Understanding media literacy in relation to adolescent soft drink consumption behavior

This paper examines relationship between media literacy and the Theory of Planned Behavior (TPB) variables focusing on consumption of soft drink among adolescents in Klang Valley, Malaysia. In addition, this paper also determines soft drink consumption, level of media literacy and the influences of the TPB variables on the intention of soft drink consumption. A cluster sampling method was used in collecting data within the Klang Valley area. The sample consisted of 436 adolescents from secondary school, aged between 13 to 18 years old. Two main scales utilized were Media Literacy (ML) scale and TPB scale. The descriptive, multiple linear regression and Pearson product-moment correlation analyses were carried out to answer the research objectives. Results revealed that 36% of respondents drank a minimum of 1 can, bottle or glass of soft drink for the past seven days and possess good level of media literacy (35%).Meanwhile, 14% of variance in adolescents’ intention of soft drink consumption is explained by TPB variables. Additionally, the total media literacy score towards soft drink advertisement was significantly positively correlated with attitude (r = 0.250, p<.05) and subjective norms (r = 0.174, p<.05). Conversely, total media literacy was significant negatively correlated with intention to consume soft drink (r = -0.19, p<.05) and indicated that media literacy could lower the intention to consume soft drink, thus can reduce soft drink consumption among adolescents. The importance of this study is to help the authorities, soft drink marketers and producers in Malaysia to better understand media literacy and adolescent soft drink consumption behavior

Study of tropospheric scintillation effects in Ku-band frequency for satellite communication system

Scintillation is a rapid fluctuation of electromagnetic waves in terms of phase and amplitude due to a small-scale inconsistency in the transmission path (or paths) with time. Scintillation exists continuously throughout a day whether during raining or clear sky conditions. The raw signal data need to exclude other propagations factors that include signal fluctuations to further understand the scintillation studies. This paper presents the analysis of tropospheric scintillation data from January 2016 till December 2016 at Ku-band frequency of 12.202 GHz beacon signal. The experimental data from MEASAT 3B were collected and analyzed to see the effect of tropospheric scintillation. The elevation angle of the dish antenna is 77.45o. The highlighted objectives are to analyze the scintillation data at Ku-band, and to compare and validate the results with other scintillation models. The result shows that the stipulated scintillation analysis has higher amplitude, which is 0.73 dB compared to other scintillation analysis which has lower scintillation amplitude: 0.45 dB (Karasawa), 0.42 dB (ITU-R), 0.4 dB (Nadirah & Rafiqul), 0.42 dB (Van De Kamp), and 0.11 dB (Anthony & Mandeep)

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

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

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

In vitro cytotoxicity analysis of bioceramic root canal sealers on human gingival fibroblast cells

Cytotoxicity of various bioceramic root canal sealers are not well understood due to the limited scientific data. Previous research focused on comparing the conventional and bioceramic root canal sealers but there was no comparison between the latter. The aim of this study is to evaluate the cytotoxicity of bioceramic root canal sealers and to propose the material that is less cytotoxic for clinical purposes. Bioceramic root canal sealers, such as GuttaFlow Bioseal, MTA Fillapex, CeraSeal Bioceramic root canal sealer and iRoot SP root canal sealer were mixed according to the manufacturers’ instructions and placed into a sterilised cylindrical silicone mold with 5 mm diameter and 3 mm thickness. Fourier transform infrared spectroscopy was used to analyse changes in the quality and consistency of all the bioceramic root canal sealers. Human gingival fibroblast cells were cultivated and exposed to material extracts for 24 h, 48 h and 72 h in a 5% CO2 humidified incubator at 37 °C. The MTT (3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide) assay was conducted to determine cell viability at each incubation period and compared between all the bioceramic root canal sealers. The cell viability was qualitatively graded as severe ( 90%). The data were analysed using Statistical Package for Social Sciences, version 25.0. GuttaFlow Bioseal showed less cytotoxicity followed by CeraSeal Bioceramic root canal sealer, iRoot SP root canal sealer, and MTA Fillapex. Clinicians should select bioceramic root canal sealers that have low cytotoxic effects during root canal treatment procedure

In vitro cytotoxicity analysis of bioceramic root canal sealers on human gingival fibroblast cells

Cytotoxicity of various bioceramic root canal sealers are not well understood due to the limited scientific data. Previous research focused on comparing the conventional and bioceramic root canal sealers but there was no comparison between the latter. The aim of this study is to evaluate the cytotoxicity of bioceramic root canal sealers and to propose the material that is less cytotoxic for clinical purposes. Bioceramic root canal sealers, such as GuttaFlow Bioseal, MTA Fillapex, CeraSeal Bioceramic root canal sealer and iRoot SP root canal sealer were mixed according to the manufacturers’ instructions and placed into a sterilised cylindrical silicone mold with 5 mm diameter and 3 mm thickness. Fourier transform infrared spectroscopy was used to analyse changes in the quality and consistency of all the bioceramic root canal sealers. Human gingival fibroblast cells were cultivated and exposed to material extracts for 24 h, 48 h and 72 h in a 5% CO2 humidified incubator at 37 °C. The MTT (3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide) assay was conducted to determine cell viability at each incubation period and compared between all the bioceramic root canal sealers. The cell viability was qualitatively graded as severe ( 90%). The data were analysed using Statistical Package for Social Sciences, version 25.0. GuttaFlow Bioseal showed less cytotoxicity followed by CeraSeal Bioceramic root canal sealer, iRoot SP root canal sealer, and MTA Fillapex. Clinicians should select bioceramic root canal sealers that have low cytotoxic effects during root canal treatment procedure