Search results for: content based image retrieval (CBIR)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33344

Search results for: content based image retrieval (CBIR)

24194 A Machine Learning-Based Model to Screen Antituberculosis Compound Targeted against LprG Lipoprotein of Mycobacterium tuberculosis

Authors: Syed Asif Hassan, Syed Atif Hassan

Abstract:

Multidrug-resistant Tuberculosis (MDR-TB) is an infection caused by the resistant strains of Mycobacterium tuberculosis that do not respond either to isoniazid or rifampicin, which are the most important anti-TB drugs. The increase in the occurrence of a drug-resistance strain of MTB calls for an intensive search of novel target-based therapeutics. In this context LprG (Rv1411c) a lipoprotein from MTB plays a pivotal role in the immune evasion of Mtb leading to survival and propagation of the bacterium within the host cell. Therefore, a machine learning method will be developed for generating a computational model that could predict for a potential anti LprG activity of the novel antituberculosis compound. The present study will utilize dataset from PubChem database maintained by National Center for Biotechnology Information (NCBI). The dataset involves compounds screened against MTB were categorized as active and inactive based upon PubChem activity score. PowerMV, a molecular descriptor generator, and visualization tool will be used to generate the 2D molecular descriptors for the actives and inactive compounds present in the dataset. The 2D molecular descriptors generated from PowerMV will be used as features. We feed these features into three different classifiers, namely, random forest, a deep neural network, and a recurring neural network, to build separate predictive models and choosing the best performing model based on the accuracy of predicting novel antituberculosis compound with an anti LprG activity. Additionally, the efficacy of predicted active compounds will be screened using SMARTS filter to choose molecule with drug-like features.

Keywords: antituberculosis drug, classifier, machine learning, molecular descriptors, prediction

Procedia PDF Downloads 384
24193 Nazca: A Context-Based Matching Method for Searching Heterogeneous Structures

Authors: Karine B. de Oliveira, Carina F. Dorneles

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The structure level matching is the problem of combining elements of a structure, which can be represented as entities, classes, XML elements, web forms, and so on. This is a challenge due to large number of distinct representations of semantically similar structures. This paper describes a structure-based matching method applied to search for different representations in data sources, considering the similarity between elements of two structures and the data source context. Using real data sources, we have conducted an experimental study comparing our approach with our baseline implementation and with another important schema matching approach. We demonstrate that our proposal reaches higher precision than the baseline.

Keywords: context, data source, index, matching, search, similarity, structure

Procedia PDF Downloads 355
24192 Developing a Green Strategic Management Model with regarding HSE-MS

Authors: Amin Padash, Gholam Reza Nabi Bid Hendi, Hassan Hoveidi

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Purpose: The aim of this research is developing a model for green management based on Health, Safety and Environmental Management System. An HSE-MS can be a powerful tool for organizations to both improve their environmental, health and safety performance, and enhance their business efficiency to green management. Model: The model is developed in this study can be used for industries as guidelines for implementing green management issue by considering Health, Safety and Environmental Management System. Case Study: The Pars Special Economic / Energy Zone Organization on behalf of Iran’s Petroleum Ministry and National Iranian Oil Company (NIOC) manages and develops the South and North oil and gas fields in the region. Methodology: This research according to objective is applied and based on implementing is descriptive and also prescription. We used technique MCDM (Multiple Criteria Decision-Making) for determining the priorities of the factors. Based on process approach the model consists of the following steps and components: first factors involved in green issues are determined. Based on them a framework is considered. Then with using MCDM (Multiple Criteria Decision-Making) algorithms (TOPSIS) the priority of basic variables are determined. The authors believe that the proposed model and results of this research can aid industries managers to implement green subjects according to Health, Safety and Environmental Management System in a more efficient and effective manner. Finding and conclusion: Basic factors involved in green issues and their weights can be the main finding. Model and relation between factors are the other finding of this research. The case is considered Petrochemical Company for promoting the system of ecological industry thinking.

Keywords: Fuzzy-AHP method , green management, health, safety and environmental management system, MCDM technique, TOPSIS

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24191 Comparison of Different Techniques to Estimate Surface Soil Moisture

Authors: S. Farid F. Mojtahedi, Ali Khosravi, Behnaz Naeimian, S. Adel A. Hosseini

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Land subsidence is a gradual settling or sudden sinking of the land surface from changes that take place underground. There are different causes of land subsidence; most notably, ground-water overdraft and severe weather conditions. Subsidence of the land surface due to ground water overdraft is caused by an increase in the intergranular pressure in unconsolidated aquifers, which results in a loss of buoyancy of solid particles in the zone dewatered by the falling water table and accordingly compaction of the aquifer. On the other hand, exploitation of underground water may result in significant changes in degree of saturation of soil layers above the water table, increasing the effective stress in these layers, and considerable soil settlements. This study focuses on estimation of soil moisture at surface using different methods. Specifically, different methods for the estimation of moisture content at the soil surface, as an important term to solve Richard’s equation and estimate soil moisture profile are presented, and their results are discussed through comparison with field measurements obtained from Yanco1 station in south-eastern Australia. Surface soil moisture is not easy to measure at the spatial scale of a catchment. Due to the heterogeneity of soil type, land use, and topography, surface soil moisture may change considerably in space and time.

Keywords: artificial neural network, empirical method, remote sensing, surface soil moisture, unsaturated soil

Procedia PDF Downloads 356
24190 Communicating Safety: A Digital Ethnography Investigating Social Media Use for Workplace Safety

Authors: Kelly Jaunzems

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Social media is a powerful instrument of communication, enabling the presentation of information in multiple forms and modes, amplifying the interactions between people, organisations, and stakeholders, and increasing the range of communication channels available. Younger generations are highly engaged with social media and more likely to use this channel than any other to seek information. Given this, it may appear extraordinary that occupational safety and health professionals have yet to seriously engage with social media for communicating safety messages to younger audiences who, in many industries, might be statistically more likely to encounter more workplace harm or injury. Millennials, defined as those born between 1981-2000, have distinctive characteristics that also impact their interaction patterns rendering many traditional occupational safety and health communication channels sub-optimal or near obsolete. Used to immediate responses, 280-character communication, shares, likes, and visual imagery, millennials struggle to take seriously the low-tech, top-down communication channels such as safety noticeboards, toolbox meetings, and passive tick-box online inductions favoured by traditional OSH professionals. This paper draws upon well-established communication findings, which argue that it is important to know a target audience and reach them using their preferred communication pathways, particularly if the aim is to impact attitudes and behaviours. Health practitioners have adopted social media as a communication channel with great success, yet safety practitioners have failed to follow this lead. Using a digital ethnography approach, this paper examines seven organisations’ Facebook posts from two one-month periods one year apart, one in 2018 and one in 2019. Each of the years informs organisation-based case studies. Comparing, contrasting, and drawing upon these case studies, the paper discusses and evaluates the (non) use of social media communication of safety information in terms of user engagement, shareability, and overall appeal. The success of health practitioners’ use of social media provides a compelling template for the implementation of social media into organisations’ safety communication strategies. Highly visible content such as that found on social media allows an organization to become more responsive and engage in two-way conversations with their audience, creating more engaged and participatory conversations around safety. Further, using social media to address younger audiences with a range of tonal qualities (for example, the use of humour) can achieve cut through in a way that grim statistics fail to do. On the basis of 18 months of interviews, filed work, and data analysis, the paper concludes with recommendations for communicating safety information via social media. It proposes exploration of the social media communication formula that, when utilised by safety practitioners, may create an effective social media presence. It is anticipated that such social media use will increase engagement, expand the number of followers and reduce the likelihood and severity of safety-related incidents. The tools offered may provide a path for safety practitioners to reach a disengaged generation of workers to build a cohesive and inclusive conversation around ways to keep people safe at work.

Keywords: social media, workplace safety, communication strategies, young workers

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24189 Dietary Factors Contributing to Osteoporosis among Postmenopausal Women in Riyadh Armed Forces Hospital

Authors: Rabab Makki

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Bone mineral density and bone metabolism are affected by various factors such as genetic, endocrine, mechanical and nutritional. Our understanding of nutritional influences on bone health is limited because most studies have focused on calcium. This study investigated the dietary factors which are likely t contribute to Osteoporosis in Saudi post-menopausal women, and correlated it with BMD. This is a case controlled study involved 36 postmenopausal Saudi females selected from the Orthopedics and osteoporosis outpatient clinics, and 25 postmenopausal Saudi females as controls from the primary clinic of Military Hospital in Riyadh. The women were diagnosed as osteoporotic based on the BMD measurement at any site (left femur neck, right femur neck, left total hip or right total hip or spine). Both the controls and the Osteoporotics were over 50 years of age and BMI between 31-34 kg/m2 had 2nd degree obesity, and were not free from other problems such as diabetes, hypertension, etc. Subjects (osteoporotics and controls) were interviewed to called data on demographic characterstics, medical history, dietary intake anthropometry (height and weight) bone mineral density. Blood samples were collected from subjects (Osteoporotics and controls). Analysis of serum calcium, vitamin D, phosphate were done at the main laboratory at Military Hospital Riyadh, by the laboratory technician while BMD was determined at the department of Nuclear Medicine by an expert technician and results were interpreted by radiologist.Data on frequency of consumption of animal food (meat, eggs, poultry and fish) and diary foods (milk, yogurt, cheese) of osteoporotic was less than control. In spite of the low intake there was no association with BMD.In general, the vegetables and fruits were consumed less by the osteoporotics than control. The only fruit which had shown a significant positive correlation is banana with right and left hip BMD total probably due to high potassium and minerals content which likely to prevent bone resorption. Mataziz vegetables combination of wheat showed a significant positive correlation with the same site (total right and left hip). Both osteoporotics abd controls were consuming table sugar. (But the sweet intake showed a significant negative correlation with left neck femur BMD, suggesting sucrose increase urinary calcium loss. Both osteoporotic and controls were consuming Arabic coffee. A negative significant correlation between intake of Arabic coffee and BMD of right neck femur of osteoporosis patient was observed. It could be suggested that increased intake of fruits and vegetables, might promote bone density while high intake of coffee and sugars might affect bone density, no significant correlation was observed between BMD at any site and diary product. We can say the major risk factors are inadequate nutrition. Further studies are needed among Saudi population to confirm these results.

Keywords: osteoporosi, Saudia Arabia, Riyadh Armed Forces, postmenopausal women

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24188 Knowledge-Driven Decision Support System Based on Knowledge Warehouse and Data Mining by Improving Apriori Algorithm with Fuzzy Logic

Authors: Pejman Hosseinioun, Hasan Shakeri, Ghasem Ghorbanirostam

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In recent years, we have seen an increasing importance of research and study on knowledge source, decision support systems, data mining and procedure of knowledge discovery in data bases and it is considered that each of these aspects affects the others. In this article, we have merged information source and knowledge source to suggest a knowledge based system within limits of management based on storing and restoring of knowledge to manage information and improve decision making and resources. In this article, we have used method of data mining and Apriori algorithm in procedure of knowledge discovery one of the problems of Apriori algorithm is that, a user should specify the minimum threshold for supporting the regularity. Imagine that a user wants to apply Apriori algorithm for a database with millions of transactions. Definitely, the user does not have necessary knowledge of all existing transactions in that database, and therefore cannot specify a suitable threshold. Our purpose in this article is to improve Apriori algorithm. To achieve our goal, we tried using fuzzy logic to put data in different clusters before applying the Apriori algorithm for existing data in the database and we also try to suggest the most suitable threshold to the user automatically.

Keywords: decision support system, data mining, knowledge discovery, data discovery, fuzzy logic

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24187 Landfill Leachate: A Promising Substrate for Microbial Fuel Cells

Authors: Jayesh M. Sonawane, Prakash C. Ghosh

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Landfill leachate emerges as a promising feedstock for microbial fuel cells (MFCs). In the present investigation, direct air-breathing cathode-based MFCs are fabricated to investigate the potential of landfill leachate. Three MFCs that have different cathode areas are fabricated and investigated for 17 days under open circuit conditions. The maximum open circuit voltage (OCV) is observed to be as high as 1.29 V. The maximum cathode area specific power density achieved in the reactor is 1513 mW m-2. Further studies are under progress to understand the origin of high OCV obtained from landfill leachate-based MFCs.

Keywords: microbial fuel cells, landfill leachate, air-breathing cathode, performance study

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24186 Knowledge Diffusion via Automated Organizational Cartography: Autocart

Authors: Mounir Kehal, Adel Al Araifi

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The post-globalisation epoch has placed businesses everywhere in new and different competitive situations where knowledgeable, effective and efficient behaviour has come to provide the competitive and comparative edge. Enterprises have turned to explicit- and even conceptualising on tacit- Knowledge Management to elaborate a systematic approach to develop and sustain the Intellectual Capital needed to succeed. To be able to do that, you have to be able to visualize your organization as consisting of nothing but knowledge and knowledge flows, whilst being presented in a graphical and visual framework, referred to as automated organizational cartography. Hence, creating the ability of further actively classifying existing organizational content evolving from and within data feeds, in an algorithmic manner, potentially giving insightful schemes and dynamics by which organizational know-how is visualised. It is discussed and elaborated on most recent and applicable definitions and classifications of knowledge management, representing a wide range of views from mechanistic (systematic, data driven) to a more socially (psychologically, cognitive/metadata driven) orientated. More elaborate continuum models, for knowledge acquisition and reasoning purposes, are being used for effectively representing the domain of information that an end user may contain in their decision making process for utilization of available organizational intellectual resources (i.e. Autocart). In this paper we present likewise an empirical research study conducted previously to try and explore knowledge diffusion in a specialist knowledge domain.

Keywords: knowledge management, knowledge maps, knowledge diffusion, organizational cartography

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24185 An Assesment of Unconventional Hydrocarbon Potential of the Silurian Dadaş Shales in Diyarbakır Basin, Türkiye

Authors: Ceren Sevimli, Sedat İnan

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The Silurian Dadaş Formation within the Diyarbakir Basin in SE Türkiye, like other Silurian shales in North Africa and Middle East, represents a significant prospect for conventional and unconventional hydrocarbon exploration. The Diyarbakır Basin remains relatively underexplored, presenting untapped potential that warrants further investigation. This study focuses on the thermal maturity and hydrocarbon generation histories of the Silurian Dadaş shales, utilizing basin modeling approach. The Dadaş shales are organic-rich and contain mainly Type II kerogen, especially the basal layer contains up to 10 wt. %TOC and thus it is named as “hot shale”. The research integrates geological, geochemical, and basin modeling data to elucidate the unconventional hydrocarbon potential of this formation, which is crucial given the global demand for energy and the need for new resources. The data obtained from previous studies were used to calibrate basin model that has been established by using PetroMod software (Schlumberger). The calibrated model results suggest that Dadaş shales are in oil generation window and that the major episode for thermal maturation and hydrocarbon generation took place prior rot Alpine orogeny (uplift and erosion) The modeling results elucidate the burial history, maturity history, and hydrocarbon production history of the Silurian-aged Dadaş shales, as well as its hydrocarbon content in the area.

Keywords: dadaş formation, diyarbakır basin, silurian hot shale, unconventional hydrocarbon

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24184 Mother as Troubles Teller: A Discourse Analytic Case Study of Mother-Adolescent Daughter Interaction

Authors: Domenica L. DelPrete

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Viewed as a type of rapport-talk, troubles telling is a common conversational practice among female friends who wish to establish connection, show empathy, or share a disconcerting experience. This study shows how troubles talk between a mother and her adolescent daughter has a different interactional outcome. Specifically, it reveals how discursive interaction with an adolescent daughter becomes increasingly volatile when the mother steps out of the role of nurturer and into the role of troubles teller. Naturally occurring interactions between a mother and her 15-year-old daughter were videotaped in their family home over a two-week period. The data were primarily analyzed from an interactional sociolinguistic perspective, using conversation analytic techniques for transcriptions and discursive analysis. The following questions guided this research: (1) How are troubles telling discursively accomplished in the everyday talk of a mother and her adolescent daughter? and (2) What topic prompts the mother to engage in troubles talk? The data show that the mother engages her daughter in troubles to talk on issues related to body image and physical appearance and does so by (1) repeated questioning, (2) not accepting the daughter’s response as adequate, and (3) proffering self-deprecation. Findings reveal that engaging an adolescent daughter in a conversational practice reserved for female friendship groups creates a negative connection and relational disharmony. Since 'telling one’s troubles' assumes an egalitarian relationship between individuals, mother’s trouble telling creates a peer-like interaction that the adolescent daughter repeatedly resists. This study also proposes a discursive consciousness raising, which hopes to enhance communication between mothers and daughters by revealing the signals that show an adolescent daughter’s unwillingness to participate in troubles talk. Being in tune to these cues may prompt mothers to hesitate before pursuing a topic that will not garner the positive interactional outcome they seek.

Keywords: discursive interaction, maternal roles, mother-daughter interaction, troubles telling

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24183 QoS-CBMG: A Model for e-Commerce Customer Behavior

Authors: Hoda Ghavamipoor, S. Alireza Hashemi Golpayegani

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An approach to model the customer interaction with e-commerce websites is presented. Considering the service quality level as a predictive feature, we offer an improved method based on the Customer Behavior Model Graph (CBMG), a state-transition graph model. To derive the Quality of Service sensitive-CBMG (QoS-CBMG) model, process-mining techniques is applied to pre-processed website server logs which are categorized as ‘buy’ or ‘visit’. Experimental results on an e-commerce website data confirmed that the proposed method outperforms CBMG based method.

Keywords: customer behavior model, electronic commerce, quality of service, customer behavior model graph, process mining

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24182 Modeling and Benchmarking the Thermal Energy Performance of Palm Oil Production Plant

Authors: Mathias B. Michael, Esther T. Akinlabi, Tien-Chien Jen

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Thermal energy consumption in palm oil production plant comprises mainly of steam, hot water and hot air. In most efficient plants, hot water and air are generated from the steam supply system. Research has shown that thermal energy utilize in palm oil production plants is about 70 percent of the total energy consumption of the plant. In order to manage the plants’ energy efficiently, the energy systems are modelled and optimized. This paper aimed to present the model of steam supply systems of a typical palm oil production plant in Ghana. The models include exergy and energy models of steam boiler, steam turbine and the palm oil mill. The paper further simulates the virtual plant model to obtain the thermal energy performance of the plant under study. The simulation results show that, under normal operating condition, the boiler energy performance is considerably below the expected level as a result of several factors including intermittent biomass fuel supply, significant moisture content of the biomass fuel and significant heat losses. The total thermal energy performance of the virtual plant is set as a baseline. The study finally recommends number of energy efficiency measures to improve the plant’s energy performance.

Keywords: palm biomass, steam supply, exergy and energy models, energy performance benchmark

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24181 The Factors Affecting Pupil Psychological Well-Being in Mainstream Schools: A Systematic Review

Authors: Chantelle Francis, Karen McKenzie, Charlotte Emmerson

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In the context of the rise in mental health difficulties amongst pupils, this review explores the factors that have been indicated as affecting psychological well-being in mainstream school contexts. Search terms relating to school-based psychological well-being were entered into five databases, and twenty-two studies were included in the review. The results suggested that pupil psychological well-being is affected by both direct and indirect factors. The former included a sense of belonging and inclusion, relationships with teachers, and academic attainment. The latter included family socioeconomic status, whole-school approaches, and individual differences factors, such as gender and Special Educational Needs. The implications for policymakers and practitioners are discussed.

Keywords: psychological wellbeing, mainstream schools, special educational needs, school-based wellbeing

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24180 EEG Analysis of Brain Dynamics in Children with Language Disorders

Authors: Hamed Alizadeh Dashagholi, Hossein Yousefi-Banaem, Mina Naeimi

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Current study established for EEG signal analysis in patients with language disorder. Language disorder can be defined as meaningful delay in the use or understanding of spoken or written language. The disorder can include the content or meaning of language, its form, or its use. Here we applied Z-score, power spectrum, and coherence methods to discriminate the language disorder data from healthy ones. Power spectrum of each channel in alpha, beta, gamma, delta, and theta frequency bands was measured. In addition, intra hemispheric Z-score obtained by scoring algorithm. Obtained results showed high Z-score and power spectrum in posterior regions. Therefore, we can conclude that peoples with language disorder have high brain activity in frontal region of brain in comparison with healthy peoples. Results showed that high coherence correlates with irregularities in the ERP and is often found during complex task, whereas low coherence is often found in pathological conditions. The results of the Z-score analysis of the brain dynamics showed higher Z-score peak frequency in delta, theta and beta sub bands of Language Disorder patients. In this analysis there were activity signs in both hemispheres and the left-dominant hemisphere was more active than the right.

Keywords: EEG, electroencephalography, coherence methods, language disorder, power spectrum, z-score

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24179 3D Model Completion Based on Similarity Search with Slim-Tree

Authors: Alexis Aldo Mendoza Villarroel, Ademir Clemente Villena Zevallos, Cristian Jose Lopez Del Alamo

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With the advancement of technology it is now possible to scan entire objects and obtain their digital representation by using point clouds or polygon meshes. However, some objects may be broken or have missing parts; thus, several methods focused on this problem have been proposed based on Geometric Deep Learning, such as GCNN, ACNN, PointNet, among others. In this article an approach from a different paradigm is proposed, using metric data structures to index global descriptors in the spectral domain and allow the recovery of a set of similar models in polynomial time; to later use the Iterative Close Point algorithm and recover the parts of the incomplete model using the geometry and topology of the model with less Hausdorff distance.

Keywords: 3D reconstruction method, point cloud completion, shape completion, similarity search

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24178 Low Overhead Dynamic Channel Selection with Cluster-Based Spatial-Temporal Station Reporting in Wireless Networks

Authors: Zeyad Abdelmageid, Xianbin Wang

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Choosing the operational channel for a WLAN access point (AP) in WLAN networks has been a static channel assignment process initiated by the user during the deployment process of the AP, which fails to cope with the dynamic conditions of the assigned channel at the station side afterward. However, the dramatically growing number of Wi-Fi APs and stations operating in the unlicensed band has led to dynamic, distributed, and often severe interference. This highlights the urgent need for the AP to dynamically select the best overall channel of operation for the basic service set (BSS) by considering the distributed and changing channel conditions at all stations. Consequently, dynamic channel selection algorithms which consider feedback from the station side have been developed. Despite the significant performance improvement, existing channel selection algorithms suffer from very high feedback overhead. Feedback latency from the STAs, due to the high overhead, can cause the eventually selected channel to no longer be optimal for operation due to the dynamic sharing nature of the unlicensed band. This has inspired us to develop our own dynamic channel selection algorithm with reduced overhead through the proposed low-overhead, cluster-based station reporting mechanism. The main idea behind the cluster-based station reporting is the observation that STAs which are very close to each other tend to have very similar channel conditions. Instead of requesting each STA to report on every candidate channel while causing high overhead, the AP divides STAs into clusters then assigns each STA in each cluster one channel to report feedback on. With the proper design of the cluster based reporting, the AP does not lose any information about the channel conditions at the station side while reducing feedback overhead. The simulation results show equal performance and, at times, better performance with a fraction of the overhead. We believe that this algorithm has great potential in designing future dynamic channel selection algorithms with low overhead.

Keywords: channel assignment, Wi-Fi networks, clustering, DBSCAN, overhead

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24177 Tablet Computer Based Cognitive Rehabilitation Program, Injini, for Children with Cognitive Impairment

Authors: Eun Jae Ko, In Young Sung, Eui Soo Joeng

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Cognitive impairment is commonly encountered problem in children with various clinical diseases, including Down syndrome, autism spectrum disorder, brain injury, and others. Cognitive impairment limits participation in education and society, and this further hinders development in cognition. However, young children with cognitive impairment tend not to respond well to traditional cognitive treatments, therefore alternative treatment choices are need. As a cognitive training program, touch screen technology can easily be applied to very young children by involving visual and auditory support. Injini was developed as tablet computer based cognitive rehabilitation program for young children or individuals with severe cognitive impairment, which targeted on cognitive ages of 18 to 36 months. The aim of this study was to evaluate the efficacy of a tablet computer based cognitive rehabilitation program (Injini) for children with cognitive impairment. 38 children between cognitive ages of 18 to 36 months confirmed by cognitive evaluations were recruited and randomly assigned to the intervention group (n=20) and the control group (n=18). The intervention group received tablet computer based cognitive rehabilitation program (Injini) for 30 minutes per session, twice a week, over a period of 12 weeks, in addition to the traditional rehabilitation program. The control group received traditional rehabilitation program only. Mental score of Bayley Scales of Infant Development II (BSID II), Pediatric Evaluation of Disability Inventory (PEDI), Laboratory Temperament Assessment Battery (Lab-TAB), Early Childhood Behavior Questionnaire (ECBQ), and Goal Attainment Scale (GAS) were evaluated before and after 12 weeks of therapeutic intervention. When comparing the baseline characteristics, there was no significant difference between the two groups in the measurements of cognitive function. After 12 weeks of treatment, both group showed improvements in all measurements. However, in comparison of improvements after treatment, the intervention group showed more improvements in the mental score of BSID II, social function domain of PEDI, observation domain of Lab-TAB, and GAS, as compared to the control group. Application of the tablet computer based cognitive rehabilitation program (Injini) would be beneficial for improvement of cognitive function in young children with cognitive impairment.

Keywords: cognitive therapy, computer-assisted therapy, early intervention, tablets

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24176 The Gender Factor in Sustainable Development Goal Investing: Evidence from Applying Conjoint Analysis

Authors: Deniss Rozkov, Hendrik Idema

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This paper researches the gender-based differences among US-American institutional investors regarding their preferences for sustainable development goals (SDGs) when investing. After employing a structured questionnaire as well as applying a choice-based conjoint analysis, it is found that female investors place significantly more emphasis on SDGs, especially in the social and ecological domain, exhibiting significantly stronger “other-regarding” characteristics compared to their male counterparts. Further, the results of the survey show that females show significantly higher risk aversion than males by selecting moderately conservative and moderate risk approaches.

Keywords: sustainable development goals, investing, socially responsible investor, gender, conjoint analysis

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24175 Best Perform of Rights and Justice in the Brothel Based Female Sex Worker's Community

Authors: Md. Kabir Azaharul Islam

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Background: The purpose of this interventions was to describe the source and extent to increase health seeking rights and uptake of quality integrated maternal health, family planning and HIV information, clinical-non clinical services, and commodities amongst young people age 10-24 among brothel based Female Sex Worker’s in Bangladesh. Such Knowledge will equip with information to develop more appropriate and effective interventions that address the problem of HIV/AIDS and SRHR within the brothel based female sex worker’s community. Methods: Before start the intervention we observed situation in brothel and identify lack of knowledge about health issues, modern health facility, sexual harassment and violence & health rights. To enable access to the intervention obtained permission from a series of stakeholders within the brothel system. This intervention to the most vulnerable young key people during January 2014 to December, 2015, it designed an intervention that focuses on using peer education and sensitization meeting with self help group leader’s, pimbs, swardarni, house owner, local leaders, law enforcement agencies and target young key people (YKPs) through peer educator’s distributed BCC materials and conducted one to one and group session issues of HIV/AIDS, life skill education, maternal health, sexual reproductive health & rights, gender based violence, STD/STI and drug users in the community. Set up community based satellite clinic to provided clinical-non clinical services and commodities for SRH, FP and HIV including general health among brothel based FSWs. Peer educator frequently move and informed target beneficiaries’ age 10-24 YKPs about satellite clinic as well as time & date in the community. Results: This intervention highly promotes of brothel based FSW utilization of local facility based health providers private and public health facilities.2400 FSWs age 10-24 received information on SRHR, FP and HIV as well as existing health facilities, most of FSWs to received service from traditional healer before intervention. More than 1080 FSWs received clinical-non clinical services and commodities from satellite clinic including 12 ANC, 12 PNC and 25 MR. Most of young FSW age 10-24 are treated bonded girls under swardarni, house owner and pimbs, they have no rights to free movement as per need. As a result, they have no rights for free movement. However the brothel self help group (SHG) has become sensitized flowing this intervention. Conclusions: The majority of female sex workers well being regarding information on SRHR, FP and HIV as well as local health facilities now they feel free to go outside facilities for better health service. not only increased FSWs’ vulnerability to HIV infection and sexual reproductive health rights but also had huge implications for their human rights. This means that even when some clients impinged FSW’s rights (for example avoiding payment for services under the pretext of dissatisfaction), they might not be able to seek redress for fear of being ejected from the brothel. They raise voice national & local level different forum.

Keywords: ANC, HIV, PNC, SRHR

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24174 Motivation and Multiglossia: Exploring the Diversity of Interests, Attitudes, and Engagement of Arabic Learners

Authors: Anna-Maria Ramezanzadeh

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Demand for Arabic language is growing worldwide, driven by increased interest in the multifarious purposes the language serves, both for the population of heritage learners and those studying Arabic as a foreign language. The diglossic, or indeed multiglossic nature of the language as used in Arabic speaking communities however, is seldom represented in the content of classroom courses. This disjoint between the nature of provision and students’ expectations can severely impact their engagement with course material, and their motivation to either commence or continue learning the language. The nature of motivation and its relationship to multiglossia is sparsely explored in current literature on Arabic. The theoretical framework here proposed aims to address this gap by presenting a model and instruments for the measurement of Arabic learners’ motivation in relation to the multiple strands of the language. It adopts and develops the Second Language Motivation Self-System model (L2MSS), originally proposed by Zoltan Dörnyei, which measures motivation as the desire to reduce the discrepancy between leaners’ current and future self-concepts in terms of the second language (L2). The tripartite structure incorporates measures of the Current L2 Self, Future L2 Self (consisting of an Ideal L2 Self, and an Ought-To Self), and the L2 Learning Experience. The strength of the self-concepts is measured across three different domains of Arabic: Classical, Modern Standard and Colloquial. The focus on learners’ self-concepts allows for an exploration of the effect of multiple factors on motivation towards Arabic, including religion. The relationship between Islam and Arabic is often given as a prominent reason behind some students’ desire to learn the language. Exactly how and why this factor features in learners’ L2 self-concepts has not yet been explored. Specifically designed surveys and interview protocols are proposed to facilitate the exploration of these constructs. The L2 Learning Experience component of the model is operationalized as learners’ task-based engagement. Engagement is conceptualised as multi-dimensional and malleable. In this model, situation-specific measures of cognitive, behavioural, and affective components of engagement are collected via specially designed repeated post-task self-report surveys on Personal Digital Assistant over multiple Arabic lessons. Tasks are categorised according to language learning skill. Given the domain-specific uses of the different varieties of Arabic, the relationship between learners’ engagement with different types of tasks and their overall motivational profiles will be examined to determine the extent of the interaction between the two constructs. A framework for this data analysis is proposed and hypotheses discussed. The unique combination of situation-specific measures of engagement and a person-oriented approach to measuring motivation allows for a macro- and micro-analysis of the interaction between learners and the Arabic learning process. By combining cross-sectional and longitudinal elements with a mixed-methods design, the model proposed offers the potential for capturing a comprehensive and detailed picture of the motivation and engagement of Arabic learners. The application of this framework offers a number of numerous potential pedagogical and research implications which will also be discussed.

Keywords: Arabic, diglossia, engagement, motivation, multiglossia, sociolinguistics

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24173 Damage-Based Seismic Design and Evaluation of Reinforced Concrete Bridges

Authors: Ping-Hsiung Wang, Kuo-Chun Chang

Abstract:

There has been a common trend worldwide in the seismic design and evaluation of bridges towards the performance-based method where the lateral displacement or the displacement ductility of bridge column is regarded as an important indicator for performance assessment. However, the seismic response of a bridge to an earthquake is a combined result of cyclic displacements and accumulated energy dissipation, causing damage to the bridge, and hence the lateral displacement (ductility) alone is insufficient to tell its actual seismic performance. This study aims to propose a damage-based seismic design and evaluation method for reinforced concrete bridges on the basis of the newly developed capacity-based inelastic displacement spectra. The capacity-based inelastic displacement spectra that comprise an inelastic displacement ratio spectrum and a corresponding damage state spectrum was constructed by using a series of nonlinear time history analyses and a versatile, smooth hysteresis model. The smooth model could take into account the effects of various design parameters of RC bridge columns and correlates the column’s strength deterioration with the Park and Ang’s damage index. It was proved that the damage index not only can be used to accurately predict the onset of strength deterioration, but also can be a good indicator for assessing the actual visible damage condition of column regardless of its loading history (i.e., similar damage index corresponds to similar actual damage condition for the same designed columns subjected to very different cyclic loading protocols as well as earthquake loading), providing a better insight into the seismic performance of bridges. Besides, the computed spectra show that the inelastic displacement ratio for far-field ground motions approximately conforms to the equal displacement rule when structural period is larger than around 0.8 s, but that for near-fault ground motions departs from the rule in the whole considered spectral regions. Furthermore, the near-fault ground motions would lead to significantly greater inelastic displacement ratio and damage index than far-field ground motions and most of the practical design scenarios cannot survive the considered near-fault ground motion when the strength reduction factor of bridge is not less than 5.0. Finally, the spectrum formula is presented as a function of structural period, strength reduction factor, and various column design parameters for far-field and near-fault ground motions by means of the regression analysis of the computed spectra. And based on the developed spectrum formula, a design example of a bridge is presented to illustrate the proposed damage-based seismic design and evaluation method where the damage state of the bridge is used as the performance objective.

Keywords: damage index, far-field, near-fault, reinforced concrete bridge, seismic design and evaluation

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24172 A Type-2 Fuzzy Model for Link Prediction in Social Network

Authors: Mansoureh Naderipour, Susan Bastani, Mohammad Fazel Zarandi

Abstract:

Predicting links that may occur in the future and missing links in social networks is an attractive problem in social network analysis. Granular computing can help us to model the relationships between human-based system and social sciences in this field. In this paper, we present a model based on granular computing approach and Type-2 fuzzy logic to predict links regarding nodes’ activity and the relationship between two nodes. Our model is tested on collaboration networks. It is found that the accuracy of prediction is significantly higher than the Type-1 fuzzy and crisp approach.

Keywords: social network, link prediction, granular computing, type-2 fuzzy sets

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24171 Commodity Factory or Food Farms an Irrational Dilemma: Reflections on the Brazilian Scenario

Authors: Monica Dantas

Abstract:

At what socio-economic costs can the food industry offer products at low prices? This research seeks to understand and to explore how we attribute competence and meaning, what enables the outcomes of agriculture and what institutions provides validation regarding food production. This study objective is to explain and interpret conditions of the present state of agriculture in Brazil centring on two distinct segments, agribusiness and family farming, as the Brazilian, rapidly changing political environment unfolds. The approach is grounded in multidisciplinary literature drawing from the politics of development, the sociology of food, the sustainability framework and the conceptual differences between agribusiness and family farming regarding the innate purpose of the two segments. In addition, a quantitative portion of the research includes secondary data analysis from statistical measurements, economic indicators, federal budget information, and census data to compare the two segments, conveying a general snapshot of the conditions investigated. The results raised questions about the perceived image of the success of agribusiness, against some contradicting economic checks and balances. Analyzing how public funds are invested in agriculture shed light on what can enable or undermine the development of food systems in Brazil. It also revealed how politics, ideology, and corporations might influence the Brazilian Federal. In the 2000-2018 observed timeline of annual federal spending on agriculture in Brazil, there is variation in the amount invested in family farming that seems to 'coincide' with the ideological direction of the federal government in power. It was also observed that significant changes in the institutional framework and financial support either promoted or purposely undermined family farming importance using public institutions to validate support for agribusiness.

Keywords: food politics, sustainability, family farming, food system, public budget

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24170 Design and Implementation of a Fan Coil Unit Controller Based on the Duty Ratio Fuzzy Method

Authors: Liang Zhao, Jili Zhang, Kai Li

Abstract:

A microcontroller-based fan coil unit (FCU) fuzzy controller is designed and implemented in this paper. The controller employs the concept of duty ratio on the electric valve control, which could make full use of the cooling and dehumidifying capacity of the FCU when the valve is off. The traditional control method and its limitations are analyzed. The hardware and software design processes are introduced in detail. The experimental results show that the proposed method is more energy efficient compared to the traditional controlling strategy. Furthermore, a more comfortable room condition could be achieved by the proposed method. The proposed low-cost FCU fuzzy controller deserves to be widely used in engineering applications.

Keywords: fan coil unit, duty ratio, fuzzy controller, experiment

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24169 Effect of Nano/Micro Alumina Matrix on Alumina-Cubic Boron Nitride Composites Consolidated by Spark Plasma Sintering

Authors: A. S. Hakeem, B. Ahmed, M. Ehsan, A. Ibrahim, H. M. Irshad, T. Laoui

Abstract:

Alumina (Al2O3) - cubic boron nitride (cBN) ceramic composites were sintered by spark plasma sintering (SPS) using α-Al2O3 particle sizes; 150 µm, 150 nm and cBN particle size of 42 µm. Alumina-cBN composites containing 10, 20 and 30wt% cBN with and without Ni coated were sintering at an elevated temperature of 1400°C at a constant uniaxial pressure of 50 MPa. The effect of matrix particle size, cBN and Ni content on mechanical properties and thermal properties, i.e., thermal conductivity, diffusivity, expansion, densification, phase transformation, microstructure, hardness and toughness of the Al2O3-cBN/(Ni) composites under specific sintering conditions were investigated. The highest relative densification of 150 nm-Al2O3 containing 30wt% cBN (Ni coated) composite was 99% at TSPS = 1400°C. In case of 150 µm- Al2O3 compositions, the phase transformation of cBN to hBN were observed, and the relative densification decreased. Thermal conductivity depicts maximum value in case of 150 nm- Al2O3-30wt% cBN-Ni composition. The Vickers hardness of this composition at TSPS = 1400°C also showed the highest value of 29 GPa.

Keywords: alumina composite, cubic boron nitride, mechanical properties, phase transformation, Spark plasma sintering

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24168 Revolutionizing Gaming Setup Design: Utilizing Generative and Iterative Methods to Prop and Environment Design, Transforming the Landscape of Game Development Through Automation and Innovation

Authors: Rashmi Malik, Videep Mishra

Abstract:

The practice of generative design has become a transformative approach for an efficient way of generating multiple iterations for any design project. The conventional way of modeling the game elements is very time-consuming and requires skilled artists to design. A 3D modeling tool like 3D S Max, Blender, etc., is used traditionally to create the game library, which will take its stipulated time to model. The study is focused on using the generative design tool to increase the efficiency in game development at the stage of prop and environment generation. This will involve procedural level and customized regulated or randomized assets generation. The paper will present the system design approach using generative tools like Grasshopper (visual scripting) and other scripting tools to automate the process of game library modeling. The script will enable the generation of multiple products from the single script, thus creating a system that lets designers /artists customize props and environments. The main goal is to measure the efficacy of the automated system generated to create a wide variety of game elements, further reducing the need for manual content creation and integrating it into the workflow of AAA and Indie Games.

Keywords: iterative game design, generative design, gaming asset automation, generative game design

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24167 Customer Preference in the Textile Market: Fabric-Based Analysis

Authors: Francisca Margarita Ocran

Abstract:

Underwear, and more particularly bras and panties, are defined as intimate clothing. Strictly speaking, they enhance the place of women in the public or private satchel. Therefore, women's lingerie is a complex garment with a high involvement profile, motivating consumers to buy it not only by its functional utility but also by the multisensory experience it provides them. Customer behavior models are generally based on customer data mining, and each model is designed to answer questions at a specific time. Predicting the customer experience is uncertain and difficult. Thus, knowledge of consumers' tastes in lingerie deserves to be treated as an experiential product, where the dimensions of the experience motivating consumers to buy a lingerie product and to remain faithful to it must be analyzed in detail by the manufacturers and retailers to engage and retain consumers, which is why this research aims to identify the variables that push consumers to choose their lingerie product, based on an in-depth analysis of the types of fabrics used to make lingerie. The data used in this study comes from online purchases. Machine learning approach with the use of Python programming language and Pycaret gives us a precision of 86.34%, 85.98%, and 84.55% for the three algorithms to use concerning the preference of a buyer in front of a range of lingerie. Gradient Boosting, random forest, and K Neighbors were used in this study; they are very promising and rich in the classification of preference in the textile industry.

Keywords: consumer behavior, data mining, lingerie, machine learning, preference

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24166 Biosurfactant: A Greener Approach for Enhanced Concrete Rheology and Strength

Authors: Olivia Anak Rayeg, Clotilda Binti Petrus, Arnel Reanturco Ascotia, Ang Chung Huap, Caroline Marajan, Rudy Tawie Joseph Sipi

Abstract:

Concrete is essential for global infrastructure, yet enhancing its rheology and strength in an environmentally sustainable manner remains a significant challenge. Conventional chemical admixtures often pose environmental and health risks. This study explores the use of a phospholipid biosurfactant, derived from Rhizopus oryzae, as an environmentally friendly admixture in concrete. Various concentrations of the biosurfactant were integrated into fresh concrete, partially replacing the water content. The inclusion of the biosurfactant markedly enhanced the workability of the concrete, as demonstrated by Vertical Slump, Slump Flow, and T50 tests. After a 28-day curing period, the concrete's mechanical properties were assessed through compressive strength and bonding tests. Results revealed that substituting up to 10% of the water with the biosurfactant not only improved workability but also significantly increased both compressive and flexural strength. These findings highlight the potential of phospholipid biosurfactant as a biodegradable and non-toxic alternative to traditional admixtures, enhancing both structural integrity and sustainability in concrete. This approach reduces environmental impact and production costs, marking a significant advancement in sustainable construction technology.

Keywords: concrete rheology, green admixture, fungal biosurfactant, phospholipids, rhizopus oryzae

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24165 Variations in the Angulation of the First Sacral Spinous Process Angle Associated with Sacrocaudal Fusion in Greyhounds

Authors: Sa'ad M. Ismail, Hung-Hsun Yen, Christina M. Murray, Helen M. S. Davies

Abstract:

In the dog, the median sacral crest is formed by the fusion of three sacral spinous processes. In greyhounds with standard sacrums, this fusion in the median sacral crest consists of the fusion of three sacral spinous processes while it consists of four in greyhounds with sacrocaudal fusion. In the present study, variations in the angulation of the first sacral spinous process in association with different types of sacrocaudal fusion in the greyhound were investigated. Sacrums were collected from 207 greyhounds (102 sacrums; type A (unfused) and 105 with different types of sacrocaudal fusion; types: B, C and D). Sacrums were cleaned by boiling and dried and then were placed on their ventral surface on a flat surface and photographed from the left side using a digital camera at a fixed distance. The first sacral spinous process angle (1st SPA) was defined as the angle formed between the cranial border of the cranial ridge of the first sacral spinous process and the line extending across the most dorsal surface points of the spinous processes of the S1, S2, and S3. Image-Pro Express Version 5.0 imaging software was used to draw and measure the angles. Two photographs were taken for each sacrum and two repeat measurements were also taken of each angle. The mean value of the 1st SPA in greyhounds with sacrocaudal fusion was less (98.99°, SD ± 11, n = 105) than those in greyhounds with standard sacrums (99.77°, SD ± 9.18, n = 102) but was not significantly different (P < 0.05). Among greyhounds with different types of sacrocaudal fusion the mean value of the 1st SPA was as follows: type B; 97.73°, SD ± 10.94, n = 39, type C: 101.42°, SD ± 10.51, n = 52, and type D: 94.22°, SD ± 11.30, n = 12. For all types of fusion these angles were significantly different from each other (P < 0.05). Comparing the mean value of the1st SPA in standard sacrums (Type A) with that for each type of fusion separately showed that the only significantly different angulation (P < 0.05) was between standard sacrums and sacrums with sacrocaudal fusion sacrum type D (only body fusion between the S1 and Ca1). Different types of sacrocaudal fusion were associated with variations in the angle of the first sacral spinous process. These variations may affect the alignment and biomechanics of the sacral area and the pattern of movement and/or the force produced by both hind limbs to the cranial parts of the body and may alter the loading of other parts of the body. We concluded that any variations in the sacrum anatomical features might change the function of the sacrum or surrounding anatomical structures during movement.

Keywords: angulation of first sacral spinous process, biomechanics, greyhound, locomotion, sacrocaudal fusion

Procedia PDF Downloads 301