Incremental Learning for Robot Perception through HRI

Scene understanding and object recognition is a difficult to achieve yet crucial skill for robots. Recently, Convolutional Neural Networks (CNN), have shown success in this task. However, there is still a gap between their performance on image datasets and real-world robotics scenarios. We present a novel paradigm for incrementally improving a robot's visual perception through active human interaction. In this paradigm, the user introduces novel objects to the robot by means of pointing and voice commands. Given this information, the robot visually explores the object and adds images from it to re-train the perception module. Our base perception module is based on recent development in object detection and recognition using deep learning. Our method leverages state of the art CNNs from off-line batch learning, human guidance, robot exploration and incremental on-line learning

An Empirical Study of Value Creation Criteria: Case of Iran

Today’s investors, creditors, and managers are look for an on-time and reliable index, with the goal of evaluating value creation amount. The aim of this study is inducing of voluble measures to users and increasing their understanding yielded these measures by comprise informative contexts accounting and economic measures for this purpose, present study by testing hypotheses and selecting 92 companies listed in Tehran’s Stock Exchange, from 2004 to 2008 is performed. The results of the study reveal that there is meaningful relation between accounting measures, just ROI and EPS with value creation.value creation, performance analysis, economic measures, and accounting measures

Modeling the interactions of forest cutting and climate change on the hydrology, biomass and biogeochemistry of a northeastern forest

Global and regional environmental disturbances, including harvesting and climate change, can lead to integrated and interactive effects on forest ecosystems, altering their structure and function, and therefore long-term sustainability. Understanding both short- and long-term impacts of harvesting practices (e.g., cutting rotation length, intensity) on forest dynamics is a key factor in developing criteria and guidelines for sustainable forest management practices. Process ecosystem models are useful tools to improve predictive understanding of complex, interacting ecological process and their response to disturbance. Few studies have rigorously tested model simulations against field measurements which would provide more confidence in efforts to quantify logging impacts over the long-term. The biogeochemical model, PnET-BGC has been used to simulate forest biomass, and soil and stream chemistry at the Hubbard Brook Experimental Forest (HBEF), New Hampshire, USA. Previous versions of PnET-BGC could accurately simulate the longer-term biogeochemical response to harvesting, but were unable to reproduce the marked changes in stream NO3- immediately after clear-cutting which is an important impact of this disturbance regime. Moreover, the dynamics of nutrients to and from major pools, including mineralization and plant uptake, were poorly predicted. The overall goal of this dissertation was to develop a simulation tool to evaluate short and long-term effects of harvesting on the hydrology and biogeochemistry of the northern forest. In the first phase of dissertation, PnET-BGC was modified and tested using field observations from an experimentally whole-tree harvested northern hardwood watershed (W5) at HBEF. In the second phase of dissertation, the parametrized/modified model was applied to other experimentally cut watersheds at the HBEF; including a devegetation experiment (W2; devegetation and herbicide treatment) and a commercial strip-cut (W4) to confirm the ability of the model to depict ecosystem response to a range of harvesting regimes. In the third phase of dissertation, the confirmed model was used as a heuristic tool to investigate long-term changes in aboveground biomass accumulation and nutrient dynamics under three different harvesting intensities (40%, 60%, 80% watershed cutting) for three rotation lengths (30, 60, 90 years) under both constant (current climate) and changing (MIROC5-RCP4.5) future climate through the year 2200. In this dissertation, the model was modified and parametrized allowing for a lower decomposition rate during the earlier years after the clear-cut and increased NH4+ plant uptake with the regrowth of new vegetation to adequately reproduce hydrology, aboveground forest biomass, and soil solution and stream water chemistry in response to a whole-tree harvest of a northern hardwood forest watershed (W5) at the HBEF. Revisions of algorithms of PnET-BGC significantly improved model performance in predicting short- and long-term dynamics of major elements for evaluating effects of various forest cutting strategies at the HBEF. The comparison among cut watersheds showed that around 15 years after the cuts, W5 biomass accumulated at a faster rate than W4 and W2. Despite some initial differences in species composition and biomass accumulation rates among the cut watersheds, simulations of total biomass for all three treated watersheds (W2, W4 and W5) are consistent with the expected growth trajectory of a second- growth watershed (W6) at the HBEF. These results suggest that though the different harvesting practices influence initial forest composition and growth, the overall impact on total aboveground biomass is minimal over the long-term at the HBEF. The modified two-soil-layer PnET-BGC was capable of capturing the immediate increase in stream concentrations of NO3-, Ca2+, Mg2+ and Na+ as well as enhanced adsorption of SO42- following the treatments and indicated a greater response for the devegetated W2 and the whole-tree harvested W5 than the strip-cut W4. Modeled soil solution Bs horizon and stream water chemistry successfully captured the rapid recovery of leaching nutrients to pre-cut levels after the treatments. Accurate simulation of vegetation regrowth allowed for improved prediction of the chemical response of soil and streamwater to cutting disturbance, indicating the important role of plant uptake in regulating the recovery of the forest ecosystem. Simulations for W2 showed more intense NO3- leaching associated with the herbicide treatment resulting in an accelerated decline in soil base saturation, to values lower than those anticipated from the effects of acid atmospheric deposition alone, and a slower recovery pattern during forest regrowth by the end of the simulation period (2100). A first-order sensitivity analyis showed that simulations by the model to a given level of perturbation of input parameters are more sensitive under mature forest (pre-cut) conditions than for an aggrading forest (post-cut conditions). Simulations of the interactions between forest harvest practices and future climate change for W5 demonstrated the greater sensitivity of forest ecosystem nutrient pools to logging strategies under climate change which included fertilization effects of atmospheric carbon dioxide, relative to constant climate conditions. These effects are accentuated with a shortening of the length of cutting interval and increasing forest harvesting intensity. Simulations of both constant and varying climate conditions considered showed greater sensitivity to varying the length of cutting period than altering cutting intensities. My simulations suggest that tree harvesting under constant current climate should affect living tree biomass and woody debris more than soil carbon, while under climate change, loss of soil organic matter pools may adversely affect site fertility. Depletion of soil base cations is accelerated under climate change due to increases in soil mineralization, coupled with increased plant uptake and enhanced biomass accumulation. Nitrogen is predicted to be the element which experiences the greatest relative loss over both short- and long- periods under different harvesting strategies, particularly with changing climate. Simulations show that all management options under climate change enhance both timber production and overall carbon storage in comparison to stationary climate, but with greater potential for a reduction in long-term soil fertility

Design and performance of cost-effective ultra high performance concrete for bridge deck overlays

The main objective of this research is to develop a cost-effective ultra-high performance concrete (UHPC) for bonded bridge deck overlays. The high durability and mechanical properties of such repair material can offer shorter traffic closures and prolong the service life of the pavement. The UHPC was optimized using supplementary cementitious materials (SCMs), proper combinations of sands, and adequate selection of fiber types and contents. Packing density studies included paste, sand, and fiber combinations. The robustness of optimized UHPC mixtures to variations of mixing and curing temperatures was examined. The efficiency of various shrinkage mitigation approaches in reducing autogenous and drying shrinkage of optimized UHPC mixtures was evaluated. This included the use of CaO-based and MgO-based expansive agents, shrinkage-reducing admixture, and pre-saturated lightweight sand. Optimized UHPC mixtures were cast as thin bonded overlays of 25, 38, and 50 mm in thickness over pavement sections measuring 1 × 2.5 m². Early-age and long-term deformation caused by concrete, humidity and temperature gradients, as well as cracking and delamination were monitored over time. Test results indicate that the designed UHPC mixtures exhibited relatively low autogenous shrinkage and drying shrinkage. The G50 mixture had the lowest autogenous and drying shrinkage of 255 µm/m at 28 days and 55 µm/m at 98 days, respectively. All tested UHPC mixtures exhibited a high mechanical properties and excellent frost durability. The use of 60% lightweight sand led to significantly reduction in autogenous shrinkage from 530 to 35 µm/m. Test results indicate that there was no surface cracking or delamination in UHPC overlays after 100 days of casting --Abstract, page iii

A SWARA-COPRAS approach to the allocation of risk in water and sewerage public–private partnership projects in Malaysia

In a situation of growing water demand, inadequate public funding, poor asset condition and lack of maintenance in developing countries, public-private partnerships (PPPs) play an important role in the development of infrastructure, such as water supply and sewerage services. The purpose of this study is to develop a quantitative approach to appropriate risk allocation, with attention directed to the impact of positive and negative factors in water and sewerage projects. The paper presents a hybrid SWARA-COPRAS approach to examine risk allocation, particularly for PPP water supply and sewerage projects in the context of Malaysia. In addition to PPP infrastructure projects, the approach has the potential to be adapted to other applications. The proposed method enables decision makers to utilise qualitative linguistic terms in the allocation of risk between the public and private sector, and to select the best strategy for risk allocation in a contract. Finally, 24 significant risks were identified: six risks would preferably be allocated to the public sector, while seven risks would be assigned to the private sector, and eleven risks would preferably be shared by both parties. The finding from this study can help the government of Malaysia to determine an attractive political strategy for private investors to support a PPP water and sewerage infrastructure project

The Role Of Urban Density And Morphology In The Air Pollution Of Tehran Metropolitan

Today, regard for the wellbeing of the group and the earth is on the plan of most nations on the planet, and one of its imperative viewpoints is the contamination of the air and figuring out how to diminish it. Without a doubt, a standout amongst the most vital ranges that assume an unequivocal part in decreasing or expanding this parameter is the city and urban morphology. Tehran, which is viewed as the capital and vital city of Iran, has experienced this issue for a long time, and there are no legitimate arrangement found to decrease its air contamination. Then again, the city has movement from different parts of the nation consistently that makes this issue harsher. The most vital issue in such manner is the city's range, and in addition, the city's extension, which decides the thickness of the city.  The failure of the vast majority to purchase houses inside the city has made satellite towns nearby Tehran. Then again, the presence of tremendous local locations around Tehran and the area of workplaces in the downtown area are among alternate issues tended to in this investigation. This examination endeavoured to utilize the explanatory expressive technique to think about the part of pressure and morphology of Tehran and its effect on the air contamination and give answers for diminishing air contamination and movement

Channel Optimized Distributed Multiple Description Coding

In this paper, channel optimized distributed multiple description vector quantization (CDMD) schemes are presented for distributed source coding in symmetric and asymmetric settings. The CDMD encoder is designed using a deterministic annealing approach over noisy channels with packet loss. A minimum mean squared error asymmetric CDMD decoder is proposed for effective reconstruction of a source, utilizing the side information (SI) and its corresponding received descriptions. The proposed iterative symmetric CDMD decoder jointly reconstructs the symbols of multiple correlated sources. Two types of symmetric CDMD decoders, namely the estimated-SI and the soft-SI decoders, are presented which respectively exploit the reconstructed symbols and a posteriori probabilities of other sources as SI in iterations. In a multiple source CDMD setting, for reconstruction of a source, three methods are proposed to select another source as its SI during the decoding. The methods operate based on minimum physical distance (in a wireless sensor network setting), maximum mutual information and minimum end-to-end distortion. The performance of the proposed systems and algorithms are evaluated and compared in detail.Comment: Submitted to IEEE Transaction on Signal Processin