Software cost estimation with incomplete data

The construction of software cost estimation models remains an active topic of research. The basic premise of cost modeling is that a historical database of software project cost data can be used to develop a quantitative model to predict the cost of future projects. One of the difficulties faced by workers in this area is that many of these historical databases contain substantial amounts of missing data. Thus far, the common practice has been to ignore observations with missing data. In principle, such a practice can lead to gross biases and may be detrimental to the accuracy of cost estimation models. We describe an extensive simulation where we evaluate different techniques for dealing with missing data in the context of software cost modeling. Three techniques are evaluated: listwise deletion, mean imputation, and eight different types of hot-deck imputation. Our results indicate that all the missing data techniques perform well with small biases and high precision. This suggests that the simplest technique, listwise deletion, is a reasonable choice. However, this will not necessarily provide the best performance. Consistent best performance (minimal bias and highest precision) can be obtained by using hot-deck imputation with Euclidean distance and a z-score standardization     

On the generation of test patterns for multiple faults

This article presents a new method to generate test patterns for multiple stuck-at faults in combinational circuits. We assume the presence of all multiple faults of all multiplicities and we do not resort to their explicit enumeration: the target fault is a single component of possibly several multiple faults. New line and gate models are introduced to handle multiple fault effect propagation through the circuits. The method tries to generate test conditions that propagate the effect of the target fault to primary outputs. When these conditions are fulfilled, the input vector is a test for the target fault and it is guaranteed that all multiple faults of all multiplicities containing the target fault as component are also detected. The method uses similar techniques to those in FAN and SOCRATES algorithms to guide the search part of the algorithm, and includes several new heuristics to enhance the performance and fault detection capability. Experiments performed on the ISCAS'85 benchmark circuits show that test sets for multiple faults can be generated with high fault coverage and a reasonable increase in cost over test generation for single stuck-at faults.     

Effect of heat treatment on the structural and optical properties of CuInTe2 thin films

The CuInTe2 thin films were prepared by thermal vacuum evaporation of the bulk compound. The structural and optical properties in the temperature range 300–47 K of thin films grown on glass substrates and annealed in vacuum were studied. The films were investigated by X-ray diffraction and electron microscope techniques. The calculated lattice constants for CuInTe₂ powder were found to bea=0.619 nm andc –1,234 nm. From the reflection and transmission data, the optical constants, refractive indexn, absorption index,k, and the absorption coefficient, , werw computed. The optical energy gap was determined for CuInTe₂ thin films heat treated at different temparatures for different periods of time. It was found thatE _g increases with both increasing temperature and time of annealing.     

Explanation-Based Learning for Diagnosis

We present explanation-based learning (EBL) methods aimed at improving the performance of diagnosis systems integrating associational and model-based components. We consider multiple-fault model-based diagnosis (MBD) systems and describe two learning architectures. One, EBLIA, is a method for learning in advance. The other, EBL(p), is a method for learning while doing. EBLIA precompiles models into associations and relies only on the associations during diagnosis. EBL(p) performs compilation during diagnosis whenever reliance on previously learned associational rules results in unsatisfactory performance—as defined by a given performance threshold p. We present results of empirical studies comparing MBD without learning versus EBLIA and EBL(p). The main conclusions are as follows. EBLIA is superior when it is feasible, but it is not feasible for large devices. EBL(p) can speed-up MBD and scale-up to larger devices in situations where perfect accuracy is not required.     

Ferrimagnetic resonance and low temperature transition in Ni- and Co-substituted powder magnetite

The effects of nickel and cobalt substitution on ferrimagnetic resonance in high-purity magnetite powder have been investigated. The low-temperature transition temperature and damping parameter, , are found to decrease with increasing solute additions. The linewidth, H, varies in proportion to the anisotropy field of the ferrites, narrowing with increasing nickel content but broadening with increasing cobalt content. Theg factor increases with the dopant concentration, passing through a maximum around room temperature. Decreasing the deviation from stoichiometry by appropriate annealing decreases the transition temperature shift but slightly increases H, g and .     

Intracellular localization of samarium in the lactating mammary gland cells: ultrastructural and microanalytical study

The frequent use of some rare earths in the medical and industrial domains make us worry about their intracellular behavior into the body. Reason for which we have investigated the subcellular localization of one of these elements, the samarium, in the mammary gland of lactating female wistar rats using two very sensitive methods of observation and microanalysis, the transmission electron microscopy and the secondary ion mass spectrometry. The ultrastructural study showed the presence of electron dense deposits in the lactating mammary glandular epithelial cell lysosomes of the samarium-treated rats, but no loaded lysosomes were observed in those of control rats. The microanalytical study allowed both the identification of the chemical species present in those deposits as samarium isotopes ((152) Sm(+)) and the cartography of its distribution. Our results confirm the previous ones showing that lysosomes of the glandular epithelial cells are the site of the intracellular concentration of foreign elements such as gallium. The intralysosomal deposits observed in the mammary glandular cells of the samarium-treated rats are similar in their form and density to those observed with the same element in other varieties of cells, such as liver, bone marrow, and spleen cells. Our ultrastructural and microanalytical results and those obtained in previous studies allow deducing that the intralysosomal deposits are very probably composed of an insoluble samarium phosphate salt.     

Assessment of sediment quality and pore water ecotoxicity in Kebir Rhumel basin (NE-Algeria): a combined approach

The objectives of this study are to use different approaches to assess the current pollution status in the wadis of the Kebir Rhumel basin. First, sediment trace metal contents were measured by flame atomic absorption spectroscopy. Then, sediment quality was assessed on the basis of contamination assessment indexes such as: Geoaccumulation Index (Igeo), Contamination factor (C(f)), Contamination degree (C(d)), Sediment Pollution Index (SPI) and SEQ guidelines (Consensus Sediment Quality Guidelines). In addition, several toxicity tests (Daphnia magna mobility inhibition acute test-48 h, Aliivibrio fischeri luminescence inhibition acute test - 15/30 mn and Pseudokirchneriella subcapitata growth inhibition chronic test - 72 h) were conducted to assess sediment pore water ecotoxicity. Trace metal concentrations followed the order: Mn > Zn > Pb > Cr > Cu > Ni > Co > Cd. Indexes used indicate varying degrees of sediment quality. Igeo, C(f), C(d) and SPI reveal a polymetallic contamination dominated by two or more elements in which Cd, Cu and Pb are of greatest concern. SEQ guidelines showed that biological effects on fauna would likely be observed occasionally and/or frequently for Cd, Cr, Cu, Pb and Zn contents. Test organisms exposed to sediment pore water showed that the algal P. subcapitata test was more sensitive than the D. magna and A. fischeri tests. Hence, algal growth inhibition proved to be the most sensitive response to contaminants present in sediment extracts but a significant relationship with trace metal contents was not demonstrated.     

Solving knapsack problems on GPU

A parallel implementation via CUDA of the dynamic programming method for the knapsack problem on NVIDIA GPU is presented. A GTX 260 card with 192 cores (1.4 GHz) is used for computational tests and processing times obtained with the parallel code are compared to the sequential one on a CPU with an Intel Xeon 3.0 GHz. The results show a speedup factor of 26 for large size problems. Furthermore, in order to limit the communication between the CPU and the GPU, a compression technique is presented which decreases significantly the memory occupancy.     

3D model based tracking for omnidirectional vision: A new spherical approach

The current work addresses the problem of 3D model tracking in the context of monocular and stereo omnidirectional vision in order to estimate the camera pose. To this end, we track 3D objects modeled by line segments because the straight line feature is often used to model the environment. Indeed, we are interested in mobile robot navigation using omnidirectional vision in structured environments. In the case of omnidirectional vision, 3D straight lines are projected as conics in omnidirectional images. Under certain conditions, these conics may have singularities.In this paper, we present two contributions. We, first, propose a new spherical formulation of the pose estimation withdrawing singularities, using an object model composed of lines. The theoretical formulation and the validation on synthetic images thus show that the new formulation clearly outperforms the former image plane one. The second contribution is the extension of the spherical representation to the stereovision case. We consider in the paper a sensor which combines a camera and four mirrors. Results in various situations show the robustness to illumination changes and local mistracking. As a final result, the proposed new stereo spherical formulation allows us to localize online a robot indoor and outdoor whereas the classical formulation fails.     

Vision Based UAV Attitude Estimation: Progress and Insights

Unmanned aerial vehicles (UAVs) are increasingly replacing manned systems in situations that are dangerous, remote, or difficult for manned aircraft to access. Its control tasks are empowered by computer vision technology. Visual sensors are robustly used for stabilization as primary or at least secondary sensors. Hence, UAV stabilization by attitude estimation from visual sensors is a very active research area. Vision based techniques are proving their effectiveness and robustness in handling this problem. In this work a comprehensive review of UAV vision based attitude estimation approaches is covered, starting from horizon based methods and passing by vanishing points, optical flow, and stereoscopic based techniques. A novel segmentation approach for UAV attitude estimation based on polarization is proposed. Our future insightes for attitude estimation from uncalibrated catadioptric sensors are also discussed.