Search results for: Camera Pose

Authors: Adinarayanane Ramamurthy, Monsingh D. Devadas

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Cities denote instantaneously a challenge and an opportunity for climate change policy. Cities are the place where most energy services are needed because urbanization is closely linked to high population densities and concentration of economic activities and production (Urban energy demand). Consequently, it is critical to explain about the role of cities within the world-s energy systems and its correlation with the climate change issue. With more than half of the world-s population already living in urban areas, and that percentage expected to rise to 75 per cent by 2050, it is clear that the path to sustainable development must pass through cities. Cities expanding in size and population pose increased challenges to the environment, of which energy is part as a natural resource, and to the quality of life. Nowadays, most cities have already understood the importance of sustainability, both at their local scale as in terms of their contribution to sustainability at higher geographical scales. It requires the perception of a city as a complex and dynamic ecosystem, an open system, or cluster of systems, where the energy as well as the other natural resources is transformed to satisfy the needs of the different urban activities. In fact, buildings and transportation generally represent most of cities direct energy demand, i.e., between 60 per cent and 80 per cent of the overall consumption. Buildings, both residential and services are usually influenced by the local physical and social conditions. In terms of transport, the energy demand is also strongly linked with the specific characteristics of a city (urban mobility).The concept of a “smart city" builds on statistics as seven key axes of a city-s success in moving towards common platform (brain nerve)of sustainable urban energy systems. With the aforesaid knowledge, the authors have suggested a frame work to role of cities, as energy actors for smart city management. The authors have discusses the potential elements needed for energy in smart cities and also identified potential energy actions and relevant barriers. Furthermore, three levels of city smartness in cities actions to overcome market /institutional failures with a local approach are distinguished. The authors have made an attempt to conceive and implement concepts of city smartness by adopting the city or local government as nerve center through an integrated planning approach. Finally, concluding with recommendations for the organization of the Smart Sustainable Cities for positive changes of urban India.

Keywords: Urbanization, Urban Energy Demand, Sustainable Urban Energy Systems, Integrated Planning Approach, Smart Sustainable City.

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Authors: Mohammad H. Taheri, David J. Brown, Nasser Sherkat

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Engagement is one of the most important factors in determining successful outcomes and deep learning in students. Existing approaches to detect student engagement involve periodic human observations that are subject to inter-rater reliability. Our solution uses real-time multimodal multisensor data labeled by objective performance outcomes to infer the engagement of students. The study involves four students with a combined diagnosis of cerebral palsy and a learning disability who took part in a 3-month trial over 59 sessions. Multimodal multisensor data were collected while they participated in a continuous performance test. Eye gaze, electroencephalogram, body pose, and interaction data were used to create a model of student engagement through objective labeling from the continuous performance test outcomes. In order to achieve this, a type of continuous performance test is introduced, the Seek-X type. Nine features were extracted including high-level handpicked compound features. Using leave-one-out cross-validation, a series of different machine learning approaches were evaluated. Overall, the random forest classification approach achieved the best classification results. Using random forest, 93.3% classification for engagement and 42.9% accuracy for disengagement were achieved. We compared these results to outcomes from different models: AdaBoost, decision tree, k-Nearest Neighbor, naïve Bayes, neural network, and support vector machine. We showed that using a multisensor approach achieved higher accuracy than using features from any reduced set of sensors. We found that using high-level handpicked features can improve the classification accuracy in every sensor mode. Our approach is robust to both sensor fallout and occlusions. The single most important sensor feature to the classification of engagement and distraction was shown to be eye gaze. It has been shown that we can accurately predict the level of engagement of students with learning disabilities in a real-time approach that is not subject to inter-rater reliability, human observation or reliant on a single mode of sensor input. This will help teachers design interventions for a heterogeneous group of students, where teachers cannot possibly attend to each of their individual needs. Our approach can be used to identify those with the greatest learning challenges so that all students are supported to reach their full potential.

Keywords: Affective computing in education, affect detection, continuous performance test, engagement, flow, HCI, interaction, learning disabilities, machine learning, multimodal, multisensor, physiological sensors, Signal Detection Theory, student engagement.

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Authors: M. I. Ribah, M. Jibir, Y. A. Bashar, S. S. Manga

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Food safety is a significant and growing public health problem in the world and Nigeria as a developing country, since food-borne diseases are important contributors to the huge burden of sickness and death of humans. In Nigeria, traditional ready-to-eat meat products (RTE-MPs) like balangu, tsire, guru and dried meat products like kilishi, dambun nama, banda, were reported to be highly appreciated because of their eating qualities. The consumption of these products was considered as safe due to the treatments that are usually involved during their production process. However, during processing and handling, the products could be contaminated by pathogens that could cause food poisoning. Therefore, a hazard identification for pathogenic bacteria on some traditional RTE-MPs was conducted in Kebbi and Sokoto States, Nigeria. A total of 116 RTE-MPs (balangu-38, kilishi-39 and tsire-39) samples were obtained from retail outlets and analyzed using standard cultural microbiological procedures in general and selective enrichment media to isolate the target pathogens. A six-fold serial dilution was prepared and using the pour plating method, colonies were counted. Serial dilutions were selected based on the prepared pre-labeled Petri dishes for each sample. A volume of 10-12 ml of molten Nutrient agar cooled to 42-45°C was poured into each Petri dish and 1 ml each from dilutions of 102, 104 and 106 for every sample was respectively poured on a pre-labeled Petri plate after which colonies were counted. The isolated pathogens were identified and confirmed after series of biochemical tests. Frequencies and percentages were used to describe the presence of pathogens. The General Linear Model was used to analyze data on pathogen presence according to RTE-MPs and means were separated using the Tukey test at 0.05 confidence level. Of the 116 RTE-MPs samples collected, 35 (30.17%) samples were found to be contaminated with some tested pathogens. Prevalence results showed that Escherichia coli, salmonella and Staphylococcus aureus were present in the samples. Mean total bacterial count was 23.82×106 cfu/g. The frequency of individual pathogens isolated was; Staphylococcus aureus 18 (15.51%), Escherichia coli 12 (10.34%) and Salmonella 5 (4.31%). Also, among the RTE-MPs tested, the total bacterial counts were found to differ significantly (P < 0.05), with 1.81, 2.41 and 2.9×104 cfu/g for tsire, kilishi, and balangu, respectively. The study concluded that the presence of pathogenic bacteria in balangu could pose grave health risks to consumers, and hence, recommended good manufacturing practices in the production of balangu to improve the products’ safety.

Keywords: Ready-to-eat meat products, retail outlets, safety assessment, public health.

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Authors: Michel Soto Chalhoub

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Building code-related literature provides recommendations on normalizing approaches to the calculation of the dynamic properties of structures. Most building codes make a distinction among types of structural systems, construction material, and configuration through a numerical coefficient in the expression for the fundamental period. The period is then used in normalized response spectra to compute base shear. The typical parameter used in simplified code formulas for the fundamental period is overall building height raised to a power determined from analytical and experimental results. However, reinforced concrete buildings which constitute the majority of built space in less developed countries pose additional challenges to the ones built with homogeneous material such as steel, or with concrete under stricter quality control. In the present paper, the particularities of reinforced concrete buildings are explored and related to current methods of equivalent static analysis. A comparative study is presented between the Uniform Building Code, commonly used for buildings within and outside the USA, and data from the Middle East used to model 151 reinforced concrete buildings of varying number of bays, number of floors, overall building height, and individual story height. The fundamental period was calculated using eigenvalue matrix computation. The results were also used in a separate regression analysis where the computed period serves as dependent variable, while five building properties serve as independent variables. The statistical analysis shed light on important parameters that simplified code formulas need to account for including individual story height, overall building height, floor plan, number of bays, and concrete properties. Such inclusions are important for reinforced concrete buildings of special conditions due to the level of concrete damage, aging, or materials quality control during construction. Overall results of the present analysis show that simplified code formulas for fundamental period and base shear may be applied but they require revisions to account for multiple parameters. The conclusion above is confirmed by the analytical model where fundamental periods were computed using numerical techniques and eigenvalue solutions. This recommendation is particularly relevant to code upgrades in less developed countries where it is customary to adopt, and mildly adapt international codes. We also note the necessity of further research using empirical data from buildings in Lebanon that were subjected to severe damage due to impulse loading or accelerated aging. However, we excluded this study from the present paper and left it for future research as it has its own peculiarities and requires a different type of analysis.

Keywords: Seismic behavior, reinforced concrete, simplified code formulas, equivalent static analysis, base shear, response spectra.

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Authors: A.H. Sajedipoor, N. Hedayat, A.Rohani, Z.Yazdi

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Sediment formation and its transport along the river course is considered as important hydraulic consideration in river engineering. Their impact on the morphology of rivers on one hand and important considerations of which in the design and construction of the hydraulic structures on the other has attracted the attention of experts in arid and semi-arid regions. Under certain conditions where the momentum energy of the flow stream reaches a specific rate, the sediment materials start to be transported with the flow. This can usually be analyzed in two different categories of suspended and bed load materials. Sedimentation phenomenon along the waterways and the conveyance of vast volume of materials into the canal networks can potentially influence water abstraction in the intake structures. This can pose a serious threat to operational sustainability and water delivery performance in the canal networks. The situation is serious where ineffective watershed management (poor vegetation cover in the water basin) is the underlying cause of soil erosion which feeds the materials into the waterways that intern would necessitate comprehensive study. The present paper aims to present an analytical investigation of the sediment process in the waterways on one hand and estimation of the sediment load transport into the lined canals using the SHARC software on the other. For this reason, the paper focuses on the comparative analysis of the hydraulic behaviors of the Sabilli main canal that feeds the pumping station with that of the Western canal in the Greater Dezful region to identify effective factors in sedimentation and ways of mitigating their impact on water abstraction in the canal systems. The method involved use of observational data available in the Dezful Dastmashoon hydrometric station along a 6 km waterway of the Sabilli main canal using the SHARC software to estimate the suspended load concentration and bed load materials. Results showed the transport of a significant volume of sediment loads from the waterways into the canal system which is assumed to have arisen from the absence of stilling basin on one hand and the gravity flow on the other has caused serious challenges. This is contrary to what occurs in the Sabilli canal, where the design feature which incorporates a settling basin just before the pumping station is the major cause of reduced sediment load transport into the canal system.Results showed that modification of the present design features by constructing a settling basin just upstream of the western intake structure can considerably reduce the entry of sediment materials into the canal system. Not only this can result in the sustainability of the hydraulic structures but can also improve operational performance of water conveyance and distribution system, all of which are the pre-requisite to secure reliable and equitable water delivery regime for the command area.

Keywords: Sedimentation, main canal, Sabilli, western canal, dez diversion weir.

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Authors: Ming-Hsiang Shih, Wen-Pei Sung, Shih-Heng Tung

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The purposes of hydraulic gate are to maintain the functions of storing and draining water. It bears long-term hydraulic pressure and earthquake force and is very important for reservoir and waterpower plant. The high tensile strength of steel plate is used as constructional material of hydraulic gate. The cracks and rusts, induced by the defects of material, bad construction and seismic excitation and under water respectively, thus, the mechanics phenomena of gate with crack are probing into the cause of stress concentration, induced high crack increase rate, affect the safety and usage of hydroelectric power plant. Stress distribution analysis is a very important and essential surveying technique to analyze bi-material and singular point problems. The finite difference infinitely small element method has been demonstrated, suitable for analyzing the buckling phenomena of welding seam and steel plate with crack. Especially, this method can easily analyze the singularity of kink crack. Nevertheless, the construction form and deformation shape of some gates are three-dimensional system. Therefore, the three-dimensional Digital Image Correlation (DIC) has been developed and applied to analyze the strain variation of steel plate with crack at weld joint. The proposed Digital image correlation (DIC) technique is an only non-contact method for measuring the variation of test object. According to rapid development of digital camera, the cost of this digital image correlation technique has been reduced. Otherwise, this DIC method provides with the advantages of widely practical application of indoor test and field test without the restriction on the size of test object. Thus, the research purpose of this research is to develop and apply this technique to monitor mechanics crack variations of weld steel hydraulic gate and its conformation under action of loading. The imagines can be picked from real time monitoring process to analyze the strain change of each loading stage. The proposed 3-Dimensional digital image correlation method, developed in the study, is applied to analyze the post-buckling phenomenon and buckling tendency of welded steel plate with crack. Then, the stress intensity of 3-dimensional analysis of different materials and enhanced materials in steel plate has been analyzed in this paper. The test results show that this proposed three-dimensional DIC method can precisely detect the crack variation of welded steel plate under different loading stages. Especially, this proposed DIC method can detect and identify the crack position and the other flaws of the welded steel plate that the traditional test methods hardly detect these kind phenomena. Therefore, this proposed three-dimensional DIC method can apply to observe the mechanics phenomena of composite materials subjected to loading and operating.

Keywords: Welded steel plate, crack variation, three-dimensional Digital Image Correlation (DIC).

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Authors: R. U. Hamzah, H. L. Muhammad, A. Sayyadi, M. B Busari, R. Garba, M. B. Umar, A. N Abubakar

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Lead (Pb) and Cadmium (Cd) are toxic, non-essential transition metals that pose many health risks for both humans and animals. They are environmental toxicants which contribute to testicular damage resulting to infertility problem among male populace worldwide. Chelating agents used for lead and cadmium toxicity are not readily available, toxic, expensive and unable to mop up most of the toxic metals accumulated in various organs. In this study, the effect of crude extract (CE), ethyl acetate fraction (EF) and acetone fraction (AF) of Pterocarpus mildbraedii leaf extract was assessed on cadmium-lead chloride induced testicular damaged in male albino Wistar rats. CE of the leaf was obtained by extracting in absolute methanol which was further subjected to solvent partitioning via vacuum liquid chromatographic (VLC) techniques using ethyl acetate, acetone and 70% methanol. A preliminary phytochemical screening and in vitro antioxidants guided activities on the CE and fractions were determined using standard methods. EF, AF and CE which exhibited significant in vitro activity were subjected to an in vivo study using Wistar rats. In vivo antioxidant markers, male reproductive hormones, testicular enzymes and DNA damage markers were analyzed on the rats’ testes supernatant. AF had the highest quantities of phenols (319.00 mg/g), flavonoids (8.87 mg/g) and tannins (8.87 mg/g) while methanol and EFs were richer in saponins (135.32 µg/g) and alkaloids (38.34 µg/g) respectively. A dose dependent 2, 2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging, ferric reducing antioxidant power (FRAP) and lipid peroxidation were observed in all the extract with high antioxidants power in CE and AF. Administration of lead-cadmium chloride solution significantly (p > 0.05) decreases the testicular superoxide dismutase (SOD) activity to 6.82 unit/mg protein, Catalase (CAT) activity to 8.07 of H2O2 consumed/unit/mg protein and Glutathione (GSH) concentration to 31.30 ug/mg protein. There was a concomitant increase in the level of Malondialdehyde (MDA) to a value of 23.70 mmol/mg protein. In addition, lead-cadmium chloride solution significantly (p > 0.05) increases the testicular marker enzymes (Alkaline phosphatase (119.57 u/L), lactate dehydrogenase (357.05 u/L), Acid phosphatase (98.65 u/L)) and DNA damage markers (conjugated dienes (93.39 nmol/mg protein), carbonyl protein (35.39 nmol/mg protein), DNA fragmentation percentage (32.12%)) with lowered testicular hormones (Testosterone (3.1 ng/mL), Follicle stimulating (0.35 IU/mL) and Luteinizing hormones (0.15 IU/mL)) of the animals in negative control group when compared with other treated groups. Treatment with Pterocarpus mildbraedii leaf extract reverts the observed changes with the best activities found in the CE and AFs in a dose dependent manner. Pterocarpus mildbraedii leaf extract ameliorated the lead/cadmium induced testicular damage in male albino rats. The restoration of the aforementioned parameters by some of the extract dosages were comparable to the standard drug with higher activities in the crude and AF. Therefore, Pterocarpus mildbraedii leaf extract can be explored further for the management of lead/cadmium induced toxicity.

Keywords: Cadmium, lead, Pterocarpus mildbraedii, testicular damage.

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Authors: Masoud Fathi Kazerouni, Jens Schlemper, Klaus-Dieter Kuhnert

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Green planet is one of the Earth’s names which is known as a terrestrial planet and also can be named the fifth largest planet of the solar system as another scientific interpretation. Plants do not have a constant and steady distribution all around the world, and even plant species’ variations are not the same in one specific region. Presence of plants is not only limited to one field like botany; they exist in different fields such as literature and mythology and they hold useful and inestimable historical records. No one can imagine the world without oxygen which is produced mostly by plants. Their influences become more manifest since no other live species can exist on earth without plants as they form the basic food staples too. Regulation of water cycle and oxygen production are the other roles of plants. The roles affect environment and climate. Plants are the main components of agricultural activities. Many countries benefit from these activities. Therefore, plants have impacts on political and economic situations and future of countries. Due to importance of plants and their roles, study of plants is essential in various fields. Consideration of their different applications leads to focus on details of them too. Automatic recognition of plants is a novel field to contribute other researches and future of studies. Moreover, plants can survive their life in different places and regions by means of adaptations. Therefore, adaptations are their special factors to help them in hard life situations. Weather condition is one of the parameters which affect plants life and their existence in one area. Recognition of plants in different weather conditions is a new window of research in the field. Only natural images are usable to consider weather conditions as new factors. Thus, it will be a generalized and useful system. In order to have a general system, distance from the camera to plants is considered as another factor. The other considered factor is change of light intensity in environment as it changes during the day. Adding these factors leads to a huge challenge to invent an accurate and secure system. Development of an efficient plant recognition system is essential and effective. One important component of plant is leaf which can be used to implement automatic systems for plant recognition without any human interface and interaction. Due to the nature of used images, characteristic investigation of plants is done. Leaves of plants are the first characteristics to select as trusty parts. Four different plant species are specified for the goal to classify them with an accurate system. The current paper is devoted to principal directions of the proposed methods and implemented system, image dataset, and results. The procedure of algorithm and classification is explained in details. First steps, feature detection and description of visual information, are outperformed by using Scale invariant feature transform (SIFT), HARRIS-SIFT, and FAST-SIFT methods. The accuracy of the implemented methods is computed. In addition to comparison, robustness and efficiency of results in different conditions are investigated and explained.

Keywords: SIFT combination, feature extraction, feature detection, natural images, natural plant recognition, HARRIS-SIFT, FAST-SIFT.

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Authors: Payam Mousavi, Andrew L. Stewart, Huiwen You, Aryeh F. G. Fayerman

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We present a decision-support tool to assist an operator in the detection and tracking of a suspect vehicle traveling to an unknown target destination. Multiple data sources, such as traffic cameras, traffic information, weather, etc., are integrated and processed in real-time to infer a suspect’s intended destination chosen from a list of pre-determined high-value targets. Previously, we presented our work in the detection and tracking of vehicles using traffic and airborne cameras. Here, we focus on the fusion and processing of that information to predict a suspect’s behavior. The network of cameras is represented by a directional graph, where the edges correspond to direct road connections between the nodes and the edge weights are proportional to the average time it takes to travel from one node to another. For our experiments, we construct our graph based on the greater Los Angeles subset of the Caltrans’s “Performance Measurement System” (PeMS) dataset. We propose a Bayesian approach where a posterior probability for each target is continuously updated based on detections of the suspect in the live video feeds. Additionally, we introduce the concept of ‘soft interventions’, inspired by the field of Causal Inference. Soft interventions are herein defined as interventions that do not immediately interfere with the suspect’s movements; rather, a soft intervention may induce the suspect into making a new decision, ultimately making their intent more transparent. For example, a soft intervention could be temporarily closing a road a few blocks from the suspect’s current location, which may require the suspect to change their current course. The objective of these interventions is to gain the maximum amount of information about the suspect’s intent in the shortest possible time. Our system currently operates in a human-on-the-loop mode where at each step, a set of recommendations are presented to the operator to aid in decision-making. In principle, the system could operate autonomously, only prompting the operator for critical decisions, allowing the system to significantly scale up to larger areas and multiple suspects. Once the intended target is identified with sufficient confidence, the vehicle is reported to the authorities to take further action. Other recommendations include a selection of road closures, i.e., soft interventions, or to continue monitoring. We evaluate the performance of the proposed system using simulated scenarios where the suspect, starting at random locations, takes a noisy shortest path to their intended target. In all scenarios, the suspect’s intended target is unknown to our system. The decision thresholds are selected to maximize the chances of determining the suspect’s intended target in the minimum amount of time and with the smallest number of interventions. We conclude by discussing the limitations of our current approach to motivate a machine learning approach, based on reinforcement learning in order to relax some of the current limiting assumptions.

Keywords: Autonomous surveillance, Bayesian reasoning, decision-support, interventions, patterns-of-life, predictive analytics, predictive insights.

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