An Evolutionary Optimization Algorithm for Automated Classical Machine Learning

Machine learning is an evolving branch of computational algorithms that allow computers to learn from experiences, make predictions, and solve different problems without being explicitly programmed. However, building a useful machine learning model is a challenging process, requiring human expertise to perform various proper tasks and ensure that the machine learning\u27s primary objective --determining the best and most predictive model-- is achieved. These tasks include pre-processing, feature selection, and model selection. Many machine learning models developed by experts are designed manually and by trial and error. In other words, even experts need the time and resources to create good predictive machine learning models. The idea of automated machine learning (AutoML) is to automate a machine learning pipeline to release the burden of substantial development costs and manual processes. The algorithms leveraged in these systems have different hyper-parameters. On the other hand, different input datasets have various features. In both cases, the final performance of the model is closely related to the final selected configuration of features and hyper-parameters. That is why they are considered as crucial tasks in the AutoML. The challenges regarding the computationally expensive nature of tuning hyper-parameters and optimally selecting features create significant opportunities for filling the research gaps in the AutoML field. This dissertation explores how to select the features and tune the hyper-parameters of conventional machine learning algorithms efficiently and automatically. To address the challenges in the AutoML area, novel algorithms for hyper-parameter tuning and feature selection are proposed. The hyper-parameter tuning algorithm aims to provide the optimal set of hyper-parameters in three conventional machine learning models (Random Forest, XGBoost and Support Vector Machine) to obtain best scores regarding performance. On the other hand, the feature selection algorithm looks for the optimal subset of features to achieve the highest performance. Afterward, a hybrid framework is designed for both hyper-parameter tuning and feature selection. The proposed framework can discover close to the optimal configuration of features and hyper-parameters. The proposed framework includes the following components: (1) an automatic feature selection component based on artificial bee colony algorithms and machine learning training, and (2) an automatic hyper-parameter tuning component based on artificial bee colony algorithms and machine learning training for faster training and convergence of the learning models. The whole framework has been evaluated using four real-world datasets in different applications. This framework is an attempt to alleviate the challenges of hyper-parameter tuning and feature selection by using efficient algorithms. However, distributed processing, distributed learning, parallel computing, and other big data solutions are not taken into consideration in this framework

A2BCF: An Automated ABC-Based Feature Selection Algorithm for Classification Models in an Education Application

Feature selection is an essential step of preprocessing in Machine Learning (ML) algorithms that can significantly impact the performance of ML models. It is considered one of the most crucial phases of automated ML (AutoML). Feature selection aims to find the optimal subset of features and remove the noninformative features from the dataset. Feature selection also reduces the computational time and makes the data more understandable to the learning model. There are various heuristic search strategies to address combinatorial optimization challenges. This paper develops an Automated Artificial Bee Colony-based algorithm for Feature Selection (A2BCF) to solve a classification problem. The application domain evaluating our proposed algorithm is education science, which solves a binary classification problem, namely, undergraduate student success. The modifications made to the original Artificial Bee Colony algorithm make the algorithm a well-performed approach

Artificial neural network simulation and sensitivity analysis of heavy oil cracking unit

This paper presents an artificial neural network (ANN) model of heavy oil catalytic cracking (HOC). The main feature of the model isto provide general and accurate and fast responding model for analysis of HOC unit. In this study, American petroleum institute index(API) , weight percentage of sulfur, Conradson carbon residue content (CCR), gas, coke, and liquid volume percent conversion (%LV)of reaction were considered as network inputs while the percentage of normal butane (N-C4), iso-butane (I-C4), butene (C4=), propane(C3), propene (C3=), heavy cycle oil (HCO), and light cycle oil (LCO) and gasoline (GASO) were considered as network outputs. 70%of all industrial collected data set were utilized to train and find the best neural network. Among the different networks, feed-forwardmulti-layer perceptron network with Levenberg Marquardt (LM) training algorithm with 10 neurons in hidden layer was found as thebest network. The trained network showed good capability in anticipating the results of the unseen data (30% of the all data) of catalytic cracking unit with high accuracy. The obtained model can be used in optimization and process planning

Mission impossible? : peacekeeping and peacemaking in Cyprus

Cyprus, the third largest Mediterranean island with a population of around 800,000, is the site of one of the globe s most intractable conflicts. However, since the beginning of the seventies, there has generally not been anything other than minor violent incidents between the two main communities on the island, which are of Greek and Turkish origin. In fact, according to Turkey and the Turkish Cypriots, the conflict in Cyprus was solved in 1974, when the Greek- and Turkish Cypriots were geographically separated into two distinct communities by the Turkish military invasion and occupation of the northern one-third of the island. This allowed for the emergence of a separate Turkish Cypriot state, TRNC, which is still not recognised by any country except Turkey. Nevertheless, despite numerous international efforts to help find a peaceful resolution, the conflict is very much alive today between the Greek- and Turkish Cypriots. In addition, Cyprus has been, and is deeply affected by the animosity between the two mother countries Greece and Turkey, and their involvement in the dispute. The aim of this study has been to gain insight about the peacemaking process in the Cyprus conflict, and the reasons for the continued stalemate on the island. Two questions have been examined: 1) to what degree and how has the United Nations engagement in Cyprus influenced the negotiation process and the prospects for peace? And, 2) to what degree and how has the European Union s accession negotiations affected the peacemaking process and the protracted stalemate? However, in order to answer these questions, it has been necessary to also consider the (pre) existing contextual environment of the conflict, in order to identify the kind of situation that confronts any actor wanting to assist in finding a solution to this protracted conflict. My working hypothesis stated that the UN s peacekeeping force in Cyprus s (UNFICYP) success in limiting armed conflict has reduced the Cypriot parties incentives for peace negotiations and has consequently hindered the UN s peacemaking efforts by reinforcing the stalemate. Zartman s hurting stalemate theory states that incentives for peace negotiations would be greater if each side felt the conflict situation as more pressing and costly. My analysis indicates that this argument has some validity in the Cyprus case. The tolerable and non-hurting status quo situation has raised the parties resistant points in the peace negotiations. Both sides have defined concessions on their part as more costly than the continuation of the status quo situation. On the other hand, I also found that UNFICYP, by contributing to calm the situation, has to a certain extent encouraged peacemaking. The analysis reveals that without the presence of UNFICYP, the odds for armed conflict on Cyprus and in the region would increase, making it even harder to get the parties to the negotiation table. This is particularly due to the deep intercommunal mistrust between the two communities on the island, as well as the interests and involvement of the mother countries Greece and Turkey, which are among the important factors contributing to the continuing stalemate on the island. UNFICYP contribution in calming the situation can thus be seen as a necessary, but not sufficient contribution to peacemaking. However, the ultimate aim of all UN involvement is to achieve a long lasting solution to the underlying issues of the conflict, thus making its own involvement superfluous. The UN s peacemaking efforts in Cyprus have not yet achieved this, in spite of countless UN led negotiations between the disputing parties over the years. My findings suggest that the main reasons for failed peacemaking are a combination of the contextual factors at the inter-communal and regional level, as well as organisational factors related to the UN itself: There are some characteristics of the UN as a third party which may make it unsuitable for breaking the continuing stalemate on Cyprus. I have shown that there are certain contradictions in the international system related to sovereignty, non-intervention and territorial integrity on the one side, and the rights of ethnic groups on the other. These contradictions can hinder mediation efforts and actually may lead to escalation, since the UN s own principle and arena can be used as a legitimate channel of conflict. It has been demonstrated that this is indeed so in Cyprus. The UN s long engagement has made it a hostage to its own resolutions, and has drawn the UN itself into the conflict environment. Adding the UN s limited leverage power, the disputants have been able to opt for a continuation of their struggle for their initial objectives, rather than a compromise. On the other hand, the EU accession negotiations have been seen as a crucial situational pressure that would alter the parties incentives for a solution. There are some strong economic and political interests tied to a EU membership. The EU may, therefore, by virtue of its own attributes, create a movement in the parties perceptions which the UN is not able to do. I therefore attempted in the last analytical chapter to examine the so-called EU catalyst effect on the Cyprus conflict. The underlying aim was to analyse whether Cyprus and Turkey s prospects for EU membership have created incentives for a solution on the part of the disputing parties. My findings showed that the EU accession process is indeed the most important factor effecting on the situation in Cyprus today. However, the EU process has not, per today, had the positive effect towards a solution as initially foreseen. I found that the accession negotiations give too much importance to economic rationality over societal security. Secondly, the EU is perceived as a biased party, accused by Turkey and the Turkish Cypriots of privileging Greek over Turkish interests. Thirdly, the analysis shows that the EU has a hard time pressing Turkey towards change because of the Turkish perception of its own geostrategic importance. Lastly, the fact that the EU removed the precondition of a settlement before Cyprus s accession leaves no strong incentives for the Greek Cypriots to concede and find a solution. As the EU accession talks proceed, each side is actually hardening its attitudes. The prospects for Cyprus joining the EU as a unified federal state seem therefore per today, as quite uncertain. The thesis found that ultimately, Turkey and the EU (through its membership offer) retain the key to allowing a political settlement in Cyprus. This implies that Ankara should be given a clear prospect of EU membership if it manages to meet all the EU requirements. Without a stronger feeling of really being accepted as a EU-candidate, it will be likely that Turkey national forces in Turkey will triumph, making the eastern Mediterranean even more disturbed in the near future

Generating Labour Cost Budget for a Construction-Oriented Fabrication Facility: Simulation-based Resource Scheduling Approach

A novel labour-hour budgeting methodology is proposed by integrating productivity concepts in project scheduling and budgeting to enhance the accuracy of labour cost budgeting for planning labour-intensive projects. The proposed methodology applies discrete event simulation approach to represent crew formation, labour resource utilization and labour resource flowing between consecutive activities, which allows for quantitatively characterizing the impact of labour semi-productive time on labour cost budgeting as a time-dependent variable. Simulation-based assessment of variations in crew sizes and labour allocations is conducive to reducing semi-productive time and thus enhancing the cost performance of the whole project. The proposed methodology is then applied in a real-world case study for planning steel girder fabrication projects in construction of highway bridges. Not limited to budgeting for labour resources in construction-oriented fabrication facility, the research contributions are also significant to other construction planning settings where limited resources are shared and utilized among different activities.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Futures Studies in Health: Choosing the Best Intelligent Data Mining Model to Predict and Diagnose liver Cancer in Early Stage

Introduction: Primary liver cancer (­HCC), is the fifth most common type of cancer and the third leading cause of death in the world. Symptoms of liver cancer will progress rapidly after the onset of the disease, and unfortunately, the patients' survival rate is very low. One of the main problems for gastroenterologists is the prediction and early detection of liver cancer. Data mining techniques can be used to understand and predict cancer. The aim of this study was to identify the best model based on intelligent data mining to predict and diagnose liver cancer in an early stage. Method: In the present article, a retrospective study was conducted on 516 cases of primary and secondary liver cancer, and 22 risk factors were examined. Data were collected from the patients' files and analyzed using 5 data mining models including VFI Classifier, Regression Classifier, Hyper Pipes Classifier, Functional trees with logistic regression, and Meta Multi Class Classifier with the highest precision (Precision). These models were compared. Results: The precision, sensitivity, specificity, and the area under the curve of VFI Classifier model were respectively 71.29%, 49%, 50%, and 63.31%, and VFI Classifier model is the best model based on intelligent data mining to predict and diagnose liver cancer in an early stage. Conclusion: If properly designed, data mining model VFI Classifier can predict liver cancer or detect it in an early stage

Developing a Smartphone-Based Educational Application for Women at Risk of Endometriosis

Introduction: Since endometriosis is a chronic disease and requires long-term care, it can have a devastating effect on life quality. For this reason, it is necessary to increase awareness and educate women about endometriosis. In this regard, a mobile phone-based endometriosis training program was designed. Method: The present paper is a development-applied study and was conducted in two stages. In the first stage, to determine the educational content, after reviewing previous studies, the questions obtained were given to eleven gynecologists and reproductive health doctors to measure the necessity and effectiveness of each question. After being designed, the program was provided to 40 women of reproductive age, and the usability of the program was assessed. Data analysis was performed using SPSS 22 software. Results: The required educational content of the application was presented in five groups and confirmed by specialists. The mean age of women who participated in this study was 32.35 ± 11.70 years. The average score of usability of the program was 8.34 out of 9 points which indicates a "good" level of satisfaction. Conclusion: Educating women through new popular tools such as mobile phones can play an important role in raising awareness and influencing their treatment. Therefore, designing a mobile phone-based training program in the field of education and awareness for women at risk of endometriosis can be advantageous

A Webometric Analysis of ISI Medical Journals Using Yahoo, AltaVista, and All the Web Search Engines

The World Wide Web is an important information source for scholarly communications. Examining the inlinks via webometrics studies has attracted particular interests among information researchers. In this study, the number of inlinks to 69 ISI medical journals retrieved by Yahoo, AltaVista, and All The web Search Engines were examined via a comparative and Webometrics study. For data analysis, SPSS software was employed. Findings revealed that British Medical Journal website attracted the most links of all in the three search engines. There is a significant correlation between the number of External links and the ISI impact factor. The most significant correlation in the three search engines exists between external links of Yahoo and AltaVista (100%) and the least correlation is found between external links of All The web & the number of pages of AltaVista (0.51). There is no significant difference between the internal links & the number of pages found by the three search engines. But in case of impact factors, significant differences are found between these three search engines. So, the study shows that journals with higher impact factor attract more links to their websites. It also indicates that the three search engines are significantly different in terms of total links, outlinks and web impact factor

Mediastinal Masses: Review of 105 Cases

There has been a highly significant increase in the number of patients with malignant mediastinal tumors in the last four decades. Since these lesions are infrequently encountered and there are very few reports in Iran concerning this issue, we performed this study to review our institutional experience of medias-tinal masses and to compare differences in the clinical spectrum between our study population and other patients studied by various reports. This was a retrospective, descriptive and cross sectional study conducted on 105 patients with mediastinal masses who underwent surgical resection over a 5-year period from 1999 to 2003 in three major hospitals in Tehran. A total of 105 patients with mediastinal masses including 65 males (62%) and 40 females (38%) with a mean age of 34 years (range,2-80 years) who had undergone surgery entered the study. Most mediastinal tumors (47%) were identified in the third and fifth decades of life and the most common malignancy during the first four decades of life was malignant lymphoma. Considering the location of mediastinal masses,the anterior mediastinum was the most common site (65%) followed by paravertebral sulci (21%) and visceral mediastinum (14%).The highest rate of malignancy was observed in visceral mediastinum (73% malignancy rate). Histopathologic evaluation of resected masses revealed twenty two types of tumors of which sixty percent were malignant. Nonspecific symptoms such as dyspnea (41%) and cough (40%) constituted the most presenting complaints. Twelve percent of patients were completely asymptomatic. The most common complication observed in this series of mediastinal masses was Superior Vena Cava (SVC) syndrome. There was no postoperative complication. Crude mortality rate of the whole series was 16%. The prevalence of tumors in our series varied from some previously published reports. We demonstrated definite differences in histologic distribution, age range, malignancy rate and diagnostic methods of mediastinal tumors between our study population and other reported cases which should be considered in the evaluation and planning of therapeutic modalities for mediastinal masses encountered in our current practice