Search results for: causal discovery

Authors: Rhadinia Tayag-Relanes, Felina C. Young

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This study was conducted to analyze the noodle production process at Yan Hu Food Manufacturing for the basis of production improvement. The study utilized the PDCA approach and record review in the gathering of data for the calendar year 2019 from August to October data of the noodle products miki, canton, and misua. Causal-comparative research was used in this study; it attempts to establish cause-effect relationships among the variables such as descriptive statistics and correlation, both were used to compute the data gathered. The study found that miki, canton, and misua production has different cycle time sets for each production and has different production outputs in every set of its production process and a different number of wastages. The company has not yet established its allowable rejection rate/ wastage; instead, this paper used a 1% wastage limit. The researcher recommended the following: machines used for each process of the noodle product must be consistently maintained and monitored; an assessment of all the production operators by checking their performance statistically based on the output and the machine performance; a root cause analysis for finding the solution must be conducted; and an improvement on the recording system of the input and output of the production process of noodle product should be established to eliminate the poor recording of data.

Keywords: continuous improvement, process, operations, PDCA

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Authors: Umesh Kumar Singh, Abhishek Raghuvanshi, Suyash Kumar Singh

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As IoT networks gain popularity, they are more susceptible to security breaches. As a result, it is crucial to analyze the IoT platform as a whole from the standpoint of core security concepts. The Internet of Things relies heavily on wireless networks, which are well-known for being susceptible to a wide variety of attacks. This article provides an analysis of many techniques that may be used to identify vulnerabilities in the software and hardware associated with the Internet of Things (IoT). In the current investigation, an experimental setup is built with the assistance of server computers, client PCs, Internet of Things development boards, sensors, and cloud subscriptions. Through the use of network host scanning methods and vulnerability scanning tools, raw data relating to IoT-based applications and devices may be collected. Shodan is a tool that is used for scanning, and it is also used for effective vulnerability discovery in IoT devices as well as penetration testing. This article presents an efficient mitigation plan for encountering vulnerabilities in the Internet of Things.

Keywords: internet of things, security, privacy, vulnerability identification, mitigation plan

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Authors: Fatimah Zawani Abdullah, Shereena Mohd Arif, Nurul Malim

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The study of molecular similarity search in chemical database is increasingly widespread, especially in the area of drug discovery. Similarity search is an application in the field of Chemoinformatics to measure the similarity between the molecular structure which is known as the query and the structure of chemical compounds in the database. Similarity search is also one of the approaches in virtual screening which involves computational techniques and scoring the probabilities of activity. The main objective of this work is to determine the best fingerprint when compared to the other five fingerprints selected in this study using PubChem chemical dataset. This paper will discuss the similarity searching process conducted using 6 types of descriptors, which are ECFP4, ECFC4, FCFP4, FCFC4, SRECFC4 and SRFCFC4 on 15 activity classes of PubChem dataset using Tanimoto coefficient to calculate the similarity between the query structures and each of the database structure. The results suggest that ECFP4 performs the best to be used with Tanimoto coefficient in the PubChem dataset.

Keywords: 2D fingerprints, Tanimoto, PubChem, similarity searching, chemoinformatics

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Authors: Fatih Ercin Guney, Hami Karagol

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Day by day, humanity's energy needs increase, to facilitate access to energy sources by energy importing countries is of great importance in terms of issues both in terms of economic security and political security. The geographical location of the oil exporting countries in the Middle East (Iran, Iraq, Kuwait, Libya, Saudi Arabia, United Arab Emirates, Qatar) today, it is observed that evaluated by emerging Arab Spring(from Tunisia to Egypt) and freedom battles(in Syria) with security issues arise sourced from terrorist activities(ISIS). Progresses related with limited natural resources, energy and it's transportation issues which worries the developing countries, the energy in the region is considered to how to transfer safely. North Region of the Black Sea , the beginning of the conflict in the regional nature formed between Russia and Ukraine (2010), followed by the relevant regions of the power transmission line (From Russia to Europe) the discovery is considered to be the east's hand began to strengthen in terms of both the economical and political sides. With the growing need for safe access to the west of the new energy transmission lines are followed by Turkey, re-interest is considered to be shifted to the Mediterranean and the Middle East by West. Also, Russia, Iran and China (three axis of east) are generally performing as carry out parallel policies about energy , economical side and security in both United Nations Security Council (Two of Five Permanent Members are Russia and China) and Shanghai Cooperation Organization. In addition, Eastern Mediterranean Region Tension are rapidly increasing about research new oil and natural gas sources by Israel, Egypt, Cyprus, Lebanon. This paper provides, new energy corridor(s) are needed to transfer sources (Oil&Natural Gas) by Europe from East to West. So The West needs either safe bridge country to transfer natural sources to Europe in region or is needed to discovery new natural sources in extraterritorial waters of Eastern Mediterranean Region. But in two opportunities are evaluated with secure transfer corridors form region to Europe in safely. Even if the natural sources can be discovered, they are considered to transfer in safe manner. This paper involved, Turkey’s importance as a leader country in region over both of political and safe energy transfer sides as bridge country between south and north of Turkey why natural sources shall be transferred over Turkey, Even if diplomatic issues-For Example; Cyprus membership in European Union, Turkey membership candidate duration, Israel-Cyprus- Egypt-Lebanon researches about new natural sources in Mediterranean - occurred. But politic balance in Middle-East is changing quickly because of lack of democratic governments in region. So it is evaluated that the alliance of natural sources researches may not be long-time relations due to share sources after discoveries. After evaluating over causes and reasons, aim to reach finding foresight about future of region for energy transfer periods in secure manner.

Keywords: Middle East, natural gas, oil, Turkey

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Authors: Raphaël Weuts, Mykyta Petik, Anton Vedder

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Artificial Intelligence has the potential to create and already creates enormous value in healthcare. Prescriptive systems might be able to make the use of healthcare capacity more efficient. Such systems might entail interpretations that exclude the effect of confounders that brings risks with it. Those risks might be mitigated by regulation that prevents systems entailing such risks to come to market. One modality of regulation is that of legislation, and the European AI Act is an example of such a regulatory instrument that might mitigate these risks. To assess the risk mitigation potential of the AI Act for those risks, this research focusses on a case study of a hypothetical application of medical device software that entails the aforementioned risks. The AI Act refers to the harmonised norms for already existing legislation, here being the European medical device regulation. The issue at hand is a causal link between a confounder and the value the algorithm optimises for by proxy. The research identifies where the AI Act already looks at confounders (i.a. feedback loops in systems that continue to learn after being placed on the market). The research identifies where the current proposal by parliament leaves legal uncertainty on the necessity to check for confounders that do not influence the input of the system, when the system does not continue to learn after being placed on the market. The authors propose an amendment to article 15 of the AI Act that would require high-risk systems to be developed in such a way as to mitigate risks from those aforementioned confounders.

Keywords: AI Act, healthcare, confounders, risks

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Authors: Zhanzhao Fu, Chongyi Ling, Jinlan Wang

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Water splitting and rechargeable air-based batteries are emerging as new renewable energy storage and conversion technologies. However, the discovery of suitable catalysts with high activity and low cost remains a great challenge. In this work, we report a single-atom trifunctional catalyst, namely Ti₃C₂O₂ supported single Pd atom (Pd1@Ti₃C₂O₂), for the hydrogen evolution reaction (HER), oxygen evolution reaction (OER) and oxygen reduction reaction (ORR). This catalyst is selected from 12 candidates and possesses low overpotentials of 0.22 V, 0.31 V and 0.34 V for the HER, OER and ORR, respectively, making it an excellent electrocatalyst for both overall water splitting and rechargeable air-based batteries. The superior OER and ORR performance originates from the optimal d band center of the supported Pd atom. Moreover, the excellent activity can be maintained even if the single Pd atoms aggregate into small clusters. This work offers new opportunities for advancing the renewable energy storage and conversion technologies and paves a new way for the development of multifunctional electrocatalysts.

Keywords: DFT, SACs, OER, ORR, HER

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Authors: Yunus Doğan, Ahmet Durap

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Coastal regions are the one of the most commonly used places by the natural balance and the growing population. In coastal engineering, the most valuable data is wave behaviors. The amount of this data becomes very big because of observations that take place for periods of hours, days and months. In this study, some statistical methods such as the wave spectrum analysis methods and the standard statistical methods have been used. The goal of this study is the discovery profiles of the different coast areas by using these statistical methods, and thus, obtaining an instance based data set from the big data to analysis by using data mining algorithms. In the experimental studies, the six sample data sets about the wave behaviors obtained by 20 minutes of observations from Mersin Bay in Turkey and converted to an instance based form, while different clustering techniques in data mining algorithms were used to discover similar coastal places. Moreover, this study discusses that this summarization approach can be used in other branches collecting big data such as medicine.

Keywords: clustering algorithms, coastal engineering, data mining, data summarization, statistical methods

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Authors: Wei Yao, Constantinos Alexiou

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In the existing literature, many studies have focused on the implementation and effectiveness of quantitative easing (QE) since 2008, but only a few have evaluated QE’s effect on commodity prices. In this context, by following Frankel’s (1986) commodity price overshooting model, we study the dynamic covariation between the expected real interest rates and six agricultural commodities’ real returns over the period from 2000:1 to 2018 for the US economy. We use wavelet analysis to investigate the causal relationship and co-movement of time series data by calculating the coefficient of determination in different frequencies. We find that a) US unconventional monetary policy may cause more positive and significant covariation between the expected real interest rates and agricultural commodities’ real returns over the short horizons; b) a lead-lag relationship that runs from agricultural commodities’ real returns to the expected real short-term interest rates over the long horizons; and c) a lead-lag relationship from agricultural commodities’ real returns to the expected real long-term interest rates over short horizons. In the realm of monetary policy, we argue that QE may shift the negative relationship between most commodities’ real returns and the expected real interest rates to a positive one over a short horizon.

Keywords: QE, commodity price, interest rate, wavelet coherence

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Authors: Mahdi Farajzadeh Ajirlou

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Ordinary fetal brain development can be considered by in vivo attractive reverberation imaging (MRI) from the 18th gestational week (GW) to term and depends fundamentally on T2-weighted and diffusion-weighted (DW) arrangements. The foremost commonly suspected brain pathologies alluded to fetal MRI for assist assessment are ventriculomegaly, lost corpus callosum, and anomalies of the posterior fossa. Brain division could be a crucial to begin with step in neuroimage examination. Within the case of fetal MRI it is especially challenging and critical due to the subjective introduction of the hatchling, organs that encompass the fetal head, and irregular fetal movement. A few promising strategies have been proposed but are constrained in their execution in challenging cases and in realtime division. Fetal MRI is routinely performed on a 1.5-Tesla scanner without maternal or fetal sedation. The mother lies recumbent amid the course of the examination, the length of which is ordinarily 45 to 60 minutes. The accessibility and continuous approval of standardizing fetal brain development directions will give critical devices for early discovery of impeded fetal brain development upon which to oversee high-risk pregnancies.

Keywords: brain, fetal, MRI, imaging

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Authors: Marie E. Docken

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At some point in the lifecycle of a country, patterns of political and social unrest of varying degrees are observed. Events involving public disorder or civil disobedience may produce effects that range a wide spectrum of varying outcomes, depending on the level of unrest. Many previous studies, primarily theoretical in nature, have attempted to measure public disorder in answering why or how it occurs in society by examining causal factors or underlying issues in the social or political position of a population. The main objective in doing so is to understand how these activities evolve or seek some predictive capability for the events. In contrast, this research involves the fusion of analytics and social studies to provide more knowledge of the public disorder and civil disobedience intensity in populations. With a greater understanding of the magnitude of these events, it is believed that we may learn how they relate to extreme actions such as mass migration or violence. Upon establishing a model for measuring civil unrest based upon empirical data, a case study on various Latin American countries is performed. Interpretations of historical events are combined with analytical results to provide insights regarding the magnitude and effect of social and political activism.

Keywords: public disorder, civil disobedience, Latin America, metrics, data analysis

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Authors: Anatoly V. Stepanov, Maria Y. Ilyushkina, Alexander S. Burnasov

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Expansion of tourism, especially after WWII, has led to significant improvements in the regional infrastructure. The present study has revealed a lot of progress in the advancement of industrial heritage narrative in the Central Urals. The evidence comes from the general public’s increased fascination with some of Europe’s oldest mining and industrial sites, and the agreement of many stakeholders that the Urals industrial heritage should be preserved. The development of tourist sites in Nizhny Tagil and Nevyansk, gold-digging in Beryosovsky, gemstone search in Murzinka, and the progress with the Urals Gemstone Ring project are the examples showing the immense opportunities of industrial heritage tourism development in the region that are still to be realized. Regardless of the economic future of the Central Urals, whether it will remain an industrial region or experience a deeper deindustrialization, the sprouts of the industrial heritage tourism should be advanced and amplified for the benefit of local communities and the tourist community at large as it is hard to imagine a more suitable site for the discovery of industrial and mining heritage than the Central Urals Region of Russia.

Keywords: industrial heritage, mining heritage, Central Urals, Russia

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Authors: Zeba Mahmood

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The modern business organizations are adopting technological advancement to achieve competitive edge and satisfy their consumer. The development in the field of Information technology systems has changed the way of conducting business today. Business operations today rely more on the data they obtained and this data is continuously increasing in volume. The data stored in different locations is difficult to find and use without the effective implementation of Data mining and Knowledge management techniques. Organizations who smartly identify, obtain and then convert data in useful formats for their decision making and operational improvements create additional value for their customers and enhance their operational capabilities. Marketers and Customer relationship departments of firm use Data mining techniques to make relevant decisions, this paper emphasizes on the identification of different data mining and Knowledge management techniques that are applied to different business industries. The challenges and issues of execution of these techniques are also discussed and critically analyzed in this paper.

Keywords: knowledge, knowledge management, knowledge discovery in databases, business, operational, information, data mining

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Authors: B. Chandra

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In Association Rule Mining, much attention has been paid for developing algorithms for large (frequent/closed/maximal) itemsets but very little attention has been paid to improve the performance of rule generation algorithms. Rule generation is an important part of Association Rule Mining. In this paper, a novel approach named NARG (Association Rule using Antecedent Support) has been proposed for rule generation that uses memory resident data structure named FCET (Frequent Closed Enumeration Tree) to find frequent/closed itemsets. In addition, the computational speed of NARG is enhanced by giving importance to the rules that have lower antecedent support. Comparative performance evaluation of NARG with fast association rule mining algorithm for rule generation has been done on synthetic datasets and real life datasets (taken from UCI Machine Learning Repository). Performance analysis shows that NARG is computationally faster in comparison to the existing algorithms for rule generation.

Keywords: knowledge discovery, association rule mining, antecedent support, rule generation

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Authors: Marcela Dvorakova, Lenka Langhansova, Premysl Landa

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A series of quinazoline derivatives bearing aromatic rings in 2- and 4-positions were prepared and tested for their biological activity. Firstly, the compounds were evaluated for their potential to inhibit various kinases, such as autophagy activating kinase ULK1, 3-Phosphoinositide-dependent kinase 1, and TANK-binding kinase 1. None of the compounds displayed any activity on these kinases. Secondly, the compounds were tested for their anti-inflammatory activity expressed as cyclooxygenase (COX) isoforms and 5-lipoxygenase (5-LOX) inhibition. Three of the compounds showed significant selectivity towards COX-1 isoform (COX-2/COX-1 SI = 20-30). They inhibited COX-1 in a single-digit µM range. There was also one compound that exhibited inhibitory activity towards all three tested enzymes in µM range (IC50COX-1 = 1.9 µM; IC50COX-2 and 5-LOX = 10.1µM. COX-1 inhibition was until recently considered undesirable due to COX-1 constitutive expression in most cell types and tissues. Thus, there are not many compounds known with selective COX-1 activity. However, it is now believed that COX-1 plays an important role in the pathophysiology of several acute and chronic disorders, including cancer or neurodegenerative diseases. Thus, the discovery of effective COX-1 selective inhibitors is desirable and important.

Keywords: cyclooxygenases, kinases, lipoxygenases, quinazolines

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Authors: Salim Khan

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The attainment of the carbon neutrality objective and Sustainable Development Goal 13 (SDG-13) target, which pertains to climate actions, received widespread attention in developing and emerging nations. Given the increasing pace of urbanization, technological advancements, and rapid growth, it is imperative to examine the linear and nonlinear effects of urbanization and economic growth and the linear impact of information and communication technology (ICT) on carbon emissions (CO2e). This study employs the Dynamic System GMM (DSGMM) and Panel Quantile Regression (PQR) methodologies to investigate the causal relationship between urbanization, ICT, economic growth, and their interplay on CO2e in 39 BRI countries from 2001 to 2020. The study's findings indicate that the impact of urbanization on CO2e exhibits linear and nonlinear patterns. The specific nonlinear impact of urbanization leads to a decrease in CO2e, hence facilitating the achievement of carbon neutrality and contributing to SDG-13. The study highlights the importance of ICT in achieving SDG-13 by reducing CO2e, emphasizing the need for informatization. Simultaneously, the findings support the Environmental Kuznets Curve (EKC) hypothesis and support the pollution haven theory. Finally, based on empirical findings, significant policy implications are suggested for achieving SGD 13 and carbon neutrality.

Keywords: urbanization, ICT, CO2 emission, EKC, pollution haven, BRI

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Authors: Yiqi Zhu, Jean Francois Trani, Rameez Ulhassan

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Extreme weather phenomena increased by 46% between 2007 and 2017 and have become more intense with the rise in global average temperatures. This increased intensity of climate variations often induces humanitarian crises and particularly affects vulnerable populations in low- and middle-income countries (LMICs). Expectant and lactating mothers are among the most vulnerable groups. Pakistan ranks 10th among the most affected countries by climate disasters. In 2022, monsoon floods submerged a third of the country, causing the loss of 1,500 lives. Approximately 650,000 expectant and lactating mothers faced systematic stress from climatic disasters. Our study used participatory methods to investigate the systematic impact of climatic disasters on maternal health. In March 2023, we conducted six Group Model Building (GMB) workshops with healthcare workers, fathers, and mothers separately in two of the most affected areas in Pakistan. This study was approved by the Islamic Relief Research Review Board. GMB workshops consist of three sessions. In the first session, participants discussed the factors that impact maternal health. After identifying the factors, they discussed the connections among them and explored the system structures that collectively impact maternal health. Based on the discussion, a causal loop diagram (CLD) was created. Finally, participants discussed action ideas that could improve the system to enhance maternal health. Based on our discussions and the causal loop diagram, we identified interconnected factors at the family, community, and policy levels. Mothers and children are directly impacted by three interrelated factors: food insecurity, unstable housing, and lack of income. These factors create a reinforcing cycle that negatively affects both mothers and newborns. After the flood, many mothers were unable to produce sufficient breastmilk due to their health status. Without breastmilk and sufficient food for complementary feeding, babies tend to get sick in damp and unhygienic environments resulting from temporary or unstable housing. When parents take care of sick children, they miss out on income-generating opportunities. At the community level, the lack of access to clean water and sanitation (WASH) and maternal healthcare further worsens the situation. Structural failures such as a lack of safety nets and programs associated with flood preparedness make families increasingly vulnerable with each disaster. Several families reported that they had not fully recovered from a flood that occurred ten years ago, and this latest disaster destroyed their lives again. Although over twenty non-profit organizations are working in these villages, few of them provide sustainable support. Therefore, participants called for systemic changes in response to the increasing frequency of climate disasters. The study reveals the systematic vulnerabilities of mothers and children after climatic disasters. The most vulnerable populations are often affected the most by climate change. Collaborative efforts are required to improve water and forest management, strengthen public infrastructure, increase access to WASH, and gradually build climate-resilient communities. Governments, non-governmental organizations, and the community should work together to develop and implement effective strategies to prevent, mitigate, and adapt to climate change and its impacts.

Keywords: climatic disasters, maternal health, Pakistan, systematic impact, flood, disaster relief.

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Authors: Nadia Elouaer

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Tax revenue is the main state resource and one of the important variables in tax policy. Nevertheless, this resource is continually decreasing, so it is important to focus on the reasons for this decline. Several studies show that the taxpayer is reluctant to pay taxes, especially in countries at risk or in countries in transition, including Tunisia. This study focuses on the tax evasion behavior of a Tunisian taxpayer under the influence of his political beliefs, as well as the influence of different tax compliance variables. Using a questionnaire, a sample of 500 Tunisian taxpayers is used to examine the relationship between political beliefs and taxpayer affiliations and tax compliance variables, as well as the study of the causal link between political beliefs and fraudulent behavior. The data were examined using correlation, factor, and regression analysis and found a positive and statistically significant relationship between the different tax compliance variables and the tax evasion behavior. There is also a positive and statistically significant relationship between tax evasion and political beliefs and affiliations. The study of the relationship between political beliefs and compliance variables shows that they are closely related. The conclusion is to admit that tax evasion and political beliefs are closely linked, and the government should update its tax policy and modernize its administration in order to strengthen the credibility and disclosure of information in order to restore a relationship of trust between public authorities and the taxpayer.

Keywords: fiscal policy, political beliefs, tax evasion, taxpayer behavior

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Authors: Faten Hatem

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This paper explores the associated understanding of the role and meaning of art and whether it is perceived to be separate from smart city construction. The paper emphasises the significance of fulfilling the inherent need for discovery and interaction, driving people to explore new places and think of works of art. This is done by exploring the ways of thinking and types of art in Milton Keynes by illustrating a general pattern of misunderstanding that relies on the separation between smart, art, and architecture, promoting a better and deeper understanding of the interconnections between neuroscience, art, and architecture. A reflective approach is used to clarify the potential and impact of using art-based research, methodology, and ways of knowing when approaching global phenomena and knowledge production while examining the process of making and developing smart cities, in particular, asserting that factors can severely impact it in the process of conducting the study itself. It follows a case study as a research strategy. The qualitative methods included data collection and analysis that involved interviews and observations that depended on visuals.

Keywords: smart cities, art and smart, smart cities design, smart cities making, sustainability, city brain and smart cities metrics, smart cities standards, smart cities applications, governance, planning and policy

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Authors: Kanita Beširević

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Open-source software development activities highly rely on Internet gathering communities volunteering in software development projects. Additionally, the libraries and cultural institutions share their metadata in the form of linked metadata to enable dissemination and enrichment. The open-source software provides free alternatives to traditional software solutions. The article aims to investigate the ever-increasing options for the digital library open source software adoption. The software available is presented and compared to other software solutions as well as to their previous versions. The top three open-source digital library software solutions are presented and compared. The comparison criteria are adopted from the UNESCO study by Bankier, J., & Gleason, K. Institutional Repository Software Comparison comprising of twelve criteria to appraise software, namely: infrastructure, front-end design, content discovery, publication tools, interoperability, and preservation. This article adopts a descriptive methodology based on data and information collected through selected software websites and the literature review.

Keywords: open source software, digital library, DSpace, Fedora, Greenstone

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Authors: Mehry Daraei

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The goal of this study was to survey the components and affective factors on organizational commitment of Islamic Azad university Khoramabad Baranch’s faculty members. The research method was correlation by causal modeling and data were gathered by questionnaire. Statistical society consisted of 147 faculty members in Islamic Azad University Khoramabad Branch and sample size was determined as 106 persons by Morgan’s sample table that were selected by class sampling. Correlation test, T-single group test and path analysis test were used for analysis of data. Data were analyzed by Lisrel software. The results showed that organizational corporate was the most effective element on organizational commitment and organizational corporate, experience work and organizational justice were only in direct relation with organizational commitment. Also, job security had direct and indirect effect on OC. Job security had effect on OC by gender. Gender variable had direct and indirect effect on OC. Gender had effect on OC by organizational corporate. Job opportunities out of university also had direct and indirect effect on OC, which means job opportunities had indirect effect on OC by organizational corporate.

Keywords: organization, commitment, job security, Islamic Azad University

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Authors: P. Wlodarczak, J. Soar, M. Ally

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The dramatic rise in the use of Social Media (SM) platforms such as Facebook and Twitter provide access to an unprecedented amount of user data. Users may post reviews on products and services they bought, write about their interests, share ideas or give their opinions and views on political issues. There is a growing interest in the analysis of SM data from organisations for detecting new trends, obtaining user opinions on their products and services or finding out about their online reputations. A recent research trend in SM analysis is making predictions based on sentiment analysis of SM. Often indicators of historic SM data are represented as time series and correlated with a variety of real world phenomena like the outcome of elections, the development of financial indicators, box office revenue and disease outbreaks. This paper examines the current state of research in the area of SM mining and predictive analysis and gives an overview of the analysis methods using opinion mining and machine learning techniques.

Keywords: social media, text mining, knowledge discovery, predictive analysis, machine learning

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Authors: Muhammad Umar Hassan

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Renal cell carcinoma is a subset of kidney cancer that arises in the lining of DCT and is present in parenchymal tissue. Diagnosis is based on lab reports, including urinalysis, renal function tests (RFTs), and electrolyte balance, along with imaging techniques. Organ failure and other complications have been commonly observed in these cases. Over the years, the presentation of patients has varied, so carcinoma was classified on the basis of site, shape, and consistency for detailed analysis. Lifestyle patterns and occupational history were inquired about and recorded. Methods: Data from 100 patients presenting to the oncology and nephrology department of Mayo Hospital in the year 2015-2020 were included in this retrospective study on a random basis. The study was specifically focused on three risk factors. Smoking, occupational exposures, and Hakim medicine are taken by the patient for any cause. After procurement of data, follow-up contacts of these patients were established, resulting in a detailed analysis of lifestyle. Conclusion: The inference drawn is a direct causal link between smoking, industrial workplace exposure, and Hakim medicine with the development of Renal Cell Carcinoma. It was shown in the majority of the patients and hence confirmed our hypothesis.

Keywords: renal cell carcinoma, kidney cancer, clear cell carcinoma

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Authors: W. Mazari, K. Boucherit, Z. Boucherit-Otmani, M. N. Rahmoun, M. Benabdallah

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The hospital or any other establishment of care can be considered as an ecosystem where the patient comes into contact with a frightening microbial universe and a risk to contract infection that is referred to as nosocomial or health care-associated. In these last years, the incidence of these infections has risen sharply. Several microorganisms are the cause of these nosocomial infections and the emergence of resistance of the microbial strains against antibiotics creates a danger to public health. The search for new antimicrobial agents to overcome this problem has produced interesting compounds through chemical synthesis, which plays a very important role in the research and discovery of new drugs. It is in this framework that our study was conducted at our laboratory and it involves evaluating the antibacterial activity of thirteen 2-pyridone derivatives synthesized by two methods, the diffusion disc method and the dilution method against eight Gram negative bacterial strains. The results seem interesting especially for two products that have shown the best activities against Escherichia coli ATCC 25922 and Enterobacter cloacae ATCC 13047 with CMI of 512µg/ml.

Keywords: heterocyclic derivatives, chemical synthesis, antimicrobial activity, biotechnology

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Authors: Kanae Suzuki

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Handheld video games are popular communication tools among Japanese elementary school students today. This study aims to examine the effects of the use of handheld video games on interpersonal relationships of the students in real and virtual worlds. A two-wave panel survey was conducted for students of ten elementary schools at an interval of approximately six months. The survey questionnaire included questions about the average amount of time spent playing a handheld video game during the past one month, the frequency of communication with players during game play, and the interpersonal relationships, such as the number of real and virtual friends the students have. A multiple regression model was constructed for 324 students to examine causal relationships. The results indicated that the more frequently the students communicated with other players while playing games, the number of the real friends tended to increase. In contrast, no significant effect of the total time spent playing games was found on interpersonal relationships. The findings suggested that communication during game play is an important factor for improving interpersonal relationships of this age group.

Keywords: communication, real friend, social adjustment, virtual friend

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Authors: Diego De Castro Rodrigues, Marcelo Lisboa Rocha, Daniela M. De Q. Trevisan, Marcos Dias Da Conceicao, Gabriel Rosa, Rommel M. Barbosa

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The use of association rules algorithms within data mining is recognized as being of great value in the knowledge discovery in databases. Very often, the number of rules generated is high, sometimes even in databases with small volume, so the success in the analysis of results can be hampered by this quantity. The purpose of this research is to present a method for reducing the quantity of rules generated with association algorithms. Therefore, a computational algorithm was developed with the use of a Weka Application Programming Interface, which allows the execution of the method on different types of databases. After the development, tests were carried out on three types of databases: synthetic, model, and real. Efficient results were obtained in reducing the number of rules, where the worst case presented a gain of more than 50%, considering the concepts of support, confidence, and lift as measures. This study concluded that the proposed model is feasible and quite interesting, contributing to the analysis of the results of association rules generated from the use of algorithms.

Keywords: data mining, association rules, rules reduction, artificial intelligence

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Authors: Jacopo Baboni Schilingi

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We here describe the theoretical and philosophical understanding of a long term use and development of algorithmic computer-based tools applied to music composition. The findings of our research lead us to interrogate some specific processes and systems of communication engaged in the discovery of specific cultural artworks: artistic creation in the sono-musical domain. Our hypothesis is that the patterns of auditory learning cannot be only understood in terms of social transmission but would gain to be questioned in the way they rely on various ranges of acoustic stimuli modes of consciousness and how the different types of memories engaged in the percept-action expressive systems of our cultural communities also relies on these shadowy conscious entities we named “Reduced Descriptive Structures”.

Keywords: algorithmic sonic computation, corrected and self-correcting learning patterns in acoustic perception, morphological derivations in sensorial patterns, social unconscious modes of communication

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Authors: P. S. Jagadeesh Kumar, Tracy Lin Huan, S. Meenakshi Sundaram

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Alzheimer’s disease is one of the prevalent kind of ailment, expected for impudent reconciliation or an effectual therapy is to be accredited hitherto. Probable detonation of patients in the upcoming years, and consequently an enormous deal of apprehension in early discovery of the disorder, this will conceivably chaperon to enhanced healing outcomes. Complex impetuosity of the brain is an observant symbolic of the disease and a unique recognition of genetic sign of the disease. Machine learning alongside deep learning and decision tree reinforces the aptitude to absorb characteristics from multi-dimensional data’s and thus simplifies automatic classification of Alzheimer’s disease. Susceptible testing was prophesied and realized in training the prospect of Alzheimer’s disease classification built on machine learning advances. It was shrewd that the decision trees trained with deep neural network fashioned the excellent results parallel to related pattern classification.

Keywords: Alzheimer's diagnosis, decision trees, deep neural network, machine learning, pattern classification

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Authors: Rasheed Sanusi Adeleke

Abstract:

Several attempts have been made by scholars, both medieval and contemporary on the impact of Islam on scientific discovery. Lesser attention, however, is always accorded to the historical antecedents of the earlier Muslim scholars, who made frantic efforts towards the discoveries. Islam as a divine religion places high premium on the acquisition of knowledge especially that of sciences. It considers knowledge as a comprehensive whole, which covers both spiritual and material aspects of human life. Islam torches every aspect of human life for the growth, development and advancement of society. Acquisition of knowledge of humanity, social sciences as well as the pure and applied sciences is comprehensively expressed in Islamic education. Not only this, the history portrays the leading indelible roles played by the early Muslims on these various fields of knowledge. That is why Islam has declared acquisition of knowledge compulsory for all Muslims. This paper therefore analyses the contributions of Islam to civilization with particular reference to sciences. It also affirms that Islam is beyond the religion of prayers and rituals. The work is historic, analytic and explorative in nature. Recommendations are also also put forward as suggestions for the present generation cum posterity in general and Muslims in particular.

Keywords: education, development, Islam, development and Islam

Procedia PDF Downloads 429

Authors: Farhad Shafiepour Motlagh, Narges Salehi

Abstract:

Purpose: The purpose of this study was to support student strategies for virtual learning in the learning management system. Methodology: The research method was based on grounded theory. The statistical population included all the articles of the ten years 2022-2010, and the sampling method was purposeful to the extent of theoretical saturation (n=31 ). Data collection was done by referring to the authoritative scientific databases of Emerald, Springer, Elsevier, Google Scholar, Sage Publication, and Science Direct. For data analysis, open coding, axial coding, and selective coding were used. Results: The results showed that causal conditions include cognitive empowerment (comprehension, analysis, composition), emotional empowerment (learning motivation, involvement in the learning system, enthusiasm for learning), psychomotor empowerment (learning to master, internalizing learning skills, creativity in learning). Conclusion: Supporting students requires their empowerment in three dimensions: cognitive, emotional empowerment, and psychomotor empowerment. In such a way that by introducing them to enter the learning management system, the capacities of the system, the toolkit of learning in the system, improve the motivation to learn in them, and in such a case, by learning more in the learning management system, they will reach mastery learning.

Keywords: student support, virtual education, learning management system, electronic

Procedia PDF Downloads 296

Authors: A. Senthil Kumar, V. Murali Bhaskaran

Abstract:

In the information technology ground, people are using various tools and software for their official use and personal reasons. Nowadays, people are worrying to choose data accessing and extraction tools at the time of buying and selling their products. In addition, worry about various quality factors such as price, durability, color, size, and availability of the product. The main purpose of the research study is to find solutions to these unsolved existing problems. The proposed algorithm is a Multidirectional Rank Prediction (MDRP) decision making algorithm in order to take an effective strategic decision at all the levels of data extraction, uses a real time textile dataset and analyzes the results. Finally, the results are obtained and compared with the existing measurement methods such as PCC, SLCF, and VSS. The result accuracy is higher than the existing rank prediction methods.

Keywords: Knowledge Discovery in Database (KDD), Multidirectional Rank Prediction (MDRP), Pearson’s Correlation Coefficient (PCC), VSS (Vector Space Similarity)

Procedia PDF Downloads 281