Search results for: urban network

Authors: Babar Rasheed

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The organizations are in continuous effort to increase their yield and to retain their associates, employees. Technology is considered an integral part of attaining apposite work practices, work environment, and employee engagement. Unconsciously, these advanced practices like work from home, personalized intra-network are disturbing employee work-life balance which ultimately increases psychological pressure on employees. The smart work practice is to develop business models and organizational practices with enhanced employee engagement, minimum trouncing of organization resources with persistent revenue and positive addition in global societies. Need of smart work practices comes from increasing employee turnover rate, global economic recession, unnecessary job pressure, increasing contingent workforce and advancement in technologies. Current practices are not enough elastic to tackle global changing work environment and organizational competitions. Current practices are causing many reciprocal problems among employee and organization mechanically. There is conscious understanding among business sectors smart work practices that will deal with new century challenges with addressing the concerns of relevant issues. It is aimed in this paper to endorse customized and smart work practice tools along knowledge framework to manage the growing concerns of employee engagement, use of technology, orgaization concerns and challenges for the business. This includes a Smart Management Information System to address necessary concerns of employees and combine with a framework to extract the best possible ways to allocate companies resources and re-align only required efforts to adopt the best possible strategy for controlling potential risks.

Keywords: employees engagement, management information system, psychological pressure, current and future HR practices

Procedia PDF Downloads 180

Authors: Sammy Kibor, Filip Huyghe, Marc Kochzius, James Kairo

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Goldstripe Sardinella, Sardinella gibbosa, (Bleeker, 1849) is a commercially and ecologically important small pelagic fish common in the Western Indian Ocean region. The present study aimed to assess genetic diversity and population structure of the species in the Kenya-Tanzania transboundary area using mtDNA and msDNA markers. Some 630 bp sequence in the mitochondrial DNA (mtDNA) Cytochrome C Oxidase I (COI) and five polymorphic microsatellite DNA loci were analyzed. Fin clips of 309 individuals from eight locations within the transboundary area were collected between July and December 2018. The S. gibbosa individuals from the different locations were distinguishable from one another based on the mtDNA variation, as demonstrated with a neighbor-joining tree and minimum spanning network analysis. None of the identified 22 haplotypes were shared between Kenya and Tanzania. Gene diversity per locus was relatively high (0.271-0.751), highest Fis was 0.391. The structure analysis, discriminant analysis of Principal component (DAPC) and the pair-wise (FST = 0.136 P < 0.001) values after Bonferroni correction using five microsatellite loci provided clear inference on genetic differentiation and thus evidence of population structure of S. gibbosa along the Kenya-Tanzania coast. This study shows a high level of genetic diversity and the presence of population structure (Φst =0.078 P < 0.001) resulting to the existence of four populations giving a clear indication of minimum gene flow among the population. This information has application in the designing of marine protected areas, an important tool for marine conservation.

Keywords: marine connectivity, microsatellites, population genetics, transboundary

Procedia PDF Downloads 118

Authors: Ravneet Kaur, Joydeep Acharya, Sudhanshu Gaur

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Artificial Intelligence (AI) has the potential to transform manufacturing by improving shop floor processes such as production, maintenance and quality. However, industrial datasets are notoriously difficult to extract in a real-time, streaming fashion thus, negating potential AI benefits. The main example is some specialized industrial controllers that are operated by custom software which complicates the process of connecting them to an Information Technology (IT) based data acquisition network. Security concerns may also limit direct physical access to these controllers for data acquisition. To connect the Operational Technology (OT) data stored in these controllers to an AI application in a secure, reliable and available way, we propose a novel Industrial IoT (IIoT) solution in this paper. In this solution, we demonstrate how video cameras can be installed in a factory shop floor to continuously obtain images of the controller HMIs. We propose image pre-processing to segment the HMI into regions of streaming data and regions of fixed meta-data. We then evaluate the performance of multiple Optical Character Recognition (OCR) technologies such as Tesseract and Google vision to recognize the streaming data and test it for typical factory HMIs and realistic lighting conditions. Finally, we use the meta-data to match the OCR output with the temporal, domain-dependent context of the data to improve the accuracy of the output. Our IIoT solution enables reliable and efficient data extraction which will improve the performance of subsequent AI applications.

Keywords: human machine interface, industrial internet of things, internet of things, optical character recognition, video analytics

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Authors: Jamal Radaideh

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Al-Asfar Lake is located about 14 km east of Al-Ahsa and is one of the most important wetland lakes in the Al Ahsa/Eastern Province of Saudi Arabia. Al-Ahsa is may be the largest oasis in the world, having an area of 20,000 hectares, in addition, it is of the largest and oldest agricultural centers in the region. The surplus farm irrigation water beside additional water supplied by treated wastewater from Al-Hofuf sewage station is collected by a drainage network and discharged into Al-Asfar Lake. The lake has good wetlands, sand dunes as well as large expanses of open and shallow water. Salt tolerant vegetation is present in some of the shallow areas around the lake, and huge stands of Phragmites reeds occur around the lake. The lake presents an important habitat for wildlife and birds, something not expected to find in a large desert. Although high evaporation rates in the range of 3250 mm are common, the water remains in the evaporation lakes during all seasons of the year is used to supply cattle with drinking water and for aquifer recharge. Investigations showed that high concentrations of nitrogen (N), phosphorus (P), biological oxygen demand (BOD), chemical oxygen demand (COD) and salinity discharge to Al Asfar Lake from the D2 drain exist. It is expected that the majority of BOD, COD and N originates from wastewater discharge and leachate from surplus irrigation water which also contribute to the majority of P and salinity. The significant content of nutrients and biological oxygen demand reduces available oxygen in the water. The present project aimed to improve the water quality of the lake using constructed wetland trains which will be built around the lake. Phragmites reeds, which already occur around the lake, will be used.

Keywords: Al Asfar lake, constructed wetland, water quality, water treatment

Procedia PDF Downloads 436

Authors: Genevaive Melendres

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School administrators face the reality of teachers losing their engagement, or schools losing the teachers. This study is then conducted to identify a structural model that best predict work engagement of private secondary teachers in Davao City. Ninety-three teachers from four sectarian schools and 56 teachers from four non-sectarian schools were involved in the completion of four survey instruments namely Organizational Climate Questionnaire, Leader Behavior Descriptive Questionnaire, Organizational Commitment Scales, and Utrecht Work Engagement Scales. Data were analyzed using frequency distribution, mean, standardized deviation, t-test for independent sample, Pearson r, stepwise multiple regression analysis, and structural equation modeling. Results show that schools have high level of organizational climate dimensions; leaders oftentimes show work-oriented and people-oriented behavior; teachers have high normative commitment and they are very often engaged at their work. Teachers from non-sectarian schools have higher organizational commitment than those from sectarian schools. Organizational climate and leadership behavior are positively related to and predict work engagement whereas commitment did not show any relationship. This study underscores the relative effects of three variables on the work engagement of teachers. After testing network of relationships and evaluating several models, a best-fitting model was found between leadership behavior and work engagement. The noteworthy findings suggest that principals pay attention and consistently evaluate their behavior for this best predicts the work engagement of the teachers. The study provides value to administrators who take decisions and create conditions in which teachers derive fulfillment.

Keywords: leadership behavior, organizational climate, organizational commitment, private secondary school teachers, structural model on work engagement

Procedia PDF Downloads 252

Authors: Ethan James

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Over one billion people worldwide suffer from some level of vision loss or blindness as a result of progressive retinal diseases. Many patients, particularly in developing areas, are incorrectly diagnosed or undiagnosed whatsoever due to unconventional diagnostic tools and screening methods. Artificial intelligence (AI) based on deep learning (DL) convolutional neural networks (CNN) have recently gained a high interest in ophthalmology for its computer-imaging diagnosis, disease prognosis, and risk assessment. Optical coherence tomography (OCT) is a popular imaging technique used to capture high-resolution cross-sections of retinas. In ophthalmology, DL has been applied to fundus photographs, optical coherence tomography, and visual fields, achieving robust classification performance in the detection of various retinal diseases including macular degeneration, diabetic retinopathy, and retinitis pigmentosa. However, there is no complete diagnostic model to analyze these retinal images that provide a diagnostic accuracy above 90%. Thus, the purpose of this project was to develop an AI model that utilizes machine learning techniques to automatically diagnose specific retinal diseases from OCT scans. The algorithm consists of neural network architecture that was trained from a dataset of over 20,000 real-world OCT images to train the robust model to utilize residual neural networks with cyclic pooling. This DL model can ultimately aid ophthalmologists in diagnosing patients with these retinal diseases more quickly and more accurately, therefore facilitating earlier treatment, which results in improved post-treatment outcomes.

Keywords: artificial intelligence, deep learning, imaging, medical devices, ophthalmic devices, ophthalmology, retina

Procedia PDF Downloads 177

Authors: Nur-E-Jannat Tinu

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Water is absolutely vital not only for the survival of human beings but also for plants, animals, and all other living organisms. Water bodies, such as lakes, rivers, ponds, and estuaries, are the source of water supply in domestic, industrial, agriculture, and aquaculture purposes. The Buriganga River flows through the south and west of Dhaka city. The water quality of this river has become a matter of concern due to anthropogenic intervention of vital pollutants such as industrial effluents, urban sewage, and solid wastes in this area. Buriganga River is at risk to contamination from untreated municipal wastes, industrial discharges, runoff from organic and inorganic fertilizers, pesticides, insecticides, and oil emission around the river. The residential and commercial establishments along the river discharge wastewater either directly into the river or through drains and canals into the river. However, several regulatory measures and policies have been enforced by the Government to protect the river Buriganga from pollution, in most cases to no affect. Water quality assessment reveals that the water is also not appropriate for irrigation purposes. The physical parameters (pH, TDS, EC, Temperature, DO, COD, BOD) indicated that the water is too poor to be useable for agricultural, drinking, or other purposes. Chemical concentrations showed significant seasonal variations with high-level concentrations during the monsoon season, presumably due to extreme seasonal surface runoff. A comparative study of Electrical Conductivity (EC) and Total Dissolved Solids (TDS) indicated a considerable increase over the last five years A change in trend was observed from 2020 June-July, probably due to monsoon and post-monsoon. EC values decreased from 775 to 665 mmho/cm during this period. DO increased significantly from the mid-post-monsoon months to the early monsoon period. The pH value of river water is strongly alkaline, ranging between 6.5 and 7.79. This indicates that ecological organic compounds cause the water to become alkaline after the monsoon and monsoon seasons. As the water pollution level is very high, an effective remediation and pollution control plan should be considered.

Keywords: precipitation, spatial distribution, effluent, remediation

Procedia PDF Downloads 139

Authors: Bicky Agarwal, Ambika Behl, Rajiv Kumar, Ashish Dhamaniya

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India ranks second for having the largest road network in the world after the United States (U.S.). According to the National Asphalt Pavement Association (NAPA), the U.S. produced about 94.6 million tons of Reclaimed Asphalt Pavement (RAP) in 2021. Despite the benefits of RAP usage, it is not widely adopted in many countries, including India. Rising asphalt binder costs and environmental concerns have spurred interest in using RAP material in asphalt mixtures. However, increasing RAP content may have adverse effects on certain characteristics of asphalt mixtures, such as cracking resistance. Cracking is a common pavement issue that affects the lifespan and durability of hot-mix asphalt pavements. Assessing cracking resistance is crucial in pavement design. Various laboratory tests and performance indicators are utilized to evaluate cracking resistance. This study aims to use the Texas Overlay Tester (TOT) to assess the impact of reclaimed asphalt pavement (RAP) on the cracking resistance of Bituminous Concrete (BC-II) mixes. Following the Marshall Mix Design method, asphalt mixes with RAP contents of 0% (Control), 30%, 40%, 50%, and 60% were prepared and tested at their Optimum Binder Content (OBC). The ITS results showed that the control mix had an ITS value of 1.2 MPa, with slight decreases observed in mixes containing up to 60% RAP, although these changes were not statistically significant (p=0.538>0.05). The TSR tests indicated that all mixes exceeded the minimum requirement of 80%. The Texas Overlay Test (TOT) was used to evaluate cracking performance and revealed that higher RAP contents had a negative impact on fatigue resistance. The 50% RAP mix exhibited the highest CFE, indicating that it has the best resistance to crack propagation despite having a lower number of cycles to failure. All mixes were categorized as falling into the Soft-crack-resistant quadrant, indicating their ability to resist crack propagation while being more susceptible to crack initiation.

Keywords: RAP, BC-II, HMA, TOT

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Authors: Tebikew Yeneabat, Tefera Belachew, Muluneh Haile

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Background: Exclusive breast-feeding (EBF) is the practice of feeding only breast milk (including expressed breast milk) during the first six months and no other liquids and solid foods except medications. The time to cessation of exclusive breast-feeding, however, is different in different countries depending on different factors. Studies showed the risk of diarrhea morbidity and mortality is higher among none exclusive breast-feeding infants, common during starting other foods. However, there is no study that evaluated the time to cessation of exclusive breast-feeding in the study area. The aim of this study was to show time to cessation of EBF and its predictors among mothers of index infants less than twelve months old. Methods: We conducted a community-based cross-sectional study from February 13 to March 3, 2012 using both quantitative and qualitative methods. This study included a total of 592 mothers of index infant using multi-stage sampling method. Data were collected by using interviewer administered structured questionnaire. Bivariate and multivariate Cox regression analyses were performed. Results: Cessation of exclusive breast-feeding occurred in 392 (69.63%) cases. Among these, 224 (57.1%) happened before six months, while 145 (37.0%) and 23 (5.9%) occurred at six months and after six months of age of the index infant respectively. The median time for infants to stay on exclusive breast-feeding was 6.36 months in rural and 5.13 months in urban, and this difference was statistically significant on a Log rank (Cox-mantel) test. Maternal and paternal occupation, place of residence, postnatal counseling on exclusive breast-feeding, mode of delivery, and birth order of the index infant were significant predictors of cessation of exclusive breast-feeding. Conclusion: Providing postnatal care counseling on EBF, routine follow-up and support of those mothers having infants stressing for working mothers can bring about implementation of national strategy on infant and young child feeding.

Keywords: exclusive breastfeeding, cessation, median duration, Ankesha Guagusa Woreda

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Authors: Gulnaz Erkomaishvili

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Introduction: The pandemic and the current economic crisis have created problems for entrepreneurship and, therefore for start-up entrepreneurs. The paper presents the challenges of start-up entrepreneurs in Georgia in the time of pandemic and the analysis of the state economic policy measures. Despite many problems, the study found that in 54.2% of start-ups surveyed under the pandemic, innovation opportunities were growing. It can be stated that the pandemic was a good opportunity to increase the innovative capacity of the enterprise. 52% of the surveyed start-up entrepreneurs managed to adapt to the current situation and increase the sale of their products/services through remote channels. As for the assessment of state support measures by start-up entrepreneurs, a large number of Georgian start-ups do not assess the measures implemented by the state positively. Methodology: The research process uses methods of analysis and synthesis, quantitative and qualitative, interview/survey, grouping, relative and average values, graphing, comparison, data analysis, and others. Main Findings: Studies have shown that for the start-up entrepreneurs, the main problem remains: inaccessible funding, workers' qualifications gap, inflation, taxes, regulation, political instability, inadequate provision of infrastructure, amount of taxes, and other factors. Conclusions: The state should take the following measures to support business start-ups: create an attractive environment for investment, availability of soft loans, creation of an insurance system, infrastructure development, increase the effectiveness of tax policy (simplicity of the tax system, clarity, optimal tax level ); promote export growth (develop strategy for opening up international markets, build up a broad marketing network, etc.).

Keywords: start-up entrepreneurs, startups, start-up entrepreneurs support programs, start-up entrepreneurs support economic policy

Procedia PDF Downloads 109

Authors: Sreetama Ghosh, Sundara Ramaprabhu

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Carbon dioxide gas has been a major cause for the worldwide increase in green house effect, which leads to climate change and global warming. So CO₂ capture & sequestration has become an effective way to reduce the concentration of CO₂ in the environment. One such way to capture CO₂ in porous materials is by adsorption process. A potential material in this aspect is porous hexagonal boron nitride or 'white graphene' which is a well-known two-dimensional layered material with very high thermal stability. It had been investigated that the sample with hierarchical pore structure and high specific surface area shows excellent performance in capturing carbon dioxide gas and thereby mitigating the problem of environmental pollution to the certain extent. Besides, the presence of sulfur as well as nitrogen in the sample synergistically helps in the increase in adsorption capacity. In this work, a cost effective single step synthesis of highly porous boron nitride nanosheets doped with sulfur had been demonstrated. Besides, the CO₂ adsorption-desorption studies were carried on using a pressure reduction technique. The studies show that the nanosheets exhibit excellent cyclic stability in storage performance. Thermodynamic studies suggest that the adsorption takes place mainly through physisorption. The studies show that the nanosheets exhibit excellent cyclic stability in storage performance. Further, the surface modification of the highly porous nano sheets carried out by incorporating ionic liquids had further enhanced the capturing capability of CO₂ gas in the nanocomposite, revealing that this particular material has the potential to be an excellent adsorbent of carbon dioxide gas.

Keywords: CO₂ capture, hexagonal boron nitride nanosheets, porous network, sulfur doping

Procedia PDF Downloads 237

Authors: Jean-Jacques Randrianarimanana, Nassim Sebaibi, Mohamed Boutouil

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In order to solve problems associated with stormwater runoff in urban areas and their effects on natural and artificial water bodies, the integration of new technical solutions to the rainwater drainage becomes even more essential. Permeable pavement systems are one of the most widely used techniques. This paper presents a laboratory analysis of stormwater runoff hydraulic and pollutant removal performance of permeable pavement system using pervious pavements based on seashell products. The laboratory prototype is a square column of 25 cm of side and consists of the surface in pervious concrete, a bedding of 3 cm in height, a geotextile and a subbase layer of 50 cm in height. A series of constant simulated rain events using semi-synthetic runoff which varied in intensity and duration were carried out. The initial vertical saturated hydraulic conductivity of the entire pervious pavement system was 0.25 cm/s (148 L/m²/min). The hydraulic functioning was influenced by both the inlet flow rate value and the test duration. The total water losses including evaporation ranged between 9% to 20% for all hydraulic experiments. The temporal and vertical variability of the pollutant removal efficiency (PRE) of the system were studied for total suspended solids (TSS). The results showed that the PRE along the vertical profile was influenced by the size of the suspended solids, and the pervious paver has the highest capacity to trap pollutant than the other porous layers of the permeable pavement system after the geotextile. The TSS removal efficiency was about 80% for the entire system. The first-flush effect of TSS was observed, but it appeared only at the beginning (2 to 6 min) of the experiments. It has been shown that the PPS can capture first-flush. The project in which this study is integrated aims to contribute to both the valorization of shellfish waste and the sustainable management of rainwater.

Keywords: hydraulic, pervious concrete, pollutant removal efficiency, seashell by-products, stormwater runoff

Procedia PDF Downloads 211

Authors: Olufunmilayo Folaranmi

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This research was carried out to examine the impact of socio-cultural factors on the management and utilization of solid waste in Ibadan Metropolis. A descriptive survey research design was adopted for the study while a systematic and stratified random sampling technique was used to select 300 respondents which were categorized into high, middle and low-density areas. Four hypothesis were tested using chi-square test on variables of unavailability of waste disposal facilities and waste management, negligence of contractors to liaise with community members, lack of adequate environmental education and waste management and utilization, low level of motivation of sanitation workers with solid wastes management, lack of community full participation with solid waste management and utilization. Results showed that significant effect of waste disposal facilities on solid waste management and utilization (X2 +16.6, P < .05). Also, there is a significant relationship between negligence of the contractors to liaise with community elites with improper disposal (X2 = 87.5, P < .05). The motivation of sanitation workers is significantly related to solid waste management (X2 = 70.4, P < .05). Adequate environmental education and awareness influenced solid waste management. There was also a significant relationship between lack of community participation with waste management disposal and improper waste disposal. Based on the findings from the study it was recommended that the quality of life in urban centers should be improved, social welfare of the populace enhanced and environment should be adequately attended to. Poverty alleviation programmes should be intensified and made to live beyond the life of a particular administration, micro-credit facilities should be available to community members to promote their welfare. Lastly, sustained environmental education programmes for citizens at all levels of education, formal and informal through the use of agencies like Ethical and Attitudinal Reorientation Commission (EARCOM) and the National Orientation Agency (NOA).

Keywords: management, social welfare, socio-cultural factors, solid waste

Procedia PDF Downloads 222

Authors: Dhanuja S. Patil, Sanjay B. Waykar

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Event detection is a standout amongst the most key parts for distinctive sorts of area applications of video data framework. Recently, it has picked up an extensive interest of experts and in scholastics from different zones. While detecting video event has been the subject of broad study efforts recently, impressively less existing methodology has considered multi-model data and issues related efficiency. Start of soccer matches different doubtful circumstances rise that can't be effectively judged by the referee committee. A framework that checks objectively image arrangements would prevent not right interpretations because of some errors, or high velocity of the events. Bayesian networks give a structure for dealing with this vulnerability using an essential graphical structure likewise the probability analytics. We propose an efficient structure for analysing and summarization of soccer videos utilizing object-based features. The proposed work utilizes the t-cherry junction tree, an exceptionally recent advancement in probabilistic graphical models, to create a compact representation and great approximation intractable model for client’s relationships in an interpersonal organization. There are various advantages in this approach firstly; the t-cherry gives best approximation by means of junction trees class. Secondly, to construct a t-cherry junction tree can be to a great extent parallelized; and at last inference can be performed utilizing distributed computation. Examination results demonstrates the effectiveness, adequacy, and the strength of the proposed work which is shown over a far reaching information set, comprising more soccer feature, caught at better places.

Keywords: summarization, detection, Bayesian network, t-cherry tree

Procedia PDF Downloads 314

Authors: Budhvin T. Withana, Sulochana Rupasinghe

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The educational system faces a significant concern with regards to Dyslexia and Dysgraphia, which are learning disabilities impacting reading and writing abilities. This is particularly challenging for children who speak the Sinhala language due to its complexity and uniqueness. Commonly used methods to detect the risk of Dyslexia and Dysgraphia rely on subjective assessments, leading to limited coverage and time-consuming processes. Consequently, delays in diagnoses and missed opportunities for early intervention can occur. To address this issue, the project developed a hybrid model that incorporates various deep learning techniques to detect the risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16, and YOLOv8 models were integrated to identify handwriting issues. The outputs of these models were then combined with other input data and fed into an MLP model. Hyperparameters of the MLP model were fine-tuned using Grid Search CV, enabling the identification of optimal values for the model. This approach proved to be highly effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention. The Resnet50 model exhibited a training accuracy of 0.9804 and a validation accuracy of 0.9653. The VGG16 model achieved a training accuracy of 0.9991 and a validation accuracy of 0.9891. The MLP model demonstrated impressive results with a training accuracy of 0.99918, a testing accuracy of 0.99223, and a loss of 0.01371. These outcomes showcase the high accuracy achieved by the proposed hybrid model in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, dyslexia, dysgraphia, deep learning, learning disabilities, data science

Procedia PDF Downloads 58

Authors: Zhongmin Wang, Wudong Fan, Hengshan Zhang, Yimin Zhou

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In data-driven prognostic methods, the prediction accuracy of the estimation for remaining useful life of bearings mainly depends on the performance of health indicators, which are usually fused some statistical features extracted from vibrating signals. However, the existing health indicators have the following two drawbacks: (1) The differnet ranges of the statistical features have the different contributions to construct the health indicators, the expert knowledge is required to extract the features. (2) When convolutional neural networks are utilized to tackle time-frequency features of signals, the time-series of signals are not considered. To overcome these drawbacks, in this study, the method combining convolutional neural network with gated recurrent unit is proposed to extract the time-frequency image features. The extracted features are utilized to construct health indicator and predict remaining useful life of bearings. First, original signals are converted into time-frequency images by using continuous wavelet transform so as to form the original feature sets. Second, with convolutional and pooling layers of convolutional neural networks, the most sensitive features of time-frequency images are selected from the original feature sets. Finally, these selected features are fed into the gated recurrent unit to construct the health indicator. The results state that the proposed method shows the enhance performance than the related studies which have used the same bearing dataset provided by PRONOSTIA.

Keywords: continuous wavelet transform, convolution neural net-work, gated recurrent unit, health indicators, remaining useful life

Procedia PDF Downloads 128

Authors: Cathal Ffrench, Ryan Barrett, Mike Quayle

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It is accepted in social psychology that categorization leads to ingroup favoritism, without further thought given to the processes that may co-occur or even precede categorization. These categorizations move away from the conceptualization of the self as a unique social being toward an increasingly collective identity. Subsequently, many individuals derive much of their self-evaluations from these collective identities. The seminal literature on this topic argues that it is primarily categorization that evokes instances of ingroup favoritism. Apropos to these theories, we argue that categorization acts to enhance and further intergroup processes rather than defining them. More accurately, we propose categorization aids initial ingroup contact and this first contact is predictive of subsequent favoritism on individual and collective levels. This analysis focuses on Virtual Interaction APPLication (VIAPPL) based studies, a software interface that builds on the flaws of the original minimal group studies. The VIAPPL allows the exchange of tokens in an intra and inter-group manner. This token exchange is how we classified the first contact. The study involves binary longitudinal analysis to better understand the subsequent exchanges of individuals based on who they first interacted with. Studies were selected on the criteria of evidence of explicit first interactions and two-group designs. Our findings paint a compelling picture in support of a motivated contact hypothesis, which suggests that an individual’s first motivated contact toward another has strong predictive capabilities for future behavior. This contact can lead to habit formation and specific favoritism towards individuals where contact has been established. This has important implications for understanding how group conflict occurs, and how intra-group individual bias can develop.

Keywords: categorization, group dynamics, initial contact, minimal social networks, momentary contact

Procedia PDF Downloads 143

Authors: Jin Hwan Cheong, Mina Hwang, Myung Hoon Han, Je Il Ryu, Young ha Oh, Seong Ho Koh, Wu Duck Won, Byung Jin Ha

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Leucine-rich repeat-containing G-protein coupled receptor 5 (LGR5) has been reported to play critical roles in the proliferation of various cancer cells. However, the roles of LGR5 in brain tumors and the specific intracellular signaling proteins directly associated with it remain unknown. Expression of LGR5 was first measured in normal brain tissue, meningioma, and pituitary adenoma of humans. To identify the downstream signaling pathways of LGR5, siRNA-mediated knockdown of LGR5 was performed in SH-SY5Y neuroblastoma cells followed by proteomics analysis with 2-dimensional polyacrylamide gel electrophoresis (2D-PAGE). In addition, the expression of LGR5-associated proteins was evaluated in LGR5-inꠓhibited neuroblastoma cells and in human normal brain, meningioma, and pituitary adenoma tissue. Proteomics analysis showed 12 protein spots were significantly different in expression level (more than two-fold change) and subsequently identified by peptide mass fingerprinting. A protein association network was constructed from the 12 identified proteins altered by LGR5 knockdown. Direct and indirect interactions were identified among the 12 proteins. HSP 90-beta was one of the proteins whose expression was altered by LGR5 knockdown. Likewise, we observed decreased expression of proteins in the hnRNP subfamily following LGR5 knockdown. In addition, we have for the first time identified significantly higher hnRNP family expression in meningioma and pituitary adenoma compared to normal brain tissue. Taken together, LGR5 and its downstream sigꠓnaling play critical roles in neuroblastoma and brain tumors such as meningioma and pituitary adenoma.

Keywords: LGR5, neuroblastoma, meningioma, pituitary adenoma, hnRNP

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Authors: Alicia Regodon Puyalto, Alfonso Garcia-Santos

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This article presents a method to analyze the use of indoor spaces based on data analytics obtained from inbuilt digital devices. The study uses the data generated by the in-place devices, such as smart locks, Wi-Fi routers, and electrical sensors, to gain additional insights on space occupancy, user behaviour, and comfort. Those devices, originally installed to facilitate remote operations, report data through the internet that the research uses to analyze information on human real-time use of spaces. Using an in-place Internet of Things (IoT) network enables a faster, more affordable, seamless, and scalable solution to analyze building interior spaces without incorporating external data collection systems such as sensors. The methodology is applied to a real case study of coliving, a residential building of 3000m², 7 floors, and 80 users in the centre of Madrid. The case study applies the method to classify IoT devices, assess, clean, and analyze collected data based on the analysis framework. The information is collected remotely, through the different platforms devices' platforms; the first step is to curate the data, understand what insights can be provided from each device according to the objectives of the study, this generates an analysis framework to be escalated for future building assessment even beyond the residential sector. The method will adjust the parameters to be analyzed tailored to the dataset available in the IoT of each building. The research demonstrates how human-centered data analytics can improve the future spatial design of indoor spaces.

Keywords: in-place devices, IoT, human-centred data-analytics, spatial design

Procedia PDF Downloads 189

Authors: Armend Kelmendi, Adnan Ahmeti

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The purpose of our study was to assess the impact of soccer in the overall wealth fare (education, health, and economic prosperity) of youth in Kosovo (age: 7-18). The research conducted measured a number of parameters (training methodologies, conditions, community leadership impact) in a sample consisting of 6 different football clubs’ academies across the country. Fifty (50) male and female football youngsters volunteered in this study. To generate more reliable results, the analysis was conducted with the help of a set of effective project management tools and techniques (Gantt chart, Logic Network, PERT chart, Work Breakdown Structure, and Budgeting Analysis). The interviewees were interviewed under a specific lens of categories (impact in education, health, and economic prosperity). A set of questions were asked i.e. what has football provided to you and the community you live in?; Did football increase your confidence and shaped your life for better?; What was the main reason you started training in football? The results generated explain how a single sport, namely that of football in Kosovo can make a huge social change, improving key social factors in a society. There was a considerable difference between the youth clubs as far as training conditions are concerned. The study found out that despite financial constraints, two out of six clubs managed to produce twice as more talented players that were introduced to professional primary league teams in Kosovo and Albania, including other soccer teams in the region, Europe, and Asia. The study indicates that better sports policy must be formulated and associated with important financial investments in soccer for it to be considered fruitful and beneficial for players of 18 plus years of age, namely professionals.

Keywords: youth, prosperity, conditions, investments, growth, free movement

Procedia PDF Downloads 235

Authors: Stephanie Hernández-Carreón, Judith Virginia Ríos-Arana

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Microplastics (MPs) are plastic particles smaller than 5 mm that has been detected in soil, air, organisms, and mostly water around the world. Most studies have focused on MPs detection in marine waters, and less so in freshwater, such is the case of Mexico, where studies about MPs in freshwaters are limited. One of the most important rivers in the country is The Rio Grande/Río Bravo, a natural border between Mexico and the United States. Its waters serve different purposes, such as fishing, habitat to endemic species, electricity generation, agriculture, and drinking water sources, among others. Despite its importance, the river’s waters have not been analyzed to determine the presence of MPs; therefore, the purpose of this research is to determine if the Rio Bravo/Rio Grande is polluted with microplastics. For doing so, three sites (Borderland, Casa de Adobe, and Guadalupe) along the El Paso-Juárez metroplex have been sampled: 30 L of water were filtered through a plankton net (64 µm) in each site and sediments-composed samples were collected. Water samples and sediments were 1) digested with a hydrogen peroxide solution (30%), 2) resuspended in a calcium chloride solution (1.5 g/cm3) to separate MPs, and 3) filtered through a 0.45 µm nitrocellulose membrane. Processed water samples were dyed with Nile Red (1 mg/ml ethanol) and analyzed by fluorescence microscopy. Two water samples have been analyzed until January 2023: Casa de Adobe and Borderland finding a concentration of 5.67 particles/L and 5.93 particles/L, respectively. Three types of particles were observed: fibers, fragments, and films, fibers being the most abundant. These data, as well as the data obtained from the rest of the samples, will be analyzed by an ANOVA (α=0.05). The concentrations and types of particles found in the Río Bravo correspond with other studies on rivers associated with urban environments and agricultural activities in China, where a range of 3.67—10.7 particles/L was reported in the Wei River. Even though we are in the early stages of the study, and three new sites will be sampled and analyzed in 2023 to provide more data about this issue in the river, this presents the first evidence of microplastic pollution in the Rio Grande.

Keywords: microplastics, fresh water, Rio Bravo, fluorescence microscopy

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Authors: Dona Ghosh, Zakir Husain

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In India, the increase in share of aged has generated many social and economic issues, of which health concerns is a major challenge that society must confront in coming years. Self-reported health (SRH) is a popular health measure in this regard but has been questioned in recent years due to its heavy dependence on the socioeconomic status. So, the validity of SRH, as a measure of health status during old age, is needed to be verified. This paper emphasizes on the self-reported health and related inconsistent responses among elderly in India. The objective of the study is bifurcated into two parts: firstly, to identify the socioeconomic determinants of subjective health status and its change over time; and secondly, to analyse the role of the socioeconomic components in providing inconsistent responses regarding the health status of elderly. Inconsistency in response can rise in two ways: positive response bias (if an individual has a health problem but reports his/her health as good) and negative response bias (if bad health is reported even if there is no health problem). However, in the present study, we focus only on the negative response bias of elderly individuals. To measure the inconsistencies in responses, self-reported health is compared with two types of physical health conditions – existence of chronicle ailment and physical immobility. Using NSS dataset of 60th and 71st rounds, the study found that subjective health has worsened over time in both rural and urban areas. Findings suggest that inconsistency in responses, related to chronic ailment, vary across social classes, living environments, geographical regions, age groups and education levels. On the contrary, variation in inconsistent responses regarding physical mobility is quite rare and difficult to explain by socioeconomic characteristics because most of the indicators are found to be insignificant in this regard. The findings indicate that in case of chronicle ailment, inconsistency between objective and subjective health status largely depends on socioeconomic conditions but the importance of such factors disappears for physical immobility.

Keywords: India, aging, self-reported health, inconsistent responses

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Authors: Migael van Zyl, Stefanie Visser, Awelani Phaswana

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The electricity landscape in South Africa is characterized by frequent occurrences of loadshedding, a measure implemented by Eskom to manage electricity generation shortages by curtailing demand. Loadshedding, classified into stages ranging from 1 to 8 based on severity, involves the systematic rotation of power cuts across municipalities according to predefined schedules. However, this practice introduces distortions in recorded electricity demand, posing challenges to accurate forecasting essential for budgeting, network planning, and generation scheduling. Addressing this challenge requires the development of a methodology to quantify the impact of loadshedding and integrate it back into metered electricity demand data. Fortunately, comprehensive records of loadshedding impacts are maintained in a database, enabling the alignment of Loadshedding effects with hourly demand data. This adjustment ensures that forecasts accurately reflect true demand patterns, independent of loadshedding's influence, thereby enhancing the reliability of electricity supply management in South Africa. This paper presents a methodology for determining the hourly impact of load scheduling and subsequently adjusting historical demand data to account for it. Furthermore, two forecasting models are developed: one utilizing the original dataset and the other using the adjusted data. A comparative analysis is conducted to evaluate forecast accuracy improvements resulting from the adjustment process. By implementing this methodology, stakeholders can make more informed decisions regarding electricity infrastructure investments, resource allocation, and operational planning, contributing to the overall stability and efficiency of South Africa's electricity supply system.

Keywords: electricity demand forecasting, load shedding, demand side management, data science

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Authors: Mequanint Birhan

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Modern urban environments present a dynamically growing field where, notwithstanding shared goals, several mutually conflicting interests frequently collide. However, it has a big impact on the city's socioeconomic standing, waiting lines and queues are common occurrences. This results in extremely long lines for both vehicles and people on incongruous routes, service coagulation, customer murmuring, unhappiness, complaints, and looking for other options sometimes illegally. The root cause of this is corruption, which leads to traffic jams, stopping, and packing vehicles beyond their safe carrying capacity, and violating the human rights and freedoms of passengers. This study focused on the optimizing time of passengers had to wait in public vehicle stations. This applied research employed both data gathering sources and mixed approaches, then 166 samples of key informants of transport station were taken by using the Slovin sampling formula. The length of time vehicles, including the drivers and auxiliary drivers ‘Weyala', had to wait was also studied. To maximize the service level at vehicle stations, a queuing model was subsequently devised ‘Menaharya’. Time, cost, and quality encompass performance, scope, and suitability for the intended purposes. The minimal response time for passengers and vehicles queuing to reach their final destination at the stations of the Tepi, Mizan, and Bonga towns was determined. A new bus station system was modeled and simulated by Arena simulation software in the chosen study area. 84% improvement on cost reduced by 56.25%, time 4hr to 1.5hr, quality, safety and designed load performance calculations employed. Stakeholders are asked to put the model into practice and monitor the results obtained.

Keywords: Arena 14 automatic rockwell, queue, transport services, vehicle stations

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Authors: Mohamed Zellagui, Heba Ahmed Hassan

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This paper proposes a new approach for the calculation of short-circuit parameters in the presence of Pulse Width Modulated based Series Compensator (PWMSC). PWMSC is a newly Flexible Alternating Current Transmission System (FACTS) device that can modulate the impedance of a transmission line through applying a variation to the duty cycle (D) of a train of pulses with fixed frequency. This results in an improvement of the system performance as it provides virtual compensation of distribution line impedance by injecting controllable apparent reactance in series with the distribution line. This controllable reactance can operate in both capacitive and inductive modes and this makes PWMSC highly effective in controlling the power flow and increasing system stability in the system. The purpose of this work is to study the impact of fault resistance (RF) which varies between 0 to 30 Ω on the fault current calculations in case of a ground fault and a fixed fault location. The case study is for a medium voltage (MV) Algerian distribution line which is compensated by PWMSC in the 30 kV Algerian distribution power network. The analysis is based on symmetrical components method which involves the calculations of symmetrical components of currents and voltages, without and with PWMSC in both cases of maximum and minimum duty cycle value for capacitive and inductive modes. The paper presents simulation results which are verified by the theoretical analysis.

Keywords: pulse width modulated series compensator (pwmsc), duty cycle, distribution line, short-circuit calculations, ground fault, symmetrical components method

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Authors: Ayesha Ali, Emilia Lindquist, Arif Jalal, Hannah Yusuf, Kayan Cheung, Rowan Eastabrook

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It is currently estimated that over a third of deaths in children under five in Tanzania are caused by acute respiratory infections (ARIs). However, despite being one of the leading causes of morbidity and mortality across the developing world, its risk factors are poorly understood. Therefore, a systematic review of the literature published between 2015 and 2020 was conducted, focusing on risk factors for ARI in Tanzanian children under the age of five. 2015 Demographic and Health Survey (DHS) for Tanzania was analysed to supplement these findings with national data. 2224 papers were retrieved from two databases and were analysed by three independent reviewers. Thirteen papers were eligible for inclusion, covering a wide range of risk factors among which comorbidities (n=6), malnutrition (n=5), lack of parental education (n=4), poor socio-economic status (n=3), and delay in seeking healthcare (n=3) were the most cited risk factors. The risk factors with the highest reported risk ratios/odds ratios were lack of parental education (RR=11.5-14.5), followed by enrolment in school (RR=4.4), delay in seeking healthcare (RR=3.8) and cooking indoors (aOR =1.8-RR=5.5). The DHS data provided local context to these risk factors. For instance, the number of children experiencing symptoms of ARI in both urban and rural areas ranged between 4.5-5% in the two weeks prior to the survey. However, 79% of symptomatic children in Zanzibar received antibiotics for treatment compared to just 34% of those in the Southern Highlands. As demonstrated by both the systematic review and the DHS analysis, risk factors for ARI are predominantly socially determined, with Tanzania’s poorer rural children possessing the highest risk for ARI and more adverse health outcomes. Therefore, the burden of ARIs in Tanzanian children may be alleviated through the provision of appropriate treatment and parental education in rural areas.

Keywords: acute respiratory infection, child, health education, morbidity, mortality, pneumonia, Tanzania

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Authors: A. F. Alves, L. Schmidt, J. Ferrao

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Portugal is one of the more vulnerable European countries to the impacts of climate change. These include: temperature increase; coastal sea level rise; desertification and drought in the countryside; and frequent and intense extreme weather events. Hence, adaptation strategies to climate change are of great importance. This is what was addressed by ClimAdaPT.Local. This policy-oriented project had the main goal of developing 26 Municipal Adaptation Strategies for Climate Change, through the identification of local specific present and future vulnerabilities, the training of municipal officials, and the engagement of local communities. It is intended to be replicated throughout the whole territory and to stimulate the creation of a national network of local adaptation in Portugal. Supported by methodologies and tools specifically developed for this project, our paper is based on the surveys, training and stakeholder engagement workshops implemented at municipal level. In an 'adaptation-as-learning' process, these tools functioned as a social-learning platform and an exercise in knowledge and policy co-production. The results allowed us to explore the nature of local vulnerabilities and the exposure of gaps in the context of reappraisal of both future climate change adaptation opportunities and possible dysfunctionalities in the governance arrangements of municipal Portugal. Development issues are highlighted when we address the sectors and social groups that are both more sensitive and more vulnerable to the impacts of climate change. We argue that a pluralistic dialogue and a common framing can be established between them, with great potential for transformational adaptation. Observed climate change, present-day climate variability and future expectations of change are great societal challenges which should be understood in the context of the sustainable development agenda.

Keywords: adaptation, ClimAdaPT.Local, climate change, Portugal, sustainable development

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Authors: Apra Sinha

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The inverted U-shaped Environmental Kuznets curve (EKC) demonstrates(pollution-income relationship)that initially the pollution and environmental degradation surpass the level of income per capita; however this trend reverses since at the higher income levels, economic growth initiates environmental upgrading. However, what effect does increased environmental degradation has on growth is the missing feedback link which has not been addressed in the EKC hypothesis. This paper examines the missing feedback link in EKC hypothesis in Indian context by examining the casual association between fossil fuel consumption, carbon dioxide emissions and economic growth for India. Fossil fuel consumption here has been taken as a proxy of driver of economic growth. The casual association between the aforementioned variables has been analyzed using five interventions namely 1) urban development for which urbanization has been taken proxy 2) industrial development for which industrial value added has been taken proxy 3) trade liberalization for which sum of exports and imports as a share of GDP has been taken as proxy 4)financial development for which a)domestic credit to private sector and b)net foreign assets has been taken as proxies. The choice of interventions for this study has been done keeping in view the economic liberalization perspective of India. The main aim of the paper is to investigate the missing feedback link for Environmental Kuznets Curve Hypothesis before and after incorporating the intervening variables. The period of study is from 1971 to 2011 as it covers pre and post liberalization era in India. All the data has been taken from World Bank country level indicators. The Johansen and Juselius cointegration testing methodology and Error Correction based Granger causality have been applied on all the variables. The results clearly show that out of five interventions, only in two interventions the missing feedback link is being addressed. This paper can put forward significant policy implications for environment protection and sustainable development.

Keywords: environmental Kuznets curve hypothesis, fossil fuel consumption, industrialization, trade liberalization, urbanization

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Authors: Bhat Geetalaxmi Jairam, D. V. Ashoka

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Wireless Sensor Networks are used in many applications to collect sensed data from different sources. Sensed data has to be delivered through sensors wireless interface using multi-hop communication towards the sink. The data collection in wireless sensor networks consumes energy. Energy consumption is the major constraints in WSN .Reducing the energy consumption while increasing the amount of generated data is a great challenge. In this paper, we have implemented two data gathering protocols with multiple mobile sinks/elements to collect data from sensor nodes. First, is Energy-Efficient Data Gathering with Tour Length-Constrained Mobile Elements in Wireless Sensor Networks (EEDG), in which mobile sinks uses vehicle routing protocol to collect data. Second is An Intelligent Agent-based Routing Structure for Mobile Sinks in WSNs (IAR), in which mobile sinks uses prim’s algorithm to collect data. Authors have implemented concepts which are common to both protocols like deployment of mobile sinks, generating visiting schedule, collecting data from the cluster member. Authors have compared the performance of both protocols by taking statistics based on performance parameters like Delay, Packet Drop, Packet Delivery Ratio, Energy Available, Control Overhead. Authors have concluded this paper by proving EEDG is more efficient than IAR protocol but with few limitations which include unaddressed issues likes Redundancy removal, Idle listening, Mobile Sink’s pause/wait state at the node. In future work, we plan to concentrate more on these limitations to avail a new energy efficient protocol which will help in improving the life time of the WSN.

Keywords: aggregation, consumption, data gathering, efficiency

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Authors: Ferdi Sönmez, Nihal Yorulmaz

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Decision making on the true planning of the public transportation systems to serve potential users is a must for metropolitan areas. To take attraction of travelers to projected modes of transport, adequately fair overall travel times should be provided. In this fashion, other benefits such as lower traffic congestion, road safety and lower noise and atmospheric pollution may be earned. The congestion which comes with increasing demand of public transportation is becoming a part of our lives and making residents’ life difficult. Hence, regulations should be done to reduce this congestion. To provide a constructive and balanced regulation in public transportation systems, right stations should be located in right places. In this study, it is aimed to design and implement a Decision Support System (DSS) Application to determine the optimal bus stop places for public transport in Istanbul which is one of the biggest and oldest cities in the world. Required information is gathered from IETT (Istanbul Electricity, Tram and Tunnel) Enterprises which manages all public transportation services in Istanbul Metropolitan Area. By using the most real-like values, cost assignments are made. The cost is calculated with the help of equations produced by bi-level optimization model. For this study, 300 buses, 300 drivers, 10 lines and 110 stops are used. The user cost of each station and the operator cost taken place in lines are calculated. Some components like cost, security and noise pollution are considered as significant factors affecting the solution of set covering problem which is mentioned for identifying and locating the minimum number of possible bus stops. Preliminary research and model development for this study refers to previously published article of the corresponding author. Model results are represented with the intent of decision support to the specialists on locating stops effectively.

Keywords: operator cost, bi-level optimization model, user cost, urban transportation

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