Search results for: multi-resolution feature fusion

Authors: Xiaoling Dai

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Many Chinese artists have used digital photography to create works with features of Chinese landscape paintings since the 20th century. The ‘New Mountains and Water’ works created by digital techniques reflect the fusion of photographic techniques and traditional Chinese aesthetic thoughts. Borrowing from Chinese landscape paintings in the Song Dynasty, the Chinese photographer Yao Lu uses digital photography to reflect contemporary environmental construction in his series New Landscapes. By portraying a variety of natural environments brought by urbanization in the contemporary period, Lu deconstructs traditional Chinese paintings and reconstructs contemporary photographic practices. The primary object of this study is to investigate how Chinese photographer Yao Lu redefines and re-interprets the relationship between tradition and contemporaneity. In this study, Yao Lu’s series work New Landscapes is used for photo elicitation, which seeks to broaden understanding of the development of Chinese landscape photography. Furthermore, discourse analysis will be used to evaluate how Chinese social developments influence the creation of photographic practices. Through visual and discourse analysis, this study aims to excavate the relationship between tradition and contemporaneity in Lu’s works. According to New Landscapes, the study argues that in Lu’s interpretations of landscapes, tradition and contemporaneity are seen to establish a new relationship. Traditional approaches to creation do not become obsolete over time. On the contrary, traditional notions and styles of creation can shed new light on contemporary issues or techniques.

Keywords: Chinese aesthetics, Yao Lu, new landscapes, tradition, contemporaneity

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Authors: Violetta Parutis

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This qualitative study aims to answer the following research questions: i) What are the factors that students perceive as relevant to a) promoting and b) preventing good grades? ii) How does socio-economic status (SES) feature in those beliefs? We conducted in-depth interviews with 19 first- and second-year undergraduates of varying SES at a research-intensive university in the UK. The interviews yielded eight factors that students perceived as promoting and six perceived as preventing good grades. The findings suggested one significant difference between the beliefs of low and high SES students in that low SES students perceive themselves to be at a greater disadvantage to their peers while high SES students do not have such beliefs. This could have knock-on effects on their performance.

Keywords: social class, education, academic performance, students’ beliefs

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Authors: Ataollah Rabiee1, Amir Hossein Kamalinia, Alireza Atf

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One of the most important issues in the design of nuclear fusion power plants is the heat removal from the hottest region at the diverter. Various methods could be employed in order to improve the heat transfer efficiency, such as generating turbulent flow and injection of nanoparticles in the host fluid. In the current study, Water/AL₂O₃ nanofluid forced swirl flow boiling has been investigated by using a homogeneous thermophysical model within the Eulerian-Eulerian framework through a twisted tape tube, and the boiling phenomenon was modeled using the Rensselaer Polytechnic Institute (RPI) approach. In addition to comparing the results with the experimental data and their reasonable agreement, it was evidenced that higher flow mixing results in more uniform bulk temperature and lower wall temperature along the twisted tape tube. The presence of AL₂O₃ nanoparticles in the boiling flow field showed that increasing the nanoparticle concentration leads to a reduced vapor volume fraction and wall temperature. The Computational fluid dynamics (CFD) results show that the average heat transfer coefficient in the tube increases both by increasing the nanoparticle concentration and the insertion of twisted tape, which significantly affects the thermal field of the boiling flow.

Keywords: nanoparticle, boiling, CFD, two phase flow, alumina, ITER

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Authors: Manoj Deepak, N. Mathivanan, K. Venkatachalam

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Nerve root stenosis is one of the main cause for back pain. There are many methods both conservative and surgical to treat this disease. It is pertinent to decompress the spine to a proper extent so as to avoid the recurrence of symptoms. But too much of an aggressive approach also has its disadvantages. We present one of the methods to effectively decompress the nerve with better results. Our study was carried out in 52 patients with foramina stenosis between 2008 to 2011.We carried out the surgical procedure of shaving off the medial part of the facet joint so as to decompress the root. We selected those patients who had symptoms of claudication for more than 2 years. They had no signs of instability and they underwent conservative treatment for a period of 2 months before the procedure. Oswersty scoring was used to record the functional level of the patient before and after the procedure. All patients were followed up for a period of minimum 2.5 years. After evaluation for a minimum of 2.5 years, 34 patients had no evidence of recurrence of symptoms with improvement in the functional level.7 patients complained of minimal pain but their functional quality had improved postop. Six patients had symptoms of lumbar canal disease which reduced with conservative treatment. 5 patients required spinal fusion surgeries in the later period. Conclusion: Thus, we can effectively conclude that our procedure is safe and effective in reducing the symptoms in those patients with neurogenic claudication.

Keywords: facetectoemy, stenosis, decompression, Lumbar Foraminal Stenosis, hemi-facetectomy

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Authors: Mayar Almasri, Rosa Helmi, Rayana Enany

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This report describes the features of AutoCAD software released by Adobe. It explains how the program makes it easier for engineers and designers and reduces their time and effort spent using AutoCAD. Moreover, it highlights how AutoCAD works, how some of the commands used in it, such as Shortcut, make it easy to use, and features that make it accurate in measurements. The results of the report show that most users of this program are designers and engineers, but few people know about it and find it easy to use. They prefer to use it because it is easy to use, and the shortcut commands shorten a lot of time for them. The feature got a high rate and some suggestions for improving AutoCAD in Aperture, but it was a small percentage, and the highest percentage was that they didn't need to improve the program, and it was good.

Keywords: artificial intelligence, design, planning, commands, autodesk, dimensions

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Authors: Golnush Masghati-Amoli, Paul Chin

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Over the past recent years, with the rapid increases in data availability and computing power, Machine Learning (ML) techniques have been called on in a range of different industries for their strong predictive capability. However, the use of Machine Learning in commercial banking has been limited due to a special challenge imposed by numerous regulations that require lenders to be able to explain their analytic models, not only to regulators but often to consumers. In other words, although Machine Leaning techniques enable better prediction with a higher level of accuracy, in comparison with other industries, they are adopted less frequently in commercial banking especially for scoring purposes. This is due to the fact that Machine Learning techniques are often considered as a black box and fail to provide information on why a certain risk score is given to a customer. In order to bridge this gap between the explain-ability and performance of Machine Learning techniques, a Hybrid Model is developed at Dun and Bradstreet that is focused on blending Machine Learning algorithms with traditional approaches such as scorecards. The Hybrid Model maximizes efficiency of traditional scorecards by merging its practical benefits, such as explain-ability and the ability to input domain knowledge, with the deep insights of Machine Learning techniques which can uncover patterns scorecard approaches cannot. First, through development of Machine Learning models, engineered features and latent variables and feature interactions that demonstrate high information value in the prediction of customer risk are identified. Then, these features are employed to introduce observed non-linear relationships between the explanatory and dependent variables into traditional scorecards. Moreover, instead of directly computing the Weight of Evidence (WoE) from good and bad data points, the Hybrid Model tries to match the score distribution generated by a Machine Learning algorithm, which ends up providing an estimate of the WoE for each bin. This capability helps to build powerful scorecards with sparse cases that cannot be achieved with traditional approaches. The proposed Hybrid Model is tested on different portfolios where a significant gap is observed between the performance of traditional scorecards and Machine Learning models. The result of analysis shows that Hybrid Model can improve the performance of traditional scorecards by introducing non-linear relationships between explanatory and target variables from Machine Learning models into traditional scorecards. Also, it is observed that in some scenarios the Hybrid Model can be almost as predictive as the Machine Learning techniques while being as transparent as traditional scorecards. Therefore, it is concluded that, with the use of Hybrid Model, Machine Learning algorithms can be used in the commercial banking industry without being concerned with difficulties in explaining the models for regulatory purposes.

Keywords: machine learning algorithms, scorecard, commercial banking, consumer risk, feature engineering

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Authors: Norbert Csizmadia

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The paper is based on a thorough investigation regarding the recent global, social and geographical processes. The ‘Geofusion’ book series by the author guides the readers with the help of newly illustrated “associative” geographic maps of the global world in the 21st century through the quest for the winning nations, communities, leaders and powers of this age. Hence, the above mentioned represent the research objectives, the preliminary findings of which are presented in this paper. The most significant recognition is that scientists who are recognized as explorers, geostrategists of this century, in this case, are expected to present guidelines for our new world full of global social and economic challenges. To do so, new maps are needed which do not miss the wisdom and tools of the old but complement them with the new structure of knowledge. Using the lately discovered geographic and economic interrelations, the study behind this presentation tries to give a prognosis of the global processes. The methodology applied contains the survey and analysis of many recent publications worldwide regarding geostrategic, cultural, geographical, social, and economic surveys structured into global networks. In conclusion, the author presents the result of the study, which is a collage of the global map of the 21st century as mentioned above, and it can be considered as a potential contribution to the recent scientific literature on the topic. In summary, this paper displays the results of several-year-long research giving the audience an image of how economic navigation tools can help investors, politicians and travelers to get along in the changing new world.

Keywords: geography, economic geography, geo-fusion, geostrategy

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Authors: Shubham Jaiswal

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In the present article, a drive is taken to compute the solution of spatial fractional order advection-dispersion equation having source/sink term with given initial and boundary conditions. The equation is converted to a system of ordinary differential equations using second-kind shifted Chebyshev polynomials, which have finally been solved using finite difference method. The striking feature of the article is the fast transportation of solute concentration as and when the system approaches fractional order from standard order for specified values of the parameters of the system.

Keywords: spatial fractional order advection-dispersion equation, second-kind shifted Chebyshev polynomial, collocation method, conservative system, non-conservative system

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Authors: S. Tehsin, S. Kausar

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The ultimate aim of machine intelligence is to explore and materialize the human capabilities, one of which is the ability to detect various text objects within one or more images displayed on any canvas including prints, videos or electronic displays. Multimedia data has increased rapidly in past years. Textual information present in multimedia contains important information about the image/video content. However, it needs to technologically testify the commonly used human intelligence of detecting and differentiating the text within an image, for computers. Hence in this paper feature set based on anatomical study of human text detection system is proposed. Subsequent examination bears testimony to the fact that the features extracted proved instrumental to text detection.

Keywords: biologically inspired vision, content based retrieval, document analysis, text extraction

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Authors: Mohamed El Morsy, Gabriela Achtenová

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Condition monitoring is used to increase machinery availability and machinery performance, whilst reducing consequential damage, increasing machine life, reducing spare parts inventories, and reducing breakdown maintenance. An efficient condition monitoring system provides early warning of faults by predicting them at an early stage. When a localized fault occurs in gears, the vibration signals always exhibit non-stationary behavior. The periodic impulsive feature of the vibration signal appears in the time domain and the corresponding gear mesh frequency (GMF) emerges in the frequency domain. However, one limitation of frequency-domain analysis is its inability to handle non-stationary waveform signals, which are very common when machinery faults occur. Particularly at the early stage of gear failure, the GMF contains very little energy and is often overwhelmed by noise and higher-level macro-structural vibrations. An effective signal processing method would be necessary to remove such corrupting noise and interference. In this paper, a new hybrid method based on optimal Morlet wavelet filter and autocorrelation enhancement is presented. First, to eliminate the frequency associated with interferential vibrations, the vibration signal is filtered with a band-pass filter determined by a Morlet wavelet whose parameters are selected or optimized based on maximum Kurtosis. Then, to further reduce the residual in-band noise and highlight the periodic impulsive feature, an autocorrelation enhancement algorithm is applied to the filtered signal. The test stand is equipped with three dynamometers; the input dynamometer serves as the internal combustion engine, the output dynamometers induce a load on the output joint shaft flanges. The pitting defect is manufactured on the tooth side of a gear of the fifth speed on the secondary shaft. The gearbox used for experimental measurements is of the type most commonly used in modern small to mid-sized passenger cars with transversely mounted powertrain and front wheel drive: a five-speed gearbox with final drive gear and front wheel differential. The results obtained from practical experiments prove that the proposed method is very effective for gear fault diagnosis.

Keywords: wavelet analysis, pitted gear, autocorrelation, gear fault diagnosis

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Authors: Nikki A. Barla, P. K. Ghosh, Sourav Das

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Two different groove sizes 13.6 mm (narrow groove) and 7.5 mm (ultra-narrow groove) of 304 LN austenitic stainless steel (ASS) plate was welded using pulse gas metal arc welding (P-GMAW). These grooves were welded using multi-pass single seam per layer (MSPPL) deposition technique with full assurance of groove wall fusion. During bead on plate deposition process, the thermal cycle was recorded using strain buster (temperature measuring device). Both the groove has heat affected Zone (HAZ) width of 1-2 mm. After welding, the microstructure studies was done which revealed that there was higher sensitization (Chromium carbide formation in grain boundary) in the HAZ of 13.6 mm groove weldment as compared to the HAZ of 7.5 mm weldment. Electrochemical potentiokinetic reactivation test (EPR) was done in 0.5 N H₂SO₄ + 1 M KSCN solution to study the degree of sensitization (DOS) and it was observed that 7.5 mm groove HAZ has lower DOS. Mass deposition in the 13.6 mm weld is higher than 7.5mm groove weld, which naturally induces higher residual stress in 13.6 mm weld. Comparison between microstructural studies and corrosion test summarized that the residual stress affects the sensitization property of welded ASS.

Keywords: austenitic stainless steel (ASS), electrochemical potentiokinetic reactivation test (EPR), microstructure, pulse gas metal arc welding (P-GMAW), sensitization

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Authors: Shaik Ayesha Fathima, Shaik Noor Jahan, Duvvada Rajeswara Rao

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Earth's environment and its evolution can be seen through satellite images in near real-time. Through satellite imagery, remote sensing data provide crucial information that can be used for a variety of applications, including image fusion, change detection, land cover classification, agriculture, mining, disaster mitigation, and monitoring climate change. The objective of this project is to propose a method for classifying satellite images according to multiple predefined land cover classes. The proposed approach involves collecting data in image format. The data is then pre-processed using data pre-processing techniques. The processed data is fed into the proposed algorithm and the obtained result is analyzed. Some of the algorithms used in satellite imagery classification are U-Net, Random Forest, Deep Labv3, CNN, ANN, Resnet etc. In this project, we are using the DeepLabv3 (Atrous convolution) algorithm for land cover classification. The dataset used is the deep globe land cover classification dataset. DeepLabv3 is a semantic segmentation system that uses atrous convolution to capture multi-scale context by adopting multiple atrous rates in cascade or in parallel to determine the scale of segments.

Keywords: area calculation, atrous convolution, deep globe land cover classification, deepLabv3, land cover classification, resnet 50

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Authors: Isa Moazen, Ali Nahvi

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Driver drowsiness is a major cause of vehicle accidents, and facial images are highly valuable to detect drowsiness. In this paper, we perform our research via a thermal camera to record drivers' facial images on a driving simulator. A robust real-time algorithm extracts the features using horizontal and vertical integration projection, contours, contour orientations, and cropping tools. The features are included four target areas on the cheeks and forehead. Qt compiler and OpenCV are used with two cameras with different resolutions. A high-resolution thermal camera is used for fifteen subjects, and a low-resolution one is used for a person. The results are investigated by four temperature plots and evaluated by observer rating of drowsiness.

Keywords: advanced driver assistance systems, thermal imaging, driver drowsiness detection, feature extraction

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Authors: Supriya H. S., Chandrakala B. M.

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Deep learning based models have been recently successful adoption for network traffic prediction. However, training a deep learning model for various prediction tasks is considered one of the critical tasks due to various reasons. This research work develops Multi-Layer Hybrid Network (MLHN) for network traffic prediction and analysis; MLHN comprises the three distinctive networks for handling the different inputs for custom feature extraction. Furthermore, an optimized and efficient parameter-tuning algorithm is introduced to enhance parameter learning. MLHN is evaluated considering the “Big Data Challenge” dataset considering the Mean Absolute Error, Root Mean Square Error and R^2as metrics; furthermore, MLHN efficiency is proved through comparison with a state-of-art approach.

Keywords: MLHN, network traffic prediction

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Authors: Bilal Arshad, Johan Barthelemy, Elliott Pilton, Pascal Perez

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Getting reliable, informative, and up-to-date information about the location, mobility, and behavioural patterns of animals will enhance our ability to research and preserve biodiversity. The fusion of infra-red sensors and camera traps offers an inexpensive way to collect wildlife data in the form of images. However, extracting useful data from these images, such as the identification and counting of animals remains a manual, time-consuming, and costly process. In this paper, we demonstrate that such information can be automatically retrieved by using state-of-the-art deep learning methods. Another major challenge that ecologists are facing is the recounting of one single animal multiple times due to that animal reappearing in other images taken by the same or other camera traps. Nonetheless, such information can be extremely useful for tracking wildlife and understanding its behaviour. To tackle the multiple count problem, we have designed a meshed network of camera traps, so they can share the captured images along with timestamps, cumulative counts, and dimensions of the animal. The proposed method takes leverage of edge computing to support real-time tracking and monitoring of wildlife. This method has been validated in the field and can be easily extended to other applications focusing on wildlife monitoring and management, where the traditional way of monitoring is expensive and time-consuming.

Keywords: computer vision, ecology, internet of things, invasive species management, wildlife management

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Authors: Yingkun Huang, Li Guo, Zekang Lan, Kai Tian

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Hard disk drives (HDD) failure of the exascale supercomputing system may lead to service interruption and invalidate previous calculations, and it will cause permanent data loss. Therefore, initiating corrective actions before hard drive failures materialize is critical to the continued operation of jobs. In this paper, a highly accurate analysis model based on CNN-LSTM and oversampling technique was proposed, which can correctly predict the necessity of a disk replacement even ten days in advance. Generally, the learning-based method performs poorly on a training dataset with long-tail distribution, especially fault prediction is a very classic situation as the scarcity of failure data. To overcome the puzzle, a new oversampling was employed to augment the data, and then, an improved CNN-LSTM with the shortcut was built to learn more effective features. The shortcut transmits the results of the previous layer of CNN and is used as the input of the LSTM model after weighted fusion with the output of the next layer. Finally, a detailed, empirical comparison of 6 prediction methods is presented and discussed on a public dataset for evaluation. The experiments indicate that the proposed method predicts disk failure with 0.91 Precision, 0.91 Recall, 0.91 F-measure, and 0.90 MCC for 10 days prediction horizon. Thus, the proposed algorithm is an efficient algorithm for predicting HDD failure in supercomputing.

Keywords: HDD replacement, failure, CNN-LSTM, oversampling, prediction

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Authors: Anastasia Stamatiou, Melissa Obermeyer, Ludger J. Fischer, Philipp Schuetz, Jörg Worlitschek

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This study evaluates unbranched, saturated carboxylic esters with respect to their suitability to be used as storage media for latent heat storage applications. Important thermophysical properties are gathered both by means of literature research as well as by experimental measurements. Additionally, esters are critically evaluated against other common phase-change materials in terms of their environmental impact and their economic potential. The experimental investigations are performed for eleven selected ester samples with a focus on the determination of their melting temperature and their enthalpy of fusion using differential scanning calorimetry. Transient Hot Bridge was used to determine the thermal conductivity of the liquid samples while thermogravimetric analysis was employed for the evaluation of the 5% weight loss temperature as well as of the decomposition temperature of the non-volatile samples. Both experimental results and literature data reveal the high potential of esters as phase-change materials. Their good thermal and environmental properties as well as the possibility for production from natural sources (e.g. vegetable oils) render esters as very promising for future storage applications. A particularly high short term application potential of esters could lie in low temperature storage applications where the main alternative is using salt hydrates as phase-change material.

Keywords: esters, phase-change materials, thermal properties, latent heat storage

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Authors: Angelo Thurairajah

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Sufficient ultimate deformation is necessary to demonstrate the member ductility, which is dependent on the section and the material ductility. The concrete cracking phase of softening prior to the plastic hinge formation is an essential feature as well. The nature of the overload behaviour is studied using the order of the ultimate deflection. The ultimate deflection is primarily dependent on the slenderness (span to depth ratio), the ductility of the reinforcing steel, the degree of moment redistribution, the type of loading, and the support conditions. The ultimate deflection and the degree of moment redistribution from the analytical study are in good agreement with the experimental results and the moment redistribution provisions of the Australian Standards AS3600 Concrete Structures Code.

Keywords: ductility, softening, ultimate deflection, overload behaviour, moment redistribution

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Authors: Meltem Bolluk, Ismail Duman

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Boron exhibits the properties of high melting temperature (2273K to 2573 K), high hardness (Mohs: 9,5), low density (2,340 g/cm3), high chemical resistance, high strength, and semiconductivity (band gap:1,6-2,1 eV). These superior properties enable to use it in several high-tech areas from electronics to nuclear industry and especially in high temperature metallurgy. Amorphous boron and crystalline boron have different application areas. Amorphous boron powder (directly amorphous and/or α-rhombohedral) is preferred in rocket firing, airbag inflating and in fabrication of superconducting MgB2 wires. The conventional ways to produce elemental boron with a purity of 85 pct to 95 prc are metallothermic reduction, fused salt electrolysis and mechanochemical synthesis; but the only way to produce high-purity boron powders is Chemical Vapour Deposition (Hot Surface CVD). In this study; amorphous boron powders with a minimum purity of 99,9 prc were synthesized in quartz tubes using BCl3-H2 gas mixture by CVD. Process conditions based on temperature and gas flow rate were determined. Thermodynamical interpretation of BCl3-H2 system for different temperatures and molar rates were performed using Fact Sage software. The characterization of powders was examined by using Xray diffraction (XRD), Scanning Electron Microscope (SEM) and Transmission Electron Microscope (TEM), Stereo Microscope (SM), Helium gas pycnometer analysis. The purities of final products were determined by titration after lime fusion.

Keywords: amorphous boron, CVD, powder production, powder characterization

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Authors: Luyao Liu, Dekui Yuan, Xu Li

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As one of the most important bays of China, the water exchange capacity of Bohai Bay can influence the economic development and urbanization of surrounding cities. However, the rapid reclamation has influenced the weak water exchange capacity of this semi-enclosed bay in recent years. This paper sets two hydrodynamic models of Bohai Bay with two shorelines before and after reclamation. The mean value and distribution of Turn-over Time, the distribution of residual current, and the feature of the tracer path are compared. After comparison, it is found that Bohai Bay keeps these characteristics; the spending time of water exchange in the northern is longer than southern, and inshore is longer than offshore. However, the mean water exchange time becomes longer after reclamation. In addition, the material spreading is blocked because of the inwardly extending shorelines, and the direction changed from along the shoreline to towards the center after reclamation.

Keywords: Bohai Bay, water exchange, reclamation, turn-over time

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Authors: Yusra Yahya

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In this paper, a new spell-out mechanism is developed and defended. This mechanism builds on the role of phase heads as both the loci of spell-out features and the transfer triggers via either Phase Impenetrability Condition 1 (PIC1) and/or Phase Impenetrability Condition 2 (PIC2). The assumption here is that phase heads, mainly v*, can regulate the spell-out process by deciding both the type of spell-out applying and the timing of spell-out relevant. This paper also proposes a new form of the constraint Wrap call it Wrap-XP’ and it is assumed to apply to IP as a functional maximal projection. This extension is shown to fall as a natural result once we assume the new theory of phases and multiple spell-out. Moreover, it is proposed in this work that some forms of XP movement are not motivated by an EPP feature of a strong phase head mainly v*, but they are rather motivated by a last resort strategy to accomplish the spell-out instruction of this phase head.

Keywords: linguistics, syntax, phonology, phase theory, optimality theory

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Authors: Jalel Khelil

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In order to improve reliability of Gas Turbine machine especially its generator equipment, a fault diagnosis system based on fuzzy approach is proposed. Three various methods namely K-NN (K-nearest neighbors), F-KNN (Fuzzy K-nearest neighbors) and FNM (Fuzzy nearest mean) are adopted to provide the measurement of relative strength of vibration defaults. Both applications consist of two major steps: Feature extraction and default classification. 09 statistical features are extracted from vibration signals. 03 different classes are used in this study which describes vibrations condition: Normal, unbalance defect, and misalignment defect. The use of the fuzzy approaches and the classification results are discussed. Results show that these approaches yield high successful rates of vibration default classification.

Keywords: fault diagnosis, fuzzy classification k-nearest neighbor, vibration

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Authors: Shih-Chieh Liao, Cheng-Yan Shuai

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The feature of a side-scrolling shooting game is facing the surrounding enemy and barraging in entire screen. The player will be in trouble when they are trying to do complicated operations because of the physical and system limitations of the joystick in the games. This study designed the prototype of a new type of arcade stick by focus group and assessed by the expert. By filtering the most representative, and build up the control system for the arcade stick, and testing time and bullets consumed in two experiments, try to prove it works in the game. Finally, the prototype of L-1 solves the dilemma of scroll shooting games when the player uses the arcade stick and improves the function of the arcade stick.

Keywords: arcade stick, joystick, user interface, 2D STG

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Authors: Waranya Imprasittichai, Patsarawadee Paojinda, Sudaratana R. Krungkrai, Nirianne Marie Q. Palacpac, Toshihiro Horii, Jerapan Krungkrai

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Fusion of the last two enzymes in the pyrimidine biosynthetic pathway in the inversed order by having COOH-terminal orotate phosphoribosyltransferase (OPRT) and NH2-terminal orotidine 5'-monophosphate decarboxylase (OMPDC), as OMPDC-OPRT, are described in many organisms. In this study, we constructed gene fusions of Plasmodium falciparum OMPDC-OPRT (1,836 bp) in pTrcHisA vector and expressed as an 6xHis-tag bifunctional protein in three Escherichia coli strains (BL21, Rosetta, TOP10) at 18 °C, 25 °C and 37 °C. The recombinant bifunctional protein was partially purified by Ni-Nitrilotriacetic acid-affinity chromatography. Specific activities of OPRT and OMPDC domains in the bifunctional enzyme expressed in E. coli TOP10 cells were approximately 3-4-fold higher than those in BL21 cells. There were no enzymatic activities when the construct vector expressed in Rosetta cells. Maximal expression of the fused gene was observed at 18 °C and the bifunctional enzyme had specific activities of OPRT and OMPDC domains in a ratio of 1:2. These results provide greater yields and better catalytic activities of the bifunctional OMPDC-OPRT enzyme for further purification and kinetic study.

Keywords: bifunctional enzyme, orotate phosphoribosyltransferase, orotidine 5'-monophosphate decarboxylase, plasmodium falciparum

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Authors: A. M. T. Jacinto, M.O. Osi

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Tamarind has various medicinal properties among which is its antibacterial property. Its bark contains saponins, alkaloids, sesquiterpenes and tannins. It is rich in phlobapenes which is responsible for antibacterial property. The objective of the study was to determine which bark will produce the highest antibacterial property, develop it into a topical cream and evaluate its quality and characteristics. Powdered barks of Tamarind were extracted by soxhlet method using 70% acetone. Stem bark produced a higher yield than trunk bark (5.85 g vs. 4.73 g). It was found that the trunk bark was more sensitive than stem bark to microorganisms namely Staphylococcus aureus, Corynebacterium minutissimum, and Streptococcus spp. Sensitivity of trunk bark can be attributed to a more developed phytoconstituents. Dermal sensitization test on both sexes of rabbits using the following concentrations: 100%, 40% and 20% of extract showed that Tamarind has no irritating property and therefore safe for formulation into an antibacterial cream. Excipients used for formulation such as methyl paraben, propyl paraben, stearyl alcohol and white petrolatum were compatible with the Tamarind acetone extract through Differential Scanning Calorimetry except sodium lauryl sulfate that exhibited crystallization when subjected at 200˚C. The method of manufacture used in cream is fusion, therefore strict compliance of processing temperature should be observed to prevent polymorphism. Quality control tests of formulated cream based on USP 30 and Philippine Pharmacopeia were satisfactory.

Keywords: antibacterial, differential scanning calorimetry, tannins, dermal sensitization

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Authors: M.R Asghari Bejestani, Gh. R. Mohammad Khani, V.R. Nafisi

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Imagined speech recognition is one of the most interesting approaches to BCI development and a lot of works have been done in this area. Many different experiments have been designed and hundreds of combinations of feature extraction methods and classifiers have been examined. Reported classification accuracies range from the chance level to more than 90%. Based on non-stationary nature of brain signals, we have introduced 3 classification modes according to time difference in inter and intra-class samples. The modes can explain the diversity of reported results and predict the range of expected classification accuracies from the brain signal accusation procedure. In this paper, a few samples are illustrated by inspecting results of some previous works.

Keywords: brain computer interface, silent talk, imagined speech, classification, signal processing

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Authors: Farouk Lawan Gambo, Hamada Mohammad

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Data compression shrinks files into fewer bits than their original presentation. It has more advantage on the internet because the smaller a file, the faster it can be transferred but learning most of the concepts in data compression are abstract in nature, therefore, making them difficult to digest by some students (engineers in particular). This paper studies the learning preference of engineering students who tend to have strong, active, sensing, visual and sequential learning preferences, the paper also studies the three shift of technology-aided that learning has experienced, which mobile learning has been considered to be the feature of learning that will integrate other form of the education process. Lastly, we propose a design and implementation of mobile learning application using software engineering methodology that will enhance the traditional teaching and learning of data compression techniques.

Keywords: data compression, learning preference, mobile learning, multimedia

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Authors: Hoda Ghavamipoor, S. Alireza Hashemi Golpayegani

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An approach to model the customer interaction with e-commerce websites is presented. Considering the service quality level as a predictive feature, we offer an improved method based on the Customer Behavior Model Graph (CBMG), a state-transition graph model. To derive the Quality of Service sensitive-CBMG (QoS-CBMG) model, process-mining techniques is applied to pre-processed website server logs which are categorized as ‘buy’ or ‘visit’. Experimental results on an e-commerce website data confirmed that the proposed method outperforms CBMG based method.

Keywords: customer behavior model, electronic commerce, quality of service, customer behavior model graph, process mining

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Authors: Eman A. Al-Hilo, Hawraa H. Al-Waelly

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In this work, fractal compression (FIC) technique is introduced based on using moment features to block indexing the zero-mean range-domain blocks. The moment features have been used to speed up the IFS-matching stage. Its moments ratio descriptor is used to filter the domain blocks and keep only the blocks that are suitable to be IFS matched with tested range block. The results of tests conducted on Lena picture and Cat picture (256 pixels, resolution 24 bits/pixel) image showed a minimum encoding time (0.89 sec for Lena image and 0.78 of Cat image) with appropriate PSNR (30.01dB for Lena image and 29.8 of Cat image). The reduction in ET is about 12% for Lena and 67% for Cat image.

Keywords: fractal gray level image, fractal compression technique, iterated function system, moments feature, zero-mean range-domain block

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Authors: Jing Hu, Xiaoping Ouyang

Abstract:

We develop an optical readout gas chamber based on avalanche-induced scintillation for energetic charged particles track. The gas chamber is equipped with a Single Anode Wires (SAW) structure to produce intensive electric field when the measured particles are of low yield or even single. In the presence of an intensive electric field around the single anode, primary electrons, resulting from the incident charged particles when depositing the energy along the track, accelerate to the anode effectively and rapidly. For scintillation gasses, this avalanche of electrons induces multiplying photons comparing with the primary scintillation excited directly from particle energy loss. The electric field distribution for different shape of the SAW structure is analyzed, and finally, an optimal one is used to study the optical readout performance. Using CF4 gas and its mixture with the noble gas, the results indicate that the optical readout characteristics of the chamber are attractive for imaging. Moreover, images of particles track including single particle track from 5.485MeV alpha particles are successfully acquired. The track resolution is quite well for the reason that the electrons undergo less diffusion in the intensive electric field. With the simple and ingenious design, the optical readout gas chamber has a high sensitivity. Since neutrons can be converted to charged particles when scattering, this optical readout gas chamber can be applied to neutron measurement for dark matter, fusion research, and others.

Keywords: optical readout, gas chamber, charged particle track, avalanche-induced scintillation, neutron measurement

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