1. Interaction. The interactions learners have with each other build interpersonal skills, such as listening, politely interrupting, expressing ideas, raising questions, disagreeing, paraphrasing, negotiating, and asking for help. 2. Interdependence. Learners must depend on one another to accomplish a common objective. Each group member has specific tasks to complete, and successful completion of each member’s tasks results in attaining the overall group objective.

将“Cooperative Learning”融入课堂——浅谈英语素质教育

A reviewer for the Journal of the Royal Statistical Society of England comments \"This is the first book covering in one volume all important topics in genetical statistics.\" Written to provide basic probability ideas in terms of genetic situations, since the theory of genetics is a probability theory; to give a definitive treatment of applications of these ideas to genetic theory; and to describe statistical methods appropriate to the data models that are developed.

An Introduction to Genetic Statistics

(1) Whereas the objectives of the Community, as laid down in the Treaty, as amended by the Treaty on European Union, include creating an ever closer union among the peoples of Europe, fostering closer relations between the States belonging to the Community, ensuring economic and social progress by common action to eliminate the barriers which divide Europe, encouraging the constant improvement of the living conditions of its peoples, preserving and strengthening peace and liberty and promoting democracy on the basis of the fundamental rights recognized in the constitution and laws of the Member States and in the European Convention for the Protection of Human Rights and Fundamental Freedoms;

Some Preliminary Comments on the DIRECTIVE 95/46/EC OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 24 October 1995 on the protection of individuals with regard to the processing of personal data and on the free movement of such data.

Solid waste issue: Sources, composition, disposal, recycling, and valorization

Social media platforms provide active communication channels during mass convergence and emergency events such as disasters caused by natural hazards. As a result, first responders, decision makers, and the public can use this information to gain insight into the situation as it unfolds. In particular, many social media messages communicated during emergencies convey timely, actionable information. Processing social media messages to obtain such information, however, involves solving multiple challenges including: parsing brief and informal messages, handling information overload, and prioritizing different types of information found in messages. These challenges can be mapped to classical information processing operations such as filtering, classifying, ranking, aggregating, extracting, and summarizing. We survey the state of the art regarding computational methods to process social media messages and highlight both their contributions and shortcomings. In addition, we examine their particularities, and methodically examine a series of key subproblems ranging from the detection of events to the creation of actionable and useful summaries. Research thus far has, to a large extent, produced methods to extract situational awareness information from social media. In this survey, we cover these various approaches, and highlight their benefits and shortcomings. We conclude with research challenges that go beyond situational awareness, and begin to look at supporting decision making and coordinating emergency-response actions.

/pdf/processing-social-media-messages-in-mass-emergency-a-survey-2wkyj3y36n.pdf

Processing Social Media Messages in Mass Emergency: A Survey

Automated and smart meters are devices that are able to monitor the energy consumption of electricity consumers in near real-time. They are considered key technological enablers of the smart grid, as the real-time consumption data that they can collect could enable new sophisticated billing schemes, could facilitate more efficient power distribution system operation and could give rise to a variety of value-added services. At the same time, the energy consumption data that the meters collect are sensitive consumer information; thus, privacy is a key concern and is a major inhibitor of real-time data collection in practice. In this paper, we review the different uses of metering data in the smart grid and the related privacy legislation. We then provide a structured overview, shortcomings, recommendations, and research directions of security solutions that are needed for privacy-preserving meter data delivery and management. We finally survey recent work on privacy-preserving technologies for meter data collection for the three application areas: 1) billing; 2) operations; and 3) value-added services including demand response.

Smart Meter Data Privacy: A Survey

We present Tweet4act, a system to detect and classify crisis-related messages communicated over a microblogging platform. Our system relies on extracting content features from each message. These features and the use of an incident-specific dictionary allow us to determine the period type of an incident that each message belongs to. The period types are: pre-incident (messages talking about prevention, mitigation, and preparedness), during-incident (messages sent while the incident is taking place), and post-incident (messages related to the response, recovery, and reconstruction). We show that our detection method can effectively identify incident-related messages with high precision and recall, and that our incident-period classification method outperforms standard machine learning classification methods.

/pdf/tweet4act-using-incident-specific-profiles-for-classifying-1wffgdi734.pdf

Muhammad Rizwan Asghar

Papers

Smart Meter Data Privacy: A Survey

Tweet4act: Using Incident-Specific Profiles for Classifying Crisis-Related Messages

Security and privacy in vehicular communications: Challenges and opportunities

Cybersecurity in Industrial Control Systems: Issues, Technologies, and Challenges

Prospects of zinc solubilizing bacteria for enhancing growth of maize.