Search results for: manual handling
1075 A New Evolutionary Algorithm for Multi-Objective Cylindrical Spur Gear Design Optimization
Authors: Hammoudi Abderazek
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The present paper introduces a modified adaptive mixed differential evolution (MAMDE) to select the main geometry parameters of specific cylindrical spur gear. The developed algorithm used the self-adaptive mechanism in order to update the values of mutation and crossover factors. The feasibility rules are used in the selection phase to improve the search exploration of MAMDE. Moreover, the elitism is performed to keep the best individual found in each generation. For the constraints handling the normalization method is used to treat each constraint design equally. The finite element analysis is used to confirm the optimization results for the maximum bending resistance. The simulation results reached in this paper indicate clearly that the proposed algorithm is very competitive in precision gear design optimization.Keywords: evolutionary algorithm, spur gear, tooth profile, meta-heuristics
Procedia PDF Downloads 1321074 Rim Size Optimization Using Mathematical Modelling
Authors: M. Tan, N. N. Wan, N. Ramli, N. H. Hassan
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Car drivers would always like to have custom wheel on their car for two reasons; to improve their car's aesthetic beauty and to improve their car handling. As the size of the rims or wheels played an important role in influencing the way of car handles around turns, this paper aims to present the optimality of rim size that drivers should have known while changing their rim. There are three factors that drivers should have considered while changing their rim: rim size, its weight and material of which they are made. Using mathematical analysis, this paper will focus on only one factor, which is rim size. Factors that are considered in calculating the optimum rim size are the vehicle rim radius, tire height and weight, and aspect ratio. This paper has found that there are limitations in percentage change in rim size from the original tire size. Failure to have the right offset size may cause problems in maneuvering the vehicle.Keywords: mathematical analysis, optimum wheel size, percentage change, custom wheel
Procedia PDF Downloads 4931073 Efficient Passenger Counting in Public Transport Based on Machine Learning
Authors: Chonlakorn Wiboonsiriruk, Ekachai Phaisangittisagul, Chadchai Srisurangkul, Itsuo Kumazawa
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Public transportation is a crucial aspect of passenger transportation, with buses playing a vital role in the transportation service. Passenger counting is an essential tool for organizing and managing transportation services. However, manual counting is a tedious and time-consuming task, which is why computer vision algorithms are being utilized to make the process more efficient. In this study, different object detection algorithms combined with passenger tracking are investigated to compare passenger counting performance. The system employs the EfficientDet algorithm, which has demonstrated superior performance in terms of speed and accuracy. Our results show that the proposed system can accurately count passengers in varying conditions with an accuracy of 94%.Keywords: computer vision, object detection, passenger counting, public transportation
Procedia PDF Downloads 1561072 A Molding Surface Auto-inspection System
Authors: Ssu-Han Chen, Der-Baau Perng
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Molding process in IC manufacturing secures chips against the harms done by hot, moisture or other external forces. While a chip was being molded, defects like cracks, dilapidation, or voids may be embedding on the molding surface. The molding surfaces the study poises to treat and the ones on the market, though, differ in the surface where texture similar to defects is everywhere. Manual inspection usually passes over low-contrast cracks or voids; hence an automatic optical inspection system for molding surface is necessary. The proposed system is consisted of a CCD, a coaxial light, a back light as well as a motion control unit. Based on the property of statistical textures of the molding surface, a series of digital image processing and classification procedure is carried out. After training of the parameter associated with above algorithm, result of the experiment suggests that the accuracy rate is up to 93.75%, contributing to the inspection quality of IC molding surface.Keywords: molding surface, machine vision, statistical texture, discrete Fourier transformation
Procedia PDF Downloads 4321071 Development and Implementation of Curvature Dependent Force Correction Algorithm for the Planning of Forced Controlled Robotic Grinding
Authors: Aiman Alshare, Sahar Qaadan
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A curvature dependent force correction algorithm for planning force controlled grinding process with off-line programming flexibility is designed for ABB industrial robot, in order to avoid the manual interface during the process. The machining path utilizes a spline curve fit that is constructed from the CAD data of the workpiece. The fitted spline has a continuity of the second order to assure path smoothness. The implemented algorithm computes uniform forces normal to the grinding surface of the workpiece, by constructing a curvature path in the spatial coordinates using the spline method.Keywords: ABB industrial robot, grinding process, offline programming, CAD data extraction, force correction algorithm
Procedia PDF Downloads 3641070 A Study on the Solutions of the 2-Dimensional and Forth-Order Partial Differential Equations
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In this study, we will carry out a comparative study between the reduced differential transform method, the adomian decomposition method, the variational iteration method and the homotopy analysis method. These methods are used in many fields of engineering. This is been achieved by handling a kind of 2-Dimensional and forth-order partial differential equations called the Kuramoto–Sivashinsky equations. Three numerical examples have also been carried out to validate and demonstrate efficiency of the four methods. Furthermost, it is shown that the reduced differential transform method has advantage over other methods. This method is very effective and simple and could be applied for nonlinear problems which used in engineering.Keywords: reduced differential transform method, adomian decomposition method, variational iteration method, homotopy analysis method
Procedia PDF Downloads 4351069 Enhanced Visual Sharing Method for Medical Image Security
Authors: Kalaivani Pachiappan, Sabari Annaji, Nithya Jayakumar
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In recent years, Information security has emerged as foremost challenges in many fields. Especially in medical information systems security is a major issue, in handling reports such as patients’ diagnosis and medical images. These sensitive data require confidentiality for transmission purposes. Image sharing is a secure and fault-tolerant method for protecting digital images, which can use the cryptography techniques to reduce the information loss. In this paper, visual sharing method is proposed which embeds the patient’s details into a medical image. Then the medical image can be divided into numerous shared images and protected by various users. The original patient details and medical image can be retrieved by gathering the shared images.Keywords: information security, medical images, cryptography, visual sharing
Procedia PDF Downloads 4161068 Impact of Work Experience and Gender on Decisional Conflict
Authors: Mohsin Aslam Khan
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Decision making tendency varies in people with different socio demographics. This study was conducted to identify the impact of work experience on decisional conflict and whether there is a gender differences in decisional conflict. Convenience sampling was more appropriate for this exploratory research. AM O’ Connor decisional conflict scale, (1995) with cronbach alpha 0.900 was administered on sample size of 109 participants (62males, 47females). The responses were scored according to the AM O’ Connor decisional conflict scale manual, (1995). The results of the study indicate that work experience has no significant impact on decisional conflict, whereas gender differences in decisional conflict illustrates significant mean score differences among male and female participants.Keywords: decision making, decisional conflict, gender decision making, work experience
Procedia PDF Downloads 6141067 Personal Information Classification Based on Deep Learning in Automatic Form Filling System
Authors: Shunzuo Wu, Xudong Luo, Yuanxiu Liao
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Recently, the rapid development of deep learning makes artificial intelligence (AI) penetrate into many fields, replacing manual work there. In particular, AI systems also become a research focus in the field of automatic office. To meet real needs in automatic officiating, in this paper we develop an automatic form filling system. Specifically, it uses two classical neural network models and several word embedding models to classify various relevant information elicited from the Internet. When training the neural network models, we use less noisy and balanced data for training. We conduct a series of experiments to test my systems and the results show that our system can achieve better classification results.Keywords: artificial intelligence and office, NLP, deep learning, text classification
Procedia PDF Downloads 2021066 Design and Implementation of Bluetooth Controlled Autonomous Vehicle
Authors: Amanuel Berhanu Kesamo
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This paper presents both circuit simulation and hardware implementation of a robot vehicle that can be either controlled manually via Bluetooth with video streaming or navigate autonomously to a target point by avoiding obstacles. In manual mode, the user controls the mobile robot using C# windows form interfaced via Bluetooth. The camera mounted on the robot is used to capture and send the real time video to the user. In autonomous mode, the robot plans the shortest path to the target point while avoiding obstacles along the way. Ultrasonic sensor is used for sensing the obstacle in its environment. An efficient path planning algorithm is implemented to navigate the robot along optimal route.Keywords: Arduino Uno, autonomous, Bluetooth module, path planning, remote controlled robot, ultra sonic sensor
Procedia PDF Downloads 1451065 Auto Classification of Multiple ECG Arrhythmic Detection via Machine Learning Techniques: A Review
Authors: Ng Liang Shen, Hau Yuan Wen
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Arrhythmia analysis of ECG signal plays a major role in diagnosing most of the cardiac diseases. Therefore, a single arrhythmia detection of an electrocardiographic (ECG) record can determine multiple pattern of various algorithms and match accordingly each ECG beats based on Machine Learning supervised learning. These researchers used different features and classification methods to classify different arrhythmia types. A major problem in these studies is the fact that the symptoms of the disease do not show all the time in the ECG record. Hence, a successful diagnosis might require the manual investigation of several hours of ECG records. The point of this paper presents investigations cardiovascular ailment in Electrocardiogram (ECG) Signals for Cardiac Arrhythmia utilizing examination of ECG irregular wave frames via heart beat as correspond arrhythmia which with Machine Learning Pattern Recognition.Keywords: electrocardiogram, ECG, classification, machine learning, pattern recognition, detection, QRS
Procedia PDF Downloads 3761064 Predicting Survival in Cancer: How Cox Regression Model Compares to Artifial Neural Networks?
Authors: Dalia Rimawi, Walid Salameh, Amal Al-Omari, Hadeel AbdelKhaleq
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Predication of Survival time of patients with cancer, is a core factor that influences oncologist decisions in different aspects; such as offered treatment plans, patients’ quality of life and medications development. For a long time proportional hazards Cox regression (ph. Cox) was and still the most well-known statistical method to predict survival outcome. But due to the revolution of data sciences; new predication models were employed and proved to be more flexible and provided higher accuracy in that type of studies. Artificial neural network is one of those models that is suitable to handle time to event predication. In this study we aim to compare ph Cox regression with artificial neural network method according to data handling and Accuracy of each model.Keywords: Cox regression, neural networks, survival, cancer.
Procedia PDF Downloads 2021063 Machine Learning Methods for Network Intrusion Detection
Authors: Mouhammad Alkasassbeh, Mohammad Almseidin
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Network security engineers work to keep services available all the time by handling intruder attacks. Intrusion Detection System (IDS) is one of the obtainable mechanisms that is used to sense and classify any abnormal actions. Therefore, the IDS must be always up to date with the latest intruder attacks signatures to preserve confidentiality, integrity, and availability of the services. The speed of the IDS is a very important issue as well learning the new attacks. This research work illustrates how the Knowledge Discovery and Data Mining (or Knowledge Discovery in Databases) KDD dataset is very handy for testing and evaluating different Machine Learning Techniques. It mainly focuses on the KDD preprocess part in order to prepare a decent and fair experimental data set. The J48, MLP, and Bayes Network classifiers have been chosen for this study. It has been proven that the J48 classifier has achieved the highest accuracy rate for detecting and classifying all KDD dataset attacks, which are of type DOS, R2L, U2R, and PROBE. Procedia PDF Downloads 2351062 Simulations of a Jet Impinging on a Flat Plate
Authors: Reda Mankbadi
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In this paper we explore the use of a second-order unstructured-grid, finite-volume code for direct noise prediction. We consider a Mach 1.5 jet impinging on a perpendicular flat plate. Hybrid LES-RANS simulations are used to calculate directly both the flow field and the radiated sound. The ANSYS Fluent commercial code is utilized for the calculations. The acoustic field is obtained directly from the simulations and is compared with the integral approach of Ffowcs Williams-Hawkings (FWH). Results indicate the existence of a preferred radiation angle. The spectrum obtained is in good agreement with observations. This points out to the possibility of handling the effects of complicated geometries on noise radiation by using unstructured second-orders codes.Keywords: CFD, Ffowcs Williams-Hawkings (FWH), imping jet, ANSYS fluent commercial code, hybrid LES-RANS simulations
Procedia PDF Downloads 4531061 Cooperative Learning Mechanism in Intelligent Multi-Agent System
Authors: Ayman M. Mansour, Bilal Hawashin, Mohammed A. Mansour
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In this paper, we propose a cooperative learning mechanism in a multi-agent intelligent system. The basic idea is that intelligent agents are capable of collaborating with one another by sharing their knowledge. The agents will start collaboration by providing their knowledge rules to the other agents. This will allow the most important and insightful detection rules produced by the most experienced agent to bubble up for the benefit of the entire agent community. The updated rules will lead to improving the agents’ decision performance. To evaluate our approach, we designed a five–agent system and implemented it using JADE and FuzzyJess software packages. The agents will work with each other to make a decision about a suspicious medical case. This system provides quick response rate and the decision is faster than the manual methods. This will save patients life.Keywords: intelligent, multi-agent system, cooperative, fuzzy, learning
Procedia PDF Downloads 6871060 Mobile Application Tool for Individual Maintenance Users on High-Rise Residential Buildings in South Korea
Authors: H. Cha, J. Kim, D. Kim, J. Shin, K. Lee
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Since 1980's, the rapid economic growth resulted in so many aged apartment buildings in South Korea. Nevertheless, there is insufficient maintenance practice of buildings. In this study, to facilitate the building maintenance the authors classified the building defects into three levels according to their level of performance and developed a mobile application tool based on each level's appropriate feedback. The feedback structure consisted of 'Maintenance manual phase', 'Online feedback phase', 'Repair work phase of the specialty contractors'. In order to implement each phase the authors devised the necessary database for each phase and created a prototype system that can develop on its own. The authors expect that the building users can easily maintain their buildings by using this application.Keywords: building defect, maintenance practice, mobile application, system algorithm
Procedia PDF Downloads 1881059 The Paralinguistic Function of Emojis in Twitter Communication
Authors: Yasmin Tantawi, Mary Beth Rosson
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In response to the dearth of information about emoji use for different purposes in different settings, this paper investigates the paralinguistic function of emojis within Twitter communication in the United States. To conduct this investigation, the Twitter feeds from 16 population centers spread throughout the United States were collected from the Twitter public API. One hundred tweets were collected from each population center, totaling to 1,600 tweets. Tweets containing emojis were next extracted using the “emot” Python package; these were then analyzed via the IBM Watson API Natural Language Understanding module to identify the topics discussed. A manual content analysis was then conducted to ascertain the paralinguistic and emotional features of the emojis used in these tweets. We present our characterization of emoji usage in Twitter and discuss implications for the design of Twitter and other text-based communication tools.Keywords: computer-mediated communication, content analysis, paralinguistics, sociology
Procedia PDF Downloads 1621058 Application of IF Rough Data on Knowledge Towards Malaria of Rural Tribal Communities in Tripura
Authors: Chhaya Gangwal, R. N. Bhaumik, Shishir Kumar
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Handling uncertainty and impreciseness of knowledge appears to be a challenging task in Information Systems. Intuitionistic fuzzy (IF) and rough set theory enhances databases by allowing it for the management of uncertainty and impreciseness. This paper presents a new efficient query optimization technique for the multi-valued or imprecise IF rough database. The usefulness of this technique was illustrated on malaria knowledge from the rural tribal communities of Tripura where most of the information is multi-valued and imprecise. Then, the querying about knowledge on malaria is executed into SQL server to make the implementation of IF rough data querying simpler.Keywords: intuitionistic fuzzy set, rough set, relational database, IF rough relational database
Procedia PDF Downloads 4461057 Analysis on Cyber Threat Actors Targeting Automated Border Security Systems
Authors: Mirko Sailio
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Border crossing automatization reduces required human resources in handling people crossing borders. As technology replaces and augments the work done by border officers, new cyber threats arise to threaten border security. This research analyses the current cyber threat actors and their capabilities. The analysis is conducted by gathering the threat actor data from a wide range of public sources. A model for a general border automatization system is presented, and its most significant cyber-security attributes are then compared to threat actor activity and capabilities in order to predict priorities in securing such systems. Organized crime and nation-state actors present the clearest threat to border cyber-security, and additional focus is given to their motivations and activities.Keywords: border automation, cyber-security, threat actors, border cyber-security
Procedia PDF Downloads 2051056 Model Based Optimization of Workplace Ergonomics by Workpiece and Resource Positioning
Authors: Edward Hage, Pieter Lietaert, Gabriel Abedrabbo
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Musculoskeletal disorders are an important category of work-related diseases. They are often caused by working in non-ergonomic postures and are preventable with proper workplace design, possibly including human-machine collaboration. This paper presents a methodology and a supporting software prototype to design a simple assembly cell with minimal ergonomic risk. The methodology helps to determine the optimal position and orientation of workpieces and workplace resources for specific operator assembly actions. The methodology is tested on an industrial use case: a collaborative robot (cobot) assisted assembly of a clamping device. It is shown that the automated methodology results in a workplace design with significantly reduced ergonomic risk to the operator compared to a manual design of the cell.Keywords: ergonomics optimization, design for ergonomics, workplace design, pose generation
Procedia PDF Downloads 1251055 Musical Instrument Recognition in Polyphonic Audio Through Convolutional Neural Networks and Spectrograms
Authors: Rujia Chen, Akbar Ghobakhlou, Ajit Narayanan
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This study investigates the task of identifying musical instruments in polyphonic compositions using Convolutional Neural Networks (CNNs) from spectrogram inputs, focusing on binary classification. The model showed promising results, with an accuracy of 97% on solo instrument recognition. When applied to polyphonic combinations of 1 to 10 instruments, the overall accuracy was 64%, reflecting the increasing challenge with larger ensembles. These findings contribute to the field of Music Information Retrieval (MIR) by highlighting the potential and limitations of current approaches in handling complex musical arrangements. Future work aims to include a broader range of musical sounds, including electronic and synthetic sounds, to improve the model's robustness and applicability in real-time MIR systems.Keywords: binary classifier, CNN, spectrogram, instrument
Procedia PDF Downloads 851054 Empirical Research on Preference for Conflict Resolution Styles of Owners and Contractors in China
Authors: Junqi Zhao, Yongqiang Chen
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The preference for different conflict resolution styles are influenced by cultural background and power distance of two parties involving in conflict. This research put forward 7 hypotheses and tested the preference differences of the five conflict resolution styles between Chinese owner and contractor as well as the preference differences concerning the same style between two parties. The research sample includes 202 practitioners from construction enterprises in mainland China. Research result found that theories concerning conflict resolution styles could be applied in the Chinese construction industry. Some results of this research were not in line with former research, and this research also gave explanation to the differences from the characteristics of construction projects. Based on the findings, certain suggestions were made to serve as a guidance for managers to choose appropriate conflict resolution styles for a better handling of conflict.Keywords: Chinese owner and contractor, conflict, construction project, conflict resolution styles
Procedia PDF Downloads 5331053 Proposed Alternative System for Existing Traffic Signal System
Authors: Alluri Swaroopa, L. V. N. Prasad
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Alone with fast urbanization in world, traffic control problem became a big issue in urban construction. Having an efficient and reliable traffic control system is crucial to macro-traffic control. Traffic signal is used to manage conflicting requirement by allocating different sets of mutually compatible traffic movement during distinct time interval. Many approaches have been made proposed to solve this discrete stochastic problem. Recognizing the need to minimize right-of-way impacts while efficiently handling the anticipated high traffic volumes, the proposed alternative system gives effective design. This model allows for increased traffic capacity and reduces delays by eliminating a step in maneuvering through the freeway interchange. The concept proposed in this paper involves construction of bridges and ramps at intersection of four roads to control the vehicular congestion and to prevent traffic breakdown.Keywords: bridges, junctions, ramps, urban traffic control
Procedia PDF Downloads 5541052 Teachers’ Perceptions on Communicating with Students Who Are Deaf-Blind in Regular Classes
Authors: Phillimon Mahanya
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Learners with deaf-blindness use touch to communicate. However, teachers are not well versed with tactile communication technicalities. Lack of technical know-how is compounded with a lack of standardisation of the tactile signs the world over. Thus, this study arose from the need to have efficient and effective tactile sign communication for learners who are deaf-blind. A qualitative approach that adopted a case study design was used. A sample of 22 participants comprising school administrators and teachers was purposively drawn from the institutions that enrolled learners who are deaf-blind. Data generated using semi-structured interviews, non-participant observations and document analysis were thematically analysed. It emerged that administrators and teachers used mammoth and solo touches that are not standardised to communicate with learners who are deaf-blind. It was recommended that there should be a standardised tactile sign manual in Zimbabwe to promote the inclusion of learners who are deaf-blind.Keywords: communication, deaf-blind, signing, tactile
Procedia PDF Downloads 2401051 Practical Methods for Automatic MC/DC Test Cases Generation of Boolean Expressions
Authors: Sekou Kangoye, Alexis Todoskoff, Mihaela Barreau
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Modified Condition/Decision Coverage (MC/DC) is a structural coverage criterion that aims to prove that all conditions involved in a Boolean expression can influence the result of that expression. In the context of automotive, MC/DC is highly recommended and even required for most security and safety applications testing. However, due to complex Boolean expressions that often embedded in those applications, generating a set of MC/DC compliant test cases for any of these expressions is a nontrivial task and can be time consuming for testers. In this paper we present an approach to automatically generate MC/DC test cases for any Boolean expression. We introduce novel techniques, essentially based on binary trees to quickly and optimally generate MC/DC test cases for the expressions. Thus, the approach can be used to reduce the manual testing effort of testers.Keywords: binary trees, MC/DC, test case generation, nontrivial task
Procedia PDF Downloads 4511050 Establishing the Optimum Location of a Single Tower Crane Using a Smart Mathematical Model
Authors: Yasser Abo El-Magd, Wael Fawzy Mohamed
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Due to the great development in construction and building field, there are many projects and huge works appeared which consume many construction materials. Accordingly, that causes difficulty in handling traditional transportation means (ordinary cranes) due to their limited capacity; there is an urgent need to use high capacity cranes such as tower cranes. However, with regard to their high expense, we have to take into consideration selecting what type of cranes to be utilized which has been discussed by many researchers. In this research, a proposed technique was created to select the suitable type of crane and the best place for crane erection, in addition to minimum radius for requested crane in order to minimize cost. To fulfill that target, a computer program is designed to numerate these problems, demonstrating an example explaining how to apply program and the result donated the best place.Keywords: tower crane, jib length, operating time, location, feasible area
Procedia PDF Downloads 2261049 Identifying Biomarker Response Patterns to Vitamin D Supplementation in Type 2 Diabetes Using K-means Clustering: A Meta-Analytic Approach to Glycemic and Lipid Profile Modulation
Authors: Oluwafunmibi Omotayo Fasanya, Augustine Kena Adjei
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Background and Aims: This meta-analysis aimed to evaluate the effect of vitamin D supplementation on key metabolic and cardiovascular parameters, such as glycated hemoglobin (HbA1C), fasting blood sugar (FBS), low-density lipoprotein (LDL), high-density lipoprotein (HDL), systolic blood pressure (SBP), and total vitamin D levels in patients with Type 2 diabetes mellitus (T2DM). Methods: A systematic search was performed across databases, including PubMed, Scopus, Embase, Web of Science, Cochrane Library, and ClinicalTrials.gov, from January 1990 to January 2024. A total of 4,177 relevant studies were initially identified. Using an unsupervised K-means clustering algorithm, publications were grouped based on common text features. Maximum entropy classification was then applied to filter studies that matched a pre-identified training set of 139 potentially relevant articles. These selected studies were manually screened for relevance. A parallel manual selection of all initially searched studies was conducted for validation. The final inclusion of studies was based on full-text evaluation, quality assessment, and meta-regression models using random effects. Sensitivity analysis and publication bias assessments were also performed to ensure robustness. Results: The unsupervised K-means clustering algorithm grouped the patients based on their responses to vitamin D supplementation, using key biomarkers such as HbA1C, FBS, LDL, HDL, SBP, and total vitamin D levels. Two primary clusters emerged: one representing patients who experienced significant improvements in these markers and another showing minimal or no change. Patients in the cluster associated with significant improvement exhibited lower HbA1C, FBS, and LDL levels after vitamin D supplementation, while HDL and total vitamin D levels increased. The analysis showed that vitamin D supplementation was particularly effective in reducing HbA1C, FBS, and LDL within this cluster. Furthermore, BMI, weight gain, and disease duration were identified as factors that influenced cluster assignment, with patients having lower BMI and shorter disease duration being more likely to belong to the improvement cluster. Conclusion: The findings of this machine learning-assisted meta-analysis confirm that vitamin D supplementation can significantly improve glycemic control and reduce the risk of cardiovascular complications in T2DM patients. The use of automated screening techniques streamlined the process, ensuring the comprehensive evaluation of a large body of evidence while maintaining the validity of traditional manual review processes.Keywords: HbA1C, T2DM, SBP, FBS
Procedia PDF Downloads 171048 Design of Low-Maintenance Sewer Pump Stations with High-Security Measures for Municipal Applications
Authors: H. V. Smit, V. H. J. de Wet
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South African municipalities are dealing with aging and dilapidated infrastructure while faced with challenges in the form of expanding informal settlements, vandalism, theft, and a lack of maintenance which place even more pressure on existing infrastructure. The existing infrastructure was never designed to cater to these challenges, and this becomes evident when evaluating the current state of many municipal sewer pump stations. A need has thus arisen to develop a sewer pump station design concept that will address these challenges and allow for a long-term sustainable solution. This article deals with the design concepts which have been developed for sewer pump stations for an effective reduction in maintenance, improved grit handling, improvement to the operation and maintenance working conditions, and the adoption of high-security design philosophy.Keywords: high security, low maintenance, municipal application, sewer pump station
Procedia PDF Downloads 1091047 Modern Imputation Technique for Missing Data in Linear Functional Relationship Model
Authors: Adilah Abdul Ghapor, Yong Zulina Zubairi, Rahmatullah Imon
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Missing value problem is common in statistics and has been of interest for years. This article considers two modern techniques in handling missing data for linear functional relationship model (LFRM) namely the Expectation-Maximization (EM) algorithm and Expectation-Maximization with Bootstrapping (EMB) algorithm using three performance indicators; namely the mean absolute error (MAE), root mean square error (RMSE) and estimated biased (EB). In this study, we applied the methods of imputing missing values in the LFRM. Results of the simulation study suggest that EMB algorithm performs much better than EM algorithm in both models. We also illustrate the applicability of the approach in a real data set.Keywords: expectation-maximization, expectation-maximization with bootstrapping, linear functional relationship model, performance indicators
Procedia PDF Downloads 4001046 A New Floating Point Implementation of Base 2 Logarithm
Authors: Ahmed M. Mansour, Ali M. El-Sawy, Ahmed T. Sayed
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Logarithms reduce products to sums and powers to products; they play an important role in signal processing, communication and information theory. They are primarily used for hardware calculations, handling multiplications, divisions, powers, and roots effectively. There are three commonly used bases for logarithms; the logarithm with base-10 is called the common logarithm, the natural logarithm with base-e and the binary logarithm with base-2. This paper demonstrates different methods of calculation for log2 showing the complexity of each and finds out the most accurate and efficient besides giving in- sights to their hardware design. We present a new method called Floor Shift for fast calculation of log2, and then we combine this algorithm with Taylor series to improve the accuracy of the output, we illustrate that by using two examples. We finally compare the algorithms and conclude with our remarks.Keywords: logarithms, log2, floor, iterative, CORDIC, Taylor series
Procedia PDF Downloads 535