Search results for: alternative selection tool

Authors: Bushra Zafar, Usman Qamar

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Large data sample size and dimensions render the effectiveness of conventional data mining methodologies. A data mining technique are important tools for collection of knowledgeable information from variety of databases and provides supervised learning in the form of classification to design models to describe vital data classes while structure of the classifier is based on class attribute. Classification efficiency and accuracy are often influenced to great extent by noisy and undesirable features in real application data sets. The inherent natures of data set greatly masks its quality analysis and leave us with quite few practical approaches to use. To our knowledge first time, we present a new approach for investigation of structure and quality of datasets by providing a targeted analysis of localization of noisy and irrelevant features of data sets. Machine learning is based primarily on feature selection as pre-processing step which offers us to select few features from number of features as a subset by reducing the space according to certain evaluation criterion. The primary objective of this study is to trim down the scope of the given data sample by searching a small set of important features which may results into good classification performance. For this purpose, a heuristic for wrapper-based feature selection using genetic algorithm and for discriminative feature selection an external classifier are used. Selection of feature based on its number of occurrence in the chosen chromosomes. Sample dataset has been used to demonstrate proposed idea effectively. A proposed method has improved average accuracy of different datasets is about 95%. Experimental results illustrate that proposed algorithm increases the accuracy of prediction of different diseases.

Keywords: data mining, generic algorithm, KNN algorithms, wrapper based feature selection

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Authors: Gulyas Erzsebet

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The multimerisation of proteins is a common feature of many cellular processes; however, it could also impair protein functions and/or be associated with the occurrence of diseases. Thus, development of a research tool monitoring the appearance/presence of multimeric protein forms has great importance for a variety of research fields. Such a tool is potentially applicable in the ante-mortem diagnosis of certain conformational diseases, such as transmissible spongiform encephalopathies (TSE) and Alzheimer’s disease. These conditions are accompanied by the appearance of aggregated protein multimers, present in low concentrations in various tissues. This detection is particularly relevant for TSE where the handling of tissues derived from affected individuals and of meat products of infected animals have become an enormous health concern. Here we demonstrate the potential of such a multimer detection approach in TSE by developing a facile approach. The Biospiral-Detect system resembles a traditional sandwich ELISA, except that the capturing antibody that is attached to a solid surface and the detecting antibody is directed against the same or overlapping epitopes. As a consequence, the capturing antibody shields the epitope on the captured monomer from reacting with the detecting antibody, therefore monomers are not detected. Thus, MDS is capable of detecting only protein multimers with high specificity. We developed an alternative system as well, where RNA aptamers were employed instead of monoclonal antibodies. In order to minimize degradation, the 3' and 5' ends of the aptamer contained deoxyribonucleotides and phosphorothioate linkages. When compared the monoclonal antibodies-based system with the aptamers-based one, the former proved to be superior. Thus all subsequent experiments were conducted by employing the Biospiral -Detect modified sandwich ELISA kit. Our approach showed an order of magnitude higher sensitivity toward mulimers than monomers suggesting that this approach may become a valuable diagnostic tool for conformational diseases that are accompanied by multimerization.

Keywords: diagnosis, ELISA, Prion, TSE

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Authors: Sharjeel Saleem

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The glass ceiling has been a burning issue for many researchers. In this research, we examine gender of the BOD, training and development, workforce diversity, positive attitude towards women, and employee acts as antecedents of glass ceiling. Furthermore, we also look for effects of glass ceiling on likelihood of female selection and promotion and on female effectiveness. Multiple linear regression conducted on data drawn from different public and private sector organizations support our hypotheses. The research, however, is limited to Faisalabad city and only females from minority group are targeted here.

Keywords: glass ceiling, stereotype attitudes, female effectiveness

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Authors: Hamza Iftikhar

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The research study focuses on the transgender community's gender recognition challenges. It is one of the issues for the transgender community, interacting directly with the difficulties of gender identity and the lives of these people who are facing gender disapproval from society. This study investigates the major flaws of the transgender act. The study's goal is to look into the strange implications of self-perceived identity as a policy tool for transgender recognition. This policy tool jeopardises the rights of Pakistan's indigenous gender-variant people as well as the country's legal and social framework. Qualitative research using semi structured interviews will be carried out. This study proposes developing a scheme for mainstreaming gender-variant people on the basis of the Pakistani Constitution, Supreme Court guidelines, and internationally recognised principles of law. This would necessitate a thorough review of current law using a new approach and reference point.

Keywords: transgender act, self perceived identity, gender variant, policy tool

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Authors: Konstantinos Pikos, Dimitrios Kaimaris

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Although designing building blocks is a procedure used by many planners around the world, there isn’t an automated tool that will help planners and designers achieve their goals with lesser effort. The difficulty of the subject lies in the repeating process of manually drawing lines, while not only it is mandatory to maintain the desirable offset but to also achieve a lesser impact to the existing building stock. In this paper, using Geographical Information Systems (GIS) and the Python programming language, an automated tool integrated into ArcGIS PRO, is being presented. Despite its simplistic enviroment and the lack of specialized building legislation due to the complex state of the field, a planner who is aware of such technical information can use the tool to draw an initial approach of the final building blocks in an area with pre-existing buildings in an attempt to organize the usually sprawling suburbs of a city or any continuously developing area. The tool uses ESRI’s ArcPy library to handle the spatial data, while interactions with the user is made throught Tkinter. The main process consists of a modification of building edgescoordinates, using NumPy library, in an effort to draw the line of best fit, so the user can get the optimal results per block’s side. Finally, after the tool runs successfully, a table of primary planning information is shown, such as the area of the building block and its coverage rate. Regardless of the primary stage of the tool’s development, it is a solid base where potential planners with programming skills could invest, so they can make the tool adapt to their individual needs. An example of the entire procedure in a test area is provided, highlighting both the strengths and weaknesses of the final results.

Keywords: arcPy, GIS, python, building blocks

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Authors: Vesile Evrim, Aliyu Awwal

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By the evolvement in technology, the way of expressing opinions switched the direction to the digital world. The domain of politics as one of the hottest topics of opinion mining research merged together with the behavior analysis for affiliation determination in text which constitutes the subject of this paper. This study aims to classify the text in news/blogs either as Republican or Democrat with the minimum number of features. As an initial set, 68 features which 64 are constituted by Linguistic Inquiry and Word Count (LIWC) features are tested against 14 benchmark classification algorithms. In the later experiments, the dimensions of the feature vector reduced based on the 7 feature selection algorithms. The results show that Decision Tree, Rule Induction and M5 Rule classifiers when used with SVM and IGR feature selection algorithms performed the best up to 82.5% accuracy on a given dataset. Further tests on a single feature and the linguistic based feature sets showed the similar results. The feature “function” as an aggregate feature of the linguistic category, is obtained as the most differentiating feature among the 68 features with 81% accuracy by itself in classifying articles either as Republican or Democrat.

Keywords: feature selection, LIWC, machine learning, politics

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Authors: Kabil Boukhari

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In the context of information retrieval, the selection of the most relevant words is a very important step. In fact, the text cleaning allows keeping only the most representative words for a better use. In this paper, we propose a library for the purpose text preprocessing within an implemented application to facilitate this task. This study has two purposes. The first, is to present the related work of the various steps involved in text preprocessing, presenting the segmentation, stemming and lemmatization algorithms that could be efficient in the rest of study. The second, is to implement a developed tool for text preprocessing in French and English. This library accepts unstructured text as input and provides the preprocessed text as output, based on a set of rules and on a base of stop words for both languages. The proposed library has been made on different corpora and gave an interesting result.

Keywords: text preprocessing, segmentation, knowledge extraction, normalization, text generation, information retrieval

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Authors: Imad Zeyad Ramadan

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In this paper a genetic algorithm was developed to construct the optimal portfolio based on the Treynor method. The GA maximizes the Treynor ratio under budget constraint to select the best allocation of the budget for the companies in the portfolio. The results show that the GA was able to construct a conservative portfolio which includes companies from the three sectors. This indicates that the GA reduced the risk on the investor as it choose some companies with positive risks (goes with the market) and some with negative risks (goes against the market).

Keywords: oOptimization, genetic algorithm, portfolio selection, Treynor method

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Authors: S. Ghorbani, N. I. Polushin

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The machinability of workpieces (AISI 1045 Steel, AA2024 aluminum alloy, A48-class30 gray cast iron) in turning operation has been carried out using different types of cutting tool (conventional, cutting tool with holes in toolholder and cutting tool filled up with composite material) under dry conditions on a turning machine at different stages of spindle speed (630-1000 rpm), feed rate (0.05-0.075 mm/rev), depth of cut (0.05-0.15 mm) and tool overhang (41-65 mm). Experimentation was performed as per Taguchi’s orthogonal array. To evaluate the relative importance of factors affecting surface roughness the single decision tree (SDT), Decision tree forest (DTF) and Group method of data handling (GMDH) were applied.

Keywords: decision tree forest, GMDH, surface roughness, Taguchi method, turning process

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Authors: Sarah M. Asar, Nabeel M. Elhady

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Egypt’s current per capita water share indicates that the country suffers and has been suffering from water poverty. The abundant utilization of turfgrass in Egypt’s new urban settlements, the reliance on freshwater for irrigation, and the inadequate plant selection increase the water demand in such settlements. Decreasing the surface area of turfgrass by using alternative landscape features such as mulching, using ornamental low-maintenance plants, increasing pathways, etc., could significantly decrease the water demand of urban landscapes. The use of Ammochloa palaestina, Cenchrus crientalis (Oriental Fountain Grass), and Cistus parviflorus (with water demands of approximately 0.005m³/m²/day) as alternatives for Cynodon dactylon (0.01m³/m²/day), which is the most commonly used grass species in Egypt’s landscape, could decrease an area’s water demand by approximately 40-50%. Moreover, creating hydro-zones of similar water demanding plants would enable irrigation facilitation rather than the commonly used uniformed irrigation. Such a practice could further reduce water consumption by 15-20%. These results are based on a case-study analysis of one of Egypt’s relatively new urban settlements, Al-Rehab. Such results emphasize the importance of utilizing native, drought-tolerant vegetation in the urban landscapes of Egypt to reduce irrigation demands. Furthermore, proper implementation, monitoring, and maintenance of automated irrigation systems could be an important factor in a space’s efficient water use. As most new urban settlements in Egypt adopt sprinkler and drip irrigation systems, the lack of maintenance leads to the manual operation of such systems, and, thereby, excessive irrigation occurs.

Keywords: alternative landscape, native plants, efficient irrigation, low water demand

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Authors: Usman Qamar, Younus Javed

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Frequent pattern mining is the process of finding a pattern (a set of items, subsequences, substructures, etc.) that occurs frequently in a data set. It was proposed in the context of frequent itemsets and association rule mining. Frequent pattern mining is used to find inherent regularities in data. What products were often purchased together? Its applications include basket data analysis, cross-marketing, catalog design, sale campaign analysis, Web log (click stream) analysis, and DNA sequence analysis. However, one of the bottlenecks of frequent itemset mining is that as the data increase the amount of time and resources required to mining the data increases at an exponential rate. In this investigation a new algorithm is proposed which can be uses as a pre-processor for frequent itemset mining. FASTER (FeAture SelecTion using Entropy and Rough sets) is a hybrid pre-processor algorithm which utilizes entropy and rough-sets to carry out record reduction and feature (attribute) selection respectively. FASTER for frequent itemset mining can produce a speed up of 3.1 times when compared to original algorithm while maintaining an accuracy of 71%.

Keywords: rough-sets, classification, feature selection, entropy, outliers, frequent itemset mining

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Authors: O. Badagadze, G. Sirbiladze, I. Khutsishvili

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The work proposes a decision support methodology for the credit risk minimization in selection of investment projects. The methodology provides two stages of projects’ evaluation. Preliminary selection of projects with minor credit risks is made using the Expertons Method. The second stage makes ranking of chosen projects using the Possibilistic Discrimination Analysis Method. The latter is a new modification of a well-known Method of Fuzzy Discrimination Analysis.

Keywords: expert valuations, expertons, investment project risks, positive and negative discriminations, possibility distribution

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Authors: Fatma Zehra Doğru, Olcay Arslan

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In this paper, we propose alternative robust estimators for the shape parameters of the Burr XII distribution. We provide a small simulation study and a real data example to illustrate the performance of the proposed estimators over the ML and the LS estimators.

Keywords: burr xii distribution, robust estimator, m-estimator, least squares

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Authors: Huseyin Guler, Cigdem Kosar

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The aim of this study is to propose Bridge estimator for seasonal unit root tests. Seasonality is an important factor for many economic time series. Some variables may contain seasonal patterns and forecasts that ignore important seasonal patterns have a high variance. Therefore, it is very important to eliminate seasonality for seasonal macroeconomic data. There are some methods to eliminate the impacts of seasonality in time series. One of them is filtering the data. However, this method leads to undesired consequences in unit root tests, especially if the data is generated by a stochastic seasonal process. Another method to eliminate seasonality is using seasonal dummy variables. Some seasonal patterns may result from stationary seasonal processes, which are modelled using seasonal dummies but if there is a varying and changing seasonal pattern over time, so the seasonal process is non-stationary, deterministic seasonal dummies are inadequate to capture the seasonal process. It is not suitable to use seasonal dummies for modeling such seasonally nonstationary series. Instead of that, it is necessary to take seasonal difference if there are seasonal unit roots in the series. Different alternative methods are proposed in the literature to test seasonal unit roots, such as Dickey, Hazsa, Fuller (DHF) and Hylleberg, Engle, Granger, Yoo (HEGY) tests. HEGY test can be also used to test the seasonal unit root in different frequencies (monthly, quarterly, and semiannual). Another issue in unit root tests is the lag selection. Lagged dependent variables are added to the model in seasonal unit root tests as in the unit root tests to overcome the autocorrelation problem. In this case, it is necessary to choose the lag length and determine any deterministic components (i.e., a constant and trend) first, and then use the proper model to test for seasonal unit roots. However, this two-step procedure might lead size distortions and lack of power in seasonal unit root tests. Recent studies show that Bridge estimators are good in selecting optimal lag length while differentiating nonstationary versus stationary models for nonseasonal data. The advantage of this estimator is the elimination of the two-step nature of conventional unit root tests and this leads a gain in size and power. In this paper, the Bridge estimator is proposed to test seasonal unit roots in a HEGY model. A Monte-Carlo experiment is done to determine the efficiency of this approach and compare the size and power of this method with HEGY test. Since Bridge estimator performs well in model selection, our approach may lead to some gain in terms of size and power over HEGY test.

Keywords: bridge estimators, HEGY test, model selection, seasonal unit root

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Authors: Agoston Restas

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Introduction: This paper describes many initiatives and shows also practical examples which happened recently using Unmanned Aerial Systems (UAS) to support disaster management. Since the operation of manned aircraft at disasters is usually not only expensive but often impossible to use as well, in many cases managers fail to use the aerial activity. UAS can be an alternative moreover cost-effective solution for supporting disaster management. Methods: This article uses thematic division of UAS applications; it is based on two key elements, one of them is the time flow of managing disasters, other is its tactical requirements. Logically UAS can be used like pre-disaster activity, activity immediately after the occurrence of a disaster and the activity after the primary disaster elimination. Paper faces different disasters, like dangerous material releases, floods, earthquakes, forest fires and human-induced disasters. Research used function analysis, practical experiments, mathematical formulas, economic analysis and also expert estimation. Author gathered international examples and used own experiences in this field as well. Results and discussion: An earthquake is a rapid escalating disaster, where, many times, there is no other way for a rapid damage assessment than aerial reconnaissance. For special rescue teams, the UAS application can help much in a rapid location selection, where enough place remained to survive for victims. Floods are typical for a slow onset disaster. In contrast, managing floods is a very complex and difficult task. It requires continuous monitoring of dykes, flooded and threatened areas. UAS can help managers largely keeping an area under observation. Forest fires are disasters, where the tactical application of UAS is already well developed. It can be used for fire detection, intervention monitoring and also for post-fire monitoring. In case of nuclear accident or hazardous material leakage, UAS is also a very effective or can be the only one tool for supporting disaster management. Paper shows some efforts using UAS to avoid human-induced disasters in low-income countries as part of health cooperation.

Keywords: disaster management, floods, forest fires, Unmanned Aerial Systems

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Authors: David Ruiz, Carlos Nava, Roberto Carbajal

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The psychological profile has become one of the most important sources of information when it comes to individual selection and the hiring process in any organization. Psychological instruments are used to collect data about variables that are considered critically important for performance in work. However, because of conceptual chaos in organizational psychology, most of the information provided by psychological testing is not directly useful for Mexican human resources professionals to take hiring decisions. The aims of this paper are 1) to underline the lack of conceptual precision in theoretical testing foundations in Mexico and 2) presenting a reliability and validity analysis of a frustration tolerance instrument created as an alternative to a heuristically conduct individual assessment in organizations. First, a description of assessment conditions in Mexico is made. Second, an instrument and a theoretical framework is presented as an alternative to the assessment practices in the country. A total of 65 Psychology Iztacala Superior Studies Faculty students were assessed. Cronbach´s alpha coefficient was calculated and an exploratory factor analysis was carried out to prove the scale unidimensionality. Reliability analysis revealed good internal consistency of the scale (Cronbach’s α = 0.825). Factor analysis produced 4 factors for the scale. However, factor loadings and explained variation give proof to the scale unidimensionality. It is concluded that the instrument has good psychometric properties that will allow human resources professionals to collect useful data. Different possibilities to conduct psychological assessment are suggested for future development.

Keywords: psychological assessment, frustration tolerance, human resources, organizational psychology

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Authors: G. Krishna Mohana Rao, P. Ravi Kumar

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Milling is the process of removing unwanted material with suitable tool. Even though the milling process is having wider application, the vibration of machine tool and work piece during the process produces chatter on the products. Various methods of preventing the chatter have been incorporated into machine tool systems. Damper is cut into equal number of parts. Each part is called as finger. Multiple fingers were inserted in the hollow portion of the shank to reduce tool vibrations. In the present work, nonlinear static and dynamic analysis of the damper inserted end milling cutter used to reduce the chatter was done. A comparison is made for the milling cutter with multiple dampers. Surface roughness was determined by machining with multiple finger inserted milling cutters.

Keywords: damping inserts, end milling, vibrations, nonlinear dynamic analysis, number of fingers

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Authors: Abul Quasem Al-Amin, Md. Hasanuzzaman, Mohammad Nurul Azam, Walter Leal Filho

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With regard to the future energy strategy and vision, this study aimed to find the drawbacks of proposed energy diversification policy for 2020. To have a clear picture of the drawback and competitive alternative, this study has explored two scenarios, namely Scenario a and Scenario b. The Scenario a indicates that in the year 2020 the GHG emissions would be 823,498.00 million tons (Mt) with a 2020 final demand and proposed fuel mix such as by the Five-Fuel Diversification Strategy. In contrast, as an alternative, the Scenario b with biofuel potentials indicates that the substitution of coal energy by 5%, 10%, and 15%, respectively, with biofuel, would reduce the GHG emissions from 374,551.00, 405,118.00, and 823,498.00 million tons to 339,964.00, 329,834.00, and 305,288.00 million tons, respectively, by the present fuel mix, business-as-usual fuel mix, and proposed fuel mix up to the year 2020. Therefore, this study has explored a healthy alternative by introducing biofuel renewable energy option instead of conventional energy utilization in the power generation with environmental aspect in minds. This study effort would lessen the gap between GHG mitigation and future sustainable development and would useful to formulate effective renewable energy strategy in Malaysia.

Keywords: energy, environmental impacts, renewable energy, biofuel, energy policy

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Authors: Sophie Oakes-Rogers, Di Bailey, Karen Slade

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Female offenders are a uniquely vulnerable group, who are at high risk of suicide. Whilst the prevention of self-harm and suicide remains a key global priority, we need to better understand the relationship between these challenging behaviours that constitute a pressing problem, particularly in environments designed to prioritise safety and security. Method choice is unlikely to be random, and is instead influenced by a range of cultural, social, psychological and environmental factors, which change over time and between countries. A key aspect of self-harm and suicide in women receiving forensic care is the lack of free access to methods. At a time where self-harm and suicide rates continue to rise internationally, understanding the role of these influencing factors and the impact of current suicide prevention strategies on the use of near-lethal methods is crucial. This poster presentation will present findings from 25 interviews and 3 focus groups, which enlisted a Participatory Action Research approach to explore the differences between self-harming and suicidal behavior. A key element of this research was using the lived experiences of women receiving forensic care from one forensic pathway in the UK, and the staffs who care for them, to discuss the role of near-lethal self-harm (NLSH). The findings and suggestions from the lived accounts of the women and staff will inform a draft assessment tool, which better assesses the risk of suicide based on the lethality of methods. This tool will be the first of its kind, which specifically captures the needs of women receiving forensic services. Preliminary findings indicate women engage in NLSH for two key reasons and is determined by their history of self-harm. Women who have a history of superficial non-life threatening self-harm appear to engage in NLSH in response to a significant life event such as family bereavement or sentencing. For these women, suicide appears to be a realistic option to overcome their distress. This, however, differs from women who appear to have a lifetime history of NLSH, who engage in such behavior in a bid to overcome the grief and shame associated with historical abuse. NLSH in these women reflects a lifetime of suicidality and indicates they pose the greatest risk of completed suicide. Findings also indicate differences in method selection between forensic provisions. Restriction of means appears to play a role in method selection, and findings suggest it causes method substitution. Implications will be discussed relating to the screening of female forensic patients and improvements to the current suicide prevention strategies.

Keywords: forensic mental health, method substitution, restriction of means, suicide

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Authors: Todd Zhou, Mikhail Yurochkin

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Out-of-distribution (OOD) detection is receiving increasing amounts of attention in the machine learning research community, boosted by recent technologies, such as autonomous driving and image processing. This newly-burgeoning field has called for the need for more effective and efficient methods for out-of-distribution generalization methods. Without accessing the label information, deploying machine learning models to out-of-distribution domains becomes extremely challenging since it is impossible to evaluate model performance on unseen domains. To tackle this out-of-distribution detection difficulty, we designed a model selection pipeline algorithm and developed a model selection framework with different impurity and randomness measurements to evaluate and choose the best-performing models for out-of-distribution data. By exploring different randomness scores based on predicted probabilities, we adopted the out-of-distribution entropy and developed a custom-designed score, ”CombinedScore,” as the evaluation criterion. This proposed score was created by adding labeled source information into the judging space of the uncertainty entropy score using harmonic mean. Furthermore, the prediction bias was explored through the equality of opportunity violation measurement. We also improved machine learning model performance through model calibration. The effectiveness of the framework with the proposed evaluation criteria was validated on the Folktables American Community Survey (ACS) datasets.

Keywords: model selection, domain generalization, model fairness, randomness measurements, bias index

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Authors: Umut Erksan Senalp

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The aim of this study is to examine the link between firm level productivity heterogeneity and firm’s decision to export. Thus, we test the self selection hypothesis which suggests only more productive firms self select themselves to export markets. We analyze UK manufacturing sector by using firm-level data for the period 2003-2011. Although our preliminary results suggest that exporters outperform non-exporters when we pool all manufacturing industries, when we examine each industry individually, we find that self-selection hypothesis does not hold for each industries.

Keywords: total factor productivity, firm heterogeneity, international trade, decision to export

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Authors: A. Achour L. Chekour, A. Mekroud

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Tribology, the science of lubrication, friction and wear, plays an important role in science "crossroads" initiated by the recent developments in the industry. Its multidisciplinary nature reinforces its scientific interest. It covers all the sciences that deal with the contact between two solids loaded and relative motion. It is thus one of the many intersections more clearly established disciplines such as solid mechanics and the fluids, rheological, thermal, materials science and chemistry. As for his experimental approach, it is based on the physical and processing signals and images. The optimization of operating conditions by cutting tool must contribute significantly to the development and productivity of advanced automation of machining techniques because their implementation requires sufficient knowledge of how the process and in particular the evolution of tool wear. In addition, technological advances have developed the use of very hard materials, refractory difficult machinability, requiring highly resistant materials tools. In this study, we present the behavior wear a machining tool during the roughing operation according to the cutting parameters. The interpretation of the experimental results is based mainly on observations and analyzes of sharp edges e tool using the latest techniques: scanning electron microscopy (SEM) and optical rugosimetry laser beam.

Keywords: friction, wear, tool, cutting

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Authors: Jacob Seddlemeyer, Tahar Messadi, Hongmei Gu, Mahboobeh Hemmati

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The main purpose of this first tier of the study is to quantify and compare the embodied environmental impacts associated with alternative materials applied to Adohi Hall, a residence building at the University of Arkansas campus, Fayetteville, AR. This 200,000square foot building has5 stories builtwith mass timber and is compared to another scenario where the same edifice is built with a steel frame. Based on the defined goal and scope of the project, the materials respectivetothe respective to the two building options are compared in terms of Global Warming Potential (GWP), starting from cradle to the construction site, which includes the material manufacturing stage (raw material extract, process, supply, transport, and manufacture) plus transportation to the site (module A1-A4, based on standard EN 15804 definition). The consumedfossil fuels and emitted CO2 associated with the buildings are the major reason for the environmental impacts of climate change. In this study, GWP is primarily assessed to the exclusion of other environmental factors. The second tier of this work is to evaluate Tally’s performance in the decision-making process through the design phases, as well as determine its strengths and weaknesses. Tally is a Life Cycle Assessment (LCA) tool capable of conducting a cradle-to-grave analysis. As opposed to other software applications, Tally is specifically targeted at buildings LCA. As a peripheral application, this software tool is directly run within the core modeling application platform called Revit. This unique functionality causes Tally to stand out from other similar tools in the building sector LCA analysis. The results of this study also provide insights for making more environmentally efficient decisions in the building environment and help in the move forward to reduce Green House Gases (GHGs) emissions and GWP mitigation.

Keywords: comparison, GWP, LCA, materials, tally

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Authors: Hamidrza Joodaki

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The most complex issue in urban land use planning is site selection that needs to assess the verity of elements and factors. Multi Criteria Decision Making (MCDM) methods are the best approach to deal with complex problems. In this paper, combination of the analytical hierarchy process (AHP) model and FUZZY logic was used as MCDM methods to select the best site for gas station in the 4th gas zone of Tehran. The first and the most important step in FUZZY-AHP model is selection of criteria and sub-criteria. Population, accessibility, proximity and natural disasters were considered as the main criteria in this study. After choosing the criteria, they were weighted based on AHP by EXPERT CHOICE software, and FUZZY logic was used to enhance accuracy and to approach the reality. After these steps, criteria layers were produced and weighted based on FUZZY-AHP model in GIS. Finally, through ARC GIS software, the layers were integrated and the 4th gas zone in TEHRAN was selected as the best site to locate gas station.

Keywords: multiple criteria decision making (MCDM), analytic hierarchy process (AHP), FUZZY logic, geographic information system (GIS)

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Authors: Vikrum Malhotra, Manpreet Kaur, Ayesha Ghotto

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Background: Cardiac registries such as ACC Percutaneous Coronary Intervention Registry require high quality data to be abstracted, including data elements such as nuclear cardiology, diagnostic coronary angiography, and PCI. Introduction: The audit tool created is used by data abstractors to provide data audits and assess the accuracy and inter-rater reliability of abstraction performed by the abstractors for a health system. This audit tool solution has been developed across 13 registries, including ACC/NCDR registries, PCI, STS, Get with the Guidelines. Methodology: The data audit tool was used to audit internal registry abstraction for all data elements, including stress test performed, type of stress test, data of stress test, results of stress test, risk/extent of ischemia, diagnostic catheterization detail, and PCI data elements for ACC/NCDR PCI registries. This is being used across 20 hospital systems internally and providing abstraction and audit services for them. Results: The data audit tool had inter-rater reliability and accuracy greater than 95% data accuracy and IRR score for the PCI registry in 50 PCI registry cases in 2021. Conclusion: The tool is being used internally for surgical societies and across hospital systems. The audit tool enables the abstractor to be assessed by an external abstractor and includes all of the data dictionary fields for each registry.

Keywords: abstraction, cardiac registry, cardiovascular registry, registry, data

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Authors: Ashish Ankus Yerunkar, Ravi Terkar

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Study aimed at evaluating the best process environment which could simultaneously satisfy requirements of both quality as well as productivity with special emphasis on reduction of cutting tool flank wear, because reduction in flank wear ensures increase in tool life. The predicted optimal setting ensured minimization of surface roughness. Purpose of this paper is focused on the analysis of optimum cutting conditions to get lowest surface roughness in turning SCM 440 alloy steel by Taguchi method. Design for the experiment was done using Taguchi method and 18 experiments were designed by this process and experiments conducted. The results are analyzed using ANOVA method. Taguchi method has depicted that the depth of cut has significant role to play in producing lower surface roughness followed by feed. The Cutting speed has lesser role on surface roughness from the tests. The vibrations of the machine tool, tool chattering are the other factors which may contribute poor surface roughness to the results and such factors ignored for analyses. The inferences by this method will be useful to other researches for similar type of study and may be vital for further research on tool vibrations, cutting forces etc.

Keywords: surface roughness (ra), machining, dry turning, taguchi method, turning process, anova method, mahr perthometer

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Authors: Lukasz Szydlowski, Jiri Ehlich, Igor Goryanin

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We demonstrate a single chamber, 96-well-plated based Microbial Fuel Cell (MFC) with printed, electronic components. This invention is aimed at robust selection of electrogenic microbial community under specific conditions, e.g., electrode potential, pH, nutrient concentration, salt concentration that can be altered within the 96 well plate array. This invention enables robust selection of electrogenic microbial community under the homogeneous reactor, with multiple conditions that can be altered to allow comparative analysis. It can be used as a standalone technique or in conjunction with other selective processes, e.g., flow cytometry, microfluidic-based dielectrophoretic trapping. Mobile conductive elements, like carbon paper, carbon sponge, activated charcoal granules, metal mesh, can be inserted inside to increase the anode surface area in order to collect electrogenic microorganisms and to transfer them into new reactors or for other analytical works. An array of 96-well plate allows this device to be operated by automated pipetting stations.

Keywords: bioengineering, electrochemistry, electromicrobiology, microbial fuel cell

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Authors: M. Javahar, H. B. Dong

Abstract:

Single crystal components manufactured using Ni-base Superalloys are routinely used in the hot sections of aero engines and industrial gas turbines due to their outstanding high temperature strength, toughness and resistance to degradation in corrosive and oxidative environments. To control the quality of the single crystal turbine blades, particular attention has been paid to grain selection, which is used to obtain the single crystal morphology from a plethora of columnar grains. For this purpose, different designs of grain selectors are employed and the most common type is the spiral grain selector. A typical spiral grain selector includes a starter block and a spiral (helix) located above. It has been found that the grains with orientation well aligned to the thermal gradient survive in the starter block by competitive grain growth while the selection of the single crystal grain occurs in the spiral part. In the present study, 2D spiral selectors with different geometries were designed and produced using a state-of-the-art Bridgeman Directional Solidification casting furnace to investigate the competitive growth during grain selection in 2d grain selectors. The principal advantage of using a 2-D selector is to facilitate the wax injection process in investment casting by enabling significant degree of automation. The automation within the process can be derived by producing 2D grain selector wax patterns parts using a split die (metal mold model) coupled with wax injection stage. This will not only produce the part with high accuracy but also at an acceptable production rate.

Keywords: grain selector, single crystal, directional solidification, CMSX-4 superalloys, investment casting

Procedia PDF Downloads 566

Authors: Kazi Hossain

Abstract:

The National Australian Built Environment Rating System (NABERS) is the key industry standard for measuring and benchmarking environmental performance of existing buildings in Australia. Developed and run by the New South Wales government, NABERS measures the operational efficiency of different types of buildings by using a set of tools that provide an easy to understand graphical rating outcome ranged from 0 to 6 stars. This set of tools also include a tool called NABERS IE which enables tenants or building managers to benchmark their buildings indoor environment quality against the national market. Launched in 2009, the number NABERS IE ratings have steadily increased from 10 certified ratings in 2011 to 43 in 2013. However there is a massive uptake of over 50 ratings alone in 2014 making the number of ratings to reach over 100. This paper outlines the methodology used to create this tool, a statistical overview of the tool, and the driving factor that motivates the building owners and managers to use this tool every year to rate their buildings.

Keywords: Acoustic comfort, Indoor air quality, Indoor Environment, NABERS, National Australian Built Environment Rating System, Performance rating, Rating System, Thermal comfort, Ventilation effectiveness, Visual comfort.

Procedia PDF Downloads 537

Authors: Zhongzhi Hu, Jie Shen, Jiqiang Wang

Abstract:

A high precision aeroengine model is needed when developing the engine control system. Compared with other main components, the axial compressor is the most challenging component to simulate. In this paper, a compressor map optimizing tool based on the introduction of a modifiable β function is developed for FWorks (FADEC Works). Three parameters (d density, f fitting coefficient, k₀ slope of the line β=0) are introduced to the β function to make it modifiable. The comparison of the traditional β function and the modifiable β function is carried out for a certain type of compressor. The interpolation errors show that both methods meet the modeling requirements, while the modifiable β function can predict compressor performance more accurately for some areas of the compressor map where the users are interested in.

Keywords: beta function, compressor map, interpolation error, map optimization tool

Procedia PDF Downloads 249