Ambiguity is a major problem of software errors because much of the requirements specification is written in a natural language format. Therefore, it is hard to identify consistencies because this format is too ambigu...
详细信息
In recent years a huge number of online auctions that use Multi Agent systems have been created. As a result there are numerous auctions that provide the same product. In this case each customer can buy a product with...
详细信息
ISBN:
(纸本)1565553195
In recent years a huge number of online auctions that use Multi Agent systems have been created. As a result there are numerous auctions that provide the same product. In this case each customer can buy a product with the lowest possible price. But searching between auctions in terms of finding the suitable product can be time consuming for consumers and also providing products in different markets is a difficult task for suppliers. So the need for an autonomous agent in these types of markets is deeply felt. On the other side the structure of an auction mechanism that provides the environment for traders to operate their trades is vital. Despite all the research that has been done about online auctions, most of them were about single markets. But in real world the stocks and commodities of companies are listed and traded in different markets. There is a growing tendency towards research about online auctions and Market Design. Particularly in recent years CAT (CATallactics) game has provided an important opportunity to develop and test new techniques in this field. In this paper after introducing CAT game and PersianCAT agent, we want to challenge the conventional accepting policy used in stock markets like New York Stock Exchange and provide a better solution that improves the general performance of the markets.
Single Carrier Transmission (SCT) is a competing technique for Orthogonal Frequency Division Multiplexing (OFDM) in Broadband Wireless systems (BWS). Recent developments in Frequency Domain Equalization (FDE) using De...
详细信息
In complex and dynamic environments where interdependencies cannot monotonously determine causality, data mining techniques may be employed in order to analyze the problem, extract key features and identify pivotal fa...
详细信息
The delay of a circuit implemented in a Lookup table (LUT) based Field-Programmable Gate Arrays (FPGAs) is a combination of routing delays, and logic block delays. However most of an FPGA's area is devoted to prog...
详细信息
The focus of this paper is a construction of better knowledge base in case-based classifier system. Our knowledge base structure is based on concept lattice where rules are built from its subconcept-superconcept relat...
详细信息
ISBN:
(纸本)9781605580463
The focus of this paper is a construction of better knowledge base in case-based classifier system. Our knowledge base structure is based on concept lattice where rules are built from its subconcept-superconcept relation. Since the lattice can only be constructed from inputs with binary attributes, descriptive and numeric attributes must be transformed to binary attributes. In this paper, we propose the transformation of numeric attributes to descriptive attributes using fuzzy set theory. We experiment on benchmark data sets, Car and Iris, to determine the performance in term of number of rules used and classification precision. The results show that trend of accuracy is proportional to the size of learning inputs. The number of rules used is relatively small compared with size of training data. Our case-based classifier produces very promising results in practice and can classify the new problem more accurate than traditional classifiers. Copyright 2008 ACM.
The duality between document and word clustering naturally leads to the consideration of storing the document dataset in a bipartite. With documents and words modeled as vertices on two sides respectively, partitionin...
详细信息
Jane sees 50 compiler errors as a challenge. John sees them as defeat. Psychology research suggests these contrasting reactions may stem from students' self-theories, or their beliefs about themselves. Jane's ...
详细信息
ISBN:
(纸本)9781605582160
Jane sees 50 compiler errors as a challenge. John sees them as defeat. Psychology research suggests these contrasting reactions may stem from students' self-theories, or their beliefs about themselves. Jane's reaction is characteristic of a growth mindset, the idea that with hard work and persistence, one's intelligence can increase. John's behavior is in line with a fixed mindset, the belief that individuals are born with a certain amount of intelligence and there is little they can do to change it. Numerous studies of self-theories have shown that students with a growth mindset perform better in academic settings;they cope more effectively with challenges, maintain higher grades, and are less susceptible to stereotype threat. In this study we attempted a "saying is believing" intervention to encourage CS1 students to adopt a growth mindset both in general and towards programming. Despite notable success of this type of intervention in a non-CS context, our results offered few statistically significant differences both from pre-survey to post-survey and between control and intervention groups. Further, the statistically significant results we did find differed in direction between institutions (some students exhibited more growth response, others less). We analyzed further evidence to explore possible confounding issues including whether our intervention even registered with students and how students interpreted the questions which we used to assess their self-theories. Copyright 2008 ACM.
This paper investigates the applicability of Gaussian processes (GP) classification for recognition of articulated and deformable human motions from image sequences. Using tensor subspace analysis (TSA), space-time hu...
详细信息
ISBN:
(纸本)9781424421749
This paper investigates the applicability of Gaussian processes (GP) classification for recognition of articulated and deformable human motions from image sequences. Using tensor subspace analysis (TSA), space-time human silhouettes (extracted from motion videos) are transformed to low-dimensional multivariate time series, based on which structure-based statistical features are calculated to summarize the motion properties. GP classification is then used to learn and predict motion categories. Experimental results on two real-world state-of-the-art datasets show that the proposed approach is effective, and outperforms support vector machine (SVM).
暂无评论