State-of-charge (SOC) is a critical parameter of battery management systems to ensure safe, efficient, reliable and durable battery operations. However, SOC cannot be directly measured and is highly sensitive to different temperatures. Thus, the SOC estimation accuracy and uncertainty management are significant for robust control and energy dispatch. Gaussian process regression (GPR) is thus becoming appealing due to its non-parametric and interpretable probabilistic advantages. But the scalability of GPR is still challenging, suffering from cubic complexity. To solve these challenges, a SOC estimation method is proposed by an end-to-end scalable deep recurrent structure with fast transfer learning at different temperatures. First, convolutional and recurrent neural networks are employed to catch nonlinear temporal dependency within measurements. Second, a GPR layer is concatenated after neural networks, so that the estimation can be quantified with uncertainty while retaining nonlinear expressive ability. Then, a non-parametric fast transfer learning is designed to realize fast transfer between different temperatures. Next, structured sparse approximations and a semi-stochastic gradient procedure are established for scalable training. Finally, the accuracy and fast transfer of the proposed structure are verified through comparison. The structure demonstrates the state-of-the-art performance on estimation accuracy and efficiency with transfer learning faster than fine-tuning strategy by two orders of magnitude.

Empirical studies are important for understanding how well current design methods and notations support development of multi-threaded programs. Unfortunately, concurrency exacerbates an already difficult problem in drawing conclusions from such studies: How to objectively measure the quality of candidate solutions produced by participants in the studies. This paper explores the use of formal modeling and analysis for this purpose. We describe initial findings of a small pilot study to determine if we can objectively differentiate sample candidate solutions with respect to their use of synchronization primitives. To do so, we faithfully model these candidate solutions and various synchronization-related properties in the Finite State Processes (FSP) notation and use the Labeled Transition System Analyzer (LTSA) to analyze the solution models against the properties.

Graduates of computer science degree programs are increasingly being asked to maintain large, multi-threaded software systems; however, the maintenance of such systems is typically not well-covered by software engineering texts or curricula. We conducted a think-aloud study with 15 students in a graduate-level computer science class to discover the strategies that students apply, and to what effect, in performing corrective maintenance on concurrent software. We collected think-aloud and action protocols, and annotated the protocols for a number of behavioral attributes and maintenance strategies. We divided the protocols into groups based on the success of the participant in both diagnosing and correcting the failure. We evaluated these groups for statistically significant differences in these attributes and strategies.

While the sources of complexity in the initial design and verification of multi-threaded software systems are well-documented, less is known of the issues specific to the maintenance of these systems. The literature contains a number of observational studies of programmers performing maintenance, conducted in the context of sequential software and designed to investigate the factors and behaviors that lead to success. To help fill the gap in knowledge in the area of concurrent software maintenance, we conducted a study that refines the findings of two prior studies, those of Littman et al. and of Vessey, to address issues and obstacles that arise in the understanding of concurrent software. We validated these refinements by observing programmers performing corrective maintenance on a small but complex multi-threaded server program.

MOTIVATION: Genomes contain biologically significant information that extends beyond that encoded in genes. Some of this information relates to various short dispersed repeats distributed throughout the genome. The goal of this work was to combine tools for detection of statistically significant dispersed repeats in DNA sequences with tools to aid development of hypotheses regarding their possible physiological functions in an easy-to-use web-based environment. RESULTS: Ab Initio Motif Identification Environment (AIMIE) was designed to facilitate investigations of dispersed sequence motifs in prokaryotic genomes. We used AIMIE to analyze the Escherichia coli and Haemophilus influenzae genomes in order to demonstrate the utility of the new environment. AIMIE detected repeated extragenic palindrome (REP) elements, CRISPR repeats, uptake signal sequences, intergenic dyad sequences and several other over-represented sequence motifs. Distributional patterns of these motifs were analyzed using the tools included in AIMIE. AVAILABILITY: AIMIE and the related software can be accessed at our web site http://www.cmbl.uga.edu/software.html.

It is generally accepted that concurrency can be difficult for students to reason about. While some studies provide insight into the nature of these difficulties [6], work remains to be done in understanding the aspects of learning about concurrency that are most difficult, and in developing approaches to dealing with this problem. We have conducted instructor interviews and an observational study of students, identified several key difficulties that students encounter, and developed a diagram that we believe will be an aid to understanding and problem-solving. We present the diagram and results of an initial user evaluation.

Programs that use multithreaded concurrency are known to be difficult to design. Moreover, research in computer-science education suggests that concurrency and synchronization concepts are generally difficult to master. It stands to reason that comprehension tasks may be more complex for programs that employ concurrency than for sequential programs. We believe that external representations, specifically refinements to some of the popular UML modeling notations, should aid students in mastering fundamental concurrency/synchronization concepts and should enable practitioners to better comprehend the dynamically evolving nature of the these programs. In this paper, we present our synchronization adorned UML (saUML) sequence diagram notation that highlights aspects of thread interactions and describe an empirical study of whether these diagrams, as opposed to purely textual representations, help students to better understand concurrent executions and concurrency concepts, as measured by their ability to answer questions about a particular execution of a multi-threaded system. A statistically significant benefit was found from the study.

UNLABELLED: We present a new tool for finding local sequence patterns in long DNA sequences. The program, Pattern Locator, uses an intuitive syntax for pattern description, and provides more flexibility than existing programs by allowing combinations of specific nucleotide sequences, direct and inverted repeats, variable length tandem repeats of subpatterns, and a specified number of errors in any part of the pattern. AVAILABILITY: The program is available for download and as a web service accessible through a CGI interface at http://www.cmbl.uga.edu/software.html. The source code is written in C and distributed under the GNU General Public License.