Integrate the GM(1,1) and Verhulst models to predict software stage effort

This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Software effort prediction clearly plays a crucial role in software project management. In keeping with more dynamic approaches to software development, it is not sufficient to only predict the whole-project effort at an early stage. Rather, the project manager must also dynamically predict the effort of different stages or activities during the software development process. This can assist the project manager to reestimate effort and adjust the project plan, thus avoiding effort or schedule overruns. This paper presents a method for software physical time stage-effort prediction based on grey models GM(1,1) and Verhulst. This method establishes models dynamically according to particular types of stage-effort sequences, and can adapt to particular development methodologies automatically by using a novel grey feedback mechanism. We evaluate the proposed method with a large-scale real-world software engineering dataset, and compare it with the linear regression method and the Kalman filter method, revealing that accuracy has been improved by at least 28% and 50%, respectively. The results indicate that the method can be effective and has considerable potential. We believe that stage predictions could be a useful complement to whole-project effort prediction methods.National Natural Science Foundation of China and the Hi-Tech Research and Development Program of Chin

Historical contingency in species interactions: towards niche-based predictions.

The way species affect one another in ecological communities often depends on the order of species arrival. The magnitude of such historical contingency, known as priority effects, varies across species and environments, but this variation has proven difficult to predict, presenting a major challenge in understanding species interactions and consequences for community structure and function. Here, we argue that improved predictions can be achieved by decomposing species' niches into three components: overlap, impact and requirement. Based on classic theories of community assembly, three hypotheses that emphasise related, but distinct influences of the niche components are proposed: priority effects are stronger among species with higher resource use overlap; species that impact the environment to a greater extent exert stronger priority effects; and species whose growth rate is more sensitive to changes in the environment experience stronger priority effects. Using nectar-inhabiting microorganisms as a model system, we present evidence that these hypotheses complement the conventional hypothesis that focuses on the role of environmental harshness, and show that niches can be twice as predictive when separated into components. Taken together, our hypotheses provide a basis for developing a general framework within which the magnitude of historical contingency in species interactions can be predicted

Per capita interactions and stress tolerance drive stress-induced changes in biodiversity effects on ecosystem functions

Environmental stress changes the relationship between biodiversity and ecosystem functions, but the underlying mechanisms are poorly understood. Because species interactions shape biodiversity-ecosystem functioning relationships, changes in per capita interactions under stress (as predicted by the stress gradient hypothesis) can be an important driver of stress-induced changes in these relationships. To test this hypothesis, we measure productivity in microalgae communities along a diversity and herbicide gradient. On the basis of additive partitioning and a mechanistic community model, we demonstrate that changes in per capita interactions do not explain effects of herbicide stress on the biodiversity-productivity relationship. Instead, assuming that the per capita interactions remain unaffected by stress, causing species densities to only change through differences in stress tolerance, suffices to predict the stress-induced changes in the biodiversity-productivity relationship and community composition. We discuss how our findings set the stage for developing theory on how environmental stress changes biodiversity effects on ecosystem functions

Organic farming enhances parasitoid diversity at the local and landscape scales

1. The magnitude of the benefits derived from organic farming within contrasting managed landscapes remains unclear and, in particular, the potential scale-dependent response of insect parasitoids is relatively unexplored. Identifying the scale at which parasitoids are affected by organic farming will be an important step to enhance their conservation. 2. We sampled tachinid parasitoids at the centre and margin of arable and grassland fields on paired organic and conventional farms located in landscapes with different proportions of organic land. A total of 192 fields were sampled in two biogeographical regions of the UK. 3. We found that the positive effect of organic farming on tachinid parasitoid diversity can be observed at multiple spatial scales. At the local scale, we found higher abundance and species richness of tachinid parasitoids on organic than on conventional farms and on field margins than on field centres. At the landscape scale, the diversity of tachinids was higher in landscapes with higher proportions of organic land. At both scales, the positive effect of organic farming was clear for arable fields, while it was almost neutral for grasslands. 4. Synthesis and applications. Any attempt to enhance parasitoid diversity in agricultural landscapes needs to consider the local management in relation to the habitat type, location within the field and agricultural management in the surrounding landscape. To restore parasitoid diversity, the promotion of organic agriculture should aim to increase both the total extent of organic farming and the connectivity of individual farms. As the benefits of organic farming to biodiversity clearly spread beyond individual farm boundaries, any assessment of organic farming should consider these positive externalities

Stingless bee further improve apple pollination and production

The use of Africanised honeybee (Apis mellifera scutellata Lepeletier) hives to increase pollination success in apple orchards is a widespread practice. However, this study is the first to investigate the number of honeybee hives ha-1 required to increase the production of fruits and seeds as well as the potential contribution of the stingless bee Mandaçaia (Melipona quadrifasciata anthidioides Lepeletier). We performed tests in a 43-ha apple orchard located in the municipality of Ibicoara (13º24’50.7’’S and 41º17’7.4’’W) in Chapada Diamantina, State of Bahia, Brazil. In 2011, fruits from the Eva variety set six seeds on average, and neither a greater number of hives (from 7 to 11 hives ha-1) nor a greater number of pollen collectors at the honeybee hives displayed general effects on the seed number. Without wild pollinators, seven Africanised honeybee hives ha-1 with pollen collectors is currently the best option for apple producers because no further increase in the seed number was observed with higher hive densities. In 2012, supplementation with both stingless bees (12 hives ha-1) and Africanised honeybees (7 hives ha-1) provided higher seed and fruit production than supplementation with honeybees (7 hives ha-1) alone. Therefore, the stingless bee can improve the performance of honeybee as a pollinator of apple flowers, since the presence of both of these bees results in increases in apple fruit and seed number.Fil: Blandina Felipe, Viana. Universidade Federal da Bahia; BrasilFil: da Encarnação Coutinho, Jeferson Gabriel. Universidade Federal da Bahia; BrasilFil: Garibaldi, Lucas Alejandro. Universidad Nacional de Rio Negro. Sede Andina; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Bragança Gastagnino, Guido Laercio. Universidade Federal da Bahia; BrasilFil: Gramacho, Katia Peres. Katia Peres; BrasilFil: Oliveira da Silva, Fabiana. Universidade Federal da Bahia; Brasi

A novel robust predictive control system over imperfect networks

This paper aims to study on feedback control for a networked system with both uncertain delays, packet dropouts and disturbances. Here, a so-called robust predictive control (RPC) approach is designed as follows: 1- delays and packet dropouts are accurately detected online by a network problem detector (NPD); 2- a so-called PI-based neural network grey model (PINNGM) is developed in a general form for a capable of forecasting accurately in advance the network problems and the effects of disturbances on the system performance; 3- using the PINNGM outputs, a small adaptive buffer (SAB) is optimally generated on the remote side to deal with the large delays and/or packet dropouts and, therefore, simplify the control design; 4- based on the PINNGM and SAB, an adaptive sampling-based integral state feedback controller (ASISFC) is simply constructed to compensate the small delays and disturbances. Thus, the steady-state control performance is achieved with fast response, high adaptability and robustness. Case studies are finally provided to evaluate the effectiveness of the proposed approach

Design of a digital compression technique for shuttle television

The determination of the performance and hardware complexity of data compression algorithms applicable to color television signals, were studied to assess the feasibility of digital compression techniques for shuttle communications applications. For return link communications, it is shown that a nonadaptive two dimensional DPCM technique compresses the bandwidth of field-sequential color TV to about 13 MBPS and requires less than 60 watts of secondary power. For forward link communications, a facsimile coding technique is recommended which provides high resolution slow scan television on a 144 KBPS channel. The onboard decoder requires about 19 watts of secondary power

Kernel Analog Forecasting: Multiscale Test Problems

Data-driven prediction is becoming increasingly widespread as the volume of data available grows and as algorithmic development matches this growth. The nature of the predictions made, and the manner in which they should be interpreted, depends crucially on the extent to which the variables chosen for prediction are Markovian, or approximately Markovian. Multiscale systems provide a framework in which this issue can be analyzed. In this work kernel analog forecasting methods are studied from the perspective of data generated by multiscale dynamical systems. The problems chosen exhibit a variety of different Markovian closures, using both averaging and homogenization; furthermore, settings where scale-separation is not present and the predicted variables are non-Markovian, are also considered. The studies provide guidance for the interpretation of data-driven prediction methods when used in practice.Comment: 30 pages, 14 figures; clarified several ambiguous parts, added references, and a comparison with Lorenz' original method (Sec. 4.5