Search results for: association rule mining

Authors: Wael Bakhit, Salma Bakhit

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This paper employs a quarterly time series to determine the timing of structural breaks for interest rates in USA over the last 60 years. The Chow test is used for investigating the non-stationary, where the date of the potential break is assumed to be known. Moreover, an empirical examination of the financial sector was made to check if it is positively related to deviations from an assumed interest rate as given in a standard Taylor rule. The empirical analysis is strengthened by analysing the rule from a historical perspective and a look at the effect of setting the interest rate by the central bank on financial imbalances. The empirical evidence indicates that deviation in monetary policy has a potential causal factor in the build-up of financial imbalances and the subsequent crisis where macro prudential intervention could have beneficial effect. Thus, our findings tend to support the view which states that the probable existence of central banks has been a source of global financial crisis since the past decade.

Keywords: Taylor rule, financial imbalances, central banks, econometrics

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Authors: Mohammad Aljuhani, Yasamina Aljuhani

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The Mining Engineering Department at College of Engineering in NBU is under establishment. It is essential to establish such department in NBU. This is because, it is the only university in the region. Moreover, the mining industry is very active in the northern borders region. However, there is no mining engineering department in KSA except one in King Abdulziz University, which is 1400 km from the mining industry in the northern borders. As a result, department graduates from KAU find difficulties to get suitable jobs in their specialization in spite of their few numbers graduated per year and the presence of many jobs vacancies at the local mining sector. Therefore, the objectives of this research are to identify, measure and analyze the above mentioned problem from educational point of view. One more objective is to add a contribution towards solving such vital, society affecting problem. For achieving the first task of the research, that is problem size identification and analyses, a questionnaire was designed. The questionnaire was directed towards experienced engineers, in the mining and related industries, including the ministry of petroleum and minerals, Saudi Geological Survey, and Ma’aden Company as being prospective employers for the mining sector. The questionnaire target was to evaluate the Saudi mining engineers from an industrial point of view and to detect the main reasons behind their failure to find jobs. In addition, the study focuses in the demand of mining engineers in the northern borders region. Moreover, the study plan of the suggested department is designed based on the requirements of the mining industry. The feedback received from the industry reflected major educational shortcomings. In order to overcome the revealed defects, the second objective of the research was achieved where a suggested study plan “curriculum” has been prepared to take into consideration all the points of weakness so as to improve the graduates’ quality to fit the local mining work market.

Keywords: mining engineering, labor market, qualifications, curriculum, mining industry, mining engineers

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Authors: Davidson E. Egirani, Nanfe R. Poyi, Napoleon Wessey

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This paper would report the environmental challenges faced by stakeholders in the development and management of mineral resources in Mindanao mining region of the Philippines. The paper would proffer solutions via the development and management of integrated mineral resource framework. This is by interfacing the views of government, operating mining companies and the mining host communities. The project methods involved the desktop review of existing local, regional, national environmental and mining legislation. This was followed up with visits to mining sites and discussions were held with stakeholders in the mineral sector. The findings from a 2-year investigation would reveal lack of information, education, and communication campaign by stakeholders on environmental, health, political, and social issues in the mining industry. Small-scale miners lack the professional muscles for a balance shift of emphasis to sustainable and responsible mining to avoid environmental degradation and human health effect. Therefore, there is a need to balance ecological requirements, sustainability of the environment and development of mineral resources. This paper would provide an environmentally friendly mineral resource development framework.

Keywords: ecological requirements, environmental degradation, human health, mining legislation, responsible mining

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Authors: J. Suneetha, Vijayalaxmi

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Sequential Pattern Mining involves applying data mining methods to large data repositories to extract usage patterns. Sequential pattern mining methodologies used to analyze the data and identify patterns. The patterns have been used to implement efficient systems can recommend on previously observed patterns, in making predictions, improve usability of systems, detecting events, and in general help in making strategic product decisions. In this paper, identified performance of approximate sequential pattern mining defines as identifying patterns approximately shared with many sequences. Approximate sequential patterns can effectively summarize and represent the databases by identifying the underlying trends in the data. Conducting an extensive and systematic performance over synthetic and real data. The results demonstrate that ApproxMAP effective and scalable in mining large sequences databases with long patterns.

Keywords: multiple data, performance analysis, sequential pattern, sequence database scalability

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Authors: Filiz Ersoz, Taner Ersoz, Erkin Guler

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This paper addresses the issues and technique for textile industry using data mining techniques. Data mining has been applied to the stitching of garments products that were obtained from a textile company. Data mining techniques were applied to the data obtained from the CHAID algorithm, CART algorithm, Regression Analysis and, Artificial Neural Networks. Classification technique based analyses were used while data mining and decision model about the production per person and variables affecting about production were found by this method. In the study, the results show that as the daily working time increases, the production per person also decreases. In addition, the relationship between total daily working and production per person shows a negative result and the production per person show the highest and negative relationship.

Keywords: data mining, textile production, decision trees, classification

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Authors: Hosein Rahmati

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The Fatimid government was one of the powerful Shiite governments that was formed in 297 AH in the Islamic Maghreb based on Ismaili ideas and played an important role in promoting the culture and civilization of the Islamic world. Ismaili is one of the Shiite sects that has its own beliefs and teachings. This research seeks to find out which of the Ismaili beliefs and teachings were considered by the Fatimid political government and which the Fatimid government paid serious attention to highlighting. The present study, based on library sources and descriptive-analytical method, has concluded that the Ismaili doctrinal foundations, especially the doctrine of Imamate, are essential elements in the formation and continuation of the Fatimid rule. Their goals were approaching.

Keywords: Fatimid rule, The Ismaili, The Islamic Maghreb, Imamate

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Authors: Fahad Hanash Alzahrani

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This paper describes some recent advances in a quickly developing area of data storing and processing based on Data Warehouses and Data Mining techniques, which are associated with software, hardware, data mining algorithms and visualisation techniques having common features for any specific problems and tasks of their implementation.

Keywords: data warehouse, data mining, knowledge discovery in databases, on-line analytical processing

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Authors: Najiba Ouled Omar, Azza Harbaoui, Henda Ben Ghezala

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Current research practices sentiment analysis with a focus on social networks, DEfi Fouille de Texte (DEFT) (Text Mining Challenge) evaluation campaign focuses on opinion mining and sentiment analysis on social networks, especially social network Twitter. It aims to confront the systems produced by several teams from public and private research laboratories. DEFT offers participants the opportunity to work on regularly renewed themes and proposes to work on opinion mining in several editions. The purpose of this article is to scrutinize and analyze the works relating to opinions mining and sentiment analysis in the Twitter social network realized by DEFT. It examines the tasks proposed by the organizers of the challenge and the methods used by the participants.

Keywords: opinion mining, sentiment analysis, emotion, polarity, annotation, OSEE, figurative language, DEFT, Twitter, Tweet

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Authors: Iliya Musa Adamu

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This paper seeks to develop an expert system that would troubleshoot computer network and evaluate the network system performance so as to reduce the workload on technicians and increase the efficiency and effectiveness of solutions proffered to computer network problems. The platform of the system was developed using ASP.NET, whereas the codes are implemented in Visual Basic and integrated with SQL Server 2005. The knowledge base was represented using production rule, whereas the searching method that was used in developing the network troubleshooting expert system is the forward-chaining-rule-based-system. This software tool offers the advantage of providing an immediate solution to most computer network problems encountered by computer users.

Keywords: expert system, forward chaining rule based system, network, troubleshooting

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Authors: Rebeca Ramirez Acosta, Sebastian Lenhoff

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Decision makers worldwide need to determine if the implementation of a new market mechanism will contribute to the sustainability and resilience of the power system. Due to smart grid technologies, new products in the distribution and transmission system can be traded; however, the impact of changing a market rule will differ between several regions. To test systematically those impacts, a market categorization has been compiled and organized in a smart grid market testing toolbox. This toolbox maps all actual energy products and sets the basis for running a co-simulation test with the new rule to be implemented. It will help to measure the impact of the new rule, based on the sustainable and resilience indicators.

Keywords: co-simulation, electricity market, smart grid market, market testing

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Authors: Hema Bhardwaj, D. Srinivasa Rao

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Technology for analysing, processing, and extracting meaningful data from enormous and complicated datasets can be termed as "big data." The technique of big data mining and big data analysis is extremely helpful for business movements such as making decisions, building organisational plans, researching the market efficiently, improving sales, etc., because typical management tools cannot handle such complicated datasets. Special computational and statistical issues, such as measurement errors, noise accumulation, spurious correlation, and storage and scalability limitations, are brought on by big data. These unique problems call for new computational and statistical paradigms. This research paper offers an overview of the literature on big data mining, its process, along with problems and difficulties, with a focus on the unique characteristics of big data. Organizations have several difficulties when undertaking data mining, which has an impact on their decision-making. Every day, terabytes of data are produced, yet only around 1% of that data is really analyzed. The idea of the mining and analysis of data and knowledge discovery techniques that have recently been created with practical application systems is presented in this study. This article's conclusion also includes a list of issues and difficulties for further research in the area. The report discusses the management's main big data and data mining challenges.

Keywords: big data, data mining, data analysis, knowledge discovery techniques, data mining challenges

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Authors: Zhidong Zhang, Zhi-Chao Zhang

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This study investigated the structural validity of externalizing issues of Achenbach System of Empirically Based Assessment (ASEBA) via a Chinese sample. The externalizing problems consist of two sub-problems: rule-breaking behavior and aggressive behavior. The rule-breaking behavior consists of 17 items, and aggressive behavior consists of 18 items. The factor analysis model was used to examine the structure validity. For the rule breaking behavior, at the first step, the most items weighted with component 2. After the rotation, there was a clear weight on both component 1 and 2. For the aggressive behavior, at the first step, there was no clear picture about the components. After the rotation, two clusters of items were closer to component 1 and 2 respectively. It seemed that both rule breaking behavior issue and aggressive behavior issue suggested two components. Further studies should be done to examine both samples and structures of externalizing problems.

Keywords: confirmatory analysis, externalizing issue, structural validity, varimax rotations

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Authors: Harpreet Singh

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Finding relevant information on the World Wide Web is becoming highly challenging day by day. Web usage mining is used for the extraction of relevant and useful knowledge, such as user behaviour patterns, from web access log records. Web access log records all the requests for individual files that the users have requested from the website. Web usage mining is important for Customer Relationship Management (CRM), as it can ensure customer satisfaction as far as the interaction between the customer and the organization is concerned. Web usage mining is helpful in improving website structure or design as per the user’s requirement by analyzing the access log file of a website through a log analyzer tool. The focus of this paper is to enhance the accessibility and usability of a guitar selling web site by analyzing their access log through Deep Log Analyzer tool. The results show that the maximum number of users is from the United States and that they use Opera 9.8 web browser and the Windows XP operating system.

Keywords: web usage mining, web mining, log file, data mining, deep log analyzer

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Authors: Ebrahim Taherzadeh, Helmi Z. M. Shafri, Kaveh Shahi

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One of the most important tasks in urban area remote sensing is detection of impervious surface (IS), such as building roof and roads. However, detection of IS in heterogeneous areas still remains as one of the most challenging works. In this study, detection of concrete roof using an object-oriented approach was proposed. A new rule-based classification was developed to detect concrete roof tile. The proposed rule-based classification was applied to WorldView-2 image. Results showed that the proposed rule has good potential to predict concrete roof material from WorldView-2 images with 85% accuracy.

Keywords: object-based, roof material, concrete tile, WorldView-2

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Authors: Tetsuro Saeki, Yuichi Kato, Shoutarou Mizuno

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STRIM (Statistical Test Rule Induction Method) has been proposed as a method to effectively induct if-then rules from the decision table which is considered as a sample set obtained from the population of interest. Its usefulness has been confirmed by simulation experiments specifying rules in advance, and by comparison with conventional methods. However, scope for future development remains before STRIM can be applied to the analysis of real-world data sets. The first requirement is to determine the size of the dataset needed for inducting true rules, since finding statistically significant rules is the core of the method. The second is to examine the capacity of rule induction from datasets with contaminated attribute values created by missing data and noise, since real-world datasets usually contain such contaminated data. This paper examines the first problem theoretically, in connection with the rule length. The second problem is then examined in a simulation experiment, utilizing the critical size of dataset derived from the first step. The experimental results show that STRIM is highly robust in the analysis of datasets with contaminated attribute values, and hence is applicable to realworld data.

Keywords: rule induction, decision table, missing data, noise

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Authors: Taşkın Deniz Yıldız, Mustafa Topaloğlu, Orhan Kural

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The right to operate a fairly long periods of prior periods and after the 3213 Mining Law has been observed to be shortened in Turkey. Permit the realization of business activities (or concession) requested the purchase of the mine operated "found mine" position, as well as the financial and technical capability to have the owner of the right to operate the mines as well as the principle of equality is important in terms of assessing the best way be. In particular, in this context, license fields "negligence" (downsizing) have noted that the current arrangement for all periods. However, in the period after 3213 Mining Act and a permit to operate more effectively within the framework of implementation of negligence is laid down.

Keywords: mining legislation, operation, permit, Turkey

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Authors: Fuad Ali Mohammed Al-Yarimi

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Many algorithms have been proposed to provide privacy preserving in data mining. These protocols are based on two main approaches named as: the perturbation approach and the Cryptographic approach. The first one is based on perturbation of the valuable information while the second one uses cryptographic techniques. The perturbation approach is much more efficient with reduced accuracy while the cryptographic approach can provide solutions with perfect accuracy. However, the cryptographic approach is a much slower method and requires considerable computation and communication overhead. In this paper, a new scalable protocol is proposed which combines the advantages of the perturbation and distortion along with cryptographic approach to perform privacy preserving in distributed frequent itemset mining on horizontally distributed data. Both the privacy and performance characteristics of the proposed protocol are studied empirically.

Keywords: anonymity data, data mining, distributed frequent itemset mining, gaussian perturbation, perturbation approach, privacy preserving data mining

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Authors: Srushti Patil, Preethi Baligar, Gopalkrishna Joshi, Gururaj N. Bhadri

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In designing learning environments, the instructional strategies can be tailored to suit the learning style of an individual to ensure effective learning. In this study, the information shared on social media like Facebook is being used to predict learning style of a learner. Previous research studies have shown that Facebook data can be used to predict user personality. Users with a particular personality exhibit an inherent pattern in their digital footprint on Facebook. The proposed work aims to correlate the user's’ personality, predicted from Facebook data to the learning styles, predicted through questionnaires. For Millennial learners, Facebook has become a primary means for information sharing and interaction with peers. Thus, it can serve as a rich bed for research and direct the design of learning environments. The authors have conducted this study in an undergraduate freshman engineering course. Data from 320 freshmen Facebook users was collected. The same users also participated in the learning style and personality prediction survey. The Kolb’s Learning style questionnaires and Big 5 personality Inventory were adopted for the survey. The users have agreed to participate in this research and have signed individual consent forms. A specific page was created on Facebook to collect user data like personal details, status updates, comments, demographic characteristics and egocentric network parameters. This data was captured by an application created using Python program. The data captured from Facebook was subjected to text analysis process using the Linguistic Inquiry and Word Count dictionary. An analysis of the data collected from the questionnaires performed reveals individual student personality and learning style. The results obtained from analysis of Facebook, learning style and personality data were then fed into an automatic classifier that was trained by using the data mining techniques like Rule-based classifiers and Decision trees. This helps to predict the user personality and learning styles by analysing the common patterns. Rule-based classifiers applied for text analysis helps to categorize Facebook data into positive, negative and neutral. There were totally two models trained, one to predict the personality from Facebook data; another one to predict the learning styles from the personalities. The results show that the classifier model has high accuracy which makes the proposed method to be a reliable one for predicting the user personality and learning styles.

Keywords: educational data mining, Facebook, learning styles, personality traits

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Authors: Burcu Oralhan, Zeki Oralhan, Nilsun Sariyer, Kumru Uyar

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Data mining has been becoming more and more important and a wide range of applications in recent years. Data mining is the process of find hidden and unknown patterns in big data. One of the applied fields of data mining is Customer Relationship Management. Understanding the relationships between products and customers is crucial for every business. Customer Relationship Management is an approach to focus on customer relationship development, retention and increase on customer satisfaction. In this study, we made an application of a data mining methods in telecommunication customer relationship management side. This study aims to determine the customers profile who likely to leave the system, develop marketing strategies, and customized campaigns for customers. Data are clustered by applying classification techniques for used to determine the churners. As a result of this study, we will obtain knowledge from international telecommunication industry. We will contribute to the understanding and development of this subject in Customer Relationship Management.

Keywords: customer churn analysis, customer relationship management, data mining, telecommunication industry

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Authors: Diriba Dereje

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Background: Cardiac and renal disease are the most prevalent chronic non-communicable diseases (CNCD) affecting the community in a significant manner. The best and recommended method in halting CNCD is by working on prevention as early as possible. This is only possible if early surrogate markers are identified. As part of the stated solution, this study will identify an association between microalbuminuria (an early surrogate marker of renal and cardiac disease) and lung function test among adult in the community. Objective: The main aim of this study was to assess an association between microalbuminuria (an early surrogate marker of renal and cardiac disease) and lung function test among adult in the community. Methodology: Community based cross sectional study was conducted among 384 adult in Jimma town. A systematic sampling technique was used in selecting participants to the study. In searching for the possible association, binary and multivariate logistic regression and t-test was conducted. Finally, the association between microalbuminuria and lung function test was well stated in the form of figures and written description. Result and Conclusion: A significant association was found between microalbuminuria and different lung function test parameters.

Keywords: microalbuminuria, lung function, association, test

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Authors: Feng Zhang

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Kashin-Beck disease (KBD) is a chronic osteochondropathy. The mechanism of hand growth and development failure of KBD remains elusive now. In this study, we conducted a two-stage genome-wide association study (GWAS) of palmar length-width ratio (LWR) of KBD, totally involving 493 Chinese Han KBD patients. Affymetrix Genome Wide Human SNP Array 6.0 was applied for SNP genotyping. Association analysis was conducted by PLINK software. Imputation analysis was performed by IMPUTE against the reference panel of the 1000 genome project. In the GWAS, the most significant association was observed between palmar LWR and rs2071358 of COL2A1 gene (P value = 4.68×10-8). Imputation analysis identified 3 SNPs surrounding rs2071358 with significant or suggestive association signals. Replication study observed additional significant association signals at both rs2071358 (P value = 0.017) and rs4760608 (P value = 0.002) of COL2A1 gene after Bonferroni correction. Our results suggest that COL2A1 gene was a novel susceptibility gene involved in the growth and development failure of hand of KBD.

Keywords: Kashin-Beck disease, genome-wide association study, COL2A1, hand

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Authors: Rokhmatul Insani, Hira Laksmiwati Soemitro

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Business Intelligence is a methodology that exploits the data to produce information and knowledge systematically, business intelligence can support the decision-making process. Some methods in business intelligence are data warehouse and data mining. A data warehouse can store historical data from transactional data. For data modelling in data warehouse, we apply dimensional modelling by Kimball. While data mining is used to extracting patterns from the data and get insight from the data. Data mining has many techniques, one of which is segmentation. For profiling of telecommunication customer, we use customer segmentation according to customer’s usage of services, customer invoice and customer payment. Customers can be grouped according to their characteristics and can be identified the profitable customers. We apply K-Means Clustering Algorithm for segmentation. The input variable for that algorithm we use RFM (Recency, Frequency and Monetary) model. All process in data mining, we use tools IBM SPSS modeller.

Keywords: business intelligence, customer segmentation, data warehouse, data mining

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Authors: A. Argiri, A. Molla, Tzouvalekas, E. Skoufogianni, N. Danalatos

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The release of heavy metals into the environment has increased over the last years. In this study, 25 soil samples (0-15 cm) from the fields near the mining area in Drama region were selected. The samples were analyzed in the laboratory for their physicochemical properties and for seven “pseudo-total’’ heavy metals content, namely Pb, Zn, Cd, Cr, Cu, Ni, and Mn. The total metal concentrations (Pb, Zn, Cd, Cr, Cu, Ni and Mn) in digests were determined by using the atomic absorption spectrophotometer. According to the results, the mean concentration of the listed heavy metals in 25 soil samples are Cd 1.1 mg/kg, Cr 15 mg/kg, Cu 21.7 mg/kg, Ni 30.1 mg/kg, Pd 50.8 mg/kg, Zn 99.5 mg/kg and Mn 815.3 mg/kg. The results show that the heavy metals remain in the soil even if the mining closed many years ago.

Keywords: Greece, heavy metals, mining, pollution

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Authors: Swapan Maiti, Dipanwita Roy Chowdhury

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Nonlinear functions are essential in different cryptoprimitives as they play an important role on the security of the cipher designs. Rule 30 was identified as a powerful nonlinear function for cryptographic applications. However, an attack (MS attack) was mounted against Rule 30 Cellular Automata (CA). Nonlinear rules as well as maximum period CA increase randomness property. In this work, nonlinear rules of maximum period nonlinear hybrid CA (M-NHCA) are studied and it is shown to be a better crypto-primitive than Rule 30 CA. It has also been analysed that the M-NHCA with single nonlinearity injection proposed in the literature is vulnerable against MS attack, whereas M-NHCA with multiple nonlinearity injections provide maximum length cycle as well as better cryptographic primitives and they are also secure against MS attack.

Keywords: cellular automata, maximum period nonlinear CA, Meier and Staffelbach attack, nonlinear functions

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Authors: Muhammet Dursun Kaya, Hasan Asil

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One of the most important factors of research and development is the deep insight into the evolutions of scientific development. The state-of-the-art tools and instruments can considerably assist the researchers, and many of the world organizations have become aware of the advantages of data mining for the acquisition of the knowledge required for the unstructured data. This paper was an attempt to review the articles on the information technology published in the past five years with the aid of data mining. A clustering approach was used to study these articles, and the research results revealed that three topics, namely health, innovation, and information systems, have captured the special attention of the researchers.

Keywords: information technology, data mining, scientific development, clustering

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Authors: Kate N. Okeke

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The ever-growing needs of man requiring satisfaction have pushed him strongly towards industrialization which has and is still leaving environmental degradation and its attendant negative impacts in its wake. It is, therefore, not surprising that the enjoyment of fundamental rights like food supply, security of lives and property, freedom of worship, health and education have been drastically affected by such degradation. In recognition of the imperative need to protect the environment and human rights, many global instruments and constitutions have recognized the right to a healthy and sustainable environment. Some environmental advocates and quite a number of literatures on the subject matter call for the recognition of environmental rights via rule of law as a vital means of achieving positive outcomes on the subject matter. However, although there are numerous countries with constitutional environmental provisions, most of them such as Nigeria, have shown poor environmental performance. A notable problem is the fact that the constitution which recognizes environmental rights appears in its other provisions to contradict its provisions by making enforceability of the environmental rights unattainable. While adopting a descriptive, analytical, comparative and explanatory study design in reviewing a successful positive environmental outcome via the rule of law, this article argues that rule of law on a balance of scale, weighs more than just environmental rights recognition and therefore should receive more attention by environmental lawyers and advocates. This is because with rule of law, members of a society are sure of getting the most out of the environmental rights existing in their legal system. Members of Niger-Delta communities of Nigeria will benefit from the environmental rights existing in Nigeria. They are exposed to environmental degradation and pollution with effects such as acidic rainfall, pollution of farmlands and clean water sources. These and many more are consequences of oil and gas exploration. It will also pave way for solving the violence between cattle herdsmen and farmers in the Middle Belt and other regions of Nigeria. Their clashes are over natural resource control. Having seen that environmental rule of law is vital to sustainable development, this paper aims to contribute to discussions on how best the vehicle of rule law can be driven towards achieving positive environmental outcomes. This will be in reliance on other enforceable provisions in the Nigerian Constitution. Other domesticated international instruments will also be considered to attain sustainable environment and development.

Keywords: environment, rule of law, constitution, sustainability

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Authors: S. Kittipongvises, A. Dubsok

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The mineral and mining industry is necessary for countries to have an adequate and reliable supply of materials to meet their socio-economic development. Despite its importance, the environmental impacts from mineral exploration are hugely significant. This study aimed to investigate and quantify the amount of GHGs emissions emitted from both electricity and diesel vehicle fuel consumption in basalt mining in Thailand. Plant A, located in the northeastern region of Thailand, was selected as a case study. Results indicated that total GHGs emissions from basalt mining and operation (Plant A) were approximately 2,501,086 kgCO₂e and 1,997,412 kgCO₂e in 2014 and 2015, respectively. The estimated carbon intensity ranged between 1.824 kgCO₂e to 2.284 kgCO₂e per ton of rock product. Scope 1 (direct emissions) was the dominant driver of its total GHGs compared to scope 2 (indirect emissions). As such, transport related combustion of diesel fuels generated the highest GHGs emission (65%) compared to emissions from purchased electricity (35%). Some of the potential implications for mining entities were also presented.

Keywords: basalt mining, diesel fuel, electricity, GHGs emissions, Thailand

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Authors: Md Tareq Ferdous Khan, Shrabanti Mazumder, MB Rao

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Background: Substance use during pregnancy is a longstanding public health problem that results in severe consequences for pregnant women and fetuses. Methods: Eight (2011-2018) datasets on pregnant women’s admissions are extracted from TEDS-A. Distributions of sociodemographic, substance abuse behaviors, and clinical characteristics are constructed and compared over the years for trends by the Cochran-Armitage test. Market basket analysis is used in mining the association among polysubstance abuse. Results: Over the years, pregnant woman admissions as the percentage of total and female admissions remain stable, where total annual admissions range from 1.54 to about 2 million with the female share of 33.30% to 35.61%. Pregnant women aged 21-29, 12 or more years of education, white race, unemployed, holding independent living status are among the most vulnerable. Concerns prevail on a significant number of polysubstance users, young age at first use, frequency of daily users, and records of prior admissions (60%). Trends of abused primary substances show a significant rise in heroin (66%) and methamphetamine (46%) over the years, although the latest year shows a considerable downturn. On the other hand, significant decreasing patterns are evident for alcohol (43%), marijuana or hashish (24%), cocaine or crack (23%), other opiates or synthetics (36%), and benzodiazepines (29%). Basket analysis reveals some patterns of co-occurrence of substances consistent over the years. Conclusions: This comprehensive study can work as a reference to identify the most vulnerable groups based on their characteristics and deal with the most hazardous substances from their evidence of co-occurrence.

Keywords: basket analysis, pregnant women, substance abuse, trend analysis

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Authors: Abdulaziz Alakeel, Roaa Alamri, Abdulrahman Alomair, Mohammed Fouda

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Introduction: Ibrutinib is a selective, potent, and irreversible small-molecule inhibitor of Bruton's tyrosine kinase (BTK). It forms a covalent bond with a cysteine residue (CYS-481) at the active site of Btk, leading to inhibition of Btk enzymatic activity. The drug is indicated to treat certain type of cancers such as mantle cell lymphoma (MCL), chronic lymphocytic leukaemia and Waldenström's macroglobulinaemia (WM). Cardiac failure is a condition referred to inability of heart muscle to pump adequate blood to human body organs. There are multiple types of cardiac failure including left and right-sided heart failure, systolic and diastolic heart failures. The aim of this review is to evaluate the risk of cardiac failure associated with the use of ibrutinib and to suggest regulatory recommendations if required. Methodology: Signal Detection team at the National Pharmacovigilance Center (NPC) of Saudi Food and Drug Authority (SFDA) performed a comprehensive signal review using its national database as well as the World Health Organization (WHO) database (VigiBase), to retrieve related information for assessing the causality between cardiac failure and ibrutinib. We used the WHO- Uppsala Monitoring Centre (UMC) criteria as standard for assessing the causality of the reported cases. Results: Case Review: The number of resulted cases for the combined drug/adverse drug reaction are 212 global ICSRs as of July 2020. The reviewers have selected and assessed the causality for the well-documented ICSRs with completeness scores of 0.9 and above (35 ICSRs); the value 1.0 presents the highest score for best-written ICSRs. Among the reviewed cases, more than half of them provides supportive association (four probable and 15 possible cases). Data Mining: The disproportionality of the observed and the expected reporting rate for drug/adverse drug reaction pair is estimated using information component (IC), a tool developed by WHO-UMC to measure the reporting ratio. Positive IC reflects higher statistical association while negative values indicates less statistical association, considering the null value equal to zero. The results of (IC=1.5) revealed a positive statistical association for the drug/ADR combination, which means “Ibrutinib” with “Cardiac Failure” have been observed more than expected when compared to other medications available in WHO database. Conclusion: Health regulators and health care professionals must be aware for the potential risk of cardiac failure associated with ibrutinib and the monitoring of any signs or symptoms in treated patients is essential. The weighted cumulative evidences identified from causality assessment of the reported cases and data mining are sufficient to support a causal association between ibrutinib and cardiac failure.

Keywords: cardiac failure, drug safety, ibrutinib, pharmacovigilance, signal detection

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Authors: Chinedu Peter, Dashrath Singh

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Membrane computing is a computability model which abstracts its structures and functions from the biological cell. The main ingredient of membrane computing is the notion of a membrane structure, which consists of several cell-like membranes recurrently placed inside a unique skin membrane. The emergence of several variants of membrane computing gives rise to the notion of a P system. The paper presents a variant of P systems for arithmetic operations on non-negative integers based on the weak priorities for rule application. Consequently, we obtain deterministic P systems. Two membranes suffice. There are at most four objects for multiplication and five objects for division throughout the computation processes. The model is simple and has a potential for possible extension to non-negative integers and real numbers in general.

Keywords: P system, binary operation, determinism, weak rule priority

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