Search results for: K-means cluster analysis

Authors: Brigitta Szabo, Miklosi Monika

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Background/Aims: In early childhood, the context of development is the caregiver-child relationship. Maternal attachment style plays a major role in the intergenerational transmission of psychopathology. The aim of this study was to explore the relationship between the mothers’ attachment style, mindful parenting, and perception of the child. Method: Data was collected from 144 non-clinical mothers who have a child below the age of 3 years. Mothers completed self-report questionnaires, including the following scales: a demographic questionnaire, Attachment Style Questionnaire (ASQ), Interpersonal Mindfulness in Parenting Scale (IMP), and the Mothers’ Object Relations Scale (MORS-SF). K-means cluster analysis was used to identify the mothers’ attachment styles. Mediation analyses with Mothers’ Object Relations Scale (MORS-SF) positive emotions and dominance subscales as dependent variables, mothers’ attachment style (ASQ) as an independent variable, and mindful parenting (IMP) as a mediator were conducted. Results: Four attachment styles (secure, preoccupied, fearful, dismissing) were identified. The relationship between mothers’ attachment style and mindful parenting was significant (R2 = .51; F(4,139) = 36.60; p < .001). Compared to the secure attachment style as a reference group, both preoccupied and dismissing styles were related to lower levels of mindful parenting; however, this relationship was the strongest in case of fearful style. In mediation analysis the direct effects of mothers’ attachment style on the perception of the child were not significant (MORS positive emotions: R2= .29; F(5,138) = 11.22; p < .001; MORS dominance: R2= .39 F(5,138) = 17.54, p < .001). However, indirect effects through mindful parenting were significant; higher levels of mindful parenting were associated with higher levels of MORS positive emotions and lower levels of MORS dominance. Conclusions: These findings suggest that attachment styles are related to the perception of the child through mindful parenting. Mindfulness-based parenting training might be useful in case of attachment-related problems to improve the parent-child relationship.

Keywords: mindfulness, mindful parenting, attachement, perception

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Authors: David Ahiamadia, Ramilan Thiagarajah, Peter Tozer

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In Sub Saharan Africa, farm typologies have been used as a practical way to address heterogeneity among farming systems which is mostly done by grouping farms into subsets with similar characteristics. Due to the complexity in farming systems among farm households, it is not possible to formulate policy recommendations for individual farmers. As a result, this study employs a multivariate statistical approach using Principal Component Analysis (PCA) coupled with cluster analysis to reduce heterogeneity in a 615-household data set from the Africa Rising Baseline Evaluation Survey for 25 farming communities in Northern Ghana. Variables selected for the study were mostly socio-economic, production potential, production intensity, production orientation, crop diversity, food security, resource endowments, and climate risk variables. To avoid making some individuals in the subpopulation worse off when aclimate risk intervention is broadly implemented, the findings of the study also account for diversity in climate risk perception among the different farm types identified and their response strategies towards climate risk. The climate risk variables used in this study involve the most severeclimate shock types perceived by the household, household response to climate shock type, and reason for crop failure (i.e., maize, rice, and groundnut). Eventually, four farm types, each with an adequate level of homogeneity in climate risk perception and response strategies, were identified. Farm type 1 and 3 were wealthy with a lower degree of climate risk perception compared to farm type 2 and 4. Also, relatively wealthy farmers used asset liquidation as a climate risk management strategy, whereas poor farmers resorted to engaging in spiritual activities such as prayers, sacrifices, and divine consultations.

Keywords: smallholder, households, climate risk, variables, typologies

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Authors: Raees Khan, Sheikh Z. Ul Abidin, Abdul S. Mumtaz, Jie Liu

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The present study is intended to assess gymnosperms pollen flora of Pakistan using Light Microscope (LM) and Scanning Electron Microscopy (SEM) for its taxonomic significance in identification of gymnosperms. Pollens of 35 gymnosperm species (12 genera and five families) were collected from its various distributional sites of gymnosperms in Pakistan. LM and SEM were used to investigate different palyno-morphological characteristics. Five pollen types (i.e., Inaperturate, Monolete, Monoporate, Vesiculate-bisaccate, and Polyplicate) were observed. In equatorial view seven types of pollens were observed, in which ten species were sub-angular, nine species were triangular, six species were perprolate, three species were rhomboidal, three species were semi-angular, two species were rectangular and two species were prolate. While five types of pollen were observed in polar view, in which ten species were spheroidal, nine species were angular, eight were interlobate, six species were circular, and two species were elliptic. Eighteen species have rugulate and 17 species has faveolate ornamentation. Eighteen species have verrucate and 17 have gemmate type sculpturing. The data was analysed through cluster analysis. The study showed that these palyno-morphological features have significance value in classification and identification of gymnosperms. Based on these different palyno-morphological features, a taxonomic key was proposed for the accurate and fast identifications of gymnosperms from Pakistan.

Keywords: gymnosperms, palynology, Pakistan, taxonomy

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Authors: Alireza Sohrabi, Hamid Mohammadi

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The pistachio fruit is a strategic product in Iran. One of the problems caused the reduction of pistachio proceeds is related to biennial- bearing or alternative bearing. Biennial- bearing is very important and is happened because of the fallen female bloom buds in vintage year. This test was done according to random blocks of 6 orchards in the type of Ahmad Aghaie with 4 iterations. Vegetative properties of branch are investigated. The results are shown that if the bunch numbers are increased, the possibility of falling is increased in bloom buds. The least possibility of falling of bloom buds is specified in trimming of one bunch and has significant difference with other trimming.

Keywords: alternate bearing, pistachio, cluster, bud

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Authors: Hamidreza Fallah Lajimi, Elham Karami, Alireza Arab, Fatemeh Alinasab

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Being responsive is an increasingly important skill for firms in today’s global economy; thus firms must be agile. Naturally, it follows that an organization’s agility depends on its supply chain being agile. However, achieving supply chain agility is a function of other abilities within the organization. This paper analyses results from a survey of 71 Iran manufacturing companies in order to identify some of the factors for agile organizations in managing their supply chains. Then we classification this company in four cluster with fuzzy c-mean technique and with Four validations functional determine automatically the optimal number of clusters.

Keywords: agile supply chain, clustering, fuzzy clustering, business engineering

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Authors: Gaoyuan Wang, Tian Chen

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China’s emission peak and carbon neutrality strategies lead to the transformation of development patterns and call for new green urban design thinking. This paper begins by revealing the evolution of green urban design thinking during the periods of carbon enlightenment, carbon dependency, and carbon decoupling from the perspective of the energy transition. Combined with the current energy situation, national strengths, and technological trends, the emergence of green urban design towards carbon neutrality becomes inevitable. Based on the preliminary analysis of its connotation, the characteristics of the new type of green urban design are generalized as low-carbon orientation, carbon-related objects, carbon-reduction means, and carbon-control patterns. Its theory is briefly clarified in terms of the human-earth synergism, quality-energy interconnection, and form-flow interpromotion. Then, its mechanism is analyzed combined with the core tasks of carbon neutrality, and the scope of design issues is defined, including carbon flow mapping, carbon source regulation, carbon sink construction, and carbon emission management. Finally, a multi-scale spatial response system is proposed across the region, city, cluster, and neighborhood level. The discussion aims to provide support for the innovation of green urban design theories and methods in the context of peak neutrality.

Keywords: carbon neutrality, green urban design, energy transition, theoretical exploration

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Authors: Maryam Mousavi Nik, Sara Pasandian

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The aim of the current research was to determine the effectiveness of Cognitive-Behavioral Group Therapy (G-CBT) on stress, illness anxiety and obsessions-compulsion caused by the coronavirus crisis in adolescents (14-18-Year-olds) in Tehran, Iran. This research was carried out in the form of a semi-experimental study with a control group and in the framework of a pre-test and post-test design for both experimental and control groups. The statistical population of this research consisted of all high schools in Tehran in 2022. The sample size includes 32 Adolescents (14-18-Year-olds) who were selected using a cluster sampling method, and then they were randomly replaced in two experimental (n=16) and control (n=16) groups. In this research, an adolescent stress questionnaire (ASQ-N) with an emphasis on the impact of Coronavirus, Coronavirus disease anxiety (CDAS) and The Children's Yale-Brown Obsessive Compulsive Symptom Scale (CY-BOCS) emphasis on the Coronavirus were used, and group therapy intervention with The cognitive-behavioral approach was conducted for 8 sessions of 90 minutes in the experimental group. The research data were analyzed by Multivariate analysis of covariance (MANCOVA) and covariance (ANCVA) tests. The results of multivariate covariance analysis showed that group therapy intervention with a cognitive-behavioral approach had a significant effect on at least one of the variables of stress, illness anxiety and obsession-compulsion at the level (P<0.01, F=94.772) in the post-test stage. Also, the results of covariance analysis of one variable showed that group therapy intervention with a cognitive-behavioral approach in the level of (P<0.01, F=106.377) stress, in the level of (P<0.01, F=48.147) disease anxiety and in the level (P>0.01, F=17.033) of obsession-compulsion had a significant effect in the post-test stage. The results showed that The treatment with GCBT can be effective in decreasing stress, illness anxiety and obsessions and compulsion caused by the coronavirus crisis in Adolescents (15-20-Year-olds) and may be considered as an alternative to either individual cognitive-behavioral therapy or medication.

Keywords: stress, disease anxiety, obsession-compulsion, coronavirus (Covid-19) crisis, and cognitive-behavioral therapy

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Authors: Maria Lopez-Ibarra, Ana Velazquez-Wong, Lucelli Yañez-Gutierrez, Maria Araujo-Solis, Fabio Salamanca-Gomez, Alfonso Mendez-Tenorio, Haydeé Rosas-Vargas

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Congenital heart diseases (CHD) are the most common congenital abnormalities. These conditions can occur as both an element of distinct chromosomal malformation syndromes or as non-syndromic forms. Their etiology is not fully understood. Genetic variants such copy number variants have been associated with CHD. The aim of our study was to analyze these genomic variants in peripheral blood from Mexican children diagnosed with non-syndromic CHD. We included 16 children with atrial and ventricular septal defects and 5 healthy subjects without heart malformations as controls. To exclude the most common heart disease-associated syndrome alteration, we performed a fluorescence in situ hybridization test to identify the 22q11.2, responsible for congenital heart abnormalities associated with Di-George Syndrome. Then, a microarray based comparative genomic hybridization was used to identify global copy number variants. The identification of copy number variants resulted from the comparison and analysis between our results and data from main genetic variation databases. We identified copy number variants gain in three chromosomes regions from pediatric patients, 4q13.2 (31.25%), 9q34.3 (25%) and 20q13.33 (50%), where several genes associated with cellular, biosynthetic, and metabolic processes are located, UGT2B15, UGT2B17, SNAPC4, SDCCAG3, PMPCA, INPP6E, C9orf163, NOTCH1, C20orf166, and SLCO4A1. In addition, after a hierarchical cluster analysis based on the fluorescence intensity ratios from the comparative genomic hybridization, two congenital heart disease groups were generated corresponding to children with atrial or ventricular septal defects. Further analysis with a larger sample size is needed to corroborate these copy number variants as possible biomarkers to differentiate between heart abnormalities. Interestingly, the 20q13.33 gain was present in 50% of children with these CHD which could suggest that alterations in both coding and non-coding elements within this chromosomal region may play an important role in distinct heart conditions.

Keywords: aCGH, bioinformatics, congenital heart diseases, copy number variants, fluorescence in situ hybridization

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Authors: Hussaini Tunde Subairu

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Small and Medium Enterprises (SMEs) sectors serve as catalyst for employment generation, national growth, poverty reduction and economic development in developing and developed countries. However, in Nigeria despite copious and plethora of government policies and stimulus schemes directed at SMEs, the sector is still characterized by high rate of failure and discontinuities. This study therefore investigated owners/managers profile, firms characteristics and external factors as possible determinants of SMEs growth from selected SMEs in Kwara State. Primary data were sourced from 200 SMEs respondents registered with the National Association of Small and Medium Enterprises (NASMES) in Kwara State Central Senatorial District. Multiple Regressions Analysis (MRA) was used to analyze the relationship between dependent and independent variables, and pair wise correlation was employed to examine the relationship among independent variables. The Analysis of Variable (ANOVA) was employed to indicate the overall significant of the model The findings revealed that Analysis of variance (ANOVA) put the value of F-statistics at 420.45 and p-value at 0.000 was significant. The values of R2 and Adjusted R2 of 0.9643 and 0.9620 respectively suggested that 96 percent of variations in employment growth were explained by the explanatory variables. The level of technical and managerial education has t- value of 24.14 and p-value of 0.001, length of managers/owners experience in similar trade with t- value of 21.37 and p-value of 0.001, age of managers/owners with t- value of 42.98 and p-value of 0.001, firm age with t- value of 25.91 and p-value of 0.001, numbers of firms in a cluster with t- value of 7.20 and p-value of 0.001, access to formal finance with t-value of 5.56 and p-value of 0.001, firm technology innovation with t- value of 25.32 and p-value of 0.01, institutional support with t- value of 18.89 and p-value of 0.01, globalization with t- value of 9.78 and p-value of 0.01, and infrastructure with t-value of 10.75 and p-value of 0.01. The result also indicated that initial size has t-value of -1.71 and p-value of 0.090 which is consistent with Gibrat’s Law. The study concluded that owners/managers profile, firm specific characteristics and external factors substantially influenced employment growths of SMEs in the study area. Therefore, policy implication should enhance human capital development of SMEs owners/managers, and strengthen fiscal policy thrust through imposition on tariff regime to minimize effect of globalization. Governments at all level must support SMEs growth radically and enhance institutional support for SMEs growth and radically and significantly upgrading key infrastructure as rail/roads, rail, telecommunications, water and power.

Keywords: external factors, firm specific characteristics, owners / manager profile, small and medium enterprises

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Authors: Seyyedeh Faezeh Hassani Ziabari, Sadegh Eskandari, Maziar Salahi

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Infinite Feature Selection (IFS) algorithm is an efficient feature selection algorithm that selects a subset of features of all sizes (including infinity). In this paper, we present an improved version of it, called clustering IFS (CIFS), by clustering the dataset in advance. To do so, first, we apply the K-means algorithm to cluster the dataset, then we apply IFS. In the CIFS method, the spatial and temporal complexities are reduced compared to the IFS method. Experimental results on 6 datasets show the superiority of CIFS compared to IFS in terms of accuracy, running time, and memory consumption.

Keywords: feature selection, infinite feature selection, clustering, graph

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Authors: Chia-Chen Wu, Chih-Fu Wu, Pey-Weng Lien, Kai-Chieh Lin

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In the past, the most comprehensively adopted light source was incandescent light bulbs, but with the appearance of LED light sources, traditional light sources have been gradually replaced by LEDs because of its numerous superior characteristics. However, many of the standards do not apply to LEDs as the two light sources are characterized differently. This also intensifies the significance of studies on LEDs. As a Kansei design study investigating the visual glare produced by traffic arrows implemented with LEDs, this study conducted a semantic analysis on the styles of traffic arrows used in domestic and international occasions. The results will be able to reduce drivers’ misrecognition that results in the unsuccessful arrival at the destination, or in traffic accidents. This study started with a literature review and surveyed the status quo before conducting experiments that were divided in two parts. The first part involved a screening experiment of arrow samples, where cluster analysis was conducted to choose five representative samples of LED displays. The second part was a semantic experiment on the display of arrows using LEDs, where the five representative samples and the selected ten adjectives were incorporated. Analyzing the results with Quantification Theory Type I, it was found that among the composition of arrows, fletching was the most significant factor that influenced the adjectives. In contrast, a “no fletching” design was more abstract and vague. It lacked the ability to convey the intended message and might bear psychological negative connotation including “dangerous,” “forbidden,” and “unreliable.” The arrow design consisting of “> shaped fletching” was found to be more concrete and definite, showing positive connotation including “safe,” “cautious,” and “reliable.” When a stimulus was placed at a farther distance, the glare could be significantly reduced; moreover, the visual evaluation scores would be higher. On the contrary, if the fletching and the shaft had a similar proportion, looking at the stimuli caused higher evaluation at a closer distance. The above results will be able to be applied to the design of traffic arrows by conveying information definitely and rapidly. In addition, drivers’ safety could be enhanced by understanding the cause of glare and improving visual recognizability.

Keywords: LED, arrow, Kansei research, preferred imagery

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Authors: Hillary Onyeka Abugu, Valentine Chinakwugwo Ezea, Janefrances Ngozi Ihedioha, Nwachukwu Romanus Ekere

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The study assessed the spring water quality in Igbo-Etiti, Nigeria, for drinking and irrigation application using Physico-chemical parameters, water quality index, mineral and trace elements, pollution indices and risk assessment. Standard methods were used to determine the physicochemical properties of the spring water in rainy and dry seasons. Trace metals such as Pb, Cd, Zn and Cu were determined with atomic absorption spectrophotometer. The results showed that most of the physicochemical properties studied were within the guideline values set by Nigeria Standard for Drinking Water Quality (NSDWQ), WHO and US EPA for drinking water purposes. However, pH of all the spring water (4.27- 4.73; and 4.95- 5.73), lead (Pb) (0.01-1.08 mg/L) and cadmium (Cd) (0.01-0.15 mg/L) concentrations were above the guideline values in both seasons. This could be attributed to the lithography of the study area, which is the Nsukka formation. Leaching of lead and sulphides from the embedded coal deposits could have led to the increased lead levels and made the water acidic. Two-way ANOVA showed significant differences in most of the parameters studied in dry and rainy seasons. Pearson correlation analysis and cluster analysis showed strong significant positive and negative correlations in some of the parameters studied in both seasons. The water quality index showed that none of the spring water had excellent water status. However, one spring (Iyi Ase) had poor water status in dry season and is considered unsafe for drinking. Iyi Ase was also considered not suitable for irrigation application as predicted by most of the pollution indices, while others were generally considered suitable for irrigation application. Probable cancer and non-cancer risk assessment revealed a probable risk associated with the consumption of the spring in the Igbo-Ettiti area, Nigeria.

Keywords: water quality, pollution index, risk assessment, physico-chemical parameters

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Authors: Thayalan Nall, Andreas Putra

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A major offshore reclamation work is currently underway in Southeast Asia for a container terminal. The total extent of the reclamation extent is 2600m x 800m and the seabed level is around -5mRL below mean sea level. Subsoil profile below seabed comprises soft marine clays of thickness varying from 8m to 15m. To contain the dredging spoil within the reclamation area, perimeter bunds have been constructed to +2.5mRL. They include breakwaters of trapezoidal geometry, made of boulder size rock along the northern, eastern and western perimeters, with a sand bund along the southern perimeter. Breakwaters were constructed on a composite bamboo pile and raft foundation system. Bamboo clusters 8m long, with 7 individual Bamboos bundled together as one, have been installed within the footprint of the breakwater below seabed in soft marine clay. To facilitate drainage two prefabricated vertical drains (PVD) have been attached to each cluster. Once the cluster piles were installed, a bamboo raft was placed as a load transfer platform. Rafts were made up of 5 layers of bamboo mattress, and in each layer bamboos were spaced at 200mm centres. The rafts wouldn’t sink under their own weight, and hence, they were sunk by loading quarry run rock onto them. Bamboo is a building material available in abundance in Indonesia and obtained at a relatively low cost. They are commonly used as semi-rigid inclusions to improve compressibility and stability of soft soils. Although bamboo is widely used in soft soil engineering design, no local design guides are available and the designs are carried out based on local experience. In June 2015, when the 1st load of sand was pumped by a dredging vessel next to the breakwater, a 150m long section of the breakwater underwent failure and displaced the breakwater between 1.2m to 4.0m. The cause of the failure was investigated to implement remedial measures to reduce the risk of further failures. Analyses using both limit equilibrium approach and finite element modelling revealed two plausible modes of breakwater failure. This paper outlines: 1) Developed Geology and the ground model, 2) The techniques used for the installation of bamboo piles, 3) Details of the analyses including modes and mechanism of failure and 4) Design changes incorporated to reduce the risk of failure.

Keywords: bamboo piles, ground improvement, reclamation, breakwater failure

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Authors: Faheema Khan

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To investigate the ability of sensitive and tolerant genotype of Glycine max to adapt to a saline environment in a field, we examined the growth performance, water relation and activities of antioxidant enzymes in relation to photosynthetic rate, chlorophyll a fluorescence, photosynthetic pigment concentration, protein and proline in plants exposed to salt stress. Ten soybean genotypes (Pusa-20, Pusa-40, Pusa-37, Pusa-16, Pusa-24, Pusa-22, BRAGG, PK-416, PK-1042, and DS-9712) were selected and grown hydroponically. After 3 days of proper germination, the seedlings were transferred to Hoagland’s solution (Hoagland and Arnon 1950). The growth chamber was maintained at a photosynthetic photon flux density of 430 μmol m−2 s−1, 14 h of light, 10 h of dark and a relative humidity of 60%. The nutrient solution was bubbled with sterile air and changed on alternate days. Ten-day-old seedlings were given seven levels of salt in the form of NaCl viz., T1 = 0 mM NaCl, T2=25 mM NaCl, T3=50 mM NaCl, T4=75 mM NaCl, T5=100 mM NaCl, T6=125 mM NaCl, T7=150 mM NaCl. The investigation showed that genotype Pusa-24, PK-416 and Pusa-20 appeared to be the most salt-sensitive. genotypes as inferred from their significantly reduced length, fresh weight and dry weight in response to the NaCl exposure. Pusa-37 appeared to be the most tolerant genotype since no significant effect of NaCl treatment on growth was found. We observed a greater decline in the photosynthetic variables like photosynthetic rate, chlorophyll fluorescence and chlorophyll content, in salt-sensitive (Pusa-24) genotype than in salt-tolerant Pusa-37 under high salinity. Numerous primers were verified on ten soybean genotypes obtained from Operon technologies among which 30 RAPD primers shown high polymorphism and genetic variation. The Jaccard’s similarity coefficient values for each pairwise comparison between cultivars were calculated and similarity coefficient matrix was constructed. The closer varieties in the cluster behaved similar in their response to salinity tolerance. Intra-clustering within the two clusters precisely grouped the 10 genotypes in sub-cluster as expected from their physiological findings.Salt tolerant genotype Pusa-37, was further analysed by 2-Dimensional gel electrophoresis to analyse the differential expression of proteins at high salt stress. In the Present study, 173 protein spots were identified. Of these, 40 proteins responsive to salinity were either up- or down-regulated in Pusa-37. Proteomic analysis in salt-tolerant genotype (Pusa-37) led to the detection of proteins involved in a variety of biological processes, such as protein synthesis (12 %), redox regulation (19 %), primary and secondary metabolism (25 %), or disease- and defence-related processes (32 %). In conclusion, the soybean plants in our study responded to salt stress by changing their protein expression pattern. The photosynthetic, biochemical and molecular study showed that there is variability in salt tolerance behaviour in soybean genotypes. Pusa-24 is the salt-sensitive and Pusa-37 is the salt-tolerant genotype. Moreover this study gives new insights into the salt-stress response in soybean and demonstrates the power of genomic and proteomic approach in plant biology studies which finally could help us in identifying the possible regulatory switches (gene/s) controlling the salt tolerant genotype of the crop plants and their possible role in defence mechanism.

Keywords: glycine max, salt stress, RAPD, genomic and proteomic variability

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Authors: Manoj K. Sharma, Neha Grover

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Dynamical cluster decay model (DCM) is applied to study the decay mechanism of 118Xe* nucleus in reference to recent data on 28Si + 90Zr → 118Xe* reaction, as an extension of our previous work on the dynamics of 112Xe* nucleus. It is relevant to mention here that DCM is based on collective clusterization approach, where emission probability of different decay paths such as evaporation residue (ER), intermediate mass fragments (IMF) and fission etc. is worked out on parallel scale. Calculations have been done over a wide range of center of mass energies with Ec.m. = 65 - 92 MeV. The evaporation residue (ER) cross-sections of 118Xe* compound nucleus are fitted in reference to available data, using spherical and quadrupole (β2) deformed choice of decaying fragments within the optimum orientations approach. It may be noted that our calculated cross-sections find decent agreement with experimental data and hence provide an opportunity to analyze the exclusive role of deformations in view of fragmentation behavior of 118Xe* nucleus. The possible contribution of IMF fragments is worked out and an extensive effort is being made to analyze the role of excitation energy, angular momentum, diffuseness parameter and level density parameter to have better understanding of the decay patterns governed in the dynamics of 28Si + 90Zr → 118Xe* reaction.

Keywords: cross-sections, deformations, fragmentation, angular momentum

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Authors: Sresha Yadav, Ishwar Kumar

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Second language learning is an important area of research in the language and linguistic domains. Literature suggests that several factors impact second language learning, including age, motivation, objectives, teacher, instructional material, classroom interaction, intelligence and previous background, previous linguistic experience, other student characteristics. Previous researchers have also highlighted that classroom atmospherics has a significant impact on learning as well as on the performance of students. However, the impact of classroom atmospherics on second language learning is still not known in the existing literature. Therefore, the purpose of the present study is to explore whether classroom atmospherics has an impact on second language learning or not? And if it does, it would be worthwhile to explore the nature of such relationship. The present study aims to explore the impact of classroom atmospherics on second language learning by dwelling into the existing literature to explore factors which impact second language learning, classroom atmospherics which impact language learning and the metrics through which such learning impacts could be measured. Based on the findings of literature review, the researchers have adopted a clustering approach for categorization and positioning of various measures of second language learning. Based on the clustering approach, the researchers have approach for measuring the impact of classroom atmospherics on second language learning by drawing a student sample consisting of 80 respondents. The results of the study uncover various basic premises of second language learning, especially with regard to classroom atmospherics. The present study is important not only from the point of view of language learning but implications could be drawn with regard to the design of classroom atmospherics, environmental psychology, anthropometrics, etc as well.

Keywords: classroom atmospherics, cluster analysis, linguistics, second language learning

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Authors: Chen Guo, Heng Tang, Ben Niu

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Clustering splits objects into different groups based on similarity, making the objects have higher similarity in the same group and lower similarity in different groups. Thus, clustering can be treated as an optimization problem to maximize the intra-cluster similarity or inter-cluster dissimilarity. In real-world applications, the datasets often have some complex characteristics: sparse, overlap, high dimensionality, etc. When facing these datasets, simultaneously optimizing two or more objectives can obtain better clustering results than optimizing one objective. However, except for the objectives weighting methods, traditional clustering approaches have difficulty in solving multi-objective data clustering problems. Due to this, evolutionary multi-objective optimization algorithms are investigated by researchers to optimize multiple clustering objectives. In this paper, the Data Clustering algorithm based on Multi-objective Periodic Bacterial Foraging Optimization with two Learning Archives (DC-MPBFOLA) is proposed. Specifically, first, to reduce the high computing complexity of the original BFO, periodic BFO is employed as the basic algorithmic framework. Then transfer the periodic BFO into a multi-objective type. Second, two learning strategies are proposed based on the two learning archives to guide the bacterial swarm to move in a better direction. On the one hand, the global best is selected from the global learning archive according to the convergence index and diversity index. On the other hand, the personal best is selected from the personal learning archive according to the sum of weighted objectives. According to the aforementioned learning strategies, a chemotaxis operation is designed. Third, an elite learning strategy is designed to provide fresh power to the objects in two learning archives. When the objects in these two archives do not change for two consecutive times, randomly initializing one dimension of objects can prevent the proposed algorithm from falling into local optima. Fourth, to validate the performance of the proposed algorithm, DC-MPBFOLA is compared with four state-of-art evolutionary multi-objective optimization algorithms and one classical clustering algorithm on evaluation indexes of datasets. To further verify the effectiveness and feasibility of designed strategies in DC-MPBFOLA, variants of DC-MPBFOLA are also proposed. Experimental results demonstrate that DC-MPBFOLA outperforms its competitors regarding all evaluation indexes and clustering partitions. These results also indicate that the designed strategies positively influence the performance improvement of the original BFO.

Keywords: data clustering, multi-objective optimization, bacterial foraging optimization, learning archives

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Authors: Yan Torres, Fernanda Simoes, Francisco Petrucci-Fonseca, Freddie-Jeanne Richard

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The non-invasive samples are an alternative of collecting genetic samples directly. Non-invasive samples are collected without the manipulation of the animal (e.g., scats, feathers and hairs). Nevertheless, the use of non-invasive samples has some limitations. The main issue is degraded DNA, leading to poorer extraction efficiency and genotyping. Those errors delayed for some years a widespread use of non-invasive genetic information. Possibilities to limit genotyping errors can be done using analysis methods that can assimilate the errors and singularities of non-invasive samples. Genotype matching and population estimation algorithms can be highlighted as important analysis tools that have been adapted to deal with those errors. Although, this recent development of analysis methods there is still a lack of empirical performance comparison of them. A comparison of methods with dataset different in size and structure can be useful for future studies since non-invasive samples are a powerful tool for getting information specially for endangered and rare populations. To compare the analysis methods, four different datasets used were obtained from the Dryad digital repository were used. Three different matching algorithms (Cervus, Colony and Error Tolerant Likelihood Matching - ETLM) are used for matching genotypes and two different ones for population estimation (Capwire and BayesN). The three matching algorithms showed different patterns of results. The ETLM produced less number of unique individuals and recaptures. A similarity in the matched genotypes between Colony and Cervus was observed. That is not a surprise since the similarity between those methods on the likelihood pairwise and clustering algorithms. The matching of ETLM showed almost no similarity with the genotypes that were matched with the other methods. The different cluster algorithm system and error model of ETLM seems to lead to a more criterious selection, although the processing time and interface friendly of ETLM were the worst between the compared methods. The population estimators performed differently regarding the datasets. There was a consensus between the different estimators only for the one dataset. The BayesN showed higher and lower estimations when compared with Capwire. The BayesN does not consider the total number of recaptures like Capwire only the recapture events. So, this makes the estimator sensitive to data heterogeneity. Heterogeneity in the sense means different capture rates between individuals. In those examples, the tolerance for homogeneity seems to be crucial for BayesN work properly. Both methods are user-friendly and have reasonable processing time. An amplified analysis with simulated genotype data can clarify the sensibility of the algorithms. The present comparison of the matching methods indicates that Colony seems to be more appropriated for general use considering a time/interface/robustness balance. The heterogeneity of the recaptures affected strongly the BayesN estimations, leading to over and underestimations population numbers. Capwire is then advisable to general use since it performs better in a wide range of situations.

Keywords: algorithms, genetics, matching, population

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Authors: Mwehe Mathenge, Ben G. J. S. Sonneveld, Jacqueline E. W. Broerse

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Smallholder farmers are important drivers of agriculture productivity, food security, and poverty reduction in Sub-Saharan Africa. However, they are faced with myriad challenges in their efforts at participating in agribusiness markets. How the geographic explicit factors existing at the local level interact to impede smallholder farmers' decision to participates (or not) in agribusiness markets is not well understood. Deconstructing the spatial complexity of the local environment could provide a deeper insight into how geographically explicit determinants promote or impede resource-poor smallholder farmers from participating in agribusiness. This paper’s objective was to identify, map, and analyze local spatial autocorrelation in factors that impede poor smallholders from participating in agribusiness markets. Data were collected using geocoded researcher-administered survey questionnaires from 392 households in Western Kenya. Three spatial statistics methods in geographic information system (GIS) were used to analyze data -Global Moran’s I, Cluster and Outliers Analysis (Anselin Local Moran’s I), and geographically weighted regression. The results of Global Moran’s I reveal the presence of spatial patterns in the dataset that was not caused by spatial randomness of data. Subsequently, Anselin Local Moran’s I result identified spatially and statistically significant local spatial clustering (hot spots and cold spots) in factors hindering smallholder participation. Finally, the geographically weighted regression results unearthed those specific geographic explicit factors impeding market participation in the study area. The results confirm that geographically explicit factors are indispensable in influencing the smallholder farming decisions, and policymakers should take cognizance of them. Additionally, this research demonstrated how geospatial explicit analysis conducted at the local level, using geographically disaggregated data, could help in identifying households and localities where the most impoverished and resource-poor smallholder households reside. In designing spatially targeted interventions, policymakers could benefit from geospatial analysis methods in understanding complex geographic factors and processes that interact to influence smallholder farmers' decision-making processes and choices.

Keywords: agribusiness markets, GIS, smallholder farmers, spatial statistics, disaggregated spatial data

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Authors: Aisling Gough, Ruth F. Hunter, Jianjun Tang, Sarah F. Brennan, Oliver Smith, Mark A. Tully, Chris Patterson, Alberto Longo, George Hutchinson, Lindsay Prior, David French, Jean Adams, Emma McIntosh, Frank Kee

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Background: As a large proportion of the UK workforce is employed in sedentary occupations, worksite interventions have the potential to contribute significantly to the health of the population. The UK Government is currently encouraging the use of financial incentives to promote healthier lifestyles but there is a dearth of evidence regarding the effectiveness and sustainability of incentive schemes to promote physical activity in the workplace. Methods: A large cluster RCT is currently underway, incorporating nested behavioural economic field experiments and process evaluation, to evaluate the effectiveness of a Physical Activity Loyalty Scheme. Office-based employees were recruited from large public sector organisations in Lisburn and Belfast (Northern Ireland) and randomised to an Intervention or Control group. Participants in the Intervention Group were encouraged to take part in 150 minutes of physical activity per week through provision of financial incentives (retailer vouchers) to those who met physical activity targets throughout the course of the 6 month intervention. Minutes of physical activity were monitored when participants passed by sensors (holding a keyfob) placed along main walking routes, parks and public transport stops nearby their workplace. Participants in the Control Group will complete the same outcome assessments (waiting-list control). The primary outcome is steps per day measured via pedometers (7 days). Secondary outcomes include health and wellbeing (Short Form-8, EuroQol-5D-5L, Warwick Edinburgh Mental Well Being Scale), and work absenteeism and presenteeism. Data will be collected at baseline, 6, 12 and 18 months. Information on PAL card & website usage, voucher downloads and redemption of vouchers will also be collected as part of a comprehensive process evaluation. Results: In total, 853 participants have been recruited from 9 workplaces in Lisburn, 12 buildings within the Stormont Estate, Queen’s University Belfast and Belfast City Hospital. Participants have been randomised to intervention and control groups. Baseline and 6-month data for the Physical Activity Loyalty Scheme has been collected. Findings regarding the effectiveness of the intervention from the 6-month follow-up data will be presented. Discussion: This study will address the gap in knowledge regarding the effectiveness and cost-effectiveness of a workplace-based financial incentive scheme to promote a healthier lifestyle. As the UK workforce is increasingly sedentary, workplace-based physical activity interventions have significant potential in terms of encouraging employees to partake in physical activity during the working day which could lead to substantial improvements in physical activity levels overall. Implications: If a workplace based physical activity intervention such as this proves to be both effective and cost-effective, there is great potential to contribute significantly to the health and wellbeing of the workforce in the future. Workplace-based physical activity interventions have the potential to improve the physical and mental health of employees which may in turn lead to economic benefits for the employer, such as reduction in rates of absenteeism and increased productivity.

Keywords: behaviour change, cluster randomised controlled trial, loyalty scheme, physical activity

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Authors: Adhithy Menon E., Biju C. A.

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In the 1960s, the concept of preserving heritage monuments was first introduced. During the 1990s, the concept of cultural landscapes gained importance, highlighting the importance of culture and heritage. Throughout this paper, we examine the second category of the cultural landscape, which is an organically evolving landscape as it represents a web of tangible, intangible, and ecological heritage and the ways in which they can be rejuvenated. Cultural landscapes in various regions, such as the Chettinad Village clusters, are in serious decline, which is identified through the Heritage Passport program of this area (2007). For this reason, it is necessary to conduct a detailed analysis of the factors that contribute to this degradation to ensure its protection in the future. An analysis of the cultural landscape of the Chettinad Village clusters and its impact on the community is presented in this paper. The paper follows the first objective, which is to understand cultural landscapes and their different criteria and categories. It is preceded by the study of various methods for protecting cultural landscapes. To identify a core area of intervention based on the parameters of Cultural Landscapes and Community Based Tourism, a study and analysis of the regional context of Chettinad village clusters considering tourism development must first be conducted. Lastly, planning interventions for integrating community-based tourism in Chettinad villages for the purpose of rejuvenating the cultural landscapes of the villages as well as their communities. The major findings include the importance of the local community in protecting cultural landscapes. The parameters identified to have an impact on Chettinad Village clusters are a community (community well-being, local maintenance, and enhancement, demand, alternative income for community, public participation, awareness), tourism (location and physical access, journey time, tourist attractions), integrity (natural factors, natural disasters, demolition of structures, deterioration of materials) authenticity (sense of place, living elements, building techniques, artistic expression, religious context) disaster management (natural disasters) and environmental impact (pollution). This area can be restored to its former glory and preserved as part of the cultural landscape for future generations by focusing on and addressing these parameters within the identified core area of the Chettinad Villages cluster (Kanadukathan TP, Kothamangalam, Kottaiyur, Athangudi, Karikudi, and Palathur).

Keywords: Chettinad village clusters, community, cultural landscapes, organically evolved.

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Authors: Shyam Shukla

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A brand is the identity of a specific product, service or business. A brand can take many forms, including a name, sign, symbol, color, combination or slogan. The word brand began simply as a way to tell one person's identity from another by means of a hot iron stamp. A legally protected brand name is called a trademark. The word brand has continued to evolve to encompass identity - it affects the personality of a product, company or service. A concept brand is a brand that is associated with an abstract concept, like AIDS awareness or environmentalism, rather than a specific product, service, or business. A commodity brand is a brand associated with a commodity1. In this paper, it is tried to explore the significance of an intellectual capital for the branding of an Institution.

Keywords: brand, commodity, consumer, cultural values, intellectual capital, zonal cluster

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Authors: Shreya Banerjee, Roshmi Sen, Subrata Chattopadhyay

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Urbanization during the second half of the last century has created many serious environment related issues leading to global warming and climate change. India is not an exception as the country is also facing the problems of global warming and urban heat islands (UHI) in all the major metropolises. This paper discusses the effect of different housing cluster layouts, site geometry, and geometry of urban street canyons on the urban heat island profile. The study is carried out using the three dimensional microclimatic computational fluid dynamics model ENVI-met version 3.1. Simulation models are done for a typical summer day of 21st June, 2015 in four different residential neighborhoods in the city of Kolkata which predominantly belongs to Warm-Humid Monsoon Climate. The results show the changing pattern of urban heat island profile with respect to different clustering layouts, geometry, and morphology of urban street canyons. The comparison between the four neighborhoods shows that different microclimatic variables are strongly dependant on the neighborhood layout pattern and geometry. The inferences obtained from this study can be indicative towards the formulation of neighborhood design by-laws that will attenuate the urban heat island effect.

Keywords: urban heat island, neighborhood morphology, site microclimate, ENVI-met, numerical analysis

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Authors: Gaelle Candel, David Naccache

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t-SNE is an embedding method that the data science community has widely used. It helps two main tasks: to display results by coloring items according to the item class or feature value; and for forensic, giving a first overview of the dataset distribution. Two interesting characteristics of t-SNE are the structure preservation property and the answer to the crowding problem, where all neighbors in high dimensional space cannot be represented correctly in low dimensional space. t-SNE preserves the local neighborhood, and similar items are nicely spaced by adjusting to the local density. These two characteristics produce a meaningful representation, where the cluster area is proportional to its size in number, and relationships between clusters are materialized by closeness on the embedding. This algorithm is non-parametric. The transformation from a high to low dimensional space is described but not learned. Two initializations of the algorithm would lead to two different embeddings. In a forensic approach, analysts would like to compare two or more datasets using their embedding. A naive approach would be to embed all datasets together. However, this process is costly as the complexity of t-SNE is quadratic and would be infeasible for too many datasets. Another approach would be to learn a parametric model over an embedding built with a subset of data. While this approach is highly scalable, points could be mapped at the same exact position, making them indistinguishable. This type of model would be unable to adapt to new outliers nor concept drift. This paper presents a methodology to reuse an embedding to create a new one, where cluster positions are preserved. The optimization process minimizes two costs, one relative to the embedding shape and the second relative to the support embedding’ match. The embedding with the support process can be repeated more than once, with the newly obtained embedding. The successive embedding can be used to study the impact of one variable over the dataset distribution or monitor changes over time. This method has the same complexity as t-SNE per embedding, and memory requirements are only doubled. For a dataset of n elements sorted and split into k subsets, the total embedding complexity would be reduced from O(n²) to O(n²=k), and the memory requirement from n² to 2(n=k)², which enables computation on recent laptops. The method showed promising results on a real-world dataset, allowing to observe the birth, evolution, and death of clusters. The proposed approach facilitates identifying significant trends and changes, which empowers the monitoring high dimensional datasets’ dynamics.

Keywords: concept drift, data visualization, dimension reduction, embedding, monitoring, reusability, t-SNE, unsupervised learning

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Authors: Guizella Rocabado, Cassidy Wilkes

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It is well known that chemistry is one of the most feared courses in college. Although many students enjoy learning about science, most of them perceive that chemistry is “too difficult”. These perceptions of chemistry result in many students not considering Science, Technology, Engineering, and Mathematics (STEM) majors because they require chemistry courses. Ultimately, these perceptions are also thought to be related to high attrition rates of students who begin STEM majors but do not persist. Students perceived costs of a chemistry class can be many, such as task effort, loss of valued alternatives, emotional, and others. These costs might be overcome by students’ interests and goals, yet the level of perceived costs might have a lasting impact on the students’ overall perception of chemistry and their desire to pursue chemistry and other STEM careers in the future. In this mixed methods study, we investigated task effort and emotional cost, as well as a mastery or performance goal orientation, and the impact these constructs may have on achievement in general chemistry classrooms. Utilizing cluster analysis as well as student interviews, we investigated students’ profiles of perceived cost and goal orientation as it relates to their final grades. Our results show that students who are well prepared for general chemistry, such as those who have taken chemistry in high school, display less negative perceived costs and thus believe they can master the material more fully. Other interesting results have also emerged from this research, which has the potential to have an impact on future instruction of these courses.

Keywords: chemistry education, motivation, affect, perceived costs, goal orientations

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Authors: Mansir Abubakar, Hazlina Hamdan, Norwati Mustapha, Teh Noranis Mohd Aris

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In order to build a matching pattern for each class correspondences of ontology, it is required to specify a set of attribute correspondences across two corresponding classes by clustering. Clustering reduces the size of potential attribute correspondences considered in the matching activity, which will significantly reduce the computation workload; otherwise, all attributes of a class should be compared with all attributes of the corresponding class. Most existing ontology matching approaches lack scalable attributes discovery methods, such as cluster-based attribute searching. This problem makes ontology matching activity computationally expensive. It is therefore vital in ontology matching to design a scalable element or attribute correspondence discovery method that would reduce the size of potential elements correspondences during mapping thereby reduce the computational workload in a matching process as a whole. The objective of this work is 1) to design a clustering method for discovering similar attributes correspondences and relationships between ontologies, 2) to discover element correspondences by classifying elements of each class based on element’s value features using K-medoids clustering technique. Discovering attribute correspondence is highly required for comparing instances when matching two ontologies. During the matching process, any two instances across two different data sets should be compared to their attribute values, so that they can be regarded to be the same or not. Intuitively, any two instances that come from classes across which there is a class correspondence are likely to be identical to each other. Besides, any two instances that hold more similar attribute values are more likely to be matched than the ones with less similar attribute values. Most of the time, similar attribute values exist in the two instances across which there is an attribute correspondence. This work will present how to classify attributes of each class with K-medoids clustering, then, clustered groups to be mapped by their statistical value features. We will also show how to map attributes of a clustered group to attributes of the mapped clustered group, generating a set of potential attribute correspondences that would be applied to generate a matching pattern. The K-medoids clustering phase would largely reduce the number of attribute pairs that are not corresponding for comparing instances as only the coverage probability of attributes pairs that reaches 100% and attributes above the specified threshold can be considered as potential attributes for a matching. Using clustering will reduce the size of potential elements correspondences to be considered during mapping activity, which will in turn reduce the computational workload significantly. Otherwise, all element of the class in source ontology have to be compared with all elements of the corresponding classes in target ontology. K-medoids can ably cluster attributes of each class, so that a proportion of attribute pairs that are not corresponding would not be considered when constructing the matching pattern.

Keywords: attribute correspondence, clustering, computational workload, k-medoids clustering, ontology matching

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Authors: Thomas Nally, Jane Ireland, Roxanne Khan, Philip Birch

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Intimate Partner Violence (IPV), a significant societal problem, affects individuals worldwide. However, the strategies victims use to keep safe are under-researched. IPV is significantly under-reported, and services often are not able to be accessed by all victims. Thus they are likely to use their own strategies to manage their victimization before being able to seek support. Two studies were completed to understand these strategies. A systematic review of the literature and study completed with professionals who work with victims was undertaken to understand this area. In study one, a systematic review of the literature (n=61 papers), were analyzed using Thematic Analysis. The results indicated that victims use a large array of behaviors to increase their sense of safety and coping with emotions but also experience significant barriers to help-seeking. In study 2, sixty-nine professionals completed a measure exploring the likelihood and effectiveness of various victim strategies regarding increasing their sense of safety. Strategies included in the measure were obtained from those identified in study 1. Findings indicated that professionals perceived victims of IPV to be more likely to employ safety strategies and coping behaviors that may be ineffective but not help-seeking behaviors. Further, the responses were analyzed using Cluster Analysis. Safety strategies resulted in five clusters; perpetrator-directed strategies, prevention strategies, cognitive reappraisal, safety planning and avoidance strategies. Help-Seeking resulted in six clusters; information or practical support, abuse-related support, emotional support, secondary support and informal support. Finally, coping resulted in four clusters; emotional coping, self-directed coping, thought recording/change and cognitive coping. Both studies indicate that victims may use a variety of strategies to manage their safety besides seeking help. Professionals working with victims, using a strength-based approach, should understand what is used and is effective for victims who are unable to leave the relationships or access external support.

Keywords: intimate partner violence, help-seeking, professional support, victims, victim coping, victim safety

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Authors: Lena Payati, Maria Kazou, Effie Tsakalidou

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Table olives are one of the most popular fermented vegetables worldwide, which along with olive oil, have a crucial role in the world economy. They are highly appreciated by the consumers for their characteristic taste and pleasant aromas, while several health and nutritional benefits have been reported as well. Until recently, microbial biogeography, i.e., the study of microbial diversity over time and space, has been mainly associated with wine. However, nowadays, the term 'terroir' has been extended to other crops and food products so as to link the geographical origin and environmental conditions to quality aspects of fermented foods. Taking the above into consideration, the present study focuses on the microbial fingerprinting of the most important olive varieties of Greece with the state-of-the-art amplicon-based metagenomics analysis. Towards this, in 2019, 61 samples from 38 different olive varieties were collected at the final stage of ripening from 13 well spread geographical regions in Greece. For the metagenomics analysis, total DNA was extracted from the olive samples, and the 16S rRNA gene and ITS DNA region were sequenced and analyzed using bioinformatics tools for the identification of bacterial and yeasts/fungal diversity, respectively. Furthermore, principal component analysis (PCA) was also performed for data clustering based on the average microbial composition of all samples from each region of origin. According to the composition, results obtained, when samples were analyzed separately, the majority of both bacteria (such as Pantoea, Enterobacter, Roserbergiella, and Pseudomonas) and yeasts/fungi (such as Aureobasidium, Debaromyces, Candida, and Cladosporium) genera identified were found in all 61 samples. Even though interesting differences were observed at the relative abundance level of the identified genera, the bacterial genus Pantoea and the yeast/fungi genus Aureobasidium were the dominant ones in 35 and 40 samples, respectively. Of note, olive samples collected from the same region had similar fingerprint (genera identified and relative abundance level) regardless of the variety, indicating a potential association between the relative abundance of certain taxa and the geographical region. When samples were grouped by region of origin, distinct bacterial profiles per region were observed, which was also evident from the PCA analysis. This was not the case for the yeast/fungi profiles since 10 out of the 13 regions were grouped together mainly due to the dominance of the genus Aureobasidium. A second cluster was formed for the islands Crete and Rhodes, both of which are located in the Southeast Aegean Sea. These two regions clustered together mainly due to the identification of the genus Toxicocladosporium in relatively high abundances. Finally, the Agrinio region was separated from the others as it showed a completely different microbial fingerprinting. However, due to the limited number of olive samples from some regions, a subsequent PCA analysis with more samples from these regions is expected to yield in a more clear clustering. The present study is part of a bigger project, the first of its kind in Greece, with the ultimate goal to analyze a larger set of olive samples of different varieties and from different regions in Greece in order to have a reliable olives’ microbial biogeography.

Keywords: amplicon-based metagenomics analysis, bacteria, microbial biogeography, olive microbiota, yeasts/fungi

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Authors: Fayez Mostafa Alhamoui, Adnan Hadi Mahdi Al- Helali

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The main issue in designing a wireless sensor network (WSN) is the finding of a proper routing protocol that complies with the several requirements of high reliability, short latency, scalability, low power consumption, and many others. This paper proposes a novel routing algorithm that complies with these design requirements. The new routing protocol divides the WSN into several sub-networks and each sub-network is divided into several clusters. This division is designed to reduce the number of radio transmission and hence decreases the power consumption. The network division may be changed dynamically to adapt with the network changes and allows the realization of the design requirements.

Keywords: wireless sensor networks, routing protocols, AD HOC topology, cluster, sub-network, WSN design requirements

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Authors: Yung-Chung Chuang

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The cultural layers of archaeological sites are mainly affected by surface land use, land cover, and root system of surface vegetation. For this reason, continuous monitoring of land use and land cover change is important for archaeological sites protection and management. However, in actual operation, on-site investigation and orthogonal photograph interpretation require a lot of time and manpower. For this reason, it is necessary to perform a good alternative for surface vegetation survey in an automated or semi-automated manner. In this study, we applied semi-automatic digital aerial survey technology and canopy characters classification with very high-resolution aerial photographs for surface vegetation interpretation of archaeological sites. The main idea is based on different landscape or forest type can easily be distinguished with canopy characters (e.g., specific texture distribution, shadow effects and gap characters) extracted by semi-automatic image classification. A novel methodology to classify the shape of canopy characters using landscape indices and multivariate statistics was also proposed. Non-hierarchical cluster analysis was used to assess the optimal number of canopy character clusters and canonical discriminant analysis was used to generate the discriminant functions for canopy character classification (seven categories). Therefore, people could easily predict the forest type and vegetation land cover by corresponding to the specific canopy character category. The results showed that the semi-automatic classification could effectively extract the canopy characters of forest and vegetation land cover. As for forest type and vegetation type prediction, the average prediction accuracy reached 80.3%~91.7% with different sizes of test frame. It represented this technology is useful for archaeological site survey, and can improve the classification efficiency and data update rate.

Keywords: digital aerial survey, canopy characters classification, archaeological sites, multivariate statistics

Procedia PDF Downloads 141