Search results for: emotion mining

Authors: Yana Gorina, Olga Lopatina, Elina Tsigeman, Larisa Mararitsa

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The ability to act in concert with others, the so-called sensorimotor synchronisation, is a fundamental human ability that underlies successful interpersonal coordination. The manifestation of accuracy and plasticity in synchronisation is an adaptive aspect of interaction with the environment, as well as the ability to predict upcoming actions and behaviour of others. The ability to temporarily coordinate one’s actions with a predictable external event is manifested in such types of social behaviour as a synchronised group dance to music played live by an orchestra, group sports (rowing, swimming, etc.), synchronised actions of surgeons during an operation, applause from an admiring audience, walking rhythms, etc. Both our body and mind are involved in achieving the synchronisation during social interactions. However, it has not yet been well described how the brain determine the external rhythm and what neuropeptides coordinate and synchronise actions. Over the past few decades, there has been an increased interest among neuroscientists and neurophysiologists regarding the neuropeptide oxytocin in the context of its complex, diverse and sometimes polar effects manifested in the emotional and social aspects of behaviour (attachment, trust, empathy, emotion recognition, stress response, anxiety and depression, etc.). Presumable, oxytocin might also be involved in social synchronisation processes. The aim of our study is to test the hypothesis that oxytocin is linked to interpersonal synchronisation in a pair of strangers.

Keywords: behavior, movement, oxytocin, synchronization

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Authors: A. Vahanyan

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The paper touches upon the problem of revision and modernization of the current curriculum on translation studies at the Armenian Higher Education Institutions (HEIs). In the contemporary world where quality and speed of services provided are mostly valued, certain higher education centers in Armenia though do not demonstrate enough flexibility in terms of the revision and amendment of courses taught. This issue is present for various curricula at the university level and Translation Studies related curriculum, in particular. Technological innovations that are of great help for translators have been long ago smoothly implemented into the global Translation Industry. According to the European Master's in Translation (EMT) framework, translation service provision comprises linguistic, intercultural, information mining, thematic, and technological competencies. Therefore, to form the competencies mentioned above, the curriculum should be seriously restructured to meet the modern education and job market requirements, relevant courses should be proposed. New courses, in particular, should focus on the formation of technological competences. These suggestions have been made upon the author’s research of the problem across various HEIs in Armenia. The updated curricula should include courses aimed at familiarization with various computer-assisted translation (CAT) tools (MemoQ, Trados, OmegaT, Wordfast, etc.) in the translation process, creation of glossaries and termbases compatible with different platforms), which will ensure consistency in translation of similar texts and speeding up the translation process itself. Another aspect that may be strengthened via curriculum modification is the introduction of interdisciplinary and Project-Based Learning courses, which will enable info mining and thematic competences, which are of great importance as well. Of course, the amendment of the existing curriculum with the mentioned courses will require corresponding faculty development via training, workshops, and seminars. Finally, the provision of extensive internship with translation agencies is strongly recommended as it will ensure the synthesis of theoretical background and practical skills highly required for the specific area. Summing up, restructuring and modernization of the existing curricula on Translation Studies should focus on three major aspects, i.e., introduction of new courses that meet the global quality standards of education, professional development for faculty, and integration of extensive internship supervised by experts in the field.

Keywords: competencies, curriculum, modernization, technical literacy, translation studies

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Authors: Nabilah Filzah Mohd Radzuan, Zalinda Othman, Azuraliza Abu Bakar, Abdul Razak Hamdan

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Uncertain data is believed to be an important issue in building up a prediction model. The main objective in the time series uncertainty analysis is to formulate uncertain data in order to gain knowledge and fit low dimensional model prior to a prediction task. This paper discusses the performance of a number of techniques in dealing with uncertain data specifically those which solve uncertain data condition by minimizing the loss of compression properties.

Keywords: compression properties, uncertainty, uncertain time series, mining technique, weather prediction

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Authors: Dauda A. Oladosu, Kamorudeen A Olaiya, Abdurahman Bello

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The deployment of smart meters by utility providers to gather fine grained spatiotemporal consumption data has grossly influenced the consumers’ emotion and behavior towards energy utilization. The quest for reduction in power consumption is now a subject of concern and one the methods adopted by the consumers to achieve this is Non-intrusive Load (appliance) Monitoring. Hence, this work presents performance Analysis of Domotics System as a tool for load monitoring when integrated with Consumer Control Unit of residential building. The system was developed with basic elements which enhance remote sensing, DTMF (Dual Tone Multi-frequency) recognition and cryptic messaging when specific task was performed. To demonstrate its applicability and suitability, this prototype was used consistently for six months at different load demands and the utilities consumed were documented. The results obtained shows good response when phone dialed, and the packet delivery of feedback SMS was quite satisfactory, making the implemented system to be of good quality with affordable cost and performs the desired functions. Besides, comparative analysis showed notable reduction in energy consumption and invariably lessened electrical bill of the consumer.

Keywords: automation, domotics, energy, load, remote, schedule

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Authors: Methawee Yuttapongtada

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Intensifier is the linguistic term and device that is generally found in different languages in order to enhance and give additional quantity, quality or emotion to the words of each language. In fact, each language in the world has both of the similar and dissimilar intensifying device. More specially, the wide variety of intensifying device is used for Thai language and one of those is usage of the impolite word or the word that used to mean something negative as intensifier. The data collection in this study was done throughout the spoken language style by collecting from intensifiers regarded as impolite words because these words as employed in the other contexts will be held as the rude, swear words or the words with negative meaning. Then, backward study to the past was done in order to consider the historical change. Explanation of the original meaning and the contexts of words use from the past till the present time were done by use of both textual documents and dictionaries available in different periods. It was found that regarding the semantics and pragmatic aspects, subjectification also is the significant motivation that changed the impolite words to intensifiers. At last, it can explain pathway of the semantic change of these very words undoubtedly. Moreover, it is found that use tendency in the impolite word or the word that used to mean something negative will more be increased and this phenomenon is commonly found in many languages in the world and results of this research may support to the belief that human language in the world is universal and the same still reflected that human has the fundamental thought as the same to each other basically.

Keywords: impolite word, intensifier, Thai, semantic change

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Authors: Long Xumeng

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Place attachment focuses on the emotions and practices between people and their environment, and the influencing factors of place attachment vary depending on the nature of the place. As an important carrier of public slow-moving activities and urban culture, the feelings, cognition, and behaviors of the subjects involved in the use of mountain city trails have become the focus of research in this field. This paper will take Daijiaxiang Cliff Walkway in Yuzhong District, Chongqing City, as an example and analyze the evaluation results and correlation of each factor through questionnaire survey and field observation, using the three scales of Recreational Experience Scale, Satisfaction Scale, and Place Attachment Scale, as well as the intensity of activity, by using SPSS software. The study shows that there is a significant difference between the demographic variables of users' identity and age and the formation of place attachment; the degree of place attachment is significantly positively correlated with the emotion, industry, and service quality of recreational experience; and the recreational experience of the Mountain City Trail is significantly positively correlated with the overall satisfaction. By analyzing the influencing factors of recreational experience, satisfaction and place attachment, the corresponding conclusions and enhancement strategies were drawn to provide references for the renewal and construction of mountain city trails.

Keywords: mountain city trail, place attachment, recreational experience, satisfaction, urban renewal

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Authors: S. Umar, B. F. Umar

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This study was conducted at Giron Masa village, located 30 km from Yauri town. The study determines the socio-economic factors influencing the use of coping strategies among farmers and herders during post-conflict situation. Simple random sampling was employed to select one hundred respondents (50 farmers and 50 herders) from the study area. Logistic regression analysis (LR) was used to ascertain the socioeconomic variables that influenced the use of the coping strategies. The results of the study shows that age, income, family size and farming experience were individually significant and thus influenced the use of POCS by farmers. Annual income and production system influenced the use of POCS by herders. Age, farm size and farming experience were found to be individually significant in influencing the use of EOCS among farmers. Specifically, years of occupation experience among the herders increased the use of emotion oriented coping strategies among herders. The use of SSCS among farmers was influenced by educational level; farm size and farming experience, while the variables are not collectively significant in influencing the use of SSCS among the herders. The research recommends a need to adopt the strategy of community coping to cope with stress.

Keywords: farmers, herders, conflict, coping strategies

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Authors: Said Baadel, Fadi Thabtah, Joan Lu

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Clustering involves the partitioning of n objects into k clusters. Many clustering algorithms use hard-partitioning techniques where each object is assigned to one cluster. In this paper, we propose an overlapping algorithm MCOKE which allows objects to belong to one or more clusters. The algorithm is different from fuzzy clustering techniques because objects that overlap are assigned a membership value of 1 (one) as opposed to a fuzzy membership degree. The algorithm is also different from other overlapping algorithms that require a similarity threshold to be defined as a priority which can be difficult to determine by novice users.

Keywords: data mining, k-means, MCOKE, overlapping

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Authors: Frode van der Laak

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The paper contributes to the feasibility of using a 5G mobile connection as a node for a Proof of Authority (PoA) blockchain, which is used for microtransactions at the same time. It uses the phone number identity of the users that are linked to the crypto wallet address. It also proposed a consensus protocol based on Proof-of-Authority (PoA) blockchain; PoA is a permission blockchain where consensus is achieved through a set of designated authority rather than through mining, as is the case with a Proof of Work (PoW) blockchain. This report will first explain the concept of a PoA blockchain and how it works. It will then discuss the potential benefits and challenges of using a 5G mobile connection as a node in such a blockchain, and finally, the main open problem statement and proposed solutions with the requirements.

Keywords: 5G, mobile, connection, node, PoA, blockchain, microtransaction

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Authors: Seyed Roozbeh Pishva, Alireza Aboudi Asl

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In this investigation a hydrocyclone by using for separation particles from fluid in oil and gas, mining and other industries is simulated. Case study is cone – cylindrical and solid - liquid hydrocyclone. The fluid is water and the solid is a type of silis having diameters of 53, 75, 106, 150, 212, 250, and 300 micron. In this investigation CFD method used for analysis flow and movement of particles in hydrocyclone. In this modeling flow is three-dimention, turbulence and RSM model have been used for solving. Particles are three dimensional, spherical and non rotating and for tracking them Lagrangian model is used. The results of this study in addition to analyzing flowfield, obtaining efficiency of hydrocyclone in 5, 7, 12, and 15 percent concentrations and compare them with experimental result that both of them had suitable agreement with each other.

Keywords: hydrocyclone, RSM Model, CFD, copper industry

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Authors: Yun Hang Stanley Cheung

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In recent years, many educators and entrepreneurs have often suggested that students’ and workers’ ability of the adversity response is very important, it would affect problem-solving strategies and ultimate success in their career or life. The meaning of resilience is discussed as the process of bouncing back and the ability to adapt well in adversity’s response, being resilient does not mean to live without any stress and difficulty, but to grow and thrive under pressure. The purpose of this study is to describe the process of resilience and adversity’s response. The use of the narrative inquiry aims for understanding the experiential process of adversity response, and the problem-solving strategies (such as emotion control, motivation, decisions making process), as well as making the experience become life story, which may be evaluated by its teller and its listeners. The narrative study describes the researcher’s self-experience of adversity’s response to the recovery of the seriously burnt injury from a hill fire at his 12 years old, as well as the adversities and obstacles related to the tragedy after the physical recovery. Sense-Making Theory and McCormack’s Lenses were used for constructive perspective and data analyzing. To conclude, this study has described the life story of fighting the adversities, also, those narratives come out some suggestions, which point out positive thinking is necessary to build up resilience and the ability of immediate adversity response. Also, some problem-solving strategies toward adversities are discussed, which are helpful for resilience education for youth and young adult.

Keywords: adversity response, life story, narrative inquiry, resilience

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Authors: Patricia Jiménez, Rafael Corchuelo, Hassan A. Sleiman

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Web mining is gaining importance at an increasing pace. Currently, there are many complementary research topics under this umbrella. Their common theme is that they all focus on applying knowledge discovery techniques to data that is gathered from the Web. Sometimes, these data are relatively easy to gather, chiefly when it comes from server logs. Unfortunately, there are cases in which the data to be mined is the data that is displayed on a web document. In such cases, it is necessary to apply a pre-processing step to first extract the information of interest from the web documents. Such pre-processing steps are performed using so-called information extractors, which are software components that are typically configured by means of rules that are tailored to extracting the information of interest from a web page and structuring it according to a pre-defined schema. Paramount to getting good mining results is that the technique used to extract the source information is exact, which requires to evaluate and compare the different proposals in the literature from an empirical point of view. According to Google Scholar, about 4 200 papers on information extraction have been published during the last decade. Unfortunately, they were not evaluated within a homogeneous framework, which leads to difficulties to compare them empirically. In this paper, we report on an original information extraction evaluation method. Our contribution is three-fold: a) this is the first attempt to provide an evaluation method for proposals that work on semi-structured documents; the little existing work on this topic focuses on proposals that work on free text, which has little to do with extracting information from semi-structured documents. b) It provides a method that relies on statistically sound tests to support the conclusions drawn; the previous work does not provide clear guidelines or recommend statistically sound tests, but rather a survey that collects many features to take into account as well as related work; c) We provide a novel method to compute the performance measures regarding unsupervised proposals; otherwise they would require the intervention of a user to compute them by using the annotations on the evaluation sets and the information extracted. Our contributions will definitely help researchers in this area make sure that they have advanced the state of the art not only conceptually, but from an empirical point of view; it will also help practitioners make informed decisions on which proposal is the most adequate for a particular problem. This conference is a good forum to discuss on our ideas so that we can spread them to help improve the evaluation of information extraction proposals and gather valuable feedback from other researchers.

Keywords: web information extractors, information extraction evaluation method, Google scholar, web

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Authors: Joanna Cabaj, Sylwia Baluta, Karol Malecha

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Catecholamines are vital neurotransmitters that mediate a variety of central nervous system functions, such as motor control, cognition, emotion, memory processing, and endocrine modulation. Dysfunctions in catecholamine neurotransmission are induced in some neurologic and neuropsychiatric diseases. Changeable neurotransmitters level in biological fluids can be a marker of several neurological disorders. Because of its significance in analytical techniques and diagnostics, sensitive and selective detection of neurotransmitters is increasingly attracting a lot of attention in different areas of bio-analysis or biomedical research. Recently, optical techniques for the detection of catecholamines have attracted interests due to their reasonable cost, convenient control, as well as maneuverability in biological environments. Nevertheless, with the observed need for a sensitive and selective catecholamines sensor, the development of a convenient method for this neurotransmitter is still at its basic level. The manipulation of nanostructured materials in conjunction with biological molecules has led to the development of a new class of hybrid-modified enzymatic sensors in which both enhancement of charge transport and biological activity preservation may be obtained. Immobilization of biomaterials on electrode surfaces is the crucial step in fabricating electrochemical as well as optical biosensors and bioelectronic devices. Continuing systematic investigation in manufacturing of enzyme–conducting sensitive systems, here is presented a convenient fluorescence as well as electrochemical sensing strategy for catecholamines detection.

Keywords: biosensors, catecholamines, fluorescence, enzymes

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Authors: Wei Yaming

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Objective: In order to compare the stress of employees sent overseas with (GRAS) before and after, we used the resource-oriented music listening intervention in this study. We also collected pertinent experimental data. Methods: The experiment involved 47 employees who were sent abroad by the Chinese side. They completed the stress scale test and documented it before the intervention. They tested for stress after five interventions and performed one-on-one interviews. Quantitative data and SPSS software were used to analyze relationships between stress reduction and resource-oriented music listening, as well as Pearson's correlation, multiple regression levels, and ANOVA. For the qualitative analysis, content analysis of one-on-one interviews was performed. Results: A comparison of data from before and after demonstrates how resource-focused music listening activities can lessen and relieve stress in remote workers. In the qualitative study, stress is broken down into six categories: relationship stress, health stress, emotional stress, and frustration stress. External pressures include work pressure and cultural stress. And it has been determined that listening to music that is resource-oriented can better ease internal stress (health, emotion, and dissatisfaction). Conclusion: The Guide Resource-oriented Music Listening (GROML) Program appears to have had some effect on the participants' stress levels. The resources that the participants encountered while listening to music are bravery, calm, letting go, and relaxing.

Keywords: resource-oriented, music listening, oversea dispatch employees, work stress

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Authors: Aysheh Maslemani, Ruth Mayo, Greg Maio, Ariel Knafo-Noam

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Values are abstract ideals that serve as guiding principles in one's life. As inherently positive and desirable concepts, values are seen as motivators for actions and behaviors. However, research has largely ignored the possibility that values may elicit negative feelings despite being explicitly important to us. In the current study, we aim to examine this possibility. Four hundred participants over 18 years(M=41.6, SD=13.7, Female=178) from the UK completed a questionnaire in which they were asked to indicate their level of positive/negative feelings towards a comprehensive list of values and then report the importance of these values to them. The results support our argument by showing that people can have negative feelings towards their values and that people can feel both positive and negative emotions towards their values simultaneously, which means feeling ambivalence. We ran a mixed-effect model with ambivalence, value type, and their interaction as fixed effects, with by subject random intercept and by subject random slope for ambivalence. The results reveal that values that elicit less ambivalence predicted higher ratings for value importance. This research contributes to the field of values on multiple levels. Theoretically, it will uncover new insights about values, such as the existence of negative emotions towards them and the presence of ambivalence towards values. These findings may inspire future studies to explore the effects of ambivalence on people's well-being, behaviors, cognition, and their affect. We discuss the findings and consider their implications for understanding the social psychological mechanisms underpinning value ambivalence.

Keywords: emotion, social cognition, values., ambivalence

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Authors: Aysheh Maslemani, Ruth Mayo, Greg Maio, Ariel Knafo-Noam

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Values are abstract ideals that serve as guiding principles in one's life. As inherently positive and desirable concepts, values are seen as motivators for actions and behaviors. However, research has largely ignored the possibility that values may elicit negative feelings despite being explicitly important to us. In the current study we aim to examine this possibility. Four hundred participants over 18 years(M=41.6,SD=13.7,Female=178) from the UK completed a questionnaire in which they were asked to indicate their level of positive/negative feelings towards a comprehensive list of values and then report the importance of these values to them. The results support our argument by showing that people can have negative feelings towards their values and that people can feel both positive and negative emotions towards their values simultaneously, which means feeling ambivalence. We ran a mixed-effect model with ambivalence, value type, and their interaction as fixed effects, with by subject random intercept, and by subject random slope for ambivalence. The results reveal that values that elicit less ambivalence predicted higher ratings for value importance. This research contributes to the field of values on multiple levels. Theoretically, it will uncover new insights about values, such as the existence of negative emotions towards them, the presence of ambivalence towards values. These findings may inspire future studies to explore the effects of ambivalence on people's well-being, behaviors, cognition, and their affect. We discuss the findings and consider their implications for understanding the social psychological mechanisms underpinning value ambivalence.

Keywords: ambivalence, emotion, social cognition, values

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Authors: Arvinder Kaur, Deepti Chopra

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Software Entropy Metrics for bug prediction have been validated on various software systems by different researchers. In our previous research, we have validated that Software Entropy Metrics calculated for Mozilla subsystem’s predict the future bugs reasonably well. In this study, the Software Entropy metrics are calculated for a subsystem of Android and it is noticed that these metrics are not suitable for bug prediction. The results are compared with a subsystem of Mozilla and a comparison is made between the two software systems to determine the reasons why Software Entropy metrics are not applicable for Android.

Keywords: android, bug prediction, mining software repositories, software entropy

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Authors: Wuttigrai Ngamsirijit

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Creative tourism is an ongoing development in many countries as an attempt to moving away from serial reproduction of culture and reviving the culture. Despite, in the destinations with diverse and potential cultural resources, creating new tourism services can be vague. This paper presents how tourism experiences are modularized and consolidated in order to form new creative tourism service offerings in evanescent cultural communities of Bangkok, Thailand. The benefits from data mining in accommodating value co-creation are discussed, and implication of experience modularization to national creative tourism policy is addressed.

Keywords: co-creation, creative tourism, new service design, experience modularization

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Authors: Abrehet Kahsay Mehari

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Aquatic plants provide the physical structure of wetlands and increase their habitat complexity and heterogeneity, and as such, have a profound influence on other biotas. In this study, we investigated how human disturbance activities influenced the species richness and community composition of aquatic plants in the wetlands of Lake Tana, Ethiopia. Twelve wetlands were selected: four lacustrine, four river mouths, and four riverine papyrus swamps. Data on aquatic plants, environmental variables, and human activities were collected during the dry and wet seasons of 2018. A linear mixed effect model and a distance-based Redundancy Analysis (db-RDA) were used to relate aquatic plant species richness and community composition, respectively, to human activities and environmental variables. A total of 113 aquatic plant species, belonging to 38 families, were identified across all wetlands during the dry and wet seasons. Emergent species had the maximum area covered at 73.45 % and attained the highest relative abundance, followed by amphibious and other forms. The mean taxonomic richness of aquatic plants was significantly lower in wetlands with high overall human disturbance scores compared to wetlands with low overall human disturbance scores. Moreover, taxonomic richness showed a negative correlation with livestock grazing, tree plantation, and sand mining. The community composition also varied across wetlands with varying levels of human disturbance and was primarily driven by turnover (i.e., replacement of species) rather than nestedness resultant(i.e., loss of species). Distance-based redundancy analysis revealed that livestock grazing, tree plantation, sand mining, waste dumping, and crop cultivation were significant predictors of variation in aquatic plant communities’ composition in the wetlands. Linear mixed effect models and distance-based redundancy analysis also revealed that water depth, turbidity, conductivity, pH, sediment depth, and temperature were important drivers of variations in aquatic plant species richness and community composition. Papyrus swamps had the highest species richness and supported different plant communities. Conservation efforts should therefore focus on these habitats and measures should be taken to restore the highly disturbed and species poor wetlands near the river mouths.

Keywords: species richness, community composition, aquatic plants, wetlands, Lake Tana, human disturbance activities

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Authors: Della Saddam Housseyn

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Gold, the quintessential noble metal, is one of the most popular metals today, given its ever-increasing cost in the international market. The Amesmessa gold deposit is one of the gold-producing deposits. The first step in our job is to analyze the ore (considered rich ore). Mineralogical and chemical analysis has shown that the general constitution of the ore is quartz in addition to other phases such as Al2O3, Fe2O3, CaO, dolomite. The second step consists of all the leaching tests carried out in rolling bottles. These tests were carried out on 14 samples to determine the maximum recovery rate and the optimum consumption of reagent (NaCN and CaO). Tests carried out on a pulp density at 50% solid, 500 ppm cyanide concentration and particle size less than 0.6 mm at alkaline pH gave a recovery rate of 94.37%.

Keywords: cyanide, DRX, FX, gold, leaching, rate of recovery, SAA

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Authors: Marie Alaghband, Niloofar Yousefi, Ivan Garibay

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Facial expressions are important parts of both gesture and sign language recognition systems. Despite the recent advances in both fields, annotated facial expression datasets in the context of sign language are still scarce resources. In this manuscript, we introduce an annotated sequenced facial expression dataset in the context of sign language, comprising over 3000 facial images extracted from the daily news and weather forecast of the public tv-station PHOENIX. Unlike the majority of currently existing facial expression datasets, FePh provides sequenced semi-blurry facial images with different head poses, orientations, and movements. In addition, in the majority of images, identities are mouthing the words, which makes the data more challenging. To annotate this dataset we consider primary, secondary, and tertiary dyads of seven basic emotions of "sad", "surprise", "fear", "angry", "neutral", "disgust", and "happy". We also considered the "None" class if the image’s facial expression could not be described by any of the aforementioned emotions. Although we provide FePh as a facial expression dataset of signers in sign language, it has a wider application in gesture recognition and Human Computer Interaction (HCI) systems.

Keywords: annotated facial expression dataset, gesture recognition, sequenced facial expression dataset, sign language recognition

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Authors: Hoda Rahmani, Gary Weckman

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The body of research examining the integration of drones into various industries is expanding rapidly. Despite progress made in addressing the cybersecurity concerns for commercial drones, knowledge deficits remain in determining potential occupational hazards and risks of drone use to employees’ well-being and health in the workplace. This creates difficulty in identifying key approaches to risk mitigation strategies and thus reflects the need for raising awareness among employers, safety professionals, and policymakers about workplace drone-related accidents. The purpose of this study is to investigate the prevalence of and possible risk factors for drone-related mishaps by comparing the application of drones in construction with manufacturing industries. The chief reason for considering these specific sectors is to ascertain whether there exists any significant difference between indoor and outdoor flights since most construction sites use drones outside and vice versa. Therefore, the current research seeks to examine the causes and patterns of workplace drone-related mishaps and suggest possible ergonomic interventions through data collection. Potential ergonomic practices to mitigate hazards associated with flying drones could include providing operators with professional pieces of training, conducting a risk analysis, and promoting the use of personal protective equipment. For the purpose of data analysis, two data mining techniques, the random forest and association rule mining algorithms, will be performed to find meaningful associations and trends in data as well as influential features that have an impact on the occurrence of drone-related accidents in construction and manufacturing sectors. In addition, Spearman’s correlation and chi-square tests will be used to measure the possible correlation between different variables. Indeed, by recognizing risks and hazards, occupational safety stakeholders will be able to pursue data-driven and evidence-based policy change with the aim of reducing drone mishaps, increasing productivity, creating a safer work environment, and extending human performance in safe and fulfilling ways. This research study was supported by the National Institute for Occupational Safety and Health through the Pilot Research Project Training Program of the University of Cincinnati Education and Research Center Grant #T42OH008432.

Keywords: commercial drones, ergonomic interventions, occupational safety, pattern recognition

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Authors: Likewin Thomas, M. V. Manoj Kumar, B. Annappa

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The aim of this study was to develop an Artificial Neural Network0 s recommendation model for an online process using the complexity of load, performance, and average servicing time of the resources. Here, the proposed model investigates the resource performance using stochastic gradient decent method for learning ranking function. A probabilistic cost function is implemented to identify the optimal θ values (load) on each resource. Based on this result the recommendation of resource suitable for performing the currently executing task is made. The test result of CoSeLoG project is presented with an accuracy of 72.856%.

Keywords: ADALINE, neural network, gradient decent, process mining, resource behaviour, polynomial regression model

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Authors: Hussaini Garba Mohammed

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Background/Significance: The lack of data gathering is affecting NGOs world-wide in general to have good data information about educational and health related issues among communities in any country and around the world. For example, HIV/AIDS smoking (Tuberculosis diseases) and COVID-19 virus carriers is becoming a serious public health problem, especially among old men and women. But there is no full details data survey assessment from communities, villages, and rural area in some countries to show the percentage of victims and patients, especial with this world COVID-19 virus among the people. These data are essential to inform programming targets, strategies, and priorities in getting good information about data gathering in any society.

Keywords: reliable information, data assessment, data mining, data communication

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Authors: M. Turmanauli, T. Todua, O. Gvaberidze, R. Javakhadze, N. Chkhaidze, N. Khatiashvili

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Background: Mining process has the significant influence on human health and quality of life. In recent years the events in Georgia were reflected on the industry working process, especially minimal requirements of labor safety, hygiene standards of workplace and the regime of work and rest are not observed. This situation is often caused by the lack of responsibility, awareness, and knowledge both of workers and employers. The control of working conditions and its protection has been worsened in many of industries. Materials and Methods: For evaluation of the current situation the prospective epidemiological study by face to face interview method was conducted at Georgian “Manganese Zestafoni Ferroalloy Plant” in 2011-2013. 65.7% of employees (1428 bulletin) were surveyed and the incidence rates of temporary disability days were studied. Results: The average length of a temporary disability single accident was studied taking into consideration as sex groups as well as the whole cohort. According to the classes of harmfulness the following results were received: Class 2.0-10.3%; 3.1-12.4%; 3.2-35.1%; 3.3-12.1%; 3.4-17.6%; 4.0-12.5%. Among the employees 47.5% and 83.1% were tobacco and alcohol consumers respectively. According to the age groups and years of work on the base of previous experience ≥50 ages and ≥21 years of work data prevalence respectively. The obtained data revealed increased morbidity rate according to age and years of work. It was found that the bone and articulate system and connective tissue diseases, aggravation of chronic respiratory diseases, ischemic heart diseases, hypertension and cerebral blood discirculation were the leading among the other diseases. High prevalence of morbidity observed in the workplace with not satisfactory labor conditions from the hygienic point of view. Conclusion: According to received data the causes of morbidity are the followings: unsafety labor conditions; incomplete of preventive medical examinations (preliminary and periodic); lack of access to appropriate health care services; derangement of gathering, recording, and analysis of morbidity data. This epidemiological study was conducted at the JSC “Manganese Ferro Alloy Plant” according to State program “ Prevention of Occupational Diseases” (Program code is 35 03 02 05).

Keywords: occupational health, mining process, morbidity level, cerebral blood discirculation

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Authors: Zeren Li, Wenkai Song

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Shanghai experienced a 3-month lockdown in 2022. This unprecedented lockdown made local residents afraid, anxious and worried about the unpredictability of the future. During the lockdown, many unethical behaviors related to lockdown are noticed by the public. Our studies documented unethical behavior during this lockdown by moral hypocrisy and moral justification examined whether or not the lockdown makes people behave more unethically, and analyzed the relationship between negative emotions and unethical behavior. In Study 1, we recruited 240 participants from Shanghai (n = 120) and other cities (n = 120) to compare people in lockdown and non-lockdown areas. Surprisingly, we found that people in lockdown areas tend to behave more ethically, exhibiting less moral hypocrisy. In addition, residents of the lockdown area have significantly higher negative emotions (afraid, nervousness, upset, and feelings of uncertainty). In Study 2, we recruited 70 respondents from Shanghai and found that people behave relatively ethically in lockdown-related scenarios (negatively correlated with anxiety about the lockdown) with relatively less moral justification than in lockdown-unrelated scenarios. We propose that negative emotions may reduce unethical behavior that may exacerbate the causes (in our study, the lockdown) of these negative emotions. Experiments may help to establish the causal relationship and verify the model in future research.

Keywords: COVID-19, unethical behavior, emotion, anxiety, moral justification, moral hypocrisy, China

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Authors: T. Hari Prasath, P. Ithaya Rani

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In the world of visual technology, recognizing emotions from the face images is a challenging task. Several related methods have not utilized the dynamic facial features effectively for high performance. This paper proposes a method for emotions recognition using dynamic facial features with high performance. Initially, local features are captured by Gabor filter with different scale and orientations in each frame for finding the position and scale of face part from different backgrounds. The Gabor features are sent to the ensemble classifier for detecting Gabor facial features. The region of dynamic features is captured from the Gabor facial features in the consecutive frames which represent the dynamic variations of facial appearances. In each region of dynamic features is normalized using Z-score normalization method which is further encoded into binary pattern features with the help of threshold values. The binary features are passed to Multi-class AdaBoost classifier algorithm with the well-trained database contain happiness, sadness, surprise, fear, anger, disgust, and neutral expressions to classify the discriminative dynamic features for emotions recognition. The developed method is deployed on the Ryerson Multimedia Research Lab and Cohn-Kanade databases and they show significant performance improvement owing to their dynamic features when compared with the existing methods.

Keywords: detecting face, Gabor filter, multi-class AdaBoost classifier, Z-score normalization

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Authors: Avelyno D'Costa, S. K. Shyama, M. K. Praveen Kumar

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The coast of Goa, India receives constant anthropogenic stress through its major rivers which carry mining rejects of iron and manganese ores from upstream mining sites and petroleum hydrocarbons from shipping and harbor-related activities which put the aquatic fauna such as bivalves at risk. The present study reports the pollution status of the Goan coast by the above xenobiotics employing genotoxicity studies. This is further supplemented by the quantification of total petroleum hydrocarbons (TPHs) and various trace metals (iron, manganese, copper, cadmium, and lead) in gills of the estuarine clam, Meretrix ovum as well as from the surrounding water and sediment, over a two-year sampling period, from January 2013 to December 2014. Bivalves were collected from a probable unpolluted site at Palolem and a probable polluted site at Vasco, based upon the anthropogenic activities at these sites. Genotoxicity was assessed in the gill cells using the comet assay and micronucleus test. The quantity of TPHs and trace metals present in gill tissue, water and sediments were analyzed using spectrofluorometry and atomic absorption spectrophotometry (AAS), respectively. The statistical significance of data was analyzed employing Student’s t-test. The relationship between DNA damage and pollutant concentrations was evaluated using multiple regression analysis. Significant DNA damage was observed in the bivalves collected from Vasco which is a region of high industrial activity. Concentrations of TPHs and trace metals (iron, manganese, and cadmium) were also found to be significantly high in gills of the bivalves collected from Vasco compared to those collected from Palolem. Further, the concentrations of these pollutants were also found to be significantly high in the water and sediments at Vasco compared to that of Palolem. This may be due to the lack of industrial activity at Palolem. A high positive correlation was observed between the pollutant levels and DNA damage in the bivalves collected from Vasco suggesting the genotoxic nature of these pollutants. Further, M. ovum can be used as a bioindicator species for monitoring the level of pollution of the estuarine/coastal regions by TPHs and trace metals.

Keywords: comet assay, metals, micronucleus test, total petroleum Hydrocarbons

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Authors: Erin Hea-Jin Kim

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This study aims to investigate scholarly communication patterns in Korean studies, which focuses on all aspects of Korea, including history, culture, literature, politics, society, economics, religion, and so on. It is called ‘national study or home study’ as the subject of the study is itself, whereas it is called ‘area study’ as the subject of the study is others, i.e., outside of Korea. Understanding of the structure of scholarly communication in Korean studies is important since the motivations, procedures, results, or outcomes of individual studies may be affected by the cooperative relationships that appear in the communication structure. To this end, we collected 1,798 articles with the (author or index) keyword ‘Korean’ published in 2018 from the Scopus database and extracted the institution and country of the authors using a text mining technique. A total of 96 countries, including South Korea, was identified. Then we constructed a co-authorship network based on the countries identified. The indicators of social network analysis (SNA), co-occurrences, and cluster analysis were used to measure the activity and connectivity of participation in collaboration in Korean studies. As a result, the highest frequency of collaboration appears in the following order: S. Korea with the United States (603), S. Korea with Japan (146), S. Korea with China (131), S. Korea with the United Kingdom (83), and China with the United States (65). This means that the most active participants are S. Korea as well as the USA. The highest rank in the role of mediator measured by betweenness centrality appears in the following order: United States (0.165), United Kingdom (0.045), China (0.043), Japan (0.037), Australia (0.026), and South Africa (0.023). These results show that these countries contribute to connecting in Korean studies. We found two major communities among the co-authorship network. Asian countries and America belong to the same community, and the United Kingdom and European countries belong to the other community. Korean studies have a long history, and the study has emerged since Japanese colonization. However, Korean studies have never been investigated by digital content analysis. The contributions of this study are an analysis of co-authorship in Korean studies with a global perspective based on digital content, which has not attempted so far to our knowledge, and to suggest ideas on how to analyze the humanities disciplines such as history, literature, or Korean studies by text mining. The limitation of this study is that the scholarly data we collected did not cover all domestic journals because we only gathered scholarly data from Scopus. There are thousands of domestic journals not indexed in Scopus that we can consider in terms of national studies, but are not possible to collect.

Keywords: co-authorship network, Korean studies, Koreanology, scholarly communication

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Authors: Trupti Diwan

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Predicting student failure at school has changed into a difficult challenge due to both the large number of factors that can affect the reduced performance of students and the imbalanced nature of these kinds of data sets. This paper surveys the two elements needed to make prediction on Students’ Academic Performances which are parameters and methods. This paper also proposes a framework for predicting the performance of engineering students. Genetic programming can be used to predict student failure/success. Ranking algorithm is used to rank students according to their credit points. The framework can be used as a basis for the system implementation & prediction of students’ Academic Performance in Higher Learning Institute.

Keywords: classification, educational data mining, student failure, grammar-based genetic programming

Procedia PDF Downloads 422