snu-aidas/HVMap-dataset huggingface dataset:
Are Slice-Based Cohesion Metrics Actually Useful in Effort-Aware Post-Release Fault-Proneness Prediction? An Empirical Study

Background. Slice-based cohesion metrics leverage program slices with respect to the output variables of a module to quantify the strength of functional relatedness of the elements within the module. Although slice-based cohesion metrics have been proposed for many years, few empirical studies have been conducted to examine their actual usefulness in predicting fault-proneness. Objective. We aim to provide an in-depth understanding of the ability of slice-based cohesion metrics in effort-aware post-release fault-proneness prediction, i.e. their effectiveness in helping practitioners find post-release faults when taking into account the effort needed to test or inspect the code. Method. We use the most commonly used code and process metrics, including size, structural complexity, Halstead's software science, and code churn metrics, as the baseline metrics. First, we employ principal component analysis to analyze the relationships between slice-based cohesion metrics and the baseline metrics. Then, we use univariate prediction models to investigate the correlations between slice-based cohesion metrics and post-release fault-proneness. Finally, we build multivariate prediction models to examine the effectiveness of slice-based cohesion metrics in effort-aware post-release fault-proneness prediction when used alone or used together with the baseline code and process metrics. Results. Based on open-source software systems, our results show that: 1) slice-based cohesion metrics are not redundant with respect to the baseline code and process metrics; 2) most slice-based cohesion metrics are significantly negatively related to post-release fault-proneness; 3) slice-based cohesion metrics in general do not outperform the baseline metrics when predicting post-release fault-proneness; and 4) when used with the baseline metrics together, however, slice-based cohesion metrics can produce a statistically significant and practically important improvement of the effectiveness in effort-aware post-release fault-proneness prediction. Conclusion. Slice-based cohesion metrics are complementary to the most commonly used code and process metrics and are of practical value in the context of effort-aware post-release fault-proneness prediction.
Forecasting emerging technologies : Use of bibliometrics and patent analysis

It is rather difficult to forecast emerging technologies as there is no historical data available. In such cases, the use of bibliometrics and patent analysis have provided useful data. This paper presents the forecasts for three emerging technology areas by integrating the use of bibliometrics and patent analysis into well-known technology forecasting tools such as scenario planning, growth curves and analogies. System dynamics is also used to be able to model the dynamic ecosystem of the technologies and their diffusion. Technologies being forecasted are fuel cell, food safety and optical storage technologies. Results from these three applications help us to validate the proposed methods as appropriate tools to forecast emerging technologies. © 2006 Elsevier Inc. All rights reserved.
Food-related illness and death in the United States.

Letters Letters Letters Letters Letters correctly identified E. faecium and E. faecalis to the species level, most (4 of 5) did not correctly identify E. gallinarum (three misidentified it as E. casseliflavus and one as E. faecalis). The results of this study are consistent with those of previous studies in the United States (4,5), South America (6), Spain (7), and Mexico (8). Although in countries like Chile, disk diffusion is practical and reliable for most susceptibility testing, detecting low-level vanco-mycin resistance in enterocci is difficult without supplementary testing. In Chile, as in other countries, strategies should be implemented to improve detection of these strains, including improvement of phenotypical and genotypical methods for VRE detection and species identification. Documentation of proficiency in detecting VRE is important for improving laboratory performance, detecting clinical isolates, and accurate and reliable reporting to local, national, and international surveillance systems. A, Febre N, et al. Epidemiologic analysis for acquisition of vancomycin-resistant enterococcus (VRE) in an intensive care unit in Brazil. Altschuler M, et al. Study to determine the ability of clinical laboratories to detect antimicrobial-resistant To the Editor: Dr. Mead and colleagues should be commended for attempting to estimate the prevalence of foodborne disease in the United States (1). Their study provides more complete estimates than previous studies in terms of the number of foodborne pathogens included; for example, it includes the first realistic estimate of the number of cases of disease due to Norwalk-like caliciviruses. However, the publication of these estimates raises some important issues. Even though " accurate estimates of disease burden are the foundation of sound public health policy " (2), most of these estimates (in particular, the assumption that unknown agents are transmitted by food in the same proportion as known agents) were derived from assumptions rather than data. Known foodborne agents clearly cannot account for most gastrointestinal illnesses (1). However, illnesses from unknown agents may be as likely to have the transmission characteristics of rotavirus (1% foodborne) or Cryptosporidium (10% foodborne) as those of the Norwalk-like viruses (40% foodborne). Furthermore , it was assumed that detecting outbreaks or cases of toxin-mediated illnesses (e.g., due to Bacillus cereus, Staphylococcus aureus, or Clostridium perfringens) follows the model of Salmonella. In the authors' entire list of known foodborne agents, data are presented for cases identified both from outbreaks and active surveillance for only three agents: Salmonella, Shigella, and Campylobacter. Salmonella is clearly the most …
Tadalafil therapy for pulmonary arterial hypertension.

BACKGROUND
Treatment options for pulmonary arterial hypertension target the prostacyclin, endothelin, or nitric oxide pathways. Tadalafil, a phosphodiesterase type-5 inhibitor, increases cGMP, the final mediator in the nitric oxide pathway.


METHODS AND RESULTS
In this 16-week, double-blind, placebo-controlled study, 405 patients with pulmonary arterial hypertension (idiopathic or associated), either treatment-naive or on background therapy with the endothelin receptor antagonist bosentan, were randomized to placebo or tadalafil 2.5, 10, 20, or 40 mg orally once daily. The primary end point was the change from baseline to week 16 in the distance walked in 6 minutes. Changes in World Health Organization functional class, clinical worsening, and health-related quality of life were also assessed. Patients completing the 16-week study could enter a long-term extension study. Tadalafil increased the distance walked in 6 minutes in a dose-dependent manner; only the 40-mg dose met the prespecified level of statistical significance (P<0.01). Overall, the mean placebo-corrected treatment effect was 33 m (95% confidence interval, 15 to 50 m). In the bosentan-naive group, the treatment effect was 44 m (95% confidence interval, 20 to 69 m) compared with 23 m (95% confidence interval, -2 to 48 m) in patients on background bosentan therapy. Tadalafil 40 mg improved the time to clinical worsening (P=0.041), incidence of clinical worsening (68% relative risk reduction; P=0.038), and health-related quality of life. The changes in World Health Organization functional class were not statistically significant. The most common treatment-related adverse events reported with tadalafil were headache, myalgia, and flushing.


CONCLUSIONS
In patients with pulmonary arterial hypertension, tadalafil 40 mg was well tolerated and improved exercise capacity and quality of life measures and reduced clinical worsening.
Learning Automata as a Basis for Multi Agent Reinforcement Learning

Learning Automata (LA) are adaptive decision making devices suited for operation in unknown environments [12]. Originally they were developed in the area of mathematical psychology and used for modeling observed behavior. In its current form, LA are closely related to Reinforcement Learning (RL) approaches and most popular in the area of engineering. LA combine fast and accurate convergence with low computational complexity, and have been applied to a broad range of modeling and control problems. However, the intuitive, yet analytically tractable concept of learning automata makes them also very suitable as a theoretical framework for Multi agent Reinforcement Learning (MARL). Reinforcement Learning (RL) is already an established and profound theoretical framework for learning in stand-alone or single-agent systems. Yet, extending RL to multi-agent systems (MAS) does not guarantee the same theoretical grounding. As long as the environment an agent is experiencing is Markov, and the agent can experiment sufficiently, RL guarantees convergence to the optimal strategy. In a MAS however, the reinforcement an agent receives, may depend on the actions taken by the other agents acting in the same environment. Hence, the Markov property no longer holds. And as such, guarantees of convergence are lost. In the light of the above problem it is important to fully understand the dynamics of multi-agent reinforcement learning. Although, they are not fully recognized as such, LA are valuable tools for current MARL research. LA are updated strictly on the basis of the response of the environment, and not on the basis of any knowledge regarding other automata, i.e. nor their strategies, nor their feedback. As such LA agents are very simple. Moreover, LA can be treated analytically. Convergence proofs do exist for a variety of settings ranging from a single automaton model acting in a simple stationary random environment to a distributed automata model interacting in a complex environment. In this paper we argue that LA are very interesting building blocks for learning in multi agent systems. The LA can be viewed as policy iterators, who update their action probabilities based on private information only. This is a very attractive property in applications where communication is expensive. LA are in particular appealing in games with stochastic payoffs. Then we move to collections of learning automata, that can independently converge to interesting solution concepts. We study the single stage setting, including the analytical results. Then we generalize to interconnected learning automata, that can deal with multi agent multi-stage problems. We also show how Ant Colony Optimization can be mapped to the interconnected Learning Automata setting. This extended abstract is a summary of an article published earlier [14].
A New Approach of copy move Forgery Detection using Rigorous Preprocessing and Feature Extraction

these days, advanced pictures are being used in an extensive variety of uses and for numerous reasons. They additionally assume an imperative part in the capacity and exchange of visual data, particularly the mystery ones. With this far reaching utilization of advanced pictures, notwithstanding the expanding number of devices and programming of computerized pictures altering, it has turned out to be anything but difficult to control and change the real data of the picture. In this way, it has turned out to be important to check the credibility and the respectability of the picture by utilizing present day and advanced methods, which add to examination and comprehension of the pictures’ substance, and after that ensure their trustworthiness. There are many sorts of picture imitation, the most critical and prominent sort is called duplicate glue fabrication, which utilizes a similar picture during the time spent falsification. This sort of fraud is utilized for one of two things, first to cover a protest or scene by replicating the region of the picture and gluing it on another zone of a similar picture. In this paper we have presented a new approach of copy move forgery detection. proposed scheme uses Oriented FAST and rotated BRIEF(ORB) alternative of scale invariant feature transform (SIFT) technique which is integrated with modified local contrast modification-contrast limited adaptive histogram equalization(LCM-CLAHE). Experimental results shows that proposed scheme is more promising in terms of false positive rate(FPR) and true positive rate(TPR) compare to state of the art techniques. Keywords— Image Processing, Image Enhancement, Histogram Equalization, SIFT, TPR, FPR, Copy move forgery, ORB
Face recognition using PCA-based method

The objective of this paper is to develop the image processing and recognize the faces using PCA-based face recognition technique. MATLAB based programs are implemented to identify the faces using Indian databases and the Face recognition data, University of Essex, UK. For matching unknown images with known images, different techniques like sum of absolute difference (SAD), sum of squared difference (SSD), normalized cross correlation (NCC) etc. can be used which has been shown in this paper. Finally, it has been shown that the performance of PCA-based face recognition system is quite satisfactory instead of having some shortcomings of the system. (Abstract)
Prediction of Rainfall Time Series Using Modular Artificial Neural Networks Coupled with Data Preprocessing Techniques

1 Dept. of Civil and Structural Engineering, Hong Kong Polytechnic University, 4 Hung Hom, Kowloon, Hong Kong, People’s Republic of China 5 6 2 Changjiang Institute of Survey, Planning, Design and Research, 7 Changjiang Water Resources Commission, 8 430010, Wuhan, HuBei, People’s Republic of China 9 10 3 Department of Civil Engineering, Ryerson University, 11 350 Victoria Street, Toronto, Ontario, Canada, M5B 2K3 12 13 *Email: cekwchau@polyu.edu.hk 14 15 ABSTRACT 16
INTEGRATION OF BIM AND GIS : THE DEVELOPMENT OF THE CITYGML GEOBIM EXTENSION

There is a growing interest in the integration of BIM and GIS. However, most of the research is focused on importing BIM data in GIS applications and vice versa. Real integration of BIM and GIS is using the strong parts of the GIS technology in BIM, and of course the strong parts from BIM technology in GIS. In this paper a mix of strong parts from both worlds is integrated in a single project. The paper describes the development of a CityGML extension called GeoBIM to get semantic IFC data into a GIS context. The conversion of IFC to CityGML (including the GeoBIM extension) is implemented in the open source Building Information Modelserver. This contribution was selected in a double blind review process to be published within the Lecture Notes in Geoinformation and Cartography series (Springer-Verlag, Heidelberg). Advances in 3D Geo-Information Sciences Kolbe, Thomas H.; König, Gerhard; Nagel, Claus (Eds.) 2011, X ISBN 978-3-642-12669-7, Hardcover Date of Publication: January 5, 2011 Series Editors: Cartwright, W., Gartner, G., Meng, L., Peterson, M.P. ISSN: 1863-2246 International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXVIII-4/W15 5th International 3D GeoInfo Conference, November 3-4, 2010, Berlin, Germany 193
An investigation into the applicability of building information models in geospatial environment in support of site selection and fire response management processes

1474-0346/$ see front matter 2008 Elsevier Ltd. A doi:10.1016/j.aei.2008.06.001 * Corresponding author. Tel.: +90 312 266 00 5 (U. Isikdag); tel.: +44 161 295 62 90; fax: +44 016 tel.: +44 0161 295 4992; fax: +44 0161 295 3173 (G. E-mail addresses: egetera@superonline.com, uisik j.underwood@salford.ac.uk (J. Underwood), g.aoauad@ Some tasks in the construction industry and urban management field such as site selection and fire response management are usually managed by using a Geographical Information System (GIS), as the tasks in these processes require a high level and amount of integrated geospatial information. Recently, a key element of this integrated geospatial information to emerge is detailed geometrical and semantic information about buildings. In parallel, Building Information Models (BIMs) of today have the capacity for storing and representing such detailed geometrical and semantic information. In this context, the research aimed to investigate the applicability of BIMs in geospatial environment by focusing specifically on these two domains; site selection and fire response management. In the first phase of the research two use case scenarios were developed in order to understand the processes in these domains in a more detailed manner and to establish the scope of a possible software development for transferring information from BIMs into the geospatial environment. In the following phase of the research two data models were developed – a Schema-Level Model View and a geospatial data model. The Schema-Level Model View was used in simplifying the information acquired from the BIM, while the geospatial data model acted as the template for creating physical files and databases in the geospatial environment. Following this, three software components to transfer building information into the geospatial environment were designed, developed, and validated. The first component served for acquiring the building information from the BIM, while the latter two served for transforming the information into the geospatial environment. The overall research demonstrated that it is possible to transfer (high level of geometric and semantic) information acquired from BIMs into the geospatial environment. The results also demonstrated that BIMs provide a sufficient level and amount of (geometric and semantic) information (about the building) for the seamless automation of data management tasks in the site selection and fire response management processes. 2008 Elsevier Ltd. All rights reserved.
How to Play any Mental Game or A Completeness Theorem for Protocols with Honest Majority

We present a polynomial-time algorithm that, given as a input the description of a game with incomplete information and any number of players, produces a protocol for playing the game that leaks no partial information, provided the majority of the players is honest.
Our algorithm automatically solves all the multi-party protocol problems addressed in complexity-based cryptography during the last 10 years. It actually is a completeness theorem for the class of distributed protocols with honest majority. Such completeness theorem is optimal in the sense that, if the majority of the players is not honest, some protocol problems have no efficient solution [C].
Counting Graphlets: Space vs Time

Counting graphlets is a well-studied problem in graph mining and social network analysis. Recently, several papers explored very simple and natural approaches based on Monte Carlo sampling of Markov Chains (MC), and reported encouraging results. We show, perhaps surprisingly, that this approach is outperformed by a carefully engineered version of color coding (CC) [1], a sophisticated algorithmic technique that we extend to the case of graphlet sampling and for which we prove strong statistical guarantees. Our computational experiments on graphs with millions of nodes show CC to be more accurate than MC. Furthermore, we formally show that the mixing time of the MC approach is too high in general, even when the input graph has high conductance. All this comes at a price however. While MC is very efficient in terms of space, CC's memory requirements become demanding when the size of the input graph and that of the graphlets grow. And yet, our experiments show that a careful implementation of CC can push the limits of the state of the art, both in terms of the size of the input graph and of that of the graphlets.
Clustering versus faceted categories for information exploration

Information seekers often express a desire for a user interface that organizes search results into meaningful groups, in order to help make sense of the results, and to help decide what to do next. A longitudinal study in which participants were provided with the ability to group search results found they changed their search habits in response to having the grouping mechanism available [2]. There are many open research questions about how to generate useful groupings and how to design interfaces to support exploration using grouping. Currently two methods are quite popular: clustering and faceted categorization. Here, I describe both approaches and summarize their advantages and disadvantages based on the results of usability studies. Clustering refers to the grouping of items according to some measure of similarity. In document clustering, similarity is typically computed using associations and commonalities among features, where features are typically words and phrases [1]. One of the better implementations of clustering of Web results can be found at Clusty.com. The greatest advantage of clustering is that it is fully automatable and can be easily applied to any text collection. Clustering can also reveal interesting and potentially unexpected or new trends in a group of documents. A query on “New Orleans”’ run on Clusty.com on Sept. 16, 2005 (shortly after the devastation wreaked by Hurricane Katrina), revealed a top-ranked cluster titled Hurricane, followed by the more standard groupings of Hotels, Louisiana, University, and Mardi Gras. Clustering can be useful for clarifying and sharpening a vague query, by showing users the dominant themes of the returned results [2]. Clustering also works well for disambiguating ambiguous queries; particularly acronyms. For example, ACL can stand for Anterior Cruciate Ligament, Association for Computational Linguistics, Atlantic Coast Line Railroad, among others. Unfortunately, because clustering algorithms are imperfect, they do not neatly group all occurrences of each acronym into one cluster, nor do they allow users to issue follow-up queries that only return documents from the intended sense (for example, “ACL meeting” will return meetings for multiple senses of the term). By Marti A. Hearst
On The Architecture Scheduling Problem Of Industry 4.0

The recently emerged Fourth Industrial Revolution (Industry 4.0) is characterised by the introduction of the new Cyber-Physical System (CPS) concepts and the Internet of Things (IoT) paradigm. These new collaborating computational entities offer a broad range of opportunity to consider with a different perspective. One of the perennial problems of the manufacturing operation is the scheduling problem of typical job-shop manufacturing systems. Starting from a comparison with the typical architecture of an operating systems scheduler module, we introduce a new manufacturing scheduling architecture. Overcoming the typical Full-Hierarchical configuration defined in the ANSI/ISA 95 in favour of a SemiHeterarchical one, the introduced scheduling architecture leads to a mixture of proactive and reactive approach to the Job-shop Scheduling Problem (JSP), taking advantage from both the common decentralised and the centralised methodology. Keywords— Industry 4.0; Cyber-Physical System (CPS); JobShop Scheduling Problem; Manufacturing System; System of