Search results for: K-means cluster analysis

Authors: Donatella Giuliani

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In this research, we propose an unsupervised grayscale image segmentation method based on a combination of the Firefly Algorithm and the Gaussian Mixture Model. Firstly, the Firefly Algorithm has been applied in a histogram-based research of cluster means. The Firefly Algorithm is a stochastic global optimization technique, centered on the flashing characteristics of fireflies. In this context it has been performed to determine the number of clusters and the related cluster means in a histogram-based segmentation approach. Successively these means are used in the initialization step for the parameter estimation of a Gaussian Mixture Model. The parametric probability density function of a Gaussian Mixture Model is represented as a weighted sum of Gaussian component densities, whose parameters are evaluated applying the iterative Expectation-Maximization technique. The coefficients of the linear super-position of Gaussians can be thought as prior probabilities of each component. Applying the Bayes rule, the posterior probabilities of the grayscale intensities have been evaluated, therefore their maxima are used to assign each pixel to the clusters, according to their gray-level values. The proposed approach appears fairly solid and reliable when applied even to complex grayscale images. The validation has been performed by using different standard measures, more precisely: the Root Mean Square Error (RMSE), the Structural Content (SC), the Normalized Correlation Coefficient (NK) and the Davies-Bouldin (DB) index. The achieved results have strongly confirmed the robustness of this gray scale segmentation method based on a metaheuristic algorithm. Another noteworthy advantage of this methodology is due to the use of maxima of responsibilities for the pixel assignment that implies a consistent reduction of the computational costs.

Keywords: clustering images, firefly algorithm, Gaussian mixture model, meta heuristic algorithm, image segmentation

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Authors: I. Gupta, B. Karmakar

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Bengal has a long history (8^th century A.D. onwards) of decorating the wall of brick-built temples with curved terracotta plaques on a diverse range of subjects. These could be considered as one of the most significant visual archives to understand the various facets of the then contemporary societies. The temples under focus include Char-bangla temple complex (circa 1755 A.D.), Bhavanishvara temple (circa 1755 A.D.) and the Gangeshvara Shiva Jor-bangla temple (circa 1753 A.D.), located within a part of the river Bhagirathi basin in Baranagar, Murshidabad, West Bengal, India. Though, a diverse range of subjects have been intricately carved mainly on the front façades of the Baranagar temple cluster, the study specifically concentrates on depictions related to religious and non-religious acts performed by practitioners of various religious sects of late medieval Bengal with the intention to acquire knowledge about the various facets of their life. Apart from this, the paper also mapped the spatial location of these religious performers on the temples’ façades to examine if any systematic plan or arrangement had been employed for connoting a particular idea. Further, an attempt is made to provide a commentary on the attire worn by followers of various religious sects of late medieval Bengal. The primary materials for the study comprise the depictions which denote religious activities carved on the terracotta plaques. The secondary material has been collected from published and unpublished theses, journals and books. These data have been further supplemented with photographic documentation, some useful line-drawings and descriptions in table format to get a clear understanding of the concerned issues.

Keywords: attire, scheme of allocation, terracotta temple, various religious sect

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Authors: K. Umbleja, M. Ichino

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Symbolic data mining has been developed to analyze data in very large datasets. It is also useful in cases when entry specific details should remain hidden. Symbolic data mining is quickly gaining popularity as datasets in need of analyzing are becoming ever larger. One type of such symbolic data is a histogram, which enables to save huge amounts of information into a single variable with high-level of granularity. Other types of symbolic data can also be described in histograms, therefore making histogram a very important and general symbolic data type - a method developed for histograms - can also be applied to other types of symbolic data. Due to its complex structure, analyzing histograms is complicated. This paper proposes a method, which allows to compare two histogram-valued variables and therefore find a dissimilarity between two histograms. Proposed method uses the Ichino-Yaguchi dissimilarity measure for mixed feature-type data analysis as a base and develops a dissimilarity measure specifically for histogram data, which allows to compare histograms with different number of bins and bin widths (so called general histogram). Proposed dissimilarity measure is then used as a measure for clustering. Furthermore, linkage method based on weighted averages is proposed with the concept of cluster compactness to measure the quality of clustering. The method is then validated with application on real datasets. As a result, the proposed dissimilarity measure is found producing adequate and comparable results with general histograms without the loss of detail or need to transform the data.

Keywords: dissimilarity measure, hierarchical clustering, histograms, symbolic data analysis

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Authors: Amirmohsen Behjat, Aleck Ostry, Christina Miewald, Bernie Pauly

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Substantial research has indicated that socioeconomic and demographic characteristics’ of neighborhoods are strong determinants of food security. The aim of this study was to develop a Food Insecurity Neighborhood Index (FINI) based on the associated socioeconomic and demographic variables to identify the areas at potential risk of food insecurity in rural British Columbia (BC). Principle Component Analysis (PCA) technique was used to calculate the FINI for each rural Dissemination Area (DA) using the food security determinant variables from Canadian Census data. Using ArcGIS, the neighborhoods with the top quartile FINI values were classified as food insecure. The results of this study indicated that the most food insecure neighborhood with the highest FINI value of 99.1 was in the Bulkley-Nechako (central BC) area whereas the lowest FINI with the value of 2.97 was for a rural neighborhood in the Cowichan Valley area. In total, 98.049 (19%) of the rural population of British Columbians reside in high food insecure areas. Moreover, the distribution of food insecure neighborhoods was found to be strongly dependent on the degree of rurality in BC. In conclusion, the cluster of food insecure neighbourhoods was more pronounced in Central Coast, Mount Wadington, Peace River, Kootenay Boundary, and the Alberni-Clayoqout Regional Districts.

Keywords: neighborhood food insecurity index, socioeconomic and demographic determinants, principal component analysis, Canada census, ArcGIS

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Authors: Vithya Veeramani, Karunanidhi Subbaiah

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Emotional problems were found to be the predominant cause of suicide and second leading cause of death among adolescents in India. Emotional problems seem to be the underlying cause for various other severe psycho-social problems experienced in adolescence and also in later years of life. The Corporation schools in Chennai city are named as Chennai High School or Chennai Higher Secondary School run by the Corporation of Chennai. These schools fulfill the educational needs of students who hail from lower socio-economic status living in slums of the Chennai city. Adolescent students of Chennai schools tend to lack basic needs like food, clothes, shelter, etc. Some of the other significant problems faced by them are broken family, lack of parental support, frequent quarrel between parents, alcoholic parents, drug abuse and substance abuse among parents and neighbors, extended family, illiterate parents, deprivation of love and care, and lack of sense of belongingness. This prevailing condition may affect them emotionally and could lead to maladaptive behaviour, aggressiveness, poor interpersonal relationship with others, school refusal behaviour, school drop-out, suicide, etc. Therefore, it is very important to investigate the emotional problems faced by the adolescent students studying in Chennai schools, Chennai. A cross-sectional survey design was used to find the prevalence of emotional problems among adolescent students. Cluster sampling technique was used to select the schools for the present study considering the school as a cluster. In total, there are 15 zones, under the control of Chennai Corporation, of which only 7 zones have Corporation Schools in Chennai city, comprising of 32 Chennai Higher Secondary Schools and 38 Chennai High Schools. Out of these 70 schools, 29 schools comprising of 17 high schools and 12 higher secondary schools were selected randomly using lottery method. A sample of 2594 adolescent students from 9th standard and 11th standard was chosen for the study. Percentage analysis was done to find out the prevalence rate of emotional problems among adolescents students studying in Chennai Schools. Results of the study revealed that, out of 2594 students surveyed, 21.04% adolescent students were found to have academic problems (n = 546), 15.99% adolescent students had social problems (n = 415), behaviour problems was found to be prevalent among 12.87% adolescent students (n = 334), depression was prevalent among 15.88% adolescent students (n = 412) and anxiety was prevalent among 14.42% adolescent students (n = 374). Prevalence of emotional problems among male and female revealed that academic problems were more prevalent compared to other problems. Behaviour problems were least prevalent among boys and anxiety was least prevalent among girls than other problems. The overall prevalence rate of emotional problems was found to be on an increasing trend among adolescent students of low socio-economic status in Chennai city. The findings indicated the need for intervention to prevent and rehabilitate these adolescent students.

Keywords: adolescents, corporation schools, emotional problems, prevalence

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Authors: Ni Wayan Sinthia Widiastuti, Komang Rahayu Indrawati

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The increasing number of tourists coming to Bali, causing accommodation facilities, such as hotels have increased. The existence of hotel needs will be the source of labor and cost efficiency, so that hotel management employs employees with different working status. The hospitality industry is one of the sectors that require organizational citizenship behavior because, the main goal of every hotel, in general, was to provide the best service and quality to tourists. The purpose of this study was to determine the differences in organizational citizenship behavior based on work status of employees at the Hotel in Bali in terms of quality of work life. Research sample was chosen randomly through two-stage cluster sampling which succeeds to obtain 126 samples from 11 hotels in Denpasar, Bali. The subjects consisted of 64 employees with Employment Agreement of Uncertain Time or who is often called a permanent employee and 62 employees with Employment Agreement of Certain Time or better known as contract employees, outsourcing, and daily workers. Instruments in this study were the scale of organizational citizenship behavior and the scale of quality of work life. The results of ANCOVA analysis showed there were differences in organizational citizenship behavior based on employee work status in terms of quality of work life. Differences in organizational citizenship behavior and quality of work life based on work status of employees using comparative test was analysis by independent sample t-test shows there were differences in organizational citizenship behavior and quality of work life between employees with different working status in hotels in Bali. The result of the regression analysis showed the functional relationship between quality of work life and organizational citizenship behavior.

Keywords: hotel in Bali, organizational citizenship behavior, quality of work life, work status of employees

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Authors: Xu Yifei, Le Yining, Yang Qingluan, Tu Yanjie

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Objective: This study aims to investigate the distribution features of Traditional Chinese Medicine (TCM) syndromes and syndrome elements in Epstein-Barr virus-associated diseases and then explores the relations between TCM syndromes or syndrome elements and laboratory indicators of Epstein-Barr virus-associated diseases. Methods: A cross-sectional study of 70 patients with EBV infection was described. We assessed the diagnostic information and laboratory indicators of these patients from Huashan Hospital Affiliated to Fudan University between November 2017 and July 2019. The disease diagnosis and syndrome differentiation were based on the diagnostic criteria of EBV-associated diseases and the theory of TCM respectively. Confidence correlation analysis, logistic regression analysis, cluster analysis, and the Sankey diagram were used to analyze the correlation between the data. Results: The differentiation of the 4 primary TCM syndromes in the collected patients was correlated with the indexes of immune function, liver function, inflammation, and anemia, especially the relationship between Qifen syndrome and high lactic acid dehydrogenase level. The common 11 TCM syndrome elements were associated with the increased CD3+ T cell rate, low hemoglobin level, high procalcitonin level, high lactic acid dehydrogenase level, and low albumin level. Conclusion: The changes in immune function indexes, procalcitonin, and liver function-related indexes in patients with EBV-associated diseases were consistent with the evolution law of TCM syndromes. This study provides a reference for judging the pathological stages of these kinds of diseases, predicting their prognosis, and guiding subsequent treatment strategies based on TCM syndrome type.

Keywords: EBV-associated diseases, traditional Chinese medicine syndrome, syndrome element, diagnostics

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Authors: Danyi Wang, Andrew Schriefer, Dennis O'Rourke, Brajendra Kumar, Yang Liu, Fei Zhong, Juergen Scheuenpflug, Zheng Feng

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Purpose: It has been recognized that the microbiome plays critical roles in disease pathogenesis, including cancer, autoimmune disease, and multiple sclerosis. To develop a clinical-grade assay for exploring microbiome-derived clinical biomarkers across disease areas, a two-phase approach is implemented. 1) Identification of the optimal sample preparation reagents using pre-mixed bacteria and healthy donor stool samples coupled with proprietary Sigma-Aldrich® bioinformatics solution. 2) Exploratory analysis of patient samples for enabling precision medicine. Study Procedure: In phase 1 study, we first compared the 16S sequencing results of two ATCC® microbiome standards (MSA 2002 and MSA 2003) across five different extraction kits (Kit A, B, C, D & E). Both microbiome standards samples were extracted in triplicate across all extraction kits. Following isolation, DNA quantity was determined by Qubit assay. DNA quality was assessed to determine purity and to confirm extracted DNA is of high molecular weight. Bacterial 16S ribosomal ribonucleic acid (rRNA) amplicons were generated via amplification of the V3/V4 hypervariable region of the 16S rRNA. Sequencing was performed using a 2x300 bp paired-end configuration on the Illumina MiSeq. Fastq files were analyzed using the Sigma-Aldrich® Microbiome Platform. The Microbiome Platform is a cloud-based service that offers best-in-class 16S-seq and WGS analysis pipelines and databases. The Platform and its methods have been extensively benchmarked using microbiome standards generated internally by MilliporeSigma and other external providers. Data Summary: The DNA yield using the extraction kit D and E is below the limit of detection (100 pg/µl) of Qubit assay as both extraction kits are intended for samples with low bacterial counts. The pre-mixed bacterial pellets at high concentrations with an input of 2 x106 cells for MSA-2002 and 1 x106 cells from MSA-2003 were not compatible with the kits. Among the remaining 3 extraction kits, kit A produced the greatest yield whereas kit B provided the least yield (Kit-A/MSA-2002: 174.25 ± 34.98; Kit-A/MSA-2003: 179.89 ± 30.18; Kit-B/MSA-2002: 27.86 ± 9.35; Kit-B/MSA-2003: 23.14 ± 6.39; Kit-C/MSA-2002: 55.19 ± 10.18; Kit-C/MSA-2003: 35.80 ± 11.41 (Mean ± SD)). Also, kit A produced the greatest yield, whereas kit B provided the least yield. The PCoA 3D visualization of the Weighted Unifrac beta diversity shows that kits A and C cluster closely together while kit B appears as an outlier. The kit A sequencing samples cluster more closely together than both the other kits. The taxonomic profiles of kit B have lower recall when compared to the known mixture profiles indicating that kit B was inefficient at detecting some of the bacteria. Conclusion: Our data demonstrated that the DNA extraction method impacts DNA concentration, purity, and microbial communities detected by next-generation sequencing analysis. Further microbiome analysis performance comparison of using healthy stool samples is underway; also, colorectal cancer patients' samples will be acquired for further explore the clinical utilities. Collectively, our comprehensive qualification approach, including the evaluation of optimal DNA extraction conditions, the inclusion of positive controls, and the implementation of a robust qualified bioinformatics pipeline, assures accurate characterization of the microbiota in a complex matrix for deciphering the deep biology and enabling precision medicine.

Keywords: 16S rRNA sequencing, analytical validation, bioinformatics pipeline, metagenomics

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Authors: José de Jesús Rivero Oliva, Jesús Salomón Llanes, Manuel Perdomo Ojeda, Antonio Torres Valle

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Combinatorial explosion is a common problem to both predominant methods for solving fault trees: Minimal Cut Set (MCS) approach and Binary Decision Diagram (BDD). High memory consumption impedes the complete solution of very complex fault trees. Only approximated non-conservative solutions are possible in these cases using truncation or other simplification techniques. The paper proposes a method (CSolv+) for solving complex fault trees, without any possibility of combinatorial explosion. Each individual MCS is immediately discarded after its contribution to the basic events importance measures and the Top gate Upper Bound Probability (TUBP) has been accounted. An estimation of the Top gate Exact Probability (TEP) is also provided. Therefore, running in a computer cluster, CSolv+ will guarantee the complete solution of complex fault trees. It was successfully applied to 40 fault trees from the Aralia fault trees database, performing the evaluation of the top gate probability, the 1000 Significant MCSs (SMCS), and the Fussell-Vesely, RRW and RAW importance measures for all basic events. The high complexity fault tree nus9601 was solved with truncation probabilities from 10-²¹ to 10-²⁷ just to limit the execution time. The solution corresponding to 10-²⁷ evaluated 3.530.592.796 MCSs in 3 hours and 15 minutes.

Keywords: system reliability analysis, probabilistic risk assessment, fault tree analysis, basic events importance measures

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Authors: Schulz Peter, Kee Kalya, Lwin May, Goh Wilson, Chia Kendrikck, Chueng Max, Lam Thomas, Sung Joseph

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As Artificial Intelligence (AI) is progressively making inroads into clinical practice, questions have arisen as to whether acceptance of AI is skewed toward certain medical practitioner segments, even within particular specializations. This study examines distinct AI acceptance among gastroenterologists with contrasting levels of seniority/experience when interacting with AI typologies. Data from 319 gastroenterologists show the presence of four distinct clusters of clinicians based on experience levels and perceived risk typologies. Analysis of cluster-based responses further revealed that acceptance of AI was not uniform. Our findings showed that clinician experience and risk perspective have an interactive role in influencing AI acceptance. Senior clinicians with low-risk perceptions were highly accepting of AI, but those with high-risk perceptions of AI were substantially less accepting. In contrast, junior clinicians were more inclined to embrace AI when they perceived high risk, yet they hesitated to adopt AI when the perceived risk was minimal.

Keywords: risk perception, acceptance, trust, medicine

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Authors: Marijana M. Ačanski, Kristian A. Pastor, Djura N. Vujić

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The identification of lipid and soluble sugar components in flour samples of different cultivars belonging to common oat species (Avena sativa L.) was performed: spring oat, winter oat and hulless oat. Fatty acids were extracted from flour samples with n-hexane, and derivatized into volatile methyl esters, using TMSH (trimethylsulfonium hydroxide in methanol). Soluble sugars were then extracted from defatted and dried samples of oat flour with 96% ethanol, and further derivatized into corresponding TMS-oximes, using hydroxylamine hydrochloride solution and BSTFA (N,O-bis-(trimethylsilyl)-trifluoroacetamide). The hexane and ethanol extracts of each oat cultivar were analyzed using GC-MS system. Lipid and simple sugar compositions are very similar in all samples of investigated cultivars. Chemometric tool was applied to numeric values of automatically integrated surface areas of detected lipid and simple sugar components in their corresponding derivatized forms. Hierarchical cluster analysis shows a very high similarity between the investigated flour samples of oat cultivars, according to the fatty acid content (0.9955). Moderate similarity was observed according to the content of soluble sugars (0.50). These preliminary results support the idea of establishing methods for oat flour authentication, and provide the means for distinguishing oat flour samples, regardless of the variety, from flour samples made of other cereal species, just by lipid and simple sugar profile analysis.

Keywords: oat cultivars, lipid composition, soluble sugar composition, GC-MS, chemometrics, authentication

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Authors: Deepak Kumar, Debasish Deb, Reena Mamgain

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Radar signal processing requires high number crunching capability. Most often this is achieved using multiprocessor platform. Though multiprocessor platform provides the capability of meeting the real time computational challenges, the architecture of the same along with mapping of the algorithm on the architecture plays a vital role in efficiently using the platform. Towards this, along with standard performance metrics, few additional metrics are defined which helps in evaluating the multiprocessor platform along with the algorithm mapping. A generic multiprocessor architecture can not suit all the processing requirements. Depending on the system requirement and type of algorithms used, the most suitable architecture for the given problem is decided. In the paper, we study different architectures and quantify the different performance metrics which enables comparison of different architectures for their merit. We also carried out case study of different architectures and their efficiency depending on parallelism exploited on algorithm or data or both.

Keywords: radar signal processing, multiprocessor architecture, efficiency, load imbalance, buffer requirement, pipeline, parallel, hybrid, cluster of processors (COPs)

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Authors: Yahaya Abdullahi, Ben Coetzee, Linda Van Den Berg

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The study aimed at establishing the global positioning system (GPS) determined singles match characteristics that act as predictors of successful and less-successful male singles badminton players’ group classification. Twenty-two (22) male single players (aged: 23.39 ± 3.92 years; body stature: 177.11 ± 3.06cm; body mass: 83.46 ± 14.59kg) who represented 10 African countries participated in the study. Players were categorised as successful and less-successful players according to the results of five championships’ of the 2014/2015 season. GPS units (MinimaxX V4.0), Polar Heart Rate Transmitter Belts and digital video cameras were used to collect match data. GPS-related variables were corrected for match duration and independent t-tests, a cluster analysis and a binary forward stepwise logistic regression were calculated. A Receiver Operating Characteristic Curve (ROC) was used to determine the validity of the group classification model. High-intensity accelerations per second were identified as the only GPS-determined variable that showed a significant difference between groups. Furthermore, only high-intensity accelerations per second (p=0.03) and low-intensity efforts per second (p=0.04) were identified as significant predictors of group classification with 76.88% of players that could be classified back into their original groups by making use of the GPS-based logistic regression formula. The ROC showed a value of 0.87. The identification of the last-mentioned GPS-related variables for the attainment of badminton performances, emphasizes the importance of using badminton drills and conditioning techniques to not only improve players’ physical fitness levels but also their abilities to accelerate at high intensities.

Keywords: badminton, global positioning system, match analysis, inertial movement analysis, intensity, effort

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Authors: Andrii Natochii

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The UA9 collaboration in the last two years has installed two different types of detectors to investigate the channeling effect in the bent silicon crystals with high-energy particles beam on the CERN accelerator facilities: Cherenkov detector CpFM and silicon pixel detector Timepix. In the current work, we describe the main performances of the Timepix detector operation at the SPS and H8 extracted beamline at CERN. We are presenting some detector calibration results and tuning. Our research topics also cover a cluster analysis algorithm for the particle hits reconstruction. We describe the optimal acquisition setup for the Timepix device and the edges of its functionality for the high energy and flux beam monitoring. The measurements of the crystal parameters are very important for the future bent crystal applications and needs a track reconstruction apparatus. Thus, it was decided to construct a short range (1.2 m long) particle telescope based on the Timepix sensors and test it at H8 SPS extraction beamline. The obtained results will be shown as well.

Keywords: beam monitoring, channeling, particle tracking, Timepix detector

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Authors: An Chengrui, Yin Zi, Wu Bingbing, Ma Yuanzhu, Jin Kaixiu, Chen Xiao, Ouyang Hongwei

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Single cell RNA sequence (scRNA-seq) is one of the effective tools to study transcriptomics of biological processes. Recently, similarity measurement of cells is Euclidian distance or its derivatives. However, the process of scRNA-seq is a multi-variate Bernoulli event model, thus we hypothesize that it would be more efficient when the divergence between cells is valued with relative entropy than Euclidian distance. In this study, we compared the performances of Euclidian distance, Spearman correlation distance and Relative Entropy using scRNA-seq data of the early, medial and late stage of limb development generated in our lab. Relative Entropy is better than other methods according to cluster potential test. Furthermore, we developed KL-SNE, an algorithm modifying t-SNE whose definition of divergence between cells Euclidian distance to Kullback–Leibler divergence. Results showed that KL-SNE was more effective to dissect cell heterogeneity than t-SNE, indicating the better performance of relative entropy than Euclidian distance. Specifically, the chondrocyte expressing Comp was clustered together with KL-SNE but not with t-SNE. Surprisingly, cells in early stage were surrounded by cells in medial stage in the processing of KL-SNE while medial cells neighbored to late stage with the process of t-SNE. This results parallel to Heatmap which showed cells in medial stage were more heterogenic than cells in other stages. In addition, we also found that results of KL-SNE tend to follow Gaussian distribution compared with those of the t-SNE, which could also be verified with the analysis of scRNA-seq data from another study on human embryo development. Therefore, it is also an effective way to convert non-Gaussian distribution to Gaussian distribution and facilitate the subsequent statistic possesses. Thus, relative entropy is potentially a better way to determine the divergence of cells in scRNA-seq data analysis.

Keywords: Single cell RNA sequence, Similarity measurement, Relative Entropy, KL-SNE, t-SNE

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Authors: Jair Servín-Aguilar, Yu Tang

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We address the problem of robust attitude tracking for agile satellites under unknown bounded torque disturbances using a double-gimbal variable-speed control-moment gyro (DGVSCMG) driven by a cluster of three permanent magnet synchronous motors (PMSMs). Uniform practical asymptotic stability is achieved at the torque control level first. The desired speed of gimbals and the acceleration of the spin wheel to produce the required torque are then calculated by a velocity-based steering law and tracked at the PMSM speed-control level by designing a speed-tracking controller with compensation for the vibration caused by eccentricity and imbalance due to mechanical imperfection in the DGVSCMG. Uniform practical asymptotic stability of the overall system is ensured by loan relying on the analysis of the resulting cascaded system. Numerical simulations are included to show the performance improvement of the proposed controller.

Keywords: agile satellites, vibration compensation, internal model, stability

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Authors: Rita Riekstina-Dolge, Zanda Kruma, Daina Karklina, Fredijs Dimins

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Apple juice is the main raw material for cider production. In this study apple juices obtained from 14 dessert and crab variety apples grown in Latvia were investigated. For all samples soluble solids, titratable acidity, pH and sugar content were determined. Crab apples produce more dry matter, total sugar and acid content compared to the dessert apples but it depends on the apple variety. Total sugar content of crab apple juices was 1.3 to 1.8 times larger than in dessert apple juices. Titratable acidity of dessert apple juices is in the range of 4.1g L-1 to 10.83g L-1 and in crab apple juices titratable acidity is from 7.87g L-1 to 19.6g L-1. Fructose was detected as the main sugar whereas glucose level varied depending on the variety. The highest titratable acidity and content of sugars was detected in ‘Cornelia’ apples juice.

Keywords: apple juice, hierarchical cluster analysis, sugars, titratable acidity

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Authors: Somayeh Akrami, Habib Onsori, Elham Tahmassebian

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Species of Anemone narcissiflora is belonged to Anemone genus of Ranunculaceae family. This species has two subspecies named narcissiflora and willdenowii which the latest is recorded in Iran in 2010. Some samples of A. narcissiflora is gathered from kuhkamar-zonouz region of East -Azerbaijan province, Iran to study the genetic diversity of the species by using RAPD molecular markers, and estimation of genetic diversity were evaluated with the using 10mer RAPD primers by PCR-RAPD method. 39 polymorphic bands were produced from the six primers used in this technique that the maximum band is related to the RP1 primer, the lowest band is related to the RP7 and the average band for all primers were 6.5 polymorphic bands. Cluster analysis of samples in done by UPGMA method in NTSYSpc 2.02 software. Dendrogram resulting from migrating bands showed that the studied samples can be divided into two groups. The first group includes samples with 1-2 flowers and the second group consists of two sub-groups which the first subgroup consists of samples with 3-5 flowers, and the second subgroup consists of samples with 6-7 flowers. The results of the comparison and analysis of the data obtained from RAPD technique and similarity matrix represents the genetic variation between collected samples. This study shows that RAPD markers can determine the polymorphisms between different genotypes of A. narcissiflora and their hybrids. So RAPD technique can serve as a suitable molecular method to determine the genetic diversity of samples.

Keywords: Anemone narcissiflora, genetic diversity, RAPD-PCR

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Authors: Nur Aziza Luxfiati

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Clustering is partitioning data sets into sub-sets or groups in such a way that elements certain properties have shared property settings with a high level of similarity within one group and a low level of similarity between groups. . The K-Means algorithm is one of thealgorithmsclustering as a grouping tool that is most widely used in scientific and industrial applications because the basic idea of the kalgorithm is-means very simple. In this research, applying the technique of clustering using the k-means algorithm as a method of solving the problem of national development imbalances between regions in Central Java Province based on macroeconomic indicators. The data sample used is secondary data obtained from the Central Java Provincial Statistics Agency regarding macroeconomic indicator data which is part of the publication of the 2019 National Socio-Economic Survey (Susenas) data. score and determine the number of clusters (k) using the elbow method. After the clustering process is carried out, the validation is tested using themethodsBetween-Class Variation (BCV) and Within-Class Variation (WCV). The results showed that detection outlier using z-score normalization showed no outliers. In addition, the results of the clustering test obtained a ratio value that was not high, namely 0.011%. There are two district/city clusters in Central Java Province which have economic similarities based on the variables used, namely the first cluster with a high economic level consisting of 13 districts/cities and theclustersecondwith a low economic level consisting of 22 districts/cities. And in the cluster second, namely, between low economies, the authors grouped districts/cities based on similarities to macroeconomic indicators such as 20 districts of Gross Regional Domestic Product, with a Poverty Depth Index of 19 districts, with 5 districts in Human Development, and as many as Open Unemployment Rate. 10 districts.

Keywords: clustering, K-Means algorithm, macroeconomic indicators, inequality, national development

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Authors: Josip Arneric, Blanka Skrabic Peric

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Forecasting of volatility, i.e. returns fluctuations, has been a topic of interest to portfolio managers, option traders and market makers in order to get higher profits or less risky positions. Based on the fact that volatility is time varying in high frequency data and that periods of high volatility tend to cluster, the most common used models are GARCH type models. As standard GARCH models show high volatility persistence, i.e. integrated behaviour of the conditional variance, it is difficult the predict volatility using standard GARCH models. Due to practical limitations of these models different approaches have been proposed in the literature, based on Markov switching models. In such situations models in which the parameters are allowed to change over time are more appropriate because they allow some part of the model to depend on the state of the economy. The empirical analysis demonstrates that Markov switching GARCH model resolves the problem of excessive persistence and outperforms uni-regime GARCH models in forecasting volatility for selected emerging markets.

Keywords: emerging markets, Markov switching, GARCH model, transition probabilities

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Authors: Mohammed Tahir, Jonas Lagergren

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Vancron 40, a nitrided powder metallurgical tool Steel, is used in cold work applications where the predominant failure mechanisms are adhesive wear or galling. Typical applications of Vancron 40 are among others fine blanking, cold extrusion, deep drawing and cold work rolls for cluster mills. Vancron 40 positive results for cold work rolls for cluster mills and as a tool for some severe metal forming process makes it competitive compared to other type of work rolls that require higher precision, among others in cold rolling of thin stainless steel, which required high surface finish quality. In this project, three roll materials for cold rolling of stainless steel strip was examined, Vancron 40, Narva 12B (a high-carbon, high-chromium tool steel alloyed with tungsten) and Supra 3 (a Chromium-molybdenum tungsten-vanadium alloyed high speed steel). The purpose of this project was to study the depth profiles of the ironed stainless steel strips, emergence of galling and to study the lubrication performance used by steel industries. Laboratory experiments were conducted to examine scratch of the strip, galling and surface roughness of the roll materials under severe tribological conditions. The critical sliding length for onset of galling was estimated for stainless steel with four different lubricants. Laboratory experiments result of performance evaluation of resistance capability of rolls toward adhesive wear under severe conditions for low and high reductions. Vancron 40 in combination with cold rolling lubricant gave good surface quality, prevents galling of metal surfaces and good bearing capacity.

Keywords: Vancron 40, cold rolling, adhesive wear, galling, surface finish, lubricant, stainless steel

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Authors: Othman E. Othman, Agnés Germot, Daniel Petit, Abderrahman Maftah

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Threats to the biodiversity are increasing due to the loss of genetic diversity within the species utilized in agriculture. Due to the progressive substitution of the less productive, locally adapted and native breeds by highly productive breeds, the number of threatened breeds is increased. In these conditions, it is more strategically important than ever to preserve as much the farm animal diversity as possible, to ensure a prompt and proper response to the needs of future generations. Mitochondrial (mtDNA) sequencing has been used to explain the origins of many modern domestic livestock species. Studies based on sequencing of sheep mitochondrial DNA showed that there are five maternal lineages in the world for domestic sheep breeds; A, B, C, D and E. Because of the eastern location of Egypt in the Mediterranean basin and the presence of fat-tailed sheep breeds- character quite common in Turkey and Syria- where genotypes that seem quite primitive, the phylogenetic studies of Egyptian sheep breeds become particularly attractive. We aimed in this work to clarify the genetic affinities, biodiversity and phylogeny of five Egyptian sheep breeds using cytochrome B sequencing. Blood samples were collected from 63 animals belonging to the five tested breeds; Barki, Rahmani, Ossimi, Saidi and Sohagi. The total DNA was extracted and the specific primer allowed the conventional PCR amplification of the cytochrome B region of mtDNA (approximately 1272 bp). PCR amplified products were purified and sequenced. The alignment of Sixty-three samples was done using BioEdit software. DnaSP 5.00 software was used to identify the sequence variation and polymorphic sites in the aligned sequences. The result showed that the presence of 34 polymorphic sites leading to the formation of 18 haplotypes. The haplotype diversity in five tested breeds ranged from 0.676 in Rahmani breed to 0.894 in Sohagi breed. The genetic distances (D) and the average number of pairwise differences (Dxy) between breeds were estimated. The lowest distance was observed between Rahmani and Saidi (D: 1.674 and Dxy: 0.00150) while the highest distance was observed between Ossimi and Sohagi (D: 5.233 and Dxy: 0.00475). Neighbour-joining (Phylogeny) tree was constructed using Mega 5.0 software. The sequences of the 63 analyzed samples were aligned with references sequences of different haplogroups. The phylogeny result showed the presence of three haplogroups (HapA, HapB and HapC) in the 63 examined samples. The other two haplogroups described in literature (HapD and HapE) were not found. The result showed that 50 out of 63 tested animals cluster with haplogroup B (79.37%) whereas 7 tested animals cluster with haplogroup A (11.11%) and 6 animals cluster with haplogroup C (9.52%). In conclusion, the phylogenetic reconstructions showed that the majority of Egyptian sheep breeds belonging to haplogroup B which is the dominant haplogroup in Eastern Mediterranean countries like Syria and Turkey. Some individuals are belonging to haplogroups A and C, suggesting that the crosses were done with other breeds for characteristic selection for growth and wool quality.

Keywords: cytochrome B, diversity, phylogheny, Egyptian sheep breeds

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Authors: Z. Abdullah, A. R. Hamdan

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Clustering is a process of grouping objects and data into groups of clusters to ensure that data objects from the same cluster are identical to each other. Clustering algorithms in one of the areas in data mining and it can be classified into partition, hierarchical, density based, and grid-based. Therefore, in this paper, we do a survey and review for four major hierarchical clustering algorithms called CURE, ROCK, CHAMELEON, and BIRCH. The obtained state of the art of these algorithms will help in eliminating the current problems, as well as deriving more robust and scalable algorithms for clustering.

Keywords: clustering, unsupervised learning, algorithms, hierarchical

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Authors: Sa’adu Mafara Abubakar, Muhammad Nuraddeen Danjuma, Adewole Tomiwa Adetunji, Richard Mundembe, Salisu Mohammed, Francis Bayo Lewu, Joseph I. Kiok

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Pearl millet is the most drought tolerant of all domesticated cereals, is cultivated extensively to feed millions of people who mainly live in hash agroclimatic zones. It serves as a major source of food for more than 40 million smallholder farmers living in the marginal agricultural lands of Northern Nigeria. Pearl millet grain is more nutritious than other cereals like maize, is also a principal source of energy, protein, vitamins, and minerals for millions of poorest people in the regions where it is cultivated. Pearl millet has recorded relatively little research attention compared with other crops and no sufficient work has analyzed its genetic diversity in north-western Nigeria. Therefore, this study was undertaken with the objectives to analyze the genetic diversity of pearl millet accessions using SSR marker and to analyze the extent of evolutionary relationship among pearl millet accessions at the molecular level. The result of the present study confirmed diversity among accessions of pearl millet in the study area. Simple Sequence Repeats (SSR) markers were used for genetic analysis and evolutionary relationship of the accessions of pearl millet. To analyze the level of genetic diversity, 8 polymorphic SSR markers were used to screen 69 accessions collected based on three maturity periods. SSR markers result reveal relationships among the accessions in terms of genetic similarities, evolutionary and ancestral origin, it also reveals a total of 53 alleles recorded with 8 microsatellites and an average of 6.875 per microsatellite, the range was from 3 to 9 alleles in PSMP2248 and PSMP2080 respectively. Moreover, both the factorial analysis and the dendrogram of phylogeny tree grouping patterns and cluster analysis were almost in agreement with each other that diversity is not clustering according to geographical patterns but, according to similarity, the result showed maximum similarity among clusters with few numbers of accessions. It has been recommended that other molecular markers should be tested in the same study area.

Keywords: pearl millet, genetic diversity, simple sequence repeat (SSR)

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Authors: Murtala Sale

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The use of instructional materials is an indispensable tool that enhances qualitative teaching and learning especially at the primary level. Instructional materials are used to facilitate comprehension of ideas in the learners as well as ensure long term retention of ideas and topics taught to pupils. This study examined the relevance of using instructional materials in primary schools in Katsina State, Nigeria. It employed survey design using cluster sampling technique. The questionnaire was used to gather data for analysis, and statistical and frequency tables were used to analyze the data gathered. The results show that teachers and students alike have realized the effectiveness of modern instructional materials in teaching and learning for the attainment of set objectives in the basic primary education policy. It also discovered that reluctance in the use of instructional materials will hamper the achievement of qualitative primary education. The study therefore suggests that there should be the provision of adequate and up-to-date instructional materials to all primary schools in Katsina State for effective teaching and learning process.

Keywords: instructional materials, effective teaching, learning quality, indispensable aspect

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Authors: Chang-Fa Liu, Yi-Ting Wang, Yuan Liu, Hai-Feng Wei, Lei Fang, Jin Li

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Heavy metals in sediments can cause adverse ecological effects while it exceeds a given criteria. The present study investigated sediment environmental quality, pollutant enrichment, ecological risk, and source identification for copper, cadmium, lead, zinc, mercury, and arsenic in the sediments collected from tidal flat marsh of Shuangtai estuary, China. The arithmetic mean integrated pollution index, geometric mean integrated pollution index, fuzzy integrated pollution index, and principal component score were used to characterize sediment environmental quality; fuzzy similarity and geo-accumulation Index were used to evaluate pollutant enrichment; correlation matrix, principal component analysis, and cluster analysis were used to identify source of pollution; environmental risk index and potential ecological risk index were used to assess ecological risk. The environmental qualities of sediment are classified to very low degree of contamination or low contamination. The similar order to element background of soil in the Liaohe plain is region of Sanjiaozhou, Honghaitan, Sandaogou, Xiaohe by pollutant enrichment analysis. The source identification indicates that correlations are significantly among metals except between copper and cadmium. Cadmium, lead, zinc, mercury, and arsenic will be clustered in the same clustering as the first principal component. Copper will be clustered as second principal component. The environmental risk assessment level will be scaled to no risk in the studied area. The order of potential ecological risk is As > Cd > Hg > Cu > Pb > Zn.

Keywords: ecological risk assessment, heavy metals, sediment, marsh, Shuangtai estuary

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Authors: Niloofar Hooman

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The present study aims at investigating the positive and negative effects of using Smartphones on couples committed relationships. Despite the fact that many couples may benefit from the positive aspects of Smartphones, it is not clear how their feeling of trust, intimacy and connection in their relationships get affected by Smartphones. This is important as it highlights the ambivalent influences of Smartphones on couple’s relationships. On the one hand, Smartphones can enhance their social and emotional interactions and on the other hand, they can cause mistrust and isolation between them. Trust, intimacy and honesty are of important factors through which a stable relationship can be constructed. Nevertheless, some characteristics of Smartphones such as being fluid and personalized can harm the relationship and consequently destroy it. Thus, it is necessary to investigate how Iranian couples in committed relationships use Smartphone to manage their relationship and how couples feel Smartphone have enhanced or detracted a sense of trust, intimacy and connection with their partner? In the first phase of the study, in-depth-interview will be conducted with 30 couples and data will be analyzed using NVIVO software. In the next phase of the study, 1500 participants aged 20 and above will be selected based on cluster sampling. Data will be analyzed both qualitatively and quantitatively.

Keywords: couple, family, internet, intimacy, Smartphone, trust

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Authors: Wanida Suwunniponth

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This research paper aimed to developing a causal relationship model of success factors of customer relationship management of tourism in Thailand and to investigating relationships among the potential factors that facilitate the success of customer relationship management (CRM). The research was conducted in both quantitative and qualitative methods, by utilizing both questionnaire and in-depth interview. The questionnaire was used in collecting the data from 250 management staff in the hotels located within Bangkok area. Sampling techniques used in this research included cluster sampling according to the service quality and simple random sampling. The data input was analyzed by use of descriptive analysis and System Equation Model (SEM). The research findings demonstrated important factors accentuated by most respondents towards the success of CRM, which were organization, people, information technology and the process of CRM. Moreover, the customer relationship management of tourism business in Thailand was found to be successful at a very significant level. The hypothesis testing showed that the hypothesis was accepted, as the factors concerning with organization, people and information technology played an influence on the process and the success of customer relationship management, whereas the process of customer relationship management factor manipulated its success. The findings suggested that tourism business in Thailand with the implementation of customer relationship management should opt in improvement approach in terms of managerial structure, corporate culture building with customer- centralized approach accentuated, and investment of information technology and customer analysis, in order to capacitate higher efficiency of customer relationship management process that would result in customer satisfaction and retention of service.

Keywords: customer relationship management, casual relationship model, tourism, Thailand

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Authors: Shamsa Al Sharji, Athar Al Jabri, Haitham Al Dughaishi, Mirfat Al Barwani, Raja Al Rawahi, Raiya Al Rajhi, Shurooq Al Ruqaishi, Thamreen Al Zadjali, Iman Al Humaidi

Abstract:

Background: External Ventricular Drains (EVDs) are critical in managing traumatic brain injuries and hydrocephalus by controlling intracranial pressure, but they carry a high risk of infection. Infection rates vary globally, ranging from 5% to 45%, leading to increased morbidity, prolonged hospital stays, and higher healthcare costs. Nursing protocols play a pivotal role in reducing these infection rates. This study investigates the impact of a structured nursing protocol on EVD-associated infections in adult neurosurgery patients at the Directorate General of Khoula Hospital, Oman, from January to September 2024. Methods: A cluster-randomized trial was conducted across neurosurgery wards and the ICU. The intervention group followed a comprehensive nursing protocol, including strict sterile insertion, standardized dressing changes, infection control training, and regular clinical audits. The control group received standard care. The primary outcome was the incidence of EVD-associated infections, with secondary outcomes including protocol compliance, infection severity, recovery times, length of stay, and 30-day mortality. Statistical analysis was conducted using Chi-square tests, paired t-tests, and logistic regression to assess the differences between groups. Results: The study involved 75 patients, with an overall infection rate of 13.3%. The intervention group showed a reduced infection rate of 8.9% compared to 20% in the control group. Compliance rates for key nursing actions were high, with 89.7% for hand hygiene and 86.2% for wound dressing. The relative risk of infection was 0.44 in the intervention group, reflecting a 55.6% reduction. Logistic regression identified obesity as a significant predictor of EVD infections. Although mortality rates were slightly higher in the intervention group, the number needed to treat (NNT) of 9 suggests that the nursing protocol may improve survival outcomes. Conclusion: This study demonstrates that structured nursing protocols can reduce EVD-related infections and improve patient outcomes in neurosurgery. While the findings are promising, further research with larger sample sizes is needed to confirm these results and optimize infection control strategies in neurosurgical care.

Keywords: EVD, CSF, nursing protocol, EVD infection

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Authors: H. S. Saini, K. Vijayalakshmi, Rishi Sayal

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Network-based education has been growing rapidly in size and quality. Knowledge clustering becomes more important in personalized information retrieval for web-learning. A personalized-Learning service after the learners’ knowledge has been classified with clustering. Through automatic analysis of learners’ behaviors, their partition with similar data level and interests may be discovered so as to produce learners with contents that best match educational needs for collaborative learning. We present a specific mining tool and a recommender engine that we have integrated in the online learning in order to help the teacher to carry out the whole e-learning process. We propose to use sequential pattern mining algorithms to discover the most used path by the students and from this information can recommend links to the new students automatically meanwhile they browse in the course. We have Developed a specific author tool in order to help the teacher to apply all the data mining process. We tend to report on many experiments with real knowledge so as to indicate the quality of using both clustering and sequential pattern mining algorithms together for discovering personalized e-learning systems.

Keywords: e-learning, cluster, personalization, sequence, pattern

Procedia PDF Downloads 427