Search results for: grey clustering

Authors: Pramoda Karunarathna, Hemamalie Gunatilaka

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This study is based on experiences of Sri Lankan lesbian and gay workers’ career in the corporate sector, which include both manufacturing and service sectors. The study has started with the intention of shedding light on a grey area to observe the negative effects on lesbian and gay workers and their experiences while they are employed in the Sri Lankan corporate sector. In order to understand the experiences of lesbian and gay workers while they are at work within the corporate sector, the study seeks to address four questions. First research question is about the challenges faced by lesbian and gay workers while they are at work, and the second research question looks at their career patterns. Third research question seeks to address the behavior at work, and the fourth research question looks at the influence of class, religion, and cultural aspects on the career of lesbian and gay workers. Methodologically, the research was based on semi-structured interviews with nine participants (five gay men and four lesbian women) having work experience in the corporate sector and residing in Colombo, the capital city of Sri Lanka. The research found that the participants have gone through the process of developing sexual identity; gay men possess more feminine characteristics, while lesbian women possess more masculine characteristics. Further, their identity gets revealed in different ways, such as through the curriculum vitae, at the interviews, through the attire and behavior, and with the use of social media. The study also found that lesbian and gay workers experience discrimination due to violation of hierarchical power difference by other employees and marginalization, verbal and nonverbal abuse by other men at work are common experiences. Another finding is that lesbian and gay workers adopt strategies for survival at work, and they prefer the NGO sector to the corporate sector. In contrast, even within the corporate sector, advertising is preferred by lesbian and gay workers. Some of the Sri Lankan corporate sector organizations, especially multinational organizations, have initiated diversity training, and it might lead to making these organisations lesbian and gay-friendly workplaces in the future. It is also found that nearly 44 percent of the participants do not have a religion, and it is due to the rejection of deviant behaviours by most of the religions. In conclusion, lesbian and gay workers experience discrimination at work in the Sri Lankan corporate sector with an exception to the companies relating to advertising and non-governmental organisations is the sector that these workers prefer the most.

Keywords: lesbian workers, gay workers, Sri Lankan corporate sector, discrimination

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Authors: Sukhleen Kaur

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In security groundwork, Intrusion Detection System (IDS) has become an important component. The IDS has received increasing attention in recent years. IDS is one of the effective way to detect different kinds of attacks and malicious codes in a network and help us to secure the network. Data mining techniques can be implemented to IDS, which analyses the large amount of data and gives better results. Data mining can contribute to improving intrusion detection by adding a level of focus to anomaly detection. So far the study has been carried out on finding the attacks but this paper detects the malicious files. Some intruders do not attack directly, but they hide some harmful code inside the files or may corrupt those file and attack the system. These files are detected according to some defined parameters which will form two lists of files as normal files and harmful files. After that data mining will be performed. In this paper a hybrid classifier has been used via Naive Bayes and Ripper classification methods. The results show how the uploaded file in the database will be tested against the parameters and then it is characterised as either normal or harmful file and after that the mining is performed. Moreover, when a user tries to mine on harmful file it will generate an exception that mining cannot be made on corrupted or harmful files.

Keywords: data mining, association, classification, clustering, decision tree, intrusion detection system, misuse detection, anomaly detection, naive Bayes, ripper

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Authors: Dina Ahmed Selim, Eman Shawky Anwar, Rasha Mohamed Abu El-Khair

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A rapid, simple and efficient method with minimal sample treatment was developed for authentication of Garcinia cambogia fruit peel powder, along with determining undeclared active pharmaceutical ingredients (APIs) in its herbal slimming dietary supplements using near infrared spectroscopy combined with chemometrics. Five featured adulterants, including sibutramine, metformin, orlistat, ephedrine, and theophylline are selected as target compounds. The Near infrared spectral data matrix of authentic Garcinia cambogia fruit peel and specimens degraded by intentional contamination with the five selected APIs was subjected to hierarchical clustering analysis to investigate their bundling figure. SIMCA models were established to ensure the genuiness of Garcinia cambogia fruit peel which resulted in perfect classification of all tested specimens. Adulterated samples were utilized for construction of PLSR models based on different APIs contents at minute levels of fraud practices (LOQ < 0.2% w/w).The suggested approach can be applied to enhance and guarantee the safety and quality of Garcinia fruit peel powder as raw material and in dietary supplements.

Keywords: Garcinia cambogia, Quality control, NIR spectroscopy, Chemometrics

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Authors: A. V. Sokolov, S. V. Vorobyev, A. Yu. Efimtcev, V. Yu. Lobzin, I. A. Lupanov, O. A. Cherdakov, V. A. Fokin

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Alzheimer’s disease (AD) is the most common form of dementia. Different brain regions are involved to the pathological process of AD. The purpose of this study was to evaluate brain activation by visual memory task in patients with Alzheimer's disease and determine correlation between memory impairment and atrophy of memory specific brain regions of frontal and medial temporal lobes. To investigate the organization of memory and localize cortical areas activated by visual memory task we used functional magnetic resonance imaging and to evaluate brain atrophy of patients with Alzheimer's disease we used voxel-based morphometry. FMRI was performed on 1.5 T MR-scanner Siemens Magnetom Symphony with BOLD (Blood Oxygenation Level Dependent) technique, based on distinctions of magnetic properties of hemoglobin. For test stimuli we used series of 12 not related images for "Baseline" and 12 images with 6 presented before for "Active". Stimuli were presented 3 times with reduction of repeated images to 4 and 2. Patients with Alzheimer's disease showed less activation in hippocampal formation (HF) region and parahippocampal gyrus then healthy persons of control group (p<0.05). The study also showed reduced activation in posterior cingulate cortex (p<0.001). Voxel-based morphometry showed significant atrophy of grey matter in Alzheimer’s disease patients, especially of both temporal lobes (fusiform and parahippocampal gyri); frontal lobes (posterior cingulate and superior frontal gyri). The study showed correlation between memory impairment and atrophy of memory specific brain regions of frontal and medial temporal lobes. Thus, reduced activation in hippocampal formation and parahippocampal gyri, in posterior cingulate gyrus in patients with Alzheimer's disease correlates to significant atrophy of these regions, detected by voxel-based morphometry, and to deterioration of specific cognitive functions.

Keywords: Alzheimer’s disease, functional MRI, voxel-based morphometry

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Authors: Hassan S. Hussein, Rania A. Abul Seoud, Amr M. Refaat

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Scientific researchers face in the analysis of very large data sets that is increasing noticeable rate in today’s and tomorrow’s technologies. Hadoop and Spark are types of software that developed frameworks. Hadoop framework is suitable for many Different hardware platforms. In this research, a scientific Linux cluster for Big Data analysis (SLBD) is presented. SLBD runs open source software with large computational capacity and high performance cluster infrastructure. SLBD composed of one cluster contains identical, commodity-grade computers interconnected via a small LAN. SLBD consists of a fast switch and Gigabit-Ethernet card which connect four (nodes). Cloudera Manager is used to configure and manage an Apache Hadoop stack. Hadoop is a framework allows storing and processing big data across the cluster by using MapReduce algorithm. MapReduce algorithm divides the task into smaller tasks which to be assigned to the network nodes. Algorithm then collects the results and form the final result dataset. SLBD clustering system allows fast and efficient processing of large amount of data resulting from different applications. SLBD also provides high performance, high throughput, high availability, expandability and cluster scalability.

Keywords: big data platforms, cloudera manager, Hadoop, MapReduce

Procedia PDF Downloads 358

Authors: Igor Filikhin, Vladimir M. Suslov, Roman Ya. Kezerashvili, Branislav Vlahivic

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The mass-polarization term of the three-body kinetic energy operator is evaluated for different systems which include two identical particles: A+A+B. The term has to be taken into account for the analysis of AB- and AA-interactions based on experimental data for two- and three-body ground state energies. In this study, we present three-body calculations within the framework of a potential model for the kaonic clusters K−K−p and ppK−, nucleus 3H and hypernucleus 6 ΛΛHe. The systems are well clustering as A+ (A+B) with a ground state energy E2 for the pair A+B. The calculations are performed using the method of the Faddeev equations in configuration space. The phenomenological pair potentials were used. We show a correlation between the mass ratio mA/mB and the value δB of the mass-polarization term. For bosonic-like systems, this value is defined as δB = 2E2 − E3, where E3 is three-body energy when VAA = 0. For the systems including three particles with spin(isospin), the models with average AB-potentials are used. In this case, the Faddeev equations become a scalar one like for the bosonic-like system αΛΛ. We show that the additional energy conected with the mass-polarization term can be decomposite to a sum of the two parts: exchenge related and reduced mass related. The state of the system can be described as the following: the particle A1 is bound within the A + B pair with the energy E2, and the second particle A2 is bound with the pair with the energy E3 − E2. Due to the identity of A particles, the particles A1 and A2 are interchangeable in the pair A + B. We shown that the mass polarization δB correlates with a type of AB potential using the system αΛΛ as an example.

Keywords: three-body systems, mass polarization, Faddeev equations, nuclear interactions

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Authors: Fei Gao, Xinyang Dong, Yisu Ge, Shufang Lu, Libo Weng

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Vehicle color recognition plays an important role in traffic accident investigation. However, due to the influence of illumination, weather, and noise, vehicle color recognition still faces challenges. In this paper, a vehicle color classification network based on spatial cluster loss and channel attention mechanism (SCNet) is proposed for vehicle color recognition. A channel attention module is applied to extract the features of vehicle color representative regions and reduce the weight of nonrepresentative color regions in the channel. The proposed loss function, called spatial clustering loss (SC-loss), consists of two channel-specific components, such as a concentration component and a diversity component. The concentration component forces all feature channels belonging to the same class to be concentrated through the channel cluster. The diversity components impose additional constraints on the channels through the mean distance coefficient, making them mutually exclusive in spatial dimensions. In the comparison experiments, the proposed method can achieve state-of-the-art performance on the public datasets, VCD, and VeRi, which are 96.1% and 96.2%, respectively. In addition, the ablation experiment further proves that SC-loss can effectively improve the accuracy of vehicle color recognition.

Keywords: feature extraction, convolutional neural networks, intelligent transportation, vehicle color recognition

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Authors: Vahid Bayrami Rad

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In this research, common methods and techniques have been investigated with a focus on intelligent fault finding and monitoring systems in the oil industry. In fact, remote and intelligent control methods are considered a necessity for implementing various operations in the oil industry, but benefiting from the knowledge extracted from countless data generated with the help of data mining algorithms. It is a avoid way to speed up the operational process for monitoring and troubleshooting in today's big oil companies. Therefore, by comparing data mining algorithms and checking the efficiency and structure and how these algorithms respond in different conditions, The proposed (Bayesian) algorithm using data clustering and their analysis and data evaluation using a colored Petri net has provided an applicable and dynamic model from the point of view of reliability and response time. Therefore, by using this method, it is possible to achieve a dynamic and consistent model of the remote control system and prevent the occurrence of leakage in oil pipelines and refineries and reduce costs and human and financial errors. Statistical data The data obtained from the evaluation process shows an increase in reliability, availability and high speed compared to other previous methods in this proposed method.

Keywords: wireless sensors, petroleum equipment troubleshooting, Bayesian algorithm, colored Petri net, rapid miner, data mining-reliability

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Authors: Barbora Chmelova, Radek Sachl

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Gangliosides are amphipathic membrane lipids. Due to the composition of bulky oligosaccharide chains containing one or more sialic acids linked to the hydrophobic ceramide base, gangliosides are classified among glycosphingolipids. This unique structure induces a high self-aggregating tendency of gangliosides and, therefore, the formation of nanoscopic clusters called nanodomains. Gangliosides are preferentially present in an extracellular membrane leaflet of all human tissues and thus have an impact on a huge number of biological processes, such as intercellular communication, cell signalling, membrane trafficking, and regulation of receptor activity. Defects in their metabolism, impairment of proper ganglioside function, or changes in their organization lead to serious health conditions such as Alzheimer´s and Parkinson´s diseases, autoimmune diseases, tumour growth, etc. This work mainly focuses on ganglioside organization into nanodomains and their dynamics within the plasma membrane. Current research investigates static ganglioside nanodomains characterization; nevertheless, the information about their diffusion is missing. In our study, fluorescence correlation spectroscopy is implemented together with stimulated emission depletion (STED-FCS), which combines the diffraction-unlimited spatial resolution with high temporal resolution. By comparison of the experiments performed on model vesicles containing 4 % of either GM1, GM2, or GM3 and Monte Carlo simulations of diffusion on the plasma membrane, the description of ganglioside clustering, diffusion of nanodomains, and even diffusion of ganglioside molecules inside investigated nanodomains are described.

Keywords: gangliosides, nanodomains, STED-FCS, flourescence microscopy, membrane diffusion

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Authors: Iram Zahair, Tanith Rose, Oyinlola Oyebode, Stephen Clayton, Iman Ghosh, Michelle Maden, Ben Barr

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Background: Gastrointestinal infections exert a significant public health burden on UK healthcare services and the community. However, there are conflicting findings on where ethnic inequalities are likely to persist. This systematic review aimed to identify studies that ascertain differences in the incidence and prevalence of gastrointestinal infections within and between UK ethnic groups and explore possible explanations for heterogeneity observed within the literature. Methods: Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidance, a systematic review methodology was used. Medline, Web of Science, CINAHL Plus, and grey literature were searched from 1980 to 2021 for studies reporting an association between ethnicity and gastrointestinal infections in UK population samples. Two reviewers independently screened the articles and conducted quality appraisals; data extraction was undertaken by one reviewer and verified by two reviewers (PROSPERO CRD 42021240714). A narrative synthesis was undertaken to synthesise the study findings. Results: The searches identified 8134 studies; 13 met the inclusion criteria. 12 out of 13 studies found a difference in the prevalence of gastrointestinal infections between different ethnic groups. UK ethnic minorities, predominantly men and children of Asian ethnicity, had an increased risk of infection than the white British majority in 12 studies; the Pakistani ethnic group had a higher risk of infection in three out of 13 studies. Studies reported that age and sex confounded the relationship between ethnicity and gastrointestinal infections. At the same time, the country of birth, socioeconomic status, and geographical location of ethnic groups mediated this association and significantly explained the heterogeneity observed across the studies. Harvest plots supported the textual synthesis. Conclusion: This systematic review elucidates the lack of extensive UK quantitative evidence examining the association between ethnicity and gastrointestinal infections. Insights into gastrointestinal infections and ethnicity's association can help address policy actions to mitigate the inequalities identified within and between UK ethnic groups.

Keywords: ethnic and racial populations, public health, public health policy, systematic review

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Authors: Acheampong Addo, Emmanuel Odartei Armah, Seth Koranteng Agyakwah, Ruby Asmah, Emmanuel Tetteh-Doku Mensah, Rhoda Lims Diyie, Sena Amewu, Catherine Ragasa, Edward Kofi Abban, Mike Yaw Osei-Atweneboana

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The study investigated genetic variation and relationships among populations of Nile tilapia cultured in small-scale fish farms in selected regions of Ghana. A total of 700 samples were collected. All samples were screened with five microsatellite markers and results were analyzed using (Genetic Analysis in Excel), (Molecular and Evolutionary Genetic Analysis software, and Genpop on the web for Heterozygosity and Shannon diversity, (Analysis of Molecular Variance), and (Principal Coordinate Analysis). Fish from the 16 populations (made up of 14 farms and 2 selectively bred populations) clustered into three groups: 7 populations clustered with the GIFT-derived strain, 4 populations clustered with the Akosombo strain, and three populations were in a separate cluster. The clustering pattern indicated groups of different strains of Nile tilapia cultured. Mantel correlation test also showed low genetic variations among the 16 populations hence the need to boost seed quality in order to accelerate aquaculture production in Ghana.

Keywords: microsatellites, small- scale, Nile tilapia, akosombo strain, GIFT strain

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Authors: Xinke Huang, Huan Wang, Lidong Guo, Changbin Ju, Runbiao Liu, Guoen Cao, Yibo Wang, Honghua Xu

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Grid connected photovoltaic (PV) power system is to be developed in the direction of large-scale, clustering. Large-scale PV generation systems connected to HVDC grid have many advantages compared to its counterpart of AC grid, and DC connection is the tendency. DC/DC converter as the most important device in the system, has become one of the hot spots recently. The paper proposes a Quasi Z-Source(QZS) based Boost Full Bridge Isolated DC/DC Converter(BFBIC) topology as a basis power module and combination through input parallel output series(IPOS) method to improve power capacity and output voltage to match with the HVDC grid. The topology has both traditional voltage source and current source advantages, it permit the H-bridge short through and open circuit, which adopt utility duty cycle control and achieved input current and output voltage balancing through input current sharing control strategy. A ±10kV/200kW system model is built in MATLAB/SIMULINK to verify the proposed topology and control strategy.

Keywords: PV Generation System, Cascaded DC/DC converter, HVDC, Quasi Z Source Converter

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Authors: Aleksandra Zysk, Pawel Badura

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Recognizing and controlling vocal registers during singing is a difficult task for beginner vocalist. It requires among others identifying which part of natural resonators is being used when a sound propagates through the body. Thus, an application has been designed allowing for sound recording, automatic vocal register recognition (VRR), and a graphical user interface providing real-time visualization of the signal and recognition results. Six spectral features are determined for each time frame and passed to the support vector machine classifier yielding a binary decision on the head or chest register assignment of the segment. The classification training and testing data have been recorded by ten professional female singers (soprano, aged 19-29) performing sounds for both chest and head register. The classification accuracy exceeded 93% in each of various validation schemes. Apart from a hard two-class clustering, the support vector classifier returns also information on the distance between particular feature vector and the discrimination hyperplane in a feature space. Such an information reflects the level of certainty of the vocal register classification in a fuzzy way. Thus, the designed recognition and training application is able to assess and visualize the continuous trend in singing in a user-friendly graphical mode providing an easy way to control the vocal emission.

Keywords: classification, singing, spectral analysis, vocal emission, vocal register

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Authors: Yuhua Yang, Yingcheng Li

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As a new form of intercity economic cooperation, innovation enclaves have received much attention from governments and scholars in China, which are of great significance in promoting the flow of innovation elements and advancing regional integration. Utilizing inter-city linkages of innovation enclaves within and beyond the Yangtze River Delta Region, we construct multi-scalar innovation enclave networks in 2018 and 2022, and analyze the evolutionary characteristics and underlying mechanisms of the networks. Overall, we find that: (1) The intercity innovation enclave networks have the characteristics of preferential connection and are gradually forming a clear multi-scale and hierarchical structure, with Shanghai, Hangzhou and Nanjing as the core and other cities as the general nodes; (2) The intercity innovation enclave networks exhibit local clustering dominated by geographical proximity connections, and are becoming more noticeable in the effect of distance decay and functionally polycentric as the spatial scale decreases; (3) The intercity innovation enclave networks are influenced by both functional distance and multidimensional proximity. While the innovation potential differences caused by urban attributes internally drive the formation of innovation enclave cooperation, geographic proximity, technological proximity and institutional proximity externally affect the selection of cooperation partners.

Keywords: economic enclave, intercity cooperation, proximity, yangtze river delta region

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Authors: Hani Malik

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Background: Clinician burnout is a growing phenomenon in current health systems worldwide. Increasing emotional exhaustion, depersonalisation, and reduced personal accomplishment threaten the effective delivery of healthcare. This can potentially be mitigated by mindfulness practice, which has shown promising results in reducing burnout, restoring compassion, and preventing moral injury in clinicians. Objectives: To conduct a scoping review and identify high-quality studies on mindfulness practice in clinician burnout, synthesize themes that emerge from these studies, and discuss the implications of the results to healthcare leadership and innovation. Methodology: A focused scoping review was carried out to investigate the effects of mindfulness practice on clinician burnout. High-ranking journals were targeted to analyse high-quality studies and synthesize common themes in the literature. Studies conducted on current, practicing physicians were included. Mindfulness practice of varying forms was the main intervention studied. Grey literature and studies conducted only on allied health personnel were excluded from this review. Analysis:31 studies were included in this scoping review. Mindfulness practice was found to decrease emotional exhaustion and depersonalisation while improving mood, responses to stress, and vigour. Self-awareness, compassion, and empathy were also increased in study participants. From this review, four themes emerged which include: innovations in mindfulness practice, mindfulness and positive psychology, the impact of mindfulness on work and patient care, and barriers and facilitators to clinician mindfulness practice. Conclusion: Mindfulness had widely been reported to benefit mental health and well-being, but the studies reviewed seemed to adopt a mono focus and omitted key considerations to healthcare leadership, systems-level culture, and practices. Mindfulness practice is a quintessential component of positive psychology and is inherently linked to effective leadership. A mindful and compassionate clinician leader will play a crucial role in addressing gaps in current practice, prioritise staff mental health, and provide a supportive platform for innovation.

Keywords: mindfulness practice, clinician burnout, healthcare leadership, COVID-19

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Authors: S. Roy, R. Rekha, K. Sriram, G. Subhadra, R. Johana

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Cardiovascular disease remains a leading cause of death in most industrialized countries. Many chemical drugs are available in the market which targets different receptor proteins related to cardiovascular diseases. Of late the traditional herbal drugs are safer when compared to chemical drugs because of its side effects. However, many herbal remedies used in treating cardiovascular diseases have not undergone scientific assessment to prove its pharmacological activities. There are many natural compounds, nature derived and Natural product mimic compounds are available which are in the market as approved drug. In the most of the cases drug activity at the molecular level are not known. Here we have categorized those compounds with our experimental compounds in different classes based on the structural similarity and physicochemical properties, using a tool, Chemmine and has attempted to understand the mechanism of the action of a experimental compound, which are clustered with Simvastatin, Lovastatin, Mevastatin and Pravastatin. Target protein molecule for Simvastatin, Lovastatin, Mevastatin and Pravastatin is HMG-CoA reductase, so we concluded that the experimental compound may be able to bind to the same target. Molecular docking and atomic interaction studies with simvastatin and our experimental compound were compared. A pharmacophore modeling was done based on the experimental compound and HMG-CoA reductase inhibitor.

Keywords: molecular docking, physicochemical properties, pharmacophore modeling structural similarity, pravastatin

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Authors: Shahabeddin Sotudian, M. H. Fazel Zarandi, I. B. Turksen

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Hepatitis is one of the most common and dangerous diseases that affects humankind, and exposes millions of people to serious health risks every year. Diagnosis of Hepatitis has always been a challenge for physicians. This paper presents an effective method for diagnosis of hepatitis based on interval Type-II fuzzy. This proposed system includes three steps: pre-processing (feature selection), Type-I and Type-II fuzzy classification, and system evaluation. KNN-FD feature selection is used as the preprocessing step in order to exclude irrelevant features and to improve classification performance and efficiency in generating the classification model. In the fuzzy classification step, an “indirect approach” is used for fuzzy system modeling by implementing the exponential compactness and separation index for determining the number of rules in the fuzzy clustering approach. Therefore, we first proposed a Type-I fuzzy system that had an accuracy of approximately 90.9%. In the proposed system, the process of diagnosis faces vagueness and uncertainty in the final decision. Thus, the imprecise knowledge was managed by using interval Type-II fuzzy logic. The results that were obtained show that interval Type-II fuzzy has the ability to diagnose hepatitis with an average accuracy of 93.94%. The classification accuracy obtained is the highest one reached thus far. The aforementioned rate of accuracy demonstrates that the Type-II fuzzy system has a better performance in comparison to Type-I and indicates a higher capability of Type-II fuzzy system for modeling uncertainty.

Keywords: hepatitis disease, medical diagnosis, type-I fuzzy logic, type-II fuzzy logic, feature selection

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Authors: Anjana Aggarwal, Sheilja Walia

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Prevalence of obesity and overweight is increasing due to sedentary lifestyles and busy schedules of people that spend less time on physical exercise. To reduce weight, people are finding easier and more convenient ways. The easiest solution is the use of dietary supplements and fat burners. These are products that decrease body weight by increasing the basal metabolic rate. Various reports have been published on the consumption of fat burners leading to heart palpitations, seizures, anxiety, depression, psychosis, bradycardia, insomnia, muscle contractions, hepatotoxicity, and even liver failure. Case reports and series are reporting that the ingredients present in the fat burners caused acute liver failure (ALF) and hepatic toxicity in many cases. Another contributing factor is the absence of regulations from the Food and Drug Administration on these products, leading to increased consumption and a higher risk of liver diseases among the population. This systematic review aims to attain a better understanding of the dietary supplements used globally to reduce weight and document the case reports/series of acute liver failure caused by the consumption of fat burners. Electronic databases like PubMed, Cochrane, Google Scholar, etc., will be systematically searched for relevant articles. Various websites of dietary products and brands that sell such supplements, Journals of Hepatology, National and international projects launched for ALF, and their reports, along with the review of grey literature, will also be done to get a better understanding of the topic. After discussing with the co-author, the selection and screening of the articles will be performed by the author. The studies will be selected based on the predefined inclusion and exclusion criteria. The case reports and case series that will be included in the final list of the studies will be assessed for methodological quality using the CARE guidelines. The results from this study will provide insights and a better understanding of fat burners. Since the supplements are easily available in the market without any restrictions on their sale, people are unaware of their adverse effects. The consumption of these supplements causes acute liver failure. Thus, this review will provide a platform for future larger studies to be conducted.

Keywords: acute liver failure, dietary supplements, fat burners, weight loss supplements

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Authors: Strahinja Kovačević, Lidija Jevrić, Miloš Kuzmanović, Sanja Podunavac-Kuzmanović

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In this paper, various derivatives of benzimidazole have been evaluated against Gram-negative bacteria Escherichia coli. For all investigated compounds the minimum inhibitory concentration (MIC) was determined. Quantitative structure-activity relationships (QSAR) attempts to find consistent relationships between the variations in the values of molecular properties and the biological activity for a series of compounds so that these rules can be used to evaluate new chemical entities. The correlation between MIC and some absorption, distribution, metabolism and excretion (ADME) parameters was investigated, and the mathematical models for predicting the antibacterial activity of this class of compounds were developed. The quality of the multiple linear regression (MLR) models was validated by the leave-one-out (LOO) technique, as well as by the calculation of the statistical parameters for the developed models and the results are discussed on the basis of the statistical data. The results of this study indicate that ADME parameters have a significant effect on the antibacterial activity of this class of compounds. Principal component analysis (PCA) and agglomerative hierarchical clustering algorithms (HCA) confirmed that the investigated molecules can be classified into groups on the basis of the ADME parameters: Madin-Darby Canine Kidney cell permeability (MDCK), Plasma protein binding (PPB%), human intestinal absorption (HIA%) and human colon carcinoma cell permeability (Caco-2).

Keywords: benzimidazoles, QSAR, ADME, in silico

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Authors: Hyojin Lim, Cuong Nguyen Khac, Yeongyu Choi, Ho-Youl Jung

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In this paper, we propose a simple moving object detection, which is based on motion vectors obtained from pyramidal Lucas-Kanade optical flow. The proposed method detects moving objects such as pedestrians, the other vehicles and some obstacles at the front-side of the host vehicle, and it can provide the warning to the driver. Motion vectors are obtained by using pyramidal Lucas-Kanade optical flow, and some outliers are eliminated by comparing the amplitude of each vector with the pre-defined threshold value. The background model is obtained by calculating the mean and the variance of the amplitude of recent motion vectors in the rectangular shaped local region called the cell. The model is applied as the reference to classify motion vectors of moving objects and those of background. Motion vectors are clustered to rectangular regions by using the unsupervised clustering K-means algorithm. Labeling method is applied to label groups which is close to each other, using by distance between each center points of rectangular. Through the simulations tested on four kinds of scenarios such as approaching motorbike, vehicle, and pedestrians to host vehicle, we prove that the proposed is simple but efficient for moving object detection in parking lots.

Keywords: moving object detection, dynamic scene, optical flow, pyramidal optical flow

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Authors: Elham Allahmoradi, Bahman Allahmoradi, Ali Bonyadi Naeini

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Complex systems have many aspects. A variety of methods have been developed to analyze these systems. The most efficient of these methods should not only be simple, but also provide useful and comprehensive information about many aspects of the system. Matrix methods are considered the most commonly methods used to analyze and design systems. Each matrix method can examine a particular aspect of the system. If these methods are combined, managers can access to more comprehensive and broader information about the system. This study was conducted in four steps. In the first step, a process model of a real project has been extracted through IDEF3. In the second step, activity levels have been attained by writing a process model in the form of a design structure matrix (DSM) and sorting it through triangulation algorithm (TA). In the third step, sub-processes have been obtained by writing the process model in the form of an interface structure matrix (ISM) and clustering it through cluster identification algorithm (CIA). In the fourth step, a mixed model has been developed to provide a unified picture of the project structure through the simultaneous presentation of activities and sub-processes. Finally, the paper is completed with a conclusion.

Keywords: integrated definition for process description capture (IDEF3) method, design structure matrix (DSM), interface structure matrix (ism), mixed matrix model, activity level, sub-process

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Authors: Rhea Khosla, Victoria Tzortziou-Brown

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Introduction: Adolescent SRH has been neglected since the start of the millennium. Adolescents comprise 16% of the global population, with the largest proportion living in Asia (650 million). By late adolescence, individuals in these regions are likely to become sexually active, and thus they must understand their SRH rights. Many lack knowledge of SRH, using unreliable sources for such information. Sex education is necessary to standardize and inform sexual knowledge, which empowers adolescents to make informed SRH decisions. School is an appropriate environment for this, however, SRH education requires effective policy to enforce. Nonetheless, this issue remains of low political priority in Asia and Africa. Current literature on sex education policy in schools in these regions is scarce and tends to have broad aims. Thus, a scoping review was necessary. Methods: Literature searches were conducted in February 2023 using six databases, including grey literature databases (PubMed, Scopus, Embase, Web of Science, Google Scholar, Global Index Medicus), returning a total of 1537 unique articles. After screening titles, abstracts and full text, 17 articles remained. References of included articles were additionally searched, producing a further 7 articles, which then underwent thematic analysis Results: Most countries in Africa and Asia did not have studies on this topic. Studies derived data from interviews with key stakeholders and quantitative methods quantified questionnaire responses. Barriers were: policy/curriculum issues, societal opinions, teaching discomfort, and lack of educator training. Limitations were insufficient timing, inconsistent implementation, insufficient hours dedicated to teaching, education received late into schooling, and discrepancies between teachers, schools, and students about whether policies were being implemented. Discussion: Based on the existing limited evidence, a cultural shift to reduce stigma seems necessary, alongside teacher and student involvement in policy formulation with effective implementation monitoring and educator training.

Keywords: adolescent, Africa, Asia, education, sexual and reproductive health, policy

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Authors: Jitendra Aswani

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In the first section of this study, impact of Global Financial Crisis (GFC) on the synchronization of fourteen Asian Stock Markets (ASM’s) of countries like Hong Kong, India, Thailand, Singapore, Taiwan, Pakistan, Bangladesh, South Korea, Malaysia, Indonesia, Japan, China, Philippines and Sri Lanka, has been analysed using the network science and its metrics like degree of node, clustering coefficient and network density. Then in the second section of this study by introducing the US stock market in existing network and developing a Minimum Spanning Tree (MST) spread of crisis from the US stock market to Asian Stock Markets (ASM) has been explained. Data used for this study is adjusted the closing price of these indices from 6th January, 2000 to 15th September, 2013 which further divided into three sub-periods: Pre, during and post-crisis. Using network analysis, it is found that Asian stock markets become more interdependent during the crisis than pre and post crisis, and also Hong Kong, India, South Korea and Japan are systemic important stock markets in the Asian region. Therefore, failure or shock to any of these systemic important stock markets can cause contagion to another stock market of this region. This study is useful for global investors’ in portfolio management especially during the crisis period and also for policy makers in formulating the financial regulation norms by knowing the connections between the stock markets and how the system of these stock markets changes in crisis period and after that.

Keywords: global financial crisis, Asian stock markets, network science, Kruskal algorithm

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Authors: Seynabou Toure, Oumar Diop, Kidiyo Kpalma, Amadou S. Maiga

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Color and texture are the two most determinant elements for perception and recognition of the objects in an image. For this reason, color and texture analysis find a large field of application, for example in image classification and segmentation. But, the pioneering work in texture analysis was conducted on grayscale images, thus discarding color information. Many grey-level texture descriptors have been proposed and successfully used in numerous domains for image classification: face recognition, industrial inspections, food science medical imaging among others. Taking into account color in the definition of these descriptors makes it possible to better characterize images. Color texture is thus the subject of recent work, and the analysis of color texture images is increasingly attracting interest in the scientific community. In optical remote sensing systems, sensors measure separately different parts of the electromagnetic spectrum; the visible ones and even those that are invisible to the human eye. The amounts of light reflected by the earth in spectral bands are then transformed into grayscale images. The primary natural colors Red (R) Green (G) and Blue (B) are then used in mixtures of different spectral bands in order to produce RGB images. Thus, good color texture discrimination can be achieved using RGB under controlled illumination conditions. Some previous works investigate the effect of using different color space for color texture classification. However, the selection of the best performing color space in land-sea segmentation is an open question. Its resolution may bring considerable improvements in certain applications like coastline detection, where the detection result is strongly dependent on the performance of the land-sea segmentation. The aim of this paper is to present the results of a study conducted on different color spaces in order to show the best-performing color space for land-sea segmentation. In this sense, an experimental analysis is carried out using five different color spaces (RGB, XYZ, Lab, HSV, YCbCr). For each color space, the Haar wavelet decomposition is used to extract different color texture features. These color texture features are then used for Fusion of Over Segmentation (FOOS) based classification; this allows segmentation of the land part from the sea one. By analyzing the different results of this study, the HSV color space is found as the best classification performance while using color and texture features; which is perfectly coherent with the results presented in the literature.

Keywords: classification, coastline, color, sea-land segmentation

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Authors: Sandra Rafael, Bruno Vicente, Vera Rodrigues, Carlos Borrego, Myriam Lopes

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Air pollution is an environmental and social issue at different spatial scales, especially in a climate change context, with an expected decrease of air quality. Air pollution is a combination of high emissions and unfavourable weather conditions, where wind speed and wind direction play a key role. The urban design (location and structure of buildings and trees) can both promote the air pollutants dispersion as well as promote their retention within the urban area. Today, most of the urban areas are applying measures to adapt to future extreme climatic events. Most of these measures are grounded on nature-based solutions, namely green roofs and green areas. In this sense, studies are required to evaluate how the implementation of these actions will influence the wind flow within the urban area and, consequently, how this will influence air pollutants' dispersion. The main goal of this study was to evaluate the influence of a set of urban morphologies in the wind conditions and in the dispersion of air pollutants, in a built-up area in Portugal. For that, two pollutants were analysed (NOx and PM10) and four scenarios were developed: i) a baseline scenario, which characterizes the current status of the study area, ii) an urban green scenario, which implies the implementation of a green area inside the domain, iii) a green roof scenario, which consists in the implementation of green roofs in a specific area of the domain; iv) a 'grey' scenario, which consists in a scenario with absence of vegetation. For that, two models were used, namely the Weather Research and Forecasting model (WRF) and the CFD model VADIS (pollutant dispersion in the atmosphere under variable wind conditions). The WRF model was used to initialize the CFD model, while the last was used to perform the set of numerical simulations, on an hourly basis. The implementation of the green urban area promoted a reduction of air pollutants' concentrations, 16% on average, related to the increase in the wind flow, which promotes air pollutants dispersion; while the application of green roofs showed an increase of concentrations (reaching 60% during specific time periods). Overall the results showed that a strategic placement of vegetation in cities has the potential to make an important contribution to increase air pollutants dispersion and so promote the improvement of air quality and sustainability of urban environments.

Keywords: air pollutants dispersion, wind conditions, urban morphologies, road traffic emissions

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Authors: Mukesh Lal Das, Muthukumar Muthuchamy

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Climate change Adaptation strategy (AS) is a scientific approach to dealing with the impacts of climate change (CC). Efforts are being made to contain the global emission of greenhouse gas within threshold limits, thereby limiting the rise of global temperature to an optimal level. Global Climate change is a spontaneous process; therefore, reversing the damage would take decades. The climate change adaptation strategy recommended by various stakeholders could be a key to resilience for biodiversity. The Indian Government has constituted the panel to synthesize the climate change action report at the federal and state levels. This review scavenged the published literature on the Western Ghats hotspots. And highlight the adaptation strategy recommended by diverse scientific actors to conserve biodiversity. It also reviews the grey literature adopted by state and federal governments and its effectiveness in mitigating the impacts on biodiversity. We have narrowed the scope of interest to the state action report by 6 Indian states such as Gujarat, Maharashtra, Goa, Karnataka, Kerala and Tamil Nadu, which host Western Ghats global biodiversity hotspot. Western Ghats(WGs) act as the water tower to the peninsular part of India, and its extensive watershed caters to the water demand of the Industry sector, Agriculture and urban community. Conservation of WGs is the key to the prosperity of Peninsular India. The global scientific community suggested more than 600+ Climate change adaptation strategies for the policymakers, stakeholders, and other state actors to take proactive actions. The preliminary analysis of the federal and the state action plan on climate change in the wake of CC indicate inadequacy in motion as per recommended scientific adaptation strategies. Tamil Nadu and Kerala state constitute nine effective adaptation strategies out of the 40+ recommended for Western Ghats conservation. And other four states' adaptation strategies are deficient, confusing and vague. Western Ghats' resilience capacity will soon or might have reached its threshold, and the frequency of severe drought and flash floods might upsurge manifold in the decades to come. The lack of a clear roadmap to climate change adaptation strategies in the federal and state action stirred us to identify the gap and address it by offering a holistic approach to WGs biodiversity conservation.

Keywords: adaptation strategy, biodiversity conservation, climate change, resilience, Western Ghats

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Authors: Mastoor Qubra

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Cyber-attacks have frequently disrupted the critical infrastructures of the major global states and now, cyber threat has become one of the dire security risks for the states across the globe. Recently, ransomware cyber-attacks, wannacry and petya, have affected hundreds of thousands of computer servers and individuals’ private machines in more than hundred countries across Europe, Middle East, Asia, United States and Australia. Although, states are rapidly becoming aware of the destructive nature of this new security threat and counter measures are being taken but states’ isolated efforts would be inadequate to deal with this heinous security challenge, rather a global coordination and cooperation is inevitable in order to develop a credible cyber deterrence policy. Hence, the paper focuses that coordinated global approach is required to deter posed cyber threat. This paper intends to analyze the cyber security counter measures in four dimensions i.e. evaluation of prevalent strategies at bilateral level, initiatives and limitations for cooperation at global level, obstacles to combat cyber terrorism and finally, recommendations to deter the threat by applying tools of deterrence theory. Firstly, it focuses on states’ efforts to combat the cyber threat and in this regard, US-Australia Cyber Security Dialogue is comprehensively illustrated and investigated. Secondly, global partnerships and strategic and analytic role of multinational organizations, particularly United Nations (UN), to deal with the heinous threat, is critically analyzed and flaws are highlighted, for instance; less significance of cyber laws within international law as compared to other conflict prone issues. In addition to this, there are certain obstacles and limitations at national, regional and global level to implement the cyber terrorism counter strategies which are presented in the third section. Lastly, by underlining the gaps and grey areas in the current cyber security counter measures, it aims to apply tools of deterrence theory, i.e. defense, attribution and retaliation, in the cyber realm to contribute towards formulating a credible cyber deterrence strategy at global level. Thus, this study is significant in understanding and determining the inevitable necessity of counter cyber terrorism strategies.

Keywords: attribution, critical infrastructure, cyber terrorism, global cooperation

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Authors: Mohammed T. Hayajneh

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Machining of Metal Matrix Composites (MMCs) is very significant process and has been a main problem that draws many researchers to investigate the characteristics of MMCs during different machining process. The poor machining properties of hard particles reinforced MMCs make drilling process a rather interesting task. Unlike drilling of conventional materials, many problems can be seriously encountered during drilling of MMCs, such as tool wear and cutting forces. Cutting tool wear is a very significant concern in industries. Cutting tool wear not only influences the quality of the drilled hole, but also affects the cutting tool life. Prediction the cutting tool life during drilling is essential for optimizing the cutting conditions. However, the relationship between tool life and cutting conditions, tool geometrical factors and workpiece material properties has not yet been established by any machining theory. In this research work, fuzzy subtractive clustering system has been used to model the cutting tool life in drilling of Al₂O₃ particle reinforced aluminum alloy composite to investigate of the effect of cutting conditions on cutting tool life. This investigation can help in controlling and optimizing of cutting conditions when the process parameters are adjusted. The built model for prediction the tool life is identified by using drill diameter, cutting speed, and cutting feed rate as input data. The validity of the model was confirmed by the examinations under various cutting conditions. Experimental results have shown the efficiency of the model to predict cutting tool life.

Keywords: composite, fuzzy, tool life, wear

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Authors: Zhou Luchen, Wu Yubing, Burra Venkata Durga Kumar

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As the scale of the network becomes larger and more complex than before, the density of user devices is also increasing. The development of Unmanned Aerial Vehicle (UAV) networks is able to collect and transform data in an efficient way by using software-defined networks (SDN) technology. This paper proposed a three-layer distributed and dynamic cluster architecture to manage UAVs by using an AI-based resource allocation calculation algorithm to address the overloading network problem. Through separating services of each UAV, the UAV hierarchical cluster system performs the main function of reducing the network load and transferring user requests, with three sub-tasks including data collection, communication channel organization, and data relaying. In this cluster, a head node and a vice head node UAV are selected considering the Central Processing Unit (CPU), operational (RAM), and permanent (ROM) memory of devices, battery charge, and capacity. The vice head node acts as a backup that stores all the data in the head node. The k-means clustering algorithm is used in order to detect high load regions and form the UAV layered clusters. The whole process of detecting high load areas, forming and selecting UAV clusters, and moving the selected UAV cluster to that area is proposed as offloading traffic algorithm.

Keywords: k-means, resource allocation, SDN, UAV network, unmanned aerial vehicles

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Authors: Athanasios A. Gavrilidis, Mihai R. Nita, Larissa N. Stoia, Diana A. Onose

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Contemporary global environmental challenges must be primarily addressed at local levels. Cities are under continuous pressure as they must ensure high quality of life levels for their citizens and at the same time to adapt and address specific environmental issues. Innovative solutions using natural features or mimicking natural systems are endorsed by the scientific community as efficient approaches for both mitigating climate change effects and the decrease of environmental quality and for maintaining high standards of living for urban dwellers. The aim of this study was to assess whether Romanian cities’ authorities are considering nature-based innovation as solutions for their planning, management, and environmental issues. Data were gathered by applying 140 questionnaires to urban authorities throughout the country. The questionnaire was designed for assessinglocal policy makers’ perspective over the efficiency of nature-based innovations as a tool to address specific challenges. It also focused on extracting data about financing sources and challenges they must overcome for adopting nature-based approaches. The gather results from the municipalities participating in our study were statistically processed, and they revealed that Romanian city managers acknowledge the benefits of nature-based innovations, but investments in this sector are not on top of their priorities. More than 90% of the selected cities have agreed that in the last 10 years, their major concern was to expand the grey infrastructure (roads and public amenities) using traditional approaches. When asked how they would react if faced with different socio-economic and environmental challenges, local urban managers indicated investments nature-based solutions as a priority only in case of biodiversity loss and extreme weather, while for other 14 proposed scenarios, they would embrace the business-as-usual approach. Our study indicates that while new concepts of sustainable urban planning emerge within the scientific community, local authorities need more time to understand and implement them. Without the proper knowledge, personnel, policies, or dedicated budgets, local administrators will not embrace nature-based innovations as solutions for their challenges.

Keywords: nature based innovations, perception analysis, policy making, urban planning

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