Search results for: Association rules mining

Authors: Manjunath A. P., Al-Ajmi G. M., Al Shukri M., Girija S

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Introduction: This study aimed to compare the ability of hysteroscopy and ultrasonography to diagnose uterine polyps. To correlate the ultrasonography and hystroscopic findings with various clinical factors and histopathology of uterine polyps. Methods: This is a retrospective study conducted at the Department of Obstetrics and Gynaecology at Sultan Qaboos University Hospital from 2014 to 2019. All women undergoing hysteroscopy for suspected uterine polyps were included. All relevant data were obtained from the electronic patient record and analysed using SPSS. Results: A total of 77 eligible women were analysed. The mean age of the patients was 40 years. The clinical risk factors; obesity, hypertension, and diabetes mellitus, showed no significant statistical association with the presence of uterine polyps (p-value>0.005). Although 20 women (52.6%) with uterine polyps had thickened endometrium (>11 mm), however, there is no statistical association (p-value>0.005). The sensitivity and specificity of ultrasonography in the detection of uterine polyp were 39% and 65%, respectively. Whereas for hysteroscopy, it was 89% and 20%, respectively. The prevalence of malignant and premalignant lesions were 1.85% and 7.4%, respectively. Conclusion: This study found that obesity, hypertension, and diabetes mellitus were not associated with the presence of uterine polyps. There was no association between thick endometrium and uterine polyps. The sensitivity is higher for hysteroscopy, whereas the specificity is higher for sonography in detecting uterine polyps. The prevalence of malignancy was very low in uterine polyps.

Keywords: endometrial polyps, hysteroscopy, ultrasonography, premalignant, malignant

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Authors: Paul Narh Doku

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The relationship between parental HIV/AIDS status or death and child mental health is well known, although the role of child maltreatment as a confounder or mediator in this relationship remains uncertain. This study examined the potential path mechanism through child maltreatment mediating the link between HIV/AIDS family dysfunction trajectories and psychosocial problems. A cross-sectional survey was conducted in the Lower Manya Municipal Assembly of Ghana. A questionnaire which consisted of the Strengths and Difficulties Questionnaire (SDQ), Social and Health Assessment (SAHA), Rosenberg Self-Esteem Scale (RSES), and the Conflict Tactics Scale (CTS) was completed by 291 adolescents. Controlling for relevant sociodemographic confounders, mediation analyses using linear regression were fitted to examine whether the association between family dysfunction and psychosocial problems is mediated by child maltreatment. The results indicate that, among adolescents, child maltreatment fully mediated the association between being orphaned by AIDS and self-esteem, delinquency and risky behaviours, and peer problems. Similarly, child maltreatment fully mediated the association between living with an HIV/AIDS-infected parent and self-esteem, delinquency and risky behaviours, depression/emotional problems, and peer problems. Partial mediation was found for hyperactivity. Child maltreatment mediates the association between the family dysfunction trajectories of parental HIV/AIDS or death and psychosocial problems among adolescents. This implies that efforts to address child maltreatment among families affected by HIV/AIDS may be helpful in the prevention of psychosocial problems among these children, thus enhancing their well-being. The findings, therefore, underscore the need for comprehensive psychosocial interventions that address both the unique negative exposures of HIV/AIDS and maltreatment for children affected by HIV.

Keywords: child maltreatment, child abuse, mental health, psychosocial problems, domestic violence, HIV/AIDS, adolescents

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Authors: Adeniyi Samuel Adekoya

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The study assessed the independent effects of age and energy expenditure on the risks of obesity among adults (20-64 years). A cross-sectional study with changes in age, changes in work and leisure-time, and physical activities information played roles, with cut-off for energy expenditure and BMI in rural and urban localities. Physical activity information determined the energy expenditure, while the BMI determined the risk of obesity among the subjects. Statistically, age has a strong and direct association with obesity in both rural and urban settings, while energy expenditure was inverse in its association. Findings from the this study showed that in developing societies, age tends to be a risk factor for obesity, whereas energy expenditure is to be protective. Level of education and economic development are also relevant modifiers of the influences exerted by these variables.

Keywords: age, energy expenditure, BMI, rural/urban

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Authors: Yosra Baaziz, Moez Labidi

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Given limited research on monetary policy rules in revolutionary countries, this paper challenges the suitability of the Taylor rule in characterizing the monetary policy behavior of the Tunisian Central Bank (BCT), especially in turbulent times. More specifically, we investigate the possibility that the Taylor rule should be formulated as a threshold process and examine the validity of such nonlinear Taylor rule as a robust rule for conducting monetary policy in Tunisia. Using quarterly data from 1998:Q4 to 2013:Q4 to analyze the movement of nominal short-term interest rate of the BCT, we find that the nonlinear Taylor rule improves its performance with the advent of special events providing thus a better description of the Tunisian interest rate setting. In particular, our results show that the adoption of an appropriate nonlinear approach leads to a reduction in the errors of 150 basis points in 1999 and 2009, and 60 basis points in 2011, relative to the linear approach.

Keywords: policy rule, central bank, exchange rate, taylor rule, nonlinearity

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Authors: Amani Ashari, Julia Omar, Arif Hashim, Shahrul Hamid

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Apolipoprotein E (APOE) gene polymorphism has influence on serum lipids which relates to cardiovascular risk. The purpose of this study was to determine the frequency distribution of APOE alleles among Malaysian Type 2 Diabetes Mellitus (DM) patients with and without coronary artery disease (CAD) and their association with serum lipid profiles. A total of 115 patients were recruited in which 78 patients had Type 2 DM without CAD and 37 patients had Type 2 DM with CAD. The APOE polymorphism was detected by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). The APOE ɛ3 allele was the most common one in both groups. There was no significant association between the APOE genotypes and the CAD status in Type 2 DM using Pearson χ² test. Further analysis indicated there were no significant differences in all lipid parameters between E2, E3 and E4 subgroups in both groups. The study showed that the E4 allele carriers of Type 2 DM with CAD patients had higher LDL-C level and lower HDL-C level compared to the other allele carriers. However, analyses showed these levels were not statistically different. The study also showed that the Type 2 DM with CAD group with E2 allele had higher triglyceride (TG). In conclusion, further study with larger sample size is needed to confirm role of E4 as a marker of CAD among Type 2 DM patients in Malaysian population.

Keywords: Apolipoprotein E, diabetes mellitus, cardiovascular disease, lipids

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Authors: Nasser S. Shebka

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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

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Authors: Elham Sharif, Nasser Rizk, Sirin Abu Aqel, Ofelia Masoud

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Background: Previous studies have investigated the association of rs1544410, rs7975232 and rs731236 polymorphisms in vitamin D receptor gene and its impact on diseases such as cancer, diabetes and hypertension in different ethnic backgrounds. Aim: The aim of this study is to investigate the association between VDR polymorphisms using three SNP’s (rs1544410, rs7975232 and rs731236) and the severity of the significant lesion in coronary arteries among angiographically diagnosed CAD. Methods: A prospective-retrospective study was conducted on 192 CAD patients enrolled from the cardiology department-Heart Hospital HMC, grouped in 96 subjects with significant stenosis and 96 with non-significant stenosis with a mean age between 30 and 75 years old. Genotyping was performed for the following SNPs rs1544410, rs7975232 and rs731236 using TaqMan assay by the Real Time PCR, ABI 7500 in Health Sciences Labs at Qatar University Biomedical Research Center. Results: The results showed that both groups have matched age and gender distribution but patients with the significant stenosis have significantly higher; BMI (p=0.047); smoking status (p=0.039); FBS (p= 0.031); CK-MB (p=0.025) and Troponin (p=0.002) than the patients with non–significant lesion. Among the traditional risk factors, smoking increases the odds of the severe stenotic lesion in CAD patients by 1.984, with 95% CI between 1.024 – 7.063, with p= 0.042.HWE showed deviations of the rs1544410 and rs731236 among the study subjects. The most frequent genotype in distribution of rs7975232 is the AA among the significant stenosis patients, while the heterozygous AC was the frequent genotype in distribution among the non-significant stenosis group. The carriers of CC genotype in rs7975232 increased the risk of having significant coronary arteries stenotic lesion by 1.83 with 95% CI (1.020 – 3.280), p=0.043. No association was found between the rs7975232 with vitamin D and VDBP. Conclusion: There is a significant association between rs7975232 and the severity of CAD lesion. The carrier of CC genotype in rs7975232 increased the risk of having significant coronary arteries atherosclerotic lesion especially in patients with smoking history independent of vitamin D.

Keywords: vitamin D, vitamin D receptor, polymorphism, coronary harat disease

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Authors: Kyung Bae Park, Sung Ho Ha

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Online user-generated contents (UGC) significantly change the way customers behave (e.g., shop, travel), and a pressing need to handle the overwhelmingly plethora amount of various UGC is one of the paramount issues for management. However, a current approach (e.g., sentiment analysis) is often ineffective for leveraging textual information to detect the problems or issues that a certain management suffers from. In this paper, we employ text mining of Latent Dirichlet Allocation (LDA) on a popular online review site dedicated to complaint from users. We find that the employed LDA efficiently detects customer complaints, and a further inspection with the visualization technique is effective to categorize the problems or issues. As such, management can identify the issues at stake and prioritize them accordingly in a timely manner given the limited amount of resources. The findings provide managerial insights into how analytics on social media can help maintain and improve their reputation management. Our interdisciplinary approach also highlights several insights by applying machine learning techniques in marketing research domain. On a broader technical note, this paper illustrates the details of how to implement LDA in R program from a beginning (data collection in R) to an end (LDA analysis in R) since the instruction is still largely undocumented. In this regard, it will help lower the boundary for interdisciplinary researcher to conduct related research.

Keywords: latent dirichlet allocation, R program, text mining, topic model, user generated contents, visualization

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Authors: Sokkhey Phauk, Takeo Okazaki

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The challenging task in educational institutions is to maximize the high performance of students and minimize the failure rate of poor-performing students. An effective method to leverage this task is to know student learning patterns with highly influencing factors and get an early prediction of student learning outcomes at the timely stage for setting up policies for improvement. Educational data mining (EDM) is an emerging disciplinary field of data mining, statistics, and machine learning concerned with extracting useful knowledge and information for the sake of improvement and development in the education environment. The study is of this work is to propose techniques in EDM and integrate it into a web-based system for predicting poor-performing students. A comparative study of prediction models is conducted. Subsequently, high performing models are developed to get higher performance. The hybrid random forest (Hybrid RF) produces the most successful classification. For the context of intervention and improving the learning outcomes, a feature selection method MICHI, which is the combination of mutual information (MI) and chi-square (CHI) algorithms based on the ranked feature scores, is introduced to select a dominant feature set that improves the performance of prediction and uses the obtained dominant set as information for intervention. By using the proposed techniques of EDM, an academic performance prediction system (APPS) is subsequently developed for educational stockholders to get an early prediction of student learning outcomes for timely intervention. Experimental outcomes and evaluation surveys report the effectiveness and usefulness of the developed system. The system is used to help educational stakeholders and related individuals for intervening and improving student performance.

Keywords: academic performance prediction system, educational data mining, dominant factors, feature selection method, prediction model, student performance

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Authors: Ghirmay Teklemicheal, Samsom Mehari, Sara Tesfay

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Objectives: A total of 1074 suspected chikungunya cases were reported in Tesseney Province, Gash Barka region, Eritrea, during an outbreak. This study was aimed to assess the possible association of chikungunya severity among ABO blood groups and other potential determinants. Methods: A sex-matched and age-matched case-control study was conducted during the outbreak. For each case, one control subject had been selected from the mild Chikungunya cases. Along the same line of argument, a second control subject had also been designated through which neighborhood of cases were analyzed, scrutinized, and appeared to the scheme of comparison. Time is always the most sacrosanct element in pursuance of any study. According to the temporal calculation, this study was pursued from October 15, 2018, to November 15, 2018. Coming to the methodological dependability, calculating odds ratios (ORs) and conditional (fixed-effect) logistic regression methods were being applied. As a consequence of this, the data was analyzed and construed on the basis of the aforementioned methodological systems. Results: In this outbreak, 137 severe suspected chikungunya cases and 137 mild chikungunya suspected patients, and 137 controls free of chikungunya from the neighborhood of cases were analyzed. Non-O individuals compared to those with O blood group indicated as significant with a p-value of 0.002. Separate blood group comparison among A and O blood groups reflected as significant with a p-value of 0.002. However, there was no significant difference in the severity of chikungunya among B, AB, and O blood groups with a p-value of 0.113 and 0.708, respectively, and a strong association of chikungunya severity was found with hypertension and diabetes (p-value of < 0.0001); whereas, there was no association between chikungunya severity and asthma with a p-value of 0.695 and also no association with pregnancy (p-value =0.881), ventilator (p-value =0.181), air conditioner (p-value = 0.247), and didn’t use latrine and pit latrine (p-value = 0.318), among individuals using septic and pit latrine (p-value = 0.567) and also among individuals using flush and pit latrine (p-value = 0.194). Conclusions: Non- O blood groups were found to be at risk more than their counterpart O blood group individuals with severe form of chikungunya disease. By the same token, individuals with chronic disease were more prone to severe forms of the disease in comparison with individuals without chronic disease. Prioritization is recommended for patients with chronic diseases and non-O blood group since they are found to be susceptible to severe chikungunya disease. Identification of human cell surface receptor(s) for CHIKV is quite necessary for further understanding of its pathophysiology in humans. Therefore, molecular and functional studies will necessarily be helpful in disclosing the association of blood group antigens and CHIKV infections.

Keywords: Chikungunya, Chikungunya virus, disease outbreaks, case-control studies, Eritrea

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Authors: Gregory Michael McMahon

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Risk management for the purposes of minimizing the damages from the operations of dams has met with opposition emerging from organisations and authorities, and their practitioners. It appears that the cause may be a misunderstanding of risk management arising from exchanges that mix deterministic thinking with risk-centric thinking and that do not separate uncertainty from reliability and accuracy from probability. This paper sets out those misunderstandings that arose from dam operations at Wivenhoe in 2011, using a comparison of outcomes that have been based on the methodology and its rules and those that have been operated by applying misunderstandings of the rules. The paper addresses the performance of one risk-centric Flood Manual for Wivenhoe Dam in achieving a risk management outcome. A mixture of engineering, administrative, and legal factors appear to have combined to reduce the outcomes from the risk approach. These are described. The findings are that a risk-centric Manual may need to assist administrations in the conduct of scenario training regimes, in responding to healthy audit reporting, and in the development of decision-support systems. The principal assistance needed from the Manual, however, is to assist engineering and the law to a good understanding of how risks are managed – do not assume that risk management is understood. The wider findings are that the critical profession for decision-making downstream of the meteorologist is not dam engineering or hydrology, or hydraulics; it is risk management. Risk management will provide the minimum flood damage outcome where actual rainfalls match or exceed forecasts of rainfalls, that therefore risk management will provide the best approach for the likely history of flooding in the life of a dam, and provisions made for worst cases may be state of the art in risk management. The principal conclusion is the need for training in both risk management as a discipline and also in the application of risk management rules to particular dam operational scenarios.

Keywords: risk management, flood control, dam operations, deterministic thinking

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Authors: Kisik Song, Kyuwoong Kim, Sungjoo Lee

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Many global firms and corporations derive new technology and opportunity by identifying vacant technology from patent analysis. However, previous studies failed to focus on technologies that promised continuous growth in industrial fields. Most studies that derive new technology opportunities do not test practical effectiveness. Since previous studies depended on expert judgment, it became costly and time-consuming to evaluate new technologies based on patent analysis. Therefore, research suggests a quantitative and systematic approach to technology evaluation indicators by using patent data to and from customer communities. The first step involves collecting two types of data. The data is used to construct evaluation indicators and apply these indicators to the evaluation of new technologies. This type of data mining allows a new method of technology evaluation and better predictor of how new technologies are adopted.

Keywords: data mining, evaluating new technology, technology opportunity, patent analysis

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Authors: Anida Causevic-Ramosevac, Sabina Semiz

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The aim of this study was to investigate the association of four single nucleotide polymorphisms (SNPs) - rs673548, rs693 in ApoB gene, rs1800775 in CETP gene and rs4846914 in GALNT2 gene with parameters of type 2 diabetes (T2D) and diabetic dyslipidemia in the population of Bosnia and Herzegovina (BH). Materials and methods: Our study involved 352 patients with T2D and 156 healthy subjects. Biochemical and anthropometric parameters were measured in all participants. DNA was extracted from the peripheral blood for the purpose of genetic testing. Polymorphisms in ApoB (rs673548, rs693), CETP (rs1800775) and GALNT2 (rs4846914) genes were analyzed by using Sequenom IPLEX platform. Results: Our results demonstrated significant associations for rs180075 polymorphism in CETP gene with levels of fasting insulin (p = 0.020; p = 0.027; p = 0.044), triglycerides (p = 0.046) and ALT (p = 0.031) activity in control group. In group of diabetic patients, results showed a significant association of rs673548 in ApoB gene with levels of fasting insulin (p = 0.008), HOMA-IR (p = 0.013), VLDL-C (p = 0.037) and CRP (p = 0.029) and rs693 in ApoB gene with BMI (p = 0.025), systolic blood pressure (p = 0.027), fasting insulin (p = 0.037) and HOMA-IR (p = 0.023) levels. Significant associations were also observed for rs1800775 in CETP gene with triglyceride (p = 0.023) levels and rs4846914 in GALNT2 gene with HbA1C (p = 0.013) and triglyceride (p = 0.043) levels. Conclusion: In conclusion, this is the first study that examined the impact of variations of candidate genes on a wide range of metabolic parameters in BH population. Our results suggest an association of variations of ApoB, CETP and GALNT2 genes with specific markers of T2D and dyslipidemia. Further studies would be needed in order to confirm these genetic effects in other ethnic groups as well.

Keywords: ApoB, CETP, dyslipidemia, GALNT2, type 2 diabetes

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Authors: Susanna Menis

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The context of this study revolves around the theme of consent and the construction of unlawfulness in judicial decisions. It aims to explore the formation of societal perceptions of unlawfulness within the context of consensual sexual acts leading to harmful consequences. This study investigates how judges create legal rules that reflect social solidarity and protect against violence. Specifically, the research aims to understand the justification behind criminalising consensual sexual activity when categorised under different offences. The main question addressed in this study will evaluate the way judges create legal rules that they believe reflect social solidarity and protect against violence. The study employs a historical genealogy approach as its methodology. This approach allows for tracing back the original formation of societal perspectives on unlawfulness, thus highlighting the socially constructed nature of the present understanding. The data for this study will be collected through an extensive literature review, examining historical legal cases and documents that shape the understanding of unlawfulness. This will provide a comprehensive view of how social attitudes toward private sexual relations influenced the creation of legal rules. The theoretical importance of this research lies in its contribution to socio-legal scholarship. This study adds to the existing knowledge on the topic by exploring questions of unconscious bias and its origins. The findings shed light on how and why individuals possess unconscious biases, particularly within the judicial system. In conclusion, this study investigates judicial decisions concerning consensual sexual acts and the construction of unlawfulness. By employing a historical genealogy approach, the research sheds light on how judges create legal rules that reflect social solidarity and aim to protect against violence. The theoretical importance of this study lies in its contribution to understanding unconscious bias and its origins within the judicial system. Through data collection and analysis procedures, this study aims to provide valuable insights into the formation of social attitudes towards private sexual relations and its impact on legal rulings.

Keywords: consent, sexual offences, offences against the person, legal genealogy, social construct

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Authors: Deeman Yousif Mahmood, Mohammed Abdullah Hussein

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The goal of a network-based intrusion detection system is to classify activities of network traffics into two major categories: normal and attack (intrusive) activities. Nowadays, data mining and machine learning plays an important role in many sciences; including intrusion detection system (IDS) using both supervised and unsupervised techniques. However, one of the essential steps of data mining is feature selection that helps in improving the efficiency, performance and prediction rate of proposed approach. This paper applies unsupervised K-means clustering algorithm with information gain (IG) for feature selection and reduction to build a network intrusion detection system. For our experimental analysis, we have used the new NSL-KDD dataset, which is a modified dataset for KDDCup 1999 intrusion detection benchmark dataset. With a split of 60.0% for the training set and the remainder for the testing set, a 2 class classifications have been implemented (Normal, Attack). Weka framework which is a java based open source software consists of a collection of machine learning algorithms for data mining tasks has been used in the testing process. The experimental results show that the proposed approach is very accurate with low false positive rate and high true positive rate and it takes less learning time in comparison with using the full features of the dataset with the same algorithm.

Keywords: information gain (IG), intrusion detection system (IDS), k-means clustering, Weka

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Authors: Atje Setiawan Abdullah, Budi Nurani Ruchjana, I. Gede Nyoman Mindra Jaya, Eddy Hermawan

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Ethnoscience is used to see the culture with a scientific perspective, which may help to understand how people develop various forms of knowledge and belief, initially focusing on the ecology and history of the contributions that have been there. One of the areas studied in ethnoscience is etno-informatics, is the application of informatics in the culture. In this study the science of informatics used is data mining, a process to automatically extract knowledge from large databases, to obtain interesting patterns in order to obtain a knowledge. While the application of culture described by naming database village on the island of Java were obtained from Geographic Indonesia Information Agency (BIG), 2014. The purpose of this study is; first, to classify the naming of the village on the island of Java based on the structure of the word naming the village, including the prefix of the word, syllable contained, and complete word. Second to classify the meaning of naming the village based on specific categories, as well as its role in the community behavioral characteristics. Third, how to visualize the naming of the village to a map location, to see the similarity of naming villages in each province. In this research we have developed two theorems, i.e theorems area as a result of research studies have collected intersection naming villages in each province on the island of Java, and the composition of the wedge theorem sets the provinces in Java is used to view the peculiarities of a location study. The methodology in this study base on the method of Knowledge Discovery in Database (KDD) on data mining, the process includes preprocessing, data mining and post processing. The results showed that the Java community prioritizes merit in running his life, always working hard to achieve a more prosperous life, and love as well as water and environmental sustainment. Naming villages in each location adjacent province has a high degree of similarity, and influence each other. Cultural similarities in the province of Central Java, East Java and West Java-Banten have a high similarity, whereas in Jakarta-Yogyakarta has a low similarity. This research resulted in the cultural character of communities within the meaning of the naming of the village on the island of Java, this character is expected to serve as a guide in the behavior of people's daily life on the island of Java.

Keywords: ethnoscience, ethno-informatics, data mining, clustering, Java island culture

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Authors: Rabia Faridi, Rizwana Maqbool, Umara Sahar Rana, Zaheer Ahmad

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Climate change impacts agriculture, notably in Germany, where spring faba beans predominate. However, improved winter hardiness aligns with milder winters, enabling autumn-sown varieties. Genetic resistance to Ascochyta blight is vital for crop integration. Traditional breeding faces challenges due to complex inheritance. This study assessed 224 homozygous faba bean lines for Ascochyta resistance traits. To achieve h²>70%, 12 replicates were required (realized h²=87%). Genetic variation and strong trait correlations were observed. Five lines outperformed 29H, while three were highly susceptible. A genome-wide association study (GWAS) with 188 inbred lines and 2058 markers, including 17 guide SNP markers, identified 12 markers associated with resistance traits, potentially indicating new resistance genes. One guide marker (Vf-Mt1g014230-001) on chromosome III validated a known QTL. The guided marker approach complemented GWAS, facilitating marker-assisted selection for Ascochyta resistance. The Göttingen Winter Bean Population offers promise for resistance breeding.

Keywords: genome wide association studies, marker assisted breeding, faba bean, ascochyta blight

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Authors: T. Nguyen, H. Rennie, S. Vallance, M. Mackay

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Municipal Associations, also called Unions, Leagues or Federations of municipalities have been established worldwide to represent the interests and needs of urban governments in the face of increasing urban issues. In 2008, the Association of Cities of Vietnam (ACVN) joined the Asian Coalition of Community Action Program (ACCA program) and introduced the community-based upgrading approach to help Vietnamese cities to address urban upgrading issues. While this community-based upgrading approach has only been implemented in a small number of Vietnamese cities and its replication has faced certain challenges, it is worthy to explore insights on how the Association of cities of Vietnam played its role in implementing some reportedly successful projects. This paper responds to this inquiry and presents results extracted from the author’s PhD study that sets out with a general objective to critically examine how social capital dimensions (i.e., bonding, bridging and linking) were formed, mobilized and maintained in a local collective and community-based upgrading process. Methodologically, the study utilized the given general categorization of bonding, bridging and linking capitals to explore and confirm how social capital operated in the real context of a community-based upgrading process, particularly in the context of Vietnam. To do this, the study conducted two exploratory and qualitative case studies of housing projects in Friendship neighbourhood (Vinh city) and Binh Dong neighbourhood (Tan An city). This paper presents the findings of the Friendship neighbourhood case study, focusing on the role of the Vietnamese municipal association in forming, mobilizing and maintaining bonding, bridging and linking capital for a community-based upgrading process. The findings highlight the essential but uncertain role of ACVN - the organization that has a hybrid legitimacy status - in such a process. The results improve our understanding both practically and theoretically. Practically, the results offer insights into the performance of a municipal association operating in a transitioning socio-political context of Vietnam. Theoretically, the paper questions the necessity of categorizing social capital dimensions (i.e., bonding, bridging and linking) by suggesting a holistic approach of looking at social capital for urban governance issues within the Vietnamese context and perhaps elsewhere.

Keywords: bonding capital, bridging capital, municipal association, linking capital, social capital, housing upgrading

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Authors: Minami Ito, Akihiro Iijima

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On March 11, 2011, the Great East Japan Earthquake occurred off the coast of Sanriku, Japan. It is important to build a sustainable society through the reconstruction process rather than simply restoring the infrastructure. To compare the goals of reconstruction plans of quake-stricken municipalities, Japanese language morphological analysis was performed by using text mining techniques. Frequently-used nouns were sorted into four main categories of “life”, “disaster prevention”, “economy”, and “harmony with environment”. Because Soma City is affected by nuclear accident, sentences tagged to “harmony with environment” tended to be frequent compared to the other municipalities. Results from cluster analysis and principle component analysis clearly indicated that the local government reinforces the efforts to reduce risks from radiation exposure as a top priority.

Keywords: eco-friendly reconstruction, harmony with environment, decontamination, nuclear disaster

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Authors: Mais Nijim, Rama Devi Chennuboyina, Waseem Al Aqqad

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Advances in spatial and spectral resolution of satellite images have led to tremendous growth in large image databases. The data we acquire through satellites, radars and sensors consists of important geographical information that can be used for remote sensing applications such as region planning, disaster management. Spatial data classification and object recognition are important tasks for many applications. However, classifying objects and identifying them manually from images is a difficult task. Object recognition is often considered as a classification problem, this task can be performed using machine-learning techniques. Despite of many machine-learning algorithms, the classification is done using supervised classifiers such as Support Vector Machines (SVM) as the area of interest is known. We proposed a classification method, which considers neighboring pixels in a region for feature extraction and it evaluates classifications precisely according to neighboring classes for semantic interpretation of region of interest (ROI). A dataset has been created for training and testing purpose; we generated the attributes by considering pixel intensity values and mean values of reflectance. We demonstrated the benefits of using knowledge discovery and data-mining techniques, which can be on image data for accurate information extraction and classification from high spatial resolution remote sensing imagery.

Keywords: remote sensing, object recognition, classification, data mining, waterbody identification, feature extraction

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Authors: Anshar Ajatasatru

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The decline of coal prices over past years have been significantly increasing the awareness of effective mining operation. A viable step must be undertaken in becoming more cost competitive while striving for best mining practice especially at Melak Coal Mine in East Kalimantan, Indonesia. This paper aims to show how effective dozer push measurement method can be implemented as it is controlled by contract rate on the unit basis of USD ($) per bcm. The method emerges from an idea of daily dozer push activity that continually shifts the overburden until final target design by mine planning. Volume calculation is then performed by calculating volume of each time overburden is removed within determined distance using cut and fill method from a high precision GNSS system which is applied into dozer as a guidance to ensure the optimum result of overburden removal. Accumulation of daily to weekly dozer push volume is found 95 bcm which is multiplied by average sell rate of $ 0,95, thus the amount monthly revenue is $ 90,25. Furthermore, the payment mechanism is then based on push distance and push grade. The push distance interval will determine the rates that vary from $ 0,9 - $ 2,69 per bcm and are influenced by certain push slope grade from -25% until +25%. The amount payable rates for dozer push operation shall be specifically following currency adjustment and is to be added to the monthly overburden volume claim, therefore, the sell rate of overburden volume per bcm may fluctuate depends on the real time exchange rate of Jakarta Interbank Spot Dollar Rate (JISDOR). The result indicates that dozer push measurement can be one of the surface mining alternative since it has enabled to refine method of work, operating cost and productivity improvement apart from exposing risk of low rented equipment performance. In addition, payment mechanism of contract rate by dozer push operation scheduling will ultimately deliver clients by almost 45% cost reduction in the form of low and consistent cost.

Keywords: contract rate, cut-fill method, dozer push, overburden volume

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Authors: Gebeyaw Molla Wondim, Damen Haile Mariam, Wubegzier Mekonnen, Catherine Arsenault

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Introduction: Maternal depression is a common psychological disorder that mostly occurs during pregnancy and after childbirth. It affects approximately one in four women worldwide. There is inconsistent evidence regarding the association between anemia and maternal depression. The objective of this systematic review was to examine the association between anemia and depression during pregnancy. Method: A comprehensive search of articles published before March 8, 2024, was conducted in seven databases such as PubMed, Scopus, Web of Science, PsycINFO, CINAHL, Cochrane Library, and Google Scholar. The Boolean operators “AND” or “OR” and “NOT” were used to connect the MeSH terms and keywords. Rayyan software was used to screen articles for final retrieval, and the PRISMA diagram was used to show the article selection process. Data extraction and risk bias assessment were done by two reviewers independently. JBI critical appraisal tool was used to assess the methodological quality of the retrieved articles. Heterogenicity was assessed through visual inspection of the extracted result, and narrative analysis was used to synthesize the result. Result: A total of 2,413 articles were obtained from seven electronic databases. Among these articles, a total of 2,398 were removed due to duplication (702 articles), by title and abstract selection criteria (1,678 articles), and by full-text review (18 articles). Finally, in this systematic review, 15 articles with a total of 628,781 pregnant women were included: seven articles were cohort studies, two were case-control, and six studies were cross-sectional. All included studies were published between 2013 and 2022. Studies conducted in the United States, South Korea, Finland, and one in South India found no significant association between anemia and maternal depression during pregnancy. On the other hand, studies conducted in Australia, Canada, Finland, Israel, Turkey, Vietnam, Ethiopia, and South India showed a significant association between anemia and depression during pregnancy. Conclusion: The overall finding of the systematic review shows the burden of anemia and antenatal depression is much higher among pregnant women in developing countries. Around three-fourths of the studies show that anemia is positively associated with antenatal depression. Almost all studies conducted in LMICs show anemia positively associated with antenatal depression.

Keywords: pregnant, women, anemia, depression

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Authors: Tae-Uk Yun, Pullip Chung, Kee-Young Kwahk, Hyunchul Ahn

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Fake news is defined as the news articles that are intentionally and verifiably false, and could mislead readers. Spread of fake news may provoke anxiety, chaos, fear, or irrational decisions of the public. Thus, detecting fake news and preventing its spread has become very important issue in our society. However, due to the huge amount of fake news produced every day, it is almost impossible to identify it by a human. Under this context, researchers have tried to develop automated fake news detection using machine learning techniques over the past years. But, there have been no prior studies proposed an automated fake news detection method for Korean news to our best knowledge. In this study, we aim to detect Korean fake news using text mining and machine learning techniques. Our proposed method consists of two steps. In the first step, the news contents to be analyzed is convert to quantified values using various text mining techniques (topic modeling, TF-IDF, and so on). After that, in step 2, classifiers are trained using the values produced in step 1. As the classifiers, machine learning techniques such as logistic regression, backpropagation network, support vector machine, and deep neural network can be applied. To validate the effectiveness of the proposed method, we collected about 200 short Korean news from Seoul National University’s FactCheck. which provides with detailed analysis reports from 20 media outlets and links to source documents for each case. Using this dataset, we will identify which text features are important as well as which classifiers are effective in detecting Korean fake news.

Keywords: fake news detection, Korean news, machine learning, text mining

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Authors: Lassaad Smirani

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In this paper we propose a Neurosymbolic Learning System (NLS) as a channel estimator for Long Term Evolution Advanced (LTE-A) uplink. The proposed system main idea based on Neural Network has modules capable of performing bidirectional information transfer between symbolic module and connectionist module. We demonstrate various strengths of the NLS especially the ability to integrate theoretical knowledge (rules) and experiential knowledge (examples), and to make an initial knowledge base (rules) converted into a connectionist network. Also to use empirical knowledge witch by learning will have the ability to revise the theoretical knowledge and acquire new one and explain it, and finally the ability to improve the performance of symbolic or connectionist systems. Compared with conventional SC-FDMA channel estimation systems, The performance of NLS in terms of complexity and quality is confirmed by theoretical analysis and simulation and shows that this system can make the channel estimation accuracy improved and bit error rate decreased.

Keywords: channel estimation, SC-FDMA, neural network, hybrid system, BER, LTE-A

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Authors: Despina Yiakoumi, Agathe Rouaix

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Laboratory experiments were run to investigate the impact of different design characteristics of the auctions, which have been implemented to procure capacity in the UK’s reformed electricity markets. The experiment studies competition among bidders in procurement multi-unit discrete descending clock auctions under different feedback policies and pricing rules. Theory indicates that feedback policy in combination with the two common pricing rules; last-accepted bid (LAB) and first-rejected bid (FRB), could affect significantly the auction outcome. Two information feedback policies regarding the bidding prices of the participants are considered; with feedback and without feedback. With feedback, after each round participants are informed of the number of items still in the auction and without feedback, after each round participants have no information about the aggregate supply. Under LAB, winning bidders receive the amount of the highest successful bid and under the FRB the winning bidders receive the lowest unsuccessful bid. Based on the theoretical predictions of the alternative auction designs, it was decided to run three treatments. First treatment considers LAB with feedback; second treatment studies LAB without feedback; third treatment investigates FRB without feedback. Theoretical predictions of the game showed that under FRB, the alternative feedback policies are indifferent to the auction outcome. Preliminary results indicate that LAB with feedback and FRB without feedback achieve on average higher clearing prices in comparison to the LAB treatment without feedback. However, the clearing prices under LAB with feedback and FRB without feedback are on average lower compared to the theoretical predictions. Although under LAB without feedback theory predicts the clearing price will drop to the competitive equilibrium, experimental results indicate that participants could still engage in cooperative behavior and drive up the price of the auction. It is showed, both theoretically and experimentally, that the pricing rules and the feedback policy, affect the bidding competitiveness of the auction by providing opportunities to participants to engage in cooperative behavior and exercise market power. LAB without feedback seems to be less vulnerable to market power opportunities compared to the alternative auction designs. This could be an argument for the use of LAB pricing rule in combination with limited feedback in the UK capacity market in an attempt to improve affordability for consumers.

Keywords: descending clock auctions, experiments, feedback policy, market design, multi-unit auctions, pricing rules, procurement auctions

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Authors: Chong Zhang, Guoming Tang, Bin Ge, Jiuyang Tang

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With the fast growing road traffic and increasingly severe traffic congestion, more and more citizens choose to use the public transportation for daily travelling. Meanwhile, the shared bike provides a convenient option for the first and last mile to the public transit. As of 2016, over one thousand cities around the world have deployed the bike-sharing system. The combination of these two transportations have stimulated the development of each other and made significant contribution to the reduction of carbon footprint. A lot of work has been done on mining the riding behaviors in various bike-sharing systems. Most of them, however, treated the bike-sharing system as an isolated system and thus their results provide little reference for the public transit construction and optimization. In this work, we treat the bike-sharing and public transit as a whole and investigate the customers’ bike-and-ride behaviors. Specifically, we develop a spatio-temporal traffic delivery model to study the riding patterns between the two transportation systems and explore the traffic characteristics (e.g., distributions of customer arrival/departure and traffic peak hours) from the time and space dimensions. During the model construction and evaluation, we make use of large open datasets from real-world bike-sharing systems (the CitiBike in New York, GoBike in San Francisco and BIXI in Montreal) along with corresponding public transit information. The developed two-dimension traffic model, as well as the mined bike-and-ride behaviors, can provide great help to the deployment of next-generation intelligent transportation systems.

Keywords: riding pattern mining, bike-sharing system, public transportation, bike-and-ride behavior

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Authors: Reiner-Ace P. Mateo, Vince Paolo F. Obille

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The traditional method of classifying the potential mineral resources requires a significant amount of time and money. In this paper, an alternative way to classify potential mineral resources with GIS application in Surigao del Sur. The three (3) analog map data inputs integrated to GIS are geologic map, topographic map, and land cover/vegetation map. The indicators used in the classification of potential nickel laterite integrated from the analog map data inputs are a geologic indicator, which is the presence of ultramafic rock from the geologic map; slope indicator and the presence of plateau edges from the topographic map; areas of forest land, grassland, and shrublands from the land cover/vegetation map. The potential mineral of the area was classified from low up to very high potential. The produced mineral potential classification map of Surigao del Sur has an estimated 4.63% low nickel laterite potential, 42.15% medium nickel laterite potential, 43.34% high nickel laterite potential, and 9.88% very high nickel laterite from its ultramafic terrains. For the validation of the produced map, it was compared with known occurrences of nickel laterite in the area using a nickel mining tenement map from the area with the application of remote sensing. Three (3) prominent nickel mining companies were delineated in the study area. The generated potential classification map of nickel-laterite in Surigao Del Sur may be of aid to the mining companies which are currently in the exploration phase in the study area. Also, the currently operating nickel mines in the study area can help to validate the reliability of the mineral classification map produced.

Keywords: mineral potential classification, nickel laterites, GIS, remote sensing, Surigao del Sur

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Authors: Nael Y. Zabel, Maged E. Georgy, Moheeb E. Ibrahim

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A knowledge-based expert system with the acronym RASPE is developed as an application tool to help decision makers in construction companies make informed decisions about managing risks in pipeline construction projects. Choosing to use expert systems from all available artificial intelligence techniques is due to the fact that an expert system is more suited to representing a domain’s knowledge and the reasoning behind domain-specific decisions. The knowledge-based expert system can capture the knowledge in the form of conditional rules which represent various project scenarios and potential risk mitigation/response actions. The built knowledge in RASPE is utilized through the underlying inference engine that allows the firing of rules relevant to a project scenario into consideration. This paper provides an overview of the knowledge acquisition process and goes about describing the knowledge structure which is divided up into four major modules. The paper shows one module in full detail for illustration purposes and concludes with insightful remarks.

Keywords: expert system, knowledge management, pipeline projects, risk mismanagement

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Authors: J. Vinay , Kusumbati Besra, Niharika Pattnaik, Shivaram Prasad Singh, Manjusha Dixit

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Gallbladder cancer (GBC) is rare but highly malignant cancer; its prevalence is more in certain geographical regions and ethnic groups, which include the Northern and Eastern states of India. Previous studies in India have reported genetic predisposition as one of the risk factors in GBC pathogenesis. Although the matrix metalloproteinase-14 (MMP14) is a well-known modulator of the tumor microenvironment and tumorigenesis and TCGA data also suggests its upregulation yet, its role in the genetic predisposition for GBC is completely unknown. We elucidated the role of MMP14 promoter variants as genetic risk factors and their implications in expression modulation. We screened MMP14 promoter variants association with GBC using Sanger’s sequencing in approximately 300 GBC and 300 control subjects and 26 GBC tissue samples of Indian ethnicity. The immunohistochemistry was used to check the MMP14 protein expression in GBC tissue samples. The role of promoter variants on expression levels was elucidated using a luciferase reporter assay. The variants rs1004030 (p-value = 0.0001) and rs1003349 (p-value = 0.0008) were significantly associated with gallbladder cancer. The luciferase assay in two different cell lines, HEK-293 (p = 0.0006) and TGBC1TKB (p = 0.0036) showed a significant increase in relative luciferase activity in the presence of risk alleles for both the single nucleotide polymorphisms (SNPs). Similarly, genotype-phenotype correlation in patients samples confirmed that the presence of risk alleles at rs1004030 and rs1003349 increased MMP14 expression. Overall, this study unravels the genetic association of MMP14 promoter variants with gallbladder cancer, which may contribute to pathogenesis by increasing its expression.

Keywords: gallbladder cancer, matrix metalloproteinase-14, single nucleotide polymorphism, case control study, genetic association study

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Authors: Elaheh Talebi, Fariba Yavari, Lucy Philip, Lesley Town

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The mining industry generates vast amounts of data, necessitating robust data management systems and advanced analytics tools to achieve better decision-making processes in the development of mining production and maintaining safety. This paper highlights the advantages of Power BI, a powerful intelligence tool, over traditional Excel-based approaches for effectively managing and harnessing mining data. Power BI enables professionals to connect and integrate multiple data sources, ensuring real-time access to up-to-date information. Its interactive visualizations and dashboards offer an intuitive interface for exploring and analyzing geotechnical data. Advanced analytics is a collection of data analysis techniques to improve decision-making. Leveraging some of the most complex techniques in data science, advanced analytics is used to do everything from detecting data errors and ensuring data accuracy to directing the development of future project phases. However, while Power BI is a robust tool, specific visualizations required by geotechnical engineers may have limitations. This paper studies the capability to use Python or R programming within the Power BI dashboard to enable advanced analytics, additional functionalities, and customized visualizations. This dashboard provides comprehensive tools for analyzing and visualizing key geotechnical data metrics, including spatial representation on maps, field and lab test results, and subsurface rock and soil characteristics. Advanced visualizations like borehole logs and Stereonet were implemented using Python programming within the Power BI dashboard, enhancing the understanding and communication of geotechnical information. Moreover, the dashboard's flexibility allows for the incorporation of additional data and visualizations based on the project scope and available data, such as pit design, rock fall analyses, rock mass characterization, and drone data. This further enhances the dashboard's usefulness in future projects, including operation, development, closure, and rehabilitation phases. Additionally, this helps in minimizing the necessity of utilizing multiple software programs in projects. This geotechnical dashboard in Power BI serves as a user-friendly solution for analyzing, visualizing, and communicating both new and historical geotechnical data, aiding in informed decision-making and efficient project management throughout various project stages. Its ability to generate dynamic reports and share them with clients in a collaborative manner further enhances decision-making processes and facilitates effective communication within geotechnical projects in the mining industry.

Keywords: geotechnical data analysis, power BI, visualization, decision-making, mining industry

Procedia PDF Downloads 92