews and the secondary data from China First Metallurgical Group and Central South Construction Group's Overseas Enterprise.FindingsThe findings show that the outbreak of the major public emergencies not only greatly increased eight risk factors but also directly led to an increase in staff turnover rate. Meanwhile, the numbers of Chinese and local managers and workers are all affected, and an increase in the number and the salary performance of local workers can be reduced, to a certain extent, to the cost-to-output ratio of the projects. The findings would help construction enterprises better cope with Personnel Localization Management and enhance the response capacity of major public emergencies.Research limitations/implicationsThis study will broaden researchers' horizons regarding “Personnel Localization Management under major public emergencies” and “risk factors of Personnel Localization Management in an international context.” Furthermore, construction enterprises looking for a better mechanism of Personnel Localization Management can benefit from research findings and lessons learned from the authors' case study during or before an outbreak of major public emergency. Lastly, the framework of optimization strategies for Personnel Localization Management can be used both for research purposes and practice issues in international construction projects.Practical implicationsThe findings from the authors' case study offer the direction for international construction enterprises in China and other countries to formulate effective measures, strengthen overseas business and establish a crisis management mechanism for Personnel Localization Management under major public emergencies, and the findings provide emergency plans for projects to improve the public crisis handling capacity and respond to major public emergencies such as the COVID-19.Social implicationsThis study analyzes the impact of the COVID-19 on the Personnel Localization Management of international construction projects from the perspective of personnel. This study provides a theoretical reference for the international construction industry to actively respond to major public emergencies. Besides, the research is conducive to improving the emergency response mechanism in the construction industry, and further promoting the high-quality and globalized development of international construction.Originality/valueThis study provides other researchers with a comprehensive understanding of the risk factors affecting the Personnel Localization Management of projects under the COVID-19 and insight for further research on localization management, risk management, and project management.

Release planning for incremental software development assigns features to releases such that most important technical, resource, risk and budget constraints are met. The research presented in this paper is based on a three staged procedure. In addition to an existing method for (i) strategic release planning that maps requirements to subsequent releases and (ii) a more fine-grained planning that defines resource allocations for each individual release, we propose a third step, i.e., (iii) stability analysis, which analyzes proposed release plans with regards to their sensitivity to unforeseen changes. Unforeseen changes can relate to alterations in expected personnel availability and productivity, feature-specific task size (measured in terms of effort), and degree of task dependency (measured in terms of work load that can only be processed if corresponding work in predecessor tasks has been completed). The focus of this paper is on stability analysis of proposed release plans. We present the simulation model REPSIM (Release Plan Simulator) and illustrate its usefulness for stability analysis with the help of a case example.

Given the large amount of existing services and the diversified needs nowadays, it is time-consuming for end-users to find appropriate services. To help end-users obtain their desired services, context-aware systems provide a promising way to automatically search and recommend services using a user's context. However, existing context-aware techniques have limited support for dynamic adaption to newly added context types (e.g., location, time and activity). Due to the diversity of user's environment, the available context types may change over time. It is challenging to anticipate a complete set of context types while we design a context aware system. In this paper, we propose a context modeling approach which can dynamically handle various context types and values. More specifically, we use ontologies to enhance the meaning of a user's context values and automatically identify the relations among different context values. Based on the relations among context values, we capture the potential services which the user might need. A case study is conducted to evaluate the effectiveness of our approach. The results show that our approach can use contexts to find users' needs and recommend their desired services with high precision and recall.

In response to recent demand, context-aware application performs significantly in the field of pervasive computing and smart environment. Many approaches have been proposed to provide functionalities and implementation using context information to observe the environment. Developing context-awareness system becomes more essential issue in order to support into the real situation and system deals with many components and complexity. There are many hardware with different platforms that make them have difficulty to communicate to each other with different layers processing in the system of context such as physical, middleware and application layers. Services in each layer need to adapt the way they behave according to the current context information. This research introduces the development of context-aware system and middleware developments that support the creation of smart application with the purpose of providing the framework of the system and deploy middleware as being the bridge to integrate physical layer and application layer seamlessly to support monitoring ubiquity environment. The system controls multi sensors to monitor the real environment from raw data through prototype platforms for managing, sensing, computing and user interacting as the outcome of the system’s performance. Implementation and experiment have been performed where user moves in / moves out from the sensor range. The proposed middleware is able to handle the complicated system and fulfill its requirement such as heterogeneity, scalability and mobility, the system and complicated components are integrated to be a completed system that operate, interpret and representation context entities to an end users. Having this control system makes a lot of benefits such as real time information access, become intermediary between layers and support to control energy system with the purpose of reducing the energy consumption, rapid communication to the users.

Date palm cultivation is economically important in the Sultanate of Oman, with significant financial investment coming from both the government and from private individuals. However, a global infestation of Dubas bug (Ommatissus lybicus Bergevin) has impacted the Middle East region, and infestations of date palms have been widespread. In this study, spatial analysis and geostatistical techniques were used to model the spatial distribution of Dubas bug infestations to (a) identify correlations between Dubas bug densities and different environmental variables, and (b) predict the locations of future Dubas bug infestations in Oman. Firstly, we considered individual environmental variables and their correlations with infestation locations. Then, we applied more complex predictive models and regression analysis techniques to investigate the combinations of environmental factors most conducive to the survival and spread of the Dubas bug. Environmental variables including elevation, geology, and distance to drainage pathways were found to significantly affect Dubas bug infestations. In contrast, aspect and hillshade did not significantly impact on Dubas bug infestations. Understanding their distribution and therefore applying targeted controls on their spread is important for effective mapping, control and management (e.g., resource allocation) of Dubas bug infestations.