Search results for: AI algorithm internal audit

Authors: B. S. Akhmetov, S. T. Akhmetova, A. I. Ivanov, T. S. Kartbayev, A. Y. Malygin

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The problem of training of a network of artificial neurons in biometric appendices is that this process has to be completely automatic, i.e. the person operator should not participate in it. Therefore, this article discusses the issues of training the network of artificial neurons and the description of the non-iterative learning algorithm of artificial neuron.

Keywords: artificial neuron, biometrics, biometrical applications, learning of neuron, non-iterative algorithm

Procedia PDF Downloads 494

Authors: Dimeji Abe, Nonso Okoye, Gideon Ikpimi, Prince Idemudia

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Multi-reservoir optimization operation has been a critical issue for river basin management. Water, as a scarce resource, is in high demand and the problems associated with the reservoir as its storage facility are enormous. The complexity in balancing the supply and demand of this prime resource has created the need to examine the best way to solve the problem using optimization techniques. The objective of this study is to evaluate the performance of the multi-objective meta-heuristic algorithm for the operation of Gariep Dam for satisfying ecological flow requirements. This study uses an evolutionary algorithm called backtrack search algorithm (BSA) to determine the best way to optimise the dam operations of hydropower production, flood control, and water supply without affecting the environmental flow requirement for the survival of aquatic bodies and sustain life downstream of the dam. To achieve this objective, the operations of the dam that corresponds to different tradeoffs between the objectives are optimized. The results indicate the best model from the algorithm that satisfies all the objectives without any constraint violation. It is expected that hydropower generation will be improved and more water will be available for ecological flow requirements with the use of the algorithm. This algorithm also provides farmers with more irrigation water as well to improve their business.

Keywords: BSA evolutionary algorithm, metaheuristics, optimization, river basin management

Procedia PDF Downloads 245

Authors: Ruth Green, Samantha Milton, Rinal Desai

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Background/Aims: Eye pain/swelling/redness is a common presentation to Barnet General Hospital (a district general hospital), pediatric emergency department, and is managed by both the pediatric and emergency teams. The management of each child differs dramatically depending on the healthcare professional who reviews them. There also appears to be confusion in diagnosis between periorbital cellulitis, pre-septal cellulitis, and orbital cellulitis. Pre septal cellulitis refers to an inflammation of the eyelids and soft tissue anterior to the orbital septum. In contrast, orbital cellulitis is a serious, rapidly progressive infection of soft tissues located posterior to the orbital septum. Pre-septal cellulitis is more prevalent and less serious than orbital cellulitis, although it may be part of a continuous spectrum if untreated. Pre-septal cellulitis should there be diagnosed and treated urgently to prevent spread to the septum. For the purpose of the audit, the term periorbital cellulitis has been used as an umbrella term for all spectrums of this infection. The audit aimed to look at, how as a whole, the department is diagnosing and managing orbital and pre-septal cellulitis. Gold Standard: Patients of the same age and diagnosis should be treated with the same medication, advice, and follow-up. Method: Data was collected retrospectively from pediatric patients ( < 18years) who attended the emergency department from June 2019 to February 2020 who had been coded as pre-septal cellulitis, periorbital cellulitis, orbital cellulitis, or eye pain/swelling/redness. Demographics, signs and symptoms, management, and follow-up were recorded for all patients with any of the diagnoses of pre-septal, periorbital, or orbital cellulitis. A Microsoft Excel spreadsheet was used to record the anonymised data. Results: There were vast discrepancies in the diagnosis, management, and follow-up of patients with periorbital cellulitis. Conclusion/Discussion: The audit concluded there is no uniform approach to managing periorbital cellulitis in Barnet General Hospital Paediatric Emergency Department. Healthcare professionals misdiagnosed conjunctivitis as periorbital cellulitis, and adequate steps did not appear to be documented on excluding red flag signs and symptoms of patients presenting. There was no consistency in follow-up, with some patients having timely phone reviews or clinical reviews for mild symptoms. Advice given by the staff was appropriate, and patients did return when symptoms got worse and were treated accordingly. Plan: Given the inconsistency, a gold standard care pathway or local easily accessible clinical guideline can be developed to help with the diagnosis and management of periorbital cellulitis. Along with this, a teaching session can be carried out for the staff of the pediatric team and emergency department to disseminate the teaching. Following the introduction of a guideline and teaching sessions, patients notes can be re-reviewed to check improvement in patient care.

Keywords: periorbital cellulitis, preseptal cellulitis, orbital cellulitis, erythematous eyelid

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Authors: Fadzil Ahmad, Noor Ashidi Mat Isa

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This study introduces an improved genetic algorithm procedure that focuses search around near optimal solution corresponded to a group of elite chromosome. This is achieved through a novel crossover technique known as Segmented Multi Chromosome Crossover. It preserves the highly important information contained in a gene segment of elite chromosome and allows an offspring to carry information from gene segment of multiple chromosomes. In this way the algorithm has better possibility to effectively explore the solution space. The improved GA is applied for the automatic and simultaneous parameter optimization and feature selection of artificial neural network in pattern recognition of medical problem, the cancer and diabetes disease. The experimental result shows that the average classification accuracy of the cancer and diabetes dataset has improved by 0.1% and 0.3% respectively using the new algorithm.

Keywords: genetic algorithm, artificial neural network, pattern clasification, classification accuracy

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Authors: Elham Jelodari Mamaghani, Christian Prins, Haoxun Chen

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In this paper, there is concentration on collaborative transportation planning (CTP) among multiple carriers with pickup and delivery requests and time windows. This problem is a vehicle routing problem with constraints from standard vehicle routing problems and new constraints from a real-world application. In the problem, each carrier has a finite number of vehicles, and each request is a pickup and delivery request with time window. Moreover, each carrier has reserved requests, which must be served by itself, whereas its exchangeable requests can be outsourced to and served by other carriers. This collaboration among carriers can help them to reduce total transportation costs. A mixed integer programming model is proposed to the problem. To solve the model, a hybrid algorithm that combines Genetic Algorithm and Simulated Annealing (GASA) is proposed. This algorithm takes advantages of GASA at the same time. After tuning the parameters of the algorithm with the Taguchi method, the experiments are conducted and experimental results are provided for the hybrid algorithm. The results are compared with those obtained by a commercial solver. The comparison indicates that the GASA significantly outperforms the commercial solver.

Keywords: centralized collaborative transportation, collaborative transportation with pickup and delivery, collaborative transportation with time windows, hybrid algorithm of GA and SA

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Authors: Jeonghwan Jeon

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Technology planning with both internal capacity and external resource is necessary for successful open innovation. Until now, many types of research have been conducted for this issue. However, technology planning for open innovation at the national level has not been researched sufficiently. This study proposes Open roadmap for open innovation at the national level. The proposed open roadmap can manage the inflow & outflow open innovation systematically. Six types of open roadmap are classified with respect to the innovation direction and characteristics. The proposed open roadmap is applied to the open innovation cases of the Roman period. The proposed open roadmap is expected to be helpful tool for technology policy planning at the national level.

Keywords: technology planning, open innovation, internal resource, external resource, technology management

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Authors: Nicolas Koslover, Tamara Levene

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Aims: Tonsilitis is one of the most common presentations to the A+E department. We aimed to assess whether patients presenting with tonsilitis are being managed in-line with current guidance. We then set out to educate A+E staff about tonsilitis management and then assessed for improvement in management. Methods: All patients presenting to A+E in one fortnight with a documented diagnosis of tonsilitis were included. We reviewed the notes to assess the choice of treatment in each case and whether a clinical score (CENTOR or FEVERPain score) was used to guide choice of treatment (in accordance with NICE guideline [NG84]). We designed and delivered an educational intervention for A+E staff covering tonsilitis guidelines. The audit was repeated two weeks later. Results: Over the study period, 49 patients were included; only 35% (n=17) had either a clinical score documented or had all components of a score recorded. In total, 39% (n=19) were treated with antibiotics. Of these, 63% (n=12) should not have been prescribed an antibiotic and 37% (n=7) were prescribed an inappropriate antibiotic. At re-audit, (n=50 cases), 58% (n=29) had a clinical score documented and 28% (n=14) were treated with antibiotics. Of these, 29% (n=4) should not have been prescribed antibiotics and 21% (n=3) were prescribed an inappropriate antibiotic. Thus, after this teaching session, there was a significant improvement in antibiotic prescribing practices (63% vs. 29%, p=0.026). Conclusions: A+E assessment and management of tonsilitis frequently deviated from guidelines, but a single teaching session vastly improved clinical scoring and antibiotic prescribing practices.

Keywords: tonsilitis, education, emergency medicine, ENT

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Authors: Satyendra Pratap Singh, S. P. Singh

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This paper presents a methodology using Gravitational Search Algorithm for optimal placement of Phasor Measurement Units (PMUs) in order to achieve complete observability of the power system. The objective of proposed algorithm is to minimize the total number of PMUs at the power system buses, which in turn minimize installation cost of the PMUs. In this algorithm, the searcher agents are collection of masses which interact with each other using Newton’s laws of gravity and motion. This new Gravitational Search Algorithm based method has been applied to the IEEE 14-bus, IEEE 30-bus and IEEE 118-bus test systems. Case studies reveal optimal number of PMUs with better observability by proposed method.

Keywords: gravitational search algorithm (GSA), law of motion, law of gravity, observability, phasor measurement unit

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Authors: Hee-Choul Kwon, Hyungjin Cho, Heeyong Kwon

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Image rotation is one of main pre-processing step in image processing or image pattern recognition. It is implemented with rotation matrix multiplication. However it requires lots of floating point arithmetic operations and trigonometric function calculations, so it takes long execution time. We propose a new high speed image rotation algorithm without two major time-consuming operations. We compare the proposed algorithm with the conventional rotation one with various size images. Experimental results show that the proposed algorithm is superior to the conventional rotation ones.

Keywords: high speed rotation operation, image processing, image rotation, pattern recognition, transformation matrix

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Authors: Jian Shi, Baoguo Yu, Haonan Jia, Meng Liu, Ping Huang

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Adapting to the flexibility of war, a large number of guided weapons launch from aircraft. Therefore, the inertial navigation system loaded in the weapon needs to undergo an alignment process in the air. This article proposes the following methods to the problem of inaccurate modeling of the system under large misalignment angles, the accuracy reduction of filtering caused by outliers, and the noise changes in GPS signals: first, considering the large misalignment errors of Strapdown Inertial Navigation System (SINS)/GPS, a more accurate model is made rather than to make a small-angle approximation, and the Unscented Kalman Filter (UKF) algorithms are used to estimate the state; then, taking into account the impact of GPS noise changes on the fine alignment algorithm, the innovation adaptive filtering algorithm is introduced to estimate the GPS’s noise in real-time; at the same time, in order to improve the anti-interference ability of the air fine alignment algorithm, a robust filtering algorithm based on outlier detection is combined with the air fine alignment algorithm to improve the robustness of the algorithm. The algorithm can improve the alignment accuracy and robustness under interference conditions, which is verified by simulation.

Keywords: air alignment, fine alignment, inertial navigation system, integrated navigation system, UKF

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Authors: John Kong Shan Ho

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Senior executives’ remunerations of public companies have aroused much debate and attention in the media. In the aftermath of the Global Financial Crisis (GFC), excessive executive pay arrangements were blamed for contributing to excessive risk-taking, which caused the financial meltdown. Since then, regulators and lawmakers around the world have introduced regulations to strengthen the corporate governance of listed companies. A key aspect of such reform is by strengthening regulatory intervention over executives’ remunerations and increasing the transparency of such information. This article is written against such background and examines the recent proposal by the UK BEIS to ask the FRC to amend the UK Corporate Governance Code (UKCGC) to strengthen clawback provisions for directors’ remuneration in listed companies as part of its audit reform. The article examines the background and debates regarding the possible implementation of such a measure in the UK. Contrary to the BEIS’ proposal, it argues that implementing it through the UKCGC is unlikely to enhance overall corporate governance and audit quality. It argues that the UK should follow the footsteps of its US and Dutch counterparts by enacting legislation to claw back directors’ remunerations. It will also provide some recommendations as to the key factors that need to be considered in drafting such a statutory provision.

Keywords: company law, corporate governance, agency problem, directors' remunerations, clawbacks

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Authors: Fuzhang Zhao

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Particle swarm optimization (PSO) is becoming one of the most important swarm intelligent paradigms for solving global optimization problems. Although some progress has been made to improve PSO algorithms over the last two decades, additional work is still needed to balance parameters to achieve better numerical properties of accuracy, efficiency, and stability. In the optimal PSO algorithm, the optimal weightings of (√ 5 − 1)/2 and (3 − √5)/2 are used for the cognitive factor and the social factor, respectively. By the same token, the same optimal weightings have been applied for intensification searches and diversification searches, respectively. Perturbation and constriction effects are optimally balanced. Simulations of the de Jong, the Rosenbrock, and the Griewank functions show that the optimal PSO algorithm indeed achieves better numerical properties and outperforms the canonical PSO algorithm.

Keywords: diversification search, intensification search, optimal weighting, particle swarm optimization

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Authors: Ghada Badr, Arwa Alturki

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The biological function of an RNA molecule depends on its structure. The objective of the alignment is finding the homology between two or more RNA secondary structures. Knowing the common functionalities between two RNA structures allows a better understanding and a discovery of other relationships between them. Besides, identifying non-coding RNAs -that is not translated into a protein- is a popular application in which RNA structural alignment is the first step A few methods for RNA structure-to-structure alignment have been developed. Most of these methods are partial structure-to-structure, sequence-to-structure, or structure-to-sequence alignment. Less attention is given in the literature to the use of efficient RNA structure representation and the structure-to-structure alignment methods are lacking. In this paper, we introduce an O(N2) Component-based Pairwise RNA Structure Alignment (CompPSA) algorithm, where structures are given as a component-based representation and where N is the maximum number of components in the two structures. The proposed algorithm compares the two RNA secondary structures based on their weighted component features rather than on their base-pair details. Extensive experiments are conducted illustrating the efficiency of the CompPSA algorithm when compared to other approaches and on different real and simulated datasets. The CompPSA algorithm shows an accurate similarity measure between components. The algorithm gives the flexibility for the user to align the two RNA structures based on their weighted features (position, full length, and/or stem length). Moreover, the algorithm proves scalability and efficiency in time and memory performance.

Keywords: alignment, RNA secondary structure, pairwise, component-based, data mining

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Authors: Niyati Sharma, Om Anand, Sanjeev Kumar Prasad

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Assuming future sale value for any of the organizations is one of the major essential characteristics of tactical development. Walmart Sales Forecasting is the finest illustration to work with as a beginner; subsequently, it has the major retail data set. Walmart uses this sales estimate problem for hiring purposes also. We would like to analyzing how the internal and external effects of one of the largest companies in the US can walk out their Weekly Sales in the future. Demand forecasting is the planned prerequisite of products or services in the imminent on the basis of present and previous data and different stages of the market. Since all associations is facing the anonymous future and we do not distinguish in the future good demand. Hence, through exploring former statistics and recent market statistics, we envisage the forthcoming claim and building of individual goods, which are extra challenging in the near future. As a result of this, we are producing the required products in pursuance of the petition of the souk in advance. We will be using several machine learning models to test the exactness and then lastly, train the whole data by Using linear regression and fitting the training data into it. Accuracy is 8.88%. The extra trees regression model gives the best accuracy of 97.15%.

Keywords: random forest algorithm, linear regression algorithm, extra trees classifier, mean absolute error

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Authors: Chunye Gong, Ming Tie, Jie Liu, Weimin Bao, Xinbiao Gan, Shengguo Li, Bo Yang, Xuguang Chen, Tiaojie Xiao, Yang Sun

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Large-scale CFD simulation relies on high-performance parallel computing, and the load balance is the key role which affects the parallel efficiency. This paper focuses on the load-balancing problem of parallel CFD simulation with structured mesh. A mathematical model for this load-balancing problem is presented. The genetic algorithm, fitness computing, two-level code are designed. Optimal selector, robust operator, and local optimization operator are designed. The properties of the presented genetic algorithm are discussed in-depth. The effects of optimal selector, robust operator, and local optimization operator are proved by experiments. The experimental results of different test sets, DLR-F4, and aircraft design applications show the presented load-balancing algorithm is robust, quickly converged, and is useful in real engineering problems.

Keywords: genetic algorithm, load-balancing algorithm, optimal variation, local optimization

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Authors: Vidya Iyer, Suresh Babu Loganathan, Yuan Hwa Lee, Kwong Fah Koh

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Introduction: It has been recommended that every patient undergoes careful preoperative evaluation in a preoperative clinic to improve theatre utilization, reduce bed occupancy and avoid unnecessary cancellation due to inadequate optimisation, communication and administrative errors. It also gives an opportunity to counsel patients regarding different aspects of anaesthesia. Methodology: A retrospective audit of all the patients seen in preoperative assessment clinic, referral letters of all the patients postponed / referred to other sub specialities in the perioperative period from June 2012 - June 2013 was done. In our clinic, we retrieved patient records who were awaiting surgery pending clearance by other sub specialities. Those patients, who could continue with their scheduled date of surgery after having been referred, were not included in the file. We also studied details of same day cancellations from the data base, during the same study period. The reasons for cancellation were examined and defined as avoidable and unavoidable. Results: Less than 0.5% was postponed from the scheduled day of surgery. Less than 0.5% was cancelled on the day of surgery. Conclusions: Patients who undergo pre anaesthetic evaluation in a well-established clinic results in adequate preoperative patient optimisation, avoids unnecessary preoperative admission, efficient theatre utilisation and greater patient satisfaction. The benefits are the result of guidelines and timely update of them which are used by the junior doctors and trainees who run the clinic and a dedicated specialist to supervise them.

Keywords: preoperative assessment, clinic, referrals, cancellation

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Authors: Guilherme Baldo Carlos

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The flexible job-shop scheduling problem (FJSP) is an NP-hard combinatorial optimization problem, which can be applied to model several applications in a wide array of industries. This problem will have its importance increase due to the shift in the production mode that modern society is going through. The demands are increasing and for products personalized and customized. This work aims to apply a meta-heuristic called a genetic algorithm (GA) to solve this problem. A GA is a meta-heuristic inspired by the natural selection of Charles Darwin; it produces a population of individuals (solutions) and selects, mutates, and mates the individuals through generations in order to find a good solution for the problem. The results found indicate that the GA is suitable for FJSP solving.

Keywords: genetic algorithm, evolutionary algorithm, scheduling, flexible job-shop scheduling

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Authors: Yeongyu Choi, Ju H. Park, Ho-Youl Jung

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In this paper, we propose labeling based RANSAC algorithm for lane detection. Advanced driver assistance systems (ADAS) have been widely researched to avoid unexpected accidents. Lane detection is a necessary system to assist keeping lane and lane departure prevention. The proposed vision based lane detection method applies Canny edge detection, inverse perspective mapping (IPM), K-means algorithm, mathematical morphology operations and 8 connected-component labeling. Next, random samples are selected from each labeling region for RANSAC. The sampling method selects the points of lane with a high probability. Finally, lane parameters of straight line or curve equations are estimated. Through the simulations tested on video recorded at daytime and nighttime, we show that the proposed method has better performance than the existing RANSAC algorithm in various environments.

Keywords: Canny edge detection, k-means algorithm, RANSAC, inverse perspective mapping

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Authors: Fatemah Al-Baroud, Sudharani Shreenivas Kshatriya

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Kuwait Oil Company (KOC) is one of the companies for gas & oil production in Kuwait. The oil and gas industry is truly global; with operations conducted in every corner of the globe, the global community will rely heavily on oil and gas supplies. KOC has made many commitments to protect all due to KOC’s operations and operational releases. As per KOC’s strategy, the substantial increase in production activities will bring many challenges in managing various environmental hazards and stresses in the company. In order to handle those environmental challenges, the need of implementing effectively the health, safety, and environmental management system (HSEMS) is significant. And by implementing the HSEMS system properly, the environmental aspects of the activities, products, and services were identified, evaluated, and controlled in order to (i) Comply with local regulatory and other obligatory requirements; (ii) Comply with company policy and business requirements; and (iii) Reduce adverse environmental impact, including adverse impact to company reputation. Assessments for the Jurassic Production Facilities are being carried out as a part of the KOC HSEMS procedural requirement and monitoring the implementation of the relevant HSEMS procedures in the facilities. The assessments have been done by conducting series of theme audits using KOC’s audit protocol at JPFs. The objectives of the audits are to evaluate the compliance of the facilities towards the implementation of environmental procedures and the status of the KEPA requirement at all JPFs. The list of the facilities that were covered during the theme audit program are the following: (1) Jurassic Production Facility (JPF) – Sabriya (2) Jurassic Production Facility (JPF) – East Raudhatian (3) Jurassic Production Facility (JPF) – West Raudhatian (4)Early Production Facility (EPF 50). The auditing process comprehensively focuses on the application of KOC HSE MS procedures at JPFs and their ability to reduce the resultant negative impacts on the environment from the operations. Number of findings and observations were noted and highlighted in the audit reports and sent to all concerned controlling teams. The results of these audits indicated that the facilities, in general view, were in line with KOC HSE Procedures, and there were commitments in documenting all the HSE issues in the right records and plans. Further, implemented several control measures at JPFs that minimized/reduced the environmental impact, such as SRU were installed for sulphur recovery. Future scope and monitoring audit after a sufficient period of time will be carried out in conjunction with the controlling teams in order to verify the current status of the recommendations and evaluate the contractors' performance towards the required actions in preserving the environment.

Keywords: assessment of the environmental compliance, environmental and social impact assessment, kuwait environment public authority regulations, health, safety and environment management procedures, jurassic production facilities

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Authors: Felix Damilola Ajibade, Opeyemi O. Enoch, Taiwo Paul Fajusigbe

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This paper is centered on conducting an inquiry into the stability of the F* iterative algorithm to the fixed point of a strongly pseudo-contractive mapping in the framework of uniformly convex Banach spaces. To achieve the desired result, certain existing inequalities in convex Banach spaces were utilized, as well as the stability criteria of Harder and Hicks. Other necessary conditions for the stability of the F* algorithm on strong pseudo-contractive mapping were also obtained. Through a numerical approach, we prove that the F* iterative algorithm is H-stable for strongly pseudo-contractive mapping. Finally, the solution of the mixed-type Volterra-Fredholm functional non-linear integral equation is estimated using our results.

Keywords: stability, F* -iterative algorithm, pseudo-contractive mappings, uniformly convex Banach space, mixed-type Volterra-Fredholm integral equation

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Authors: Mallikarjuna Rao Yamarthy, Subramanyam Makam Venkata, Satya Prasad Kodati

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The main objective of the proposed work is to reduce the overall network traffic incurred by mobility management, packet delivery cost and to increase the resource utilization. The proposed algorithm, An Efficient Resource Management Algorithm (ERMA) for mobility management in wireless mesh networks, relies on pointer based mobility management scheme. Whenever a mesh client moves from one mesh router to another, the pointer is set up dynamically between the previous mesh router and current mesh router based on the distance constraints. The algorithm evaluated for signaling cost, data delivery cost and total communication cost performance metrics. The proposed algorithm is demonstrated for both internet sessions and intranet sessions. The proposed algorithm yields significantly better performance in terms of signaling cost, data delivery cost, and total communication cost.

Keywords: data delivery cost, mobility management, pointer forwarding, resource management, wireless mesh networks

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Authors: Jason Digalakis, John Cotronis

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Memetic algorithms (MAs) are useful for solving optimization problems. It is quite difficult to search the search space of the optimization problem with large dimensions. There is a challenge to use all the cores of the system. In this study, a sequential implementation of the memetic algorithm is converted into a concurrent version, which is executed on the cores of both CPU and GPU. For this reason, CUDA and OpenMP libraries are operated on the parallel algorithm to make a concurrent execution on CPU and GPU, respectively. The aim of this study is to compare CPU and GPU implementation of the memetic algorithm. For this purpose, fourteen benchmark functions are selected as test problems. The obtained results indicate that our approach leads to speedups up to five thousand times higher compared to one CPU thread while maintaining a reasonable results quality. This clearly shows that GPUs have the potential to acceleration of MAs and allow them to solve much more complex tasks.

Keywords: memetic algorithm, CUDA, GPU-based memetic algorithm, open multi processing, multimodal functions, unimodal functions, non-linear optimization problems

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Authors: C. Rekha, G. N. Krishnamurthy

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This paper attempts to develop a different approach for key scheduling algorithm which uses both Blowfish and AES algorithms. The main drawback of Blowfish algorithm is, it takes more time to create the S-box entries. To overcome this, we are replacing process of S-box creation in blowfish, by using key dependent S-box creation from AES without affecting the basic operation of blowfish. The method proposed in this paper uses good features of blowfish as well as AES and also this paper demonstrates the performance of blowfish and new algorithm by considering different aspects of security namely Encryption Quality, Key Sensitivity, and Correlation of horizontally adjacent pixels in an encrypted image.

Keywords: AES, blowfish, correlation coefficient, encryption quality, key sensitivity, s-box

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Authors: Flavio O. Torres, Maria J. Castilla, Rodrigo A. Augsburger, Pedro I. Cachana, Katherine S. Reyes

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In this paper, we present a scene-based nonuniformity correction method using a modified recursive least square algorithm with a feedback system on the updates. The feedback is designed to remove impulsive noise contamination images produced by a recursive least square algorithm by measuring the output of the proposed algorithm. The key advantage of the method is based on its capacity to estimate detectors parameters and then compensate for impulsive noise contamination image in a frame by frame basics. We define the algorithm and present several experimental results to demonstrate the efficacy of the proposed method in comparison to several previously published recursive least square-based methods. We show that the proposed method removes impulsive noise contamination image.

Keywords: infrared focal plane arrays, infrared imaging, least mean square, nonuniformity correction

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Authors: Shuhua Lai, Kairui Chen

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In this paper, we present a fast and efficient mesh coarsening algorithm for 3D triangular meshes. Theis approach can be applied to very complex 3D meshes of arbitrary topology and with millions of vertices. The algorithm is based on the clustering of the input mesh elements, which divides the faces of an input mesh into a given number of clusters for clustering purpose by approximating the Centroidal Voronoi Tessellation of the input mesh. Once a clustering is achieved, it provides us an efficient way to construct uniform tessellations, and therefore leads to good coarsening of polygonal meshes. With proliferation of 3D scanners, this coarsening algorithm is particularly useful for reverse engineering applications of 3D models, which in many cases are dense, non-uniform, irregular and arbitrary topology. Examples demonstrating effectiveness of the new algorithm are also included in the paper.

Keywords: coarsening, mesh clustering, shape approximation, mesh simplification

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Authors: Guenther Schuh, Michael Riesener, Frederic Diels

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Nowadays, manufacturing companies are faced with the challenge of meeting heterogeneous customer requirements in short product life cycles with a variety of product functions. So far, some of the functional requirements remain unknown until late stages of the product development. A way to handle these uncertainties is the highly iterative product development (HIP) approach. By structuring the development project as a highly iterative process, this method provides customer oriented and marketable products. There are first approaches for combined, hybrid models comprising deterministic-normative methods like the Stage-Gate process and empirical-adaptive development methods like SCRUM on a project management level. However, almost unconsidered is the question, which development scopes can preferably be realized with either empirical-adaptive or deterministic-normative approaches. In this context, a development scope constitutes a self-contained section of the overall development objective. Therefore, this paper focuses on a methodology that deals with the uncertainty of requirements within the early development stages and the corresponding selection of the most appropriate development approach. For this purpose, internal influencing factors like a company’s technology ability, the prototype manufacturability and the potential solution space as well as external factors like the market accuracy, relevance and volatility will be analyzed and combined into an Agile-Indicator. The Agile-Indicator is derived in three steps. First of all, it is necessary to rate each internal and external factor in terms of the importance for the overall development task. Secondly, each requirement has to be evaluated for every single internal and external factor appropriate to their suitability for empirical-adaptive development. Finally, the total sums of internal and external side are composed in the Agile-Indicator. Thus, the Agile-Indicator constitutes a company-specific and application-related criterion, on which the allocation of empirical-adaptive and deterministic-normative development scopes can be made. In a last step, this indicator will be used for a specific clustering of development scopes by application of the fuzzy c-means (FCM) clustering algorithm. The FCM-method determines sub-clusters within functional clusters based on the empirical-adaptive environmental impact of the Agile-Indicator. By means of the methodology presented in this paper, it is possible to classify requirements, which are uncertainly carried out by the market, into empirical-adaptive or deterministic-normative development scopes.

Keywords: agile, highly iterative development, agile-indicator, product development

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Authors: Seyed Mohsen Jameii

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Wireless underwater sensor networks are a type of sensor networks that are located in underwater environments and linked together by acoustic waves. The application of these kinds of network includes monitoring of pollutants (chemical, biological, and nuclear), oil fields detection, prediction of the likelihood of a tsunami in coastal areas, the use of wireless sensor nodes to monitor the passing submarines, and determination of appropriate locations for anchoring ships. This paper proposes a boundary coverage algorithm for intrusion detection in underwater sensor networks. In the first phase of the proposed algorithm, optimal deployment of nodes is done in the water. In the second phase, after the employment of nodes at the proper depth, clustering is executed to reduce the exchanges of messages between the sensors. In the third phase, the algorithm of "divide and conquer" is used to save energy and increase network efficiency. The simulation results demonstrate the efficiency of the proposed algorithm.

Keywords: boundary coverage, clustering, divide and ‎conquer, underwater sensor nodes

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Authors: Huma Sarwar, Muhammad Ishtiaq Ishaq, Junaid Aftab

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The hospitality sector contributes significantly to the global economy but it is also responsible for imposing adverse influences both environmentally and socially. The objective of this research is two-fold: (1) examining the direct impact of internal CSR and external CSR and indirect impact via organizational identification on creative performance and organizational citizenship behavior (OCB), and (2) determining the moderating role of ethical leadership in the relationships of internal- and external- CSR with organizational identification in a cross-cultural context. The data was were collected using multi-respondents and time-lagged data from 260 Pakistani and 239 UK respondents working in upscale hotels of the United Kingdom and Pakistan. The results demonstrate significant differences in both cultures as external CSR has a more substantial impact on organizational identification in the UK, whereas organizational identification has a relatively stronger influence on OCB and creative performance in collectivistic culture (i.e., Pakistan). The findings also confirmed that ethical leadership significantly moderates the relationship of internal- and external - CSR on organizational identification.

Keywords: Huma Sarwar, Muhammad Ishtiaq Ishaq, Junaid Aftab

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Authors: Tobias Horstmann, Thomas Le Garrec, Daniel-Ciprian Mincu, Emmanuel Lévêque

Abstract:

Despite the efficiency and low dissipation of the stream-collide formulation of the Lattice Boltzmann (LB) algorithm, which is nowadays implemented in many commercial LBM solvers, there are certain situations, e.g. mesh transition, in which a classical finite-volume or finite-difference formulation of the LB algorithm still bear advantages. In this paper, we present an algorithm that combines the node-based streaming of the distribution functions with a second-order finite volume discretization of the advection term of the BGK-LB equation on a uniform D2Q9 lattice. It is shown that such a coupling is possible for a multi-domain approach as long as the overlap, or buffer zone, between two domains, is achieved on at least 2Δx. This also implies that a direct coupling (without buffer zone) of a stream-collide and finite-volume LB algorithm on a single grid is not stable. The critical parameter in the coupling is the CFL number equal to 1 that is imposed by the stream-collide algorithm. Nevertheless, an explicit filtering step on the finite-volume domain can stabilize the solution. In a further investigation, we demonstrate how such a coupling can be used for mesh transition, resulting in an intrinsic conservation of mass over the interface.

Keywords: algorithm coupling, finite volume formulation, grid refinement, Lattice Boltzmann method

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Authors: Trung Hieu Tran, Jesse O'Hanley, Russell Fowler

Abstract:

When in-wheel wireless charging technology for electric vehicles becomes mature, a need for such integrated charging stations network development is essential. In this paper, we thus investigate the optimisation problem of in-wheel wireless electric vehicle charging network design. A mixed-integer linear programming model is formulated to solve into optimality the problem. In addition, a meta-heuristic algorithm is proposed for efficiently solving large-sized instances within a reasonable computation time. A parallel computing strategy is integrated into the algorithm to speed up its computation time. Experimental results carried out on the benchmark instances show that our model and algorithm can find the optimal solutions and their potential for practical applications.

Keywords: electric vehicle, wireless charging station, mathematical programming, meta-heuristic algorithm, parallel computing

Procedia PDF Downloads 79