Exploration of perovskite-like catalysts: Ba2CoWO6 and Ba2FeNbO6 in NO reduction and CO oxidation

The perovskite-like compounds Ba₂CoWO₆ and Ba₂FeNbO₆ are active catalysts in the reduction of NO with a mixture of CO and H₂ and in the oxidation of CO with O₂. Crushed single crystals of the compounds were used in a continuous-flow reactor. The catalytic activity is comparable to that of manganese-based rare-earth perovskites. However, the present “double perovskites” do not show a selective reduction of NO to N₂O and N₂, but also yield NH₃ in the entire temperature range where they are active. The catalytic activity for CO oxidation is dependent on the oxidation state of the catalysts. Ba₂FeNbO₆ is somewhat more active than Ba₂CoWO₆ in NO reduction and CO oxidation. Their activities are compared with KNbO₃, LaFeO₃ and LaCoO₃.     

On the application of remote sensing towards the estimation of cultivated land lost to urbanization

In this research work, a 40-km² SPOT-5 High-Resolution Imagery (HRI) of the Warsak locality in district Peshawar, Pakistan, was utilized to approximate the quantity of cultivated land lost to urbanization, due to the construction of new homes and buildings. The imagery from a period of 2005 to 2015 for wheat crop was taken, specifically during the months of March and June when the crop is rich green and golden ripe respectively. eCognition ® program’s Object-Oriented Classification Method (OOCM) was employed for recognition of land versus buildings. Nearest Neighbour (NN), Support Vector Machine (SVM), Decision Trees (DT) and Random Forests (RF) were utilized for the classification process. The results demonstrated that the urbanized area had increased by approximately 28 per cent in the area considered. Moreover, the efficacy of the proposed method is depicted by an accuracy of 97.9 per cent and a Kappa Statistics of 0.975 for the SVM classifier.     

Root Cause Failure Analysis of a Domestic Pressure Cooker Through Metallurgical Characterization and Computational Simulation

Pressure cooker is a closed domestic pressure cooking vessel for use with external heat source and capable of maintaining nominal cooking pressure up to 1.0 kgf/cm² (100 kN/m² approximately) gauge nominal. In pressure cookers, despite the development of electronic controllers, the basic edition of such vessels are still equipped with fewer advanced safety functions due to economic constraints. Although the provision of pressure relief valves (PRV) is considered as one of the major protective features, however, pressure cooker failure accidents have been reported frequently. This paper describes the analysis of pressure cooker failure that failed prematurely after 1 year of service considering the design life of > 5 years. It was hypothesized that the root cause of pipe failure was either material degradation from exposure to an aggressive environment or an inherent defect in the pressure cooker. To test this hypothesis, a thorough visual examination of the exhumed failed section and the fracture surface was undertaken, followed by liquid penetrant testing, material identification, hardness testing, and metallographic analysis. Computational models of static and transient loading were also used to determine the stress distribution along the actual geometry of the failed cooker and to understand the main causes of recurrent failures. Visual and macroscale examination revealed significant body deformation at the lower dish-ended shell showing distorted locking grooves. It was also noticed that dirt and food particle, from the earlier cooking, were stuck in the pressure valves orifice. In addition, no evidence of metallurgical defect was observed. The inspection indicated that the cause of failure is primarily due to the choking of pressure relief value (PRV) and overpressure safety valves. Consequently, the pressure release occurred from the sealing side of the top lid, which resulted in its ejection.     

MIMO iterative receiver SNR estimation strategies for link to system interfacing

This paper presents link to system (L2S) interfacing technique for multiple input and multiple output (MIMO) iterative receivers. In L2S interfacing, usually the post detection signal to noise ratio (SNR)‐based frame error rate lookup tables (LUT) are used to predict the link level performance of receivers. While L2S interfacing for linear MIMO receivers can be conveniently implemented, it is more challenging for MIMO iterative receivers due to unavailability of the closed form SNR expressions. In this paper, we propose three methods for post detection SNR estimation for MIMO iterative receivers. The first is based on the QR decomposition of the channel matrix, the second relies on the residual noise calculation based on the soft symbols, and the third exploits the closed form SNR expressions for linear receivers. A link to system interface model for iterative receivers is developed for evaluating the reference curves for different modulation and coding schemes, and results are validated by comparing the simulated and predicted frame error rates. It is shown that linear and residual noise‐based SNR approximations result in a very good prediction performance whereas the performance of QR decomposition‐based method degrades for higher order modulations and coding schemes. This paper presents link to system interfacing technique for MIMO iterative receivers. A link to system interface model for iterative receivers is developed for evaluating the reference curves for different modulation and coding schemes, and results are validated by comparing the simulated and predicted frame error rates. Three post detection SNR evaluation schemes have been proposed for link to system interfacing all of which give good prediction performance especially at lower order modulation.     

Air pollution assessment in urban areas and its impact on human health in the city of Quetta, Pakistan

Nowadays, air over major cities throughout the world has become overburdened with gases produced by automobiles. The death rate due to automobile pollution is increasing rapidly in the metropolitan areas. With passage of time, people realized that polluted air has serious effects on their health, climate and economics. Weather and climate have integrated impact on human activities resulting in worldwide concentration of the particulates of environmental pollution, viz., chlorofluorocarbons, carbon dioxide, methane, nitrogen oxide, lead and several other dust and gaseous particles. Like many other mega cities in the world the ambient air quality of Quetta, Pakistan is also deteriorating nowadays. Automobile exhausts and certain industrial pollutants produce O₃ by photochemical reactions. The particulate matter, particularly less than 10 μm in size, can pass through the natural protective mechanism of human respiratory system and plays an important role in genesis and augmentation of allergic disorders. Sources of air pollution in the area and the unique problem arising out of the emission from the vehicles, industries, etc. have been described. Ambient air quality was monitored along with micrometeorological data and the results are discussed. The status of air pollution in the area has been evaluated and a questionnaire survey was conducted to estimate the allergic symptoms and exposure to assess the respiratory disorders. The data are analyzed to evaluate the critical situation arising out of the emission of air pollutants and the impact on human health due to respirable diseases (RDs) in middle class sub-population (activity-wise) in the area assessed. A strategic air quality management plan has been proposed. For the mitigation of air pollution problems in the city, different measures to be adopted to maintain the balance between sustainable development and environmental management have been discussed. Air pollution has significant effects on exacerbation of asthma, allergy and other respiratory diseases.     

Superconducting ceramics: preparation,XRD, SEM and EPR measurements to study the influence of compositional variations on superconductivity of La-(Ba/Sr/Ca)-CuO ceramic systems

A systematic substitution of strontium ions by barium and/or calcium ions in the 21-structure ternary oxide La_1.85Sr_0.15CuO_4–y , considered as the host system in this study, was carried out to produce four- and five-component metal oxides of the type La_1.85(Sr_0.15–x R _x ) CuO_4–y , where R=Ba and/or Ca and x<0.15. A series of samples was prepared using an oxalate coprecipitation procedure where high-purity starting materials, usually required in solid-state pyrolysis reactions, were not required. The experimental conditions for co-precipitation, annealing and pulverization processes were optimized. The X-ray powder diffraction patterns were used to indicate when the materials would become superconducting after annealing. The transition temperatures, T _c, were measured from resistance versus temperature data which confirm that strontium is the best alkaline-earth metal among calcium, barium and strontium. Substitution or partial doping of strontium by calcium and/or barium in the host system decreased the T _c of these ceramics. SEM measurements were carried out to determine the grain size of these materials and characteristic electron paramagnetic resonance spectra for these materials at different temperatures are reported.     

An efficient deep learning technique for facial emotion recognition

Emotion recognition from facial images is considered as a challenging task due to the varying nature of facial expressions. The prior studies on emotion classification from facial images using deep learning models have focused on emotion recognition from facial images but face the issue of performance degradation due to poor selection of layers in the convolutional neural network model.To address this issue, we propose an efficient deep learning technique using a convolutional neural network model for classifying emotions from facial images and detecting age and gender from the facial expressions efficiently. Experimental results show that the proposed model outperformed baseline works by achieving an accuracy of 95.65% for emotion recognition, 98.5% for age recognition, and 99.14% for gender recognition.

     

Towards ontology-based multilingual URL filtering: a big data problem

Web content filtering is one among many techniques to limit the exposure of selective content on the Internet. It has gotten trivial with time, yet filtering of multilingual web content is still a difficult task, especially while considering big data landscape. The enormity of data increases the challenge of developing an effective content filtering system that can work in real time. There are several systems which can filter the URLs based on artificial intelligence techniques to identify the site with objectionable content. Most of these systems classify the URLs only in the English language. These systems either fail to respond when multilingual URLs are processed, or over-blocking is experienced. This paper introduces a filtering system that can classify multilingual URLs based on predefined criteria for URL, title, and metadata of a web page. Ontological approaches along with local multilingual dictionaries are used as the knowledge base to facilitate the challenging task of blocking URLs not meeting the filtering criteria. The proposed work shows high accuracy in classifying multilingual URLs into two categories, white and black. Evaluation results conducted on a large dataset show that the proposed system achieves promising accuracy, which is on a par with those achieved in state-of-the-art literature on semantic-based URL filtering.     

Novel and compact open‐ended CRLH‐TL notch filter

A novel and very small metamaterial notch filter below 900 MHz is proposed in this paper. In the UHF band, compared to the size of the open‐ended quarter‐wavelength stub that is, 0.25 λ_g (42 mm), the length of the proposed filter is 0.07 λ_g (12 mm) approximately five times smaller. The notch filter is realized by a very short 90°‐phase shifter of the CRLH structure with one‐end open‐terminated. The design method is explained theoretically, while the circuit and geometry are simulated and validated through EM simulations and fabrication. The measured results show a high degree of agreement with the simulated results. The results illustrate the notch created at 900 MHz by the filter to avoid the conflict with Z‐wave communication, UHF RFID tag and uplink of GSM‐E. © 2016 Wiley Periodicals, Inc. Int J RF and Microwave CAE 26:247–253, 2016.     

Automating test oracles from restricted natural language agile requirements

Manual testing of software requirements written in natural language for agile or any other methodology requires more time and human resources. This leaves the testing process error prone and time consuming. For satisfied end users with bug‐free software delivered on time, there is a need to automate the test oracle process for natural language or informal requirements. The automation of the test oracle is relatively easier with formal requirements, but this task is difficult to achieve with natural language requirements. This study proposes an approach called Restricted Natural Language Agile Requirements Testing (ReNaLART) to automate the test oracle from restricted natural language agile requirements. For this purpose, it uses an existing user story template with some modifications for writing user stories. This helps in identifying test input and expected output for a user story. For comparison of expected and observed outputs it makes use of a regex pattern and string distance functions. It is capable of assigning different types of verdicts automatically depending upon the similarity/dissimilarity between observed and expected outputs of user stories. ReNaLART is validated using several case studies of different domains, namely, OLX Pakistan, Mental Health Tests, McDelivery Pakistan, BlueStacks, Power Searching with Google, TensorFlow Playground, w3Schools 2018 offline and Touch'D. It revealed several faults in five of the above listed eight applications. Plus, the proposed test oracle on an average took 0.02 s for test data generation, expected output generation and verdict assignment. Both these facts show the fault revealing effectiveness and efficiency of ReNaLART.