Learning multiple experiences useful visual features for active maps localization in crowded environments

Crowded urban environments are composed of different types of dynamic and static elements. Learning and classification of features is a major task in solving the localization problem in such environments. This work presents a gradual learning methodology to learn the useful features using multiple experiences. The usefulness of an observed element is evaluated by a scoring mechanism which uses two scores – reliability and distinctiveness. The visual features thus learned are used to partition the visual map into smaller regions. The robot is efficiently localized in such a partitioned environment using two-level localization. The concept of active map (AM) is proposed here, which is a map that represents one partition of the environment in which there is a high probability of the robot existing. High-level localization is used to track the mode of the AMs using discrete Bayes filter. Low-level localization uses a bag-of-words model to retrieve images and accurately localize the robot. The pose of the robot is the one retrieved from the AM that has maximum a posteriori. Experiments have been conducted on a unique highly crowded data-set collected from Indian roads. The results support the proposed method due to speed and localization accuracy.     

Deep features-based speech emotion recognition for smart affective services

Emotion recognition from speech signals is an interesting research with several applications like smart healthcare, autonomous voice response systems, assessing situational seriousness by caller affective state analysis in emergency centers, and other smart affective services. In this paper, we present a study of speech emotion recognition based on the features extracted from spectrograms using a deep convolutional neural network (CNN) with rectangular kernels. Typically, CNNs have square shaped kernels and pooling operators at various layers, which are suited for 2D image data. However, in case of spectrograms, the information is encoded in a slightly different manner. Time is represented along the x-axis and y-axis shows frequency of the speech signal, whereas, the amplitude is indicated by the intensity value in the spectrogram at a particular position. To analyze speech through spectrograms, we propose rectangular kernels of varying shapes and sizes, along with max pooling in rectangular neighborhoods, to extract discriminative features. The proposed scheme effectively learns discriminative features from speech spectrograms and performs better than many state-of-the-art techniques when evaluated its performance on Emo-DB and Korean speech dataset.

     

The effect of some alloying elements on the corrosion resistance of lead-antimony alloys — II. Silver

The effect of Ag on the stationary and non-stationary anodic corrosion rates of PbSbCd and PbSb alloys in H₂SO₄ has been studied. Anodic polarization curves were constructed under galvanostatic and potentiostatic conditions. Optical microscopic examination and microprobe analysis of the alloys were conducted. The beneficial effect of Ag was ascribed to a delay in closure of pores in the initial PbSO₄ film. The leaching out of Sb from the outermost layers and the simultaneous nucleation of PbSO₄ and Ag₂SO₄ from supersaturated solutions in the pores is thus made possible.     

Atomic-Resolution Structures and Mode of Action of Clinically Relevant Antimicrobial Peptides

Global rise of infections and deaths caused by drug-resistant bacterial pathogens are among the unmet medical needs. In an age of drying pipeline of novel antibiotics to treat bacterial infections, antimicrobial peptides (AMPs) are proven to be valid therapeutics modalities. Direct in vivo applications of many AMPs could be challenging; however, works are demonstrating encouraging results for some of them. In this review article, we discussed 3-D structures of potent AMPs e.g., polymyxin, thanatin, MSI, protegrin, OMPTA in complex with bacterial targets and their mode of actions. Studies on human peptide LL37 and de novo-designed peptides are also discussed. We have focused on AMPs which are effective against drug-resistant Gram-negative bacteria. Since treatment options for the infections caused by super bugs of Gram-negative bacteria are now extremely limited. We also summarize some of the pertinent challenges in the field of clinical trials of AMPs.     

BUILDING USER TASK SPACE BY MINING TEMPORALLY PROXIMATE DESKTOP ACTIONS

Awareness of the user's current context, that is, the task the user resides in, can allow for various ways of supporting their work. In this article we present a novel approach for mining user's regular tasks on the basis of temporal proximity of users’ desktop actions without user intervention in a completely automatic, unobtrusive, and unsupervised manner. The proposed method is based on time-based clustering of a user's desktop actions and, in contrast to previous approaches, it does not enforce fixed time constraints on the mined actions, and typical transition times, when they exist, emerge from the logged activity data for that specific user. The performance of our technique was evaluated on a large data set of 724 days of desktop work by five knowledge workers. The results showed that our approach performed very well and was able to cluster those temporally proximate user actions that commonly used fix time window techniques fail to deal with. Notably, the main improvement is in the recall of the tasks, where our approach recalled 10.18% more actions than the predefined time window technique.     

Effects of thermal and mechanical activation methods on compressive strength of ordinary Portland cement–slag mortar

Activation methods and curing regimes have crucial effects on the strength of mortars and concretes. The objective of this investigation is to examine the early and later compressive strength of activated ordinary Portland cement (OPC)–ground granulated blast-furnace slag (GGBFS) mortars and identify the most effective activation technique. The methods of activation used were thermal, mechanical and thermal–mechanical combined. Two curing regimes were adopted and five groups of mortars were prepared. It was observed that OPC–GGBFS mortars have greater sensitivity to OPC mortars against the curing regimes. However, the study revealed that there was no particular activation method which when used gave the best results for both early and later strengths and did not cause strength loss. It also proved that the most effective activation method for early strength is a combination of both the thermal and mechanical, while for later strengths, none of the activation methods was recommended.     

Physicochemical Properties of Mammalian Gelatin in Relation to Membrane Process Requirement

In any of the membrane process application, understanding of the characteristics of the feed solution is essential in order to achieve desired level of separation performance. In this study, in an effort to substitute evaporation with membrane processes partially, experiments were carried out to investigate the physicochemical properties of gelatins, namely, molecular weight distribution, pH, viscosity, isoelectric point, and gel strength, which are, of foremost, important parameters in the characterization of gelatin. Two different mammalian gelatins, i.e. from bovine (type B) and porcine (type A) sources, were used in this study. The pH was significantly varied for all gelatins in the vicinity of 4.75–5.51 (±0.01). Experimental result revealed that both sources of mammalian gelatin contained components of different molecular weights with wide distribution ranging from 10 to 400 kDa. Analysis of the molecular weight distribution result also showed strong correlation between average molecular weight and gel strength of gelatin. The isoelectric points of gelatins from bovine were 4.60 ± 0.08 to 5.25 ± 0.43 and porcine gelatins were in the range of 7–9.3, which agreed well with the results obtained from other researchers. The high bloom strength mammalian gelatins were also significantly more viscous and thus, had a higher melting point.     

Performance analysis of an industrial waste heat‐based trigeneration system

The thermodynamic performance of an industrial waste heat recovery‐based trigeneration system is studied through energy and exergy efficiency parameters. The effects of exhaust gas inlet temperature, process heat pressure, and ambient temperature on both energy and exergy efficiencies, and electrical to thermal energy ratio of the system are investigated. The energy efficiency increases while electrical to thermal energy ratio and exergy efficiency decrease with increasing exhaust gas inlet temperature. On the other hand, with the increase in process heat pressure, energy efficiency decreases but exergy efficiency and electrical to thermal energy ratio increase. The effect of ambient temperature is also observed due to the fact that with an increase in ambient temperature, energy and exergy efficiencies, and electrical to thermal energy ratio decrease slightly. These results clearly show that performance evaluation of trigeneration system based on energy analysis is not adequate and hence more meaningful evaluation must include exergy analysis. The present analysis contributes to further information on the role of exhaust gas inlet temperature, process heat pressure, ambient temperature influence on the performance of waste heat recovery‐based trigeneration from a thermodynamic point of view. Copyright © 2009 John Wiley & Sons, Ltd.     

Optimization of biohydrogen production by Clostridium butyricum EB6 from palm oil mill effluent using response surface methodology

Clostridium butyricum EB6 successfully produced hydrogen gas from palm oil mill effluent (POME). In this study, central composite design and response surface methodology were applied to determine the optimum conditions for hydrogen production (P_c) and maximum hydrogen production rate (R_max) from POME. Experimental results showed that the pH, temperature and chemical oxygen demand (COD) of POME affected both the hydrogen production and production rate, both individually and interactively. The optimum conditions for hydrogen production (P_c) were pH 5.69, 36 °C, and 92 g COD/l; with an estimated P_c value of 306 ml H₂/g carbohydrate. The optimum conditions for maximum hydrogen production rate (R_max) were pH 6.52, 41 °C and 60 g COD/l; with an estimated R_max value of 914 ml H₂/h. An overlay study was performed to obtain an overall model optimization. The optimized conditions for the overall model were pH 6.05, 36 °C and 94 g COD/l. The hydrogen content in the biogas produced ranged from 60% to 75%.     

New Synthetic Control Charts for Monitoring Process Mean and Process Dispersion

A statistical quality control chart is widely recognized as a potentially powerful tool that is frequently used in many manufacturing and service industries to monitor the quality of the product or manufacturing processes. In this paper, we propose new synthetic control charts for monitoring the process mean and the process dispersion. The proposed synthetic charts are based on ranked set sampling (RSS), median RSS (MRSS), and ordered RSS (ORSS) schemes, named synthetic‐RSS, synthetic‐MRSS, and synthetic‐ORSS charts, respectively. Average run lengths are used to evaluate the performances of the control charts. It is found that the synthetic‐RSS and synthetic‐MRSS mean charts perform uniformly better than the Shewhart mean chart based on simple random sampling (Shewhart‐SRS), synthetic‐SRS, double sampling‐SRS, Shewhart‐RSS, and Shewhart‐MRSS mean charts. The proposed synthetic charts generally outperform the exponentially weighted moving average (EWMA) chart based on SRS in the detection of large mean shifts. We also compare the performance of the synthetic‐ORSS dispersion chart with the existing powerful dispersion charts. It turns out that the synthetic‐ORSS chart also performs uniformly better than the Shewhart‐R, Shewhart‐S, synthetic‐R, synthetic‐S, synthetic‐D, cumulative sum (CUSUM) ln S², CUSUM‐R, CUSUM‐S, EWMA‐ln S², and change point CUSUM charts for detecting increases in the process dispersion. A similar trend is observed when the proposed synthetic charts are constructed under imperfect RSS schemes. Illustrative examples are used to demonstrate the implementation of the proposed synthetic charts. Copyright © 2014 John Wiley & Sons, Ltd.