Search results for: decision tree classifier

Authors: Kemal Polat

Abstract:

In this paper, an attribute weighting method called fuzzy C-means clustering based attribute weighting (FCMAW) for classification of Diabetes disease dataset has been used. The aims of this study are to reduce the variance within attributes of diabetes dataset and to improve the classification accuracy of classifier algorithm transforming from non-linear separable datasets to linearly separable datasets. Pima Indians Diabetes dataset has two classes including normal subjects (500 instances) and diabetes subjects (268 instances). Fuzzy C-means clustering is an improved version of K-means clustering method and is one of most used clustering methods in data mining and machine learning applications. In this study, as the first stage, fuzzy C-means clustering process has been used for finding the centers of attributes in Pima Indians diabetes dataset and then weighted the dataset according to the ratios of the means of attributes to centers of theirs. Secondly, after weighting process, the classifier algorithms including support vector machine (SVM) and k-NN (k- nearest neighbor) classifiers have been used for classifying weighted Pima Indians diabetes dataset. Experimental results show that the proposed attribute weighting method (FCMAW) has obtained very promising results in the classification of Pima Indians diabetes dataset.

Keywords: fuzzy C-means clustering, fuzzy C-means clustering based attribute weighting, Pima Indians diabetes, SVM

Procedia PDF Downloads 398

Authors: Jeremy Goldsmith

Abstract:

The Gambia, the smallest country in mainland Africa and one of the poorest countries on Earth, is currently experiencing historically unprecedented levels of out-migration to Europe. As a result, Gambians are currently among the top four nationalities emigrating to Europe. The central question that this thesis will address is: what factors impact the migration-related decision-making capabilities of Gambians? Based on interviews with NGOs, as well as those who have migrated and returned, are planning to migrate, and their friends and families, a pattern will emerge. This pattern will be woven into first person narratives which will explore the politico-economic, environmental, and socio-cultural factors that inform individual decision-making with regards to migration.

Keywords: migration, The Gambia, Africa, politico-economic, sociocultural, environmental

Procedia PDF Downloads 316

Authors: Mariam Shah

Abstract:

Strict liability is frequently used in magistrate’s courts for TV license and driving offences.There is existing research suggesting that the strict liability approach to criminal offences can result in ‘absurd’ judicial outcomes, or potentially ‘injustice’.This paper will discuss the potential merits of strict liability as a method for dealing with shoplifting offences.Currently, there is disparity in sentencing outcomes in the UK, particularly in relation to shoplifting offences.This paper will question whether ‘injustice’ is actually in the differentiation of defendants based upon their ‘perceived’ circumstances, which could be resulting in arbitrary judicial decision making.

Keywords: arbitrary, decision making, judicial decision making, shoplifting, stereotypes, strict liability

Procedia PDF Downloads 301

Authors: Kuanrong Qiu, Sebnem Madrali, Evgueniy Entchev

Abstract:

To achieve the satisfactory objectives in deploying integrated renewable energy systems, it is crucial to consider all the related parameters affecting the design and decision-making. The multi-criteria evaluation method is a reliable and efficient tool for achieving the most appropriate solution. The approach considers the influential factors and their relative importance in prioritizing the alternatives. In this paper, a multi-criteria decision framework, based on the criteria including technical, economic, environmental and reliability, is developed to evaluate and prioritize renewable energy technologies and configurations of their integrated systems for community applications, identify their viability, and thus support the adoption of the clean energy technologies and the decision-making regarding energy transitions and transition patterns. Case studies for communities in Canada show that resource availability and the configurations of the integrated systems significantly impact the economic performance and environmental performance.

Keywords: multi-criteria, renewables, integrated energy systems, decision-making, model

Procedia PDF Downloads 78

Authors: Itai Kohavi, Wojciech Nowiak

Abstract:

This article explores the stagnation of the Israeli -Palestinian peace negotiation process, and the reasons behind the failure of more than 12 international initiatives to resolve the conflict. Twenty-seven top members of the Israeli national security elite (INSE) were interviewed, including heads of the negotiation teams, the National Security Council, the Mossad, and other intelligence and planning arms. The interviewees provided their insights on the Israeli challenges in reaching a sustainable and stable peace agreement and in dealing with the international pressure on Israel to negotiate a peace agreement while preventing anti-Israeli UN decisions and sanctions. The findings revealed a decision tree, with red herring deception strategies implemented to postpone the negotiation process and to delay major decisions during the negotiation process. Beyond the possible applications for the Israeli – Palestinian conflict, the findings shed more light on the phenomenon of rational deception of allies in a negotiation process, a subject less frequently researched as compared with deception of rivals.

Keywords: deception, Israeli-Palestinian conflict, negotiation, red herring, terrorist state, treadmill negotiation

Procedia PDF Downloads 289

Authors: Nurunnaher Nurunnaher

Abstract:

This paper examines the impact of women’s participation in microcredit on women’s decision making in the slum areas of Dhaka city, Bangladesh. There is confusion in the literature about whether women’s empowerment is or is not a trickle down impact of poverty alleviation or household well-being, and the studies use more or less similar indicators to measure the status of household and the status of women. Studies very rarely conceptualize and operationalize the term ‘empowerment’ as the word is often used without proper care by policy makers and development practitioners instead of household wellbeing. Currently, decision making in many studies has been used as an indicator of women’s empowerment when assessing the impact of microcredit programs on women. Based on a qualitative and feminist study this paper operationalizes women’s empowerment through the development of a conceptual framework, the identification of assessment criteria and the development of proper indicators that guided the whole study. The testimonies of participants, both men and women, were the basis of exploration of women’s lived experiences, which is the most appropriate method to explore the impact of such programs on women’s empowerment. The study considers empowerment as a process that affects various levels of life and gender relationships. The study found that there is a positive change in women’s position in decision making when women have developed an independent economic base with credit money. However, predominantly, women’s decision making is shared with men with the final decision still in the men’s hands. It can be said that women’s microcredit participation has not significantly challenged the social norms, therefore it is not surprising that women who hand over credit to their husband rarely have any power in intra-household bargaining process. Nevertheless, overall it is evident that women are continuously struggling toward the freedom to have the authority over household, economic and personal matters. It is concluded that while making strategic choices or gaining empowerment requires several steps, women’s participation in decision-making has several implications on their lives and potentially challenges patriarchy.

Keywords: women, gender inequality/equality, decision making, empowerment, microcredit, slums, Dhaka, Bangladesh

Procedia PDF Downloads 429

Authors: Dionne Coley B. A.

Abstract:

The role of a lawyer as a mediator is to be impartial in assisting parties to arrive at a decision. This decision should be made in a voluntary and mutually acceptable manner where the mediator encourages the parties to communicate, identify their interests, assess risks and consider settlement options. One of the key components to mediation is impartiality where mediators are to have a duty to remain impartial throughout the course of mediation and uphold an “objective” demeanor with both parties. The question is whether a mediator should take on evaluative role while encouraging the parties to come to a decision. This means that the mediator would not only encourage dialogue and responses between the parties but also assess and provide an opinion on the matter. This paper submits the argument that the role of a mediator should not be one of evaluation as this does not encourage the dialogue, process or desired outcomes associated with mediation.

Keywords: evaluation, lawyer, mediation, reform

Procedia PDF Downloads 411

Authors: Markou Vasiliki, Serdaris Panagiotis

Abstract:

The consumer behavior and decision-making process of consumers is a process that is affected by the factor of uncertainty. The onslaught of the Covid 19 pandemic has changed the consumer decision-making process in many ways. This change can be seen both in the buying process (how and where they shop) but also in the types of goods and services they are looking for. In addition, due to the mainly economic uncertainty that came from this event, but also the effects on both society and the economy in general, new consumer behaviors were created. Traditional forms of shopping are no longer a primary choice, consumers have turned to digital channels such as e-commerce and social media to fulfill needs. The purpose of this particular article is to examine how much the consumer's decision-making process has been affected after the pandemic and if consumer behavior has changed. An online survey was conducted to examine the change in decision making. Essentially, the demographic factors that influence the decision-making process were examined, as well as the social and economic factors. The research is divided into two parts. The first part included a literature review of the research that has been carried out to identify the factors, and the second part where the empirical investigation was carried out using a questionnaire and was done electronically with the help of Google Forms. The questionnaire was divided into several sections. They included questions about consumer behavior, but mainly about how they make decisions today, whether those decisions have changed due to the pandemic, and whether those changes are permanent. Also, for decision-making, goods were divided into essential products, high-tech products, transactions with the state and others. Αbout 500 consumers aged between 18 and 75 participated in the research. The data was processed with both descriptive statistics and econometric models. The results showed that the consumer behavior and decision-making process has changed. Now consumers widely use the internet for shopping, consumer behaviors and consumer patterns have changed. Social and economic factors play an important role. Income, gender and other factors were found to be statistically significant. In addition, it is worth noting that the percentage who made purchases during the pandemic through the internet for the first time was remarkable and related to age. Essentially, the arrival of the pandemic caused uncertainty for individuals, mainly financial, and this affected the decision-making process. In addition, shopping through the internet is now the first choice, especially among young people, and it seems that it is about to become established.

Keywords: consumer behavior, decision making, COVID-19, Greece, behavior change

Procedia PDF Downloads 34

Authors: Kemi Olalekan Oduntan

Abstract:

This paper was carried out in order to empirical, and descriptively analysis how interest rate and foreign exchange rate liberalization influence investment decision in Nigeria. The study spanned through the period of 1985 – 2014, secondary data were restricted to relevant variables such as investment (Proxy by Gross Fixed Capital Formation) saving rate, interest rate and foreign exchange rate. Theories and empirical literature from various scholars were reviews in the paper. Ordinary Least Square regression method was used for the analysis of data collection. The result of the regression was critically interpreted and discussed. It was discovered for empirical finding that tax investment decision in Nigeria is highly at sensitive rate. Hence, all the alternative hypotheses were accepted while the respective null hypotheses were rejected as a result of interest rate and foreign exchange has significant effect on investment in Nigeria. Therefore, impact of interest rate and foreign exchange rate on the state of investment in the economy cannot be over emphasized.

Keywords: interest rate, foreign exchange liberalization, investment decision, economic growth

Procedia PDF Downloads 356

Authors: I. Khutsishvili, G. Sirbiladze, B. Ghvaberidze

Abstract:

This work proposes a fuzzy methodology to support the investment decisions. While choosing among competitive investment projects, the methodology makes ranking of projects using the new aggregation OWA operator – AsPOWA, presented in the environment of possibility uncertainty. For numerical evaluation of the weighting vector associated with the AsPOWA operator the mathematical programming problem is constructed. On the basis of the AsPOWA operator the projects’ group ranking maximum criteria is constructed. The methodology also allows making the most profitable investments into several of the project using the method developed by the authors for discrete possibilistic bicriteria problems. The article provides an example of the investment decision-making that explains the work of the proposed methodology.

Keywords: expert evaluations, investment decision making, OWA operator, possibility uncertainty

Procedia PDF Downloads 547

Authors: Marina Diković

Abstract:

By giving personal opinions, suggestions and criticism through e-democracy, young people can reinforce the adoption of decisions which they have an impact on. The purpose of this research was to examine the opinion of university students about the possibility of their decision-making by using information and communication technology (ICT). The questionnaire examined young people's values and behaviour associated with e-democracy and the related decision-making. Students are most active online when it comes to finding information connected with their academic responsibilities, but less frequently take part in democratic processes in society, both at the national and local level. E-democracy as a tool can be learned in programmes of Human Rights Education and Citizenship Education. 

Keywords: active citizens, e-democracy, information and communication technology (ICT), university students

Procedia PDF Downloads 210

Authors: Pablo Oteiza, Ricardo Alvarez, Mehrdad Pirnia, Fuat Can

Abstract:

To effectively combat climate change, many countries around the world have committed to a decarbonisation of their electricity, along with promoting a large-scale integration of renewable energy sources (RES). While this trend represents a unique opportunity to effectively combat climate change, achieving a sound and cost-efficient energy transition towards low-carbon power systems poses significant challenges for the multi-year Transmission Network Expansion Planning (TNEP) problem. The objective of the multi-year TNEP is to determine the necessary network infrastructure to supply the projected demand in a cost-efficient way, considering the evolution of the new generation mix, including the integration of RES. The rapid integration of large-scale RES increases the variability and uncertainty in the power system operation, which in turn increases short-term flexibility requirements. To meet these requirements, flexible generating technologies such as energy storage systems must be considered within the TNEP as well, along with proper models for capturing the operational challenges of future power systems. As a consequence, TNEP formulations are becoming more complex and difficult to solve, especially for its application in realistic-sized power system models. To meet these challenges, there is an increasing need for developing efficient algorithms capable of solving the TNEP problem with reasonable computational time and resources. In this regard, a promising research area is the use of artificial intelligence (AI) techniques for solving large-scale mixed-integer optimization problems, such as the TNEP. In particular, the use of AI along with mathematical optimization strategies based on decomposition has shown great potential. In this context, this paper presents an efficient algorithm for solving the multi-year TNEP problem. The algorithm combines AI techniques with Column Generation, a traditional decomposition-based mathematical optimization method. One of the challenges of using Column Generation for solving the TNEP problem is that the subproblems are of mixed-integer nature, and therefore solving them requires significant amounts of time and resources. Hence, in this proposal we solve a linearly relaxed version of the subproblems, and trained a binary classifier that determines the value of the binary variables, based on the results obtained from the linearized version. A key feature of the proposal is that we integrate the binary classifier into the optimization algorithm in such a way that the optimality of the solution can be guaranteed. The results of a study case based on the HRP 38-bus test system shows that the binary classifier has an accuracy above 97% for estimating the value of the binary variables. Since the linearly relaxed version of the subproblems can be solved with significantly less time than the integer programming counterpart, the integration of the binary classifier into the Column Generation algorithm allowed us to reduce the computational time required for solving the problem by 50%. The final version of this paper will contain a detailed description of the proposed algorithm, the AI-based binary classifier technique and its integration into the CG algorithm. To demonstrate the capabilities of the proposal, we evaluate the algorithm in case studies with different scenarios, as well as in other power system models.

Keywords: integer optimization, machine learning, mathematical decomposition, transmission planning

Procedia PDF Downloads 74

Authors: Sihem Oujdi, Hafida Belbachir

Abstract:

Existing methods of data mining cannot be applied on spatial data because they require spatial specificity consideration, as spatial relationships. This paper focuses on the classification with decision trees, which are one of the data mining techniques. We propose an extension of the C4.5 algorithm for spatial data, based on two different approaches Join materialization and Querying on the fly the different tables. Similar works have been done on these two main approaches, the first - Join materialization - favors the processing time in spite of memory space, whereas the second - Querying on the fly different tables- promotes memory space despite of the processing time. The modified C4.5 algorithm requires three entries tables: a target table, a neighbor table, and a spatial index join that contains the possible spatial relationship among the objects in the target table and those in the neighbor table. Thus, the proposed algorithms are applied to a spatial data pattern in the accidentology domain. A comparative study of our approach with other works of classification by spatial decision trees will be detailed.

Keywords: C4.5 algorithm, decision trees, S-CART, spatial data mining

Procedia PDF Downloads 604

Authors: Jovana M. Ćirković, Aleksandar M. Radojković, Sanja Z. Perać, Jelena N. Jovanović, Zorica M. Branković, Slobodan D. Milanović, Ivan Lj. Milenković, Jovan N. Dobrosavljević, Nemanja V. Simović, Vanja M. Tadić, Ana R. Žugić, Goran O. Branković

Abstract:

The protection of forests is a national interest and of strategic importance in every country. The spongy moth (Lymantria dispar) is a damaging invasive pest that can weaken and destroy trees by defoliating them. Chemical pesticides commonly used to protect forests against spongy moths not only have a negative impact on terrestrial and aquatic organisms/ecosystems but also often fail to provide significant protection. Therefore, many eco-friendly alternatives have been considered. Within this research, a new biopesticide was developed based on the method of nanoencapsulation of plant extracts in a biopolymer matrix, which provides a slow release of the active components during a substantial time period. The antifeedant activity of plant extracts of common (Fraxinus excelsior L.), manna (F. ornus L.) ash tree, and the tree of heaven Ailanthus altissima (Mill.) was tested on the spongy moth (Lymantria dispar L, 1758) larvae. To test the antifeedant activity of these compounds, the choice and non-choice tests in laboratory conditions for different plant extract concentrations (0.01, 0.1, 0.5, and 1 % v/v) were carried out. In both cases, the best results showed formulations based on the tree of heaven and common ash for the concentration of 1%, with deterioration indices of 163 and 132, respectively. The main benefit of these formulations is their versatility, effectiveness, prolonged effect, and because they are completely environmentally acceptable. Therefore, they can be considered for suppression of the spongy moth in forest ecosystems.

Keywords: Ailanthus altissima (Mill.), Fraxinus excelsior L., encapsulation, Lymantria dispar

Procedia PDF Downloads 58

Authors: Loai AbdAllah, Mahmoud Kaiyal

Abstract:

Missing values in real-world datasets are a common problem. Many algorithms were developed to deal with this problem, most of them replace the missing values with a fixed value that was computed based on the observed values. In our work, we used a distance function based on Bhattacharyya distance to measure the distance between objects with missing values. Bhattacharyya distance, which measures the similarity of two probability distributions. The proposed distance distinguishes between known and unknown values. Where the distance between two known values is the Mahalanobis distance. When, on the other hand, one of them is missing the distance is computed based on the distribution of the known values, for the coordinate that contains the missing value. This method was integrated with Wikaya, a digital health company developing a platform that helps to improve prevention of chronic diseases such as diabetes and cancer. In order for Wikaya’s recommendation system to work distance between users need to be measured. Since there are missing values in the collected data, there is a need to develop a distance function distances between incomplete users profiles. To evaluate the accuracy of the proposed distance function in reflecting the actual similarity between different objects, when some of them contain missing values, we integrated it within the framework of k nearest neighbors (kNN) classifier, since its computation is based only on the similarity between objects. To validate this, we ran the algorithm over diabetes and breast cancer datasets, standard benchmark datasets from the UCI repository. Our experiments show that kNN classifier using our proposed distance function outperforms the kNN using other existing methods.

Keywords: missing values, incomplete data, distance, incomplete diabetes data

Procedia PDF Downloads 208

Authors: Malte Brettel, David Bendig, Michael Keller, Marius Rosenberg

Abstract:

What are the core competences necessary in order to sustain manufacturing in high-wage countries? Aspiring countries all over the world gain market share in manufacturing and rapidly close the productivity and quality gap that has until now protected some parts of the industry in Europe and the United States from dislocation. However, causal production planning and manufacturing, the basis for productivity and quality, is challenged by the ever-greater need for flexibility and customized products in an uncertain business environment. This article uses a case-study-based approach to assess how production managers in high-wage countries can apply decision-making principals from successful entrepreneurs. 'Effectuation' instead of causal decision making can be applied to handle uncertainty of mass customization, to seek the right partners in alliances and to advance towards virtual production. The findings help managers to use their resources more efficiently and contribute to bridge the gap between production research and entrepreneurship.

Keywords: case studies, decision-making behavior, effectuation, production planning

Procedia PDF Downloads 335

Authors: Payman Tajalli, Steven Segal

Abstract:

Applied ethics is an area of ethics which is looked upon most favorably as the most appropriate and useful for educational purposes; after all if ethics finds no application would any investment of time, effort and finance by the educational institutions be warranted? The current approaches to ethics in business and management often entail appealing to various types of moral theories and to this end almost every major philosophical approach has been enlisted. In this paper, we look at ethics through the philosophy of Emmanuel Levinas to argue that since ethics is ‘first philosophy’ it can neither be rule-based nor rule-governed, not something that can be worked out first and then applied to a given situation, hence the overwhelming emphasis on ‘applied ethics’ as a field of study in business and management education is unjustified. True ethics is not applied ethics. This assertion does not mean that teaching ethical theories and philosophies need to be abandoned rather it is the acceptance of the fact that an increase in cognitive awareness of such theories and ethical models and frameworks, or the mastering of techniques and procedures for ethical decision making, will not affect the desired ethical transformation in our students. Levinas himself argued for an ethics without a foundation, not one that required us to go ‘beyond good and evil’ as Nietzsche contended, rather an ethics which necessitates going ‘before good and evil'. Such an ethics does not provide us with a set of methods or techniques or a decision tree that enable us determine the rightness of an action and what we ought to do, rather it is about a way of being, an ethical posture or approach one takes in the inter-subjective relationship with the other that holds the promise of ethical conduct. Ethics in this Levinasian sense then is one of infinite and unconditional responsibility for the other person in relationship, an ethics which is not subject to negotiation, calculation or reciprocity, and as such it could neither be applied nor taught through conventional pedagogy with its focus on knowledge transfer from the teacher to student, and to this end Levinas offers a non-maieutic, non-conventional approach to pedagogy. The paper concludes that from a Levinasian perspective on ethics and education, we may need to guide our students to move away from the clear and objective professionalism of the management and applied ethics towards the murky individual spiritualism. For Levinas, this is ‘the Copernican revolution’ in ethics.

Keywords: business ethics, ethics education, Levinas, maieutic teaching, ethics without foundation

Procedia PDF Downloads 313

Authors: Snezhana G. Gocheva-Ilieva, Maya P. Stoimenova

Abstract:

Ambient air pollution with fine particulate matter (PM10) is a systematic permanent problem in many countries around the world. The accumulation of a large number of measurements of both the PM10 concentrations and the accompanying atmospheric factors allow for their statistical modeling to detect dependencies and forecast future pollution. This study applies the classification and regression trees (CART) method for building and analyzing PM10 models. In the empirical study, average daily air data for the city of Pleven, Bulgaria for a period of 5 years are used. Predictors in the models are seven meteorological variables, time variables, as well as lagged PM10 variables and some lagged meteorological variables, delayed by 1 or 2 days with respect to the initial time series, respectively. The degree of influence of the predictors in the models is determined. The selected best CART models are used to forecast future PM10 concentrations for two days ahead after the last date in the modeling procedure and show very accurate results.

Keywords: cross-validation, decision tree, lagged variables, short-term forecasting

Procedia PDF Downloads 185

Authors: Umar D. M., Aminu A. M., Izaddeen K. Y.

Abstract:

Deployments of mini macrocell base stations also referred to as femtocells, improve the quality of service of indoor and outdoor users. Nevertheless, mobility management remains a key issue with regards to their deployment. This paper is leaned towards this issue, with an in-depth focus on the most important aspect of mobility management -handover. In handover management, making a handover decision in the LTE two-tier macrocell femtocell network is a crucial research area. Decision algorithms in this research are classified and comparatively analyzed according to received signal strength, user equipment speed, cost function, and interference. However, it was observed that most of the discussed decision algorithms fail to consider cell selection with hybrid access policy in a single macrocell multiple femtocell scenario, another observation was a majority of these algorithms lack the incorporation of user equipment residence parameter. Not including this parameter boosts the number of unnecessary handover occurrence. To deal with these issues, a sophisticated handover decision algorithm is proposed. The proposed algorithm considers the user’s velocity, received signal strength, residence time, as well as the femtocell base station’s access policy. Simulation results have shown that the proposed algorithm reduces the number of unnecessary handovers when compared to conventional received signal strength-based handover decision algorithm.

Keywords: user-equipment, radio signal service, long term evolution, mobility management, handoff

Procedia PDF Downloads 111

Authors: Parya Tabei, Maryam Habibifar

Abstract:

Decision-making is an important cognitive function that can be defined as the process of choosing an option among available options to achieve a specific goal. Consumer ‘need’ is the main reason for purchasing decisions. Human decision-making while buying products online is subject to various factors, one of which is the quality and effect of advertising photos. Advertising photo editing can have a significant impact on people's virtual purchase decisions. This technique helps improve the quality and overall appearance of photos by adjusting various aspects such as brightness, contrast, colors, cropping, resizing, and adding filters. This study, by examining the effect of editing advertising photos on the virtual purchase decision using EEG data, tries to investigate the effect of edited images on the decision-making of customers. A group of 30 participants were asked to react to 24 edited and unedited images while their EEG was recorded. Analysis of the EEG data revealed increased alpha wave activity in the occipital regions (O1, O2) for both edited and unedited images, which is related to visual processing and attention. Additionally, there was an increase in beta wave activity in the frontal regions (FP1, FP2, F4, F8) when participants viewed edited images, suggesting involvement in cognitive processes such as decision-making and evaluating advertising content. Gamma wave activity also increased in various regions, especially the frontal and parietal regions, which are associated with higher cognitive functions, such as attention, memory, and perception, when viewing the edited images. While the visual processing reflected by alpha waves remained consistent across different visual conditions, editing advertising photos appeared to boost neural activity in frontal and parietal regions associated with decision-making processes. These Findings suggest that photo editing could potentially influence consumer perceptions during virtual shopping experiences by modulating brain activity related to product assessment and purchase decisions.

Keywords: virtual purchase decision, advertising photo, EEG parameters, decision Making

Procedia PDF Downloads 32

Authors: Dhanuja S. Patil, Sanjay B. Waykar

Abstract:

Event detection is a standout amongst the most key parts for distinctive sorts of area applications of video data framework. Recently, it has picked up an extensive interest of experts and in scholastics from different zones. While detecting video event has been the subject of broad study efforts recently, impressively less existing methodology has considered multi-model data and issues related efficiency. Start of soccer matches different doubtful circumstances rise that can't be effectively judged by the referee committee. A framework that checks objectively image arrangements would prevent not right interpretations because of some errors, or high velocity of the events. Bayesian networks give a structure for dealing with this vulnerability using an essential graphical structure likewise the probability analytics. We propose an efficient structure for analysing and summarization of soccer videos utilizing object-based features. The proposed work utilizes the t-cherry junction tree, an exceptionally recent advancement in probabilistic graphical models, to create a compact representation and great approximation intractable model for client’s relationships in an interpersonal organization. There are various advantages in this approach firstly; the t-cherry gives best approximation by means of junction trees class. Secondly, to construct a t-cherry junction tree can be to a great extent parallelized; and at last inference can be performed utilizing distributed computation. Examination results demonstrates the effectiveness, adequacy, and the strength of the proposed work which is shown over a far reaching information set, comprising more soccer feature, caught at better places.

Keywords: summarization, detection, Bayesian network, t-cherry tree

Procedia PDF Downloads 306

Authors: Sultan Mahmud, Qamar Zaman, Travis Esau, Young Chang

Abstract:

Strawberry powdery mildew (PM) is a serious disease that has a significant impact on strawberry production. Field scouting is still a major way to find PM disease, which is not only labor intensive but also almost impossible to monitor disease severity. To reduce the loss caused by PM disease and achieve faster automatic detection of the disease, this paper proposes an approach for detection of the disease, based on image texture and classified with support vector machines (SVMs) and k-nearest neighbors (kNNs). The methodology of the proposed study is based on image processing which is composed of five main steps including image acquisition, pre-processing, segmentation, features extraction and classification. Two strawberry fields were used in this study. Images of healthy leaves and leaves infected with PM (Sphaerotheca macularis) disease under artificial cloud lighting condition. Colour thresholding was utilized to segment all images before textural analysis. Colour co-occurrence matrix (CCM) was introduced for extraction of textural features. Forty textural features, related to a physiological parameter of leaves were extracted from CCM of National television system committee (NTSC) luminance, hue, saturation and intensity (HSI) images. The normalized feature data were utilized for training and validation, respectively, using developed classifiers. The classifiers have experimented with internal, external and cross-validations. The best classifier was selected based on their performance and accuracy. Experimental results suggested that SVMs classifier showed 98.33%, 85.33%, 87.33%, 93.33% and 95.0% of accuracy on internal, external-I, external-II, 4-fold cross and 5-fold cross-validation, respectively. Whereas, kNNs results represented 90.0%, 72.00%, 74.66%, 89.33% and 90.3% of classification accuracy, respectively. The outcome of this study demonstrated that SVMs classified PM disease with a highest overall accuracy of 91.86% and 1.1211 seconds of processing time. Therefore, overall results concluded that the proposed study can significantly support an accurate and automatic identification and recognition of strawberry PM disease with SVMs classifier.

Keywords: powdery mildew, image processing, textural analysis, color co-occurrence matrix, support vector machines, k-nearest neighbors

Procedia PDF Downloads 111

Authors: I. Ahmad, A. Hannan, S. Ahmad, M. Asif, M. F. Nawaz, M. A. Tanvir, M. F. Azhar

Abstract:

During this research, a comprehensive survey of tree growing areas of Faisalabad district of Pakistan was conducted to observe the symptoms, spectrum, occurrence and severity of A. nilotica and E. camaldulensis decline. Objective of current research was to investigate specific fungal pathogens involved in decline of A. nilotica and E. camaldulensis. For this purpose, infected roots, bark, neck portion, stem, branches, leaves and infected soils were collected to identify associated fungi. Potato dextrose agar (PDA) and Czepak dox agar media were used for isolations. Identification of isolated fungi was done microscopically and different fungi were identified. During survey of urban locations of Faisalabad, disease incidence on Kikar and Eucalyptus was recorded as 3.9-7.9% and 2.6-7.1% respectively. Survey of Agroforest zones of Faisalabad revealed decline incidence on kikar 7.5% from Sargodha road while on Satiana and Jhang road it was not planted. In eucalyptus trees, 4%, 8% and 0% disease incidence was observed on Jhang road, Sargodha road and Satiana road respectively. The maximum fungus isolated from the kikar tree was Drechslera australiensis (5.00%) from the stem part. Aspergillus flavus also gave the maximum value of (3.05%) from the bark. Alternaria alternata gave the maximum value of (2.05%) from leaves. Rhizopus and Mucor spp. were recorded minimum as compared to the Drechslera, Alternaria and Aspergillus. The maximum fungus isolated from the Eucalyptus tree was Armillaria luteobubalina (5.00%) from the stem part. The other fungi isolated were Macrophamina phaseolina and A. niger.

Keywords: decline, frequency of mycoflora, A. nilotica and E. camaldulensis, Drechslera australiensis, Armillaria luteobubalina

Procedia PDF Downloads 356

Authors: Mehdi Asgarkhani

Abstract:

Today, investment on Information Technology (IT) solutions in most organizations is the largest component of capital expenditure. As capital investment on IT continues to grow, IT managers and strategists are expected to develop and put in practice effective decision making models (frameworks) that improve decision-making processes for the use of IT in organizations and optimize the investment on IT solutions. To be exact, there is an expectation that organizations not only maximize the benefits of adopting IT solutions but also avoid the many pitfalls that are associated with rapid introduction of technological change. Different organizations depending on size, complexity of solutions required and processes used for financial management and budgeting may use different techniques for managing strategic investment on IT solutions. Decision making processes for strategic use of IT within organizations are often referred to as IT Governance (or Corporate IT Governance). This paper examines IT governance - as a tool for best practice in decision making about IT strategies. Discussions in this paper represent phase I of a project which was initiated to investigate trends in strategic decision making on IT strategies. Phase I is concerned mainly with review of literature and a number of case studies, establishing that the practice of IT governance, depending on the complexity of IT solutions, organization's size and organization's stage of maturity, varies significantly – from informal approaches to sophisticated formal frameworks.

Keywords: IT governance, corporate governance, IT governance frameworks, IT governance components, aligning IT with business strategies

Procedia PDF Downloads 394

Authors: Vesile Evrim, Aliyu Awwal

Abstract:

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

Procedia PDF Downloads 373

Authors: Seyed Hossein Iranmanesh, Hassan Nouri, Seyed Reza Iranmanesh

Abstract:

In the dynamic and complex landscape of today’s business, organizations often face challenges in impactful decision-making across multi-project settings. To efficiently allocate resources, coordinate tasks, and optimize project outcomes, establishing robust decision-making processes is essential. Furthermore, the increasing importance of information systems and their integration within organizational workflows introduces an additional layer of complexity. This research proposes the use of blockchain technology as a suitable solution to enhance decision-making in multi-project environments, particularly within the realm of information systems. The conceptual framework in this study comprises four independent variables and one dependent variable. The identified independent variables for the targeted research include: Blockchain Layer in Integrated Systems, Quality of Generated Information ,User Satisfaction with Integrated Systems and Utilization of Integrated Systems. The project’s performance, considered as the dependent variable and moderated by organizational policies and procedures, reflects the impact of blockchain technology adoption on organizational effectiveness1. The results highlight the significant influence of blockchain implementation on organizational performance.

Keywords: multi-project environments, decision support systems, information systems, blockchain technology, decentralized systems.

Procedia PDF Downloads 43

Authors: Miguel Mellado, Cecilia Zapata

Abstract:

Goats can be exploited in harsh environments due to their capacity to adjust to limited quantity and quality forage sources. In these environments, leguminous trees can be used as supplementary feeds as foliage and fruits of these trees can contribute to maintain or improve production efficiency in ruminants. The objective of this study was to determine the nutritional value of three leguminous trees heavily selected by goats in a xerophyllous shrubland. Chemical composition and in vitro dry matter disappearance (IVDMD) of leaves and pods from leucaena (Leucaena leucocephala), mesquite (Prosopis laevigata) and huisache (Acacia farnesiana) is presented. Crude protein (CP) ranged from 17.3% for leaves of huisache to 21.9% for leucaena. The neutral detergent fiber (NDF) content ranged from 39.0 to 40.3 with no difference among fodder threes. Across tree species, mean IVDMD was 61.6% for pods and 52.2% for leaves. IVDMD for leaves was highest (P < 0.01) for leucaena (54.9%) and lowest for huisache (47.3%). Condensed tannins in an acetonic extract were highest for leaves of huisache (45.3 mg CE/g DM) and lowest for mesquite (25.9 mg CE/g DM). Pods and leaves of huisache presented the highest number of secondary metabolites, mainly related to hydrobenzoic acid and flavonols; leucaena and mesquite presented mainly flavonols and anthocyanins. It was concluded that leaves and pods of leucaena, mesquite and huisache constitute valuable forages for ruminant livestock due to its low fiber, high CP levels, moderate in vitro fermentation characteristics and high mineral content. Keywords: Fodder tree; ruminants; secondary metabolites; minerals; tannins

Keywords: fodder tree, ruminants, secondary metabolites, minerals, tannins

Procedia PDF Downloads 132

Authors: Azene Zenebe

Abstract:

Deep learning is a subset of machine learning which incorporates techniques for the construction of artificial neural networks and found to be useful for modeling complex problems with large dataset. Deep learning requires a very high power computational and longer time for training. By aggregating computing power, high performance computer (HPC) has emerged as an approach to resolving advanced problems and performing data-driven research activities. Cyber threat intelligence (CIT) is actionable information or insight an organization or individual uses to understand the threats that have, will, or are currently targeting the organization. Results of review of literature will be presented along with results of experimental study that compares the performance of tree-based and function-base machine learning including deep learning algorithms using secondary dataset collected from darknet.

Keywords: deep-learning, cyber security, cyber threat modeling, tree-based machine learning, function-based machine learning, data science

Procedia PDF Downloads 140

Authors: Malay Niraj, Praveen Kumar

Abstract:

The present study is a new approach for improving equipment life and Overall Equipment Efficiency (O.E.E.) through suitable maintenance practice with the help of value engineering. Value engineering is a one of the most powerful decision-making techniques which depend on many factors. The improvements are the result of recommendations made by multidisciplinary teams representing all parties involved. VE is a rigorous, systematic effort to improve the OEE and optimize the life cycle cost of a facility. The study describes problems in maintenance arising due to the absence of having clear criteria and strong decision constrain how to maintain failing equipment. Using factor comparisons, the study has been made between different maintenance practices and finally best maintenance practice based on value engineering technique has been selected.

Keywords: maintenance strategy, overall equipment efficiency, value engineering, decision-making

Procedia PDF Downloads 396

Authors: Nastaran Hajiheydari, Mohammad Soltani Delgosha

Abstract:

Vendor (supplier) selection is a group decision-making (GDM) process, in which, based on some predetermined criteria, the experts’ preferences are provided in order to rank and choose the most desirable suppliers. In the real business environment, our attitudes or our choices would be made in an uncertain and indecisive situation could not be expressed in a crisp framework. Intuitionistic fuzzy sets (IFSs) could handle such situations in the best way. VIKOR method was developed to solve multi-criteria decision-making (MCDM) problems. This method, which is used to determine the compromised feasible solution with respect to the conflicting criteria, introduces a multi-criteria ranking index based on the particular measure of 'closeness' to the 'ideal solution'. Until now, there has been a little investigation of VIKOR with IFS, therefore we extended the intuitionistic fuzzy (IF) VIKOR to solve vendor selection problem under IF GDM environment. The present study intends to develop an IF VIKOR method in a GDM situation. Therefore, a model is presented to calculate the criterion weights based on entropy measure. Then, the interval-valued intuitionistic fuzzy weighted geometric (IFWG) operator utilized to obtain the total decision matrix. In the next stage, an approach based on the positive idle intuitionistic fuzzy number (PIIFN) and negative idle intuitionistic fuzzy number (NIIFN) was developed. Finally, the application of the proposed method to solve a vendor selection problem illustrated.

Keywords: group decision making, intuitionistic fuzzy set, intuitionistic fuzzy entropy measure, vendor selection, VIKOR

Procedia PDF Downloads 142