The Influence of Psychological Conflict Toward Elsa's Character Development in Frozen Film

In this research, the researcher focused to find the psychological conflict and its influence toward the main character's character development in Frozen film. The researcher used two theories to answer the two research problems. For the first question, the researcher used the theory of psychological conflict by Kurt Lewin to find the kinds of psychological conflict expressed by the main character in Frozen film. To answer the second question, the researcher used the theory of personality development by Elizabeth B. Hurlock to explain the influence of psychological conflict toward the character development of the main character. In this research, the method that the researcher used was qualitative research method. The result of the analysis showed that Elsa expressed two kinds of psychological conflict which were approach-avoidance conflict and avoidance-avoidance conflict. And those two kinds of psychological conflict influence Elsa's character development in five determinants they are intellectual, emotional, social, aspiration & achievement, and family

Estimating average daily traffic using alternative method for single carriageway road in Southern Region Malaysia

Average Annual Daily Traffic (AADT) and Average Daily Traffic (ADT) are two parameters that are commonly required by traffic engineers and road designers to design and analyse the traffic operational performance of a road segment. In Malaysia, ADT is normally used to forecast the volume of traffic in the design year as well as to design the pavement thickness. Basically, ADT can be generated using expansion factor estimates from Peak Hour Volume (PHV). Current practice in Malaysia uses an expansion of 10% to estimate ADT from PHV. This paper discusses the results of a study carried out to establish a model for estimating ADT using PHV for single carriageway road. The 24-hours traffic data were collected at 9 sites in the districts of Johor, Malaysia for the period of 14 days. The 7-days data were used to establish the model and the other 7-days data were used to validate the model. For validation purposes, the absolute percent error (APE) for each estimate of ADT obtained from the model was calculated and compared with observed ADT. The statistical test at 95% confidence level was conducted to determine the significance difference between the ADT from actual data and the estimate ADT from model. The result shows that a power-formed trend line (y=axb) suits to the observed data with the coefficient of determination of about 0.90. Validation result shows that the ADT for the model has lesser APE compared with the ADT estimated using the factoring approach. A comparison of both estimated and actual ADT values using t-Test shows that there is no significant difference between the estimated ADT using models and the actual ADT. However, the ADT estimated using the expansion factor of 10% shows the vice versa. Such a finding implies that the model obtained from this study predicts ADT accurately than the current practice

Time series forecasting of the number of Malaysia Airlines and AirAsia passengers

The standard practice in forecasting process involved by fitting a model and further analysis on the residuals. If we know the distributional behaviour of the time series data, it can help us to directly analyse the model identification, parameter estimation, and model checking. In this paper, we want to compare the distributional behaviour data from the number of Malaysia Airlines (MAS) and AirAsia passenger’s. From the previous research, the AirAsia passengers are govern by geometric Brownian motion (GBM). The data were normally distributed, stationary and independent. Then, GBM was used to forecast the number of AirAsia passenger’s. The same methods were applied to MAS data and the results then were compared. Unfortunately, the MAS data were not govern by GBM. Then, the standard approach in time series forecasting will be applied to MAS data. From this comparison, we can conclude that the number of AirAsia passengers are always in peak season rather than MAS passengers

Treatment of outliers via interpolation method with neural network forecast performances

Outliers often lurk in many datasets, especially in real data. Such anomalous data can negatively affect statistical analyses, primarily normality, variance, and estimation aspects. Hence, handling the occurrences of outliers require special attention. Therefore, it is important to determine the suitable ways in treating outliers so as to ensure that the quality of the analyzed data is indeed high. As such, this paper discusses an alternative method to treat outliers via linear interpolation method. In fact, assuming outlier as a missing value in the dataset allows the application of the interpolation method to interpolate the outliers thus, enabling the comparison of data series using forecast accuracy before and after outlier treatment. With that, the monthly time series of Malaysian tourist arrivals from January 1998 until December 2015 had been used to interpolate the new series. The results indicated that the linear interpolation method, which was comprised of improved time series data, displayed better results, when compared to the original time series data in forecasting from both Box-Jenkins and neural network approaches

Design of planar dielectric resonator antenna array at 28 GHz

This article presents a planar array of rectangular Dielectric Resonator Antenna operating for 28 GHz applications. The proposed antenna is formed through two stages of designs which are a single element and planar array. It is made up from a ceramic material with a dielectric constant of 10 and mounted on RT/Duroid 5880 with a relative permittivity of 2.2 and a thickness of 0.254 mm. A prospective study using three different configurations of three by three planar array is done in order to obtain the best performance in terms of bandwidth, gain, and cost reduction. Besides that, this study is also conducted for a beam steering capability of each configuration. Finally, the best configuration is proposed for 5G application

Effects of Current Density and Deposition Time on Corrosion Behaviour of Nickel-based Alloy Coatings

Corrosion of fasteners is an on-going issue and stainless steel 304 (SS304) is prone to this destructive process. One method to mitigate corrosion is electrodeposition of Co-Ni-Fe nanoparticles.  This paper studied the effects of deposition time and current density on corrosion behaviour of Co-Ni-Fe coated SS304 bolt. Co-Ni-Fe ternary alloys were electrodeposited onto SS304 bolt in 15, 30, or 45 minutes by using current density of 28, 35, 42 mA/cm2. Combinations of these parameters produced 9 samples. These samples were electrochemically tested by a potentiostat using open circuit potential (OCP) and potentiodynamic polarization (PDP). The samples were also characterised in terms of surface roughness and thickness of the coatings by using 3D surface metrology system. The OCP value decreased when deposition time was increased. All sample synthesised in 30 minutes had a more stable OCP curve. PDP curves exhibited active behaviour without passivation region. The corrosion potential (Ecorr) of T15 samples was more anodic than T30 and T45 samples. The corrosion current density (Icorr) of all samples fluctuated. Sample synthesised in 30 minutes using 42 mA/cm2 had the lowest corrosion rate. It was found that the surface roughness influences the corrosion behaviour in which a lower surface roughness tends to produce coating with better corrosion performance. Current density had small effect on the thickness of coating, whereas the tendency of a thickness to increase was obvious for deposition time

Effects of Current Density and Deposition Time on Corrosion Behaviour of Nickel-based Alloy Coatings

Corrosion of fasteners is an on-going issue and stainless steel 304 (SS304) is prone to this destructive process. One method to mitigate corrosion is electrodeposition of Co-Ni-Fe nanoparticles.  This paper studied the effects of deposition time and current density on corrosion behaviour of Co-Ni-Fe coated SS304 bolt. Co-Ni-Fe ternary alloys were electrodeposited onto SS304 bolt in 15, 30, or 45 minutes by using current density of 28, 35, 42 mA/cm2. Combinations of these parameters produced 9 samples. These samples were electrochemically tested by a potentiostat using open circuit potential (OCP) and potentiodynamic polarization (PDP). The samples were also characterised in terms of surface roughness and thickness of the coatings by using 3D surface metrology system. The OCP value decreased when deposition time was increased. All sample synthesised in 30 minutes had a more stable OCP curve. PDP curves exhibited active behaviour without passivation region. The corrosion potential (Ecorr) of T15 samples was more anodic than T30 and T45 samples. The corrosion current density (Icorr) of all samples fluctuated. Sample synthesised in 30 minutes using 42 mA/cm2 had the lowest corrosion rate. It was found that the surface roughness influences the corrosion behaviour in which a lower surface roughness tends to produce coating with better corrosion performance. Current density had small effect on the thickness of coating, whereas the tendency of a thickness to increase was obvious for deposition time

Clustering for binary data sets by using genetic algorithm-incremental K-means

This research was initially driven by the lack of clustering algorithms that specifically focus in binary data. To overcome this gap in knowledge, a promising technique for analysing this type of data became the main subject in this research, namely Genetic Algorithms (GA). For the purpose of this research, GA was combined with the Incremental Kmeans (IKM) algorithm to cluster the binary data streams. In GAIKM, the objective function was based on a few sufficient statistics that may be easily and quickly calculated on binary numbers. The implementation of IKM will give an advantage in terms of fast convergence. The results show that GAIKM is an efficient and effective new clustering algorithm compared to the clustering algorithms and to the IKM itself. In conclusion, the GAIKM outperformed other clustering algorithms such as GCUK, IKM, Scalable K-means (SKM) and K-means clustering and paves the way for future research involving missing data and outliers

Implementing Inquiry-based Learning and Examining the Effects in Junior College Probability Lessons

This study examined how Year 12 students use their inquiry skills in solving conditional probability questions by means of Inquiry-Based Learning application. The participants consisted of 66 students of similar academic abilities in Mathematics, selected from three classes, along with their respective teachers. Observational rubric and lesson observation checklist were used as the data collection instruments. The results obtained were analyzed and then quantitatively reported. Findings from the observational rubric revealed that Year 12 students were able to understand most of the questions during the activity, but they only select and use one previously learned method to solve the questions during the activity. In addition, these students rarely seek and asked probing questions during the activity. They only used words, diagrams and numbers to interpret the solutions to the questions and make connections between them but with few mistakes detected.DOI: http://dx.doi.org/10.22342/jme.8.2.3964.157-16

Hasil Belajar Kognitif IPA Fisika Siswa melalui Penerapan Strategi Bowling Campus di Kelas Viii6 SMPN 15 Pekanbaru

This research aims at describe cognitive learning outcomes science of physics through the implementation strategy Bowling Campus on light subject at SMPN 15 Pekanbaru. The expected benefits of this research is for students implementation Bowling Campus strategy can improve the cognitive learning to become a better student. For teachers can be used as an alternative teaching strategies to improve the quality of science physics teaching. This research was conducted in SMP 15 Pekanbaru precisely in March 2015 until June 2015 in class VIII6 totaling 39 students. The design of the research is Pre-experimental design shapes One Shot Case study. From the research results obtained by the average value of absorption of students by 76.53% and categorized as good. Based on the average value of absorption was also found that the effectiveness of learning by applying Bowling Campus declared effective strategy. Based on 20 indicators of achievement of competencies in a given light material, 14 indicators declared complete with a percentage of 70%. It can be concluded that the application of Bowling Campus strategy can be used as an alternative in order to achieve the learning outcomes of cognitive learning better students in the classroom VIII6 SMP 15 Pekanbaru