Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Fusion of Local Statistical Parameters for Buried Underwater Mine Detection in Sonar Imaging
What are anomalies/outliers?
The set of data points that are considerably different than the remainder of the data
Variants of Anomaly/Outlier Detection Problems
Given a database D, find all the data points x D with anomaly scores greater than some threshold t
Given a database D, find all the data points x D having the top-n largest anomaly scores f(x)
Given a database D, containing mostly normal (but unlabeled) data points, and a test point x, compute the anomaly score of x with respect to D
Credit card fraud detection, telecommunication fraud detection, netwo...
Various text mining algorithms require the process of feature selection. High-level semantically rich features, such as ﬁgurative language uses, speech errors etc., are very promising for such problems as e.g. writing style detection, but automatic extraction of such features is a big challenge. In this paper, we propose a framework for ﬁgurative language use detection.
We introduce an error mining technique for automatically detecting errors in resources that are used in parsing systems. We applied this technique on parsing results produced on several million words by two distinct parsing systems, which share the syntactic lexicon and the pre-parsing processing chain. We were thus able to identify missing and erroneous information in these resources.
In this paper, we present a novel approach for automatic summarization. Our system, called CBSEAS, integrates a new method to detect redundancy at its very core, and produce more expressive summaries than previous approaches. Moreover, we show that our system is versatile enough to integrate opinion mining techniques, so that it is capable of producing opinion oriented summaries. The very competitive results obtained during the last Text Evaluation Conference (TAC 2008) show that our approach is efﬁcient. ...
We present a web tool that allows users to explore news stories concerning the 2012 US Presidential Elections via an interactive interface. The tool is based on concepts of “narrative analysis”, where the key actors of a narration are identiﬁed, along with their relations, in what are sometimes called “semantic triplets” (one example of a triplet of this kind is “Romney Criticised Obama”).
Mining retrospective events from text streams has been an important research topic. Classic text representation model (i.e., vector space model) cannot model temporal aspects of documents. To address it, we proposed a novel burst-based text representation model, denoted as BurstVSM. BurstVSM corresponds dimensions to bursty features instead of terms, which can capture semantic and temporal information.
Social Event Radar is a new social networking-based service platform, that aim to alert as well as monitor any merchandise flaws, food-safety related issues, unexpected eruption of diseases or campaign issues towards to the Government, enterprises of any kind or election parties, through keyword expansion detection module, using bilingual sentiment opinion analysis tool kit to conclude the specific event social dashboard and deliver the outcome helping authorities to plan “risk control” strategy. ...
Weblogs are a source of human activity knowledge comprising valuable information such as facts, opinions and personal experiences. In this paper, we propose a method for mining personal experiences from a large set of weblogs. We define experience as knowledge embedded in a collection of activities or events which an individual or group has actually undergone.
In Cross-Language Information Retrieval (CLIR), Out-of-Vocabulary (OOV) detection and translation pair relevance evaluation still remain as key problems. In this paper, an English-Chinese Bi-Directional OOV translation model is presented, which utilizes Web mining as the corpus source to collect translation pairs and combines supervised learning to evaluate their association degree.
This paper studies the problem of identifying erroneous/correct sentences. The problem has important applications, e.g., providing feedback for writers of English as a Second Language, controlling the quality of parallel bilingual sentences mined from the Web, and evaluating machine translation results. In this paper, we propose a new approach to detecting erroneous sentences by integrating pattern discovery with supervised learning models. Experimental results show that our techniques are promising. ...
database maintained by the National Library of Medicine1 (NLM), which incorporates around 40,000 Health Sciences papers each month. Researchers depend on these electronic resources to keep abreast of their rapidly changing field. In order to maintain and update vital indexing references such as the Unified Medical Language System (UMLS) resources, the MeSH and SPECIALIST vocabularies, the NLM staff needs to review 400,000 highly-technical papers each year.
United Nation Department of Human Affairs (UNDHA) assesses that there are more than 100 million mines that are scattered across the world and pose significant hazards in more than 68 countries. The international Committee of the Red Cross (ICRC) estimates that the casualty rate from landmines currently exceeds 26,000 persons every year.
Landmines and explosive remnants of war (ERW), which include unexploded ordnance
(UXO) and abandoned explosive ordnance, represent a major threat to civilian. This
demands that all the mines and ERW affecting the places where ordinary people live must
be cleared, and safety of people in areas that have been cleared must be guaranteed.
Automatic Clustering Detection - Khi con người cố gắng làm cho ý nghĩa của các câu hỏi phức tạp, xu hướng tự nhiên của chúng tôi là để phá vỡ đối tượng thành những miếng nhỏ hơn, mỗi trong số đó có thể được giải thích đơn giản hơn. Clustering là một kỹ thuật được sử dụng để kết hợp các đối tượng quan sát thành các nhóm, cụm sao cho: Mỗi nhóm hoặc cụm được đồng nhất hoặc nhỏ gọn đối với một số đặc điểm.
Contrary to popular perception, the New Zealand economy has a lower proportion of employees
in small to medium-sized enterprises (19 or fewer employees) than the OECD mean and has
a similar proportion of large ﬁ rms to the OECD mean. However, New Zealand’s large ﬁ rms are
smaller than the OECD mean, suggesting that New Zealand has fewer very large ﬁ rms.
Labour productivity levels differ substantially across the New Zealand industries.
At low levels of development measured by per capita GDP, environment pollution will
increase. As a country reaches a certain level of GDP, environmental pollution tends to
decrease as income increases.
The Environmental Kuznets Curve (EKC) basically describes the relationship
between the concentrations of air pollution in the country relative to its gross national income
per capita. It is stated that as a country starts to develop (as depicted by the increase of
GNP/capita), air pollution level rises due to the increase in production of commodities.
Our estimated results are therefore consistent and
free frombias. Fourth,we investigate the impact of amore comprehensive set
of demographic factors on pollution including the age composition, the
urbanization rate and the average household size.Many existing econometric
studies neglect demographic factors other than total population size. Parikh
and Shukla’s (1995) analysis of the effect of the urbanization rate on energy
use and greenhouse gas emissions in developing countries represents a
notable exception in this regard....
Although the basic approach appears to be simple, devel-
oping a comprehensive solution in which devices rely on the
geo-location service to determine white spaces availability is
non-trivial. This is because our design introduces some unique
challenges that must be overcome.
A key issue in a network such as SenseLess is that it
must continue to afford the same protection to incumbents
as spectrum sensing would. This challenge coupled with all
WSDs having to rely on a database to discover white spaces
is a signiﬁcant departure from conventional network designs.
Because of the asymptomatic process of carcinogenesis, the early detection
of cancers such as hepatocellular carcinoma (HCC) is very challenging.
Tumor-prone transgenic mouse models of oncogenesis can provide a stable
and powerful tool for the analysis of cancer initiation, and are therefore
promising for the discovery of early putative biomarkers of HCC.