Countering imbalanced datasets to improve adverse drug event predictive models in labor and delivery Background: The IOM report, Preventing Medication Errors, emphasizes the overall lack of knowledge of the incidence of adverse drug events (ADE). Operating rooms, emergency departments and intensive care units are known to have a higher incidence of ADE. Labor and delivery (L&D) is an emergency care unit that could have an increased risk of ADE, where reported rates remain low and under-reporting is suspected. Risk factor identification with electronic pattern recognition techniques could improve ADE detection rates. Objective: The objective of the present study is to apply Synthetic Minority Over Sampling Technique (SMOTE) as an enhanced sampling method in a sparse dataset to generate prediction models to identify ADE in women admitted for labor and delivery based on patient risk factors and comorbidities. Results: By creating synthetic cases with the SMOTE algorithm and using a 10-fold cross-validation technique, we demonstrated improved performance of the Naïve Bayes and the decision tree algorithms. The true positive rate (TPR) of 0.32 in the raw dataset increased to 0.67 in the 800% over-sampled dataset. Conclusion: Enhanced performance from classification algorithms can be attained with the use of synthetic minority class oversampling techniques in sparse clinical datasets. Predictive models created in this manner can be used to develop evidence based ADE monitoring systems.Ó 2008 Elsevier Inc. All rights reserved.The Institute of Medicine (IOM) in the report, Preventing Medication Errors [1] recommended the implementation of decision support tools derived from evidence based knowledge and patient information as part of the strategies to prevent medication errors (ME). The report also recommended the active monitoring of medication use to promote prevention strategies. Although medical research has actively pursued these problems, the reported incidence of ME is suspected to be under-estimated [1] [2] [3] .These IOM reports [1,2] define ME as avoidable errors occurring in the medication use process. Adverse drug event (ADE) is a more inclusive definition that covers both ME and adverse drug reactions.Operating rooms, emergency departments and intensive care units are known to have a higher incidence of ADE [4] . Labor and delivery (L&D) areas are considered by quality assurance groups as special care units and pregnant women are considered by the FDA as a vulnerable group for ADE [1] . L&D provides emergency care and therefore should also be treated as a high risk area Studies published in the literature focus on specific drugs and anesthesiology events [5] [6] [7] [8] [9] . To the best of our knowledge there are no published studies of ADE as a general category in pregnant women. Our findings indicate an incidence of 0.34% of ADE in women admitted to L&D. This incidence is surprisingly low in a population that includes at least 10% of high risk pregnancies that require poly-pharmacy [10] .One of the most complex tasks in the design and development of automated decision support tools is evidence based rule generation and knowledge extraction from existing data [11] . The task is even more challenging in those cases where the class label of interest or ADE patients as in this case, has an incidence of 1% or less [12] . Datasets with these characteristics are also known as skewed or imbalanced datasets. The class of interest is relatively rare and there are important trade-offs in the decision between false negatives and/or false positives. Overall, it is more costly to have a false negative versus a false positive. More so in a medical application 1532-0464/$ -see front matter Ó The use of knowledge extraction techniques in clinical applications with sparse data is prone to failure without further data manipulation. Enhanced performance from classification algorithms can be attained with the use of SMOTE in the clinical setting as demonstrated in this study and previously reported by other clinical specialties [14] . Models obtained through this methodology can be used as starting points to develop prediction models for future experiments that will ultimately aid in the development of automatic reporting tools. The importance of developing automatic detection tools for ADE has been widely emphasized [29] . The current low ADE reporting rate creates unbalanced datasets that are very difficult to analyze and use for automatic rule extraction. Electronic methods used for knowledge extraction are likely to fail as demonstrated by the evaluation of the classifiers in the raw dataset. Alternative data manipulation methodologies are a subject of current research in disciplines outside of medicine where it is also necessary to develop knowledge bases to predict rare occurrences of an event [12] . Sparse data sets that would otherwise be useless can be used to create the starting point of evidence based electronic systems. Predictive models created in this manner can be used to develop evidence based ADE monitoring systems with the potential to increase ADE detection.. Increased detection of patients at risk for ADE can lead to changes in patient care protocols and improve patient safety and quality of care. One role of biomedical informatics is to evaluate these methodologies and determine the usability in the clinical arena [20, [30] [31] [32] [33] .. The use of ICD9 coded data for clinical research has been controversial. However, multiple research studies have demonstrated its usefulness [14, 27] . In addition Yasmeen et al. proved the reliability of reports of disease incidence using such classification. It should be kept in mind that the resulting clinical classification is a general classification of risk factors and comorbidities with the limitations and short comings of a system as inespecific as ICD9. Nonetheless, it can be used to create useful predictive models to automatically detect those patients at higher risk for ADE and even as an automatic method to detect disease incidence or study populations for further research.. Obstetric indicators report severe pregnancy induced hypertension, embolism and infection as the three leading causes for severe maternal morbidity and mortality [34, 35] . Our results show severe hypertension and wound infection as two of the leading factors for variability in the dataset. It is unclear to us why ''trauma" appears as the leading factor for variability since the incidence of trauma is extremely low. We can only speculate that it is because these patients are at higher risk for obstetrical complications such as embolism, infections and hemorrhage as reported in the literature [36] .. As noted in the introduction, existing methodologies for detection of ADE and AE in general are insufficient, under-reporting is suspected at all levels. We believe that the introduction of machine learning methods could have a promising future in this arena if we are able to create predictive models that could deal with clinical factors of low incidence like ADE. Machine learning methods are capable of detecting associations that are not evident when the prevalence is low. Clinical data are numerous, complex, can be confounding and noisy, as a consequence datasets of this nature are likely to be sparse and difficult to analyze. The introduction of boosting algorithms like SMOTE where the original structure of the data is maintained is promising and future research is necessary. However, for an real time automatic detection method to be reliable, the clinical data of interest would have to be coded in real time. Existing real time reports of Natural Language processing and detection of antidote drugs for ADE are promising [37, 38] . There were 106,480 cases that met the inclusion criteria and 371 ADE were identified based on the clinical classification previously described.. The demographic maternal characteristics as well as fetal outcomes showed no significant variation on ADE as indicated by the Eigenvalues of the PC. Surgical procedures (cesarean section and forceps) had the highest variation. Fifty-five independent comorbidities were identified and accounted for explaining 80% of the variation in the dataset and were used in the final model. The Institute of Medicine (IOM) in the report, Preventing Medication Errors [1] recommended the implementation of decision support tools derived from evidence based knowledge and patient information as part of the strategies to prevent medication errors (ME). The report also recommended the active monitoring of medication use to promote prevention strategies. Although medical research has actively pursued these problems, the reported incidence of ME is suspected to be under-estimated [1] [2] [3] .. These IOM reports [1, 2] define ME as avoidable errors occurring in the medication use process. Adverse drug event (ADE) is a more inclusive definition that covers both ME and adverse drug reactions.. Operating rooms, emergency departments and intensive care units are known to have a higher incidence of ADE [4] . Labor and delivery (L&D) areas are considered by quality assurance groups as special care units and pregnant women are considered by the FDA as a vulnerable group for ADE [1] . L&D provides emergency care and therefore should also be treated as a high risk area Studies published in the literature focus on specific drugs and anesthesiology events [5] [6] [7] [8] [9] . To the best of our knowledge there are no published studies of ADE as a general category in pregnant women. Our findings indicate an incidence of 0.34% of ADE in women admitted to L&D. This incidence is surprisingly low in a population that includes at least 10% of high risk pregnancies that require poly-pharmacy [10] .. One of the most complex tasks in the design and development of automated decision support tools is evidence based rule generation and knowledge extraction from existing data [11] . The task is even more challenging in those cases where the class label of interest or ADE patients as in this case, has an incidence of 1% or less [12] . Datasets with these characteristics are also known as skewed or imbalanced datasets. The class of interest is relatively rare and there are important trade-offs in the decision between false negatives and/or false positives. Overall, it is more costly to have a false negative versus a false positive. More so in a medical application where the interest is detecting patients with adverse outcomes that can be prevented. Without loss of generality, we will assume that the larger class or the majority class is the negative class and the class of interest is the minority (smaller) or positive class. We will use these terms inter-changeably in the paper. The use of machine learning algorithms in sparse datasets with class imbalance causes suboptimal classification performance as these techniques get overwhelmed by the majority class. Recent work has focused on sampling techniques that counter the problem of class imbalance by either oversampling the minority class or undersampling the majority class [12] [13] [14] [15] .. In this paper, we focus on the application of the Synthetic Minority Over Sampling Technique (SMOTE). SMOTE works by generating new instances from the existing cases. SMOTE effectively counters the imbalance in data by not only solving the problem of high class skew but also the problem of high sparsity. It works in the ''feature space'' rather than ''data space''. The synthetic samples are created by taking each minority class sample and the k nearest neighbors. The synthetic sample shares features of both the chosen minority class sample and one or more of the nearest neighbors. This approach effectively forces the decision region of the minority class to become more general. The synthetic cases will not only increase the data space but will also amplify the features of the minority class without duplicating the original data. SMOTE's effectiveness has been shown in a variety of domains and with a variety of classifiers [15, 16] .. The objective of the present study was to apply SMOTE as an enhanced sampling method using a sparse dataset and to identify a prediction model for ADE in women admitted for L&D based on patient risk factors and comorbidities. We would like to note here that we tried other of oversampling methods like replication and random under-sampling but none of them resulted in improvement. Hence, for clarity of presentation in the paper, we only focus our discussion and results on using SMOTE.

O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Quantum Property Testing of Group Solvability Abstract Testing efficiently whether a finite set with a binary operation · over it, given as an oracle, is a group is a well-known open problem in the field of property testing. Recently, Friedl, Ivanyos and Santha have made a significant step in the direction of solving this problem by showing that it is possible to test efficiently whether the input ( , ·) is an abelian group or is far, with respect to some distance, from any abelian group. In this paper, we make a step further and construct an efficient quantum algorithm that tests whether ( , ·) is a solvable group, or is far from any solvable group. More precisely, the number of queries used by our algorithm is polylogarithmic in the size of the set . Our algorithm appears in Fig. 1

O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Multi-core real-time scheduling for generalized parallel task models Abstract Multi-core processors offer a significant performance increase over singlecore processors. They have the potential to enable computation-intensive real-time applications with stringent timing constraints that cannot be met on traditional single-core processors. However, most results in traditional multiprocessor real-time scheduling are limited to sequential programming models and ignore intra-task parallelism. In this paper, we address the problem of scheduling periodic parallel tasks with implicit deadlines on multi-core processors. We first consider a synchronous task model where each task consists of segments, each segment having an arbitrary number of parallel threads that synchronize at the end of the segment. We propose a new task decomposition method that decomposes each parallel task into a set of sequential tasks. We prove that our task decomposition achieves a resource augmentation bound of 4 and 5 when the decomposed tasks are scheduled using global EDF and partitioned deadline monotonic scheduling, respectively. Finally, we extend our analysis to a directed acyclic graph (DAG) task model where each node in the DAG has a unit execution requirement. We show how these tasks can be converted into synchronous tasks such that the same decomposition can be applied and the same augmentation In recent years, multi-core processor technology has improved dramatically as chip manufacturers try to boost performance while minimizing power consumption. This development has shifted the scaling trends from increasing processor clock frequencies to increasing the number of cores per processor. For example, Intel has recently put 80 cores in a Teraflops Research Chip (Intel 2007 ) with a view to making it generally available, and ClearSpeed has developed a 96-core processor (ClearSpeed 2008) . While hardware technology is moving at a rapid pace, software and programming models have failed to keep pace. For example, Intel (2007) has set a time frame of 5 years to make their 80-core processor generally available due to the inability of current operating systems and software to exploit the benefits of multi-core processors.. As multi-core processors continue to scale, they provide an opportunity for performing more complex and computation-intensive tasks in real-time. However, to take full advantage of multi-core processing, these systems must exploit intra-task parallelism, where parallelizable real-time tasks can utilize multiple cores at the same time. By exploiting intra-task parallelism, multi-core processors can achieve significant real-time performance improvement over traditional single-core processors for many computation-intensive real-time applications such as video surveillance, radar tracking, and hybrid real-time structural testing (Huang et al. 2010) where the performance limitations of traditional single-core processors have been a major hurdle.. The growing importance of parallel task models for real-time applications poses new challenges to real-time scheduling theory that had previously mostly focused on sequential task models. The state-of-the-art work (Lakshmanan et al. 2010 ) on parallel scheduling for real-time tasks with intra-task parallelism analyzes the resource augmentation bound using partitioned Deadline Monotonic (DM) scheduling. A resource augmentation under a scheduling policy quantifies processor-speed up factor (how much we have to increase the processor speed) with respect to an optimal algorithm to guarantee the schedulability of a task set under that policy. The state-ofthe-art work (Lakshmanan et al. 2010) considers a synchronous task model, where each parallel task consists of a series of sequential or parallel segments. We call this model synchronous, since all the threads of a parallel segment must finish before the next segment starts, creating a synchronization point. However, that task model is restrictive in that, for every task, all the segments have an equal number of parallel threads, and the execution requirements of all threads in a segment are equal. Most importantly, in that task model, the number of threads in every segment is no greater than the total number of processor cores.. While the work presented by Lakshmanan et al. (2010) represents a promising step towards parallel real-time scheduling on multi-core processors, the restrictions on the task model make the solutions unsuitable for many real-time applications that often employ different numbers of threads in different segments of computation. In addition, it analyzes the resource augmentation bound under partitioned DM scheduling only, and does not consider other scheduling policies such as global EDF. In this work, we consider real-time scheduling on multi-core processors for a more general synchronous task model. Our tasks still contain segments where the threads of each segment synchronize at its end. However, in contrast to the restrictive task model addressed in Lakshmanan et al. (2010) , for any task in our model, each segment can contain an arbitrary number of parallel threads. That is, different segments of the same parallel task can contain different numbers of threads, and segments can contain more threads than the number of processor cores. Furthermore, the execution requirements of the threads in any segment can vary. This model is more portable, since the same task can be executed on machines with small as well as large numbers of cores. Specifically, our work makes the following new contributions to real-time scheduling for periodic parallel tasks.. -For the general synchronous task model, we propose a task decomposition algorithm that converts each implicit deadline parallel task into a set of constrained deadline sequential tasks. -We derive a resource augmentation bound of 4 when these decomposed tasks are scheduled using global EDF scheduling. To our knowledge, this is the first resource augmentation bound for global EDF scheduling of parallel tasks. -Using the proposed task decomposition, we also derive a resource augmentation bound of 5 for our more general task model under partitioned DM scheduling. -Finally, we extend our analyses for a Directed Acyclic Graph (DAG) task model where each node in a DAG has a unit execution requirement. This is an even more general model for parallel tasks. Namely, we show that we can transform unit-node DAG tasks into synchronous tasks, and then use our proposed decomposition to get the same resource augmentation bounds for the former.. We evaluate the performance of the proposed decomposition through simulations based on synthetic workloads. The results indicate that the derived bounds are safe and sufficient. In particular, the resource augmentations required to schedule the decomposed tasks in our simulations are at most 2.4 and 3.4 for global EDF and partitioned DM scheduling, respectively, which are significantly smaller than the corresponding theoretical bounds.. In the rest of the paper, Sect. 2 describes the parallel synchronous task model. Section 3 presents the proposed task decomposition. Section 4 presents the analysis for global EDF scheduling. Section 5 presents the analysis for partitioned DM scheduling. Section 6 extends our results and analyses for unit-node DAG task models. Section 7 presents the simulation results. Section 8 reviews related work. Finally, we conclude in Sect. 9. With the advent of the era of multi-core computing, real-time scheduling of parallel tasks is crucial for real-time applications to exploit the power of multi-core processors. While recent research on real-time scheduling of parallel tasks has shown promise, the efficacy of existing approaches is limited by their restrictive parallel task models. To overcome these limitations, in this paper we have presented new results on real-time scheduling for generalized parallel task models. First, we have considered a general synchronous parallel task model where each task consists of segments, each having an arbitrary number of parallel threads. Then we have proposed a novel task decomposition algorithm that decomposes each parallel task into a set of sequential tasks. We have derived a resource augmentation bound of 4 under global EDF scheduling, which to our knowledge is the first resource augmentation bound for global EDF scheduling of parallel tasks. We have also derived a resource augmentation bound of 5 for partitioned DM scheduling. Finally, we have shown how to convert a task represented as a Directed Acyclic Graph (DAG) with unit time nodes into a synchronous task, thereby holding our results for this more general task model.. Through simulations, we have observed that bounds in practice are significantly smaller than the theoretical bounds. These results suggest many directions of future work. First, we can try to provide better bounds and/or provide lower bound arguments that suggest that the bounds are in fact tight. In the future, we also plan to consider even more general DAG tasks where nodes have arbitrary execution requirements, and to provide analysis requiring no transformation to synchronous model. We also plan to address system issues such as cache effects, preemption penalties, and resource contention. There has been extensive work on traditional multiprocessor real-time scheduling (Davis and Burns 2011) . Most of this work focuses on scheduling sequential tasks on multiprocessor or multi-core systems. There has also been extensive work on scheduling of one or more parallel jobs on multiprocessors (Polychronopoulos and Kuck 1987; Drozdowski 1996; Deng et al. 1996; Arora et al. 1998; Bansal et al. 2004; Edmonds et al. 2003; Agrawal et al. 2006; Calandrino and Anderson 2008; Calandrino et al. 2007a Calandrino et al. , 2007b . However, the work in Polychronopoulos and Kuck (1987) , Drozdowski (1996) , Deng et al. (1996) , Arora et al. (1998) , Bansal et al. (2004) , Edmonds et al. (2003) , Agrawal et al. (2006) does not consider task deadlines, and that in Calandrino and Anderson (2008) , Calandrino et al. (2007a Calandrino et al. ( , 2007b considers soft real-time scheduling. In contrast to the goal of a hard real-time system (i.e. to meet all task deadlines), in a soft real-time system the goal is to meet a certain subset of deadlines based on some application specific criteria.. There has been little work on hard real-time scheduling of parallel tasks. Anderson and Calandrino (2006) proposes the concept of megatask as a way to reduce miss rates in shared caches on multi-core platforms, and consider Pfair scheduling by inflating the weights of a megatask's component tasks. Preemptive fixed-priority scheduling of parallel tasks is shown to be NP-hard by Han and Lin (1989) . Kwon and Chwa (1999) explores preemptive EDF scheduling of parallel task systems with linear-speedup parallelism. Wang and Cheng (1992) considers a heuristic for nonpreemptive scheduling. However, this work focuses on metrics like makespan (Wang and Cheng 1992) or total work that meets deadline (Kwon and Chwa 1999) , and considers simple task models where a task is executed on up to a given number of processors.. Most of the other work on real time scheduling of parallel tasks also address simplistic task models. Jansen (2004) , Lee and Lee (2006) , and Collette et al. (2008) study the scheduling of malleable tasks, where each task is assumed to execute on a given number of cores or processors and this number may change during execution. Manimaran et al. (1998) studies non-preemptive EDF scheduling for moldable tasks, where the actual number of used processors is determined before starting the system and remains unchanged. Kato and Ishikawa (2009) addresses Gang EDF scheduling of moldable parallel task systems. They require the users to select at submission time the number of processors upon which a parallel task will run. They further assume that a parallel task generates the same number of threads as processors selected before the execution. In contrast, the parallel task model addressed in this paper allows tasks to have different numbers of threads in different stages, which makes our solution applicable to a much broader range of applications. For parallel tasks, Nelissen et al. (2012) has studied real-time scheduling to minimize the required number of processors. In contrast, we study schedulability of parallel tasks in terms of processor speed-up factor. Recently, processor speed up factor for a task represented as a DAG has been addressed by Baruah et al. (2012) . But this work considers scheduling of a single task. In contrast, we consider scheduling a set of parallel tasks on multi-core platform.. Our work is most related to, and is inspired by, the recent work of Lakshmanan et al. (2010) on real-time scheduling for a restrictive synchronous parallel task model. In their model, every task is an alternate sequence of parallel and sequential segments. All the parallel segments in a task have an equal number of threads, and that number cannot exceed the total number of processor cores. They also convert each parallel task into a set of sequential tasks, and then analyze the resource augmentation bound for partitioned DM scheduling. However, their strategy of decomposition is different from ours. They use a stretch transformation that makes a master thread of execution requirement equal to the task period, and assign one processor core exclusively to it. The remaining threads are scheduled using the FBB-FDD algorithm. Unlike ours, their results do not hold if, in a task, the number of threads in different segments vary, or exceed the number of cores. In addition, tasks that can be expressed as a DAG of unit time nodes cannot be converted to their task model in a work and critical path length conserving manner. Therefore, unlike ours, their analysis does not directly apply to these more general task models.. Our work in this paper has two major extensions beyond our previous work that appears as a conference version (Saifullah et al. 2011) . First, we have added a detailed description of how the FBB-FFD partitioned deadline monotonic scheduling policy should be adopted for decomposed tasks with offsets. The conference version of the paper provided a resource augmentation bound for the FBB-FFD algorithm, and did not provide the detailed procedure for partitioning of the tasks with offsets. Note that the FBB-FFD algorithm, by default, is not offset-aware. Hence, we have provided a modified version of this algorithm to make it offset-aware. Second, we have provided evaluation results based on simulations. The conference version of the paper did not provide any evaluation result. In addition, we have presented how our results will hold for task models where a synchronous task may have some segment containing threads of different execution requirements. The conference version of the paper considered the synchronous task model where each segment in a task consists of equal-length threads.

O B I O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O B I O O B I O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O B I I O O O O O O O O O O O O O B I I O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O B I O O O O O O O B I O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Low-Power Circuit Techniques for Low-Voltage Pipelined ADCs Based on Switched-Opamp Architecture This paper proposes useful circuit structures for achieving a low-voltage/low-power pipelined ADC based on switched-opamp architecture. First, a novel unity-feedback-factor sample-and-hold which manipulates the features of switched-opamp technique is presented. Second, opamp-sharing is merged into switched-opamp structure with a proposed dual-output opamp configuration. A 0.8-V, 9-bit, 10-Msample/s pipelined ADC is designed to verify the proposed circuit. Simulation results using a 0.18-μm CMOS 1P6M process demonstrate the figure-of-merit of this pipelined ADC is only 0.71 pJ/step. Serving as a crucial component in many communicationrelated products, analog-to-digital converters (ADCs) with high performance while dissipating low power are highly preferred. Pipelined ADC proves to be a popular architecture since it employs concurrent operation to achieve high throughput in a power-efficient manner. However, as process technology scales, the design of pipelined ADC becomes much more complicated when low-voltage is also a significant concern. Lower supply voltage inherently translates into lower power in digital domain while this is not the case considering analog circuit [1] , [2] . In order to maintain the required dynamic range and speed performance with reduced voltage supply, extra power is needed to suppress the noise floor as well as boosting the opamp bandwidth. As a result, for a given signal-to-noise ratio (SNR) specification, the total power consumption will inversely increase with reduced supply. Insufficient switch overdrive voltage is another critical problem for low-voltage circuit which may lead to higher distortion and longer settling. Limited opamp structure choices which often fail to provide enough gain and bandwidth even deteriorate the situation.. Many approaches have been proposed to deal with insufficient switch conduction at low voltage [2] - [4] . Switched-opamp (SO) architecture removes the critical switch and replaces it with a switchable opamp [3] . It is fully compatible with deep-submicron technology and allows for extensive applications with low supply voltage such as switched-capacitor (SC) filters [5] , [6] , sigma-delta modulator [7] , and pipelined ADCs [8] - [13] .. Manuscript received June 21, 2007 . Manuscript revised September 10, 2007 . † The authors are with the Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan.. a) E-mail: petero@spic.ee.ncku.edu.tw DOI: 10.1093/ietfec/e91-a.2.461. For a switched-opamp based pipelined ADC, since lower supply voltage does not promise lower power, the power minimization issue can be tackled from two aspects by examining the power distribution phenomenon. In the architectural level, sample-and-hold (S/H) is the dominant power contributor since it processes the full resolution and bandwidth of an ADC [14] . In the circuit level, opamps generally consume more than 80% of an overall ADC power and therefore opamp-sharing are widely used in pipelined ADCs [15] - [18] . This work proposes power saving design techniques for switched-opamp based ADCs following these two guidelines. A novel S/H architecture is introduced to relax the power and noise contribution of traditional SObased S/H [9] , [13] . Furthermore, a power-efficient ADC architecture by incorporating the opamp-sharing technique into switched-opamp configuration is presented [10] . A 0.8-V 9-bit 10-MS/s ADC is designed to demonstrate the proposed ideas.. This paper is organized as follows: Sect. 2 presents the architecture of the proposed ADC. A novel S/H as well as the SO-based opamp-sharing architecture which altogether constitute the low-voltage/low-power pipelined ADC are described and clarified. Low-voltage building blocks such as opamp and comparator are discussed in Sect. 3. Simulation results of the developed ADC using 0.18-μm CMOS 1P6M device models are demonstrated and analyzed in Sect. 4. Figure 1 shows the architecture of the overall pipelined ADC based on switched-opamp technique. It consists of a dedicated sample-and-hold, seven 1.5-bit/stage pipelined [19] and a final 2-bit flash ADC. A total of 16 bits are collected and processed by the digital error correction unit to remove the redundancy and retrieve the effective 9-bit digital output. The front-end S/H is realized with a novel SO-based technique which allows itself to operate in unity-feedback configuration. In addition, opamp-sharing is applied along the pipeline stages. Total four opamps are used, in which S/H and first multiplying-digital-to-analogconverter (MDAC) share a common opamp and then the following six MDACs share the other three opamps. The opamp sharing allocation is illustrated as the dashed blocks in Fig. 1 . The proposed S/H and opamp-sharing scheme are described in detail in the following sub-sections. Switched-opamp technique has been extensively employed in many switched-capacitor applications to deal with the poor conduction state of switches operated with low voltage supply. On the other hand, opamp sharing approach is an effective way to reduce the power consumption since it directly saves half the number of the required opamps. This paper proposed the methods and circuit structures required to reuse the opamps in a switched-opamp circuit configuration. In addition, a S/H with unity feedback factor in switched-opamp structure was proposed to further reduce the overall input-referred noise and also the power consumption. Using a 0.18-μm CMOS 1P6M process, a 0.8-V 9-bit 10-MS/s pipelined ADC with 2.4 mW and 0.71 pJ/step FOM has been designed and verified the proposed ideas.

O O O O B O O O O B O O O O O O O O O O O B I O O B O O O O O B O O O O O B O O O O B O O O B O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O B I O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O


Unsupervised query segmentation using clickthrough for information retrieval Query segmentation is an important task toward understanding queries accurately, which is essential for improving search results. Existing segmentation models either use labeled data to predict the segmentation boundaries, for which the training data is expensive to collect, or employ unsupervised strategy based on a large text corpus, which might be inaccurate because of the lack of relevant information. In this paper, we propose a probabilistic model to exploit clickthrough data for query segmentation, where the model parameters are estimated via an efficient EM algorithm. We further study how to properly interpret the segmentation results and utilize them to improve retrieval accuracy. Specifically, we propose an integrated language model based on the standard bigram language model to exploit the probabilistic structure obtained through query segmentation. Experiment results on two datasets show that our segmentation model outperforms existing segmentation models. Furthermore, extensive experiments on a large retrieval dataset reveals that the results of query segmentation can be leveraged to improve retrieval relevance by using the proposed integrated language model. Since an accurate understanding of the user's query is critical to improving retrieval results, query segmentation is one of the most important tasks in modern information retrieval. For example, accurate query segmentation is the prerequisite for semantic retrieval models, phrase-based query reformulation and automatic relevance feedback. Supervised techniques have been used to solve the query segmentation problem in the past [3, 23] . However, they require lots of segmentation labels which are expensive to collect. An unsupervised approach based on a large text corpus and Wikipedia has been reported to achieve competitive performance [19] ; but its accuracy without Wikipedia is still low, partly due to the lack of relevant information about the query structure.. In a modern search engine, there is a large amount of relevant data in the form of clickthroughs. Such data reflects users' implicit preference of documents, and can be leveraged to infer the underlying segmentation of the queries. In this paper, we propose a unsupervised probabilistic model to exploit user clickthroughs for query segmentation. Model parameters are estimated by an efficient EM algorithm. Segmentation results on a standard dataset demonstrate that our model significantly outperforms the EM model in [19] without the use of Wikipedia. Additionally, by combining more data from external resources, such as the Microsoft Web N-gram [22] , our model can outperform state-of-theart baselines.. One of the most important applications for query segmentation is to improve the retrieval models by incorporating query segmentation. Most information retrieval techniques, such as vector space models and language modeling approaches, rely on the bag-of-words assumption that every query term is independent in the relevance computation. But this assumption is over simplified; users have an order in mind when formulating queries to search for information. One of the reasons why bag-of-words based methods remain popular is because data sparsity makes it harder to estimate models imposing term dependencies [4, 5, 18] . Successful query segmentation has a great potential to lead to better retrieval models that can utilize higher-order term dependencies.. However, query segmentation is ambiguous in nature -the same query can be segmented in difference ways by different people. Although several methods for query segmentation have been proposed, surprisingly little research has been performed to address the segmentation ambiguity and incorporate this information into retrieval models. In this paper, we propose a query segmentation model that quantifies the uncertainty in segmentation by probabilistically modeling the query and clicked document pairs. We further incorporate the probabilistic query segmentation into a unified language model for information retrieval. Experiments on a large web search dataset from a major commercial search engine show that the integrated language model with query segmentation (QSLM) outperforms both the BM25 model and other language models. In this paper we propose a novel unsupervised query segmentation model by jointly modeling the query-clicked documents from the search log. Experimental results on two datasets confirm the effectiveness of our model. Furthermore, we develop a unified language model with query segmentation to improve the search ranking. The implicit relevance information in the clickthrough data is the bridge between our query segmentation model and QSLM. Thorough experiments on a large-scale web search dataset show that search relevance can be improved by leveraging the query segmentations. As there is still a large gap in retrieval performance between the oracle ranker and the QSLM model, we plan to further refine the model to reduce gap in the future. Specifically, we would like to explore the use of QSLM as features to other advanced retrieval models [12] . Query segmentation models have been well studied in recent literature [10, 11, 3, 23, 19, 6] . Initially, the mutual information (MI) between adjacent words in a query is employed to segment queries with a cutoff [10, 11] .The major drawback of MI based methods is that they are unable to detect multi-word or phrase based dependencies. Compared with MI based models, supervised query segmentation approaches can achieve higher accuracies [3, 23] . For example, by considering every boundary between two consecutive query words as a binary decision variable, Bersgma and Wang [3] trains the weights of a linear decision function with a set of syntactic and shallow semantic features extracted from the labeled data. However, its focus on noun phrase features may not be appropriate for the segmentation of web queries. Furthermore, acquiring training labels demands a great deal of manual effort that may not scale to the web. As another supervised learning approach, Yu and Shi [23] applies conditional random fields to obtain good query segmentation performance. However, it relies on field information features specific to databases, not available for general unstructured web queries. Moreover, the evaluation was conducted only on synthetic data, which is less desirable than real query data.. Tan and Peng [19] introduce a generative model in the unsupervised setting by adopting n-gram frequency counts from a large text corpus and computing the segment scores via expectation maximization (EM). It also utilizes Wikipedia as another term in the minimum description length objective function. Similarly our model in this paper also includes n-gram statistics and applies the EM algorithm to estimate the model parameters. However, we employ clickthrough query-document pairs to improve segmentation accuracy and further refine the retrieval model by utilizing probabilistic query segmentation. Similar probabilistic model is also proposed in [24] , but this model focuses in parsing noun phrases thus not generally applicable to web queries.. This work is also closely related to the retrieval models that capture higher order dependencies of query terms. There are several research attempts to incorporate term dependency in query or document to retrieval models [12] . For example, some attempts have been made to add proximity heuristics to the vector space model or generative query LM model [13, 20] . However these methods rely on heuristics, which is not a principled way of incorporating term dependency. More unified higher-order language models have been studied by Srikanth et al. (Biterm LM) [18] . However, their assumption that every position is dependent is too strong. In fact, the word dependency is stronger within a semantic unit than across the unit, which is what we assume in our work. LM with query syntactics [5] assumes a structure on the query, but they are too complex to estimate accurately. More important, the query syntactic models usually take only the top (most likely) query structure in the modeling process. However, it is more appropriate to assess the probability for all possible segmentation if multiple structures have comparable probabilities to represent the query.. In addition, search log and clickthrough data have been reported to be able to improve the performance of personalized search [9, 1, 17] . For example, Joachims [9] first proposes to improve the retrieval quality of search engines by learning from the user clickthrough. Shen et al. [17] propose a decision-theoretic approach to improve search performance via user feedback. And Agichtein et al. [1] demonstrate that web search ranking can be improved by considering user behavior. We add to this line of work a novel way of exploiting the clickthrough data for query segmentation.

O B I O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O B I O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I B O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O B I O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I


New Binomial Bent Functions Over the Finite Fields of Odd Characteristic The p-ary function f(x) mapping GF(p 4k ) to GF(p) and given by f (x) = Tr 4k x p +p 0p +1 + x 2 is proven to be a weakly regular bent function and the exact value of its Walsh transform coefficients is found. This is the first proven infinite class of nonquadratic generalized bent functions over the fields of an arbitrary odd characteristic. The proof is based on a few new results in the area of exponential sums and polynomials over finite fields that may also be interesting as independent problems.Index Terms--ary bent function, polynomial over finite field, root, Walsh transform, weakly regular bent function. B OOLEAN bent functions were first introduced by Rothaus in 1976 as an interesting combinatorial object with the important property of having the maximum Hamming distance to the set of all affine functions. Later, the research in this area was stimulated by the significant relation to the following topics in computer science: coding theory, sequences and cryptography (design of stream ciphers and -boxes for block ciphers). Kumar et al. in [1] generalized the notion of Boolean bent functions to the case of functions over an arbitrary finite field. Complete classification of bent functions looks hopeless even in the binary case. In the case of generalized bent functions, things are naturally much more complicated. However, many explicit methods are known for constructing bent functions either from scratch or based on other, simpler bent functions.. Given Recently, weakly regular bent functions were shown to be useful for constructing certain combinatorial objects such as partial difference sets, strongly regular graphs and association schemes (see [3] and [4] ). This justifies why the classes of (weakly) regular bent functions are of independent interest. Throughout this paper, with odd stands for the positive square root of . For a comprehensive reference on monomial and quadratic -ary bent functions we refer reader to [5] .. In the present paper, we take an odd prime and examine prospective -ary bent functions having the form with and arbitrary integer exponents for . Functions of this type with both coefficients being nonzero are called binomial. We prove that is a weakly regular bent function for and find the exact value of its Walsh transform coefficients. This is the first proven infinite class of nonquadratic generalized bent functions over the fields of an arbitrary odd characteristic. It is interesting that in the binary case when , the decimation which is cyclotomic equivalent to the exponent in the first term of the above bent function, was studied by Niho in [6, Theorem3-7] and Helleseth in [7] . They proved that the cross-correlation function between two binary -sequences that differ by this decimation is four-valued and found the distribution.. Note that the only not weakly regular bent function known so far is the power function from [5, Fact1] . Here, we present a binomial with this property.. Fact 1: The ternary function mapping to given by , where and is a primitive element of , is bent and not weakly regular bent.. It is interesting to note that for . Unfortunately, we were not able to find a family containing the function from Fact 1. Naturally, more binomial bent functions of these types can be constructed using cyclotomic equivalence of exponents and coefficients. 0018-9448/$26.00 © 2010 IEEE

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I I O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I I B B I B I I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I I O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


The bicompletion of fuzzy quasi-metric spaces Extending the well-known result that every fuzzy metric space, in the sense of Kramosil and Michalek, has a completion which is unique up to isometry, we show that every KM-fuzzy quasi-metric space has a bicompletion which is unique up to isometry, and deduce that for each KM-fuzzy quasi-metric space, the completion of its induced fuzzy metric space coincides with the fuzzy metric space induced by its bicompletion. Kramosil and Michalek introduced in [11] their celebrated notion of a fuzzy metric space and established its relation with the notion of a probabilistic metric space. In particular, they observed that the class of fuzzy metric spaces, in their sense, is "equivalent" to the class of Menger spaces having a continuous t-norm. Sherwood proved in [21] that every Menger space belonging to this class has a completion which is unique up to isometry, and thus one can easily deduce that every fuzzy metric space has a completion which is unique up to isometry.. The concept of metric fuzzy metric space was generalized to the quasi-metric setting in [1] and [9] , where several properties of these structures were discussed. Recently, it were given in [16] , [17] and [18] , applications of fixed point theorems, in the realm of fuzzy quasi-metric spaces, to deduce the existence and uniqueness of solution for the recurrence equations associated to some types of algorithms, whereas in [15] it was presented a study of a notion of Hausdorff fuzzy quasi-pseudo-metric on the collection of nonempty subsets of a given fuzzy quasi-metric space.. In this context, the completion of fuzzy quasi-metric spaces appears as a natural and attractive question, which will be discussed here. In fact, we show that every fuzzy quasi-metric space (in the sense of Definition 2 below) has a (fuzzy quasi-metric) bicompletion which is unique up to isometry. Then, the completion of a fuzzy metric space is restated as a particular case, and we deduce that for each fuzzy quasi-metric space, the completion of its induced fuzzy metric space coincides with the fuzzy metric space induced by its bicompletion.Some illustrative example are also given. We emphasize at this point the while Sherwood's construction is strongly based on the properties of Lévy's metric (see [6, 14] for its definition and properties), our construction avoids the use of Lévy's metric and directly uses suprema of subsets of [0, 1] and lower limits of sequences in [0,1].

O B O B I O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O B O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O B I O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O B I B O O O O O B O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Proof rules for the correctness of quantum programs We apply the notion of quantum predicate proposed by D'Hondt and Panangaden to analyze a simple language fragment which may describe the quantum part of a future quantum computer in Knill's architecture. The notion of weakest liberal precondition semantics, introduced by Dijkstra for classical deterministic programs and by McIver and Morgan for probabilistic programs, is generalized to our quantum programs. To help reasoning about the correctness of quantum programs, we extend the proof rules presented by Morgan for classical probabilistic loops to quantum loops. These rules are shown to be complete in the sense that any correct assertion about the quantum loops can be proved using them. Some illustrative examples are also given to demonstrate the practicality of our proof rules. The theory of quantum computing has attracted considerable research efforts in the past twenty years. Benefiting from the possibility of superposition of different states and the linearity of quantum operations, quantum computing may provide considerable speedup over its classical analogue [22, 6, 7] . The existing quantum algorithms, however, are described at a very low level: they are usually represented as quantum circuits. A few works have been done to develop quantum programming languages which identify and promote high-level abstractions. The first step of writing quantum pseudo-code was taken by Knill [11] ; while the first actual quantum programming language is due toÖmer [17, 18] . After that, Sanders and Zuliani [19, 24] , Bettelli et al. [2] , and Selinger [21] also proposed various quantum languages each having different features. We refer to [20] for a survey of this field.. The standard weakest precondition calculus [5] and its probabilistic extension [16] have been successful in reasoning about the correctness and even the rigorous derivation of classical programs. This success motivates us to develop analogous tools for quantum programs. Sanders and Zuliani [19] have provided for their qGCL a stepwise refinement mechanism. The approach, however, is classical in the sense that they treated the quantum programs as special cases of probabilistic programs. As a consequence, known results about the probabilistic weakest precondition calculus can be applied directly to the quantum programs. Indeed, Butler and Hartel [3] have used it to reason about Grover's algorithm.. The first step towards really quantum weakest precondition calculus was made by D'Hondt and Panangaden [4] . They proposed the brilliant idea that we can treat an observable, mathematically described by a hermitian matrix, as the quantum analogue of 'predicate'. The elegant duality between state-transformer semantics and the weakest precondition semantics (wp-semantics for short) of quantum programs, when described by completely positive and trace-nonincreasing linear operators, was then proven to hold in a more direct way.. In this paper, we apply the ideas in [4] to analyze a simple quantum language fragment describing the quantum part of a potential quantum computer in Knill's architecture [11] . The syntax follows Selinger's style [21] except that we are only concerned with purely quantum data. We make this limitation on our language fragment merely for the sake of simplification. The results presented in this paper can be extended easily to a general language where both classical and quantum variables are involved. The denotational semantics of our language is given and shown to be a super-operator for each program construct; the wp-semantics which is useful for reasoning about the total correctness of quantum programs is presented following the correspondence between denotational semantics and wp-semantics proposed in [4] . To reason about the partial correctness of programs written in our quantum language, we extend the notion of weakest liberal precondition semantics (wlp-semantics for short), first introduced by Dijkstra [5] for deterministic programs and then generalized by McIver and Morgan [13] for probabilistic programs, to our quantum language. The numerical relations between these three semantics are also discussed.. In order to help reasoning about the quantum programs involving loops, we extend the notion of loop invariant which is the key in proving correctness of classical programs (see [5] for deterministic and [15] for probabilistic loop invariants) to quantum setting. Based on it, we develop some rules to reason about the partial and total correctness of quantum loops. These rules are natural quantum extensions of those for classical probabilistic programs introduced by Morgan [15] . We also show the completeness of these rules in the sense that any correct assertion about the quantum loops can be proved using them. To demonstrate the practicality of our proof rules, some illustrative examples are also presented. Particularly, we consider a discrete coined quantum walk on an n-cycle with an absorbing boundary at position 1, and prove using our proof rules that this kind of walk will ultimately terminate at position 1 with unit probability.. This paper is organized as follows. Section 2 is the preliminary part where basic concepts and notations used in this paper are reviewed. In Section 3, we propose the syntax and denotational semantics of our quantum language fragment. The wp-semantics is also given following the correspondence presented in [4] . Our main contribution starts from Section 4, where we extend the notion of wlp-semantics to the quantum language we consider. The quantity relations of these three semantics presented are also discussed. In Section 5, the wp-and wlp-semantics are used to present some proof rules of reasoning about quantum loop programs. The completeness of these rules is proved and some illustrative examples are also given. Section 6 is the concluding section in which we draw the conclusion and point out some problems for further studies.

B I O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O B I O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Dynamic data rectification using particle filters The basis of dynamic data rectification is a dynamic process model. The successful application of the model requires the fulfilling of a number of objectives that are as wide-ranging as the estimation of the process states, process signal denoising and outlier detection and removal. Current approaches to dynamic data rectification include the conjunction of the Extended Kalman filter (EKF) and the expectation-maximization algorithm. However, this approach is limited due to the EKF being less applicable where the state and measurement functions are highly non-linear or where the posterior distribution of the states is non-Gaussian. This paper proposes an alternative approach whereby particle filters, based on the sequential Monte Carlo method, are utilized for dynamic data rectification. By formulating the rectification problem within a probabilistic framework, the particle filters generate Monte Carlo samples from the posterior distribution of the system states, and thus provide the basis for rectifying the process measurements. Furthermore, the proposed technique is capable of detecting changes in process operation and thus complements the task of process fault diagnosis. The appropriateness of particle filters for dynamic data rectification is demonstrated through their application to an illustrative non-linear dynamic system, and a benchmark pH neutralization process. Mechanistic (phenomenological) models, based on mathematical representations of the physical and chemical behaviour of the process, have been widely applied for process optimization, process monitoring and process control. Whilst a set of differential equations are generally utilized in mechanistic modelling to describe the process of interest, in application studies they are typically discretized to give difference equations. These equations can be regarded as a general state space model (Jazwinski, 1970) with the difference variables defining the states. A typical state space model comprises both state and measurement functions, k f and k h , respectively :. ( ). where k is the time index, and the vectors, x , u, and z , are the process states, the input variables and the process measurements, respectively. v and n denote independent and identically distributed noise for the process states and measurements, respectively. In practice the noise terms can take other forms, such as multiplicative and auto-correlated.. This study focuses on the model defined in Eqs.. (1) and (2) due to its wide-spread applicability in process engineering Romanenko and Castro, 2004; Terwiesch & Agarwal, 1995) .. However due to the presence of uncertainty both in the process states and the measurements (i.e. v and n ), the on-line estimation of the process states, and the removal of noise and outliers, i.e.. random abrupt peaks, in the measurements, is critical to the application of a mechanistic model for process optimization, control and performance monitoring. This task is termed dynamic data rectification (or dynamic data reconciliation) (Darouach & Zasadzinski, 1991; Liebman, Edgar & Lasdon, 1992; Singhal & Seborg, 2000) , and differs to the "steady" rectification techniques reported in the literature (Morad, Young & Svrcek, 2005; Tong & Crowe, 1997) which are designed around the steady state operation of processes and thus do not need to take into account the process dynamics. Dynamic data rectification is especially challenging when the state and/or measurement functions are highly non-linear, and the posterior distribution of the process states, is not Gaussian.. These issues form the basis of this paper. Martin, 2005) . These approaches specifically focus on state and/or parameter estimation but do not explicitly consider the rectification of measurements which may be affected by outliers.. This paper proposes the application of particle filters for dynamic data rectification with the goal of attaining satisfactory state estimates and detecting the presence of outliers, thereby recovering the "true" measurements from the corrupted values. The rectification problem will initially be presented within a probabilistic framework, prior to describing the specific application of particle filters for this task. In addition, this technique is shown to be applicable for the detection of process changes and thus complements the task of process fault diagnosis. The proposed approach for dynamic data rectification is illustrated by its application to a non-linear dynamic system, and a simulated benchmark pH neutralization reactor, and it is observed to exhibit improved performance over the rectification techniques based on the EKF and the EKF with the EM algorithm (EKF-EM) (Singhal & Seborg, 2000) .. In summary this paper focuses on the formulation, and solution, of the dynamic data rectification problem utilising a probabilistic and statistical framework. In the literature considerable research has been reported to address this problem, most notably deterministic optimization algorithms using non-linear programming and moving horizon estimation (Abu-el-zeet, Becerra & Roberts, 2002; Liebman, Edgar & Lasdon, 1992) . The execution of a comparative study between probabilistic filtering methods, such as the EKF and particle filter, is considered in this paper, but deterministic optimization based solutions are outwith the scope of this paper. This paper applied particle filters for on-line dynamic data rectification, which is aimed at addressing three tasks simultaneously: accurate state estimation, the detection of outliers or process changes, and the removal of measurement noise. In situations where the EKF is not applicable due to highly non-linear behaviour and non-Gaussian distribution of states, particle filters were observed to achieve significantly enhanced results in terms of improved state estimation and measurement rectification. The proposed approach has been further shown to be able to detect process changes, which is potentially useful in model-based process fault detection.. The proposed methodology is potentially applicable for process fault detection and diagnosis, where the difference between the rectified and the actual process measurements,. , could be used to facilitate fault diagnosis. Furthermore, in situations where historical process data is available for various fault scenarios, a pattern recognition system may be developed in conjunction with the proposed methodology to provide accurate identification and diagnosis of process faults. These issues will be investigated in future work.

B I I O B I O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O B I I O O O O B I I O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O B I I O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


A New Fuzzy Set Merging Technique Using Inclusion-Based Fuzzy Clustering Abstract-This paper proposes a new method of merging parameterized fuzzy sets based on clustering in the parameters space, taking into account the degree of inclusion of each fuzzy set in the cluster prototypes. The merger method is applied to fuzzy rule base simplification by automatically replacing the fuzzy sets corresponding to a given cluster with that pertaining to cluster prototype. The feasibility and the performance of the proposed method are studied using an application in mobile robot navigation. The results indicate that the proposed merging and rule base simplification approach leads to good navigation performance in the application considered and to fuzzy models that are interpretable by experts. In this paper, we concentrate mainly on fuzzy systems with Gaussian membership functions, but the general approach can also be applied to other parameterized fuzzy sets. C LUSTERING has been acknowledged as a powerful tool to analyze data and to build data-driven models. It is similar to the ability of humans to divide objects into groups or clusters sharing common characteristics. Children for instance can quickly label objects referring to buildings, vehicles, people, animals, etc. Since the introduction of the fuzzy set theory, its application to classification has produced very appealing outcomes, both from the theoretical perspective as testified by the exponential growth of literature in fuzzy clustering, and from the practical viewpoint as suggested by the emerging successful applications. In fuzzy modeling, clustering is equivalent to finding the fuzzy sets sharing the same features or characteristics. In data-driven approaches, the membership functions that represent the linguistic terms in the model are derived from these fuzzy sets (clusters). Usually, one observes a large degree of overlap among the fuzzy sets obtained. In this sense, the fuzzy sets are said to be similar according to some concept or measure of similarity. In order to increase the interpretability of fuzzy models, these similar fuzzy sets are often combined or merged [1] , [2] .

O O O O B O O O B I O O O O O O O B O B I O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O B I O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O B I O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O


Lead-like, drug-like or "Pub-like": how different are they? Academic and industrial research continues to be focused on discovering new classes of compounds based on HTS. Post-HTS analyses need to prioritize compounds that are progressed to chemical probe or lead status. We report trends in probe, lead and drug discovery by examining the following categories of compounds: 385 leads and the 541 drugs that emerged from them; "active" (152) and "inactive" (1488) compounds from the Molecular Libraries Initiative Small Molecule Repository (MLSMR) tested by HTS; "active" (46) and "inactive" (72) compounds from Nature Chemical Biology (NCB) tested by HTS; compounds in the drug development phase (I, II, III and launched), as indexed in MDDR; and medicinal chemistry compounds from WOMBAT, separated into high-activity (5,784 compounds with nanomolar activity or better) and low-activity (30,690 with micromolar activity or less). We examined Molecular weight (MW), molecular complexity, flexibility, the number of hydrogen bond donors and acceptors, LogP-the octanol/water partition coefficient estimated by ClogP and ALOGPS), LogSw (intrinsic water solubility, estimated by ALOGPS) and the number of Rule of five (Ro5) criteria violations. Based on the 50% and 90% distribution moments of the above properties, there were no significant difference between leads of known drugs and "actives" from MLSMR or NCB (chemical probes). "Inactives" from NCB and MLSMR were also found to exhibit similar properties. From these combined sets, we conclude that "Actives" (569 compounds) are less complex, less flexible, and more soluble than drugs (1,651 drugs), and significantly smaller, less complex, less hydrophobic and more soluble than the 5,784 high-activity WOMBAT compounds. These trends indicate that chemical probes are similar to leads with respect to some properties, e.g., complexity, solubility, and hydrophobicity. The set of MLSMR and NCB actives (198 compounds) was found to be similar to the set of documented (historical) Leads (385 compounds), as summarized in Table 1 . This observation, applicable to the anticipated set of chemical probes, is even more remarkable when one compares the (significant) differences between the property distribution values of the 569 Actives and the 5,784 high-activity molecules from medicinal chemistry literature. The WB9 subset contains molecules that are, on average, larger, more hydrophobic and less soluble than any of the other datasets examined here. In the same manner, it can be noted that the Actives (pub-like) subset contains molecules that are, on average, smaller, less complex, less hydrophobic and more soluble than the other datasets.. As the academic community is embarking on chemical probe discovery, the issue of what constitutes high-quality probes is likely to be debated. Arguments such as ''historical bias'' are, and perhaps should be, used when it comes to defining property boundaries such as the Ro5 limits. And yet, the road to success is paved with multiple failures: Rather than increasing, the annual number of new approved drugs has decreased in the past decade, despite significantly larger numbers of molecules, and targets, being considered. Whether the boundary limits will be extend beyond the Ro5 ''cube'', only time will tell. We note, however, that over 55% of the top 200 oral drug products in the United States, Great Britain, Japan and Spain are ''high-solubility drugs'' [30] , and that only 18 of the 133 active principles from these drugs have ClogP values greater than 4.0 (data not shown). If past experience is to be related to therapeutic and economic success, as defined by the Top 200 drugs, and by the Actives subset, one is advised to observe the boundaries of this property space, and to carefully decide which of these properties should be allowed to exceed these values.

O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O B I O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O B I O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Looking for the impact of peer review: does count of funding acknowledgements really predict research impact? Abstract A small number of studies have sought to establish that research papers with more funding acknowledgements achieve higher impact and have claimed that such a link exists because research supported by more funding bodies undergoes more peer review. In this paper, a test of this link is made using recently available data from the Web of Science, a source of bibliographic data that now includes funding acknowledgements. The analysis uses 3,596 papers from a single year, 2009, and a single journal, the Journal of Biological Chemistry. Analysis of this data using OLS regression and two ranks tests reveals the link between count of funding acknowledgements and high impact papers to be statistically significant, but weak. It is concluded that count of funding acknowledgements should not be considered a reliable indicator of research impact at this level. Relatedly, indicators based on assumptions that may hold true at one level of analysis may not be appropriate at other levels. This paper seeks to examine an important bibliometric relationship that has been assumed to exist between the count of the funding acknowledgements received by a research paper and the paper's impact. The paper examines this relationship, between the count of funding acknowledgements of a paper and its citation impact within the context of a single journal. Such a focus upon the count of citations as a measure of the impact of a paper rather than upon the impact factor facilitates a more precise statistical test of the relationship between the count of funding sources and impact. Account is also taken in the analysis of background or implicit funding which is indicated by the address information in the publication record.. The paper begins by reviewing the evidence on the link between the funding acknowledgements of papers and the impact of papers, and considers the reasons that have been given for such a relationship. An empirical study of a dataset of papers is then presented, the results of an analysis are then given and discussed, and conclusions made. This paper has sought to examine the relationship between funding of research as evidenced by the count of funding acknowledgements on the paper and the extent of a paper's impact, measured here by the count of citations. The aim has been to examine in detail, using actual citation impacts rather than journal impact factors, and in the case of the entire publication set of a foremost journal of the biochemical sciences for a period of two and half years, the relationship between the count of funding acknowledgements and the impact of publications.. The relationships found between the count of funding acknowledgements and the impact of papers suggests little effect if any of a peer review effect influencing the quality of publications. Other factors, such as the quality of the researchers involved, and the post publication activities of other researchers may exert more of an influence upon quality than the enhanced peer review effect of multiple grant awarding bodies.. The evidence suggests that the nature of the link observed by other scholars, but not by all, is very weak at the level of a specific journal. Further work would appear to be justified to determine if an effect is visible across a larger numbers of journals in the same field, and across scientific fields, and using citation impact rather than aggregate measures, such as impact factors.. The paper also has implications for indicator development within science policy. Where indicators are used, it is regularities of relationship between variables, positive or negative, that provide the basis upon which indicators can be created. This paper has argued that while a relationship may be found at certain levels of aggregation, analysis of empirical data presented here shows the relationship between funding and impact to be negligible at the level of the individual journal. It is suggested therefore that indicators are only useful when they can be shown to apply at the level at which they are to be used.. Finally, while multiple awards, resulting in a paper's having a higher count of funding acknowledgements, might appear to be a sign of quality, the need to manage a multiplicity of funds for research projects and to subject the research to the possibly contrasting and conflicting criteria of different funding bodies may in fact constrain, rather than enhance, quality of research. The association between grant winning and carrying out research is a commonplace of research policy and practice and leads to the simplistic assumption that more funding leads to better work of higher quality. However, the evidence presented here is that such a relationship, measured at this scale and in terms of citations counts, is evident but is weak and questionable. Further investigation into the connection between resource input, the identity of funding bodies and other variables noted in the literature would appear timely. The evidence presented above has been obtained from a focused analysis of the papers from a single journal. This approach aimed to ensure a reliable and as accurate a test as possible of the relationship between the counts of funding acknowledgements of papers (explicit and implicit) and their citation impact. The analysis suggests that the count of explicit funding acknowledgements is statistically significantly related at this scale of analysis to citation impact of papers, but has an extremely small influence upon impact. It is only with univariate methods that the link between funding and impact is visible. The two ranks tests carried out on the data suggest that no link exists, the results of such tests suggesting that papers with funding acknowledgements of either explicit or implicit kind or of both kinds are no more or less likely to have a greater citation impact than papers without funding acknowledgements (i.e. papers that have a count of funding acknowledgements of 0). It may therefore be suggested that the count of funding acknowledgements on a paper as an indicator of quality, a view based on the assumption of funding being associated with greater peer review of a research proposal, may need some re-examination. Data presented above gives little credible evidence that the most highly cited papers are those that result where there is funding acknowledged. If the count of grants received in terms of explicit funding and the count of implicit funding received does not indicate the extent of quality control of research, where do differences in impact arise? Could such differences in citation impact arise after the fact, once the funding has been allocated and the research is being done and cited? The dynamic character of scientific knowledge discovery and its uncertainty of outcome suggest this is more likely as an explanation.

O O O O O B I O O O B I O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O B I O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O B I O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O B I O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O