Search results for: using an Anisotropic Analytical Algorithm (AAA)

Authors: Ryan Messina, Mehedi Hasan

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This research is to examine the impacts of using data to generate performance requirements for automation in visual inspections using machine vision. These situations are intended for design and how projects can smooth the transfer of tacit knowledge to using an algorithm. We have proposed a framework when specifying machine vision systems. This framework utilizes varying levels of automation as contingency planning to reduce data processing complexity. Using data assists in extracting tacit knowledge from those who can perform the manual tasks to assist design the system; this means that real data from the system is always referenced and minimizes errors between participating parties. We propose using three indicators to know if the project has a high risk of failing to meet requirements related to accuracy and reliability. All systems tested achieved a better integration into operations after applying the framework.

Keywords: automation, contingency planning, continuous engineering, control theory, machine vision, system requirements, system thinking

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Authors: Qasim HamaKhurshid HamaMurad, Normal Mat Jusoh, Uznir Ujang

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The concept of the city with an infrastructure of (information and communication) Technology embraces several definitions depending on the meanings of the word "smart" are (intelligent city, smart city, knowledge city, ubiquitous city, sustainable city, digital city). Many definitions of the city exist, but this chapter explores which one has been universally acknowledged. From literature analysis, it emerges that Smart City is the most used terminologies in literature through the digital database to indicate the smartness of a city. This paper share exploration the research from main seven website digital databases and journal about Smart City from "January 2015 to the February of 2020" to (a) Time research, to examine the causes of the Smart City phenomenon and other concept literature in the last five years (b) Review of words, to see how and where the smart city specification and relation different definition And(c) Geographical research to consider where Smart Cities' greatest concentrations are in the world and are Malaysia has interacting with the smart city, and (d) how many papers published from all Malaysia from 2015 to 2020 about smart citie. Three steps are followed to accomplish the goal. (1)The analysis covered publications Build a systematic literature review search strategy to gather a representative sub-set of papers on Smart City and other definitions utilizing (GoogleScholar, Elsevier, Scopus, ScienceDirect, IEEEXplore, WebofScience, Springer) January2015-February2020. (2)A bibliometric map was formed based on the bibliometric evaluation using the mapping technique VOSviewer to visualize differences. (3)VOSviewer application program was used to build initial clusters. The Map of Bibliometric Visualizes the analytical findings which targeted the word harmony.

Keywords: bibliometric research, smart city, ICT, VOSviewer, urban modernization

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Authors: Amin Ranjbar, Amir Arsalan Jalili Zolfaghari, Amir Abolfazl Suratgar, Mehrdad Khajavi

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This paper describes two stages of learning-based fault detection procedure in alternators. The procedure consists of three states of machine condition namely shortened brush, high impedance relay and maintaining a healthy condition in the alternator. The fault detection algorithm uses Wigner-Ville distribution as a feature extractor and also appropriate feature classifier. In this work, ANN (Artificial Neural Network) and also SVM (support vector machine) were compared to determine more suitable performance evaluated by the mean squared of errors criteria. Modules work together to detect possible faulty conditions of machines working. To test the method performance, a signal database is prepared by making different conditions on a laboratory setup. Therefore, it seems by implementing this method, satisfactory results are achieved.

Keywords: alternator, artificial neural network, support vector machine, time-frequency analysis, Wigner-Ville distribution

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Authors: Wendy Flory, Kazi Czarnecki, Matthijs Mercy, Mark Joswiak, Mary Beth Seasholtz

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Polyurethane Materials are present in a wide range of industrial segments such as Furniture, Building and Construction, Composites, Automotive, Electronics, and more. Dow is one of the leaders for the manufacture of the two main raw materials, Isocyanates and Polyols used to produce polyurethane products. Dow is also a key player for the manufacture of Polyurethane Systems/Formulations designed for targeted applications. In 1990, the first analytical chemometric models were developed and deployed for use in the Dow QC labs of the polyols business for the quantification of OH, water, cloud point, and viscosity. Over the years many models have been added; there are now over 140 models for quantification and hundreds for product identification, too many to be reasonable for support. There are 29 global models alone for the quantification of OH across > 70 products at many sites. An attempt was made to consolidate these into a single model. While the consolidated model proved good statistics across the entire range of OH, several products had a bias by ASTM E1655 with individual product validation. This project summary will show the strategy for global model updates for OH, to reduce the number of models for quantification from over 140 to 5 or less using chemometric methods. In order to gain an understanding of the best product groupings, we identify clusters by reducing spectra to a few dimensions via Principal Component Analysis (PCA) and Uniform Manifold Approximation and Projection (UMAP). Results from these cluster analyses and a separate validation set allowed dow to reduce the number of models for predicting OH from 29 to 3 without loss of accuracy.

Keywords: hydroxyl, global model, model maintenance, near infrared, polyol

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Authors: Ammar Alali, Mahmoud Abughaban

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Cost reduction and drilling optimization is the goal of many drilling operators. Historically, stuck pipe incidents were a major segment of non-productive time (NPT) associated costs. Traditionally, stuck pipe problems are part of the operations and solved post-sticking. However, the real key to savings and success is in predicting the stuck pipe incidents and avoiding the conditions leading to its occurrences. Previous attempts in stuck-pipe predictions have neglected the local geology of the problem. The proposed predictive tool utilizes geophysical data processing techniques and Machine Learning (ML) algorithms to predict drilling activities events in real-time using surface drilling data with minimum computational power. The method combines two types of analysis: (1) real-time prediction, and (2) cause analysis. Real-time prediction aggregates the input data, including historical drilling surface data, geological formation tops, and petrophysical data, from wells within the same field. The input data are then flattened per the geological formation and stacked per stuck-pipe incidents. The algorithm uses two physical methods (stacking and flattening) to filter any noise in the signature and create a robust pre-determined pilot that adheres to the local geology. Once the drilling operation starts, the Wellsite Information Transfer Standard Markup Language (WITSML) live surface data are fed into a matrix and aggregated in a similar frequency as the pre-determined signature. Then, the matrix is correlated with the pre-determined stuck-pipe signature for this field, in real-time. The correlation used is a machine learning Correlation-based Feature Selection (CFS) algorithm, which selects relevant features from the class and identifying redundant features. The correlation output is interpreted as a probability curve of stuck pipe incidents prediction in real-time. Once this probability passes a fixed-threshold defined by the user, the other component, cause analysis, alerts the user of the expected incident based on set pre-determined signatures. A set of recommendations will be provided to reduce the associated risk. The validation process involved feeding of historical drilling data as live-stream, mimicking actual drilling conditions, of an onshore oil field. Pre-determined signatures were created for three problematic geological formations in this field prior. Three wells were processed as case studies, and the stuck-pipe incidents were predicted successfully, with an accuracy of 76%. This accuracy of detection could have resulted in around 50% reduction in NPT, equivalent to 9% cost saving in comparison with offset wells. The prediction of stuck pipe problem requires a method to capture geological, geophysical and drilling data, and recognize the indicators of this issue at a field and geological formation level. This paper illustrates the efficiency and the robustness of the proposed cross-disciplinary approach in its ability to produce such signatures and predicting this NPT event.

Keywords: drilling optimization, hazard prediction, machine learning, stuck pipe

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Authors: Shiuh-Jer Huang, Su-Shean Chen, Sheam-Chyun Lin

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Two-wheel inverted pendulum robot (TWIPR) is designed with two-hub DC motors for human riding and motion control evaluation. In order to measure the tilt angle and angular velocity of the inverted pendulum robot, accelerometer and gyroscope sensors are chosen. The mobile robot’s moving position and velocity were estimated based on DC motor built in hall sensors. The control kernel of this electric mobile robot is designed with embedded Arduino Nano microprocessor. A handle bar was designed to work as steering mechanism. The intelligent model-free fuzzy sliding mode control (FSMC) was employed as the main control algorithm for this mobile robot motion monitoring with different control purpose adjustment. The intelligent controllers were designed for balance control, and moving speed control purposes of this robot under different operation conditions and the control performance were evaluated based on experimental results.

Keywords: balance control, speed control, intelligent controller, two wheel inverted pendulum

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Authors: Gyoutae Park, Seungho Han, Byungduk Kim, Youngdo Jo, Yongsop Shim, Yeonjae Lee, Sangguk Ahn, Hiesik Kim, Jungil Park

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In this paper, we presented not only development technology of an explosion proof type and portable combustible gas leak detector but also algorithm to improve accuracy for measuring gas concentrations. The presented techniques are to apply the flame-proof enclosure and intrinsic safe explosion proof to an infrared gas leak detector at first in Korea and to improve accuracy using linearization recursion equation and Lagrange interpolation polynomial. Together, we tested sensor characteristics and calibrated suitable input gases and output voltages. Then, we advanced the performances of combustible gaseous detectors through reflecting demands of gas safety management fields. To check performances of two company's detectors, we achieved the measurement tests with eight standard gases made by Korea Gas Safety Corporation. We demonstrated our instruments better in detecting accuracy other than detectors through experimental results.

Keywords: accuracy improvement, IR gas sensor, gas leak, detector

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Authors: Sobar M. Johari, Ida Putri Anjarsari

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In the transmission of monetary instrument towards real sector of the economy, Bank Indonesia as monetary authority has developed Islamic Bank Indonesia Certificate (abbreviated as SBIS) as an instrument in Islamic open market operation. One of the monetary transmission channels could take place through financing channel from which the fund is used as the source of banking financing. This study aims to analyse the impact of Islamic monetary instrument towards output or economic growth. Data used in this research is taken from Bank Indonesia and Central Board of Statistics for the period of January 2008 until December 2015. The study employs Granger Causality Test, Vector Error Correction Model (VECM), Impulse Response Function (IRF) technique and Forecast Error Variance Decomposition (FEVD) as its analytical methods. The results show that, first, the transmission mechanism of banking financing channel are not linked to output. Second, estimation results of VECM show that SBIS, PUAS, and FIN have significant impact in the long term towards output. When there is monetary shock, output or economic growth could be recovered and stabilized in the short term. FEVD results show that Islamic banking financing contributes 1.33 percent to increase economic growth.

Keywords: Islamic monetary instrument, Islamic banking financing channel, economic growth, Vector Error Correction Model (VECM)

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Authors: Shahbaz G. Hassan

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Water quality models are very important to predict the changes in surface water quality for environmental management. The aim of this paper is to give an overview of the water qualities, and to provide directions for selecting models in specific situation. Water quality models include one kind of model based on a mechanistic approach, while other models simulate water quality without considering a mechanism. Mechanistic models can be widely applied and have capabilities for long-time simulation, with highly complexity. Therefore, more spaces are provided to explain the principle and application experience of mechanistic models. Mechanism models have certain assumptions on rivers, lakes and estuaries, which limits the application range of the model, this paper introduces the principles and applications of water quality model based on the above three scenarios. On the other hand, mechanistic models are more easily to compute, and with no limit to the geographical conditions, but they cannot be used with confidence to simulate long term changes. This paper divides the empirical models into two broad categories according to the difference of mathematical algorithm, models based on artificial intelligence and models based on statistical methods.

Keywords: empirical models, mathematical, statistical, water quality

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Authors: Alex Soares Castro, Matheus Manoel Teles de Menezes, Larissa Silva de Azevedo, Ana Carolina Caleffi Patelli, Osmair Vital de Oliveira, Aline Thais Bruni, Marcelo Firmino de Oliveira

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Considering the problem of the seizure of illicit drugs, as well as the development of electrochemical sensors using chemically modified electrodes, this work shows the study of the electrochemical activity of cocaine in carbon paste electrode chemically modified with Cu (II) trans 3-MeO salcn complex. In this context, cyclic voltammetry was performed on 0.1 mol.L⁻¹ KCl supporting electrolyte at a scan speed of 100 mV s⁻¹, using an electrochemical cell composed of three electrodes: Ag /AgCl electrode (filled KCl 3 mol.L⁻¹) from Metrohm® (reference electrode); a platinum spiral electrode, as an auxiliary electrode, and a carbon paste electrode chemically modified with Cu (II) trans 3-MeO complex (as working electrode). Two forms of cocaine were analyzed: cocaine hydrochloride (pH 3) and cocaine free base form (pH 8). The PM7 computational method predicted that the hydrochloride form is more stable than the free base form of cocaine, so with cyclic voltammetry, we found electrochemical signal only for cocaine in the form of hydrochloride, with an anodic peak at 1.10 V, with a linearity range between 2 and 20 μmol L⁻¹ had LD and LQ of 2.39 and 7.26x10-5 mol L⁻¹, respectively. The study also proved that cocaine is adsorbed on the surface of the working electrode, where through an irreversible process, where only anode peaks are observed, we have the oxidation of cocaine, which occurs in the hydrophilic region due to the loss of two electrons. The mechanism of this reaction was confirmed by the ab-inito quantum method.

Keywords: ab-initio computational method, analytical method, cocaine, Schiff base complex, voltammetry

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Authors: Amit S. Chauhan, S. Mandal

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The structural response of shear walls subjected to various types of loads is difficult to predict precisely. They are incorporated in buildings to resist lateral forces and support the gravity loads. The steel plate shear walls (SPSWs) are used as lateral load resisting systems for buildings and acts as an alternative to reinforced concrete shear walls (RCSWs). This paper compares the behavior of SPSW with the RCSW incorporated in a building frame having G+6 storey, located in Zone III, using the technique of Equivalent Static Method (ESM) as per Indian Standard Criteria For Earthquake Resistant Design of Structures IS 1893:2002. This paper intends to evaluate several parameters such as lateral displacement at tip, inter-storey drift, weight of steel and volume of concrete with the alteration of the shear wall with respect to different types viz., SPSW and RCSW. The strip model employed in this study is a widely accepted analytical tool for SPSW analysis. SPSW can be modelled as truss members by using a series of diagonal tension strips positioned at 45-degree angles. In this paper, by replacing the SPSWs with the tension strips, the G+6 building has been analyzed using STAAD.Pro V8i. Based on the present study, it can be concluded that structure with SPSWs is much better then structure with RCSWs.

Keywords: equivalent static method, inter-storey drift, lateral displacement, Steel plate shear wall, strip model

Procedia PDF Downloads 241

Authors: Sıdıka Kaya, Gülay Sain Güven, Seda Karsavuran, Onur Toka

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This study is part of an ongoing research project supported by the Scientific and Technological Research Council of Turkey (TUBITAK) under Project Number 114K404, and participation to this conference was supported by Hacettepe University Scientific Research Coordination Unit under Project Number 10243. Evaluation of hospital readmissions is gaining importance in terms of quality and cost, and is becoming the target of national policies. In Turkey, the topic of hospital readmission is relatively new on agenda and very few studies have been conducted on this topic. The aim of this study was to determine 30-day readmission rates and risk factors for readmission. Whether readmission was planned, related to the prior admission and avoidable or not was also assessed. The study was designed as a ‘prospective cohort study.’ 472 patients hospitalized in internal medicine departments of a university hospital in Turkey between February 1, 2015 and April 30, 2015 were followed up. Analyses were conducted using IBM SPSS Statistics version 22.0 and SPSS Modeler 16.0. Average age of the patients was 56 and 56% of the patients were female. Among these patients 95 were readmitted. Overall readmission rate was calculated as 20% (95/472). However, only 31 readmissions were unplanned. Unplanned readmission rate was 6.5% (31/472). Out of 31 unplanned readmission, 24 was related to the prior admission. Only 6 related readmission was avoidable. To determine risk factors for readmission we constructed Chi-square automatic interaction detector (CHAID) decision tree algorithm. CHAID decision trees are nonparametric procedures that make no assumptions of the underlying data. This algorithm determines how independent variables best combine to predict a binary outcome based on ‘if-then’ logic by portioning each independent variable into mutually exclusive subsets based on homogeneity of the data. Independent variables we included in the analysis were: clinic of the department, occupied beds/total number of beds in the clinic at the time of discharge, age, gender, marital status, educational level, distance to residence (km), number of people living with the patient, any person to help his/her care at home after discharge (yes/no), regular source (physician) of care (yes/no), day of discharge, length of stay, ICU utilization (yes/no), total comorbidity score, means for each 3 dimensions of Readiness for Hospital Discharge Scale (patient’s personal status, patient’s knowledge, and patient’s coping ability) and number of daycare admissions within 30 days of discharge. In the analysis, we included all 95 readmitted patients (46.12%), but only 111 (53.88%) non-readmitted patients, although we had 377 non-readmitted patients, to balance data. The risk factors for readmission were found as total comorbidity score, gender, patient’s coping ability, and patient’s knowledge. The strongest identifying factor for readmission was comorbidity score. If patients’ comorbidity score was higher than 1, the risk for readmission increased. The results of this study needs to be validated by other data–sets with more patients. However, we believe that this study will guide further studies of readmission and CHAID is a useful tool for identifying risk factors for readmission.

Keywords: decision tree, hospital, internal medicine, readmission

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Authors: Su Sin Chong, Abdul Aziz Abdul Raman, Sulaiman Wadi Harun, Hamzah Arof

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Chemical Oxygen Demand (COD) plays a vital role determination of an appropriate strategy for wastewater treatment including the control of the quality of an effluent. In this study, a new sensing method was introduced for the first time and developed to investigate chemical oxygen demand (COD) using a Mach-Zehner Interferometer (MZI)-based dye sensor. The sensor is constructed by bridging two single mode fibres (SMF1 and SMF2) with a short section (~20 mm) of multimode fibre (MMF) and was formed by tapering the MMF to generate evanescent field which is sensitive to perturbation of sensing medium. When the COD concentration increase takes effect will induce changes in output intensity and effective refractive index between the microfiber and the sensing medium. The adequacy of decisions based on COD values relies on the quality of the measurements. Therefore, the dual output response can be applied to the analytical procedure enhance measurement quality. This work presents a detailed assessment of the determination of COD values in synthetic wastewaters. Detailed models of the measurement performance, including sensitivity, reversibility, stability, and uncertainty were successfully validated by proficiency tests where supported on sound and objective criteria. Comparison of the standard method with the new proposed method was also conducted. This proposed sensor is compact, reliable and feasible to investigate the COD value.

Keywords: chemical oxygen demand, environmental sensing, Mach-Zehnder interferometer sensor, online monitoring

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Authors: Cora Bulmău

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Soil polluted with hydrocarbons spills is a major global concern today. As a response to this issue, our experimental study tries to put in evidence the option to choose for one environmentally friendly method: use of the biochar, despite to a classical procedure; incineration of contaminated soil. Biochar represents the solid product obtained through the pyrolysis of biomass, its additional use being as an additive intended to improve the quality of the soil. The positive effect of biochar addition to soil is represented by its capacity to adsorb and contain petroleum products within its pores. Taking into consideration the capacity of the biochar to interact with organic contaminants, the purpose of the present study was to experimentally establish the effects of the addition of wooden biomass-derived biochar on a soil contaminated with oil. So, the contaminated soil was amended with biochar (10%) produced by pyrolysis in different operational conditions of the thermochemical process. After 25 days, the concentration of petroleum hydrocarbons from soil treated with biochar was measured. An analytical method as Soxhlet extraction was adopted to estimate the concentrations of total petroleum products (TPH) in the soil samples: This technique was applied to contaminated soil, also to soils remediated by incineration/adding biochar. The treatment of soil using biochar obtained from pyrolysis of the Birchwood led to a considerable decrease in the concentrations of petroleum products. The incineration treatments conducted under experimental stage to clean up the same soil, contaminated with petroleum products, involved specific parameters: temperature of about 600°C, 800°C and 1000°C and treatment time 30 and 60 minutes. The experimental results revealed that the method using biochar has registered values of efficiency up to those of all incineration processes applied for the shortest time.

Keywords: biochar, biomass, remediaton, soil, TPH

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Authors: Saifullahi Umar, Baba Mamman Yarima, Mohammed Bello Usman, Hassan Mohammed

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This study was conducted along with the Hadejia valley project irrigation under the Hadejia-Jama’are River Basin Development Authority (HRBDA) in Jigawa State. The multi-stage sampling procedure was used to select 72 rice farmers operating along with the Hadejia Valley Irrigation Project. Data for the study were collected using a structured questionnaire. The analytical tools employed for the study were descriptive statistics and Farm budget technique. The result shows that 55% of the farmers were between 31-40 years of age, 66.01% were male, and the result also revealed that the total cost of cultivation of an acre of land for rice production during the dry season was N73,900 with input cost accounting for 63.59% of the total cost of production. The gross return was N332,500, with a net return of N258,600 per acre. The estimated benefit-cost ratio of 3.449 indicates the strong performance of the dry season rice production. The leading constraints to dry season rice production were low access to quality extension services, low access to finance, poor quality fertilizers, and poor prices. The study, therefore, concludes that dry season rice production is a profitable enterprise in the study area hence, to productivity the farmers should be linked to effective extension service delivery institutions, expanding their access to productive sources of finances, the government should strengthen fertilizer quality control measures and comprehensive market linkages for the farmers.

Keywords: Auyo, dry season, Hadejia Valley, rice

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Authors: Abdelghani Alidra, Mohamed Tahar Kimour

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Genetic algorithm must adapt themselves at design time to cope with the search problem specific requirements and at runtime to balance exploration and convergence objectives. In a previous article, we have shown that modeling and implementing Genetic Algorithms (GA) using the software product line (SPL) paradigm is very appreciable because they constitute a product family sharing a common base of code. In the present article we propose to extend the use of the feature model of the genetic algorithms family to model the potential states of the GA in what is called a Dynamic Software Product Line. The objective of this paper is the systematic generation of a reconfigurable architecture that supports the dynamic of the GA and which is easily deduced from the feature model. The resultant GA is able to perform dynamic reconfiguration autonomously to fasten the convergence process while producing better solutions. Another important advantage of our approach is the exploitation of recent advances in the domain of dynamic SPLs to enhance the performance of the GAs.

Keywords: self-adaptive genetic algorithms, software engineering, dynamic software product lines, reconfigurable architecture

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Authors: Amir Sharifi Miavaghi

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It is believed recombination mechnisms in graphene-bonded perovskite solar cells based on numerical model in which doped-graphene structures are employed as anode/cathode bonding semiconductor. Moreover, th‌‌‌‌e da‌‌‌‌‌rk-li‌‌‌‌‌ght c‌‌‌‌urrent d‌‌‌‌ens‌‌‌‌ity-vo‌‌‌‌‌‌‌ltage density-voltage cu‌‌‌‌‌‌‌‌‌‌‌rves are investigated by regression analysis. L‌‌‌oss m‌‌‌‌echa‌‌‌‌nisms suc‌‌‌h a‌‌‌‌‌‌s ba‌‌‌‌ck c‌‌‌ontact b‌‌‌‌‌arrier, d‌‌‌‌eep surface defect i‌‌‌‌n t‌‌‌‌‌‌‌he adsorbent la‌‌‌yer is det‌‌‌‌‌ermined b‌‌‌y adapting th‌‌‌e sim‌‌‌‌‌ulated ce‌‌‌‌‌ll perfor‌‌‌‌‌mance to t‌‌‌‌he measure‌‌‌‌ments us‌‌‌‌ing the diffe‌‌‌‌‌‌rential evolu‌‌‌‌‌tion of th‌‌‌‌e global optimization algorithm. T‌‌‌‌he performance of t‌‌‌he c‌‌‌‌ell i‌‌‌‌n the connection proc‌‌‌‌‌ess incl‌‌‌‌‌‌udes J-V cur‌‌‌‌‌‌ves that are examined at di‌‌‌‌‌fferent tempe‌‌‌‌‌‌‌ratures an‌‌‌d op‌‌‌‌en cir‌‌‌‌cuit vol‌‌‌‌tage (V) und‌‌‌‌er differ‌‌‌‌‌ent light intensities as a function of temperature. Ba‌‌‌‌sed o‌‌‌n t‌‌‌he prop‌‌‌‌osed nu‌‌‌‌‌merical mod‌‌‌‌el a‌‌‌‌nd the acquired lo‌‌‌‌ss mecha‌‌‌‌‌‌nisms, our approach can be used to improve the efficiency of the solar cell further. Due to the high demand for alternative energy sources, solar cells are good alternatives for energy storage using the photovoltaic phenomenon.

Keywords: numerical model, recombination mechanism, graphen, perovskite solarcell

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Authors: V. Rashtchi, H. Bizhani, F. R. Tatari

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This paper presents a new online loss minimization for an induction motor drive. Among the many loss minimization algorithms (LMAs) for an induction motor, a particle swarm optimization (PSO) has the advantages of fast response and high accuracy. However, the performance of the PSO and other optimization algorithms depend on the accuracy of the modeling of the motor drive and losses. In the development of the loss model, there is always a trade off between accuracy and complexity. This paper presents a new online optimization to determine an optimum flux level for the efficiency optimization of the vector-controlled induction motor drive. An induction motor (IM) model in d-q coordinates is referenced to the rotor magnetizing current. This transformation results in no leakage inductance on the rotor side, thus the decomposition into d-q components in the steady-state motor model can be utilized in deriving the motor loss model. The suggested algorithm is simple for implementation.

Keywords: induction machine, loss minimization, magnetizing current, particle swarm optimization

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Authors: S. Tebibel, R. L. Bouchouka, C. Mechati, S. Messaoudi

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The stomach cancer or gastric cancer is an aggressive cancer with a significant geographic disparity. The decrease in frequency is attributed to refrigeration, which has several beneficial consequences, increased consumption of fresh fruits and vegetables, reduced consumption of salt, which was widely used as a food preservative, and less contamination of food by carcinogenic compounds. The infection with Helicobacter pylori is responsible for progressive inflammatory changes in the gastric mucosa usually evolving into stomach cancer in 80% of cases. Methodology: This epidemiological and analytical study concerns 65 patients (46 men and 19 women) with gastric adenocarcinomas with an average age of 56.5 years and a male predominance with a sex ratio of 2.4. Results and Discussion: In this series, the clinical symptoms are dominated by epigastralgia (72.31%), vomiting (27,69%), and slimming (24,62%). The FOGD (Oeso-Gastro Duodenal Fibroscopy) performed in the 65 patients revealed a predominance of the antro-pyloric localization in 19 cases (i.e., 29.23%) and anulcerative budding appearance in 33 subjects (50,77%). Histologically, the moderately differentiated adenocarcinoma is found in 30.77% of patients, followed by well differentiated adenocarcinoma with 26.15% of patients. The immunohistochemical study revealed a positive labeling of half of the T cells by anti-CD3 AC, and a positive labeling of anti-CD20 AC in a diffuse and intense manner, with the presence of CD20-positive lymphoepithelial lesions compatible with CD20 a low grade MALT non-Hodgkin's lymphoma. Conclusion: This framework of analysis revealed some risk factors for gastric cancer, such as food, hygiene, Helicobacter pylori infection, smoking and family history.

Keywords: cancer, Helicobacter pylori, immunohistochemistry, stomach

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Authors: Samara A. Testoni, Vander F. Melo, Lorna A. Dawson, Fabio A. S. Salvador

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Soil traces are useful as forensic evidence due to their potential to transfer and adhere to different types of surfaces on a range of objects or persons. The great variability expressed by soil physical, chemical, biological and mineralogical properties show soil traces as complex mixtures. Soils are continuous and variable, no two soil samples being indistinguishable, nevertheless, the complexity of soil characteristics can provide powerful evidence for comparative forensic purposes. This work aimed to establish a Standard Operating Procedure (SOP) for forensic soil analysis in Brazil. We carried out a simulated crime scene with double blind sampling to calibrate the sampling procedures. Samples were collected at a range of locations covering a range of soil types found in South of Brazil: Santa Candida and Boa Vista, neighbourhoods from Curitiba (State of Parana) and in Guarani and Guaraituba, neighbourhoods from Colombo (Curitiba Metropolitan Region). A previously validated sequential analyses of chemical, physical and mineralogical analyses was developed in around 2 g of soil. The suggested SOP and the sequential range of analyses were effective in grouping the samples from the same place and from the same parent material together, as well as successfully discriminated samples from different locations and originated from different rocks. In addition, modifications to the sample treatment and analytical protocol can be made depending on the context of the forensic work.

Keywords: clay mineralogy, forensic soils analysis, sequential analyses, kaolinite, gibbsite

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Authors: Akram Sadat Jafari Roodbandi, Parisa Kahani, Fatollah Rahimi Bafrani, Ali Dehghan, Nava Seyedi, Vafa Feyzi, Zohreh Forozanfar

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Introduction: Movement function is considered as the ability to produce and maintain balance, stability, and movement throughout the movement chain. Having a score of 14 and above on 7 sub-tests in the functional movement screening (FMS) test shows agility and optimal movement performance. On the other hand, the person's body is an important factor in physical fitness and optimal movement performance. The aim of this study was to identify effective anthropometric dimensions in increasing motor function. Methods: This study was a descriptive-analytical and cross-sectional study using simple random sampling. FMS test and 25 anthropometric dimensions and subcutaneous in five body regions measured in 139 healthy students of Bam University of Medical Sciences. Data analysis was performed using SPSS software and univariate tests and linear regressions at a significance level of 0.05. Results: 139 students were enrolled in the study, 51.1% (71 subjects) and the rest were female. The mean and standard deviation of age, weight, height, and arm subcutaneous fat were 21.5 ± 1.45, 12.6 ± 64.3, 168.7 ± 9.8, 15.3 ± 7, respectively. 17 subjects (12.2%) of the participants in the study have a score of less than 14, and the rest were above 14. Using regression analysis, it was found that exercise and arm subcutaneous fat are predictive variables associated with obtaining a high score in the FMS test. Conclusion: Exercise and weight loss are effective factors for increasing the movement performance of individuals, and this factor is independent of the size of other physical dimensions.

Keywords: functional movement, screening test, anthropometry, ergonomics

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Authors: Thomas L. McCullough, John D. Hague, Marylesa M. Howard, Matthew K. Kiser, Michael A. Mazur, Lance K. McLean, Johanna L. Turk

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Radiological search and mapping depends on the successful recognition of anomalies in large data sets which contain varied and dynamic backgrounds. We present a new algorithmic approach for real-time anomaly detection which is resistant to common detector imperfections, avoids the limitations of a source template library and provides immediate, and easily interpretable, user feedback. This algorithm is based on a continuous wavelet transform for variance reduction and evaluates the deviation between a foreground measurement and a local background expectation using methods from linear algebra. We also present a technique for recognizing and visualizing spectrally similar clusters of data. This technique uses Laplacian Eigenmap Manifold Learning to perform dimensional reduction which preserves the geometric "closeness" of the data while maintaining sensitivity to outlying data. We illustrate the utility of both techniques on real-world data sets.

Keywords: radiological search, radiological mapping, radioactivity, radiation protection

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Authors: Ashish James, Anusha James

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The impressive predictive performance of deep learning techniques on a wide range of tasks has led to its widespread use. Estimating the confidence of these predictions is paramount for improving the safety and reliability of such systems. However, the uncertainty estimates provided by neural networks (NNs) tend to be overconfident and unreasonable. Ensemble of NNs typically produce good predictions but uncertainty estimates tend to be inconsistent. Inspired by these, this paper presents a framework that can quantitatively estimate the uncertainties by leveraging the advances in transfer learning through slight modification to the existing training pipelines. This promising algorithm is developed with an intention of deployment in real world problems which already boast a good predictive performance by reusing those pretrained models. The idea is to capture the behavior of the trained NNs for the base task by augmenting it with the uncertainty estimates from a supplementary network. A series of experiments with known and unknown distributions show that the proposed approach produces well calibrated uncertainty estimates with high quality predictions.

Keywords: uncertainty estimation, neural networks, transfer learning, regression

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Authors: Sonia Anand Knowlton

Abstract:

There are some cases where we as a society feel deeply uncomfortable with the use of Artificial Intelligence (AI) tools in the judicial decision-making process, and justifiably so. A perfect example is COMPAS, an algorithmic model that predicts recidivism rates of offenders to assist in the determination of their bail conditions. COMPAS turned out to be extremely racist: it massively overpredicted recidivism rates of Black offenders and underpredicted recidivism rates of white offenders. At the same time, there are certain uses of AI in the judicial decision-making process that many would feel more comfortable with and even support. Take, for example, a “super-breathalyzer,” an (albeit imaginary) tool that uses AI to deliver highly detailed information about the subject of the breathalyzer test to the legal decision-makers analyzing their drunk-driving case. This article evaluates the point at which a judge’s use of AI tools begins to undermine the public’s trust in the administration of justice. It argues that the answer to this question depends on whether the AI tool is in a role in which it must perform a moral evaluation of a human being.

Keywords: artificial intelligence, judicial reasoning, morality, technology, algorithm

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Authors: Xuan Zhou, Litian Zhang, Shuixiang Li

Abstract:

Mesh deformation using radial basis function interpolation method has been demonstrated to produce quality meshes with relatively little computational cost using a concise algorithm. However, it still suffers from the limited deformation ability, especially in large deformation. In this paper, a pre-displacement improvement is proposed to improve the problem that illegal meshes always appear near the moving inner boundaries owing to the large relative displacement of the nodes near inner boundaries. In this improvement, nodes near the inner boundaries are first associated to the near boundary nodes, and a pre-displacement based on the displacements of associated boundary nodes is added to the nodes near boundaries in order to make the displacement closer to the boundary deformation and improve the deformation capability. Several 2D and 3D numerical simulation cases have shown that the pre-displacement improvement for radial basis function (RBF) method significantly improves the mesh quality near inner boundaries and deformation capability, with little computational burden increasement.

Keywords: mesh deformation, mesh quality, background mesh, radial basis function

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Authors: Kuen Ming Shu, Ren Kai Ho

Abstract:

Ultrasonic horn has the functions of amplifying amplitude and reducing resonant impedance in ultrasonic system. Its primary function is to amplify deformation or velocity during vibration and focus ultrasonic energy on the small area. It is a crucial component in design of ultrasonic vibration system. There are five common design methods for ultrasonic horns: analytical method, equivalent circuit method, equal mechanical impedance, transfer matrix method, finite element method. In addition, the general optimization design process is to change the geometric parameters to improve a single performance. Therefore, in the general optimization design process, we couldn't find the relation of parameter and objective. However, a good optimization design must be able to establish the relationship between input parameters and output parameters so that the designer can choose between parameters according to different performance objectives and obtain the results of the optimization design. In this study, an ultrasonic horn provided by Maxwide Ultrasonic co., Ltd. was used as the contrast of optimized ultrasonic horn. The ANSYS finite element analysis (FEA) software was used to simulate the distribution of the horn amplitudes and the natural frequency value. The results showed that the frequency for the simulation values and actual measurement values were similar, verifying the accuracy of the simulation values. The ANSYS DesignXplorer was used to perform Response Surface optimization, which could shows the relation of parameter and objective. Therefore, this method can be used to substitute the traditional experience method or the trial-and-error method for design to reduce material costs and design cycles.

Keywords: horn, natural frequency, response surface optimization, ultrasonic vibration

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Authors: Ghada S. Moussa

Abstract:

Vehicle classification is an important task in traffic surveillance and intelligent transportation systems. Classification of vehicle images is facing several problems such as: high intra-class vehicle variations, occlusion, shadow, illumination. These problems and others must be considered to develop a reliable vehicle classification system. In this study, a reliable multi-type vehicle classification system based on Bag-of-Words (BoW) paradigm is developed. Our proposed system used and compared four well-known classifiers; Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), k-Nearest Neighbour (KNN), and Decision Tree to classify vehicles into four categories: motorcycles, small, medium and large. Experiments on a large dataset show that our approach is efficient and reliable in classifying vehicles with accuracy of 95.7%. The SVM outperforms other classification algorithms in terms of both accuracy and robustness alongside considerable reduction in execution time. The innovativeness of developed system is it can serve as a framework for many vehicle classification systems.

Keywords: vehicle classification, bag-of-words technique, SVM classifier, LDA classifier, KNN classifier, decision tree classifier, SIFT algorithm

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Authors: Korosh Khorshidi, Mohammad Khodadadi

Abstract:

In this paper, exact close form solution for out of plate free flexural vibration of moderately thick rectangular nanoplates are presented based on nonlocal modified trigonometric shear deformation theory, with assumptions of the Levy's type boundary conditions, for the first time. The aim of this study is to evaluate the effect of small-scale parameters on the frequency parameters of the moderately thick rectangular nano-plates. To describe the effects of small-scale parameters on vibrations of rectangular nanoplates, the Eringen theory is used. The Levy's type boundary conditions are combination of six different boundary conditions; specifically, two opposite edges are simply supported and any of the other two edges can be simply supported, clamped or free. Governing equations of motion and boundary conditions of the plate are derived by using the Hamilton’s principle. The present analytical solution can be obtained with any required accuracy and can be used as benchmark. Numerical results are presented to illustrate the effectiveness of the proposed method compared to other methods reported in the literature. Finally, the effect of boundary conditions, aspect ratios, small scale parameter and thickness ratios on nondimensional natural frequency parameters and frequency ratios are examined and discussed in detail.

Keywords: exact solution, nonlocal modified sinusoidal shear deformation theory, out of plane vibration, moderately thick rectangular plate

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Authors: Mahmoud M. Othman, Almoataz Y. Abdelaziz, Yasser G. Hegazy

Abstract:

This paper presents a load control strategy based on modification of the Big Bang Big Crunch optimization method. The proposed strategy aims to determine the optimal load to be controlled and the corresponding time of control in order to minimize the energy purchased from substation. The presented strategy helps the distribution network operator to rely on the renewable energy sources in supplying the system demand. The renewable energy sources used in the presented study are modeled using the diagonal band Copula method and sequential Monte Carlo method in order to accurately consider the multivariate stochastic dependence between wind power, photovoltaic power and the system demand. The proposed algorithms are implemented in MATLAB environment and tested on the IEEE 37-node feeder. Several case studies are done and the subsequent discussions show the effectiveness of the proposed algorithm.

Keywords: big bang big crunch, distributed generation, load control, optimization, planning

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Authors: Abdulatif Abdulsalam Mohamed Shaban

Abstract:

This paper states that the art of Procedure Entry Array (PEA) plan with a focus on control system applications. This paper begins with an impression of PEA technology development, followed by an arrangement of design technologies, and the use of programmable description languages and system-level design tools. They allow a practical approach based on a unique model for complete engineering electronics systems. There are three main design rules are implemented in the system. These are algorithm based fine-tuning, modularity, and the control act and the architectural constraints. An overview of contributions and limits of PEAs is also given, followed by a short survey of PEA-based gifted controllers for recent engineering systems. Finally, two complete and timely case studies are presented to illustrate the benefits of a PEA implementation when using the proposed system modelling and devise attitude. These consist of the direct control for training motor drives and the control of a diesel-driven stand-alone generator with the help of logical design.

Keywords: control (DC), engineering electronics systems, training motor drives, procedure entry array

Procedia PDF Downloads 511