Formatives Assessment gilt als eines der wirksamsten Rahmenkonzepte zur Förderung schulischen Lernens. Es bezeichnet die lernbegleitende Beurteilung von Schülerleistung mit dem Ziel, diagnostische Informationen zu nutzen, um Unterricht und Lernen zu verbessern. Grundlegende Merkmale von formativem Assessment sind die Klärung von Lernzielen, die Diagnose der individuellen Leistung sowie eine darauf...
against terrorism. To achieve such goals we need to use Feature extraction techniques that are speaker independent and for detecting occurrences we propose to use approximate string matching techniques normally used when searching for substrings in long DNA strings allowing errors. We adapted feature extraction methods used
Die naturwissenschaftliche Bildung ist wieder vermehrt in den Fokus fachdidaktischer, erziehungswissenschaftlicher und politischer Diskussionen gerückt. In diesem Reviewartikel werden Schwerpunkte der naturwissenschaftsdidaktischen Forschung und Perspektiven der Entwicklung des naturwissenschaftlichen Unterrichts präsentiert. Dabei geht es einerseits um Ziele naturwissenschaftlicher Bildung, andererseits...
, service discovery and service selection operations for building SBSs based on keyword search. KS3 assists system engineers without detailed knowledge of SOA techniques in searching for component services to build SBSs by typing a few keywords that represent the tasks of the SBSs with quality constraints and optimisation
Ranking(PPSE) scheme that supports Top-k retrieval in stringent privacy requirements. For the first time, we formulate the privacy issue and design goals for personalized search in SE. We introduce the Open Directory Project to construct a formal model for integrating preferential ranking with keyword search reasonably and
Efficient multi-keyword fuzzy search over encrypted data is a desirable technology for data outsourcing in cloud storage. The current solutions can only support part of these goals. In this paper, we propose a novel encrypted data searching scheme that can support multiples keywords fuzzy search with high efficiency
% to 75% with Scopus being the most precise.Cited reference searches were more sensitive than keyword searches, making it a more comprehensive strategy to identify all studies that use a particular instrument. Keyword searches provide a quick way of finding some but not all relevant articles. Goals, time, and resources
keywords for a given topic by reading representative documents on diverse aspects of the topic. Using a crowdsourced pilot study, we compare the learning outcomes of users across four conditions corresponding to rankings that optimize for different levels of keyword density. We find that adding keyword density to the
as well as range query on cloud encrypted data through two-layered BFs per document. Extensive security analysis and experimental results on real-world data set show that our proposed scheme can securely reach the design goals for keyword search on encrypted data. To the best of our knowledge, this is the first try to
customers for fear of risks of single‐point failure threats and potential malicious insiders. To this end, we propose two efficient keyword search over encrypted data in multi‐cloud setting schemes which exploit Identity‐Based Encryption (IBE) and Key‐Policy Attribute‐Based Encryption (KP‐ABE), respectively. Formal security
) procedures based on the descriptions of Web services. In addition, to check the effectiveness of the functional-goals tagged, we designed a goal-driven semantic service discovery algorithm and compared it with other approaches: keyword-based, ontology-based, and topic-based service discovery. As results, our proposed goal
With the fast growth of the Web, users often suffer from the problem of information overload since many existing search engines response lots of non-relevant documents containing query terms based on the search mechanism of keyword matching. In fact, it is eagerly expected by both users and search engine developers to
Nowadays, Internet is widely used by users to satisfy their various information needs. Whenever a user submits any query/topic/keyword to search engine, it provides a long list of results for same query. As a consequence of this, users have to spend a lot of time in searching information of his/her interest. Most of
explanations that are comprehensible to the learner and adequate to his/her background knowledge, needs and goals. They comprise grammaticality judgments, in-class comparison of well-formed examples for rule identification, explicit corrective (peer) feedback and discussion of multiple-choice items and gap-fills.
IT industry is booming. So, the requirement for resources is also on the increase. Industry requires more processing power and storage capability to meet their goal. Here, Cloud Computing comes in the picture, it provides IT industry the much-needed resources on a large scale at low cost and makes their task easy
through weakly supervised non-negative matrix factorization (NMF). The goal of this study is to investigate how we can improve word learning when the number of interaction examples is low. We demonstrate two approaches to train NMF models on scarce data: 1) training word models using smoothed training data, and 2) training
information, to our system for providing appropriate services to users. For achieving the design goal, we first collected motion logs. We collected the motion data from motion sensing input device. Life logs can then be created from these motion logs. We discuss different service modes of our information community system. The
Financed by the National Centre for Research and Development under grant No. SP/I/1/77065/10 by the strategic scientific research and experimental development program:
SYNAT - “Interdisciplinary System for Interactive Scientific and Scientific-Technical Information”.