Search results for: scalable automation testing
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3689

Search results for: scalable automation testing

2339 Imputation of Incomplete Large-Scale Monitoring Count Data via Penalized Estimation

Authors: Mohamed Dakki, Genevieve Robin, Marie Suet, Abdeljebbar Qninba, Mohamed A. El Agbani, Asmâa Ouassou, Rhimou El Hamoumi, Hichem Azafzaf, Sami Rebah, Claudia Feltrup-Azafzaf, Nafouel Hamouda, Wed a.L. Ibrahim, Hosni H. Asran, Amr A. Elhady, Haitham Ibrahim, Khaled Etayeb, Essam Bouras, Almokhtar Saied, Ashrof Glidan, Bakar M. Habib, Mohamed S. Sayoud, Nadjiba Bendjedda, Laura Dami, Clemence Deschamps, Elie Gaget, Jean-Yves Mondain-Monval, Pierre Defos Du Rau

Abstract:

In biodiversity monitoring, large datasets are becoming more and more widely available and are increasingly used globally to estimate species trends and con- servation status. These large-scale datasets challenge existing statistical analysis methods, many of which are not adapted to their size, incompleteness and heterogeneity. The development of scalable methods to impute missing data in incomplete large-scale monitoring datasets is crucial to balance sampling in time or space and thus better inform conservation policies. We developed a new method based on penalized Poisson models to impute and analyse incomplete monitoring data in a large-scale framework. The method al- lows parameterization of (a) space and time factors, (b) the main effects of predic- tor covariates, as well as (c) space–time interactions. It also benefits from robust statistical and computational capability in large-scale settings. The method was tested extensively on both simulated and real-life waterbird data, with the findings revealing that it outperforms six existing methods in terms of missing data imputation errors. Applying the method to 16 waterbird species, we estimated their long-term trends for the first time at the entire North African scale, a region where monitoring data suffer from many gaps in space and time series. This new approach opens promising perspectives to increase the accuracy of species-abundance trend estimations. We made it freely available in the r package ‘lori’ (https://CRAN.R-project.org/package=lori) and recommend its use for large- scale count data, particularly in citizen science monitoring programmes.

Keywords: biodiversity monitoring, high-dimensional statistics, incomplete count data, missing data imputation, waterbird trends in North-Africa

Procedia PDF Downloads 158
2338 Rapid and Culture-Independent Detection of Staphylococcus Aureus by PCR Based Protocols

Authors: V. Verma, Syed Riyaz-ul-Hassan

Abstract:

Staphylococcus aureus is one of the most commonly found pathogenic bacteria and is hard to eliminate from the human environment. It is responsible for many nosocomial infections, besides being the main causative agent of food intoxication by virtue of its variety of enterotoxins. Routine detection of S. aureus in food is usually carried out by traditional methods based on morphological and biochemical characterization. These methods are time-consuming and tedious. In addition, misclassifications with automated susceptibility testing systems or commercially available latex agglutination kits have been reported by several workers. Consequently, there is a need for methods to specifically discriminate S. aureus from other staphylococci as quickly as possible. Data on protocols developed using molecular means like PCR technology will be presented for rapid and specific detection of this pathogen in food, clinical and environmental samples, especially milk.

Keywords: food Pathogens, PCR technology, rapid and specific detection, staphylococcus aureus

Procedia PDF Downloads 513
2337 Heterogeneous Artifacts Construction for Software Evolution Control

Authors: Mounir Zekkaoui, Abdelhadi Fennan

Abstract:

The software evolution control requires a deep understanding of the changes and their impact on different system heterogeneous artifacts. And an understanding of descriptive knowledge of the developed software artifacts is a prerequisite condition for the success of the evolutionary process. The implementation of an evolutionary process is to make changes more or less important to many heterogeneous software artifacts such as source code, analysis and design models, unit testing, XML deployment descriptors, user guides, and others. These changes can be a source of degradation in functional, qualitative or behavioral terms of modified software. Hence the need for a unified approach for extraction and representation of different heterogeneous artifacts in order to ensure a unified and detailed description of heterogeneous software artifacts, exploitable by several software tools and allowing to responsible for the evolution of carry out the reasoning change concerned.

Keywords: heterogeneous software artifacts, software evolution control, unified approach, meta model, software architecture

Procedia PDF Downloads 447
2336 Enhancing Technical Trading Strategy on the Bitcoin Market using News Headlines and Language Models

Authors: Mohammad Hosein Panahi, Naser Yazdani

Abstract:

we present a technical trading strategy that leverages the FinBERT language model and financial news analysis with a focus on news related to a subset of Nasdaq 100 stocks. Our approach surpasses the baseline Range Break-out strategy in the Bitcoin market, yielding a remarkable 24.8% increase in the win ratio for all Friday trades and an impressive 48.9% surge in short trades specifically on Fridays. Moreover, we conduct rigorous hypothesis testing to establish the statistical significance of these improvements. Our findings underscore considerable potential of our NLP-driven approach in enhancing trading strategies and achieving greater profitability within financial markets.

Keywords: quantitative finance, technical analysis, bitcoin market, NLP, language models, FinBERT, technical trading

Procedia PDF Downloads 76
2335 Machine Learning Methods for Network Intrusion Detection

Authors: Mouhammad Alkasassbeh, Mohammad Almseidin

Abstract:

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.

Keywords: IDS, DDoS, MLP, KDD

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2334 Methods Used to Achieve Airtightness of 0.07 Ach@50Pa for an Industrial Building

Authors: G. Wimmers

Abstract:

The University of Northern British Columbia needed a new laboratory building for the Master of Engineering in Integrated Wood Design Program and its new Civil Engineering Program. Since the University is committed to reducing its environmental footprint and because the Master of Engineering Program is actively involved in research of energy efficient buildings, the decision was made to request the energy efficiency of the Passive House Standard in the Request for Proposals. The building is located in Prince George in Northern British Columbia, a city located at the northern edge of climate zone 6 with an average low between -8 and -10.5 in the winter months. The footprint of the building is 30m x 30m with a height of about 10m. The building consists of a large open space for the shop and laboratory with a small portion of the floorplan being two floors, allowing for a mezzanine level with a few offices as well as mechanical and storage rooms. The total net floor area is 1042m² and the building’s gross volume 9686m³. One key requirement of the Passive House Standard is the airtight envelope with an airtightness of < 0.6 ach@50Pa. In the past, we have seen that this requirement can be challenging to reach for industrial buildings. When testing for air tightness, it is important to test in both directions, pressurization, and depressurization, since the airflow through all leakages of the building will, in reality, happen simultaneously in both directions. A specific detail or situation such as overlapping but not sealed membranes might be airtight in one direction, due to the valve effect, but are opening up when tested in the opposite direction. In this specific project, the advantage was the overall very compact envelope and the good volume to envelope area ratio. The building had to be very airtight and the details for the windows and doors installation as well as all transitions from walls to roof and floor, the connections of the prefabricated wall panels and all penetrations had to be carefully developed to allow for maximum airtightness. The biggest challenges were the specific components of this industrial building, the large bay door for semi-trucks and the dust extraction system for the wood processing machinery. The testing was carried out in accordance with EN 132829 (method A) as specified in the International Passive House Standard and the volume calculation was also following the Passive House guideline resulting in a net volume of 7383m3, excluding all walls, floors and suspended ceiling volumes. This paper will explore the details and strategies used to achieve an airtightness of 0.07 ach@50Pa, to the best of our knowledge the lowest value achieved in North America so far following the test protocol of the International Passive House Standard and discuss the crucial steps throughout the project phases and the most challenging details.

Keywords: air changes, airtightness, envelope design, industrial building, passive house

Procedia PDF Downloads 148
2333 Integrating Machine Learning and Rule-Based Decision Models for Enhanced B2B Sales Forecasting and Customer Prioritization

Authors: Wenqi Liu, Reginald Bailey

Abstract:

This study proposes a comprehensive and effective approach to business-to-business (B2B) sales forecasting by integrating advanced machine learning models with a rule-based decision-making framework. The methodology addresses the critical challenge of optimizing sales pipeline performance and improving conversion rates through predictive analytics and actionable insights. The first component involves developing a classification model to predict the likelihood of conversion, aiming to outperform traditional methods such as logistic regression in terms of accuracy, precision, recall, and F1 score. Feature importance analysis highlights key predictive factors, such as client revenue size and sales velocity, providing valuable insights into conversion dynamics. The second component focuses on forecasting sales value using a regression model, designed to achieve superior performance compared to linear regression by minimizing mean absolute error (MAE), mean squared error (MSE), and maximizing R-squared metrics. The regression analysis identifies primary drivers of sales value, further informing data-driven strategies. To bridge the gap between predictive modeling and actionable outcomes, a rule-based decision framework is introduced. This model categorizes leads into high, medium, and low priorities based on thresholds for conversion probability and predicted sales value. By combining classification and regression outputs, this framework enables sales teams to allocate resources effectively, focus on high-value opportunities, and streamline lead management processes. The integrated approach significantly enhances lead prioritization, increases conversion rates, and drives revenue generation, offering a robust solution to the declining pipeline conversion rates faced by many B2B organizations. Our findings demonstrate the practical benefits of blending machine learning with decision-making frameworks, providing a scalable, data-driven solution for strategic sales optimization. This study underscores the potential of predictive analytics to transform B2B sales operations, enabling more informed decision-making and improved organizational outcomes in competitive markets.

Keywords: machine learning, XGBoost, regression, decision making framework, system engineering

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2332 Bi-Lateral Comparison between NIS-Egypt and NMISA-South Africa for the Calibration of an Optical Spectrum Analyzer

Authors: Osama Terra, Hatem Hussein, Adriaan Van Brakel

Abstract:

Dense wavelength division multiplexing (DWDM) technology requires tight specification and therefore measurement of wavelength accuracy and stability of the telecommunication lasers. Thus, calibration of the used Optical Spectrum Analyzers (OSAs) that are used to measure wavelength is of a great importance. Proficiency testing must be performed on such measuring activity to insure the accuracy of the measurement results. In this paper, a new comparison scheme is introduced to test the performance of such calibrations. This comparison scheme is implemented between NIS-Egypt and NMISA-South Africa for the calibration of the wavelength scale of an OSA. Both institutes employ reference gas cell to calibrate OSA according to the standard IEC/ BS EN 62129 (2006). The result of this comparison is compiled in this paper.

Keywords: OSA calibration, HCN gas cell, DWDM technology, wavelength measurement

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2331 ANFIS Based Technique to Estimate Remnant Life of Power Transformer by Predicting Furan Contents

Authors: Priyesh Kumar Pandey, Zakir Husain, R. K. Jarial

Abstract:

Condition monitoring and diagnostic is important for testing of power transformer in order to estimate the remnant life. Concentration of furan content in transformer oil can be a promising indirect measurement of the aging of transformer insulation. The oil gets contaminated mainly due to ageing. The present paper introduces adaptive neuro fuzzy technique to correlate furanic compounds obtained by high performance liquid chromatography (HPLC) test and remnant life of the power transformer. The results are obtained by conducting HPLC test at TIFAC-CORE lab, NIT Hamirpur on thirteen power transformer oil samples taken from Himachal State Electricity Board, India.

Keywords: adaptive neuro fuzzy technique, furan compounds, remnant life, transformer oil

Procedia PDF Downloads 464
2330 Field Study for Evaluating Winter Thermal Performance of Auckland School Buildings

Authors: Bin Su

Abstract:

Auckland has a temperate climate with comfortable warm, dry summers and mild, wet winters. An Auckland school normally does not need air conditioning for cooling during the summer and only needs heating during the winter. The Auckland school building thermal design should more focus on winter thermal performance and indoor thermal comfort for energy efficiency. This field study of testing indoor and outdoor air temperatures, relative humidity and indoor surface temperatures of three classrooms with different envelopes were carried out in the Avondale College during the winter months in 2013. According to the field study data, this study is to compare and evaluate winter thermal performance and indoor thermal conditions of school buildings with different envelopes.

Keywords: building envelope, building mass effect, building thermal comfort, building thermal performance, school building

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2329 Feasibility Study of Friction Stir Welding Application for Kevlar Material

Authors: Ahmet Taşan, Süha Tirkeş, Yavuz Öztürk, Zafer Bingül

Abstract:

Friction stir welding (FSW) is a joining process in the solid state, which eliminates problems associated with the material melting and solidification, such as cracks, residual stresses and distortions generated during conventional welding. Among the most important advantages of FSW are; easy automation, less distortion, lower residual stress and good mechanical properties in the joining region. FSW is a recent approach to metal joining and although originally intended for aluminum alloys, it is investigated in a variety of metallic materials. The basic concept of FSW is a rotating tool, made of non-consumable material, specially designed with a geometry consisting of a pin and a recess (shoulder). This tool is inserted as spinning on its axis at the adjoining edges of two sheets or plates to be joined and then it travels along the joining path line. The tool rotation axis defines an angle of inclination with which the components to be welded. This angle is used for receiving the material to be processed at the tool base and to promote the gradual forge effect imposed by the shoulder during the passage of the tool. This prevents the material plastic flow at the tool lateral, ensuring weld closure on the back of the pin. In this study, two 4 mm Kevlar® plates which were produced with the Kevlar® fabrics, are analyzed with COMSOL Multiphysics in order to investigate the weldability via FSW. Thereafter, some experimental investigation is done with an appropriate workbench in order to compare them with the analysis results.

Keywords: analytical modeling, composite materials welding, friction stir welding, heat generation

Procedia PDF Downloads 159
2328 Ballast Water Management Triad: Administration, Ship Owner and the Seafarer

Authors: Rajoo Balaji, Omar Yaakob

Abstract:

The Ballast Water Convention requires less than 5% of the world tonnage for ratification. Consequently, ships will have to comply with the requirements. Compliance evaluation and enforcement will become mandatory. Ship owners have to invest in treatment systems and shipboard personnel have to operate them and ensure compliance. The monitoring and enforcement will be the responsibilities of the Administrations. Herein, a review of the current status of the Ballast Water Management and the issues faced by these are projected. Issues range from efficacy and economics of the treatment systems to sampling and testing. Health issues of chemical systems, paucity of data for decision support etc., are other issues. It is emphasized that management of ballast water must be extended to ashore and sustainable solutions must be researched upon. An exemplar treatment system based on ship’s waste heat is also suggested.

Keywords: Ballast Water Management, compliance evaluation, compliance enforcement, sustainability

Procedia PDF Downloads 440
2327 The Genus Bacillus, Effect on Commercial Crops of Colombia

Authors: L. C. Sánchez, L. C. Corrales, A. G. Lancheros, E. Castañeda, Y. Ariza, L. S. Fuentes, L. Sierra, J. L. Cuervo

Abstract:

The importance of environment friendly alternatives in agricultural processes is the reason why the research group Ceparium, the Colegio Mayor de Cundinamarca University, Colombia, investigated the genus Bacillus and its applicability for improving crops of economic importance in Colombia. In this investigation, we presented a study in which the genus Bacillus plays a leading role as beneficial microorganism. The objective was to identify the biochemical potential of three indigenous species of Bacillus, which were able to carry out actions for biological control against pathogens and pests or promoted growth to improve productivity of crops in Colombia. The procedures were performed in three phases: first, the production of biomass of an indigenous strain and a reference strain starting from culture media for production of spores and toxins were made. Spore count was done in a Neubauer chamber, concentrations of spores of Bacillus sphaericus were prepared and a bioassay was done at the Laboratory of Entomology at the University Jorge Tadeo Lozano of Plutella xylostella larvae, insect pest of crucifers in several Colombian regions. The second phase included the extraction in the liquid state fermentation, a secondary metabolite that has antibiosis action against fungi, call iturin B, and was obtained from strains of Bacillus subtilis. The molecule was identified using High Resolution Chromatography (HPLC) and its biocontrol effect on Fusarium sp fungus causes vascular wilt in economically important plant varieties, was confirmed using testing of antagonism in Petri dish. In the third phase, an initial procedure in that let recover and identify microorganisms of the genus Bacillus from the rhizosphere in two aromatic herbs, Rosmarinus officinalis and Thymus vulgaris L. was used. Subsequently, testing of antagonism against Fusarium sp were made and an assay was done under greenhouse conditions to observe biocontrol and growth promoting action by comparing growth in length and dry weight. In the first experiment, native Bacillus sphaericus was lethal to 92% Plutella xylostella larvae in 10 DDA. In the second experiment, iturin B was identified and biological control of Fusarium sp was demonstrated. In the third study, all strains demonstrated biological control and the B14 strain identified as Bacillus megaterium increased root length and productivity of the two plants in terms of weight. It was concluded that the native microorganisms of the genus Bacillus has a great biochemical potential that provides a beneficial interactions with plants, improve their growth and development and therefore a greater impact on production.

Keywords: genus bacillus, biological control, PGPRs, biochemical potential

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2326 Brain-Computer Interface Based Real-Time Control of Fixed Wing and Multi-Rotor Unmanned Aerial Vehicles

Authors: Ravi Vishwanath, Saumya Kumaar, S. N. Omkar

Abstract:

Brain-computer interfacing (BCI) is a technology that is almost four decades old, and it was developed solely for the purpose of developing and enhancing the impact of neuroprosthetics. However, in the recent times, with the commercialization of non-invasive electroencephalogram (EEG) headsets, the technology has seen a wide variety of applications like home automation, wheelchair control, vehicle steering, etc. One of the latest developed applications is the mind-controlled quadrotor unmanned aerial vehicle. These applications, however, do not require a very high-speed response and give satisfactory results when standard classification methods like Support Vector Machine (SVM) and Multi-Layer Perceptron (MLPC). Issues are faced when there is a requirement for high-speed control in the case of fixed-wing unmanned aerial vehicles where such methods are rendered unreliable due to the low speed of classification. Such an application requires the system to classify data at high speeds in order to retain the controllability of the vehicle. This paper proposes a novel method of classification which uses a combination of Common Spatial Paradigm and Linear Discriminant Analysis that provides an improved classification accuracy in real time. A non-linear SVM based classification technique has also been discussed. Further, this paper discusses the implementation of the proposed method on a fixed-wing and VTOL unmanned aerial vehicles.

Keywords: brain-computer interface, classification, machine learning, unmanned aerial vehicles

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2325 A Multi-Agent Urban Traffic Simulator for Generating Autonomous Driving Training Data

Authors: Florin Leon

Abstract:

This paper describes a simulator of traffic scenarios tailored to facilitate autonomous driving model training for urban environments. With the rising prominence of self-driving vehicles, the need for diverse datasets is very important. The proposed simulator provides a flexible framework that allows the generation of custom scenarios needed for the validation and enhancement of trajectory prediction algorithms. Its controlled yet dynamic environment addresses the challenges associated with real-world data acquisition and ensures adaptability to diverse driving scenarios. By providing an adaptable solution for scenario creation and algorithm testing, this tool proves to be a valuable resource for advancing autonomous driving technology that aims to ensure safe and efficient self-driving vehicles.

Keywords: autonomous driving, car simulator, machine learning, model training, urban simulation environment

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2324 A Nonlinear Approach for System Identification of a Li-Ion Battery Based on a Non-Linear Autoregressive Exogenous Model

Authors: Meriem Mossaddek, El Mehdi Laadissi, El Mehdi Loualid, Chouaib Ennawaoui, Sohaib Bouzaid, Abdelowahed Hajjaji

Abstract:

An electrochemical system is a subset of mechatronic systems that includes a wide variety of batteries and nickel-cadmium, lead-acid batteries, and lithium-ion. Those structures have several non-linear behaviors and uncertainties in their running range. This paper studies an effective technique for modeling Lithium-Ion (Li-Ion) batteries using a Nonlinear Auto-Regressive model with exogenous input (NARX). The Artificial Neural Network (ANN) is trained to employ the data collected from the battery testing process. The proposed model is implemented on a Li-Ion battery cell. Simulation of this model in MATLAB shows good accuracy of the proposed model.

Keywords: lithium-ion battery, neural network, energy storage, battery model, nonlinear models

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2323 Design Considerations for the Construction of an Open Decontamination Facility for Managing Civil Emergencies

Authors: Sarmin, S., Ologuin, R.S.

Abstract:

Background: Rapid population growth and land constraints in Singapore results in a possible situation in which we face a higher number of casualties and lack of operational space in healthcare facilities during disasters and HAZMAT events, collectively known as Civil Emergencies. This creates a need for available working space within hospital grounds to be amphibious or multi-functional, to ensure the institution’s capability to respond efficiently to Civil Emergencies. The Emergency Department (ED) mitigates this issue by converting the Ambulance Assembly Area used during peacetime into an Open Decontamination Facility (ODF) during Civil Emergency Response, for decontamination of casualties before they proceed to treatment areas into Ambulance Assembly Area used during peacetime. Aims: To effectively operationalize the Open Decontamination Facility (ODF) through the reduction of manual handling. Methods: From past experiences on Civil Emergency exercises, it was labor-intensive for staff to set up the Open Decontamination Facility (ODF). Manual handling to set up the Decontamination lanes by bringing down the curtains and supply of water was required to be turned on. Conclusion: The effectiveness of the design construction of an Open Decontamination Facility (ODF) is based on the use of automation of bringing down the curtains on the various lanes. The use of control panels for water supply to decontaminate patients. Safety within the ODF was considered with the installation of panic buttons, intercom for staff communication, and perimeter curtains were installed with stability arm to manage the condition with high wind velocity.

Keywords: civil emergencies, disaster, emergency department, Hazmat

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2322 Simulation-Based Unmanned Surface Vehicle Design Using PX4 and Robot Operating System With Kubernetes and Cloud-Native Tooling

Authors: Norbert Szulc, Jakub Wilk, Franciszek Górski

Abstract:

This paper presents an approach for simulating and testing robotic systems based on PX4, using a local Kubernetes cluster. The approach leverages modern cloud-native tools and runs on single-board computers. Additionally, this solution enables the creation of datasets for computer vision and the evaluation of control system algorithms in an end-to-end manner. This paper compares this approach to method commonly used Docker based approach. This approach was used to develop simulation environment for an unmanned surface vehicle (USV) for RoboBoat 2023 by running a containerized configuration of the PX4 Open-source Autopilot connected to ROS and the Gazebo simulation environment.

Keywords: cloud computing, Kubernetes, single board computers, simulation, ROS

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2321 Design and Evaluation of a Pneumatic Muscle Actuated Gripper

Authors: Tudor Deaconescu, Andrea Deaconescu

Abstract:

Deployment of pneumatic muscles in various industrial applications is still in its early days, considering the relative newness of these components. The field of robotics holds particular future potential for pneumatic muscles, especially in view of their specific behaviour known as compliance. The paper presents and discusses an innovative constructive solution for a gripper system mountable on an industrial robot, based on actuation by a linear pneumatic muscle and transmission of motion by gear and rack mechanism. The structural, operational and constructive models of the new gripper are presented, along with some of the experimental results obtained subsequently to the testing of a prototype. Further presented are two control variants of the gripper system, one by means of a 3/2-way fast-switching solenoid valve, the other by means of a proportional pressure regulator. Advantages and disadvantages are discussed for both variants.

Keywords: gripper system, pneumatic muscle, structural modelling, robotics

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2320 Symbiotic Organism Search (SOS) for Solving the Capacitated Vehicle Routing Problem

Authors: Eki Ruskartina, Vincent F. Yu, Budi Santosa, A. A. N. Perwira Redi

Abstract:

This paper introduces symbiotic organism search (SOS) for solving capacitated vehicle routing problem (CVRP). SOS is a new approach in metaheuristics fields and never been used to solve discrete problems. A sophisticated decoding method to deal with a discrete problem setting in CVRP is applied using the basic symbiotic organism search (SOS) framework. The performance of the algorithm was evaluated on a set of benchmark instances and compared results with best known solution. The computational results show that the proposed algorithm can produce good solution as a preliminary testing. These results indicated that the proposed SOS can be applied as an alternative to solve the capacitated vehicle routing problem.

Keywords: symbiotic organism search, capacitated vehicle routing problem, metaheuristic

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2319 Nano-Immunoassay for Diagnosis of Active Schistosomal Infection

Authors: Manal M. Kame, Hanan G. El-Baz, Zeinab A.Demerdash, Engy M. Abd El-Moneem, Mohamed A. Hendawy, Ibrahim R. Bayoumi

Abstract:

There is a constant need to improve the performance of current diagnostic assays of schistosomiasis as well as develop innovative testing strategies to meet new testing challenges. This study aims at increasing the diagnostic efficiency of monoclonal antibody (MAb)-based antigen detection assays through gold nanoparticles conjugated with specific anti-Schistosoma mansoni monoclonal antibodies. In this study, several hybidoma cell lines secreting MAbs against adult worm tegumental Schistosoma antigen (AWTA) were produced at Immunology Department of Theodor Bilharz Research Institute and preserved in liquid nitrogen. One MAb (6D/6F) was chosen for this study due to its high reactivity to schistosome antigens with highest optical density (OD) values. Gold nanoparticles (AuNPs) were functionalized and conjugated with MAb (6D/6F). The study was conducted on serum samples of 116 subjects: 71 patients with S. mansoni eggs in their stool samples group (gp 1), 25 with other parasites (gp2) and 20 negative healthy controls (gp3). Patients in gp1 were further subdivided according to egg count in their stool samples into Light infection {≤ 50 egg per gram(epg) (n= 17)}, moderate {51-100 epg (n= 33)} and severe infection {>100 epg(n= 21)}. Sandwich ELISA was performed using (AuNPs -MAb) for detection of circulating schistosomal antigen (CSA) levels in serum samples of all groups and the results were compared with that after using MAb/ sandwich ELISA system. Results Gold- MAb/ ELISA system reached a lower detection limit of 10 ng/ml compared to 85 ng/ml on using MAb/ ELISA and the optimal concentrations of AuNPs -MAb were found to be 12 folds less than that of MAb/ ELISA system for detection of CSA. The sensitivity and specificity of sandwich ELISA for detection of CSA levels using AuNPs -MAb were 100% & 97.8 % respectively compared to 87.3% &93.38% respectively on using MAb/ ELISA system. It was found that CSA was detected in 9 out of 71 S.mansoni infected patients on using AuNPs - MAb/ ELISA system and was not detected by MAb/ ELISA system. All those patients (9) was found to have an egg count below 50 epg feces (patients with light infections). ROC curve analyses revealed that sandwich ELISA using gold-MAb was an excellent diagnostic investigator that could differentiate Schistosoma patients from healthy controls, on the other hand it revealed that sandwich ELISA using MAb was not accurate enough as it could not recognize nine out of 71 patients with light infections. Conclusion Our data demonstrated that: Loading gold nanoparticles with MAb (6D/6F) increases the sensitivity and specificity of sandwich ELISA for detection of CSA, thus active (early) and light infections could be easily detected. Moreover this binding will decrease the amount of MAb consumed in the assay and lower the coast. The significant positive correlation that was detected between ova count (intensity of infection) and OD reading in sandwich ELISA using gold- MAb enables its use to detect the severity of infections and follow up patients after treatment for monitoring of cure.

Keywords: Schistosomiasis, nanoparticles, gold, monoclonal antibodies, ELISA

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2318 Turbine Engine Performance Experimental Tests of Subscale UAV

Authors: Haluk Altay, Bilal Yücel, Berkcan Ulcay, Yücel Aydın

Abstract:

In this study, the design, integration, and testing of measurement systems required for performance tests of jet engines used in small-scale unmanned aerial vehicles are described. Performance tests are carried out as thrust and fuel consumption. For thrust tests, measurements are made using a load cell. Amplifier and filter designs have been made for the load cell to measure accurately to meet the desired sensitivity. It was calibrated by making multiple measurements at different thrust levels. As a result of these processes, the cycle thrust graph was obtained. For fuel consumption tests, tests are carried out using a flow meter. Performance graphics were obtained by finding the fuel consumption for different RPM levels of the engine.

Keywords: jet engine, UAV, experimental test, loadcell, thrust, fuel consumption

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2317 Engineering Optimization Using Two-Stage Differential Evolution

Authors: K. Y. Tseng, C. Y. Wu

Abstract:

This paper employs a heuristic algorithm to solve engineering problems including truss structure optimization and optimal chiller loading (OCL) problems. Two different type algorithms, real-valued differential evolution (DE) and modified binary differential evolution (MBDE), are successfully integrated and then can obtain better performance in solving engineering problems. In order to demonstrate the performance of the proposed algorithm, this study adopts each one testing case of truss structure optimization and OCL problems to compare the results of other heuristic optimization methods. The result indicates that the proposed algorithm can obtain similar or better solution in comparing with previous studies.

Keywords: differential evolution, Truss structure optimization, optimal chiller loading, modified binary differential evolution

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2316 Implementation of a Paraconsistent-Fuzzy Digital PID Controller in a Level Control Process

Authors: H. M. Côrtes, J. I. Da Silva Filho, M. F. Blos, B. S. Zanon

Abstract:

In a modern society the factor corresponding to the increase in the level of quality in industrial production demand new techniques of control and machinery automation. In this context, this work presents the implementation of a Paraconsistent-Fuzzy Digital PID controller. The controller is based on the treatment of inconsistencies both in the Paraconsistent Logic and in the Fuzzy Logic. Paraconsistent analysis is performed on the signals applied to the system inputs using concepts from the Paraconsistent Annotated Logic with annotation of two values (PAL2v). The signals resulting from the paraconsistent analysis are two values defined as Dc - Degree of Certainty and Dct - Degree of Contradiction, which receive a treatment according to the Fuzzy Logic theory, and the resulting output of the logic actions is a single value called the crisp value, which is used to control dynamic system. Through an example, it was demonstrated the application of the proposed model. Initially, the Paraconsistent-Fuzzy Digital PID controller was built and tested in an isolated MATLAB environment and then compared to the equivalent Digital PID function of this software for standard step excitation. After this step, a level control plant was modeled to execute the controller function on a physical model, making the tests closer to the actual. For this, the control parameters (proportional, integral and derivative) were determined for the configuration of the conventional Digital PID controller and of the Paraconsistent-Fuzzy Digital PID, and the control meshes in MATLAB were assembled with the respective transfer function of the plant. Finally, the results of the comparison of the level control process between the Paraconsistent-Fuzzy Digital PID controller and the conventional Digital PID controller were presented.

Keywords: fuzzy logic, paraconsistent annotated logic, level control, digital PID

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2315 Effect of Nanoparticle Addition in the Urea-Formaldehyde Resin on the Formaldehyde Emission from MDF

Authors: Sezen Gurdag, Ayse Ebru Akin

Abstract:

There is a growing concern all over the world on the health effect of the formaldehyde emission coming from the adhesive used in the MDF production. In this research, we investigated the effect of nanoparticle addition such as nanoclay and halloysite into urea-formadehyde resin on the total emitted formaldehyde from MDF plates produced using the resin modified as such. First, the curing behavior of the resin was studied by monitoring the pH, curing time, solid content, density and viscosity of the modified resin in comparison to the reference resin with no added nanoparticle. The dosing of the nanoparticle in the dry resin was kept at 1wt%, 3wt% or 5wt%. Consecutively, the resin was used in the production of 50X50 cm MDF samples using laboratory scale press line with full automation system. Modulus of elasticity, bending strength, internal bonding strength, water absorption were also measured in addition to the main interested parameter formaldehyde emission levels which is determined via spectrometric technique following an extraction procedure. Threshold values for nanoparticle dosing levels were determined to be 5wt% for both nanoparticles. However, the reinforcing behavior was observed to be occurring at different levels in comparison to the reference plates with each nanoparticle such that the level of reinforcement with nanoclay was shown to be more favorable than the addition of halloysite due to higher surface area available with the former. In relation, formaldehyde emission levels were observed to be following a similar trend where addition of 5wt% nanoclay into the urea-formaldehyde adhesive helped decrease the formaldehyde emission up to 40% whereas addition of halloysite at its threshold level demonstrated as the same level, i.e., 5wt%, produced an improvement of 18% only.

Keywords: halloysite, nanoclay, fiberboard, urea-formaldehyde adhesive

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2314 Quantitative Structure Activity Relationship Model for Predicting the Aromatase Inhibition Activity of 1,2,3-Triazole Derivatives

Authors: M. Ouassaf, S. Belaidi

Abstract:

Aromatase is an estrogen biosynthetic enzyme belonging to the cytochrome P450 family, which catalyzes the limiting step in the conversion of androgens to estrogens. As it is relevant for the promotion of tumor cell growth. A set of thirty 1,2,3-triazole derivatives was used in the quantitative structure activity relationship (QSAR) study using regression multiple linear (MLR), We divided the data into two training and testing groups. The results showed a good predictive ability of the MLR model, the models were statistically robust internally (R² = 0.982) and the predictability of the model was tested by several parameters. including external criteria (R²pred = 0.851, CCC = 0.946). The knowledge gained in this study should provide relevant information that contributes to the origins of aromatase inhibitory activity and, therefore, facilitates our ongoing quest for aromatase inhibitors with robust properties.

Keywords: aromatase inhibitors, QSAR, MLR, 1, 2, 3-triazole

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2313 Evaluation of Ultrasonic Techniques for the Estimation of Air Voids in Asphalt Concrete

Authors: Majid Zargar, Frank Bullen, Ron Ayers

Abstract:

One of the important factors in the design of asphalt concrete mixes is the accurate measurement of air voids and their variable distribution. Both can have significant impact on long and short term fatigue and creep behaviour under traffic. While some simple methods exist for overall evaluation of air voids, measuring air void distribution in asphalt concrete is very complex, involving expensive techniques such as X-ray methodologies. The research reported in the paper investigated the use of non-destructive ultrasonic techniques as an alternative to estimate the amount of air voids and their distribution within asphalt samples. Seventy-four Standard AC–14 asphalt samples made with three types of bitumen; Multigrade, PMB and C320 were analysed using ultrasonic techniques. The results have illustrated that ultrasonic testing has the potential of being a rapid, accurate and cost-effective method of estimating air void distribution in asphalt.

Keywords: asphalt concrete, air voids, ultrasonic, mechanical behaviour

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2312 Facial Recognition on the Basis of Facial Fragments

Authors: Tetyana Baydyk, Ernst Kussul, Sandra Bonilla Meza

Abstract:

There are many articles that attempt to establish the role of different facial fragments in face recognition. Various approaches are used to estimate this role. Frequently, authors calculate the entropy corresponding to the fragment. This approach can only give approximate estimation. In this paper, we propose to use a more direct measure of the importance of different fragments for face recognition. We propose to select a recognition method and a face database and experimentally investigate the recognition rate using different fragments of faces. We present two such experiments in the paper. We selected the PCNC neural classifier as a method for face recognition and parts of the LFW (Labeled Faces in the Wild) face database as training and testing sets. The recognition rate of the best experiment is comparable with the recognition rate obtained using the whole face.

Keywords: face recognition, labeled faces in the wild (LFW) database, random local descriptor (RLD), random features

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2311 A Large Ion Collider Experiment (ALICE) Diffractive Detector Control System for RUN-II at the Large Hadron Collider

Authors: J. C. Cabanillas-Noris, M. I. Martínez-Hernández, I. León-Monzón

Abstract:

The selection of diffractive events in the ALICE experiment during the first data taking period (RUN-I) of the Large Hadron Collider (LHC) was limited by the range over which rapidity gaps occur. It would be possible to achieve better measurements by expanding the range in which the production of particles can be detected. For this purpose, the ALICE Diffractive (AD0) detector has been installed and commissioned for the second phase (RUN-II). Any new detector should be able to take the data synchronously with all other detectors and be operated through the ALICE central systems. One of the key elements that must be developed for the AD0 detector is the Detector Control System (DCS). The DCS must be designed to operate safely and correctly this detector. Furthermore, the DCS must also provide optimum operating conditions for the acquisition and storage of physics data and ensure these are of the highest quality. The operation of AD0 implies the configuration of about 200 parameters, from electronics settings and power supply levels to the archiving of operating conditions data and the generation of safety alerts. It also includes the automation of procedures to get the AD0 detector ready for taking data in the appropriate conditions for the different run types in ALICE. The performance of AD0 detector depends on a certain number of parameters such as the nominal voltages for each photomultiplier tube (PMT), their threshold levels to accept or reject the incoming pulses, the definition of triggers, etc. All these parameters define the efficiency of AD0 and they have to be monitored and controlled through AD0 DCS. Finally, AD0 DCS provides the operator with multiple interfaces to execute these tasks. They are realized as operating panels and scripts running in the background. These features are implemented on a SCADA software platform as a distributed control system which integrates to the global control system of the ALICE experiment.

Keywords: AD0, ALICE, DCS, LHC

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2310 Post Covid-19 Landscape of Global Pharmaceutical Industry

Authors: Abu Zafor Sadek

Abstract:

Pharmaceuticals were one of the least impacted business sectors during the corona pandemic as they are the center point of Covid-19 fight. Emergency use authorization, unproven indication of some commonly used drugs, self-medication, research and production capacity of an individual country, capacity of producing vaccine by many countries, Active Pharmaceutical Ingredients (APIs) related uncertainty, information gap among manufacturer, practitioners and user, export restriction, duration of lock-down, lack of harmony in transportation, disruption in the regulatory approval process, sudden increased demand of hospital items and protective equipment, panic buying, difficulties in in-person product promotion, e-prescription, geo-politics and associated issues added a new dimension to this industry. Although the industry maintains a reasonable growth throughout Covid-19 days; however, it has been characterized by both long- and short-term effects. Short-term effects have already been visible to so many countries, especially those who are import-dependent and have limited research capacity. On the other hand, it will take a few more time to see the long-term effects. Nevertheless, supply chain disruption, changes in strategic planning, new communication model, squeezing of job opportunity, rapid digitalization are the major short-term effects, whereas long-term effects include a shift towards self-sufficiency, growth pattern changes of certain products, special attention towards clinical studies, automation in operations, the increased arena of ethical issues etc. Therefore, this qualitative and exploratory study identifies the post-covid-19 landscape of the global pharmaceutical industry.

Keywords: covid-19, pharmaceutical, businees, landscape

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