Search results for: AI algorithm internal audit

Authors: Fatih Suleyman Taskincan, Ahmet Karaarslan

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In this article, the study and analysis of Single Ended Primary Inductance Converter (SEPIC) are presented for battery charging applications that will be used in military applications. The usage of this kind of converters come from its advantage of non-reverse polarity at outputs. As capacitors charge and discharge through inductance, peak current does not occur on capacitors. Therefore, the efficiency will be high compared to buck-boost converters. In this study, the converter (SEPIC) is designed to be operated with Internal Model Controller (IMC). The traditional controllers like Proportional Integral Controller are not preferred as its linearity behavior. Hence IMC is designed for this converter. This controller is a model-based control and provides more robustness and better set point monitoring. Moreover, it can be used for an unstable process where the conventional controller cannot handle the dynamic operation. Matlab/Simulink environment is used to simulate the converter and its controller, then, the results are shown and discussed.

Keywords: DC/DC converter, single ended primary inductance converter, SEPIC, internal model controller, IMC, switched mode power supply

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Authors: Waseem Al-Talalwah

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The superior vesical artery usually arises directly from the anterior division of the internal iliac artery. It may arise from the umbilical artery as three or four branches to supply the upper and middle parts of bladder. Current study focuses on the different origins of the superior vesical artery to provide a sufficient data for surgeons to disease iatrogenic fault. The superior vesical artery arises directly from the anterior division of the internal iliac artery in 24.5% whereas it arises indirectly as from umbilical artery in 83.7%. Further, it may arise from any branch of the anterior division as from the utrine and obturator arteries in 6.1% and in 6.3% respectively. It also shares the origin of the internal pudendal and inferior glutyeal artery as it arises from the gluteopudendal trunk in 4.1%. The superior vesical artery arises as a single, double, triple and quadruple in 69.4%, 20.4%, 8.2% and 2% respectively. In case of cystectomy for bladder cancer, surgeons have to be aware of the origin variability of superior vesical artery to prevent post-surgical complication such as intra-pelvic bleeding. Also, the as intra-pelvic bleeding has to be expected in case of hysterectomy therefore a great caution of the vesical branches arising from uterine artery has to be considered. In case of aneurysm resection of inferior gluteal artery arising from the gluteopudendal trunk, the surgeons have to be careful of the vascular supply of urinary bladder coming from above and below this common trunk as from superior and inferior vesical arteries respectively. Therefore, present study increases the awareness of clinical significance of superior vesical artery origin for surgeons to minimise the iatroginc errors.

Keywords: superior vesical artery, anterior division, internal iliac, internal pudendal, inferior glutyeal, intra-pelvic bleeding, hysterectomy, cystectomy

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Authors: Ramya P, Lino Abraham Varghese, S. Bose

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By cloud storage services, the data can be stored in the cloud, and can be shared across multiple users. Due to the unexpected hardware/software failures and human errors, which make the data stored in the cloud be lost or corrupted easily it affected the integrity of data in cloud. Some mechanisms have been designed to allow both data owners and public verifiers to efficiently audit cloud data integrity without retrieving the entire data from the cloud server. But public auditing on the integrity of shared data with the existing mechanisms will unavoidably reveal confidential information such as identity of the person, to public verifiers. Here a privacy-preserving mechanism is proposed to support public auditing on shared data stored in the cloud. It uses group signatures to compute verification metadata needed to audit the correctness of shared data. The identity of the signer on each block in shared data is kept confidential from public verifiers, who are easily verifying shared data integrity without retrieving the entire file. But on demand, the signer of the each block is reveal to the owner alone. Group private key is generated once by the owner in the static group, where as in the dynamic group, the group private key is change when the users revoke from the group. When the users leave from the group the already signed blocks are resigned by cloud service provider instead of owner is efficiently handled by efficient proxy re-signature scheme.

Keywords: data integrity, dynamic group, group signature, public auditing

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Authors: Adrian Craig, Jonathan Easaw, Rose Jordan, Ben Hall

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The prescription of intravenous fluids is a fundamental component of inpatient management, but it is one which usually lacks thought. Fluids are a drug, which like any other can cause harm when prescribed inappropriately or wrongly. However, it is well recognised that it is poorly done, especially in the acute portals. The National Institute for Health and Care Excellence (NICE) recommends 1mmol/kg of potassium, sodium, and chloride per day. With various options of fluids, clinicians tend to face difficulty in choosing the most appropriate maintenance fluid, and there is a reluctance to prescribe potassium as part of an intravenous maintenance fluid regime. The aim was to prospectively audit the prescription of the first bag of intravenous maintenance fluids, the use of urea and electrolytes results to guide the choice of fluid and the use of fluid prescription charts, in a busy emergency department of a major trauma centre in Stoke-on-Trent, United Kingdom. This was undertaken over a week in early November 2016. Of those prescribed maintenance fluid only 8.9% were prescribed a fluid which was most appropriate for their daily electrolyte requirements. This audit has helped to highlight further the issues that are faced in busy Emergency Departments within hospitals that are stretched and lack capacity for prompt transfer to a ward. It has supported the findings of NICE, that emergency admission portals such as Emergency Departments poorly prescribed intravenous fluid therapy. The findings have enabled simple steps to be taken to educate clinicians about their fluid of choice. This has included: posters to remind clinicians to consider the urea and electrolyte values before prescription, suggesting the inclusion of a suggested intravenous fluid of choice in the prescription chart of the trust and the inclusion of a session within the introduction programme revising intravenous fluid therapy and daily electrolyte requirements. Moving forward, once the interventions have been implemented then, the data will be reaudited in six months to note any improvement in maintenance fluid choice. Alongside this, an audit of the rate of intravenous maintenance fluid therapy would be proposed to further increase patient safety by avoiding unintentional fluid overload which may cause unnecessary harm to patients within the hospital. In conclusion, prescription of maintenance fluid therapy was poor within the Emergency Department, and there is a great deal of opportunity for improvement. Therefore, the measures listed above will be implemented and the data reaudited.

Keywords: chloride, electrolyte, emergency department, emergency medicine, fluid, fluid therapy, intravenous, maintenance, major trauma, potassium, sodium, trauma

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Authors: Anton Stadler, Thorsten Ike

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In this paper, we present a video based smoke detection algorithm based on TVL1 optical flow estimation. The main part of the algorithm is an accumulating system for motion angles and upward motion speed of the flow field. We optimized the usage of TVL1 flow estimation for the detection of smoke with very low smoke density. Therefore, we use adapted flow parameters and estimate the flow field on difference images. We show in theory and in evaluation that this improves the performance of smoke detection significantly. We evaluate the smoke algorithm using videos with different smoke densities and different backgrounds. We show that smoke detection is very reliable in varying scenarios. Further we verify that our algorithm is very robust towards crowded scenes disturbance videos.

Keywords: low density, optical flow, upward smoke motion, video based smoke detection

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Authors: Murat Yazici

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Anomalies are irregularities found in data that do not adhere to a well-defined standard of normal behavior. The identification of outliers or anomalies in data has been a subject of study within the statistics field since the 1800s. Over time, a variety of anomaly detection techniques have been developed in several research communities. The cluster analysis can be used to detect anomalies. It is the process of associating data with clusters that are as similar as possible while dissimilar clusters are associated with each other. Many of the traditional cluster algorithms have limitations in dealing with data sets containing categorical properties. To detect anomalies in categorical data, fuzzy clustering approach can be used with its advantages. The fuzzy k-Mode (FKM) clustering algorithm, which is one of the fuzzy clustering approaches, by extension to the k-means algorithm, is reported for clustering datasets with categorical values. It is a form of clustering: each point can be associated with more than one cluster. In this paper, anomaly detection is performed on two simulated data by using the FKM cluster algorithm. As a significance of the study, the FKM cluster algorithm allows to determine anomalies with their abnormality degree in contrast to numerous anomaly detection algorithms. According to the results, the FKM cluster algorithm illustrated good performance in the anomaly detection of data, including both one anomaly and more than one anomaly.

Keywords: fuzzy k-mode clustering, anomaly detection, noise, categorical data

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Authors: Yanwen Li, Shuguo Xie

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In electromagnetic imaging, because of the diffraction limited system, the pixel values could change slowly near the edge of the image targets and they also change with the location in the same target. Using traditional digital image segmentation methods to segment electromagnetic gradient images could result in lots of errors because of this change in pixel values. To address this issue, this paper proposes a novel image segmentation and extraction algorithm based on Mean-Shift and dictionary learning. Firstly, the preliminary segmentation results from adaptive bandwidth Mean-Shift algorithm are expanded, merged and extracted. Then the overlap rate of the extracted image block is detected before determining a segmentation region with a single complete target. Last, the gradient edge of the extracted targets is recovered and reconstructed by using a dictionary-learning algorithm, while the final segmentation results are obtained which are very close to the gradient target in the original image. Both the experimental results and the simulated results show that the segmentation results are very accurate. The Dice coefficients are improved by 70% to 80% compared with the Mean-Shift only method.

Keywords: gradient image, segmentation and extract, mean-shift algorithm, dictionary iearning

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Authors: Nelson Igaba, C. Onaga, S. Hlongwane

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Background: Medical Male Circumcision (MMC) is part of a comprehensive HIV prevention strategy. The quality of MMC done at Right To Care (RtC) sites is maintained by Continuous Quality Improvement (CQI) based on findings of assessments by internal and independent external assessors who evaluate such parameters as the quality of the surgical procedure, infection control, etc. There are 12 RtC MMC teams in Mpumalanga, two of which are headed by Medical Officers and 10 by Clinical Associates (Clin A). Objectives: To compare the quality (i) of care rendered at doctor headed sites (DHS) versus Clin A headed sites (CHS); (ii) of CQI assessments (external versus internal). Methodology: A retrospective review of data from RightMax™ (a novel RtC data management system) and CQI reports (external and internal) was done. CQI assessment scores of October 2015 and October 2016 were taken as the baseline and latest respectively. Four sites with 745-810 circumcisions per annum were purposively selected; the two DHS (group A) and two CHS (group B). Statistical analyses were conducted using R (2017 version). Results: There were no significant difference in latest CQI scores between the two groups (DHS and CHS) (Anova, F = 1.97, df = 1, P = 0.165); between internal and external CQI assessment scores (Anova, F = 2.251, df = 1, P = 0.139) or among the individual sites (Anova, F = 1.095, df = 2, P = 0.341). Of the total of 16 adverse events reported by the four sites in the 12 months reviewed (all were infections), there was no statistical evidence that the documented severity of the infection was different for DHS and CHS (Fisher’s exact test, p-value = 0.269). Conclusion: At RtC VMMC sites in Mpumalanga, internal and external/independent CQI assessments are comparable, and quality of care of VMMC is standardized with the performance of well-supervised clinical associates comparing well with those of medical officers.

Keywords: adverse events, Right to Care, male medical circumcision, continuous quality improvement

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Authors: Mohamed Noureldin, Jinkoo Kim

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In this study, a genetic algorithm was used to find out the optimum locations of the slit dampers satisfying a target displacement. A seismic retrofit scheme for a building structure was presented using steel plate slit dampers. A cyclic loading test was used to verify the energy dissipation capacity of the slit damper. The seismic retrofit of the model structure using the slit dampers was compared with the retrofit with enlarging shear walls. The capacity spectrum method was used to propose a simple damper distribution scheme proportional to the inter-story drifts. The validity of the simple story-wise damper distribution procedure was verified by comparing the results of the genetic algorithm. It was observed that the proposed simple damper distribution pattern was in a good agreement with the optimum distribution obtained from the genetic algorithm. Acknowledgment: This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2017R1D1A1B03032809).

Keywords: slit dampers, seismic retrofit, genetic algorithm, optimum design

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Authors: Mohamed Rahal, Djaouida Guetta

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In this paper, the one-dimensional unconstrained global optimization problem of continuous functions satifying a Hölder condition is considered. We extend the algorithm of sequential covering SCA for Lipschitz functions to a large class of Hölder functions. The convergence of the method is studied and the algorithm can be applied to systems of nonlinear equations. Finally, some numerical examples are presented and illustrate the efficiency of the present approach.

Keywords: global optimization, Hölder functions, sequential covering method, systems of nonlinear equations

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Authors: Said Elkassimi, Said Safi, B. Manaut

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This paper presented a study of three algorithms, the equalization algorithm to equalize the transmission channel with ZF and MMSE criteria, application of channel Bran A, and adaptive filtering algorithms LMS and RLS to estimate the parameters of the equalizer filter, i.e. move to the channel estimation and therefore reflect the temporal variations of the channel, and reduce the error in the transmitted signal. So far the performance of the algorithm equalizer with ZF and MMSE criteria both in the case without noise, a comparison of performance of the LMS and RLS algorithm.

Keywords: adaptive filtering second equalizer, LMS, RLS Bran A, Proakis (B) MMSE, ZF

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Authors: Yuri Zinchenko

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Recently, distributed storage systems have been used more and more in various aspects of everyday life. They provide such necessary properties as Scalability, Fault Tolerance, Durability, and others. At the same time, not only reliable but also fast data storage remains one of the most pressing issues in this area. That brings us to the consensus algorithm as one of the most important components that has a great impact on the functionality of a distributed system. This paper is the result of an analysis of several well-known consensus algorithms, such as Paxos and Raft. The algorithm it offers, called Sync, promotes, but does not insist on simultaneous writing to the nodes (which positively affects the overall writing speed) and tries to minimize the system's inactive time. This allows nodes to reach agreement on the system state in a shorter period, which is a critical factor for distributed systems. Also when developing Sync, a lot of attention was paid to such criteria as simplicity and intuitiveness, the importance of which is difficult to overestimate.

Keywords: sync, consensus algorithm, distributed system, leader-based, synchronization.

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Authors: M. Al-Shamery, R. Young, P. Birch, C. Chatwin

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Computer Generated Holography (CGH) is employed to create digitally defined coherent wavefronts. A CGH can be created by using different techniques such as by using a detour-phase technique or by direct phase modulation to create a kinoform. The detour-phase technique was one of the first techniques that was used to generate holograms digitally. The disadvantage of this technique is that the reconstructed image often has poor quality due to the limited dynamic range it is possible to record using a medium with reasonable spatial resolution.. The kinoform (phase-only hologram) is an alternative technique. In this method, the phase of the original wavefront is recorded but the amplitude is constrained to be constant. The original object does not need to exist physically and so the kinoform can be used to reconstruct an almost arbitrary wavefront. However, the image reconstructed by this technique contains high levels of noise and is not identical to the reference image. To improve the reconstruction quality of the kinoform, iterative techniques such as the Gerchberg-Saxton algorithm (GS) are employed. In this paper the GS algorithm is described for the optimisation of a kinoform used for the reconstruction of a complex wavefront. Iterations of the GS algorithm are applied to determine the phase at a plane (with known amplitude distribution which is often taken as uniform), that satisfies given phase and amplitude constraints in a corresponding Fourier plane. The GS algorithm can be used in this way to enhance the reconstruction quality of the kinoform. Different images are employed as the reference object and their kinoform is synthesised using the GS algorithm. The quality of the reconstructed images is quantified to demonstrate the enhanced reconstruction quality achieved by using this method.

Keywords: computer generated holography, digital holography, Gerchberg-Saxton algorithm, kinoform

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Authors: Gourida Siham

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Chinese society has witnessed a continuing trend of nationwide rural to urban migration since the 1970's. Before that age, under restricted hukou systems, peasants were kept still and fixed in the farm land. The year 1978 and later years saw the control of migration in China was relaxed gradually, freeing peasants to start their own businesses and reach out to work also in urban areas. Since then the “floating population” (migrants without local hukou) took great momentum and drew great attention from both the media and academia. The scale of such internal migration is enormous –the floating population has reached to a number of 79 million in 2000, and as of 2010, the number of migrant workers from rural China amounts to over 221 million and according to the annual survey results projections by National Bureau of Statistics; the total migrant workers in china in 2012 amounted to 262.61 million, which refers to an increase of 9.83 million compared with the previous year with increase percentage by 3.9%. Using China’s Jiangxi Province as a case, this paper examines patterns of internal migration as a response of emigrations in the context of high emigration communities. Our findings suggest that emigration of individuals initially deterred both inter-provincial and intra- provincial migration of other family members, and yet, overtime they had an increasing propensity to migrate internally at both scales.

Keywords: internal migration, jiangxi, nanchang, remittances

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Authors: Hakim S. Sultan Aljibori

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An experimental procedure is developed to study the performance of composite thin wall cylinders subjected to internal pressure loading for investigations of stress distribution through the composite cylinders wall. Three types of fibers were used in this study are; woven roving glass fiber/epoxy, hybrid fiber/epoxy, and Kevlar fiber/epoxy composite specimens were fabricated and tested. All of these specimens subjected to uniformed pressure load using the hydraulic pump. Axial stress is identified, and values were found after collecting all the results. Comparison between the deferent types of specimens was done. Thus, the present investigation concludes the efficient and effective composite cylinder experimentally and provides a considerable advantage for using woven roving fibers in pressure vessels applications.

Keywords: stress distribution, composite material, internal pressure, glass fiber, hybrid fiber

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Authors: Hitesh Tahbildar

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The cost of test data generation for a program is computationally very high. In general case, no algorithm to generate test data for all types of algorithms has been found. The cost of generating test data for different types of algorithm is different. Till date, people are emphasizing the need to generate test data for different types of programming constructs rather than different types of algorithms. The test data generation methods have been implemented to find heuristics for different types of algorithms. Some algorithms that includes divide and conquer, backtracking, greedy approach, dynamic programming to find the minimum cost of test data generation have been tested. Our experimental results say that some of these types of algorithm can be used as a necessary condition for selecting heuristics and programming constructs are sufficient condition for selecting our heuristics. Finally we recommend the different heuristics for test data generation to be selected for different types of algorithms.

Keywords: ongest path, saturation point, lmax, kL, kS

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Authors: Konstanca Nikolajevic, Nicolas Belanger, David Duvivier, Rabie Ben Atitallah, Abdelhakim Artiba

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Finding the optimal 3D path of an aerial vehicle under flight mechanics constraints is a major challenge, especially when the algorithm has to produce real-time results in flight. Kinematics models and Pythagorian Hodograph curves have been widely used in mobile robotics to solve this problematic. The level of difficulty is mainly driven by the number of constraints to be saturated at the same time while minimizing the total length of the path. In this paper, we suggest a pragmatic algorithm capable of saturating at the same time most of dimensioning helicopter 3D trajectories’ constraints like: curvature, curvature derivative, torsion, torsion derivative, climb angle, climb angle derivative, positions. The trajectories generation algorithm is able to generate versatile complex 3D motion primitives feasible by a helicopter with parameterization of the curvature and the climb angle. An upper ”motion primitives’ concatenation” algorithm is presented based. In this article we introduce a new way of designing three-dimensional trajectories based on what we call the ”Dubins gliding symmetry conjecture”. This extremely performing algorithm will be soon integrated to a real-time decisional system dealing with inflight safety issues.

Keywords: robotics, aerial robots, motion primitives, helicopter

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Authors: Oluremi I. Bamgbade, Oluwayomi Babatunde

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Governments and nonprofits have been in the support of sustainability as the goal of businesses especially in the construction industry because of its considerable impacts on the environment, economy, and society. However, to measure the degree to which an organisation is being sustainable or pursuing sustainable growth can be difficult as a result of the clear sustainability strategy required to assume their commitment to the goal and competitive advantage. This research investigated the influence of organisational culture and organisational structure in achieving sustainable construction among South African construction firms. A total of 132 consultants from the nine provinces in South Africa participated in the survey. The data collected were initially screened using SPSS (version 21) while Partial Least Squares Structural Equation Modeling (PLS-SEM) algorithm and bootstrap techniques were employed to test the hypothesised paths. The empirical evidence also supported the hypothesised direct effects of organisational culture and organisational structure on sustainable construction. Similarly, the result regarding the relationship between organisational culture and organisational structure was supported. Therefore, construction industry can record a considerable level of construction sustainability and establish suitable cultures and structures within the construction organisations. Drawing upon organisational control theory, these findings supported the view that these organisational internal factors have a strong contingent effect on sustainability adoption in construction project execution. The paper makes theoretical, practical and methodological contributions within the domain of sustainable construction especially in the context of South Africa. Some limitations of the study are indicated, suggesting opportunities for future research.

Keywords: organisational culture, organisational structure, South African construction firms, sustainable construction

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Authors: D. S. Nagesh, G. L. Datta

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In the field of welding, various studies had been made by some of the previous investigators to predict as well as optimize weld bead geometric descriptors. Modeling of weld bead shape is important for predicting the quality of welds. In most of the cases, design of experiments technique to postulate multiple linear regression equations have been used. Nowadays, Genetic Algorithm (GA) an intelligent information treatment system with the characteristics of treating complex relationships as seen in welding processes used as a tool for inverse mapping/optimization of the process is attempted.

Keywords: smaw, genetic algorithm, bead geometry, optimization/inverse mapping

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Authors: D. S. Nagesh, G. L. Datta

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In the field of welding, various studies had been made by some of the previous investigators to predict as well as optimize weld bead geometric descriptors. Modeling of weld bead shape is important for predicting the quality of welds. In most of the cases design of experiments technique to postulate multiple linear regression equations have been used. Nowadays Genetic Algorithm (GA) an intelligent information treatment system with the characteristics of treating complex relationships as seen in welding processes used as a tool for inverse mapping/optimization of the process is attempted.

Keywords: SMAW, genetic algorithm, bead geometry, optimization/inverse mapping

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Authors: Tushar Bhardwaj

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Internet of Things (IoT) possesses a dynamic network where the network nodes (mobile devices) are added and removed constantly and randomly, hence the traffic distribution in the network is quite variable and irregular. The basic but very important part in any network is route searching. We have many conventional route searching algorithms like link-state, and distance vector algorithms but they are restricted to the static point to point network topology. In this paper we propose a model that uses the Ant Colony Algorithm for route searching. It is dynamic in nature and has positive feedback mechanism that conforms to the route searching. We have also embedded the concept of Non-Deterministic Finite Automata [NDFA] minimization to reduce the network to increase the performance. Results show that Ant Colony Algorithm gives the shortest path from the source to destination node and NDFA minimization reduces the broadcasting storm effectively.

Keywords: routing, ant colony algorithm, NDFA, IoT

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Authors: Latifa Sabri, Mohammed Benzirar, Mimoun Zazoui

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The installation of photovoltaic systems is one of future sources to generate electricity without emitting pollutants. The photovoltaic cells used in these systems have demonstrated enormous efficiencies and advantages. Several researches have discussed the maximum efficiency of these technologies, but only a few experiences have succeeded to right weather conditions to get these results. In this paper, two types of cells were selected: crystalline and amorphous silicon. Using the method of genetic algorithm, the results show that for an ambient temperature of 25°C and direct irradiation of 625 W/m², the efficiency of crystalline silicon is 12% and 5% for amorphous silicon.

Keywords: PV, maximum efficiency, solar cell, genetic algorithm

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Authors: Chandra Mukherjee

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The present paper is a representation of the work done in the field of ECG signal analysis using MATLAB 7.1 Platform. An accurate and simple ECG feature extraction algorithm is presented in this paper and developed algorithm is validated using BIOPAC software. To detect the QRS peak, ECG signal is processed by following mentioned stages- First Derivative, Second Derivative and then squaring of that second derivative. Efficiency of developed algorithm is tested on ECG samples from different database and real time ECG signals acquired using BIOPAC system. Firstly we have lead wise specified threshold value the samples above that value is marked and in the original signal, where these marked samples face change of slope are spotted as R-peak. On the left and right side of the R-peak, faces change of slope identified as Q and S peak, respectively. Now the inbuilt Detection algorithm of BIOPAC software is performed on same output sample and both outputs are compared. ECG baseline modulation correction is done after detecting characteristics points. The efficiency of the algorithm is tested using some validation parameters like Sensitivity, Positive Predictivity and we got satisfied value of these parameters.

Keywords: first derivative, variable threshold, slope reversal, baseline modulation correction

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Authors: Nureni O. Adeboye, Dawud A. Agunbiade

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This research attempts to investigate the effects of heteroscedasticity and periodicity in a Panel Data Regression Model (PDRM) by extending previous works on balanced panel data estimation within the context of fitting PDRM for Banks audit fee. The estimation of such model was achieved through the derivation of Joint Lagrange Multiplier (LM) test for homoscedasticity and zero-serial correlation, a conditional LM test for zero serial correlation given heteroscedasticity of varying degrees as well as conditional LM test for homoscedasticity given first order positive serial correlation via a two-way error component model. Monte Carlo simulations were carried out for 81 different variations, of which its design assumed a uniform distribution under a linear heteroscedasticity function. Each of the variation was iterated 1000 times and the assessment of the three estimators considered are based on Variance, Absolute bias (ABIAS), Mean square error (MSE) and the Root Mean Square (RMSE) of parameters estimates. Eighteen different models at different specified conditions were fitted, and the best-fitted model is that of within estimator when heteroscedasticity is severe at either zero or positive serial correlation value. LM test results showed that the tests have good size and power as all the three tests are significant at 5% for the specified linear form of heteroscedasticity function which established the facts that Banks operations are severely heteroscedastic in nature with little or no periodicity effects.

Keywords: audit fee lagrange multiplier test, heteroscedasticity, lagrange multiplier test, Monte-Carlo scheme, periodicity

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Authors: Mina Samizadeh

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In the past few decades, there has been an explosion in the amount of available data produced from various sources with different topics. The availability of this enormous data necessitates us to adopt effective computational tools to explore the data. This leads to an intense growing interest in the research community to develop computational methods focused on processing this text data. A line of study focused on condensing the text so that we are able to get a higher level of understanding in a shorter time. The two important tasks to do this are keyword extraction and text summarization. In keyword extraction, we are interested in finding the key important words from a text. This makes us familiar with the general topic of a text. In text summarization, we are interested in producing a short-length text which includes important information about the document. The TextRank algorithm, an unsupervised learning method that is an extension of the PageRank (algorithm which is the base algorithm of Google search engine for searching pages and ranking them), has shown its efficacy in large-scale text mining, especially for text summarization and keyword extraction. This algorithm can automatically extract the important parts of a text (keywords or sentences) and declare them as a result. However, this algorithm neglects the semantic similarity between the different parts. In this work, we improved the results of the TextRank algorithm by incorporating the semantic similarity between parts of the text. Aside from keyword extraction and text summarization, we develop a topic clustering algorithm based on our framework, which can be used individually or as a part of generating the summary to overcome coverage problems.

Keywords: keyword extraction, n-gram extraction, text summarization, topic clustering, semantic analysis

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Authors: Waqas Ahmad, Eisha Tahir, Shahper Aqeel, Imran Khalid Niazi, Amjad Iqbal

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Background: Breast conservation surgery applies a number of techniques for accurate localization of lesions. Wire localization remains the method of choice in non-palpable breast cancers post-neoadjuvant chemotherapy. Objective: The aim of our study was to determine the accuracy of wire localization procedures in our department and compare it with internationally set protocols as per the Royal College of Radiologists. Post wire mammography, as well as the margin status of the postoperative specimen, assessed the accuracy of the procedure. Methods: We retrospectively reviewed the data of 225 patients who presented to our department from May 2014 to June 2015 post neoadjuvant chemotherapy with non-palpable cancers. These patients are candidates for wire localized lumpectomies either under ultrasound or stereotactic guidance. Metallic marker was placed in all the patients at the time of biopsy. Post wire mammogram was performed in all the patients and the distance of the wire tip from the marker was calculated. The presence or absence of the metallic clip in the postoperative specimen, as well as the marginal status of the postoperative specimen, was noted. Results: 157 sonographic and 68 stereotactic wire localization procedures were performed. 95% of the wire tips were within 1 cm of the metallic marker. Marginal status was negative in 94% of the patients in histopathological specimen. Conclusion: Our audit report declares more than 95% accuracy of image guided wire localization in successful excision of non-palpable breast lesions.

Keywords: breast, cancer, non-palpable, wire localization

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Authors: Pejman Hosseinioun, Hasan Shakeri, Ghasem Ghorbanirostam

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In recent years, we have seen an increasing importance of research and study on knowledge source, decision support systems, data mining and procedure of knowledge discovery in data bases and it is considered that each of these aspects affects the others. In this article, we have merged information source and knowledge source to suggest a knowledge based system within limits of management based on storing and restoring of knowledge to manage information and improve decision making and resources. In this article, we have used method of data mining and Apriori algorithm in procedure of knowledge discovery one of the problems of Apriori algorithm is that, a user should specify the minimum threshold for supporting the regularity. Imagine that a user wants to apply Apriori algorithm for a database with millions of transactions. Definitely, the user does not have necessary knowledge of all existing transactions in that database, and therefore cannot specify a suitable threshold. Our purpose in this article is to improve Apriori algorithm. To achieve our goal, we tried using fuzzy logic to put data in different clusters before applying the Apriori algorithm for existing data in the database and we also try to suggest the most suitable threshold to the user automatically.

Keywords: decision support system, data mining, knowledge discovery, data discovery, fuzzy logic

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Authors: Toni Maristela C. Estabillo, Michaela V. Matienzo, Mikaela L. Sabangan, Rosette M. Tienzo, Justine L. Bahinting

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This study is about blind watermarking on images with different categories and properties using two algorithms namely, Discrete Wavelet Transform and Patchwork Algorithm. A program is created to perform watermark embedding, extraction and evaluation. The evaluation is based on three watermarking criteria namely: image quality degradation, perceptual transparency and security. Image quality is measured by comparing the original properties with the processed one. Perceptual transparency is measured by a visual inspection on a survey. Security is measured by implementing geometrical and non-geometrical attacks through a pass or fail testing. Values used to measure the following criteria are mostly based on Mean Squared Error (MSE) and Peak Signal to Noise Ratio (PSNR). The results are based on statistical methods used to interpret and collect data such as averaging, z Test and survey. The study concluded that the combined DWT and Patchwork algorithms were less efficient and less capable of watermarking than DWT algorithm only.

Keywords: blind watermarking, discrete wavelet transform algorithm, patchwork algorithm, digital watermark

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Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

Abstract:

In this paper, we propose a novel inference algorithm for the multi-class Gaussian process classification model that can be used in the field of human behavior recognition. This algorithm can drive simultaneously both a posterior distribution of a latent function and estimators of hyper-parameters in a Gaussian process classification model with multi-class. Our algorithm is based on the Laplace approximation (LA) technique and variational EM framework. This is performed in two steps: called expectation and maximization steps. First, in the expectation step, using the Bayesian formula and LA technique, we derive approximately the posterior distribution of the latent function indicating the possibility that each observation belongs to a certain class in the Gaussian process classification model. Second, in the maximization step, using a derived posterior distribution of latent function, we compute the maximum likelihood estimator for hyper-parameters of a covariance matrix necessary to define prior distribution for latent function. These two steps iteratively repeat until a convergence condition satisfies. Moreover, we apply the proposed algorithm with human action classification problem using a public database, namely, the KTH human action data set. Experimental results reveal that the proposed algorithm shows good performance on this data set.

Keywords: bayesian rule, gaussian process classification model with multiclass, gaussian process prior, human action classification, laplace approximation, variational EM algorithm

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Authors: Mehrdad Rezaei, Reza Haghmaram, Nima Amjadi

Abstract:

This paper proposes an operating and cost optimization model for micro-grid (MG). This model takes into account emission costs of NOx, SO2, and CO2, together with the operation and maintenance costs. Wind turbines (WT), photovoltaic (PV) arrays, micro turbines (MT), fuel cells (FC), diesel engine generators (DEG) with different capacities are considered in this model. The aim of the optimization is minimizing operation cost according to constraints, supply demand and safety of the system. The proposed genetic algorithm (GA), with the ability to fine-tune its own settings, is used to optimize the micro-grid operation.

Keywords: micro-grid, optimization, genetic algorithm, MG

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