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Frequent episode mining has been proposed as a data mining task with the goal of recovering sequential patterns from temporal data sequences. While several episode mining approaches have been proposed in the last fifteen years, most of the developed techniques have not been evaluated on a common benchmark data set, limiting the insights gained from experimental evaluations. In particular, it is unclear...
Test failure data produced during post-silicon validation contain accurate design- and process-specific information about the DUD (design-under-debug). Prior research efforts and industry practice focused on feeding this information back to the design flow via bug root-cause analysis. However, the value of this silicon data for helping further improvement of the post-silicon validation process has...
Due to the heterogeneous, opaqueness and dynamic nature of Cloud Computing, existing MapReduce approach is not suitable for perform Parallel Computing on the cloud. In this paper, we propose a modified MapReduce framework which extracts the physical network topology information from the Virtual Machine Monitor (VMM) feature of VMs, in order to exploit dynamic resource allocations, and hence enable...
Identifying software vulnerabilities is becoming more important as critical and sensitive systems increasingly rely on complex software systems. It has been suggested in previous work that some bugs are only identified as vulnerabilities long after the bug has been made public. These vulnerabilities are known as hidden impact vulnerabilities. This paper discusses existing bug data mining classifiers...
Parallelization of big-data analytics services over a federation of heterogeneous clouds has been considered to improve performance. However, contrary to common intuition, there is an inherent tradeoff between the level of parallelism and the performance for big-data analytics principally because of a significant delay for big-data to get transferred over the network. The data transfer delay can be...
Sensor networks are exposed to hostile environments that may cause failures of single nodes and communication links which affect the whole network. Localizing the cause of the problem in space and time requires to collect diagnostic data from the network. Due to resource and energy constraints, however, it is not possible to continuously collect detailed diagnostic data from all nodes. We therefore...
The US equity exchange market is organized as a National Market System, enforcing price priority across exchanges, but otherwise allowing competition for order flow among exchanges. This flexibility has naturally evolved to a market where exchanges have varying quality and cost of execution. To meet the obligation for best execution, a broker must employ a strategy for selecting the exchange to which...
As design size gets larger and becomes more complicated with feature integration, the runtime for Static Timing Analysis (STA) becomes more of a concern. Due to time-to-market pressure, the validation of the design is performed in parallel with the physical synthesis flow; therefore it is not uncommon to find last minute critical logic bugs during final design integration iterations. However, timing...
A large number of papers usually use the so-called actually detected fetal ECG data in DAISY database to test their fetal ECG extraction algorithms. However, we found that the fetal ECG data in DAISY database are not sure to be the real measured data from the abdominal surface. The reasons are: (1) In the comparative waveform analysis of the data's different channel signals, it is noticed that there...
The time-series data analysis described here is based on the simple idea that the accumulation of the effects of lifestyle events, such as ingestion and exercise, could affect personal health with some delay. The delay may reflect complex bio-reactions such as those of metabolism in a human body. In the analysis, the accumulation of the effects of lifestyle events is represented by a summation of...
The analysis of human motion data is interesting for the purpose of activity recognition or emergency event detection, especially in the case of elderly or disabled people living independently in their homes. Several techniques have been proposed for identifying such distress situations using either motion, audio or video sensors on the monitored subject (wearable sensors) or the surrounding environment...
Run time variability of parallel applications continues to be a significant challenge in high performance computing (HPC) systems. We are currently studying run time variability in the context of both systemic performance and energy management. Our perspective is from that of the application, focusing on the interactions of the inter-process communication system on the set of concurrently executing...
The absence of predictability of flight operations in the National Airspace System (NAS) is a significant source of excess cost, requiring airlines to pad flight schedules, staff for worst-case scenarios, and build and maintain mitigation plans and equipment. Flight plan routes are selected by airlines to optimize their operations (e.g. minimize crew time, fuel burn and delays). In the absence of...
The motivation for this study is the need for careful analysis of aperiodicity of the excitation component in expressive voices. The paper proposes analysis methods which can preserve the excitation information corresponding to sequence of impulse-like excitation with variable strengths. To analyze the details of the excitation source characteristics, the epochs and the strength of the excitation...
Approximate computing techniques that exploit the inherent resilience in algorithms through mechanisms such as voltage over-scaling (VOS) have gained significant interest. In this work, we focus on meta-functions that represent computational kernels commonly found in application domains that demonstrate significant inherent resilience, namely Multimedia, Recognition and Data Mining. We propose design...
A critical problem to P2P VoD systems is to provide efficient user interactivity support. In this paper, we study intra- and inter-video operations separately and aim to reduce the latency of these VoD operations by exploiting the locality of reference in user access patterns. With a relaxed definition of data chunk holder, intra-video locality can facilitate a high likelihood of a peer seeking within...
Road-vehicle noise samples generated by common vehicles under various operating conditions were replayed using headphones. Ten subjects were instructed to describe and quantify their subjective responses to the noises. A wealth of numerical perceptual information was obtained and investigated by principal component analysis. Based on the human auditory-brain system theory, the physical factors extracted...
Speed-limiting paths are critical paths that limit the performance of one or more silicon chips. This paper present a data mining methodology for analyzing speed-limiting paths extracted from AC delay test measurements. Based on data collected on 15 packaged silicon units of a four-core microprocessor design, we show that the proposed methodology can efficiently discovered actionable, design-related...
Real-time physiological monitoring of athletes during sporting events has tremendous potential for maximizing player performance while preventing burn-out and injury, and also enabling exciting new applications such as referee-assist services and enhanced television broadcast. Emerging advanced monitoring devices have the right combination of light weight and unobtrusive size to allow truly non-intrusive...
The advent of data mining has contributed significantly to the field of customer management. The payment center in Maersk finds that it's difficult to charge customers for the balance due. Thus the research on the application of artificial neural networks in classification of data mining will be conducted in this paper. Since the knowledge captured by neural networks is represented at a sub-symbolic...
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