Search results for: Integration Testing Techniques

Authors: Sara Jelodarian

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Organic agriculture is a kind of living and dynamic agriculture that was introduced in the early 20^th century. The fundamental basis for organic agriculture is in harmony with nature. This version of farming emphasizes removing growth hormones, chemical fertilizers, toxins, radiation, genetic manipulation and instead, integration of modern scientific techniques (such as biologic and microbial control) that leads to the production of healthy food and the preservation of the environment and use of agricultural products such as forage and manure. Supports from governments for the markets producing organic products and taking advantage of the experiences from other successful societies in this field can help progress the positive and effective aspects of this technology, especially in developing countries. This research proves that till 2030, 25% of the global agricultural lands would be covered by organic farming. Consequently Iran, due to its rich genetic resources and various climates, can be a pioneer in promoting organic products. In addition, for sustainable farming, blend of organic and other innovative systems is needed. Important limitations exist to accept these systems, also a diversity of policy instruments will be required to comfort their development and implementation. The paper was conducted to results of compilation of reports, issues, books, articles related to the subject with library studies and research. Likewise we combined experimental and survey to get data.

Keywords: Development, production markets, progress, strategic role, technology.

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Authors: Pradyumna Kumar Sahoo, Prasanta Kumar Satpathy

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This paper aims at finding a suitable neural network for monitoring congestion level in electrical power systems. In this paper, the input data has been framed properly to meet the target objective through supervised learning mechanism by defining normal and abnormal operating conditions for the system under study. The congestion level, expressed as line congestion index (LCI), is evaluated for each operating condition and is presented to the NN along with the bus voltages to represent the input and target data. Once, the training goes successful, the NN learns how to deal with a set of newly presented data through validation and testing mechanism. The crux of the results presented in this paper rests on performance comparison of a multi-layered feed forward neural network with eleven types of back propagation techniques so as to evolve the best training criteria. The proposed methodology has been tested on the standard IEEE-14 bus test system with the support of MATLAB based NN toolbox. The results presented in this paper signify that the Levenberg-Marquardt backpropagation algorithm gives best training performance of all the eleven cases considered in this paper, thus validating the proposed methodology.

Keywords: Line congestion index, critical bus, contingency, neural network.

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Authors: Venkata Reddy Kota

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These days, the industrial trend is moving away from heavy and bulky passive components to power converter systems that use more and more semiconductor elements. Also, it is difficult to connect the traditional converters to the high and medium voltage. For these reasons, a new family of multilevel inverters has appeared as a solution for working with higher voltage levels. Different modulation topologies like Sinusoidal Pulse Width Modulation (SPWM), Selective Harmonic Elimination Pulse Width Modulation (SHE-PWM) are available for multilevel inverters. In this work, different hybrid modulation techniques which are combination of fundamental frequency modulation and multilevel sinusoidal-modulation are compared. The main characteristic of these modulations are reduction of switching losses with good harmonic performance and balanced power loss dissipation among the device. The proposed hybrid modulation schemes are developed and simulated in Matlab/Simulink for cascaded H-bridge inverter. The results validate the applicability of the proposed schemes for cascaded multilevel inverter.

Keywords: Hybrid PWM techniques, Cascaded Multilevel Inverters, Switching loss minimization.

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Authors: Darmawan Napitupulu, Dana Indra Sensuse, Aniati Murni

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The research was conducted to empirically validate the proposed maturity model of e-Government implementation, composed of four dimensions, further specified by 54 success factors as attributes. To do so, there are two steps were performed. First, expert’s judgment was conducted to test its content validity. The second, reliability study was performed to evaluate inter-rater agreement by using Fleiss Kappa approach. The kappa statistic (kappa coefficient) is the most commonly used method for testing the consistency among raters. Fleiss Kappa was a generalization of Kappa in extensions to the case of more than two raters (multiple raters) with multi-categorical ratings. Our findings show that most attributes of the proposed model were related to their corresponding dimensions. According to our results, The percentage of agree answers given by the experts was 73.69% in dimension A, 89.76% in B, 81.5% in C and 60.37% in D. This means that more than half of the attributes of each dimensions were appropriate or relevant to the dimensions they were supposed to measure, while 85% of attributes were relevant enough to their corresponding dimensions. Inter-rater reliability coefficient also showed satisfactory result and interpreted as substantial agreement among raters. Therefore, the proposed model in this paper was valid and reliable to measure the maturity of e-Government implementation.

Keywords: E-Government, Model, Maturity, Validity, Reliability Kappa.

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Authors: Mohammad I. Hossain, Omar F. Hamim

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This paper presents a case study on a pile integrity test for assessing the integrity of piles as well as a physical dimension (e.g., cross-sectional area, length), continuity, and consistency of the pile materials. The recent boom in the socio-economic condition of Bangladesh has given rise to the building of high-rise commercial and residential infrastructures. The advantage of the pile integrity test lies in the fact that it is possible to get an approximate indication regarding the quality of the sub-structure before commencing the construction of the super-structure. This paper aims at providing a classification of cast-in-situ piles based on characteristic reflectograms obtained using the Sonic Integrity Testing program for the sub-soil condition of Narayanganj, Bangladesh. The piles have been classified as 'Pile Type-1', 'Pile Type-2', 'Pile Type-3', 'Pile type-4', 'Pile Type-5' or 'Pile Type-6' from the visual observations of reflections from the generated stress waves by striking the pile head with a handheld hammer. With respect to construction quality and integrity, piles have been further classified into three distinct categories, i.e., satisfactory, may be satisfactory, and unsatisfactory.

Keywords: Cast-in-situ piles, characteristic reflectograms, pile integrity test, sonic integrity testing program.

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Authors: N. Matveev, A. Pervov

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Local utilities often face problems of local industrial wastes, storm water disposal due to existing strict regulations. For many local industries, the problem of wastewater treatment and discharge into surface reservoirs can’t be solved through the use of conventional biological treatment techniques. Current discharge standards require very strict removal of a number of impurities such as ammonia, nitrates, phosphate, etc. To reach this level of removal, expensive reagents and sorbents are used. The modern concept of rational water resources management requires the development of new efficient techniques that provide wastewater treatment and reuse. As RO membranes simultaneously reject all dissolved impurities such as BOD, TDS, ammonia, phosphates etc., they become very attractive for the direct treatment of wastewater without biological stage. To treat wastewater, specially designed membrane "open channel" modules are used that do not possess "dead areas" that cause fouling or require pretreatment. A solution to RO concentrate disposal problem is presented that consists of reducing of initial wastewater volume by 100 times. Concentrate is withdrawn from membrane unit as sludge moisture. The efficient use of membrane RO techniques is connected with a salt balance in water system. Thus, to provide high ecological efficiency of developed techniques, all components of water supply and wastewater discharge systems should be accounted for.

Keywords: Reverse osmosis, stormwater treatment, openchannel module, wastewater reuse.

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Authors: H. J. Yang, R. Z. Jin, I. J. Park, C. T. Hyun

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There has been gradual progress of late in construction projects, particularly in big-scale megaprojects. Due to the long-term construction period, however, with large-scale budget investment, lack of construction management technologies, and increase in the incomplete elements of project schedule management, a plan to conduct efficient operations and to ensure business safety is required. In particular, as the project management information system (PMIS) is meant for managing a single project centering on the construction phase, there is a limitation in the management of program-scale businesses like megaprojects. Thus, a program management information system (PgMIS) that includes program-level management technologies is needed to manage multiple projects. In this study, a support tool was developed for managing the cost and schedule information occurring in the construction phase, at the program level. In addition, a case study on the developed support tool was conducted to verify the usability of the system. With the use of the developed support tool program, construction managers can monitor the progress of the entire project and of the individual subprojects in real time.

Keywords: Cost∙Schedule integration management, Supporting Tool, UI, WBS, CBS, introduce PgMIS (Program Management Information System), PMIS (Project Management Information System)

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Authors: Mohd Tarmizi Ali, Mohd Khairul Mohd Salleh, Md. Mahfudz Md. Zan

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Dielectric sheet perturbation to the dominant TE111 mode resonant frequency of a circular cavity is studied and presented in this paper. The dielectric sheet, placed at the middle of the airfilled cavity, introduces discontinuities and disturbs the configuration of electromagnetic fields in the cavity. For fixed dimensions of cavity and fixed thickness of the loading dielectric, the dominant resonant frequency varies quite linearly with the permittivity of the dielectric. This quasi-linear relationship is plotted using Maple software and verified using 3D electromagnetic simulations. Two probes are used in the simulation for wave excitation into and from the cavity. The best length of probe is found to be 3 mm, giving the closest resonant frequency to the one calculated using Maple. A total of fourteen different dielectrics of permittivity ranging from 1 to 12.9 are tested one by one in the simulation. The works show very close agreement between the results from Maple and the simulation. A constant difference of 0.04 GHz is found between the resonant frequencies collected during simulation and the ones from Maple. The success of this project may lead to the possibility of using the middle loaded cavity at TE111 mode as a microwave non-destructive testing of solid materials.

Keywords: Middle-loaded cavity, dielectric sheet perturbation.

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Authors: Luay A. Fraiwan, Natheer Y. Khaswaneh, Khaldon Y. Lweesy

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Sleep stage scoring is the process of classifying the stage of the sleep in which the subject is in. Sleep is classified into two states based on the constellation of physiological parameters. The two states are the non-rapid eye movement (NREM) and the rapid eye movement (REM). The NREM sleep is also classified into four stages (1-4). These states and the state wakefulness are distinguished from each other based on the brain activity. In this work, a classification method for automated sleep stage scoring based on a single EEG recording using wavelet packet decomposition was implemented. Thirty two ploysomnographic recording from the MIT-BIH database were used for training and validation of the proposed method. A single EEG recording was extracted and smoothed using Savitzky-Golay filter. Wavelet packets decomposition up to the fourth level based on 20th order Daubechies filter was used to extract features from the EEG signal. A features vector of 54 features was formed. It was reduced to a size of 25 using the gain ratio method and fed into a classifier of regression trees. The regression trees were trained using 67% of the records available. The records for training were selected based on cross validation of the records. The remaining of the records was used for testing the classifier. The overall correct rate of the proposed method was found to be around 75%, which is acceptable compared to the techniques in the literature.

Keywords: Features selection, regression trees, sleep stagescoring, wavelet packets.

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Authors: M. Satya Sai Ram, P. Siddaiah, M. Madhavi Latha

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Vector quantization is a powerful tool for speech coding applications. This paper deals with LPC Coding of speech signals which uses a new technique called Multi Switched Split Vector Quantization (MSSVQ), which is a hybrid of Multi, switched, split vector quantization techniques. The spectral distortion performance, computational complexity, and memory requirements of MSSVQ are compared to split vector quantization (SVQ), multi stage vector quantization(MSVQ) and switched split vector quantization (SSVQ) techniques. It has been proved from results that MSSVQ has better spectral distortion performance, lower computational complexity and lower memory requirements when compared to all the above mentioned product code vector quantization techniques. Computational complexity is measured in floating point operations (flops), and memory requirements is measured in (floats).

Keywords: Linear predictive Coding, Multi stage vectorquantization, Switched Split vector quantization, Split vectorquantization, Line Spectral Frequencies (LSF).

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Authors: Rajesh Kumar, Puneet Aggarwal

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In context of understanding problems faced by undergraduate students while carrying out laboratory experiments dealing with high voltages, it was found that most of the students are hesitant to work directly on machine. The reason is that error in the circuitry might lead to deterioration of machine and laboratory instruments. So, it has become inevitable to include modern pedagogic techniques for undergraduate students, which would help them to first carry out experiment in virtual system and then to work on live circuit. Further advantages include that students can try out their intuitive ideas and perform in virtual environment, hence leading to new research and innovations. In this paper, virtual environment used is of MATLAB/Simulink for three-phase induction machines. The performance analysis of three-phase induction machine is carried out using virtual environment which includes Direct Current (DC) Test, No-Load Test, and Block Rotor Test along with speed torque characteristics for different rotor resistances and input voltage, respectively. Further, this paper carries out computer aided teaching of basic Voltage Source Inverter (VSI) drive circuitry. Hence, this paper gave undergraduates a clearer view of experiments performed on virtual machine (No-Load test, Block Rotor test and DC test, respectively). After successful implementation of basic tests, VSI circuitry is implemented, and related harmonic distortion (THD) and Fast Fourier Transform (FFT) of current and voltage waveform are studied.

Keywords: Block rotor test, DC test, no-load test, virtual environment, VSI.

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Authors: Nhu Van NGUYEN, Jean-Marc OGIER, Salvatore TABBONE, Alain BOUCHER

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The state-of-the-art Bag of Words model in Content- Based Image Retrieval has been used for years but the relevance feedback strategies for this model are not fully investigated. Inspired from text retrieval, the Bag of Words model has the ability to use the wealth of knowledge and practices available in text retrieval. We study and experiment the relevance feedback model in text retrieval for adapting it to image retrieval. The experiments show that the techniques from text retrieval give good results for image retrieval and that further improvements is possible.

Keywords: Relevance feedback, bag of words model, probabilistic model, vector space model, image retrieval

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Authors: H. Apaza, L. Chévez, H. Loro

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Plastic and microplastic pollution in human food chain is a big problem for human health that requires more elaborated techniques that can identify their presences in different kinds of food. Hyperspectral imaging technique is an optical technique than can detect the presence of different elements in an image and can be used to detect plastics and microplastics in a scene. To do this statistical techniques are required that need to be evaluated and compared in order to find the more efficient ones. In this work, two problems related to the presence of plastics are addressed, the first is to detect and identify pieces of plastic immersed in almond seeds, and the second problem is to detect and quantify microplastic in almond flour. To do this we make use of the analysis hyperspectral images taken in the range of 900 to 1700 nm using 4 unmixing techniques of hyperspectral imaging which are: least squares unmixing (LSU), non-negatively constrained least squares unmixing (NCLSU), fully constrained least squares unmixing (FCLSU), and scaled constrained least squares unmixing (SCLSU). NCLSU, FCLSU, SCLSU techniques manage to find the region where the plastic is found and also manage to quantify the amount of microplastic contained in the almond flour. The SCLSU technique estimated a 13.03% abundance of microplastics and 86.97% of almond flour compared to 16.66% of microplastics and 83.33% abundance of almond flour prepared for the experiment. Results show the feasibility of applying near-infrared hyperspectral image analysis for the detection of plastic contaminants in food.

Keywords: Food, plastic, microplastic, NIR hyperspectral imaging, unmixing.

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Authors: R. Latif, W. Jenkal, A. Toumanari, A. Hatim

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This paper presents an efficient method of electrocardiogram signal denoising based on a hybrid approach. Two techniques are brought together to create an efficient denoising process. The first is an Adaptive Dual Threshold Filter (ADTF) and the second is the Discrete Wavelet Transform (DWT). The presented approach is based on three steps of denoising, the DWT decomposition, the ADTF step and the highest peaks correction step. This paper presents some application of the approach on some electrocardiogram signals of the MIT-BIH database. The results of these applications are promising compared to other recently published techniques.

Keywords: Hybrid technique, ADTF, DWT, tresholding, ECG signal.

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Authors: Said Baadel, Fadi Thabtah, Joan Lu

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Clustering involves the partitioning of n objects into k clusters. Many clustering algorithms use hard-partitioning techniques where each object is assigned to one cluster. In this paper we propose an overlapping algorithm MCOKE which allows objects to belong to one or more clusters. The algorithm is different from fuzzy clustering techniques because objects that overlap are assigned a membership value of 1 (one) as opposed to a fuzzy membership degree. The algorithm is also different from other overlapping algorithms that require a similarity threshold be defined a priori which can be difficult to determine by novice users.

Keywords: Data mining, k-means, MCOKE, overlapping.

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Authors: Mohammad Reza Zamani Kouhpanji

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This paper presents a MEMS/NEMS device for fatigue and fracture characterization of nanomaterials. This device can apply static loads, cyclic loads, and their combinations in nanomechanical experiments. It is based on the electromagnetic force induced between paired parallel wires carrying electrical currents. Using this concept, the actuator and sensor parts of the device were designed and analyzed while considering the practical limitations. Since the PWCC device only uses two wires for actuation part and sensing part, its fabrication process is extremely easier than the available MEMS/NEMS devices. The total gain and phase shift of the MEMS/NEMS device were calculated and investigated. Furthermore, the maximum gain and sensitivity of the MEMS/NEMS device were studied to demonstrate the capability and usability of the device for wide range of nanomaterials samples. This device can be readily integrated into SEM/TEM instruments to provide real time study of the mechanical behaviors of nanomaterials as well as their fatigue and fracture properties, softening or hardening behaviors, and initiation and propagation of nanocracks.

Keywords: Sensors and actuators, MEMS/NEMS devices, fatigue and fracture nanomechanical testing device, static and cyclic nanomechanical testing device.

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Authors: Temitope O. Tokosi

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Healthcare is a human right. The sensitivity of health issues has necessitated the introduction of Enterprise Content Management (ECM) at district hospitals in the Western Cape Province of South Africa. The objective is understanding clinicians’ perception of ECM at their workplace. It is a descriptive case study design of constructivist paradigm. It employed a phenomenological data analysis method using a pattern matching deductive based analytical procedure. Purposive and s4nowball sampling techniques were applied in selecting participants. Clinicians expressed concerns and frustrations using ECM such as, non-integration with other hospital systems. Inadequate access points to ECM. Incorrect labelling of notes and bar-coding causes more time wasted in finding information. System features and/or functions (such as search and edit) are not possible. Hospital management and clinicians are not constantly interacting and discussing. Information turnaround time is unacceptably lengthy. Resolving these problems would involve a positive working relationship between hospital management and clinicians. In addition, prioritising the problems faced by clinicians in relation to relevance can ensure problem-solving in order to meet clinicians’ expectations and hospitals’ objective. Clinicians’ perception should invoke attention from hospital management with regards technology use. The study’s results can be generalised across clinician groupings exposed to ECM at various district hospitals because of professional and hospital homogeneity.

Keywords: Clinician, electronic content management, hospital, perception, technology.

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Authors: Wei-Jong Yang, Yu-Siang Su, Pau-Choo Chung, Jar-Ferr Yang

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Moving object detection (MOD) is an important issue in advanced driver assistance systems (ADAS). There are two important moving objects, pedestrians and scooters in ADAS. In real-world systems, there exist two important challenges for MOD, including the computational complexity and the detection accuracy. The histogram of oriented gradient (HOG) features can easily detect the edge of object without invariance to changes in illumination and shadowing. However, to reduce the execution time for real-time systems, the image size should be down sampled which would lead the outlier influence to increase. For this reason, we propose the histogram of uniformly-oriented gradient (HUG) features to get better accurate description of the contour of human body. In the testing phase, the support vector machine (SVM) with linear kernel function is involved. Experimental results show the correctness and effectiveness of the proposed method. With SVM classifiers, the real testing results show the proposed HUG features achieve better than classification performance than the HOG ones.

Keywords: Moving object detection, histogram of oriented gradient histogram of oriented gradient, histogram of uniformly-oriented gradient, linear support vector machine.

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Authors: Muhammad Raza Ali, Tim Morris

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Skin color is an important visual cue for computer vision systems involving human users. In this paper we combine skin color and optical flow for detection and tracking of skin regions. We apply these techniques to gesture recognition with encouraging results. We propose a novel skin similarity measure. For grouping detected skin regions we propose a novel skin region grouping mechanism. The proposed techniques work with any number of skin regions making them suitable for a multiuser scenario.

Keywords: Bayesian tracking, chromaticity space, optical flowgesture recognition

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Authors: Shaoyan Sun, Liwei Zhang, Chonghui Guo

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As the use of registration packages spreads, the number of the aligned image pairs in image databases (either by manual or automatic methods) increases dramatically. These image pairs can serve as a set of training data. Correspondingly, the images that are to be registered serve as testing data. In this paper, a novel medical image registration method is proposed which is based on the a priori knowledge of the expected joint intensity distribution estimated from pre-aligned training images. The goal of the registration is to find the optimal transformation such that the distance between the observed joint intensity distribution obtained from the testing image pair and the expected joint intensity distribution obtained from the corresponding training image pair is minimized. The distance is measured using the divergence measure based on Tsallis entropy. Experimental results show that, compared with the widely-used Shannon mutual information as well as Tsallis mutual information, the proposed method is computationally more efficient without sacrificing registration accuracy.

Keywords: Multimodality images, image registration, Shannonentropy, Tsallis entropy, mutual information, Powell optimization.

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Authors: Ganiyu Amuda Yusuf, Sarajul Fikri Mohamed

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The procurement and cost management approach adopted for mechanical and electrical (M&E) services in Malaysian construction industry have been criticized for its inefficiency. The study examined early cost estimating practices adopted for mechanical and electrical services (M&E) in Malaysia so as to understand the level of compliance of the current techniques with best practices. The methodology adopted for the study is a review of bidding documents used on both completed and on – going building projects awarded between 2008 – 2010 under 9th Malaysian Plan. The analysis revealed that, M&E services cost cannot be reliably estimated at pre-contract stage; the bidding techniques adopted for M&E services failed to provide uniform basis for contractors to submit tender; detailed measurement of items were not made which could complicate post contract cost control and financial management. The paper concluded that, there is need to follow a structured approach in determining the pre-contract cost estimate for M&E services which will serve as a virile tool for post contract cost control.

Keywords: Cost Management, Mechanical and Electrical Services, Procurement, Standard Method of Measurement

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Authors: A. Krishna Veni, R.Geetha

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Wireless Sensor Networks (WSNs) are suitable for many scenarios in the real world. The retrieval of data is made efficient by the data aggregation techniques. Many techniques for the data aggregation are offered and most of the existing schemes are not energy efficient and secure. However, the existing techniques use the traditional clustering approach where there is a delay during the packet transmission since there is no proper scheduling. The presented system uses the Velocity Energy-efficient and Link-aware Cluster-Tree (VELCT) scheme in which there is a Data Collection Tree (DCT) which improves the lifetime of the network. The VELCT scheme and the construction of DCT reduce the delay and traffic. The network lifetime can be increased by avoiding the frequent change in cluster topology. Secure and Efficient Transmission of Aggregated data (SETA) improves the security of the data transmission via the trust value of the nodes prior the aggregation of data. Since SETA considers the data only from the trustworthy nodes for aggregation, it is more secure in transmitting the data thereby improving the accuracy of aggregated data.

Keywords: Aggregation, lifetime, network security, wireless sensor network.

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Authors: Hyun-Woo Cho

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Real-time or in-line process monitoring frameworks are designed to give early warnings for a fault along with meaningful identification of its assignable causes. In artificial intelligence and machine learning fields of pattern recognition various promising approaches have been proposed such as kernel-based nonlinear machine learning techniques. This work presents a kernel-based empirical monitoring scheme for batch type production processes with small sample size problem of partially unbalanced data. Measurement data of normal operations are easy to collect whilst special events or faults data are difficult to collect. In such situations, noise filtering techniques can be helpful in enhancing process monitoring performance. Furthermore, preprocessing of raw process data is used to get rid of unwanted variation of data. The performance of the monitoring scheme was demonstrated using three-dimensional batch data. The results showed that the monitoring performance was improved significantly in terms of detection success rate of process fault.

Keywords: Process Monitoring, kernel methods, multivariate filtering, data-driven techniques, quality improvement.

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Authors: Nader Ghareeb, R¨udiger Schmidt

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Minimizing the weight in flexible structures means reducing material and costs as well. However, these structures could become prone to vibrations. Attenuating these vibrations has become a pivotal engineering problem that shifted the focus of many research endeavors. One technique to do that is to design and implement an active control system. This system is mainly composed of a vibrating structure, a sensor to perceive the vibrations, an actuator to counteract the influence of disturbances, and finally a controller to generate the appropriate control signals. In this work, two different techniques are explored to create two different mathematical models of an active control system. The first model is a finite element model with a reduced number of nodes and it is called a super-element. The second model is in the form of state-space representation, i.e. a set of partial differential equations. The damping coefficients are calculated and incorporated into both models. The effectiveness of these models is demonstrated when the system is excited by its first natural frequency and an active control strategy is developed and implemented to attenuate the resulting vibrations. Results from both modeling techniques are presented and compared.

Keywords: Finite element analysis, super-element, state-space model.

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Authors: Rossitza M. Setchi, Nikolaos Lagos

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Problem solving has traditionally been one of the principal research areas for artificial intelligence. Yet, although artificial intelligence reasoning techniques have been employed in several product support systems, the benefit of integrating product support, knowledge engineering, and problem solving, is still unclear. This paper studies the synergy of these areas and proposes a knowledge engineering framework that integrates product support systems and artificial intelligence techniques. The framework includes four spaces; the data, problem, hypothesis, and solution ones. The data space incorporates the knowledge needed for structured reasoning to take place, the problem space contains representations of problems, and the hypothesis space utilizes a multimodal reasoning approach to produce appropriate solutions in the form of virtual documents. The solution space is used as the gateway between the system and the user. The proposed framework enables the development of product support systems in terms of smaller, more manageable steps while the combination of different reasoning techniques provides a way to overcome the lack of documentation resources.

Keywords: Knowledge engineering framework, product support, case-based reasoning, model-based reasoning, multimodal reasoning.

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Authors: H. Shareef, A. Mohamed, S. A. Khalid, Aziah Khamis

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This paper presents application artificial intelligent (AI) techniques, namely artificial neural network (ANN), adaptive neuro fuzzy interface system (ANFIS), to estimate the real power transfer between generators and loads. Since these AI techniques adopt supervised learning, it first uses modified nodal equation method (MNE) to determine real power contribution from each generator to loads. Then the results of MNE method and load flow information are utilized to estimate the power transfer using AI techniques. The 25-bus equivalent system of south Malaysia is utilized as a test system to illustrate the effectiveness of both AI methods compared to that of the MNE method. The mean squared error of the estimate of ANN and ANFIS power transfer allocation methods are 1.19E-05 and 2.97E-05, respectively. Furthermore, when compared to MNE method, ANN and ANFIS methods computes generator contribution to loads within 20.99 and 39.37msec respectively whereas the MNE method took 360msec for the calculation of same real power transfer allocation. 

Keywords: Artificial intelligence, Power tracing, Artificial neural network, ANFIS, Power system deregulation.

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Authors: Chintanu K. Sarmah, Sandhya Samarasinghe, Don Kulasiri, Daniel Catchpoole

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Gene expression profiling is rapidly evolving into a powerful technique for investigating tumor malignancies. The researchers are overwhelmed with the microarray-based platforms and methods that confer them the freedom to conduct large-scale gene expression profiling measurements. Simultaneously, investigations into cross-platform integration methods have started gaining momentum due to their underlying potential to help comprehend a myriad of broad biological issues in tumor diagnosis, prognosis, and therapy. However, comparing results from different platforms remains to be a challenging task as various inherent technical differences exist between the microarray platforms. In this paper, we explain a simple ratio-transformation method, which can provide some common ground for cDNA and Affymetrix platform towards cross-platform integration. The method is based on the characteristic data attributes of Affymetrix- and cDNA- platform. In the work, we considered seven childhood leukemia patients and their gene expression levels in either platform. With a dataset of 822 differentially expressed genes from both these platforms, we carried out a specific ratio-treatment to Affymetrix data, which subsequently showed an improvement in the relationship with the cDNA data.

Keywords: Gene expression profiling, microarray, cDNA, Affymetrix, childhood leukaemia.

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Authors: Henri El Zakhem, Christina Romanos, Charlie Bakhos, Hassan Chahal, Jessica Koura

Abstract:

Squalene is a valuable component of the oil composed of 30 carbon atoms and is mainly used for cosmetic materials. The main concern of this article is to study the Squalene composition in the Lebanese olive oil and to compare it with foreign oil results. To our knowledge, extraction of Squalene from the Lebanese olive oil has not been conducted before. Three different techniques were studied and experiments were performed on three brands of olive oil, Al Wadi Al Akhdar, Virgo Bio and Boulos. The techniques performed are the Fractional Crystallization, the Soxhlet and the Esterification. By comparing the results, it is found that the Lebanese oil contains squalene and Soxhlet method is the most effective between the three methods extracting about 6.5E-04 grams of Squalene per grams of olive oil.

Keywords: Squalene, extraction, crystallization, Soxhlet.‎

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Authors: Younies Mahmoud, Mai Mabrouk, Elsayed Sallam

Abstract:

Analyzing DNA microarray data sets is a great challenge, which faces the bioinformaticians due to the complication of using statistical and machine learning techniques. The challenge will be doubled if the microarray data sets contain missing data, which happens regularly because these techniques cannot deal with missing data. One of the most important data analysis process on the microarray data set is feature selection. This process finds the most important genes that affect certain disease. In this paper, we introduce a technique for imputing the missing data in microarray data sets while performing feature selection.

Keywords: DNA microarray, feature selection, missing data, bioinformatics.

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Authors: Dong Xie, Leah Howard, Yiming Weng

Abstract:

The objective of this study was to synthesize and characterize 5-acryloyloxy-3,4-dichlorocrotonolactone (a furanone derivative), use this derivative to modify a dental restorative, and study the effect of the derivative on the antibacterial activity and compressive strength of the formed restorative. In this study, a furanone derivative was synthesized, characterized, and used to formulate a dental restorative. Compressive strength (CS) and S. mutans viability were used to evaluate the mechanical strength and antibacterial activity of the formed restorative. The fabricated restorative specimens were photocured and conditioned in distilled water at 37^oC for 24 h, followed by direct testing for CS or/and incubating with S. mutans for 48 h for antibacterial testing. The results show that the modified dental restorative showed a significant antibacterial activity without substantially decreasing the mechanical strengths. With addition of the antibacterial derivative up to 30%, the restorative kept its original CS nearly unchanged but showed a significant antibacterial activity with 68% reduction in the S. mutans viability. Furthermore, the antibacterial function of the modified restorative was not affected by human saliva. The aging study also indicates that the modified restorative may have a long-lasting antibacterial function. It is concluded that this experimental antibacterial restorative may potentially be developed into a clinically attractive dental filling restorative due to its high mechanical strength and antibacterial function.

Keywords: Antibacterial, dental filling restorative, compressive strength, S. mutans viability.

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