Developing a requirements management toolset: Lessons learned

Requirements Engineering (RE) is a multi-faceted discipline involving various methods, techniques and tools. RE researchers and practitioners are emphasizing the importance of having an integrated RE process. The need for an integrated toolset to support the effective management of such an integrated RE process cannot be over-emphasized. Tools integration has been identified as an important next step toward the future of requirements management tools. This paper reports on some of the significant architectural and technical issues encountered and the lessons learned in the process of developing an integrated Requirements Management (RM) Toolset: PARsed Natural language Input Processor (PARSNIP) by integrating various independent tools. This paper provides insights on architectural and technological issues typical of these types of projects, the approaches and techniques used to address the architectural mismatches and the technological incompatibilities

Towards Agile Scalability Engineering

Scalability engineering is currently not well integrated into agile development techniques. This paper extends agile development techniques so that scalability can be handled in an incremental and iterative development process. By scalability we mean the ability of a system to handle increasing workload. We propose the ScrumScale Method which includes scalability engineering in Scrum. This extension should also be applicable to other agile techniques. For scalability testing, we indicate how quality thresholds should be scaled up or down according to the degree of completeness of the product, test hardware, test software, test data and test workload. Using action research, we have conducted three pilots in three Norwegian software organizations. These three pilots have different architectures and operate in different markets yet have in common scalability challengespublishedVersio

Cost Function based Soft Feedback Iterative Channel Estimation in OFDM Underwater Acoustic Communication

Underwater Acoustic (UWA) communication is mainly characterized by bandwidth limited complex UWA channels. Orthogonal Frequency Division Multiplexing (OFDM) solves the bandwidth problem and an efficient channel estimation scheme estimates the channel parameters. Iterative channel estimation refines the channel estimation by reducing the number of pilots and coupling the channel estimator with channel decoder. This paper proposes an iterative receiver for OFDM UWA communication, based on a novel cost function threshold driven soft decision feedback iterative channel technique. The receiver exploits orthogonal matching pursuit (OMP) channel estimation and low density parity check (LDPC) coding techniques after comparing different channel estimation and coding schemes. The performance of the proposed receiver is verified by simulations as well as sea experiments. Furthermore, the proposed iterative receiver is compared with other non-iterative and soft decision feedback iterative receivers

Security requirement management for cloud-assisted and internet of things⇔enabled smart city

The world is rapidly changing with the advance of information technology. The expansion of the Internet of Things (IoT) is a huge step in the development of the smart city. The IoT consists of connected devices that transfer information. The IoT architecture permits on-demand services to a public pool of resources. Cloud computing plays a vital role in developing IoT-enabled smart applications. The integration of cloud computing enhances the offering of distributed resources in the smart city. Improper management of security requirements of cloud-assisted IoT systems can bring about risks to availability, security, performance, confidentiality, and privacy. The key reason for cloud- and IoT-enabled smart city application failure is improper security practices at the early stages of development. This article proposes a framework to collect security requirements during the initial development phase of cloud-assisted IoT-enabled smart city applications. Its three-layered architecture includes privacy preserved stakeholder analysis (PPSA), security requirement modeling and validation (SRMV), and secure cloud-assistance (SCA). A case study highlights the applicability and effectiveness of the proposed framework. A hybrid survey enables the identification and evaluation of significant challenges

Pentaquarks: review of the experimental evidence

Pentaquarks, namely baryons made by 4 quarks and one antiquark have been predicted and searched for since several decades without success. Theoretical and experimental advances in the last 2 years led to the observation of a number of pentaquark candidates. We review the experimental evidence for pentaquarks as well as their non-observations by some experiments, and discuss to which extend these sometimes contradicting informations may lead to a consistent picture.Comment: Contribution to the International Conference on 'Strangeness in Quark Matter', 15-21 Sept. 2004, Cape Tawn, South Afric

Genetic analysis of indirect selection for winter wheat grain yield using spectral reflectance indices

Selection criteria that can facilitate grain yield improvement would be considered important plant breeding tools. We assessed the value of spectral reflectance indices (SRI) as indirect selection tools for grain yield improvement in winter wheat (Triticum aestivum L.). The objectives of this study were to estimate genetic correlation between SRI and grain yield, heritability, response to selection, correlated response of grain yield, and relative selection efficiency of SRI for grain yield improvement. Three field experiments consisting of 25 winter wheat cultivars and 2 sets of 25 recombinant inbred lines were conducted in the Oklahoma State University Agronomy Farm for 2 yr. Eight SRI were calculated at three growth stages (booting, heading, and grain-filling). The water-based indices (water index and normalized water indices) showed moderate to high heritability and higher genetic correlations with grain yield compared to the commonly used vegetation-based indices (normalized difference vegetation index and simple ratio). The water-based indices also showed higher correlated response than direct response for grain yield. Up to 83% of the top 25% highest-yielding genotypes were selected by the two newly developed water-based indices (normalized water index 3 [NWI-3] and normalized water index 4 [NWI-4]). These results suggest the strong genetic basis of NWI-3 and NWI-4 as potential selection tools for winter wheat grain yield improvement under Great Plains conditions.Peer reviewedPlant and Soil SciencesBiosystems and Agricultural Engineerin