Search results for: input data stream

Authors: Bharatendra Rai

Abstract:

Predictive data analysis and modeling involving machine learning techniques become challenging in presence of too many explanatory variables or features. Presence of too many features in machine learning is known to not only cause algorithms to slow down, but they can also lead to decrease in model prediction accuracy. This study involves housing dataset with 79 quantitative and qualitative features that describe various aspects people consider while buying a new house. Boruta algorithm that supports feature selection using a wrapper approach build around random forest is used in this study. This feature selection process leads to 49 confirmed features which are then used for developing predictive random forest models. The study also explores five different data partitioning ratios and their impact on model accuracy are captured using coefficient of determination (r-square) and root mean square error (rsme).

Keywords: Housing data, feature selection, random forest, Boruta algorithm, root mean square error.

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Authors: W. Jaipahkdee, C. Srinilta

Abstract:

The overall service performance of I/O intensive system depends mainly on workload on its storage system. In heterogeneous storage environment where storage elements from different vendors with different capacity and performance are put together, workload should be distributed according to storage capability. This paper addresses data placement issue in short video sharing website. Workload contributed by a video is estimated by the number of views and life time span of existing videos in same category. Experiment was conducted on 42,000 video titles in six weeks. Result showed that the proposed algorithm distributed workload and maintained balance better than round robin and random algorithms.

Keywords: data placement, heterogeneous storage system, YouTube, short videos

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Authors: M A Hannan, A. Hussain, S. A. Samad, K. A. Ishak, A. Mohamed

Abstract:

This paper presents a general trainable framework for fast and robust upright human face and non-human object detection and verification in static images. To enhance the performance of the detection process, the technique we develop is based on the combination of fast neural network (FNN) and classical neural network (CNN). In FNN, a useful correlation is exploited to sustain high level of detection accuracy between input image and the weight of the hidden neurons. This is to enable the use of Fourier transform that significantly speed up the time detection. The combination of CNN is responsible to verify the face region. A bootstrap algorithm is used to collect non human object, which adds the false detection to the training process of the human and non-human object. Experimental results on test images with both simple and complex background demonstrate that the proposed method has obtained high detection rate and low false positive rate in detecting both human face and non-human object.

Keywords: Algorithm, detection of human and non-human object, FNN, CNN, Image training.

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Authors: G. Parmar, S. Mukherjee, R. Prasad

Abstract:

The authors present an optimization algorithm for order reduction and its application for the determination of the relative mapping errors of linear time invariant dynamic systems by the simplified models. These relative mapping errors are expressed by means of the relative integral square error criterion, which are determined for both unit step and impulse inputs. The reduction algorithm is based on minimization of the integral square error by particle swarm optimization technique pertaining to a unit step input. The algorithm is simple and computer oriented. It is shown that the algorithm has several advantages, e.g. the reduced order models retain the steady-state value and stability of the original system. Two numerical examples are solved to illustrate the superiority of the algorithm over some existing methods.

Keywords: Order reduction, Particle swarm optimization, Relative mapping error, Stability.

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Authors: S. Raja Ratna, R. Ravi

Abstract:

Securing the confidential data transferred via wireless network remains a challenging problem. It is paramount to ensure that data are accessible only by the legitimate users rather than by the attackers. One of the most serious threats to organization is jamming, which disrupts the communication between any two pairs of nodes. Therefore, designing an attack-defending scheme without any packet loss in data transmission is an important challenge. In this paper, Dependence based Malicious Route Defending DMRD Scheme has been proposed in multi path routing environment to prevent jamming attack. The key idea is to defend the malicious route to ensure perspicuous transmission. This scheme develops a two layered architecture and it operates in two different steps. In the first step, possible routes are captured and their agent dependence values are marked using triple agents. In the second step, the dependence values are compared by performing comparator filtering to detect malicious route as well as to identify a reliable route for secured data transmission. By simulation studies, it is observed that the proposed scheme significantly identifies malicious route by attaining lower delay time and route discovery time; it also achieves higher throughput.

Keywords: Attacker, Dependence, Jamming, Malicious.

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Authors: K. Kalaiselvan, K. Sekar, S. Elavarasi

Abstract:

The use of laser beam welding for joining titanium and aluminum offers more advantages compared with conventional joining processes. Dissimilar metal combination is very much needed for aircraft structural industries and research activities. The quality of a weld joint is directly influenced by the welding input parameters. The common problem that is faced by the manufactures is the control of the process parameters to obtain a good weld joint with minimal detrimental. To overcome this issue, various parameters can be preferred to obtain quality of weld joint. In this present study an overall literature review on processing parameters such as offset distance, welding speed, laser power, shielding gas and filler metals are discussed with the effects on quality weldment. Additionally, mechanical properties of welds joint are discussed. The aim of the report is to review the recent progress in the welding of dissimilar titanium (Ti) and aluminum (Al) alloys to provide a basis for follow up research.

Keywords: Laser beam welding, titanium, aluminum, process parameters.

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Authors: Fatma H. Elfouly, Mohamed I. Mahmoud, Moawad I. M. Dessouky, Salah Deyab

Abstract:

Recently, the Field Programmable Gate Array (FPGA) technology offers the potential of designing high performance systems at low cost. The discrete wavelet transform has gained the reputation of being a very effective signal analysis tool for many practical applications. However, due to its computation-intensive nature, current implementation of the transform falls short of meeting real-time processing requirements of most application. The objectives of this paper are implement the Haar and Daubechies wavelets using FPGA technology. In addition, the Bit Error Rate (BER) between the input audio signal and the reconstructed output signal for each wavelet is calculated. From the BER, it is seen that the implementations execute the operation of the wavelet transform correctly and satisfying the perfect reconstruction conditions. The design procedure has been explained and designed using the stat-ofart Electronic Design Automation (EDA) tools for system design on FPGA. Simulation, synthesis and implementation on the FPGA target technology has been carried out.

Keywords: Daubechies wavelet, discrete wavelet transform, Haar wavelet, Xilinx FPGA.

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Authors: M. Tarafdar Haque, S. Najafi

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Improving the reactive power and voltage profile of a distribution substation is investigated in this paper. The purpose is to properly determination of the shunt capacitors on/off status and suitable tap changer (TC) position of a substation transformer. In addition, the limitation of secondary bus voltage, the maximum allowable number of switching operation in a day for on load tap changer and on/off status of capacitors are taken into account. To achieve these goals, an artificial neural network (ANN) is designed to provide preliminary scheduling. Input of ANN is active and reactive powers of transformer and its primary and secondary bus voltages. The output of ANN is capacitors on/off status and TC position. The preliminary schedule is further refined by fuzzy dynamic programming in order to reach the final schedule. The operation of proposed method in Q/V improving is compared with the results obtained by operator operation in a distribution substation.

Keywords: Neuro-fuzzy, Dynamic programming, Reactive power, Voltage profile.

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Authors: Alok Sharma, Dr. Harvinder S. Saini, Raviteja Tiruvury

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This paper outlines the application of Knowledge Management (KM) principles in the context of Educational institutions. The paper caters to the needs of the engineering institutions for imparting quality education by delineating the instruction delivery process in a highly structured, controlled and quantified manner. This is done using a software tool EDULOGIC+. The central idea has been based on the engineering education pattern in Indian Universities/ Institutions. The data, contents and results produced over contiguous years build the necessary ground for managing the related accumulated knowledge. Application of KM has been explained using certain examples of data analysis and knowledge extraction.

Keywords: Education software system, information system, knowledge management.

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Authors: P. Visutsak

Abstract:

The study of the interaction between humans and computers has been emerging during the last few years. This interaction will be more powerful if computers are able to perceive and respond to human nonverbal communication such as emotions. In this study, we present the image-based approach to emotion classification through lower facial expression. We employ a set of feature points in the lower face image according to the particular face model used and consider their motion across each emotive expression of images. The vector of displacements of all feature points input to the Adaptive Support Vector Machines (A-SVMs) classifier that classify it into seven basic emotions scheme, namely neutral, angry, disgust, fear, happy, sad and surprise. The system was tested on the Japanese Female Facial Expression (JAFFE) dataset of frontal view facial expressions [7]. Our experiments on emotion classification through lower facial expressions demonstrate the robustness of Adaptive SVM classifier and verify the high efficiency of our approach.

Keywords: emotion classification, facial expression, adaptive support vector machines, facial expression classifier.

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Authors: Madiha Khan, Sidrah Ramzan, Seemab Khan, Shahzad Hassan, Kamran Saeed

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Measuring semantic similarity between texts is calculating semantic relatedness between texts using various techniques. Our web application (Measuring Relatedness of Concepts-MRC) allows user to input two text corpuses and get semantic similarity percentage between both using WordNet. Our application goes through five stages for the computation of semantic relatedness. Those stages are: Preprocessing (extracts keywords from content), Feature Extraction (classification of words into Parts-of-Speech), Synonyms Extraction (retrieves synonyms against each keyword), Measuring Similarity (using keywords and synonyms, similarity is measured) and Visualization (graphical representation of similarity measure). Hence the user can measure similarity on basis of features as well. The end result is a percentage score and the word(s) which form the basis of similarity between both texts with use of different tools on same platform. In future work we look forward for a Web as a live corpus application that provides a simpler and user friendly tool to compare documents and extract useful information.

Keywords: GraphViz representation, semantic relatedness, similarity measurement, WordNet similarity.

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Authors: Fanqiang Kong, Chending Bian

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In this work, we exploit two assumed properties of the abundances of the observed signatures (endmembers) in order to reconstruct the abundances from hyperspectral data. Joint-sparsity is the first property of the abundances, which assumes the adjacent pixels can be expressed as different linear combinations of same materials. The second property is rank-deficiency where the number of endmembers participating in hyperspectral data is very small compared with the dimensionality of spectral library, which means that the abundances matrix of the endmembers is a low-rank matrix. These assumptions lead to an optimization problem for the sparse unmixing model that requires minimizing a combined l_2,p-norm and nuclear norm. We propose a variable splitting and augmented Lagrangian algorithm to solve the optimization problem. Experimental evaluation carried out on synthetic and real hyperspectral data shows that the proposed method outperforms the state-of-the-art algorithms with a better spectral unmixing accuracy.

Keywords: Hyperspectral unmixing, joint-sparse, low-rank representation, abundance estimation.

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Authors: Nastaran Moosavi, Mohammad Mokhtari

Abstract:

Seismic inversion is a technique which has been in use for years and its main goal is to estimate and to model physical characteristics of rocks and fluids. Generally, it is a combination of seismic and well-log data. Seismic inversion can be carried out through different methods; we have conducted and compared post-stack and pre- stack seismic inversion methods on real data in one of the fields in the Persian Gulf. Pre-stack seismic inversion can transform seismic data to rock physics such as P-impedance, S-impedance and density. While post- stack seismic inversion can just estimate P-impedance. Then these parameters can be used in reservoir identification. Based on the results of inverting seismic data, a gas reservoir was detected in one of Hydrocarbon oil fields in south of Iran (Persian Gulf). By comparing post stack and pre-stack seismic inversion it can be concluded that the pre-stack seismic inversion provides a more reliable and detailed information for identification and prediction of hydrocarbon reservoirs.

Keywords: Density, P-impedance, S-impedance, post-stack seismic inversion, pre-stack seismic inversion.

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Authors: G. Parmar, S. Mukherjee, R. Prasad

Abstract:

The authors present an algorithm for order reduction of linear time invariant dynamic systems using the combined advantages of the eigen spectrum analysis and the error minimization by particle swarm optimization technique. Pole centroid and system stiffness of both original and reduced order systems remain same in this method to determine the poles, whereas zeros are synthesized by minimizing the integral square error in between the transient responses of original and reduced order models using particle swarm optimization technique, pertaining to a unit step input. It is shown that the algorithm has several advantages, e.g. the reduced order models retain the steady-state value and stability of the original system. The algorithm is illustrated with the help of two numerical examples and the results are compared with the other existing techniques.

Keywords: Eigen spectrum, Integral square error, Orderreduction, Particle swarm optimization, Stability.

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Authors: Jinn-Yi Yeh, Tai-Hsi Wu

Abstract:

Hemodialysis patients might suffer from unhealthy care behaviors or long-term dialysis treatments. Ultimately they need to be hospitalized. If the hospitalization rate of a hemodialysis center is high, its quality of service would be low. Therefore, how to decrease hospitalization rate is a crucial problem for health care. In this study we combined temporal abstraction with data mining techniques for analyzing the dialysis patients' biochemical data to develop a decision support system. The mined temporal patterns are helpful for clinicians to predict hospitalization of hemodialysis patients and to suggest them some treatments immediately to avoid hospitalization.

Keywords: Hemodialysis, Temporal abstract, Data mining, Healthcare quality.

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Authors: Anant Oonsivilai, Sanom Saichoomdee

Abstract:

To determine the presence and location of faults in a transmission by the adaptation of protective distance relay based on the measurement of fixed settings as line impedance is achieved by several different techniques. Moreover, a fast, accurate and robust technique for real-time purposes is required for the modern power systems. The appliance of radial basis function neural network in transmission line protection is demonstrated in this paper. The method applies the power system via voltage and current signals to learn the hidden relationship presented in the input patterns. It is experiential that the proposed technique is competent to identify the particular fault direction more speedily. System simulations studied show that the proposed approach is able to distinguish the direction of a fault on a transmission line swiftly and correctly, therefore suitable for the real-time purposes.

Keywords: radial basis function neural network, transmission lines protection, relaying, power system.

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Authors: M. Abdullah-Al-Wadud

Abstract:

Sensor-based Activity Recognition systems usually accounts which sensors have been activated to perform an activity. The system then combines the conditional probabilities of those sensors to represent different activities and takes the decision based on that. However, the information about the sensors which are not activated may also be of great help in deciding which activity has been performed. This paper proposes an approach where the sensory data related to both usage and non-usage of objects are utilized to make the classification of activities. Experimental results also show the promising performance of the proposed method.

Keywords: Naïve Bayesian-based classification, Activity recognition, sensor data, object-usage model.

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Authors: Y. Harold Robinson, M. Rajaram, E. Golden Julie, S. Balaji

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This paper describes the proficient way of choosing the cluster head based on dominating set algorithm in a wireless sensor network (WSN). The algorithm overcomes the energy deterioration problems by this selection process of cluster heads. Clustering algorithms such as LEACH, EEHC and HEED enhance scalability in WSNs. Dominating set algorithm keeps the first node alive longer than the other protocols previously used. As the dominating set of cluster heads are directly connected to each node, the energy of the network is saved by eliminating the intermediate nodes in WSN. Security and trust is pivotal in network messaging. Cluster head is secured with a unique key. The member can only connect with the cluster head if and only if they are secured too. The secured trust model provides security for data transmission in the dominated set network with the group key. The concept can be extended to add a mobile sink for each or for no of clusters to transmit data or messages between cluster heads and to base station. Data security id preferably high and data loss can be prevented. The simulation demonstrates the concept of choosing cluster heads by dominating set algorithm and trust evaluation using DSTE. The research done is rationalized.

Keywords: Wireless Sensor Networks, LEECH, EEHC, HEED, DSTE.

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Authors: Kozak K, M. Kozak, K. Stapor

Abstract:

The k-nearest neighbors (knn) is a simple but effective method of classification. In this paper we present an extended version of this technique for chemical compounds used in High Throughput Screening, where the distances of the nearest neighbors can be taken into account. Our algorithm uses kernel weight functions as guidance for the process of defining activity in screening data. Proposed kernel weight function aims to combine properties of graphical structure and molecule descriptors of screening compounds. We apply the modified knn method on several experimental data from biological screens. The experimental results confirm the effectiveness of the proposed method.

Keywords: biological screening, kernel methods, KNN, QSAR

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Authors: M. A. Foda, K. A. Alsaif, M. M. ElMadany, A.S. Aguib

Abstract:

In this paper, the noise maps for the area encircled by the Second Ring Road in Riyadh city are developed based on real measured data. Sound level meters, GPS receivers to determine measurement position, a database program to manage the measured data, and a program to develop the maps are used. A baseline noise level has been established at each short-term site so subsequent monitoring may be conducted to describe changes in Riyadh-s noise environment. Short-term sites are used to show typical daytime and nighttime noise levels at specific locations by short duration grab sampling.

Keywords: Noise mapping, Noise measurements, GPS, noise level.

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Authors: Neves, L., Ferreira, V., Oliveira, R.

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Addition of an oily waste to a co-composting process of dairy cow manure with food waste, and the influence in the final product was evaluated. Three static composting piles with different substrates concentrations were assessed. Sawdust was also added to all composting piles to attain 60%, humidity at the beginning of the process. In pile 1, the co-substrates were the solid-phase of dairy cow manure, food waste and sawdust as bulking agent. In piles 2 and 3 there was an extra input of oily waste of 7 and 11% of the total volume, respectively, corresponding to 18 and 28% in dry weight. The results showed that the co-composting process was feasible even at the highest fat content. Another positive effect due to the oily waste addition was the requirement of extra humidity, due to the hydrophobic properties of this specific waste, which may imply reduced need of a bulking agent. Moreover, this study shows that composting can be a feasible way of adding value to fatty wastes. The three final composts presented very similar and suitable properties for land application.

Keywords: Cow manure, composting, food waste, lipids content.

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Authors: Salim Ouchtati, Bedda Mouldi, Abderrazak Lachouri

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In this paper we present an off line system for the recognition of the handwritten numeric chains. Our work is divided in two big parts. The first part is the realization of a recognition system of the isolated handwritten digits. In this case the study is based mainly on the evaluation of neural network performances, trained with the gradient back propagation algorithm. The used parameters to form the input vector of the neural network are extracted on the binary images of the digits by several methods: the distribution sequence, the Barr features and the centred moments of the different projections and profiles. The second part is the extension of our system for the reading of the handwritten numeric chains constituted of a variable number of digits. The vertical projection is used to segment the numeric chain at isolated digits and every digit (or segment) will be presented separately to the entry of the system achieved in the first part (recognition system of the isolated handwritten digits). The result of the recognition of the numeric chain will be displayed at the exit of the global system.

Keywords: Optical Characters Recognition, Neural networks, Barr features, Image processing, Pattern Recognition, Featuresextraction.

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Authors: Siti Khadijah Che Osmi, Syed Mohd Ahmad

Abstract:

This paper presents a methodology to develop fragility curves for shallow tunnels so as to describe a relationship between seismic hazard and tunnel vulnerability. Emphasis is given to the influence of surrounding soil material properties because the dynamic behaviour of the tunnel mostly depends on it. Four ground properties of soils ranging from stiff to soft soils are selected. A 3D nonlinear time history analysis is used to evaluate the seismic response of the tunnel when subjected to five real earthquake ground intensities. The derived curves show the future probabilistic performance of the tunnels based on the predicted level of damage states corresponding to the peak ground acceleration. A comparison of the obtained results with the previous literature is provided to validate the reliability of the proposed fragility curves. Results show the significant role of soil properties and input motions in evaluating the seismic performance and response of shallow tunnels.

Keywords: Fragility analysis, seismic performance, tunnel lining, vulnerability.

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Authors: May Zin Lwin., Mya Mya Oo

Abstract:

In the first part of the research work, an electrolyzer (10.16 cm dia and 24.13 cm height) to produce hydrogen and oxygen was constructed for single slice O2/H2 fuel cell using cation exchange membrane. The electrolyzer performance was tested with 23% NaOH, 30% NaOH, 30% KOH and 35% KOH electrolyte solution with current input 4 amp and 2.84 V from the rectifier. Rates of volume of hydrogen produced were 0.159 cm3/sec, 0.155 cm3/sec, 0.169 cm3/sec and 0.163 cm3/sec respectively from 23% NaOH, 30% NaOH, 30% KOH and 35% KOH solution. Rates of volume of oxygen produced were 0.212 cm3/sec, 0.201 cm3/sec, 0.227 cm3/sec and 0.219 cm3/sec respectively from 23% NaOH, 30% NaOH, 30% KOH and 35% KOH solution (1.5 L). In spite of being tested the increased concentration of electrolyte solution, the gas rate does not change significantly. Therefore, inexpensive 23% NaOH electrolyte solution was chosen to use as the electrolyte in the electrolyzer. In the second part of the research work, graphite serpentine flow plates, fiberglass end plates, stainless steel screen electrodes, silicone rubbers were made to assemble the single slice O2/H2 polymer electrolyte membrane fuel cell (PEMFC).

Keywords: electrolyzer, electrolyte solution, fuel cell, rectifier

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Authors: Bhaskar M., Venkataramani B.

Abstract:

In the literature, surfing technique has been proposed for single ended wave-pipelined serial interconnects to increase the data transfer rate. In this paper a novel surfing technique is proposed for differential wave-pipelined serial interconnects, which uses a 'Controllable inverter pair' for surfing. To evaluate the efficiency of this technique, a transceiver with transmitter, receiver, delay locked loop (DLL) along with 40mm metal 4 interconnects using the proposed surfing technique is implemented in UMC 180nm technology and their performances are studied through post layout simulations. From the study, it is observed that the proposed scheme permits 1.875 times higher data transmission rate compared to the single ended scheme whose maximum data transfer rate is 1.33 GB/s. The proposed scheme has the ability to receive the correct data even with stuck-at-faults in the complementary line.

Keywords: Controllable inverter pair, differential interconnect, serial link, surfing, wave pipelining.

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Authors: Budihardjo Sarwo Sastrosudiro, Arnas Lubis, Muhammad Idrus Alhamid, Nasruddin Jusuf

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Solar thermal cooling system was installed on Mechanical Research Center (MRC) Building that is located in Universitas Indonesia, Depok, Indonesia. It is the first cooling system in Indonesia that utilizes solar energy as energy input combined with natural gas; therefore, the control system must be appropriated with the climates. In order to stabilize the cooling capacity and also to maximize the use of solar energy, the system applies some controllers. Constant flow rate and on/off controller are applied for the hot water, chilled water and cooling water pumps. The hot water circulated by pump when the solar radiation is over than 400W/m², and the chilled water is continually circulated by pump and its temperature is kept constant 7 °C by absorption chiller. The cooling water is also continually circulated until the outlet temperature of cooling tower below than 27 ^oC. Furthermore, the three-way valve is used to control the hot water for generate vapor on absorption chiller. The system performance using that control system is shown in this study results.

Keywords: Absorption chiller, control system, solar cooling, solar energy.

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Authors: Akram M. Zeki, Azizah A. Manaf

Abstract:

Least Significant Bit (LSB) technique is the earliest developed technique in watermarking and it is also the most simple, direct and common technique. It essentially involves embedding the watermark by replacing the least significant bit of the image data with a bit of the watermark data. The disadvantage of LSB is that it is not robust against attacks. In this study intermediate significant bit (ISB) has been used in order to improve the robustness of the watermarking system. The aim of this model is to replace the watermarked image pixels by new pixels that can protect the watermark data against attacks and at the same time keeping the new pixels very close to the original pixels in order to protect the quality of watermarked image. The technique is based on testing the value of the watermark pixel according to the range of each bit-plane.

Keywords: Watermarking, LSB, ISB, Robustness.

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Authors: J. K. Alhassan, S. A. Lawal

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This work is on decision tree-based classification for the disbursement of scholarship. Tree-based data mining classification technique is used in other to determine the generic rule to be used to disburse the scholarship. The system based on the defined rules from the tree is able to determine the class (status) to which an applicant shall belong whether Granted or Not Granted. The applicants that fall to the class of granted denote a successful acquirement of scholarship while those in not granted class are unsuccessful in the scheme. An algorithm that can be used to classify the applicants based on the rules from tree-based classification was also developed. The tree-based classification is adopted because of its efficiency, effectiveness, and easy to comprehend features. The system was tested with the data of National Information Technology Development Agency (NITDA) Abuja, a Parastatal of Federal Ministry of Communication Technology that is mandated to develop and regulate information technology in Nigeria. The system was found working according to the specification. It is therefore recommended for all scholarship disbursement organizations.

Keywords: Decision tree, classification, data mining, scholarship.

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Authors: Bunphot Paosombat, Thitiporn Suttikul, Sumaeth Chavadej

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The effects of ethylene (C2H4) feed position and O2/C2H4 feed molar ratio on ethylene epoxidation in a parallel dielectric barrier discharge (DBD) were studied. The results showed that the ethylene feed position fraction of 0.5 and the feed molar ratio of O2/C2H4 of 0.2:1 gave the highest EO selectivity of 34.3% and the highest EO yield of 5.28% with low power consumptions of 2.11×10-16 Ws/molecule of ethylene converted and 6.34×10-16 Ws/molecule of EO produced when the DBD system was operated under the best conditions: an applied voltage of 19 kV, an input frequency of 500 Hz and a total feed flow rate of 50 cm3/min. The separate ethylene feed system provided much higher epoxidation activity as compared to the mixed feed system which gave EO selectivity of 15.5%, EO yield of 2.1% and the power consumption of EO produced of 7.7×10-16 Ws/molecule.

Keywords: Dielectric Barrier Discharge, C2H4 Feed Position, Epoxidation, Ethylene Oxide

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Authors: Sabina Akter, Osiris Valdez Banda, Pentti Kujala, Jani Romanoff

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This paper examines the relationship between on-board environmental factors and customer overall satisfaction in the context of the cruise on-board experience. The on-board environmental factors considered are ambient, layout/design, social, product/service and on-board enjoyment factors. The study presents a data-driven framework and model for the on-board cruise experience. The data are collected from 893 respondents in an application of a self-administered online questionnaire of their cruise experience. This study reveals the cruise passengers’ on-board experience through the customer decision journey based on the publicly available data. Pearson correlation and regression analysis have been applied, and the results show a positive and a significant relationship between the environmental factors and on-board experience. These data help understand the cruise passengers’ on-board experience, which will be used for the ultimate decision-making process in cruise ship design.

Keywords: Cruise behavior, on-board environmental factors, on-board experience, user or customer satisfaction.

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