Tracking and Analysis of Pedestrian’s Behavior in Public Places

Crowd management becomes a global concern due to increased population in urban areas. Better management of pedestrians leads to improved use of public places. Behavior of pedestrian’s is a major factor of crowd management in public places. There are multiple applications available in this area but the challenge is open due to complexity of crowd and depends on the environment. In this paper, we have proposed a new method for pedestrian’s behavior detection. Kalman filter has been used to detect pedestrian’s using movement based approach. Next, we have performed occlusion detection and removal using region shrinking method to isolate occluded humans. Human verification is performed on each human silhouette and wavelet analysis and particle gradient motion are extracted for each silhouettes. Gray Wolf Optimizer (GWO) has been utilized to optimize feature set and then behavior classification has been performed using the Extreme Gradient (XG) Boost classifier. Performance has been evaluated using pedestrian’s data from avenue and UBI-Fight datasets, where both have different environment. The mean achieved accuracies are 91.3% and 85.14% over the Avenue and UBI-Fight datasets, respectively. These results are more accurate as compared to other existing methods.     

The influence of industrial policy and national systems of innovation on emerging economy suppliers’ learning capability

This paper links the industrial policy and national systems of innovation literature to the investigation of learning capabilities of suppliers in the context of the automotive parts industry of Pakistan. Drawing data from 50 Pakistani autoparts suppliers, the findings suggest that industrial policy has been helpful in creating a local parts supply base and facilitating the entry of Japanese assemblers in the market. However, the implementation of the policy has been weak, and it is an arduous journey for the local suppliers to develop ambidextrous (exploratory and exploitative) learning capabilities. The findings also indicate that where local training and support from R&D institutions are weak, networking alone with foreign multinationals is not sufficient on its own to develop exploratory learning capabilities of local suppliers. This paper shows the importance of creating national–provincial institutions offering learning and skills development aimed towards innovation.     

Does power posing affect gerontechnology adoption among older adults?

Recognising the rise of an aging population and independent living among older adults, many governments and organisations have developed and promoted new technologies in the form of gerontechnologies to support the needs and enhance the well-being of older adults. However, the adoption of products using such technology remains modest among the aging population. This study introduces the notion of power in the form of power posing and examines its impact on new technology adoption, particularly gerontechnology, among older adults. Using an experimental approach on a sample of older adults exposed to an in-house near-field communication-enabled light system, the study finds that high-power poses have a greater and more positive impact on older adults’ perceived ease of use of, perceived usefulness of, and intentions to use gerontechnology than low-power poses. Implications, limitations, and future research directions are discussed.     

Ternary adsorbent photocatalyst hybrid (APH) nanomaterials for improved abstraction of tetracycline from water

ABSTRACT

Current health situations have instigated increased frequency of taking antibiotics for cure of infections but this amplified use is posing threats to environment. This research is focused to remove Tetracycline (TC), an antibiotic from water, using an advanced nanohybrid that compact the properties of adsorbent and photocatalyst. Compared to conventional methods for remediation of TC, large surface area (452 m²g^?1) adsorbent photocatalyst hybrid (APH) g-C₃N₄/α-MoO₃/ZIF-67 (CMZ) have found much effective as 97% degradation of TC is observed in 110 min with 0.1 g of APH. Increasing g-C₃N₄ in the hybrids has improved percent degradation of TC molecules. CMZ-3 is found as a potential candidate for water treatment.     

Bond Slip Analysis of Fiber-Reinforced Polymer-Strengthened Beams

The second order differential equation of interface shear is formulated for fiber-reinforced polymer-strengthened beams using beam theory with a shear deformable adhesive layer. The solution of the boundary value problem is obtained in closed form and is used to derive deflection expressions for different loading conditions. The solution is also extended to analyze partially plated beams. The results converge to the extreme cases of very poorly and perfectly bonded plates and they help identify values of the adhesive shear modulus for effective stiffening. Furthermore, the solution of partially plated beams aids in defining anchorage lengths needed to develop the full or the highest possible composite action at midspan.     

Synthesis of Boron Nitride Microtubes and Formation of Boron Nitride Nanosheets

Boron nitride microtubes are synthesized in a dual zone quartz tube furnace at 1200°C with ammonia as a reaction atmosphere. Field emission scanning electron microscopy (FE-SEM) results show a unique cone-like morphology of the tubes with larger internal space and thin walls structure. The diameters of the tubes were found to be in the range of 1 to ～2 µm with the walls thickness estimated to be from 10 to 100 nm. XPS survey shows N 1 s and B 1 s peaks at 398.7 and 191 eV, respectively, that represent h-BN in the sample. Raman spectroscopy indicates a high-intensity peak at 1372.53 (cm^?1) that corresponds to the E_2g mode of h-BN. Along with the novel tubular morphology of boron nitride microtubes, the present work also explains a mechanism for the formation of boron nitride nanosheets (from boron nitride microtubes) found in the FE-SEM results of the current sample.     

Comparison of myoglobin, creatine kinase-MB, and cardiac troponin I for diagnosis of acute myocardial infarction

Serial plasma concentrations of myoglobin, creatine kinase MB (CK-MB) isoenzyme, and cardiac troponin I (cTnI) were measured in 25 patients with a confirmed diagnosis of acute myocardial infarction (AMI), and 74 patients who were suspected of AMI but were subsequently ruled out for this diagnosis. The cutoff concentration for the cTnI assay was optimally determined to be 2.5 ng/mL. Of the three markers, myoglobin had the highest clinical sensitivity (50 percent) when blood was collected between 0 to 6 h after the onset of chest pain. Assays for all serum markers used had high clinical sensitivity (> 93 percent) 6 to 24 h after onset. The CK-MB remained highly sensitive for 48 h, while cTnI was sensitive for up to 72 h. Between 72 and 150 h, cTnI had a clinical sensitivity of 70 percent as compared to 21 percent and 18 percent for myoglobin and CK-MB, respectively. The clinical specificity of cTnI for non-AMI patients was equivalent to CK-MB and significantly higher than for myoglobin. The clinical efficiency of cTnI for all samples was better than either CK-MB or myoglobin, owing mainly to the wider diagnostic window. The specificity of cTnI for 59 patients with chronic renal failure, skeletal muscle trauma and disease was better than all of these markers including cardiac troponin T (cTnT). Results of this study show that cTnI is an effective marker for the retrospective diagnosis of AMI, and consideration should be given to its use in place of CK-MB.     

Controlling the material removal and roughness of Inconel 718 in laser machining

Nickel alloys including Inconel 718 are considered as challenging materials for machining. Laser beam machining could be a promising choice to deal with such materials for simple to complex machining features. The machining accuracy is mainly dependent on the rate of material removal per laser scan. Because of the involvement of many laser parameters and complexity of the machining mechanism it is not always simple to achieve machining with desired accuracy. Actual machining depth extremely varies from very low to aggressively high values with reference to the designed depth. Thus, a research is needed to be carried out to control the process parameters to get actual material removal rate (MRR_act) equals to the theoretical material removal rate (MRR_th) with minimum surface roughness (SR) of the machined surfaces. In this study, five important laser parameters have been used to investigate their effects on MRR and SR. Statistical analysis are performed to identify the significant parameters with their strength of effects. Mathematical models have been developed and validated to predict the machining responses. Optimal set of laser parameters have also been proposed and confirmed to achieve the actual MRR close to the designed MRR (MRR_% = 100.1%) with minimum surface roughness (R_a = 2.67 µm).