Search results for: association rule
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3012

Search results for: association rule

2922 The Power of Transparency Norms in the Wto Legal Framework: Beyond the Trade Context

Authors: Tran Van Long

Abstract:

Beyond trade facilitation, transparency in the WTO legal context is, implicitly and explicitly, aimed at addressing problems in domestic administrative law. Through the lens of global governance, this paper attempts to shed more light on the power of transparency norms enshrined in multilateral trading agreements under the aegis of the WTO. In this global ruled-base system, transparency has become sufficiently powerful to be a multifunctional instrument for promoting rule of law, good governance, and democracy.

Keywords: WTO, transparency, good governance, rule of law, global administrative law.

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2921 Decision Tree Based Scheduling for Flexible Job Shops with Multiple Process Plans

Authors: H.-H. Doh, J.-M. Yu, Y.-J. Kwon, J.-H. Shin, H.-W. Kim, S.-H. Nam, D.-H. Lee

Abstract:

This paper suggests a decision tree based approach for flexible job shop scheduling with multiple process plans, i. e. each job can be processed through alternative operations, each of which can be processed on alternative machines. The main decision variables are: (a) selecting operation/machine pair; and (b) sequencing the jobs assigned to each machine. As an extension of the priority scheduling approach that selects the best priority rule combination after many simulation runs, this study suggests a decision tree based approach in which a decision tree is used to select a priority rule combination adequate for a specific system state and hence the burdens required for developing simulation models and carrying out simulation runs can be eliminated. The decision tree based scheduling approach consists of construction and scheduling modules. In the construction module, a decision tree is constructed using a four-stage algorithm, and in the scheduling module, a priority rule combination is selected using the decision tree. To show the performance of the decision tree based approach suggested in this study, a case study was done on a flexible job shop with reconfigurable manufacturing cells and a conventional job shop, and the results are reported by comparing it with individual priority rule combinations for the objectives of minimizing total flow time and total tardiness.

Keywords: flexible job shop scheduling, decision tree, priority rules, case study

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2920 Association of Non Synonymous SNP in DC-SIGN Receptor Gene with Tuberculosis (Tb)

Authors: Saima Suleman, Kalsoom Sughra, Naeem Mahmood Ashraf

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Mycobacterium tuberculosis is a communicable chronic illness. This disease is being highly focused by researchers as it is present approximately in one third of world population either in active or latent form. The genetic makeup of a person plays an important part in producing immunity against disease. And one important factor association is single nucleotide polymorphism of relevant gene. In this study, we have studied association between single nucleotide polymorphism of CD-209 gene (encode DC-SIGN receptor) and patients of tuberculosis. Dry lab (in silico) and wet lab (RFLP) analysis have been carried out. GWAS catalogue and GEO database have been searched to find out previous association data. No association study has been found related to CD-209 nsSNPs but role of CD-209 in pulmonary tuberculosis have been addressed in GEO database.Therefore, CD-209 has been selected for this study. Different databases like ENSEMBLE and 1000 Genome Project has been used to retrieve SNP data in form of VCF file which is further submitted to different software to sort SNPs into benign and deleterious. Selected SNPs are further annotated by using 3-D modeling techniques using I-TASSER online software. Furthermore, selected nsSNPs were checked in Gujrat and Faisalabad population through RFLP analysis. In this study population two SNPs are found to be associated with tuberculosis while one nsSNP is not found to be associated with the disease.

Keywords: association, CD209, DC-SIGN, tuberculosis

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2919 Association of Xeroderma pigmentosum Group D Gene Polymorphism with Colorectal Cancer Risk in Kashmiri Population

Authors: Syed Sameer Aga, Saniya Nissar

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The Xeroderma pigmentosum group D gene (XPD) plays a key role in nucleotide excision repair (NER) pathway of the damaged DNA. Genetic polymorphisms in the coding region of the XPD gene may alter DNA repair capacity of the protein and hence can modulate the risk of colorectal cancer (CRC) risk. The aim of the study was to determine the genetic association of XPD Lys751Gln polymorphism with the risk of colorectal cancer (CRC) development. 120 CRC patients and 160 normal controls were assessed for genotype frequencies of XPD Lys751Gln polymorphism using PCR-RFLP technique. We observed a significant association (p < 0.05) between the XPD Lys751Gln polymorphism and the risk of developing CRC (p < 0.05). Additionally, Gln/Gln genotype of the XPD gene doubled the risk for the development of CRC [p < 0.05; OR=2.25 95% CI (1.07-4.7)]. Our results suggest that there is a significant association between the XPD Lys751Gln polymorphism and the risk of CRC.

Keywords: colorectal cancer, polymorphism, RFLP, DNA Repair, NER, XPD

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2918 Exploring Non-Governmental Organizations’ Performance Management: Bahrain Athletics Association as a Case Study

Authors: Nooralhuda Aljlas

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In the ever-growing field of non-governmental organizations, the enhancement of performance management and measurement systems has been increasingly acknowledged by political, economic, social, legal, technological and environmental factors. Within Bahrain Athletics Association, such enhancement results from the key factors leading performance management including collaboration, feedback, human resource management, leadership and participative management. The exploratory, qualitative research conducted reviewed performance management theory. As reviewed, the key factors leading performance management were identified. Drawing on a non-governmental organization case study, the key factors leading Bahrain Athletics Association’s performance management were explored. By exploring the key factors leading Bahrain Athletics Association’s performance management, the research study proposed a theoretical framework of the key factors leading performance management in non-governmental organizations in general. The research study recommended further investigation of the role of the two key factors of command and control and leadership, combining military and civilian approaches to enhancing non-governmental organizations’ performance management.

Keywords: Bahrain athletics association, exploratory, key factor, performance management

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2917 Power Energy Management For A Grid-Connected PV System Using Rule-Base Fuzzy Logic

Authors: Nousheen Hashmi, Shoab Ahmad Khan

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Active collaboration among the green energy sources and the load demand leads to serious issues related to power quality and stability. The growing number of green energy resources and Distributed-Generators need newer strategies to be incorporated for their operations to keep the power energy stability among green energy resources and micro-grid/Utility Grid. This paper presents a novel technique for energy power management in Grid-Connected Photovoltaic with energy storage system under set of constraints including weather conditions, Load Shedding Hours, Peak pricing Hours by using rule-based fuzzy smart grid controller to schedule power coming from multiple Power sources (photovoltaic, grid, battery) under the above set of constraints. The technique fuzzifies all the inputs and establishes fuzzify rule set from fuzzy outputs before defuzzification. Simulations are run for 24 hours period and rule base power scheduler is developed. The proposed fuzzy controller control strategy is able to sense the continuous fluctuations in Photovoltaic power generation, Load Demands, Grid (load Shedding patterns) and Battery State of Charge in order to make correct and quick decisions.The suggested Fuzzy Rule-based scheduler can operate well with vague inputs thus doesn’t not require any exact numerical model and can handle nonlinearity. This technique provides a framework for the extension to handle multiple special cases for optimized working of the system.

Keywords: photovoltaic, power, fuzzy logic, distributed generators, state of charge, load shedding, membership functions

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2916 The Increasing Importance of CFC Rules: An OECD+ Country Overview

Authors: Axel Prettl

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This paper provides an overview of the different CFC rule settings in the OECD and 22 additional countries for the years 2004 to 2014 and compares them. In order to do so, it gives a summary of law amendments for every country, provides a comparison and afterwards all CFC rules are rated in their ”power of anti-avoidance” over time. For that rating of CFC rules, the largest common denominator of rule characteristics is used to keep it as abstract as necessary and possible. The paper points out that the CFC rules in the considered countries are very different in their specifications and they reach from very strict to very low binding. All in all these rules get more and more common and important; more countries implement a CFC legislation and the strictness of most of them rises over time.

Keywords: CFC rules, international taxation, corporate taxation, country comparison

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2915 Anatta: A Buddhist Remedy to the Problem of Associating Eternal Self to Non-Eternal Body

Authors: Maitreyee Datta

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In Anātmalaksana Sutra, Buddha talks about the importance of anattā (no-self). This notion of no-self is a critical response towards the Brahmanical tradition of classical India in which self has been taken to be eternal. Though self is taken to be eternal, ‘I’ refer to Person who is the self as determined by non-eternal body. Buddha raises questions regarding the possibility of the association between eternal self and non-eternal body. According to him, such an association is not possible. Thus, instead of an eternal self and its association with the non-eternal body, he speaks about association among five different non-eternal parts (skandhas). He holds that ‘I’ refers to Person, but this Person is not eternal self as determined by the non-eternal body. It is the combination of five different skandhas each of which is non-eternal. So according to Buddha, there is no eternal self which in association with non-eternal body is referred to as ‘I,’ but ‘I’ is a convenient designator which designates the combination of five non-eternal skandhas. If ‘I’ is taken to refer the combination of five non-eternal skandhas, then the problematic of the association between eternal self (attā) and non-eternal body will not be there. The realization that ‘I’ does not refer to any eternal self as determined by non-eternal body, but instead refer to the combination of five non-eternal skandhas leads to the cessation of suffering (duhkkha). The root of suffering lies in craving for something or the other. Thus, as soon as one realizes that the person is not constituted of any eternal self but is constituted of non-eternal skandhas, his desire to acquire and possess will be stopped. Thus, in the whole conceptual framework of Buddhist philosophy, anattā occupies a pivotal role the realization of which is admitted to be the cause of the cessation of suffering. In the present paper, an effort will be made to analyse this notion of anattā to show how the realization of the truth that person is a combination of five skandhas each of which is non-eternal helps an individual to get rid of the bondage. If eternal self is to be admitted, then there always remains the problem of connecting the eternal self with the non-eternal body, because this connection only gives rise to the notion of person in such framework.

Keywords: anatta, atta, duhkkha, skandha

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2914 A Uniformly Convergent Numerical Scheme for a Singularly Perturbed Volterra Integrodifferential Equation

Authors: Nana Adjoah Mbroh, Suares Clovis Oukouomi Noutchie

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Singularly perturbed problems are parameter dependent problems, and they play major roles in the modelling of real-life situational problems in applied sciences. Thus, designing efficient numerical schemes to solve these problems is of much interest since the exact solutions of such problems may not even exist. Generally, singularly perturbed problems are identified by a small parameter multiplying at least the highest derivative in the equation. The presence of this parameter causes the solution of these problems to be characterized by rapid oscillations. This unique feature renders classical numerical schemes inefficient since they are unable to capture the behaviour of the exact solution in the part of the domain where the rapid oscillations are present. In this paper, a numerical scheme is proposed to solve a singularly perturbed Volterra Integro-differential equation. The scheme is based on the midpoint rule and employs the non-standard finite difference scheme to solve the differential part whilst the composite trapezoidal rule is used for the integral part. A fully fledged error estimate is performed, and Richardson extrapolation is applied to accelerate the convergence of the scheme. Numerical simulations are conducted to confirm the theoretical findings before and after extrapolation.

Keywords: midpoint rule, non-standard finite difference schemes, Richardson extrapolation, singularly perturbed problems, trapezoidal rule, uniform convergence

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2913 Association of Major Histocompatibility Complex with Cell Mediated Immunity

Authors: Atefeh Esmailnejad, Gholamreza Nikbakht Brujeni

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Major histocompatibility complex (MHC) is one of the best characterized genetic regions associated with immune responses and controlling disease resistance in chicken. Association of the MHC with a wide range of immune responses makes it a valuable predictive factor for the disease pathogenesis and outcome. In this study, the association of MHC with cell-mediated immune responses was analyzed in commercial broiler chicken. The tandem repeat LEI0258 was applied to investigate the MHC polymorphism. Cell-mediated immune response was evaluated by peripheral blood lymphocyte proliferation assay using MTT method. Association study revealed a significant influence of MHC alleles on cellular immune responses in this population. Alleles 385 and 448 bp were associated with elevated cell-mediated immunity. Haplotypes associated with improved immune responses could be considered as candidate markers for disease resistance and applied to breeding strategies.

Keywords: MHC, cell-mediated immunity, broiler, chicken

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2912 Nigerian Central Bank Governor’s Autonomy: Disregard of Procedure for Removal Vis-A-Vis the Rule of Law

Authors: Adeola Ayodele Oluwabiyi

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The study undertook an in depth examination of the relevant sections of the Nigerian Constitution and the Central Bank of Nigeria (CBN) Act as it relates to the appointment and removal of the CBN Governor; It analysed the Constitutional issues that arose from the removal of the immediate past Governor of the CBN; and made recommendations as appropriate. The study relied on primary and secondary sources of information. The primary sources included the Constitution of the Federal Republic of Nigeria, Statutes, Conventions and Judicial decisions, while the secondary sources included Books, Journals Articles, Newspapers and Internet Materials. The study revealed that the removal of the CBN Governor was not in accordance with the Nigerian Constitution and the CBN Act that Guarantee such. It also revealed some of the arguments in support of the removal. The study concluded that the removal of the immediate past Governor of CBN was an outright disregard for the rule of law. The study concluded that if Government treat the laws in question with levity and contempt the confidence of the citizens in such government will be seriously eroded and the effect of that will be the beginning of anarchy in replacement of the rule of law. It could also have serious economic implications on the economy of any nation.

Keywords: central bank, governor, laws, Nigeria

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2911 Higher Freshwater Fish and Sea Fish Intake Is Inversely Associated with Liver Cancer in Patients with Hepatitis B

Authors: Maomao Cao

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Background and aims While the association between higher consumption of fish and lower liver cancer risk has been confirmed, however, the association between specific fish intake and liver cancer risk remains unknown. We aimed to identify the association between specific fish consumption and the risk of liver cancer. Methods: Based on a community-based seropositive hepatitis B cohort involving 18404 individuals, face to face interview was conducted by a standardized questionnaire to acquire baseline information. Three common fish types in this study were analyzed, including freshwater fish, sea fish, and small fish (shrimp, crab, conch, and shell). All participants received liver cancer screening, and possible cases were identified by CT or MRI. Multivariable logistic models were applied to estimate the odds ratio (OR) and 95% confidence intervals (CI). Multivariate multiple imputations were utilized to impute observations with missing values. Results: 179 liver cancer cases were identified. Consumption of freshwater fish and sea fish at least once a week had a strong inverse association with liver cancer risk compared with the lowest intake level, with an adjusted OR of 0.53 (95% CI, 0.38-0.75) and 0.38 (95% CI, 0.19-0.73), respectively. This inverse association was also observed after the imputation. There was no statistically significant association between intake of small fish and liver cancer risk (OR=0.58, 95%, CI 0.32-1.08). Conclusions: Our findings suggest that consumption of freshwater fish and sea fish at least once a week could reduce liver cancer risk.

Keywords: cross-sectional study, fish intake, liver cancer, risk factor

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2910 Analysis and Design Modeling for Next Generation Network Intrusion Detection and Prevention System

Authors: Nareshkumar Harale, B. B. Meshram

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The continued exponential growth of successful cyber intrusions against today’s businesses has made it abundantly clear that traditional perimeter security measures are no longer adequate and effective. We evolved the network trust architecture from trust-untrust to Zero-Trust, With Zero Trust, essential security capabilities are deployed in a way that provides policy enforcement and protection for all users, devices, applications, data resources, and the communications traffic between them, regardless of their location. Information exchange over the Internet, in spite of inclusion of advanced security controls, is always under innovative, inventive and prone to cyberattacks. TCP/IP protocol stack, the adapted standard for communication over network, suffers from inherent design vulnerabilities such as communication and session management protocols, routing protocols and security protocols are the major cause of major attacks. With the explosion of cyber security threats, such as viruses, worms, rootkits, malwares, Denial of Service attacks, accomplishing efficient and effective intrusion detection and prevention is become crucial and challenging too. In this paper, we propose a design and analysis model for next generation network intrusion detection and protection system as part of layered security strategy. The proposed system design provides intrusion detection for wide range of attacks with layered architecture and framework. The proposed network intrusion classification framework deals with cyberattacks on standard TCP/IP protocol, routing protocols and security protocols. It thereby forms the basis for detection of attack classes and applies signature based matching for known cyberattacks and data mining based machine learning approaches for unknown cyberattacks. Our proposed implemented software can effectively detect attacks even when malicious connections are hidden within normal events. The unsupervised learning algorithm applied to network audit data trails results in unknown intrusion detection. Association rule mining algorithms generate new rules from collected audit trail data resulting in increased intrusion prevention though integrated firewall systems. Intrusion response mechanisms can be initiated in real-time thereby minimizing the impact of network intrusions. Finally, we have shown that our approach can be validated and how the analysis results can be used for detecting and protection from the new network anomalies.

Keywords: network intrusion detection, network intrusion prevention, association rule mining, system analysis and design

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2909 Decision Making System for Clinical Datasets

Authors: P. Bharathiraja

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Computer Aided decision making system is used to enhance diagnosis and prognosis of diseases and also to assist clinicians and junior doctors in clinical decision making. Medical Data used for decision making should be definite and consistent. Data Mining and soft computing techniques are used for cleaning the data and for incorporating human reasoning in decision making systems. Fuzzy rule based inference technique can be used for classification in order to incorporate human reasoning in the decision making process. In this work, missing values are imputed using the mean or mode of the attribute. The data are normalized using min-ma normalization to improve the design and efficiency of the fuzzy inference system. The fuzzy inference system is used to handle the uncertainties that exist in the medical data. Equal-width-partitioning is used to partition the attribute values into appropriate fuzzy intervals. Fuzzy rules are generated using Class Based Associative rule mining algorithm. The system is trained and tested using heart disease data set from the University of California at Irvine (UCI) Machine Learning Repository. The data was split using a hold out approach into training and testing data. From the experimental results it can be inferred that classification using fuzzy inference system performs better than trivial IF-THEN rule based classification approaches. Furthermore it is observed that the use of fuzzy logic and fuzzy inference mechanism handles uncertainty and also resembles human decision making. The system can be used in the absence of a clinical expert to assist junior doctors and clinicians in clinical decision making.

Keywords: decision making, data mining, normalization, fuzzy rule, classification

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2908 Effects of Physical Activity on the Association of CETP Gene with HDL Cholesterol Levels in Korean Population

Authors: Jae Woong Sull, Sun Ha Jee

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High-density lipoprotein (HDL) cholesterol levels are associated with decreased risk of coronary artery disease. Several genome-wide association studies (GWAS) for HDL cholesterol levels have implicated cholesterol ester transfer protein (CETP) as possibly causal. We tested for the association between single nucleotide polymorphisms (SNPs) in CETP gene and HDL cholesterol levels in Korean population. Subjects were selected from the Korean Metabolic Syndrome Research Initiative study in the Bundang-Gu area. A total of 2,304 individuals from Bundang-Gu were recruited in 2008. Other subjects were selected from the Severance Hospital (N=4,294). SNP rs6499861 in the CETP gene was associated with mean HDL cholesterol levels (effect per allele -2.044 mg/dL, p=7.23×10-7). Subjects with the CG/GG genotype had a 1.46 -fold (range 1.24–1.72-fold) higher risk of having abnormal HDL cholesterol levels (<40 mg/dL) than subjects with the CC genotype. When analyzed by gender, the association of CETP was stronger in women than in men. When analyzed by physical activity behavior, the association with CETP was much stronger in male subjects with low physical activity (OR=1.54, 95% CI: 1.23-1.92, P=0.0001) than in male subjects with high physical activity. This study clearly demonstrates that genetic variants in CETP influence HDL cholesterol levels in Korean adults.

Keywords: CETP, HDL cholesterol, physical activity, polymorphisms

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2907 The Association Between COL4A3 Variant RS55703767 With the Susceptibility to Diabetic Kidney Disease in Patients with Type 2 Diabetes Mellitus: Results from the Cohort Study

Authors: Zi-Han Li, Zi-Jun Sun, Dong-Yuan Chang, Li Zhu, Min Chen, Ming-Hui Zhao

Abstract:

Aims: A genome-wide association study (GWAS) reported that patients with the rs55703767 minor allele in collagen type IV α3 chain encoding gene COL4A3 showed protection against diabetic kidney disease (DKD) in type 1 diabetes mellitus (T1DM). However, the role of rs55703767 in type 2 DKD has not been elucidated. The aim of the current study was to investigate the association between COL4A3 variant rs55703767 and DKD risk in Chinese patients with type 2 diabetes mellitus (T2DM). Methods: This nested case-control study was performed on 1311 patients who had T2DM for at least 10 years, including 580 with DKD and 731 without DKD. We detected the genotypes of all patients by TaqMan SNP Genotyping Assay and analyzed the association between COL4A3 variant rs55703767 and DKD risk. Results: Genetic analysis revealed that there was no significant difference between T2DM patients with DKD and those without DKD regarding allele or genotype frequencies of rs55703767, and the effect of this variant was not hyperglycemia specific. Conclusion: Our findings suggested that there was no detectable association between the COL4A3 variant rs55703767 and the susceptibility to DKD in the Chinese T2DM population.

Keywords: collagen type IV α3 chain, gene polymorphism, type 2 diabetes, diabetic kidney disease

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2906 Gender Difference in the Association between Different Components of the Metabolic Syndrome and Vitamin D Levels in Saudi Patients

Authors: Amal Baalash, Shazia Mukaddam, M. Adel El-Sayed

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Background: Several studies have suggested non-skeletal effects of vitamin D and linked its deficiency with features of many chronic conditions. In this study, We aimed to investigate the relationship between vitamin D levels and different components of the metabolic syndrome in male and female Saudi patients. Methods: the study population consisted of 111 patients with metabolic syndrome (71 females and 40 males) aged 37-63 years enrolled from patients attending the internal medicine outpatient clinics of King Fahad Medical City. The parameters for diagnosis of the metabolic syndrome according to the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) were measured, which included waist circumference, TG, HDL-C, Blood pressure and fasting blood glucose (FBS). The association between each parameter and serum 25-hydroxyvitamin D (25(OH) D) was studied in both male and female patients separately. Results: in male patients, 25(OH) D levels were inversely associated with FBS and TG and positively associated with HDL-C and diastolic blood pressure, With highest association with the HDL-C levels. On the other hand 25(OH) D, Showed no significant association with any of the measured metabolic syndrome parameters in female patients. Conclusion: in Saudi patients with metabolic syndrome, the association between the parameters of metabolic syndrome and the levels of 25 (OH) D is more pronounced in males rather than females.

Keywords: gender, metabolic syndrome, Saudi patients, vitamin D

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2905 Predicting Groundwater Areas Using Data Mining Techniques: Groundwater in Jordan as Case Study

Authors: Faisal Aburub, Wael Hadi

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Data mining is the process of extracting useful or hidden information from a large database. Extracted information can be used to discover relationships among features, where data objects are grouped according to logical relationships; or to predict unseen objects to one of the predefined groups. In this paper, we aim to investigate four well-known data mining algorithms in order to predict groundwater areas in Jordan. These algorithms are Support Vector Machines (SVMs), Naïve Bayes (NB), K-Nearest Neighbor (kNN) and Classification Based on Association Rule (CBA). The experimental results indicate that the SVMs algorithm outperformed other algorithms in terms of classification accuracy, precision and F1 evaluation measures using the datasets of groundwater areas that were collected from Jordanian Ministry of Water and Irrigation.

Keywords: classification, data mining, evaluation measures, groundwater

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2904 Validating the Micro-Dynamic Rule in Opinion Dynamics Models

Authors: Dino Carpentras, Paul Maher, Caoimhe O'Reilly, Michael Quayle

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Opinion dynamics is dedicated to modeling the dynamic evolution of people's opinions. Models in this field are based on a micro-dynamic rule, which determines how people update their opinion when interacting. Despite the high number of new models (many of them based on new rules), little research has been dedicated to experimentally validate the rule. A few studies started bridging this literature gap by experimentally testing the rule. However, in these studies, participants are forced to express their opinion as a number instead of using natural language. Furthermore, some of these studies average data from experimental questions, without testing if differences existed between them. Indeed, it is possible that different topics could show different dynamics. For example, people may be more prone to accepting someone's else opinion regarding less polarized topics. In this work, we collected data from 200 participants on 5 unpolarized topics. Participants expressed their opinions using natural language ('agree' or 'disagree') and the certainty of their answer, expressed as a number between 1 and 10. To keep the interaction based on natural language, certainty was not shown to other participants. We then showed to the participant someone else's opinion on the same topic and, after a distraction task, we repeated the measurement. To produce data compatible with standard opinion dynamics models, we multiplied the opinion (encoded as agree=1 and disagree=-1) with the certainty to obtain a single 'continuous opinion' ranging from -10 to 10. By analyzing the topics independently, we observed that each one shows a different initial distribution. However, the dynamics (i.e., the properties of the opinion change) appear to be similar between all topics. This suggested that the same micro-dynamic rule could be applied to unpolarized topics. Another important result is that participants that change opinion tend to maintain similar levels of certainty. This is in contrast with typical micro-dynamics rules, where agents move to an average point instead of directly jumping to the opposite continuous opinion. As expected, in the data, we also observed the effect of social influence. This means that exposing someone with 'agree' or 'disagree' influenced participants to respectively higher or lower values of the continuous opinion. However, we also observed random variations whose effect was stronger than the social influence’s one. We even observed cases of people that changed from 'agree' to 'disagree,' even if they were exposed to 'agree.' This phenomenon is surprising, as, in the standard literature, the strength of the noise is usually smaller than the strength of social influence. Finally, we also built an opinion dynamics model from the data. The model was able to explain more than 80% of the data variance. Furthermore, by iterating the model, we were able to produce polarized states even starting from an unpolarized population. This experimental approach offers a way to test the micro-dynamic rule. This also allows us to build models which are directly grounded on experimental results.

Keywords: experimental validation, micro-dynamic rule, opinion dynamics, update rule

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2903 The Distribution of rs5219 Polymorphism in the Non-Diabetic Elderly Jordanian Subject

Authors: Foad Alzoughool

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Conflicting studies on the association between the rs5219 polymorphism and type 2 diabetes, some studies have confirmed a strong relationship between this variant and type2 diabetes, on the other hand, many studies denied the existence of this association. This study aimed to provide evidence about whether the rs5219 polymorphism has or hasn't a role as a risk factor for diabetes and meta-analysis to investigate the role of the control age group in the association. Genotyping of the rs5219 polymorphism was performed in a cohort of 266 healthy elderly subjects with a mean age (60.2 ± 5.1) with no history of diabetes (HbA1c < 6%) using standard Sanger sequencing methods. Lys/Lys alleles were detected in 20 persons (7.5%), Lys/Glu alleles in 96 persons (36.1%), and Glu/Glu in 150 persons (56.4%). The genotype distribution was consistent with Hardy–Weinberg equilibrium (P =0.7). Meta-analysis notably indicates no association between rs5219 polymorphism and type 2 diabetes in all studies used the younger age of the control group compared to the patient's age. In conclusion, our study sheds light on the importance of age factor among the control group recruited in case-control studies.

Keywords: Type 2 diabetes, rs5219 polymorphism, E23K, KCNJ11 gene

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2902 A Comprehensive Survey and Improvement to Existing Privacy Preserving Data Mining Techniques

Authors: Tosin Ige

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Ethics must be a condition of the world, like logic. (Ludwig Wittgenstein, 1889-1951). As important as data mining is, it possess a significant threat to ethics, privacy, and legality, since data mining makes it difficult for an individual or consumer (in the case of a company) to control the accessibility and usage of his data. This research focuses on Current issues and the latest research and development on Privacy preserving data mining methods as at year 2022. It also discusses some advances in those techniques while at the same time highlighting and providing a new technique as a solution to an existing technique of privacy preserving data mining methods. This paper also bridges the wide gap between Data mining and the Web Application Programing Interface (web API), where research is urgently needed for an added layer of security in data mining while at the same time introducing a seamless and more efficient way of data mining.

Keywords: data, privacy, data mining, association rule, privacy preserving, mining technique

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2901 Spatio-Temporal Data Mining with Association Rules for Lake Van

Authors: Tolga Aydin, M. Fatih Alaeddinoğlu

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People, throughout the history, have made estimates and inferences about the future by using their past experiences. Developing information technologies and the improvements in the database management systems make it possible to extract useful information from knowledge in hand for the strategic decisions. Therefore, different methods have been developed. Data mining by association rules learning is one of such methods. Apriori algorithm, one of the well-known association rules learning algorithms, is not commonly used in spatio-temporal data sets. However, it is possible to embed time and space features into the data sets and make Apriori algorithm a suitable data mining technique for learning spatio-temporal association rules. Lake Van, the largest lake of Turkey, is a closed basin. This feature causes the volume of the lake to increase or decrease as a result of change in water amount it holds. In this study, evaporation, humidity, lake altitude, amount of rainfall and temperature parameters recorded in Lake Van region throughout the years are used by the Apriori algorithm and a spatio-temporal data mining application is developed to identify overflows and newly-formed soil regions (underflows) occurring in the coastal parts of Lake Van. Identifying possible reasons of overflows and underflows may be used to alert the experts to take precautions and make the necessary investments.

Keywords: apriori algorithm, association rules, data mining, spatio-temporal data

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2900 The Parallelization of Algorithm Based on Partition Principle for Association Rules Discovery

Authors: Khadidja Belbachir, Hafida Belbachir

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subsequently the expansion of the physical supports storage and the needs ceaseless to accumulate several data, the sequential algorithms of associations’ rules research proved to be ineffective. Thus the introduction of the new parallel versions is imperative. We propose in this paper, a parallel version of a sequential algorithm “Partition”. This last is fundamentally different from the other sequential algorithms, because it scans the data base only twice to generate the significant association rules. By consequence, the parallel approach does not require much communication between the sites. The proposed approach was implemented for an experimental study. The obtained results, shows a great reduction in execution time compared to the sequential version and Count Distributed algorithm.

Keywords: association rules, distributed data mining, partition, parallel algorithms

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2899 Is Hormone Replacement Therapy Associated with Age-Related Macular Degeneration? A Systematic Review and Meta-Analysis

Authors: Hongxin Zhao, Shibing Yang, Bingming Yi, Yi Ning

Abstract:

Background: A few studies have found evidence that exposure to endogenous or postmenopausal exogenous estrogens may be associated with a lower prevalence of age-related macular degeneration (AMD), but dispute over this association is ongoing due to inconsistent results reported by different studies. Objectives: To conduct a systematic review and meta-analysis to investigate the association between hormone replacement therapy (HRT) use and AMD. Methods: Relevant studies that assessed the association between HRT and AMD were searched through four databases (PubMed, Web of Science, Cochrane Library, EMBASE) and reference lists of retrieved studies. Study selection, data extraction and quality assessment were conducted by three independent reviewers. The fixed-effect meta-analyses were performed to estimate the association between HRT ever-use and AMD by pooling risk ratio (RR) or odds ratio (OR) across studies. Results: The review identified 2 prospective and 7 cross-sectional studies with 93992 female participants that reported an estimate of the association between HRT ever-use and presence of early AMD or late AMD. Meta-analyses showed that there were no statistically significant associations between HRT ever-use and early AMD (pooled RR for cohort studies was 1.04, 95% CI 0.86 - 1.24; pooled OR for cross-sectional studies was 0.91, 95% CI 0.82 - 1.01). The pooled results from cross-sectional studies also showed no statistically significant association between HRT ever-use and late AMD (OR 1.01; 95% CI 0.89 - 1.15). Conclusions: The pooled effects from observational studies published to date indicate that HRT use is associated with neither early nor late AMD. Exposure to HRT may not protect women from developing AMD.

Keywords: hormone replacement therapy, age-related macular degeneration, meta-analysis, systematic review

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2898 Biostimulation Effect of Ozone Therapy and Superficial Peeling on Facial Rejuvenation: A Case Report and Literature Review

Authors: Ferreira R., Rocha K.

Abstract:

Ozone therapy is indicated for improving skin aesthetics, adjusting oxidative tissue levels, increasing collagen production, and even skin volumizing. This paper aims to carry out a case report that demonstrates the positive results of ozone therapy in association with superficial peeling. The application in association showed positive results for bio-stimulating activities in the reported case demonstrating to be a viable clinical technique. The bio-stimulating effect of ozone therapy in association with peeling is a promising aesthetic therapeutic modality with fast and safe results as an aesthetic therapeutic option.

Keywords: bio-stimulating effect, ozone therapy, neocollagenesis, peeling

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2897 Application of Granular Computing Paradigm in Knowledge Induction

Authors: Iftikhar U. Sikder

Abstract:

This paper illustrates an application of granular computing approach, namely rough set theory in data mining. The paper outlines the formalism of granular computing and elucidates the mathematical underpinning of rough set theory, which has been widely used by the data mining and the machine learning community. A real-world application is illustrated, and the classification performance is compared with other contending machine learning algorithms. The predictive performance of the rough set rule induction model shows comparative success with respect to other contending algorithms.

Keywords: concept approximation, granular computing, reducts, rough set theory, rule induction

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2896 Rule-Of-Mixtures: Predicting the Bending Modulus of Unidirectional Fiber Reinforced Dental Composites

Authors: Niloofar Bahramian, Mohammad Atai, Mohammad Reza Naimi-Jamal

Abstract:

Rule of mixtures is the simple analytical model is used to predict various properties of composites before design. The aim of this study was to demonstrate the benefits and limitations of the Rule-of-Mixtures (ROM) for predicting bending modulus of a continuous and unidirectional fiber reinforced composites using in dental applications. The Composites were fabricated from light curing resin (with and without silica nanoparticles) and modified and non-modified fibers. Composite samples were divided into eight groups with ten specimens for each group. The bending modulus (flexural modulus) of samples was determined from the slope of the initial linear region of stress-strain curve on 2mm×2mm×25mm specimens with different designs: fibers corona treatment time (0s, 5s, 7s), fibers silane treatment (0%wt, 2%wt), fibers volume fraction (41%, 33%, 25%) and nanoparticles incorporation in resin (0%wt, 10%wt, 15%wt). To study the fiber and matrix interface after fracture, single edge notch beam (SENB) method and scanning electron microscope (SEM) were used. SEM also was used to show the nanoparticles dispersion in resin. Experimental results of bending modulus for composites made of both physical (corona) and chemical (silane) treated fibers were in reasonable agreement with linear ROM estimates, but untreated fibers or non-optimized treated fibers and poor nanoparticles dispersion did not correlate as well with ROM results. This study shows that the ROM is useful to predict the mechanical behavior of unidirectional dental composites but fiber-resin interface and quality of nanoparticles dispersion play important role in ROM accurate predictions.

Keywords: bending modulus, fiber reinforced composite, fiber treatment, rule-of-mixtures

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2895 Rule Based Architecture for Collaborative Multidisciplinary Aircraft Design Optimisation

Authors: Nickolay Jelev, Andy Keane, Carren Holden, András Sóbester

Abstract:

In aircraft design, the jump from the conceptual to preliminary design stage introduces a level of complexity which cannot be realistically handled by a single optimiser, be that a human (chief engineer) or an algorithm. The design process is often partitioned along disciplinary lines, with each discipline given a level of autonomy. This introduces a number of challenges including, but not limited to: coupling of design variables; coordinating disciplinary teams; handling of large amounts of analysis data; reaching an acceptable design within time constraints. A number of classical Multidisciplinary Design Optimisation (MDO) architectures exist in academia specifically designed to address these challenges. Their limited use in the industrial aircraft design process has inspired the authors of this paper to develop an alternative strategy based on well established ideas from Decision Support Systems. The proposed rule based architecture sacrifices possibly elusive guarantees of convergence for an attractive return in simplicity. The method is demonstrated on analytical and aircraft design test cases and its performance is compared to a number of classical distributed MDO architectures.

Keywords: Multidisciplinary Design Optimisation, Rule Based Architecture, Aircraft Design, Decision Support System

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2894 Optimization of Dez Dam Reservoir Operation Using Genetic Algorithm

Authors: Alireza Nikbakht Shahbazi, Emadeddin Shirali

Abstract:

Since optimization issues of water resources are complicated due to the variety of decision making criteria and objective functions, it is sometimes impossible to resolve them through regular optimization methods or, it is time or money consuming. Therefore, the use of modern tools and methods is inevitable in resolving such problems. An accurate and essential utilization policy has to be determined in order to use natural resources such as water reservoirs optimally. Water reservoir programming studies aim to determine the final cultivated land area based on predefined agricultural models and water requirements. Dam utilization rule curve is also provided in such studies. The basic information applied in water reservoir programming studies generally include meteorological, hydrological, agricultural and water reservoir related data, and the geometric characteristics of the reservoir. The system of Dez dam water resources was simulated applying the basic information in order to determine the capability of its reservoir to provide the objectives of the performed plan. As a meta-exploratory method, genetic algorithm was applied in order to provide utilization rule curves (intersecting the reservoir volume). MATLAB software was used in order to resolve the foresaid model. Rule curves were firstly obtained through genetic algorithm. Then the significance of using rule curves and the decrease in decision making variables in the system was determined through system simulation and comparing the results with optimization results (Standard Operating Procedure). One of the most essential issues in optimization of a complicated water resource system is the increasing number of variables. Therefore a lot of time is required to find an optimum answer and in some cases, no desirable result is obtained. In this research, intersecting the reservoir volume has been applied as a modern model in order to reduce the number of variables. Water reservoir programming studies has been performed based on basic information, general hypotheses and standards and applying monthly simulation technique for a statistical period of 30 years. Results indicated that application of rule curve prevents the extreme shortages and decrease the monthly shortages.

Keywords: optimization, rule curve, genetic algorithm method, Dez dam reservoir

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2893 Conflict Resolution in Fuzzy Rule Base Systems Using Temporal Modalities Inference

Authors: Nasser S. Shebka

Abstract:

Fuzzy logic is used in complex adaptive systems where classical tools of representing knowledge are unproductive. Nevertheless, the incorporation of fuzzy logic, as it’s the case with all artificial intelligence tools, raised some inconsistencies and limitations in dealing with increased complexity systems and rules that apply to real-life situations and hinders the ability of the inference process of such systems, but it also faces some inconsistencies between inferences generated fuzzy rules of complex or imprecise knowledge-based systems. The use of fuzzy logic enhanced the capability of knowledge representation in such applications that requires fuzzy representation of truth values or similar multi-value constant parameters derived from multi-valued logic, which set the basis for the three t-norms and their based connectives which are actually continuous functions and any other continuous t-norm can be described as an ordinal sum of these three basic ones. However, some of the attempts to solve this dilemma were an alteration to fuzzy logic by means of non-monotonic logic, which is used to deal with the defeasible inference of expert systems reasoning, for example, to allow for inference retraction upon additional data. However, even the introduction of non-monotonic fuzzy reasoning faces a major issue of conflict resolution for which many principles were introduced, such as; the specificity principle and the weakest link principle. The aim of our work is to improve the logical representation and functional modelling of AI systems by presenting a method of resolving existing and potential rule conflicts by representing temporal modalities within defeasible inference rule-based systems. Our paper investigates the possibility of resolving fuzzy rules conflict in a non-monotonic fuzzy reasoning-based system by introducing temporal modalities and Kripke's general weak modal logic operators in order to expand its knowledge representation capabilities by means of flexibility in classifying newly generated rules, and hence, resolving potential conflicts between these fuzzy rules. We were able to address the aforementioned problem of our investigation by restructuring the inference process of the fuzzy rule-based system. This is achieved by using time-branching temporal logic in combination with restricted first-order logic quantifiers, as well as propositional logic to represent classical temporal modality operators. The resulting findings not only enhance the flexibility of complex rule-base systems inference process but contributes to the fundamental methods of building rule bases in such a manner that will allow for a wider range of applicable real-life situations derived from a quantitative and qualitative knowledge representational perspective.

Keywords: fuzzy rule-based systems, fuzzy tense inference, intelligent systems, temporal modalities

Procedia PDF Downloads 92