The Future

This book addresses understanding of and solutions to teleworking, trustworthiness, and performance issues. Overall, it suggests using a strategic approach that encourages participation and that is required to achieve, understand, and build buy-in for teleworking. The organizationally sanctioned program must exist. The use of LMX is beneficial in exploring the factors that contribute to motivating the target audience: employees. A culture of self-motivation is necessary to empower employees, but there must also be a culture of enforcement when needed. Finally, buy-in at all levels of the organizations is crucial to the success of a telework program. The parts of the strategic approach mentioned here will be enhanced with the resources provided in this book: how to develop leaders, motivating employees, increasing productivity, using EI, managing radical change, and learning from the research provided. Viewed through the lens of a management context, these components make the recommended strategic approach possible and can deliver an effective framework for results.

Constructing efficient and secure batch signature schemes

In ordinary signature schemes, such as RSA, DSA, ECDSA, the signing process is performed only for a single message. Due to performance issues, in some contexts, the above solutions will become unsuitable if a party needs to sign multiple messages simultaneously. For example, in the authenticated key exchange protocols based on signatures between client and server, the server is expected to handle multiple key exchange requests from different clients simultaneously. Batch signing is a solution that generates signatures for multi-messages simultaneously with a single (ordinary) signature generation. In this article, we will consider some of the existing batch signing solutions and point out a few of their weakness. To deal with these problems, the paper also proposes two secure types of batch signature schemes, but still ensures the same efficiency as the existing batch signing solution.

Thinking Time in Music Practice

We asked school- and college-aged instrumentalists ( N = 32) to imagine an ideal performance of a brief passage of music, record a performance of the passage, and describe discrepancies they noticed between their imagined and actual performances. The more experienced participants took at least as much time to imagine their idealized performances as it took to perform them; less experienced participants took less time to imagine what they were about to play. There were no differences among experience levels in the numbers or types of discrepancies identified. The differences between more and less experienced participants were also evident in a subsequent practice period. More experienced musicians’ practice included more frequent moments of pause, whereas school-aged participants seldom paused and tended to address performance issues other than those identified in their commentaries.

REDACT

Refraction networking is a promising censorship circumvention technique in which a participating router along the path to an innocuous destination deflects traffic to a covert site that is otherwise blocked by the censor. However, refraction networking faces major practical challenges due to performance issues and various attacks (e.g., routing-around-the-decoy and fingerprinting). Given that many sites are now hosted in the cloud, data centers offer an advantageous setting to implement refraction networking due to the physical proximity and similarity of hosted sites. We propose REDACT, a novel class of refraction networking solutions where the decoy router is a border router of a multi-tenant data center and the decoy and covert sites are tenants within the same data center. We highlight one specific example REDACT protocol, which leverages TLS session resumption to address the performance and implementation challenges in prior refraction networking protocols. REDACT also offers scope for other designs with different realistic use cases and assumptions.

Program analysis via efficient symbolic abstraction

This paper concerns the scalability challenges of symbolic abstraction: given a formula ϕ in a logic L and an abstract domain A , find a most precise element in the abstract domain that over-approximates the meaning of ϕ. Symbolic abstraction is an important point in the space of abstract interpretation, as it allows for automatically synthesizing the best abstract transformers. However, current techniques for symbolic abstraction can have difficulty delivering on its practical strengths, due to performance issues. In this work, we introduce two algorithms for the symbolic abstraction of quantifier-free bit-vector formulas, which apply to the bit-vector interval domain and a certain kind of polyhedral domain, respectively. We implement and evaluate the proposed techniques on two machine code analysis clients, namely static memory corruption analysis and constrained random fuzzing. Using a suite of 57,933 queries from the clients, we compare our approach against a diverse group of state-of-the-art algorithms. The experiments show that our algorithms achieve a substantial speedup over existing techniques and illustrate significant precision advantages for the clients. Our work presents strong evidence that symbolic abstraction of numeric domains can be efficient and practical for large and realistic programs.

Hybrid Approach for Enhancing Performance of Genomic Data for Stream Matching

In gene expression analysis, the expression levels of thousands of genes are analyzed, such as separate stages of treatments or diseases. Identifying particular gene sequence pattern is a challenging task with respect to performance issues. The proposed solution addresses the performance issues in genomic stream matching by involving assembly and sequencing. Counting the k-mer based on k-input value and while performing DNA sequencing tasks, the researches need to concentrate on sequence matching. The proposed solution addresses performance issue metrics such as processing time for k-mer counting, number of operations for matching similarity, memory utilization while performing similarity search, and processing time for stream matching. By suggesting an improved algorithm, Revised Rabin Karp(RRK) for basic operation and also to achieve more efficiency, the proposed solution suggests a novel framework based on Hadoop MapReduce blended with Pig & Apache Tez. The measure of memory utilization and processing time proposed model proves its efficiency when compared to existing approaches.

Hybrid Approach for Enhancing Performance of Genomic Data for Stream Matching

In gene expression analysis, the expression levels of thousands of genes are analyzed, such as separate stages of treatments or diseases. Identifying particular gene sequence pattern is a challenging task with respect to performance issues. The proposed solution addresses the performance issues in genomic stream matching by involving assembly and sequencing. Counting the k-mer based on k-input value and while performing DNA sequencing tasks, the researches need to concentrate on sequence matching. The proposed solution addresses performance issue metrics such as processing time for k-mer counting, number of operations for matching similarity, memory utilization while performing similarity search, and processing time for stream matching. By suggesting an improved algorithm, Revised Rabin Karp(RRK) for basic operation and also to achieve more efficiency, the proposed solution suggests a novel framework based on Hadoop MapReduce blended with Pig & Apache Tez. The measure of memory utilization and processing time proposed model proves its efficiency when compared to existing approaches.

Beyond Subjectiviness: Assessing Abilities and Preferences to Create Software Development Teams

The creation of software development teams that are affected by performance issues is a problem frequently observed in companies in the software development market. This process is commonly done through subjective methodologies. Such methodologies can be influenced by interpersonal relationships and susceptible to human error. This paper proposes a quantitative and data-oriented alternative to the process of forming workgroups through the use of a genetic algorithm capable of optimizing collaborator’s abilities and preferences when executing a specific task within a project. As a result, we show that the use of such genetic algorithm is able to create teams similar to the teams assembled by the project managers of companies in the industry of software engineering. Therefore, the ability of genetic algorithm on supporting the process of develoment teams assembly becomes evident.