International Journal on Advanced Science, Engineering and Information Technology
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Charts for Exponentially Weighted Moving Average Classical and Robust: A Comparative Study
Get PDFThis research discusses the comparison between two control charts classical & robust for both types (EWMA-SMQ) and (EWMA-SM) for the exponentially weighted moving average, which is showed that the robust (EWMA-SMQ) chart for the process is a superior alternative to the (EWMA-SM) chart when the outliers are present in the data. Generally, the (EWMA-SMQ) chart enables easier detection of outliers in the subgroups and is also more sensitive to other forms of out-of-control situations when outliers are present. Hence, the (EWMA-SMQ) becomes a preferred alternative to be taken and applied in quality control. The data used in this research represent the weights of the Al-Sabah Iraqi newspaper published by the Iraqi media networks. Twenty-five samples were taken and each sample consisted of five observations. These samples were taken at different production times, as the average weight of the newspaper was approximately (150) g. Through the application of the classical control chart (EWMA), exit four points for the upper and lower control limits, and the application of (EWMA-SM), (4) points are out of the upper and lower limits of the control; the control limits have been extended from the top and bottom sides of the (EWMA-SM) chart, making it less sensitive to the diagnosis of the shift in the mean process. The (EWMA-SMQ) chart detected extra points out of control. There were (7) points out of the upper and lower limits for the control, tight control limits of the (EWMA-SMQ) chart from the top and bottom sides. Due to this narrowness, three additional points were detected. Therefore (EWMA-SMQ) chart is more robust than the (EWMA-SM) control chart. This research aims to make a comparative study between the classical and robust for both types (EWMA-SM) & (EWMA-SMQ) for the exponentially weighted moving average control chart. The most important result of the research that the (EWMA-SMQ) chart is more suitable than the (EWMA-SM) & classical (EWMA) when outliers are present in the data. This gives importance to it to control the quality of the product. By this robust chart, the outliers must be detected, investigated and the special cause removed if possible. The presence of outliers will reduce the sensitivity of a control chart. The (EWMA-SMQ) control chart is more sensitive to out-of-control conditions when outliers are present in data. The limits computed from the estimate of the interquartile ranges for the (EWMA-SMQ) chart are less influenced by outliers than the (EWMA-SM) chart where the limits are computed based on the sample ranges. Thus the (EWMA-SMQ) chart is more robust than the (EWMA-SM) chart
The Comparative of Morphological and Gravity Anomaly Lineaments in West Progo Mountains, Indonesia The Comparative of Morphological and Gravity Anomaly Lineaments in West Progo Mountains, Indonesia
No full textIn Yogyakarta Special Region, the West Progo Dome comprises the Nanggulan Formation and Old-Andesite Formation as the oldest formations. The Nanggulan Formation is composed of sedimentary rock with a density of 2.5 g/cm3, while the Old-Andesite Formation is composed of volcanic rock with a density of 2.7 g/cm3. Dome morphology is formed by vertical endogenous energy that radiates SE-NW, NE-SW, and E-W. This study aims to describe the correlation between the hill lineaments and gravity anomaly lineaments in the Nanggulan Formation and Old-Andesian Formation. Identification of the hill lineament uses Shuttle Radar Topography Mission (SRTM), while the gravity anomaly lineament uses gravity anomaly map. The standard used in the gravity survey concerning the American Society for Testing and Materials Standard (ASTM). The measurement system utilizes a looping distance of 200-350 meters. The lineaments of the hill and gravity anomaly show the same direction SE-NW. Both lineaments are calculated by fractal dimension (D) utilize the box-counting method. The result of overlaying the two lineaments' fractal dimension produces the same value and the different value. The same fractal dimension value (D=0.81-1.20) indicates whether the hill lineament and gravity anomaly lineament are correlated, while the different fractal dimension values indicate that the two lineaments are not correlated. The fractal dimension value is different due to small intrusions and faults
Local Trajectory Occurrence Patterns for Partial Action and Gesture Recognition
Get PDFAction and gesture recognition is essential in computer vision because of their multiple and potential applications. Nowadays, in the literature, dramatic advances have been reported regarding recognizing gestures and actions under uncontrolled scenarios with significant appearance and motion variations. Nevertheless, much of these approaches still require manual segmentation of temporal action boundaries and complete processing of whole sequences to obtain a prediction. This work introduces a novel motion description that can recognize actions and gestures over partial sequences. The approach starts by representing video sequences as a set of key-point trajectories. Such trajectories are then hierarchically represented from a local and regional perspective, following a statistical counting process. Firstly, each trajectory is defined as a binary occurrence pattern that allows for standing out critical motions by neighborhood densities from a local perspective. Such occurrence patterns are involved in a regional bag-of-words representation of actions. Both representations could be obtained for any interval inside the video, achieving a partial recognition of motion, and regional representation is mapped to a support vector machine to obtain a prediction. The proposed approach was evaluated on academic action recognition datasets and a large gesture dataset used for sign recognition. Regarding partial video sequence recognition, the proposed approach achieves an accuracy rate of 63% using only 20% of frames. The proposed strategy achieved a very compact description, with only 400 scalar values, which ideal for online applications
Application of Sub-bituminous Coal Activated with Urea to Improve Chemical Properties of Ultisols and Palm Oil's Growth (Elaeis Guineensis Jacq.) In Pulau Punjung, Dharmasraya
Get PDFUltisols are a type of suboptimal land with low fertility, so it is necessary to add ameliorants such as Sub-bituminous (unproductive young coal as an energy source) to increase soil fertility. This study aimed to examine the effect of Sub-bituminous coal activated by Urea in improving the chemical properties of Ultisols and the growth of oil palm. The study was conducted in Nagari Sungai Dareh, Pulau Punjung, Dharmasraya West Sumatra using a Randomized Block Design with 6 treatments and 3 groups. The treatments are the dose of Sub-bituminous coal (g (planting hole)-1) and Urea fertilizer, which is A = 150; B = 300; C = 450; D = 150 + 10% Urea; E = 300 + 10% Urea; and F = 450 + 10% Urea. The results showed that the administration of Sub-bituminous coal at a dose of 450 g (planting hole)-1 activated by 10% Urea was able to improve the chemical properties of Ultisols such as increasing the soil pH by 0.57 units; total-N by 0.13%; organic-C by 0.69%; available P by 3.25 ppm; CEC by 16,14 cmolc kg-1 and can reduce of Al-exch to immeasurable compared to 150 g (planting hole)-1. Sub-bituminous coal activated by 10% Urea increases oil palm growth (Elaeis guineensis Jacq.). Increasing plant growth was found in 450 g (planting hole)-1 + 10% Urea with an increase in plant height by 48.34 cm, the number of midribs of 4 strands, stem diameter by 1.71 cm, and nutrient plant of N, P and K by 0.014; 0.005; and 0.003%
An Empirical Study of Online Learning in Non-stationary Data Streams Using Ensemble of Ensembles
Get PDFNumerous information system applications produce a huge amount of non-stationary streaming data that demand real-time analytics. Classification of data streams engages supervised models to learn from a continuous infinite flow of labeled observations. The critical issue of such learning models is to handle dynamicity in data streams where the data instances undergo distributional change called concept drift. The online learning approach is essential to cater to learning in the streaming environment as the learning model is built and functional without the complete data for training in the beginning. Also, the ensemble learning method has proven to be successful in responding to evolving data streams. A multiple learner scheme boosts a single learner's prediction by integrating multiple base learners that outperform each independent learner. The proposed algorithm EoE (Ensemble of Ensembles) is an integration of ten seminal ensembles. It employs online learning with the majority voting to deal with the binary classification of non-stationary data streams. Utilizing the learning capabilities of individual sub ensembles and overcoming their limitations as an individual learner, the EoE makes a better prediction than that of its sub ensembles. The current communication empirically and statistically analyses the performance of the EoE on different figures of merits like accuracy, sensitivity, specificity, G-mean, precision, F1-measure, balanced accuracy, and overall performance measure when tested on a variety of real and synthetic datasets. The experimental results claim that the EoE algorithm outperforms its state-of-the-art independent sub ensembles in classifying non-stationary data streams
UV-Vis Absorbance and Fluorescence Characterization of Pasig River Surface Water Samples Towards the Development of an LED Fluorescence Lidar System
Get PDFThe status of water quality in Pasig River was studied using UV-Vis absorbance, 3D excitation-emission matrices (EEMs), fluorescence measurements of dissolved organic matter (DOM), and physicochemical parameters measurements. The study was conducted at seven selected sampling stations in Pasig river from April 2019 to June 2019. It has been years since the government has conducted rehabilitation on the Pasig river and we want to determine its current water quality status with the additional information provided by the UV-Vis absorbance and fluorescence spectroscopy. Several surface water samples were collected using the Pasig River ferry system at (St 1) Lawton Station, (St 4) Valenzuela Station, and (St 7) San Joaquin Station. After computing for the absorbance values at 280-nm, 250-nm/365-nm, 253-nm/203-nm, and 226-400, we have used this method to determine the presence of organic carbon and its aromatic substituents. The results showed low humification degree and aromatic structure and vary from April to June 2019. (St 3) shows higher stability organic molecules containing benzene ring structures. A seasonal variability has been observed from the water quality parameters, which is also present from the fluorescence measurements. DOM sources were measured using fluorescence index (FI), the results showed that all surface water samples were terrestrially derived DOM concentrations. The variance can be attributed to the effluents from the land use types near the sampling stations such as industrial and residential waste. Based on the water quality, absorbance and fluorescence results, the impact of marine waters greatly affects the characterization and production of organic materials
A Proposed Classification Method in Menu Engineering Using the K-Nearest Neighbors Algorithm
Get PDFIn the culinary business, the menu is crucial; therefore, the performance of each menu needs to be known to maintain business continuity. Menu engineering is a special technique used to see the performance comparison of each menu item. This research proposes modeling menu engineering with a new approach in classifying menu items using the k-Nearest Neighbors (k-NN) algorithm using the sales training data of sales data in 2019 belonging to one of the micro, small and medium-sized enterprises in the culinary sub-sector in Salatiga, Indonesia. In the modeling, the popularity index (menu mix) and item contribution margin are used as variables, while the menu item class is used as the label attribute of the classification. Determination of the k value in the k-NN algorithm was done by the experimental method so that it produces the most optimal k based on the highest accuracy value, while the distance calculation on k-NN was done using euclidean distance. Evaluation of the model was done using 10-fold cross-validation with four performance evaluation criteria, namely weighted mean recall, weighted mean precision, accuracy, classification error. Based on the evaluation results, an accuracy of 96.84% was obtained; thus, the proposed model is considered to have given good and accurate results. This proposed model has been implemented in MSME sales data to classify menu items. The results of this classification were used as a basis for recommending menu engineering strategies to MSMEs
The Terpenoid Activity of Ethanol extracted from Purple Yam Sap to Inhibit the Growth of R. oligosporus and S. cerevisiae
Get PDFPlants that contain secondary metabolite components can be used as an anti-microbial. Terpenoids are part of secondary metabolic, which is naturally in the plants. This study aims to investigate the terpenoid activity of purple yam sap as an anti-microbe to prevent the growth of R. Oligosporus’mold and S.Cerevicea’s yeast. The terpenoid property within the purple yam sap was identified using the thin-layer chromatography (TLC) eluent toluene of Etil Asetat (3: 7). The anti-microbial activity was tested using the agar diffusion method, and the cell damage analysis was carried out using SEM. This study showed that the anti-microbial activities of the terpenoid to inhibit the growth of R. Oligosporus mold were as follow: the 96% ethanol extract had the inhibition zone of 8.5 mm, the 80% ethanol extract had the inhibition zone of 9.5 mm, and 65% ethanol extract had the inhibition zone of 10.03 mm, whereas the 50% ethanol extract had the highest inhibition zone by 10.93 mm. Meanwhile, 96% ethanol extract had the most robust ability to inhibit the growth of S.crevicea yeast by 11.07 mm, and 80% of the ethanol extract had the weakest ability to inhibit the growth of this yeast only 9.23 mm diameter of inhibition zone. The terpenoids substance with the minimum concentrate (0.01%). Extract causes the cell of the R.oligosporus fungus and cells the S. Cereviceae’s yeast to leak; thus, the cell ruptured and died. On the one hand, the S.cereviceae  cell changes the shapes and experiences cell damage
Power Loss Reduction and Voltage Profile Improvement in Electrical Power Distribution Networks Using Static Var Compensators
Get PDFRising demand for electrical power due to the global technological advancement has brought so many challenges such as instability of voltage, huge power loss, and unstable power factor on the distribution network. This work applied Static Var Compensator (SVC) to the power distribution network of Ado-Ekiti, Nigeria, to study its effect on active power loss reduction and voltage profile improvement of the network. The bus voltage, power, and the current flowing through the selected feeders were measured and recorded accordingly for analysis. Test network parameters like route length, transformer parameters, and maximum power flow were obtained from Benin Electricity Distribution Company, Ado-Ekiti, Nigeria. The distribution network was then modeled and simulated with and without SVC in NEPLAN software environment. The simulation results of the power flow and voltage stability analyses of the network without SVCs showed that some distribution lines were overloaded and that the network parameters were not within the statutory tolerable limits of 0.95 p.u. and 1.05 p.u. nominal voltage. There was 9.73% reduction in the active power loss when SVCs were incorporated into the test network. The voltage stability curve showed an increase in distribution network capacity from an initial steady-state of 150% to 263% of the total active load when the SVCs were incorporated. Hence, the need to normalize the network by applying SVCs to all the buses with very low voltages. This work will assist the power distribution supply companies in making some informed decisions in reducing power losses on their networks
Loads of Pollution to Lake Toba and Their Impacts
Get PDFLakes provide various ecosystem services that support biotic habitats and human life. In contrast, many lakes in the world are degraded due to pollutant supply from surrounding areas and human activities in the lake. Lake Toba, which is the largest lake in Indonesia, has indicated a polluted condition. However, the source and load of each pollutant are not yet known. A study has been conducted to determine nutrient and organic load levels entering the lake represented by Total Phosphorus (TP) and Chemical Oxygen Demand (COD), respectively. Observations were carried out in November 2017 at 22 locations, i.e., at 12 inlet rivers debouching to the lake and 10 sites at the lake. The pollutant impact was assessed from water class criteria based on COD, waters trophic status based on TP, and vertical oxygen profile representing cage aquaculture (CA) and non-cage aquaculture (NCA) areas. Based on COD and government regulation number 82/2001, water quality at the lake inlets was class III and IV. In the lake area, water class in NCA was III, while in CA the water class tends to be III and IV. Estimated TP loading from the catchment area was 138 tonnes/yr, while that from cage aquaculture activity was 570.33 tonnes/yr. Pollutants have caused the worsening of water class, increasing water column anoxia in the hypolimnion layer and eutrophication in Lake Toba