Let Trajectories Speak Out the Traffic Bottlenecks

Traffic bottlenecks are a set of road segments that have an unacceptable level of traffic caused by a poor balance between road capacity and traffic volume. A huge volume of trajectory data which captures realtime traffic conditions in road networks provides promising new opportunities to identify the traffic bottlenecks. In this paper, we define this problem as trajectory-driven traffic bottleneck identification : Given a road network R , a trajectory database T , find a representative set of seed edges of size K of traffic bottlenecks that influence the highest number of road segments not in the seed set. We show that this problem is NP-hard and propose a framework to find the traffic bottlenecks as follows. First, a traffic spread model is defined which represents changes in traffic volume for each road segment over time. Then, the traffic diffusion probability between two connected segments and the residual ratio of traffic volume for each segment can be computed using historical trajectory data. We then propose two different algorithmic approaches to solve the problem. The first one is a best-first algorithm BF , with an approximation ratio of 1-1/ e . To further accelerate the identification process in larger datasets, we also propose a sampling-based greedy algorithm SG . Finally, comprehensive experiments using three different datasets compare and contrast various solutions, and provide insights into important efficiency and effectiveness trade-offs among the respective methods.

Efficiency and Effectiveness of Web Application Vulnerability Detection Approaches: A Review

Most existing surveys and reviews on web application vulnerability detection (WAVD) approaches focus on comparing and summarizing the approaches’ technical details. Although some studies have analyzed the efficiency and effectiveness of specific methods, there is a lack of a comprehensive and systematic analysis of the efficiency and effectiveness of various WAVD approaches. We conducted a systematic literature review (SLR) of WAVD approaches and analyzed their efficiency and effectiveness. We identified 105 primary studies out of 775 WAVD articles published between January 2008 and June 2019. Our study identified 10 categories of artifacts analyzed by the WAVD approaches and 8 categories of WAVD meta-approaches for analyzing the artifacts. Our study’s results also summarized and compared the effectiveness and efficiency of different WAVD approaches on detecting specific categories of web application vulnerabilities and which web applications and test suites are used to evaluate the WAVD approaches. To our knowledge, this is the first SLR that focuses on summarizing the effectiveness and efficiencies of WAVD approaches. Our study results can help security engineers choose and compare WAVD tools and help researchers identify research gaps.

Opportunities and Challenges in Code Search Tools

Code search is a core software engineering task. Effective code search tools can help developers substantially improve their software development efficiency and effectiveness. In recent years, many code search studies have leveraged different techniques, such as deep learning and information retrieval approaches, to retrieve expected code from a large-scale codebase. However, there is a lack of a comprehensive comparative summary of existing code search approaches. To understand the research trends in existing code search studies, we systematically reviewed 81 relevant studies. We investigated the publication trends of code search studies, analyzed key components, such as codebase, query, and modeling technique used to build code search tools, and classified existing tools into focusing on supporting seven different search tasks. Based on our findings, we identified a set of outstanding challenges in existing studies and a research roadmap for future code search research.

Coproduce Conservation Technology With Conservation Decision Makers and Practitioners to Increase Its Impact

Addressing the biodiversity crisis will mean developing and adopting new resources and methods that effectively improve public conservation efforts. Technologies have a long track record of increasing the efficiency of carrying out time-consuming tasks or even making new feats possible, and if applied thoughtfully, can serve as a key means of strengthening conservation outcomes. Yet technology development sometimes proceeds without clear mechanisms for application and scaling, or key adopters like government agencies are not able to use the technologies. To overcome these discrepancies, we recommend the use of a coproduction model of conservation technology development that starts from detailed knowledge of conservation laws, regulations, policies, and their implementation; identifies choke points in those processes amenable to technological solutions; and then develops those solutions while integrating existing users and needs. To illustrate the model, we describe three tools recently developed to help improve the efficiency and effectiveness of implementing the U.S. Endangered Species Act. We also highlight several outstanding questions and challenges that the broad conservation technology and policy communities may help address.

PACAM: A Pairwise-Allocated Strategy and Capability Average Matrix-Based Task Scheduling Approach for Edge Computing

With the development of the smart Internet of Things (IoT), an increasing number of tasks are deployed on the edge of the network. Considering the substantially limited processing capability of IoT devices, task scheduling as an effective solution offers low latency and flexible computation to improve the system performance and increase the quality of services. However, limited computing resources make it challenging to assign the right tasks to the right devices at the edge of the network. To this end, we propose a polynomial-time solution, which consists of three steps, i.e., identifying available devices, estimating device quantity, and searching for feasible schedules. In order to shrink the number of potential schedules, we present a pairwise-allocated strategy (PA). Based on these, a capability average matrix (CAM)-based index is designed to further boost efficiency. In addition, we evaluate the schedules by the technique for order preference by similarity to an ideal solution (TOPSIS). Extensive experimental evaluation using both real and synthetic datasets demonstrates the efficiency and effectiveness of our proposed approach.

A conceptual framework for operational performance measurement in wholesale organisations

PurposePerformance measurement involves gaining useful information about performance. The purpose is to develop a conceptual framework to assist wholesale managers in selecting useful information to evaluate operational performance. The proposed framework identifies core operations, measures of operational performance and factors that affect the performance of wholesale organisations.Design/methodology/approachThe research essentially relies on the available literature to develop a conceptual framework and define related components. Research primary data were used to validate the framework components and to implement the framework in wholesale organisations by allocating performance factors to the different components of the proposed framework. Using a semi-structured interview design, ten face-to-face interviews were conducted with managers of ten different wholesale organisations.FindingsThe research identifies five core operations that affect the operational performance in wholesale organisations, four measures for evaluating efficiency and effectiveness in every core operation and 28 factors that influence operational performance in wholesale organisations.Originality/valueOperational performance is monitored by evaluating the achievement of efficiency and effectiveness in operations. The research introduces a performance measurement framework that identifies the required information to evaluate the efficiency and effectiveness of core operations in wholesale organisations.

Pedagogical Strategies for the learning of medicine students

With the epidemiological contingency, the learning processes were modified by teaching with virtualization. The teaching staff implemented pedagogical strategies structuring methodologies, interaction dynamics, fulfilling the objectives set out in the educational curriculum. Objective: To implement pedagogical strategies involved in virtualization during the learning process in medical students. Methodology: A descriptive, observational study with a qualitative approach over a period of 8 months. The sample was 225 students from the 5th semester of the Surgeon Degree. Results: It was shown that group activities, synchronous online conferences have 68% approval, dynamics such as discussion forums have 85% approval. Video recording has 45%, essays 25%, and mind maps 30%. Conclusion: Implementing educational strategies allows assessing efficiency and effectiveness promoting learning for the development of professional intellect.

Internal Control and Its Application in Public Management: a Literature Review

Currently, having a transparent and orderly public institution is related to the public policy of modernization of the state, which is not easy because it requires managers who have the will to implement an internal control system that allows the efficiency and effectiveness of the acts of the entities. The internal control in recent years has greater relevance seeking that the state entities are strengthened through new processes and changes of actions that allow transparency and achieve the objectives set and have an efficient management with a level of security of their administrative acts. The objective of this research is to study the simplification of actions and administrative transformations in public management through internal control. The methodology used for the literature review was descriptive, a search was made through the Scopus database, obtaining general data of 24 records, a not very significant number for the topic addressed, which has been subjected to bibliometric analysis that allowed to determine that the growth of publications from 1977 to 2020 has had an insignificant growth, having been accentuated in 2 publications from 2019 to 2020, likewise the greatest number of researches have been carried out in undefined countries, followed by Portugal, United Kingdom and United States, being the article the publication medium that has the greatest significance and the area that stands out most in publications is the social sciences followed by the economic sciences. Likewise, the Vos viewer was used to obtain the study map and the heat map of the Internal Control and Public Management theme. From the analysis, the theories related to the paradigms of internal control and public management have been analyzed, which will lead us to understand the changes or actions that public entities have or have had.

Designing a Medical Supply Chain Network Considering the Risk of Supply and Flexible Production in Two-Stage Uncertain Conditions

In the green supply chain approach, all the links that are put together to provide a product or service are considered, and strategic and operational decisions are made to increase the efficiency and effectiveness of the entire chain. At the same time, the environmental effects should be minimized. In this research, a nonlinear mixed-integer multiobjective model is developed to design a green closed-loop supply chain for medical products. In this supply chain, the echelons include supplier, manufacturer, warehouse, and customer in the forward supply chain and collection centers, repair services, and disposal centers in the reverse supply chain. In the proposed model, four objectives of customer satisfaction, environmental effects, supply risk, and total costs of the supply chain were considered. The developed model is implemented in a supply chain of medical products, and after optimizing the model, the main results including location and capacity of facilities, planning for flexible production, purchase of materials, service and maintenance plan, product transfer, and inventory level are determined and analyzed.

Application of Geospatial Methods in Evaluating Environmental Interventions and Related Socioeconomic Benefits

Environmental interventions underpin the Sustainable Development Goals (SDGs) and the Rio Conventions. The SDGs are integrated and embody all three aspects of sustainable development—environmental, social, and economic—to capture the interlinkages among the three areas. The Rio Conventions—on biodiversity, climate change, and desertification, also intrinsically linked—operate in the same ecosystems and address interdependent issues, and represent a way of contributing to the SDGs. Assessing the results of environmental interventions and the related socioeconomic benefits is challenging due to their complexity, interlinkages, and often limited data. The COVID-19 crisis has also necessitated creativity to ensure that evaluation’s critical role continues during the crisis. Satellite and other geospatial information, combined with existing survey data, leverage open-source and readily available data to determine the impact of projects. Working with geospatial data helps maintain flexibility and can fill data gaps without designing new and often expensive data tools for every unique evaluation. Using data on interventions implemented by the Global Environment Facility in biodiversity, land degradation, and climate change, we present the application of geospatial approaches to evaluate the relevance, efficiency, and effectiveness of interventions in terms of their environmental outcomes and observable socioeconomic and health co-benefits.