Search results for: corrugation patterns

Authors: Carmela Perta

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Among the studies flourished in the field of historical sociolinguistics, mainly in the strand devoted to English history, during its Medieval and early modern phases, multilingual texts had been analysed using theories and models coming from contact linguistics, thus applying synchronic models and approaches to the past. This is true also in the case of contact phenomena which would transcend the writing level involving the language systems implicated in contact processes to the point of perceiving a new variety. This is the case for medieval administrative-commercial texts in which, according to some Scholars, the degree of fusion of Anglo-Norman, Latin and middle English is so high a mixed code emerges, and there are recurrent patterns of mixed forms. Interesting is a collection of multilingual business writings by John Balmayn, an Englishman overseeing a large shipment in Tuscany, namely the Cantelowe accounts. These documents display various analogies with multilingual texts written in England in the same period; in fact, the writer seems to make use of the above-mentioned patterns, with Middle English, Latin, Anglo-Norman, and the newly added Italian. Applying an atomistic yet dynamic approach to the study of contact phenomena, we will investigate these documents, trying to explore the nature of the switching forms they contain from an intra-writer variation perspective. After analysing the accounts and the type of multilingualism in them, we will take stock of the assumed mixed code nature, comparing the characteristics found in this genre with modern assumptions. The aim is to evaluate the possibility to consider the switching forms as core elements of a mixed code, used as professional variety among merchant communities, or whether such texts should be analysed from a switching perspective.

Keywords: historical sociolinguistics, historical code switching, letters, medieval england

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Authors: Jaeyoung Lee, Minji Je

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Objectives: The adolescents not attending school are named out-of-school adolescents. They are more vulnerable to health management and are likely to be exposed to a number of risk factors. This study was conducted to investigate the problem behavior of out-of-school adolescents and analyze the difference caused by gender. Methods: In this study, the problem behaviors of out-of-school adolescents, the vulnerable class, were defined in 8 types and based on this definition, the survey on run away from home, drop out, prostitution, violence, internet game addiction, theft, drug addiction, and smoking was conducted. The study was conducted in a total of 507 out-of-school adolescents, including 342 males, and 165 females. The type, frequency and start time of the 8 problem behaviors were identified. The collected data were analyzed with chi-square test and t-test using SPSS statistics 22. Results: Among the problem behaviors of the subjects, violence ( =17.41, p < .001), internet game addiction ( =16.14, p < .001), theft ( =22.48, p < .001), drug addiction ( =4.17, p=.041), and smoking ( =3.90, p=.048) were more significantly high in male out-of-school adolescents than female out-of-school adolescents. In addition, the frequency of the problem behavior was higher in male out-of-school adolescents with statistical significance than in female out-of-school adolescents (t=5.08, p= < .001). In terms of the start time of the problem behavior, only internet game addiction was higher in male out-of-school adolescents with the statistical significance than in female out-of-school adolescents ( =6.22, p=.032). No statistically significant difference was found in other problem behaviors (p > .05). Conclusions: In this study, it was found that gender difference in problem behaviors of out-of-school adolescents exists, and its frequency and difference of types were identified. When the social countermeasures were provided for those adolescents, a distinguished approach is required depending on the patterns of problem behavior and gender. When preparing policy alternatives and interventions for out-of-school adolescents, it is required to reflect the results of this study.

Keywords: addictive behavior, adolescent, gender, problem behavior

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Authors: F. O. Arimoro, F. N. Okonkwo, R. B. Ikomi

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The environmental determinants structuring species richness has been generating interest recently but we still lack an understanding of these patterns in various regions (e.g. Afrotropical), and how seasons help to structure these patterns. Our aim was to assessed the environmental drivers importance in regulating species richness and community structure of fish species. The lchthyofauna assemblage of Warri River, Niger Delta area of Nigeria was studied between August 2013 and July 2014. A total of 1152 individuals representing 43 species in 23 families and 30 genera were caught. Of the 43 species recorded, 67.4%, 53.5% and 67.4% of the species occurred in Stations 1, 2 and 3 respectively. Eight taxa representing 18.6% of the total abundance were ubiquitous. The claroteid, Chrysichthys walkeri and the cichlid, Chromidotilapia guentheri were the most dominant species accounting for 19.2% and 6.0% respectively of the total catch. The species richness and general diversity were relatively higher in station 1 although Jaccard similarity index revealed that stations 1 and 3 were significantly similar while station 2 showed complete dissimilarity with stations 1 and 3. Canonical correspondence analysis indicated that dissolved oxygen, electrical conductivity, total nitrogen, Biochemical Oxygen demand and temperature were important variables structuring the overall fish assemblages. The presence of appreciable number of juveniles in this water body suggests that the Warri River is a breeding and nursery ground for fish species particularly those of brackish origin. These findings indicate that the water body is still useful as a good fishing ground for the rural communities and every effort should be put in place to ensure its protection and conservation for the production of healthy fish.

Keywords: Chrysichthys walkeri, fish communities, mangrove ecosystem, physicochemical parameters, Warri River

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Authors: Damini Thawait, S. K. Dwivedi, Amit K. Patel, Samaptika Kar

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The experiment was carried out at Raipur during season of 2012 to find out the optimum planting patterns for scented rice cultivation. The treatment (T2) planting of two to three seedlings hill-1 transplanted in the spacing of 25 cm from plant to plant and 25 cm from row to row recorded significantly good grain quality i.e. higher head rice recovery (41.41) along with higher gain length (8.05).

Keywords: rice, scented, quality, yield

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Authors: K. Sathishkumar, V. Thiagarasu

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Due to recent advances in DNA microarray technology, it is now feasible to obtain gene expression profiles of tissue samples at relatively low costs. Many scientists around the world use the advantage of this gene profiling to characterize complex biological circumstances and diseases. Microarray techniques that are used in genome-wide gene expression and genome mutation analysis help scientists and physicians in understanding of the pathophysiological mechanisms, in diagnoses and prognoses, and choosing treatment plans. DNA microarray technology has now made it possible to simultaneously monitor the expression levels of thousands of genes during important biological processes and across collections of related samples. Elucidating the patterns hidden in gene expression data offers a tremendous opportunity for an enhanced understanding of functional genomics. However, the large number of genes and the complexity of biological networks greatly increase the challenges of comprehending and interpreting the resulting mass of data, which often consists of millions of measurements. A first step toward addressing this challenge is the use of clustering techniques, which is essential in the data mining process to reveal natural structures and identify interesting patterns in the underlying data. This work presents an analysis of several clustering algorithms proposed to deals with the gene expression data effectively. The existing clustering algorithms like Support Vector Machine (SVM), K-means algorithm and evolutionary algorithm etc. are analyzed thoroughly to identify the advantages and limitations. The performance evaluation of the existing algorithms is carried out to determine the best approach. In order to improve the classification performance of the best approach in terms of Accuracy, Convergence Behavior and processing time, a hybrid clustering based optimization approach has been proposed.

Keywords: microarray technology, gene expression data, clustering, gene Selection

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Authors: Sang-Keun Moon, Hong-Rok Lim, Jin-O Kim

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This paper presents a Power Quality (PQ) modeling and filtering processes for the distribution system disturbances using recognition learning methods. Typical PQ waveforms with mathematical applications and gathered field data are applied to the proposed models. The objective of this paper is analyzing PQ data with respect to monitoring, discriminating, and evaluating the waveform of power disturbances to ensure the system preventative system failure protections and complex system problem estimations. Examined signal filtering techniques are used for the field waveform noises and feature extractions. Using extraction and learning classification techniques, the efficiency was verified for the recognition of the PQ disturbances with focusing on interactive modeling methods in this paper. The waveform of selected 8 disturbances is modeled with randomized parameters of IEEE 1159 PQ ranges. The range, parameters, and weights are updated regarding field waveform obtained. Along with voltages, currents have same process to obtain the waveform features as the voltage apart from some of ratings and filters. Changing loads are causing the distortion in the voltage waveform due to the drawing of the different patterns of current variation. In the conclusion, PQ disturbances in the voltage and current waveforms indicate different types of patterns of variations and disturbance, and a modified technique based on the symmetrical components in time domain was proposed in this paper for the PQ disturbances detection and then classification. Our method is based on the fact that obtained waveforms from suggested trigger conditions contain potential information for abnormality detections. The extracted features are sequentially applied to estimation and recognition learning modules for further studies.

Keywords: power quality recognition, PQ modeling, waveform feature extraction, disturbance trigger condition, PQ signal filtering

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Authors: Shi-Bo Feng, Sheng-Jie Zhang, Jin Zhou

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The relationship between microbial diversity and algal bloom has received considerable attention for decades. Microbes undoubtedly affect annual bloom events and impact the physiology of both partners, as well as shape ecosystem diversity. However, knowledge about interactions and network correlations among broader-spectrum microbes that lead to the dynamics in a complete bloom cycle are limited. In this study, pyrosequencing and network approaches simultaneously assessed the associate patterns among bacteria, archaea, and microeukaryotes in surface water and sediments in response to a natural dinoflagellate (Alexandrium sp.) bloom. In surface water, among the bacterial community, Gamma-Proteobacteria and Bacteroidetes dominated in the initial bloom stage, while Alpha-Proteobacteria, Cyanobacteria, and Actinobacteria become the most abundant taxa during the post-stage. In the archaea biosphere, it clustered predominantly with Methanogenic members in the early pre-bloom period while the majority of species identified in the later-bloom stage were ammonia-oxidizing archaea and Halobacteriales. In eukaryotes, dinoflagellate (Alexandrium sp.) was dominated in the onset stage, whereas multiply species (such as microzooplankton, diatom, green algae, and rotifera) coexistence in bloom collapse stag. In sediments, the microbial species biomass and richness are much higher than the water body. Only Flavobacteriales and Rhodobacterales showed a slight response to bloom stages. Unlike the bacteria, there are small fluctuations of archaeal and eukaryotic structure in the sediment. The network analyses among the inter-specific associations show that bacteria (Alteromonadaceae, Oceanospirillaceae, Cryomorphaceae, and Piscirickettsiaceae) and some zooplankton (Mediophyceae, Mamiellophyceae, Dictyochophyceae and Trebouxiophyceae) have a stronger impact on the structuring of phytoplankton communities than archaeal effects. The changes in population were also significantly shaped by water temperature and substrate availability (N & P resources). The results suggest that clades are specialized at different time-periods and that the pre-bloom succession was mainly a bottom-up controlled, and late-bloom period was controlled by top-down patterns. Additionally, phytoplankton and prokaryotic communities correlated better with each other, which indicate interactions among microorganisms are critical in controlling plankton dynamics and fates. Our results supplied a wider view (temporal and spatial scales) to understand the microbial ecological responses and their network association during algal blooming. It gives us a potential multidisciplinary explanation for algal-microbe interaction and helps us beyond the traditional view linked to patterns of algal bloom initiation, development, decline, and biogeochemistry.

Keywords: microbial community, harmful algal bloom, ecological process, network

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Authors: B. Niez, B. Moulia, J. Dlouha, E. Badel

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Trees adjust their development to the environmental conditions they experience. Storms events of last decades showed that acclimation of trees to mechanical stresses due to wind is a very important process that allows the trees to sustain for long years. In the future, trees will experience new wind patterns, namely, more often strong winds and fewer daily moderate winds. Moreover, these patterns will go along with drought periods that may interact with the capacity of trees to adjust their growth to mechanical stresses due to wind. It is necessary to understand the mechanisms of wood functional acclimations to environmental conditions in order to predict their behaviour and in order to give foresters and breeders the relevant tools to adapt their forest management. This work aims to study how trees adjust the mechanical and hydraulic functions of their wood to environmental stresses and how this acclimation may be beneficial for the tree to resist to future stresses. In this work, young poplars were grown under controlled climatic conditions that include permanent environmental stress (daily mechanical stress of the stem by bending and/or hydric stress). Then, the properties of wood formed under these stressed conditions were characterized. First, hydraulic conductivity and sensibility to cavitation were measured at the tissue level in order to evaluate the changes in water transport capacity. Secondly, bending tests and Charpy impact tests were carried out at the millimetric scale to locally measure mechanical parameters such as elastic modulus, elastic limit or rupture energy. These experimental data allow evaluating the impacts of mechanical and water stress on the wood material. At the stem level, they will be merged in an integrative model in order to evaluate the beneficial aspect of wood acclimation for trees.

Keywords: acclimation, environmental stresses, hydraulics, mechanics, wood

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Authors: Montasser Mohamed Abdelwahab Mahmoud, Abdelwahab Saber Esawi

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The language of the Qur’an has a wide range of understanding, reflection, and meanings. Therefore, translation of the Qur’an is inevitably nothing but a translation of the interpretation of the meanings of the Qur’an. It requires special competencies and skills for translators so that they can get close to the intended meaning of the verse of the Qur’an and convey it with precision. In the Arabic language, the verbal noun “AlMasdar” is a very important derivative that properly expresses the verbal idea in the form of a noun. It sounds the same as the base form of the verb with minor changes in the vowel pattern. It is one of the important topics in morphology. The morphologists divided verbal nouns into auditory and analogical, and they stated that that the verbal nouns (Masadars) originating from three-letter verbs are auditory, although they set controls for some of them in order to preserve them. As for the lexicographers, they mentioned the verbal nouns while talking about the lexical materials, and in some cases, their explanation of them exceeded that made by the morphologists, especially in their discussion of structures that the morphologists did not refer to in their books. The verb kafara (disbelief), for example, has three patterns, namely: al-kufْr, al-kufrān, and al-kufūr, and it was mentioned in the Holy Qur’an with different connotations. The verb ṣāma (fasted) with his two patterns (al-ṣaūm and al-ṣīām) was mentioned in the Holy Qur’an while their semantic meaning is different. The problem discussed in this research paper lied in the "linguistic loss" committed by translators when dealing with Islamic religious texts, especially the Qur'an. The study tried to identify the strategy adopted by translators of the Holy Qur'an in translating words that were classified as verbal nouns through analyzing the translation rendered by five translations of the Qur’an into English: Yusuf Ali, Pickthall, Mohsin Khan, Muhammad Sarwar, and Shakir. This study was limited to the verbal nouns in the Quraan that originate from three-letter verbs and have different semantic meanings.

Keywords: pattern, three-letter verbs, translation of the Quran, verbal nouns

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Authors: Kaisy Xinhong Ye, Su Lin Lim, Jialiang Li, Lei Feng

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background: Multiple healthful dietary patterns have been linked with dementia, but limited studies have looked at the role of diet in cognitive health in Asians whose eating habits are very different from their counterparts in the west. This study aimed to derive a dietary pattern that is associated with the risk of cognitive impairment (CI) in the Singaporean population. Method: The analysis was based on 719 community older adults aged 60 and above. Dietary intake was measured using a validated semi-quantitative food-frequency questionnaire (FFQ). Reduced rank regression (RRR) was used to extract dietary pattern from 45 food groups, specifying sugar, dietary fiber, vitamin A, calcium, and the ratio of polyunsaturated fat to saturated fat intake (P:S ratio) as response variables. The RRR-derived dietary patterns were subsequently investigated using multivariate logistic regression models to look for associations with the risk of CI. Results: A dietary pattern characterized by greater intakes of green leafy vegetables, red-orange vegetables, wholegrains, tofu, nuts, and lower intakes of biscuits, pastries, local sweets, coffee, poultry with skin, sugar added to beverages, malt beverages, roti, butter, and fast food was associated with reduced risk of CI [multivariable-adjusted OR comparing extreme quintiles, 0.29 (95% CI: 0.11, 0.77); P-trend =0.03]. This pattern was positively correlated with P:S ratio, vitamin A, and dietary fiber and negatively correlated with sugar. Conclusion: A dietary pattern providing high P:S ratio, vitamin A and dietary fiber, and a low level of sugar may reduce the risk of cognitive impairment in old age. The findings have significance in guiding local Singaporeans to dementia prevention through food-based dietary approaches.

Keywords: dementia, cognitive impairment, diet, nutrient, elderly

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Authors: Qiuying Li

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It is a shared opinion that sustainable development requires a system discontinuity, meaning that radical changes in the way we produce and consume are needed. Within this framework there is an emerging understanding that an important contribution to this change can be directly linked to decisions taken in the design phase of products, services and systems. Design schools have therefore to be able to provide design students with a broad knowledge and effective Design for Sustainability tools, in order to enable a new generation of designers in playing an active role in reorienting our consumption and production patterns.

Keywords: design for sustainability, services, systems, materials, ecomaterials

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Authors: Mir Jalil Razavi, Tianming Liu, Xianqiao Wang

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Cortical folding, characterized by convex gyri and concave sulci, has an intrinsic relationship to the brain’s functional organization. Understanding the mechanism of the brain’s convoluted patterns can provide useful clues into normal and pathological brain function. During the development, the cerebral cortex experiences a noticeable expansion in volume and surface area accompanied by tremendous tissue folding which may be attributed to many possible factors. Despite decades of endeavors, the fundamental mechanism and key regulators of this crucial process remain incompletely understood. Therefore, to taking even a small role in unraveling of brain folding mystery, we present a mechanical model to find mechanism of 3-hinges formation in a growing brain that it has not been addressed before. A 3-hinge is defined as a gyral region where three gyral crests (hinge-lines) join. The reasons that how and why brain prefers to develop 3-hinges have not been answered very well. Therefore, we offer a theoretical and computational explanation to mechanism of 3-hinges formation in a growing brain and validate it by experimental observations. In theoretical approach, the dynamic behavior of brain tissue is examined and described with the aid of a large strain and nonlinear constitutive model. Derived constitute model is used in the computational model to define material behavior. Since the theoretical approach cannot predict the evolution of cortical complex convolution after instability, non-linear finite element models are employed to study the 3-hinges formation and secondary morphological folds of the developing brain. Three-dimensional (3D) finite element analyses on a multi-layer soft tissue model which mimics a small piece of the brain are performed to investigate the fundamental mechanism of consistent hinge formation in the cortical folding. Results show that after certain amount growth of cortex, mechanical model starts to be unstable and then by formation of creases enters to a new configuration with lower strain energy. By further growth of the model, formed shallow creases start to form convoluted patterns and then develop 3-hinge patterns. Simulation results related to 3-hinges in models show good agreement with experimental observations from macaque, chimpanzee and human brain images. These results have great potential to reveal fundamental principles of brain architecture and to produce a unified theoretical framework that convincingly explains the intrinsic relationship between cortical folding and 3-hinges formation. This achieved fundamental understanding of the intrinsic relationship between cortical folding and 3-hinges formation would potentially shed new insights into the diagnosis of many brain disorders such as schizophrenia, autism, lissencephaly and polymicrogyria.

Keywords: brain, cortical folding, finite element, three hinge

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Authors: Rosanna Tramutoli

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Studies on several languages have demonstrated how different emotions are categorized in various linguistic constructions. It exists in several writings on the codification of emotions in Western African languages. A recent study on the semantic description of Swahili body terminology has demonstrated that body part terms, such as moyo (heart), uso (face) and jicho (eye) are involved in several metaphorical expressions describing emotions. However, so far hardly anything has been written on the linguistic description of emotions in Swahili. Thus, this study describes how emotional concepts, such as ‘love’ and ‘anger’ are codified in Swahili, in order to highlight common semantic and syntactic patterns, etymological sources and metaphorical expressions. The research seeks to answer a number of questions, such as which are the Swahili terms for ‘emotions’? Is there a distinction between ‘emotions’ and ‘feelings’? Which emotional lexical items have Bantu origin and which come from Arabic? Which metaphorical expressions/cognitive schemas are used to codify emotions? (e.g. kumpanda mtu kichwani, lit. ‘to climb on somebody’s head’, to make somebody feel angry, kushuka moyo, lit. ‘to be down the heart’, to feel discouraged, kumpa mtu moyo lit. ‘to give someone heart’, to encourage someone). Which body terms are involved as ‘containers/locus of emotions’? For instance, it has been shown that moyo (‘heart’) occurs as container of ‘love’ (e.g. kumtia mtu moyoni, lit. ‘to put somebody in the heart’, to love somebody very much) and ‘kindness’ (moyo wake ulijaa hisani, ‘his heart was filled with kindness’). The study also takes into account the syntactic patterns used to code emotions. For instance, when does the experiencer occur in subject position? (e.g. nina furaha, nimefurahi, ‘I am happy’) and when in object position (e.g. Huruma iliniingia moyoni, lit. ‘Pity entered me inside my heart’, ‘I felt pity’)? Data have been collected mostly through the analysis of Swahili digital corpora, containing different kinds of Swahili texts (e.g. novels, drama, political essays).

Keywords: emotions, cognitive linguistics, metaphors, Swahili

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Authors: Maritza Granados Manjarrés

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This paper makes part of an investigation project which experiments with flat surfaces in order to pleat them using tessellations and flat origami conditions. The aim of the investigation is to eventually propose not only a methodology on how to pleat those surfaces but also to find an structural system to make them work as building skins. This stage of the investigation emphasizes on the experimentation with flat surfaces and different kinds of folding patterns and shows the many examples that can be made from this experimentation.

Keywords: flat origami, fold, space, surface

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Authors: Shiran Bord, Assaf Oshri, Matthew W. Carlson, Sihong Liu

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Background: Alcohol-impaired driving (AID) and binge drinking are major health concerns among college students. Although the link between binge drinking and AID is well established, knowledge regarding binge drinking patterns, the factors influencing binge drinking, and the associations between consumption patterns and alcohol-related risk behaviors is lacking. Aims: To examine heterogeneous trajectories of binge drinking during college and tests factors that might predict class membership as well as class membership outcomes. Methods: Data were obtained from a sample of 1,265 college students (Mage = 18.5, SD = .66) as part of the Longitudinal Study of Violence Against Women (N = 1,265; 59.3% female; 69.2% white). Analyses were completed in three stages. First, a growth curve analysis was conducted to identify trajectories of binge drinking over time. Second, growth curve mixture modeling analyses were pursued to assess unobserved growth trajectories of binge drinking without predictors. Lastly, parental drinking variables were added to the model as predictors of class membership, and AID and being a passenger of a drunk driver were added to the model as outcomes. Results: Three binge drinking trajectories were identified: high-convex, medium concave and low-increasing. Parental drinking was associated with being in high-convex and medium-concave classes. Compared to the low-increasing class, the high convex and medium concave classes reported more AID and being a passenger of a drunk driver more frequently. Conclusions: Parental drinking may affect children’s later engagement in AID. Efforts should focus on parents' education regarding the consequences of parental modeling of alcohol consumption.

Keywords: alcohol impaired driving, alcohol consumption, binge drinking, college students, parental modeling

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Authors: Peter Baji

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In recent years, a growing body of literature emphasizes the increasingly negative impacts of urban road congestion in the everyday life of citizens. Although there are different responses from the public sector to decrease traffic congestion in urban regions, the most effective public intervention is using congestion charges. Because travel is an economic asset, its consumption can be controlled by extra taxes or prices effectively, but this demand-side intervention is often unpopular. Measuring traffic flows with the help of different methods has a long history in transport sciences, but until recently, there was not enough sufficient data for evaluating road traffic flow patterns on the scale of an entire road system of a larger urban area. European cities (e.g., London, Stockholm, Milan), in which congestion charges have already been introduced, designated a particular zone in their downtown for paying, but it protects only the users and inhabitants of the CBD (Central Business District) area. Through the use of Google Maps data as a resource for revealing urban road traffic flow patterns, this paper aims to provide a solution for a fairer and smarter congestion pricing method in cities. The case study area of the research contains three bordering districts of Budapest which are linked by one main road. The first district (5th) is the original downtown that is affected by the congestion charge plans of the city. The second district (13th) lies in the transition zone, and it has recently been transformed into a new CBD containing the biggest office zone in Budapest. The third district (4th) is a mainly residential type of area on the outskirts of the city. The raw data of the research was collected with the help of Google’s Distance Matrix API (Application Programming Interface) which provides future estimated traffic data via travel times between freely fixed coordinate pairs. From the difference of free flow and congested travel time data, the daily congestion patterns and hot spots are detectable in all measured roads within the area. The results suggest that the distribution of congestion peak times and hot spots are uneven in the examined area; however, there are frequently congested areas which lie outside the downtown and their inhabitants also need some protection. The conclusion of this case study is that cities can develop a real-time and place-based congestion charge system that forces car users to avoid frequently congested roads by changing their routes or travel modes. This would be a fairer solution for decreasing the negative environmental effects of the urban road transportation instead of protecting a very limited downtown area.

Keywords: Budapest, congestion charge, distance matrix API, application programming interface, pilot study

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Authors: Zainab Mutlaq Ibrahim, Mohamed Bader-El-Den, Mihaela Cocea

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Students' textual feedback can hold unique patterns and useful information about learning process, it can hold information about advantages and disadvantages of teaching methods, assessment components, facilities, and other aspects of teaching. The results of analysing such a feedback can form a key point for institutions’ decision makers to advance and update their systems accordingly. This paper proposes a data mining framework for analysing end of unit general textual feedback using part of speech feature (PoS) with four machine learning algorithms: support vector machines, decision tree, random forest, and naive bays. The proposed framework has two tasks: first, to use the above algorithms to build an optimal model that automatically classifies the whole data set into two subsets, one subset is tailored to assessment practices (assessment related), and the other one is the non-assessment related data. Second task to use the same algorithms to build an optimal model for whole data set, and the new data subsets to automatically detect their sentiment. The significance of this paper is to compare the performance of the above four algorithms using part of speech feature to the performance of the same algorithms using n-grams feature. The paper follows Knowledge Discovery and Data Mining (KDDM) framework to construct the classification and sentiment analysis models, which is understanding the assessment domain, cleaning and pre-processing the data set, selecting and running the data mining algorithm, interpreting mined patterns, and consolidating the discovered knowledge. The results of this paper experiments show that both models which used both features performed very well regarding first task. But regarding the second task, models that used part of speech feature has underperformed in comparison with models that used unigrams and bigrams.

Keywords: assessment, part of speech, sentiment analysis, student feedback

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Authors: Wang Yunhong

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The present paper is preoccupied with the different styles of three translators in their translating a Chinese classical novel Shuihu Zhuan. Based on a parallel corpus, it adopts a target-oriented approach to look into whether and what stylistic differences and shifts the three translations have revealed. The findings show that the three translators demonstrate different styles concerning their word choices and sentence preferences, which implies that identification of recurrent textual patterns may be a basic step for investigating the style of a translator.

Keywords: corpus, lexical choices, sentence characteristics, style

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Authors: Ayodele James Akinola

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This study investigated the use of English in doctor-patient interaction in a university teaching hospital from a southwestern state in Nigeria with the aim of identifying the role of communication in an L2, patterns of communication, discourse strategies, pragmatic acts, and contexts that shape the interaction. Jacob Mey’s Pragmatic Acts notion complemented with Emanuel and Emanuel’s model of doctor-patient relationship provided the theoretical standpoint. Data comprising 7 audio-recorded doctors-patient interactions were collected from a University Hospital in Oyo state, Nigeria. Interactions involving the use of English language were purposefully selected. These were supplemented with patients’ case notes and interviews conducted with doctors. Transcription was patterned alongside modified Arminen’s notations of conversation analysis. In the study, interaction in English between doctor and patients has the preponderance of direct-translation, code-mixing and switching, Nigerianism and use of cultural worldviews to express medical experience. Irrespective of these, three patterns communication, namely the paternalistic, interpretive, and deliberative were identified. These were exhibited through varying discourse strategies. The paternalistic model reflected slightly casual conversational conventions and registers. These were achieved through the pragmemic activities of situated speech acts, psychological and physical acts, via patients’ quarrel-induced acts, controlled and managed through doctors’ shared situation knowledge. All these produced empathising, pacifying, promising and instructing practs. The patients’ practs were explaining, provoking, associating and greeting in the paternalistic model. The informative model reveals the use of adjacency pairs, formal turn-taking, precise detailing, institutional talks and dialogic strategies. Through the activities of the speech, prosody and physical acts, the practs of declaring, alerting and informing were utilised by doctors, while the patients exploited adapting, requesting and selecting practs. The negotiating conversational strategy of the deliberative model featured in the speech, prosody and physical acts. In this model, practs of suggesting, teaching, persuading and convincing were utilised by the doctors. The patients deployed the practs of questioning, demanding, considering and deciding. The contextual variables revealed that other patterns (such as phatic and informative) are also used and they coalesced in the hospital within the situational and psychological contexts. However, the paternalistic model was predominantly employed by doctors with over six years in practice, while the interpretive, informative and deliberative models were found among registrar and others below six years of medical practice. Doctors’ experience, patients’ peculiarities and shared cultural knowledge influenced doctor-patient communication in the study.

Keywords: pragmatics, communication pattern, doctor-patient interaction, Nigerian hospital situation

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Authors: Shirin jalili, Hadi Shirzad, Mahasti Modarresi, Samaneh Nabavi, Somayeh Khanjani

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Identifying the source tissue of biological material found at crime scenes can be very informative in a number of cases. Despite their usefulness, current visual, catalytic, enzymatic, and immunologic tests for presumptive and confirmatory tissue identification are applicable only to a subset of samples, might suffer limitations such as low specificity, lack of sensitivity, and are substantially impacted by environmental insults. In addition their results are operator-dependent. Recently the possibility of discriminating body fluids using mRNA expression differences in tissues has been described but lack of long term stability of that Molecule and the need to normalize samples for each individual are limiting factors. The use of DNA should solve these issues because of its long term stability and specificity to each body fluid. Cells in the human body have a unique epigenome, which includes differences in DNA methylation in the promoter of genes. DNA methylation, which occurs at the 5′-position of the cytosine in CpG dinucleotides, has great potential for forensic identification of body fluids, because tissue-specific patterns of DNA methylation have been demonstrated, and DNA is less prone to degradation than proteins or RNA. Previous studies have reported several body fluid-specific DNA methylation markers.The presence or absence of a methyl group on the 5’ carbon of the cytosine pyridine ring in CpG dinucleotide regions called ‘CpG islands’ dictates whether the gene is expressed or silenced in the particular body fluid. Were described methylation patterns at tissue specific differentially methylated regions (tDMRs) to be stable and specific, making them excellent markers for tissue identification. The results demonstrate that methylation-based tissue identification is more than a proof-of-concept. The methodology holds promise as another viable forensic DNA analysis tool for characterization of biological materials.

Keywords: DNA methylation, forensic science, epigenome, tDMRs

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Authors: Chao-Ton Su, Li-Fei Chen

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The parameter design is crucial to improving the uniformity of a product or process. In the product design stage, parameter design aims to determine the optimal settings for the parameters of each element in the system, thereby minimizing the functional deviations of the product. In the process design stage, parameter design aims to determine the operating settings of the manufacturing processes so that non-uniformity in manufacturing processes can be minimized. The parameter design, trying to minimize the influence of noise on the manufacturing system, plays an important role in the high-tech companies. Taiwan has many well-known high-tech companies, which show key roles in the global economy. Quality remains the most important factor that enables these companies to sustain their competitive advantage. In Taiwan however, many high-tech companies face various quality problems. A common challenge is related to root causes and defect patterns. In the R&D stage, root causes are often unknown, and defect patterns are difficult to classify. Additionally, data collection is not easy. Even when high-volume data can be collected, data interpretation is difficult. To overcome these challenges, high-tech companies in Taiwan use more advanced quality improvement tools. In addition to traditional statistical methods and quality tools, the new trend is the application of powerful tools, such as neural network, fuzzy theory, data mining, industrial engineering, operations research, and innovation skills. In this study, several examples of optimizing the parameter settings for the manufacturing process in Taiwan’s tech companies will be presented to illustrate proposed approach’s effectiveness. Finally, a discussion of using traditional experimental design versus the proposed approach for process optimization will be made.

Keywords: quality engineering, parameter design, neural network, genetic algorithm, experimental design

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Authors: Siqin Wang, Jonathan Corcoran, Yan Liu, Thomas Sigler

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Australia is a quintessentially immigrant nation with 28 percent of its residents being foreign-born. By 2011, People’s Republic of China (PRC) overtook the United Kingdom to become the largest source country in Australia. Significantly, the profile of PRC-born migrants has changed to mirror broader global shifts towards high-skilled labour, education-related, and investment-focussed migration, all of which reflect an increasing trend in the mobility of wealthy and/or educated cohorts. Together, these coalesce to form a more complex pattern of migrant settlement –both spatially and socio-economically. This paper focuses on the PRC-born migration, redresses these lacunae, with regard to the settlement outcomes of PRC migrants to Australia, with a particular focus on spatial evolution and residential mobility at both the metropolitan and national scales. By drawing on Census Data and migration Micro Datasets, the aim of this paper is to examine the shifting dynamics of PRC-born migrants in Australian capital cities to unveil their socioeconomic characteristics, residential patterns and change of spatial concentrations during their transition into the new host society. This paper finds out three general patterns in the residential evolution of PRC-born migrants depending on the size of capital cities where they settle down, as well as the association of socio-economic characters with the formation of enclaves. It also examines the residential mobility across states and cities from 2001 to 2011 indicating the rising status of median-size Australian capital cities for receiving PRC-born migrants. The paper concludes with a discussion of evidences for policy formation, facilitates the effective transition of PRC-born populations into the mainstream of host society and enhances social harmony to help Australia become a more successful multicultural nation.

Keywords: Australia, Chinese migrants, residential mobility, spatial evolution

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Authors: Narjes Abbasabadi

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As the world continues to urbanize and suburbanize, where suburbanization associated with mass sprawl has been the dominant form of this expansion, sustainable development challenges will be more concerned. Sprawling, characterized by low density and automobile dependency, presents significant environmental issues regarding energy consumption and Co2 emissions. This paper examines the vertical expansion of suburbs integrated into mass transit nodes as a planning strategy for boosting density, intensification of land use, conversion of single family homes to multifamily dwellings or mixed use buildings and development of viable alternative transportation choices. It analyzes the spatial patterns of tall building transit-oriented development (TB-TOD) of suburban regions in Sydney (Australia), Toronto (Canada), and Washington D.C. (United States). The main objectives of this research seek to understand the effect of the new morphology of suburban tall, the physical dimensions of individual buildings and their arrangement at a larger scale with energy efficiency. This study aims to answer these questions: 1) why and how can the potential phenomenon of vertical expansion or high-rise development be integrated into suburb settings? 2) How can this phenomenon contribute to an overall denser development of suburbs? 3) Which spatial pattern or typologies/ sub-typologies of the TB-TOD model do have the greatest energy efficiency? It addresses these questions by focusing on 1) energy, heat energy demand (excluding cooling and lighting) related to design issues at two levels: macro, urban scale and micro, individual buildings—physical dimension, height, morphology, spatial pattern of tall buildings and their relationship with each other and transport infrastructure; 2) Examining TB-TOD to provide more evidence of how the model works regarding ridership. The findings of the research show that the TB-TOD model can be identified as the most appropriate spatial patterns of tall buildings in suburban settings. And among the TB-TOD typologies/ sub-typologies, compact tall building blocks can be the most energy efficient one. This model is associated with much lower energy demands in buildings at the neighborhood level as well as lower transport needs in an urban scale while detached suburban high rise or low rise suburban housing will have the lowest energy efficiency. The research methodology is based on quantitative study through applying the available literature and static data as well as mapping and visual documentations of urban regions such as Google Earth, Microsoft Bing Bird View and Streetview. It will examine each suburb within each city through the satellite imagery and explore the typologies/ sub-typologies which are morphologically distinct. The study quantifies heat energy efficiency of different spatial patterns through simulation via GIS software.

Keywords: energy efficiency, spatial pattern, suburb, tall building transit-oriented development (TB-TOD)

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Authors: Aparna Lal, Ashwin Swaminathan, Teisa Holani

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Background: Clostridium difficile infections (CDIs) have been on the rise globally. In Australia, rates of CDI in all States and Territories have increased significantly since mid-2011. Identifying risk factors for CDI in the community can help inform targeted interventions to reduce infection. Methods: We examine the role of neighbourhood socio-economic status, demography, testing practices and the number of residential aged care facilities on spatial patterns in CDI incidence in the Australian Capital Territory. Data on all tests conducted for CDI were obtained from ACT Pathology by postcode for the period 1st January 2004 through 31 December 2014. Distribution of age groups and the neighbourhood Index of Relative Socio-economic Advantage Disadvantage (IRSAD) were obtained from the Australian Bureau of Statistics 2011 National Census data. A Bayesian spatial conditional autoregressive model was fitted at the postcode level to quantify the relationship between CDI and socio-demographic factors. To identify CDI hotspots, exceedance probabilities were set at a threshold of twice the estimated relative risk. Results: CDI showed a positive spatial association with the number of tests (RR=1.01, 95% CI 1.00, 1.02) and the resident population over 65 years (RR=1.00, 95% CI 1.00, 1.01). The standardized index of relative socio-economic advantage disadvantage (IRSAD) was significantly negatively associated with CDI (RR=0.74, 95% CI 0.56, 0.94). We identified three postcodes with high probability (0.8-1.0) of excess risk. Conclusions: Here, we demonstrate geographic variations in CDI in the ACT with a positive association of CDI with socioeconomic disadvantage and identify areas with a high probability of elevated risk compared with surrounding communities. These findings highlight community-based risk factors for CDI.

Keywords: spatial, socio-demographic, infection, Clostridium difficile

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Authors: Novee Lor C. Leyso, Maylin C. Palatino

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Under-five malnutrition continues to persist in the Philippines, particularly in the island Province of Marinduque, with prevalence of some forms of malnutrition even worsening in recent years. Local spatial cluster detection provides a spatial perspective in understanding this phenomenon as key in analyzing patterns of geographic variation, identification of community-appropriate programs and interventions, and focused targeting on high-risk areas. Using data from a province-wide household-based census conducted in 2014–2016, this study aimed to determine and evaluate spatial clusters of under-five malnutrition, across the province and within each municipality at the individual level using household location. Malnutrition was defined as weight-for-age z-score that fall outside the 2 standard deviations from the median of the WHO reference population. The Kulldorff’s elliptical spatial scan statistic in binomial model was used to locate clusters with high-risk of malnutrition, while adjusting for age and membership to government conditional cash transfer program as proxy for socio-economic status. One large significant cluster of under-five malnutrition was found southwest of the province, in which living in these areas at least doubles the risk of malnutrition. Additionally, at least one significant cluster were identified within each municipality—mostly located along the coastal areas. All these indicate apparent geographical variations across and within municipalities in the province. There were also similarities and disparities in the patterns of risk of malnutrition in each cluster across municipalities, and even within municipality, suggesting underlying causes at work that warrants further investigation. Therefore, community-appropriate programs and interventions should be identified and should be focused on high-risk areas to maximize limited government resources. Further studies are also recommended to determine factors affecting variations in childhood malnutrition considering the evidence of spatial clustering found in this study.

Keywords: Binomial model, Kulldorff’s elliptical spatial scan statistic, Philippines, under-five malnutrition

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Authors: Akhila Potluru

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Worldwide, more than 250 bodies of water are transboundary, meaning they cross the political boundaries of multiple countries. This creates a system of hydrological, economic, and social interdependence between communities reliant on these water sources. Transboundary water conflicts can occur as a result of this intense interdependence. Many factors contribute to the sparking of transboundary water conflicts, ranging from natural hydrological factors to hydro-political interactions. Previous attempts to predict transboundary water conflicts by analysing changes or trends in the contributing factors have typically failed because patterns in the data are hard to identify. However, there is potential for artificial intelligence and machine learning to fill this gap and identify future ‘hotspots’ up to a year in advance by identifying patterns in data where humans can’t. This research determines the extent to which AI can be used to predict and prevent transboundary water conflicts. This is done via a critical literature review of previous case studies and datasets where AI was deployed to predict water conflict. This research not only delivered a more nuanced understanding of previously undervalued factors that contribute toward transboundary water conflicts (in particular, culture and disinformation) but also by detecting conflict early, governance bodies can engage in processes to de-escalate conflict by providing pre-emptive solutions. Looking forward, this gives rise to significant policy implications and water-sharing agreements, which may be able to prevent water conflicts from developing into wide-scale disasters. Additionally, AI can be used to gain a fuller picture of water-based conflicts in areas where security concerns mean it is not possible to have staff on the ground. Therefore, AI enhances not only the depth of our knowledge about transboundary water conflicts but also the breadth of our knowledge. With demand for water constantly growing, competition between countries over shared water will increasingly lead to water conflict. There has never been a more significant time for us to be able to accurately predict and take precautions to prevent global water conflicts.

Keywords: artificial intelligence, machine learning, transboundary water conflict, water management

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Authors: M. A. Barros, M. V. Barros

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The aim of this work is to analyze the discursive dynamics of preservice teachers during the implementation of a didactic sequence on topics of Quantum Mechanics for High School. Our research methodology was qualitative, case study type, in which we selected two prospective teachers on the Physics Teacher Training Course of the Sao Carlos Institute of Physics, at the University of Sao Paulo/Brazil. The set of modes of communication analyzed were the intentions and interventions of the teachers, the established communicative approach, the patterns and the contents of the interactions between teachers and students. Data were collected through video recording, interviews and questionnaires conducted before and after an 8 hour mini-course, which was offered to a group of 20 secondary students. As teaching strategy we used an active learning methodology, called: Peer Instruction. The episodes pointed out that both future teachers used interactive dialogic and authoritative communicative approaches to mediate the discussion between peers. In the interactive dialogic dimension the communication pattern was predominantly I-R-F (initiation-response-feedback), in which the future teachers assisted the students in the discussion by providing feedback to their initiations and contributing to the progress of the discussions between peers. Although the interactive dialogic dimension has been preferential during the use of the Peer Instruction method the authoritative communicative approach was also employed. In the authoritative dimension, future teachers used predominantly the type I-R-E (initiation-response-evaluation) communication pattern by asking the students several questions and leading them to the correct answer. Among the main implications the work contributes to the improvement of the practices of future teachers involved in applying active learning methodologies in classroom by identifying the types of communicative approaches and communication patterns used, as well as researches on curriculum innovation in physics in high school.

Keywords: curricular innovation, high school, physics teaching, discursive dynamics

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Authors: Md Motibur Rahman

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The present paper attempts to study the electoral politics and voting behavior of 2011 assembly election of West Bengal state in India. Electoral geography is considered as the study of geographical aspects of the organization, conduct, and result of elections. It deals with the spatial voting patterns/behaviour or the study of the spatial distribution of political phenomena of voting. Voting behavior is a form of political psychology which played a great role in political decision-making process. The voting behavior of the electorates is largely influenced by their perception that existing during the time of election. The main focus of the study will be to analyze the electoral politics of the party organizations and political profile of the electorates. The principle objectives of the present work are i) to study the spatial patterns of voting behavior in 2011 assembly election in West Bengal, ii) to analysis the result and finding of 2011 assembly election. The whole study based on the secondary source of data. The electoral data have taken from Election Commission of India, New Delhi and Centre for the study of Developing Societies (CSDS) in New Delhi. In the battle of 2011 Assembly election in West Bengal, the two major parties were Left Front and Trinamool Congress. This election witnessed the remarkable successes of Trinamool Congress and decline of 34 years longest ruler party that is Left Front. Trinamool Congress won a majority of seats that 227 out of 294 but Left Front won only 62 seats out of 294 seats. The significance of the present study is that it helps in understanding the voting pattern, voting behaviour, trends of voting and also helps for further study of electoral geography in West Bengal. The study would be highly significant and helpful to the planners, politicians, and administrators who are involved in the formulation of development plans and programmes for the people of the state.

Keywords: assembly election, electoral geography, electoral politics, voting behaviour

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Authors: Adu-Ampomah Yaw Junior

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Local procurement has become one of the latest trends in the discourse of sustainable tourism due to the economic benefits it generates for tourist destinations in developing countries. Local procurement helps in creating jobs which consequently helps in alleviating poverty. However, there have been limited studies on local procurement patterns in developing countries. Research on hotel procurement practices has mainly emphasized the challenges that hoteliers face when procuring locally, leaving questions regarding their motivations to engage in local procurement unanswered. The institutional theory provides a suitable framework to better understand these motivations as it underlines the importance of individual cognitive perceptions on issues in shaping organizational response strategies. More specifically, the extent to which an issue is perceived to belong to the organization’s responsibility. Also the organizational actors’ belief of losses or gains resultant from acting or not acting on an issue (degree of importance). Furthermore the organizational actors’ belief of the probability of resolving an issue (degree of feasibility). These factors influence how an organization will act on this issue. Hence, this paper adopts an institutional perspective to examine local procurement patterns of food by hoteliers in Ghana. Qualitative interviews with 20 procurement managers about their procurement practices and motivations, as well as interviews with different stakeholders for data triangulation purposes, indicated that most hotels sourced their food from middlemen who imported most of their products. However, direct importation was more prevalent foreign owned hotels as opposed to locally owned ones. Notwithstanding, the importation and the usage of foreign foods as opposed to local ones can be explained by the lack of pressure from NGOs and trade associations on hotels to act responsibly. Though guests’ menu preferences were perceived as important to hoteliers business operations, western tourists demand foreign food primarily with the foreign owned hotels make it less important to procure local produce. Lastly hoteliers, particularly those in foreign owned ones, perceive local procurement to be less feasible, raising concerns about quality and variety of local produce. The paper outlines strategies to improve the perception and degree of local Firstly, there is the need for stakeholder engagement in order to make hoteliers feel responsible for acting on the issue.Again it is crucial for Ghana government to promote and encourage hotels to buy local produce. Also, the government has to also make funds and storage facilities available for farmers to impact on the quality and quantity of local produce. Moreover, Sites need to be secured for farmers to engage in sustained farming.Furthermore, there is the need for collaborations between various stakeholders to organize training programs for farmers. Notwithstanding hotels need to market local produce to their guests. Finally, the Ghana hotels association has to encourage hotels to indulge in local procurement.

Keywords: sustainable tourism, feasible, important, local procurement

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Authors: Reza Nematirad, Anil Pahwa, Balasubramaniam Natarajan

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Time series data consist of successive data points collected over a period of time. Accurate prediction of future values is essential for informed decision-making in several real-world applications, including electricity load demand forecasting, lifetime estimation of industrial machinery, traffic planning, weather prediction, and the stock market. Due to their critical relevance and wide application, there has been considerable interest in time series forecasting in recent years. However, the proliferation of sensors and IoT devices, real-time monitoring systems, and high-frequency trading data introduce significant intricate temporal variations, rapid changes, noise, and non-linearities, making time series forecasting more challenging. Classical methods such as Autoregressive integrated moving average (ARIMA) and Exponential Smoothing aim to extract pre-defined temporal variations, such as trends and seasonality. While these methods are effective for capturing well-defined seasonal patterns and trends, they often struggle with more complex, non-linear patterns present in real-world time series data. In recent years, deep learning has made significant contributions to time series forecasting. Recurrent Neural Networks (RNNs) and their variants, such as Long short-term memory (LSTMs) and Gated Recurrent Units (GRUs), have been widely adopted for modeling sequential data. However, they often suffer from the locality, making it difficult to capture local trends and rapid fluctuations. Convolutional Neural Networks (CNNs), particularly Temporal Convolutional Networks (TCNs), leverage convolutional layers to capture temporal dependencies by applying convolutional filters along the temporal dimension. Despite their advantages, TCNs struggle with capturing relationships between distant time points due to the locality of one-dimensional convolution kernels. Transformers have revolutionized time series forecasting with their powerful attention mechanisms, effectively capturing long-term dependencies and relationships between distant time points. However, the attention mechanism may struggle to discern dependencies directly from scattered time points due to intricate temporal patterns. Lastly, Multi-Layer Perceptrons (MLPs) have also been employed, with models like N-BEATS and LightTS demonstrating success. Despite this, MLPs often face high volatility and computational complexity challenges in long-horizon forecasting. To address intricate temporal variations in time series data, this study introduces Times2D, a novel framework that parallelly integrates 2D spectrogram and derivative heatmap techniques. The spectrogram focuses on the frequency domain, capturing periodicity, while the derivative patterns emphasize the time domain, highlighting sharp fluctuations and turning points. This 2D transformation enables the utilization of powerful computer vision techniques to capture various intricate temporal variations. To evaluate the performance of Times2D, extensive experiments were conducted on standard time series datasets and compared with various state-of-the-art algorithms, including DLinear (2023), TimesNet (2023), Non-stationary Transformer (2022), PatchTST (2023), N-HiTS (2023), Crossformer (2023), MICN (2023), LightTS (2022), FEDformer (2022), FiLM (2022), SCINet (2022a), Autoformer (2021), and Informer (2021) under the same modeling conditions. The initial results demonstrated that Times2D achieves consistent state-of-the-art performance in both short-term and long-term forecasting tasks. Furthermore, the generality of the Times2D framework allows it to be applied to various tasks such as time series imputation, clustering, classification, and anomaly detection, offering potential benefits in any domain that involves sequential data analysis.

Keywords: derivative patterns, spectrogram, time series forecasting, times2D, 2D representation

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