Search results for: robust ranking technique

Authors: Anek Apipatkul, Paphakorn Pitayachaval

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Preventive maintenance is a standardized procedure to control and prevent risky problems affecting production in order to increase work efficiency. Machine monitoring also routinely works to collect data for a scheduling maintenance period. This paper is to present the application of machine monitoring by using the internet of things (IOTs) and a lean technique in order to manage with complex maintenance tasks of an automated plastic granule packing machine. To organize the preventive maintenance, there are several processes that the machine monitoring was applied, starting with defining a clear scope of the machine, establishing standards in maintenance work, applying a just-in-time (JIT) technique for timely delivery in the maintenance work, solving problems on the floor, and also improving the inspection process. The result has shown that wasted time was reduced, and machines have been operated as scheduled. Furthermore, the efficiency of the scheduled maintenance period was increased by 95%.

Keywords: internet of things, preventive maintenance, machine monitoring, lean technique

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Authors: Devinder Singh, Arvind Kumar, Rajneesh Kumar

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The general solution of the equations for a homogeneous isotropic microstretch thermo elastic medium with mass diffusion for two dimensional problems is obtained due to normal and tangential forces. The integral transform technique is used to obtain the components of displacements, microrotation, stress and mass concentration, temperature change and mass concentration. A particular case of interest is deduced from the present investigation.

Keywords: normal force, tangential force, microstretch, thermoelastic, the integral transform technique, deforming force, microstress force, boundary value problem

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Authors: Mohammad Azam

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The purpose of this study is to investigate risk and real excess portfolio returns using inflation adjusted risk-free rates, a measuring technique that focuses on the momentum augmented Fama-French six-factor model and use monthly data from 1994 to 2022. With the exception of profitability, the data show that market, size, value, momentum, and investment factors are all strongly associated to excess portfolio stock returns using ordinary lease square regression technique. According to the Gibbons, Ross, and Shanken test, the momentum augmented Fama-French six-factor model outperforms the market. This technique discovery may be utilised by academics and professionals to acquire an in-depth knowledge of the Pakistan Stock Exchange across a broad stock pattern for investing decisions and portfolio construction.

Keywords: real excess portfolio returns, momentum augmented fama & french five-factor model, GRS-test, pakistan stock exchange

Procedia PDF Downloads 102

Authors: Kailas S. Jagtap, Karthik Sundarraj, Nirmal Kumar, S. Rajnarasimha, Prakash S. Kulkarni

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The issue of turbulence base streams and the drag related to it have been of important attention for rockets, missiles, and aircraft. Different techniques are used for base drag reduction. This paper presents the numerical study of numerous drag reduction technique. The base drag or afterbody drag of bluff bodies can be reduced easily using locked vortex drag reduction technique. For bluff bodies having a cylindrical shape, the base drag is much larger compared to streamlined bodies. For such bodies using splitter plates, the vortex can be trapped between the base and the plate, which results in smooth flow. Splitter plate with round and curved corner shapes has influence in drag reduction. In this paper, the comparison is done between single splitter plate as different positions and with the bluff body. Base drag for the speed of 30m/s can be reduced about 20% to 30% by using single splitter plate as compared to the bluff body.

Keywords: base drag, bluff body, splitter plate, vortex flow, ANSYS, fluent

Procedia PDF Downloads 180

Authors: Thewodros K. Geberemariam

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The rapid physical expansion of urbanization coupled with aging infrastructure presents a unique decision and management challenges for many big city municipalities. Cities must therefore upgrade and maintain the existing aging urban drainage infrastructure systems to keep up with the demands. Given the overall contribution of assets to municipal revenue and the importance of infrastructure to the success of a livable city, many municipalities are currently looking for a robust and smart urban drainage infrastructure asset management solution that combines management, financial, engineering and technical practices. This robust decision-making shall rely on sound, complete, current and relevant data that enables asset valuation, impairment testing, lifecycle modeling, and forecasting across the multiple asset portfolios. On this paper, predictive computational intelligence (CI) and multi-class machine learning (ML) coupled with online, offline, and historical record data that are collected from an array of multi-parameter sensors are used for the extraction of different operational and non-conforming patterns hidden in structured and unstructured data to determine and produce actionable insight on the current and future states of the network. This paper aims to improve the strategic decision-making process by identifying all possible alternatives; evaluate the risk of each alternative, and choose the alternative most likely to attain the required goal in a cost-effective manner using historical and near real-time urban drainage infrastructure data for urban drainage infrastructures assets that have previously not benefited from computational intelligence and machine learning advancements.

Keywords: computational intelligence, machine learning, urban drainage infrastructure, machine learning, classification, prediction, asset management space

Procedia PDF Downloads 152

Authors: Auwal Abubakar, Shazril Imran Shaukat, Noor Khairiah A. Karim, Mohammed Zakir Kassim, Gokula Kumar Appalanaido, Hafiz Mohd Zin

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Background: Voluntary deep inspiration breath-hold radiotherapy (vDIBH-RT) is an effective cardiac dose reduction technique during left breast radiotherapy. This study aimed to assess the accuracy of the implementation of the vDIBH technique among left breast cancer patients without the use of a special device such as a surface-guided imaging system. Methods: The vDIBH-RT technique was implemented among thirteen (13) left breast cancer patients at the Advanced Medical and Dental Institute (AMDI), Universiti Sains Malaysia. Breath-hold monitoring was performed based on breath-hold skin marks and laser light congruence observed on zoomed CCTV images from the control console during each delivery. The initial setup was verified using cone beam computed tomography (CBCT) during breath-hold. Each field was delivered using multiple beam segments to allow a delivery time of 20 seconds, which can be tolerated by patients in breath-hold. The data were analysed using an in-house developed MATLAB algorithm. PTV margin was computed based on van Herk's margin recipe. Results: The setup error analysed from CBCT shows that the population systematic error in lateral (x), longitudinal (y), and vertical (z) axes was 2.28 mm, 3.35 mm, and 3.10 mm, respectively. Based on the CBCT image guidance, the Planning target volume (PTV) margin that would be required for vDIBH-RT using CCTV/Laser monitoring technique is 7.77 mm, 10.85 mm, and 10.93 mm in x, y, and z axes, respectively. Conclusion: It is feasible to safely implement vDIBH-RT among left breast cancer patients without special equipment. The breath-hold monitoring technique is cost-effective, radiation-free, easy to implement, and allows real-time breath-hold monitoring.

Keywords: vDIBH, cone beam computed tomography, radiotherapy, left breast cancer

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Authors: Sherif M. Hafez, Remon F. Aziz, May S. A. Elalim

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Project managers today rely on scheduling tools based on the Critical Path Method (CPM) to determine the overall project duration and the activities’ float times which lead to greater efficiency in planning and control of projects. CPM was useful for scheduling construction projects, but researchers had highlighted a number of serious drawbacks that limit its use as a decision support tool and lacks the ability to clearly record and represent detailed information. This paper discusses the drawbacks of CPM as a scheduling technique and presents a modified critical path method (CPM) model which is called critical path segments (CPS). The CPS scheduling mechanism addresses the problems of CPM in three ways: decomposing the activity duration of separated but connected time segments; all relationships among activities are converted into finish–to–start relationship; and analysis and calculations are made with forward path. Sample cases are included to illustrate the shortages in CPM, CPS full analysis and calculations are explained in details, and how schedules can be handled better with the CPS technique.

Keywords: construction management, scheduling, critical path method, critical path segments, forward pass, float, project control

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Authors: Umar Albalawi, Sang C. Suh, Jinoh Kim

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As internet continues to expand its usage with an enormous number of applications, cyber-threats have significantly increased accordingly. Thus, accurate detection of malicious traffic in a timely manner is a critical concern in today’s Internet for security. One approach for intrusion detection is to use Machine Learning (ML) techniques. Several methods based on ML algorithms have been introduced over the past years, but they are largely limited in terms of detection accuracy and/or time and space complexity to run. In this work, we present a novel method for intrusion detection that incorporates a set of supervised learning algorithms. The proposed technique provides high accuracy and outperforms existing techniques that simply utilizes a single learning method. In addition, our technique relies on partial flow information (rather than full information) for detection, and thus, it is light-weight and desirable for online operations with the property of early identification. With the mid-Atlantic CCDC intrusion dataset publicly available, we show that our proposed technique yields a high degree of detection rate over 99% with a very low false alarm rate (0.4%).

Keywords: intrusion detection, supervised learning, traffic classification, computer networks

Procedia PDF Downloads 350

Authors: Somaya A. Abd El Mottaleb, Ahmed Abd El Aziz, Heba A. Fayed, Moustafa H. Aly

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In this paper, we present the performance of spectral amplitude coding optical code division multiple access using different detectors at different transmission distances using single photodiode detection technique. Modified double weight codes are used as signature codes. Simulation results show that the system using avalanche photo detector can move distance longer than that using positive intrinsic negative photo detector.

Keywords: avalanche photodiode, modified double weight, multiple access technique, single photodiode.

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Authors: G. V. Siva Krishna Rao, B. Srinivasa Rao

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The main aim of the paper is to implement a technique using distributed generation in distribution systems to reduce the distribution system losses and to improve voltage profiles. The fuzzy logic technique is used to select the proper location of DG and an analytical method is proposed to calculate the size of DG unit at any power factor. The optimal sizes of DG units are compared with optimal sizes obtained using the genetic algorithm. The suggested method is programmed under Matlab software and is tested on IEEE 33 bus system and the results are presented.

Keywords: DG Units, sizing of DG units, analytical methods, optimum size

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Authors: Palash Dutta

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More frequently uncertainties are encountered in medical diagnosis and therefore it is the most important and interesting area of applications of fuzzy set theory. In this present study, an attempt has been made to extend Sanchez’s approach for medical diagnosis via interval valued picture fuzzy sets and exhibit the technique with suitable case studies. In this article, it is observed that a refusal can be expressed in the databases concerning the examined objects. The technique is performing diagnosis on the basis of distance measures and as a result, this approach makes it possible to introduce weights of all symptoms and consequently patient can be diagnosed directly.

Keywords: medical diagnosis, uncertainty, fuzzy set, picture fuzzy set, interval valued picture fuzzy set

Procedia PDF Downloads 379

Authors: Restu Misrianti

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The amino acid variation of Asn (allele A) at position 631 in Mx gene was specific to positive antiviral to avian viral desease. This research was aimed at identifying polymorphism of Mx gene in duck using molecular technique. Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP) technique was used to select the genotype of AA, AG and GG. There were thirteen duck from Indragiri Hulu regency (Riau Province) used in this experiment. DNA amplification results showed that the Mx gene in duck is found in a 73 bp fragment. Mx gene in duck did not show any polymorphism. The frequency of the resistant allele (AA) was 0%, while the frequency of the susceptible allele (GG) was 100%.

Keywords: duck, Mx gene, PCR, RFLP

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Authors: Manverpreet Kaur, Amarpreet Singh

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The demand of Vehicular ad hoc networks is increasing day by day, due to offering the various applications and marvelous benefits to VANET users. Clustering in VANETs is most important to overcome the connectivity problems of VANETs. In this paper, we proposed a new clustering technique Enhanced cluster based connectivity maintenance in vehicular ad hoc network. Our objective is to form long living clusters. The proposed approach is grouping the vehicles, on the basis of the longest list of neighbors to form clusters. The cluster formation and cluster head selection process done by the RSU that may results it reduces the chances of overhead on to the network. The cluster head selection procedure is the vehicle which has closest speed to average speed will elect as a cluster Head by the RSU and if two vehicles have same speed which is closest to average speed then they will be calculate by one of the new parameter i.e. distance to their respective destination. The vehicle which has largest distance to their destination will be choosing as a cluster Head by the RSU. Our simulation outcomes show that our technique performs better than the existing technique.

Keywords: VANETs, clustering, connectivity, cluster head, intelligent transportation system (ITS)

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Authors: R. Horchani

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Optical pumping technique with laser fields combined with photo-association of ultra-cold atoms leads to control on demand the vibrational and/or the rotational population of molecules. Here, we review the basic concepts and main steps should be followed, including the excitation schemes and detection techniques we use to achieve the ro-vibrational cooling of Cs2 molecules. We also discuss the extension of this technique to other molecules. In addition, we present a theoretical model used to support the experiment. These simulations can be widely used for the preparation of various experiments since they allow the optimization of several important experimental parameters.

Keywords: cold molecule, photo-association, optical pumping, vibrational and rotational cooling

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Authors: Hussain Ali Bekhet, Tuan Ab Rashid Bin Tuan Abdullah, Tahira Yasmin

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It is very important for electric utility to determine dominant sectors which have more impacts on electricity consumption in national economy system. The aim of this paper is to examine the electricity demand multipliers in Malaysia for (2005-2014) period. Malaysian Input-output tables, 2005 and 2010 are used. Besides, a new concept, electricity demand multiplier (EDM), is presented to identify key sectors imposing great impacts on electricity demand quantitatively. In order to testify the effectiveness of the Malaysian energy policies, it notes that there is fluctuation of the ranking sectors between 2005 and 2010. This could be reflected that there is efficiency with pace of development in Malaysia. This can be good indication for decision makers for designing future energy policies.

Keywords: input-output model, demand multipliers, electricity, key sectors, Malaysia

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Authors: Wasif Mughees, Malik Al-Ahmad, Muhammad Naeem

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This research involves the design and analysis of pinch-based water/wastewater networks to minimize water utility in the petrochemical and petroleum industries. A study has been done on Tehran Oil Refinery to analyze feasibilities of regeneration, reuse and recycling of water network. COD is considered as a single key contaminant. Amount of freshwater was reduced about 149m3/h (43.8%) regarding COD. Re-design (or retrofitting) of water allocation in the networks was undertaken. The results were analyzed through graphical method and mathematical programming technique which clearly demonstrated that amount of required water would be determined by mass transfer of COD.

Keywords: minimization, water pinch, water management, pollution prevention

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Authors: Nagalingam Arun Prasanth, Ahmed Syed Adnan, S. H. Yeo

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Surface topography plays a significant role in the functional performance of engineered parts. It is important to have a control on the surface geometry and understanding on the surface details to get the desired performance. Hence, in the current research contribution, a non-contact micro-texturing technique has been explored and developed. The technique involves ultrasonic excitation of a tool as a prime source of surface texturing for aluminum alloy workpieces. The specimen surface is polished first and is then immersed in a liquid bath containing 10% weight concentration of Ti6Al4V grade 5 spherical powders. A submerged slurry jet is used to recirculate the spherical powders under the ultrasonic horn which is excited at an ultrasonic frequency and amplitude of 40 kHz and 70 µm respectively. The distance between the horn and workpiece surface was remained fixed at 200 µm using a precision control stage. Texturing effects were investigated for different process timings of 1, 3 and 5 s. Thereafter, the specimens were cleaned in an ultrasonic bath for 5 mins to remove loose debris on the surface. The developed surfaces are characterized by optical and contact surface profiler. The optical microscopic images show a texture of circular spots on the workpiece surface indented by titanium spherical balls. Waviness patterns obtained from contact surface profiler supports the texturing effect produced from the proposed technique. Furthermore, water droplet tests were performed to show the efficacy of the proposed technique to develop hydrophilic surfaces and to quantify the texturing effect produced.

Keywords: surface texturing, surface modification, topography, ultrasonic

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Authors: Noritaka Shigei, Kazuto Matsumoto, Yoshiki Nakashima, Hiromi Miyajima

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Although Mobile Wireless Sensor Networks (MWSNs), which consist of mobile sensor nodes (MSNs), can cover a wide range of observation region by using a small number of sensor nodes, they need to construct a network to collect the sensing data on the base station by moving the MSNs. As an effective method, the network construction method based on Virtual Rails (VRs), which is referred to as VR method, has been proposed. In this paper, we propose two types of effective techniques for the VR method. They can prolong the operation time of the network, which is limited by the battery capabilities of MSNs and the energy consumption of MSNs. The first technique, an effective arrangement of VRs, almost equalizes the number of MSNs belonging to each VR. The second technique, an adaptive movement method of MSNs, takes into account the residual energy of battery. In the simulation, we demonstrate that each technique can improve the network lifetime and the combination of both techniques is the most effective.

Keywords: mobile sensor node, relay of sensing data, residual energy, virtual rail, wireless sensor network

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Authors: Salma Loukman, Reda Benmrid, Najat Bouchmaa, Hicham Hboub, Rachid El Fatimy, Rachid Benhida

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In this study, it use integrated transcriptomic datasets from the GEO repository with the purpose of investigating immune dysregulation in COVID-19. Thus, in this context, we decided to be focused on NK cells and CD14+ monocytes gene expression, considering datasets GSE165461 and GSE198256, respectively. Other datasets with PBMCs, lung, olfactory, and sensory epithelium and lymph were used to provide robust validation for our results. This approach gave an integrated view of the immune responses in COVID-19, pointing out a set of potential biomarkers and therapeutic targets with special regard to standards of physiological conditions. IFI27, MKI67, CENPF, MBP, HBA2, TMEM158, THBD, HBA1, LHFPL2, SLA, and AC104564.3 were identified as key genes from our analysis that have critical biological processes related to inflammation, immune regulation, oxidative stress, and metabolic processes. Consequently, such processes are important in understanding the heterogeneous clinical manifestations of COVID-19—from acute to long-term effects now known as 'long COVID'. Subsequent validation with additional datasets consolidated these genes as robust biomarkers with an important role in the diagnosis of COVID-19 and the prediction of its severity. Moreover, their enrichment in key pathophysiological pathways presented them as potential targets for therapeutic intervention.The results provide insight into the molecular dynamics of COVID-19 caused by cells such as NK cells and other monocytes. Thus, this study constitutes a solid basis for targeted diagnostic and therapeutic development and makes relevant contributions to ongoing research efforts toward better management and mitigation of the pandemic.

Keywords: SARS-COV-2, RNA-seq, biomarkers, severity, long COVID-19, bio analysis

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Authors: Changiz Valmohammadi

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The main purpose of this study is to explore the perception of Iranian experts and executive managers of sample organizations on the benefits and barriers of Internet of Things (IoT) solutions implementation. Based on the review of the related literature and web sites, benefits and barriers of successful implementation to IoT solutions were identified. Through a self-administered questionnaire which was collected from 67 Iranian organizations the ranking and importance of benefits and barriers of IoT solutions implementation were determined based on the perception of the experts of the surveyed organizations. Analysis of data and the obtained results revealed that “improved customer experience” and “Supply chain optimization and responsiveness” are the most important benefits that the survey organizations expect to reap as a result of IoT solutions implementation. Also,” Integration challenges" and “cannot find right suppliers” were ranked as the most challenging barriers to IoT solutions implementation.

Keywords: internet of things (IoT), exploratory study, benefits, barriers, Iran

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Authors: Chisakan Papapankiad

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The purpose of this research was to study the level of satisfaction from the perspective of inbound tourists who visited Bangkok, Thailand during January to March of 2014. While the independent variables included gender, age, levels of education, occupation, and income, the dependent variables were ten reasons for their visiting Thailand. A quota sampling method was utilized to get 200 respondents with 50 percent male and 50 percent female respondents. The majority of respondents were between 30-40 years old. Most were married and had an undergraduate degree. The average income of the respondents was between $30,000-50,000 per year. The findings revealed the ranking levels of satisfaction by highest mean to lowest mean as follows: Thai food and beverage, nature-beach-mountain, spa-massage-beauty, malls-shopping places, souvenir and handcraft, festivals and activities, tradition markets, museum-art-history, night entertainment, and conference-expo. In addition, the overall means is 4.19 with 0.790 SD.

Keywords: inbound tourists, satisfaction, visiting, Thailand

Procedia PDF Downloads 384

Authors: Atanu K Samanta, Asim Ali Khan

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Due to the acquisition of huge amounts of brain tumor magnetic resonance images (MRI) in clinics, it is very difficult for radiologists to manually interpret and segment these images within a reasonable span of time. Computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of radiologists and reduce the time required for accurate diagnosis. An intelligent computer-aided technique for automatic detection of a brain tumor through MRI is presented in this paper. The technique uses the following computational methods; the Level Set for segmentation of a brain tumor from other brain parts, extraction of features from this segmented tumor portion using gray level co-occurrence Matrix (GLCM), and the Artificial Neural Network (ANN) to classify brain tumor images according to their respective types. The entire work is carried out on 50 images having five types of brain tumor. The overall classification accuracy using this method is found to be 98% which is significantly good.

Keywords: brain tumor, computer-aided diagnostic (CAD) system, gray-level co-occurrence matrix (GLCM), tumor segmentation, level set method

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Authors: Badr M. Alshammari, T. Guesmi

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In recent years, the combined economic and emission power dispatch is one of the main problems of electrical power system. It aims to schedule the power generation of generators in order to minimize cost production and emission of harmful gases caused by fossil-fueled thermal units such as CO, CO₂, NO_x, and SO₂. To solve this complicated multi-objective problem, an improved version of the particle swarm optimization technique that includes non-dominated sorting concept has been proposed. Valve point loading effects and system losses have been considered. The three-unit and ten-unit benchmark systems have been used to show the effectiveness of the suggested optimization technique for solving this kind of nonconvex problem. The simulation results have been compared with those obtained using genetic algorithm based method. Comparison results show that the proposed approach can provide a higher quality solution with better performance.

Keywords: power dispatch, valve point loading effects, multiobjective optimization, Pareto solutions

Procedia PDF Downloads 273

Authors: Usama Ahmed

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Data mining is the process of analyze data which are used to predict helpful information. It is the field of research which solve various type of problem. In data mining, classification is an important technique to classify different kind of data. Diabetes is most common disease. This paper implements different classification technique using Waikato Environment for Knowledge Analysis (WEKA) on diabetes dataset and find which algorithm is suitable for working. The best classification algorithm based on diabetic data is Naïve Bayes. The accuracy of Naïve Bayes is 76.31% and take 0.06 seconds to build the model.

Keywords: data mining, classification, diabetes, WEKA

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Authors: Nguyen Quynh Trang, Nguyễn Thị Hông Nhung

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The study aimed to identify the effectiveness of using the mind map technique to enhance students’ medical vocabulary retention among a group of students at a higher education institution - Thai Nguyen University of Medicine and Pharmacy during the first semester of the school year 2022-2023. The research employed a quasi-experimental method, exploring primary sources such as questionnaires and the analyzed results of pre-and-post tests. Almost teachers and students showed high preferences for the implementation of the mind map technique in language teaching and learning. Furthermore, results from the pre-and-post tests between the experimental group and control one pointed out that this technique brought back positive academic performance in teaching and learning English. The research findings revealed that there should be more supportive policies to evoke the use of the mind map technique in a pedagogical context. Aim of the Study: The purpose of this research was to investigate whether using mind mapping can help students to enhance nursing students’ medical vocabulary retention and to assess the students’ attitudes toward using mind mapping as a tool to improve their vocabulary. The methodology of the study: The research employed a quasi-experimental method, exploring primary sources such as questionnaires and the analyzed results of pre-and-post tests. The contribution of the study: The research contributed to the innovation of teaching vocabulary methods for English teachers at a higher education institution. Moreover, the research helped the English teachers and the administrators at a university evoke and maintain the motivation of students not only in English classes but also in other subjects. The findings of this research were beneficial to teachers, students, and researchers interested in using mind mapping to teach and learn English vocabulary. The research explored and proved the effectiveness of applying mind mapping in teaching and learning English vocabulary. Therefore, teaching and learning activities were conducted more and more effectively and helped students overcome challenges in remembering vocabulary and creating motivation to learn English vocabulary.

Keywords: medical vocabulary retention, mind map technique, nursing students, medical vocabulary

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Authors: Abdelsalam A. Ahmed

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Fast speed drives for Permanent Magnet Synchronous Motor (PMSM) is a crucial performance for the electric traction systems. In this paper, PMSM is drived with a Model-based Predictive Control (MPC) technique. Fast speed tracking is achieved through optimization of the DC source utilization using MPC. The technique is based on predicting the optimum voltage vector applied to the driver. Control technique is investigated by comparing to the cascaded PI control based on Space Vector Pulse Width Modulation (SVPWM). MPC and SVPWM-based FOC are implemented with the TMS320F2812 DSP and its power driver circuits. The designed MPC for a PMSM drive is experimentally validated on a laboratory test bench. The performances are compared with those obtained by a conventional PI-based system in order to highlight the improvements, especially regarding speed tracking response.

Keywords: permanent magnet synchronous motor, model-based predictive control, DC source utilization, cascaded PI control, space vector pulse width modulation, TMS320F2812 DSP

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Authors: Alexander Cramer, Kenneth Cramer

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Since the inauguration of President George Washington in 1789, the United States of America has seen the governance of some 44 individual presidents. Although such presidents share a variety of attributes, they still differ from one another on many others. Significantly, these traits may be used to construct distinct sets of 'families' of presidents throughout American history. By comparatively analyzing data from experts on the U.S. presidency – in this case, the C-SPAN Presidential Historians Surveys from 2000, 2009, and 2017 – this article identifies a consistent set of six presidential families: the All Stars; the Conservative Visionaries; the Postwar Progressives; the Average Joes; the Forgettables; and the Regrettables. In situating these categories in history, this article argues that U.S. presidents can be accurately organized into cohesive, like-performing families whose constituents share a common set of criteria.

Keywords: C-SPAN, POTUS presidential performance, presidential ranking, presidential studies, presidential surveys, United States

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Authors: Sergei Aleinik, Yuri Matveev

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In this paper a novel method for the detection of clipping in speech signals is described. It is shown that the new method has better performance than known clipping detection methods, is easy to implement, and is robust to changes in signal amplitude, size of data, etc. Statistical simulation results are presented.

Keywords: clipping, clipped signal, speech signal processing, digital signal processing

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Authors: Reda Abdel Azim, Tariq Shehab

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The main objective of this study is to develop a subsurface fracture map of naturally fractured reservoirs by overcoming the limitations associated with different data sources in characterising fracture properties. Some of these limitations are overcome by employing a nested neuro-stochastic technique to establish inter-relationship between different data, as conventional well logs, borehole images (FMI), core description, seismic attributes, and etc. and then characterise fracture properties in terms of fracture density and fractal dimension for each data source. Fracture density is an important property of a system of fracture network as it is a measure of the cumulative area of all the fractures in a unit volume of a fracture network system and Fractal dimension is also used to characterize self-similar objects such as fractures. At the wellbore locations, fracture density and fractal dimension can only be estimated for limited sections where FMI data are available. Therefore, artificial intelligence technique is applied to approximate the quantities at locations along the wellbore, where the hard data is not available. It should be noted that Artificial intelligence techniques have proven their effectiveness in this domain of applications.

Keywords: naturally fractured reservoirs, artificial intelligence, fracture intensity, fractal dimension

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Authors: Ezza Nasir, Babar Ramzan

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Silicon washes on altered knitted fabrics will provide diverse shrinkage trends. The expectation on shrinkage for various apparel products are also changed. However, the effect of shrinkage in garment is still ambiguous. As a result, analysis of shrinkage after different concentrations of silicon washes can provide a more realistic study. The purpose of this study is to analyze the shrinkage with commercial sewing threads in knitted fabric. Study focuses on the effect of different washes on garment measurement and to study the effect of washes on fabric shrinkage. Four different types of knitted fabric were sewn with same length and width measurements. To study the effect of softener washes on shrinkage of garment through subjective ranking, there were critical dimensions for measurements done on body length and width garment appearance and shrinkage.

Keywords: shrinkage, dimensions, knitted fabric, silicon

Procedia PDF Downloads 473