Analysis on background subtraction for street surveillance

Background subtraction is a well-known technique used in computer vision applications. However, in public surveillance system, the utilization of background subtraction still new and far from being solved. Insufficient analysis of the background subtraction algorithms made the situation getting worse. The analysis of the commonly-used algorithms is presented in this paper. Experiments are conducted to quantitatively evaluate the performance of the algorithms by using three video sequences. The more suitable algorithm for various conditions is expected to be presented as the results in this paper

Analysis of artificial neural network and viola-jones algorithm based moving object detection

In recent years, the worrying rate of street crime has demanded more reliable and efficient public surveillance system. Analysis of moving object detection methods is presented in this paper, includes Artificial Neural Network (ANN) and Viola-Jones algorithm. Both methods are compared based on their precision of correctly classify the moving objects. The emphasis is on two major issues involve in the analysis of moving object detection, and object classification to two groups, pedestrian and motorcycle. Experiments are conducted to quantitatively evaluate the performance of the algorithms by using two types of dataset, which are different in term of complexity of the background. The utilization of cascade architecture to the extracted features, benefits the algorithm. The algorithms have been tested on simulated events, and the more suitable algorithm with high detection rate is expected to be presented in this paper

Multiple-Objective Optimization Techniques in Laser Joining of Dissimilar Materials Classes: A Comparison between Grey and Ratio Analyses

Multiple-objective optimization using grey relational analysis (GRA) has found widespread applications especially in manufacturing and machining processes that involve complex processing parameters and output attributes. On the other hand, multiple-objective optimization on the basis of ratio analysis (MOORA) is often applied in the fields of construction and economy. One distinctive feature of MOORA is the assessment of relative importance of all responses (i.e. weighting ratio) which are taken into account mathematically while GRA emphasis the need of a priori information for accurate assignment of weighting ratio. This paper compares these two seemingly different methods by considering their applications in laser joining of dissimilar materials classes in a number of case studies: (a) laser joining of polymer and ceramic, (b) laser joining of polymer and stainless steel, and (c) laser joining of polymer and aluminium alloy. The outcomes of the two methods are compared and discussed. In majority of the cases, the predicted top-ranked alternatives were comparably matched. It is concluded that MOORA is more favourable compared to GRA since it eliminates prior assumption concerning the relative importance of the measured responses, which can lead to unnecessary bias

The effect of heat stress on the oxidative status of red hybrid tilapia (Oreochromis sp.) infected with Streptococcus Agalactiae

A commercial red hybrid tilapia was experimented with S. agalactiae infection under influences of heat stress which indicated by plasma malondialdehyde (MDA) and erythrocyte superoxide dismutase (SOD) as biomarkers of stress. To achieve these objectives, 110 red hybrid tilapia in good health were divided into five groups of 22 fish each. Group A was challenged with 2.3 109 CFU of S. agalactiae and exposed to heat stress at 33 ± 0.5C on day 1. Group B was challenged on day 1 as in Group A but heat stress was introduced on day 7 post challenge (pc). Group C was exposed to heat stress on day 1 and challenged on day 7 pc while groups D and E served as a positive and negative controls respectively. Blood samples were collected at days 0, 3, 7, 10 and 14 for MDA and SOD analysis. Groups A and B recorded high mortality following exposure to heat stress and bacteria inoculation, with group A reaching 100% mortality at day 7 post inoculation. Overall, Groups A, B, C and Group D showed pattern of increase in MDA level as early as day 3 and decrease pattern for SOD activity. Group E did not show any significant difference in MDA level throughout the study period. Clinical signs such as erratic swimming, exopthalmia, skin haemorrhage and cloudy eye were predominantly observed in group A 24 h post inoculation. Based on the findings of this study, it was concluded that heat stress plays crucial role in the pathogenesis of S. agalactiae, via alteration of the oxidant defence system

Detection of different classes moving object in public surveillance using artificial neural network (ANN)

Public surveillance monitoring is rapidly finding its way into Intelligent Surveillance Systems. Street crimes such as snatch theft is increasing drastically in recent years, cause a serious threat to human life worldwide. In this paper, a moving object detection and classification model was developed using novel Artificial Neural Network (ANN) simulation with the aim to identify its suitability for different classes of moving objects, particularly in public surveillance conditions. The result demonstrated that the proposed method consistently performs well with different classes of moving objects such as, motorcyclist, and pedestrian. Thus, it is reliable to detect different classes of moving object in public surveillance camera. It is also computationally fast and applicable for detecting moving objects in real-time

Moving object detection and classification using neuro-fuzzy approach

Public surveillance monitoring is rapidly finding its way into Intelligent Surveillance System. Street crime is increasing in recent years, which has demanded more reliable and intelligent public surveillance system. In this paper, the ability and the accuracy of an Adaptive Neuro-Fuzzy Inference System (ANFIS) was investigated for the classification of moving objects for street scene applications. The goal of this paper is to classify the moving objects prior to its communal attributes that emphasize on three major processes which are object detection, discriminative feature extraction, and classification of the target. The intended surveillance application would focus on street scene, therefore the target classes of interest are pedestrian, motorcyclist, and car. The adaptive network based on Neuro-fuzzy was independently developed for three output parameters, each of which constitute of three inputs and 27 Sugeno-rules. Extensive experimentation on significant features has been performed and the evaluation performance analysis has been quantitatively conducted on three street scene dataset, which differ in terms of background complexity. Experimental results over a public dataset and our own dataset demonstrate that the proposed technique achieves the performance of 93.1% correct classification for street scene with moving objects, with compared to the solely approaches of neural network or fuzzy

Application of jasmonic acid:effects on growth and phenolic constituents’ production of roselle (Hibiscus sabdariffa var. ukm-2)

Plant growth regulators (PGRs) are widely reported to have key role related to plant growth and metabolite production. However, studies on the impact of PGRs especially jasmonic acid (JA) on phenolic constituents in Roselle has not been reported yet in any previous studies. The present study investigates the effect on plant growth and phenolic constituents’ production in response to JA application with different concentrations of H. sabdariffa var. UKMR-2. JA solution was applied at 65 days after transplanting (DAT) according to their treatment designated; 0.5 mM (JA1), 1 mM (JA2) and Control (untreated). The growth performance was recorded and the assessments of phenolic constituents in the calyx water extract followed Folin-Ciocalteu assay, pH differential method and DPPH assay. The results showed that application of JA has significant influences on phenolic constituent production and antioxidant activity (p 0.05). Therefore, the result suggested that exposure to JA decreased the UKMR-2 plant growth and calyx yields, phenolic constituents’ content and antioxidant activity compared to Control with the sequence: Control > JA1 > JA2

Dye-Sensitized Solar Cell (DSSC): effects on light quality, microclimate, and growth of Orthosiphon stamineus in tropical climatic condition

The main challenge facing greenhouse designers is to achieve environment-appropriate greenhouses, especially in tropical regions. The excess radiant energy transmitted into the greenhouse predisposes plants to photo-inhibition and consequently reduces crop production. Lately, photovoltaic (PV) modules are equipped as a greenhouse rooftop to minimize the level of irradiation and air temperature in the greenhouse, simultaneously improving its energy consumption. Nevertheless, due to the low level of irradiation, denser conventional PV internal shading would influence the cultivated crops’ growth. Thus, Dye Sensitized Solar Cell (DSSC) possesses several attractive features such as transparent, sensitive to low light levels, and various color options that render DSSC a perfect choice able to serve substantially in energy buildings. This study assessed the microclimate conditions inside the greenhouse with semi-transparent DSSC mounted on top of it, describing the Photosynthetic Photon Flux Density (PPFD) (µmol m−2 s−1), Vapor Pressure Deficit VPD (kPa), relative humidity (%), and also temperature (°C). The Overall Thermal Transfer Value (OTTV), which indicates the average thermal energy transmission rate across the external layer of a structure envelope, is also presented. The effects of colored DSSC in altering the spectral of sunlight in reference to the Orthosiphon stamineus growth responses were determined. The information of the condition of DSSC greenhouse microclimate helps to identify the information for designing PV greenhouses and to produce income from both electric power and agronomic activity

What information and the extent of information research participants need in informed consent forms: a multi-country survey

Background: The use of lengthy, detailed, and complex informed consent forms (ICFs) is of paramount concern in biomedical research as it may not truly promote the rights and interests of research participants. The extent of information in ICFs has been the subject of debates for decades; however, no clear guidance is given. Thus, the objective of this study was to determine the perspectives of research participants about the type and extent of information they need when they are invited to participate in biomedical research. Methods: This multi-center, cross-sectional, descriptive survey was conducted at 54 study sites in seven Asia-Pacific countries. A modified Likert-scale questionnaire was used to determine the importance of each element in the ICF among research participants of a biomedical study, with an anchored rating scale from 1 (not important) to 5 (very important). Results: Of the 2484 questionnaires distributed, 2113 (85.1%) were returned. The majority of respondents considered most elements required in the ICF to be \u27moderately important\u27 to \u27very important\u27 for their decision making (mean score, ranging from 3.58 to 4.47). Major foreseeable risk, direct benefit, and common adverse effects of the intervention were considered to be of most concerned elements in the ICF (mean score = 4.47, 4.47, and 4.45, respectively). Conclusions: Research participants would like to be informed of the ICF elements required by ethical guidelines and regulations; however, the importance of each element varied, e.g., risk and benefit associated with research participants were considered to be more important than the general nature or technical details of research. Using a participant-oriented approach by providing more details of the participant-interested elements while avoiding unnecessarily lengthy details of other less important elements would enhance the quality of the ICF