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Authors: Mala Mukherjee

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Background: India is urbanizing very fast and urbanisation in India is treated as one of the most crucial components of economic growth. Though the pace of urbanisation (31.6 per cent in 2011) is however slower and lower than the average for Asia but the absolute number of people residing in cities and towns has increased substantially. Rapid urbanization leads to urban poverty and it is well represented in slums. Currently India has four metropolises and 53 million plus cities. All of them have significant slum population but the standard of living and success of slum development programmes varies across regions. Objectives: Objectives of the paper are to show how urbanisation and slum development varies across space; to show spatial variation in the standard of living in Indian slums; to analyse how the implementation of slum development policies like JNNURM, Rajiv Awas Yojana varies across cities and bring different results in different regions and what are the factors responsible for such variation. Data Sources and Methodology: Census 2011 data on urban population and slum households and amenities have been used for analysing the regional variation of urbanisation in 53 million plus cities of India. Special focus has been put on Kolkata Metropolitan Area. Statistical techniques like z-score and PCA have been employed to work out Standard of Living Deprivation score for all the slums of 53 metropolises. ARC-GIS software is used for making maps. Standard of living has been measured in terms of access to basic amenities, infrastructure and assets like drinking water, sanitation, housing condition, bank account, and so on. Findings: 1. The first finding reveals that migration and urbanization is very high in Greater Mumbai, Delhi, Bangaluru, Chennai, Hyderabad and Kolkata; but slum population is high in Greater Mumbai (50% population live in slums), Meerut, Faridabad, Ludhiana, Nagpur, Kolkata etc. Though the rate of urbanization is high in southern and western states but the percentage of slum population is high in northern states (except Greater Mumbai). 2. Standard of Living also varies widely. Slums of Greater Mumbai and North Indian Cities score fairly high in the index indicating the fact that standard of living is high in those slums compare to the slums in eastern India (Dhanbad, Jamshedpur, Kolkata). Therefore, though Kolkata have relatively lesser percentage of slum population compare to north and south Indian cities but the standard of living in Kolkata’s slums is deplorable. 3. It is interesting to note that even within Kolkata Metropolitan Area slums located in the southern and eastern municipal towns like Rajpur-Sonarpur, Pujali, Diamond Harbour, Baduria and Dankuni have lower standard of living compare to the slums located in the Hooghly Industrial belt like Titagarh, Rishrah, Srerampore etc. Slums of the Hooghly Industrial Belt are older than the slums located in eastern and southern part of the urban agglomeration. 4. Therefore, urban development and emergence of slums should not be the only issue of urban governance but standard of living should be the main focus. Slums located in the main cities like Delhi, Mumbai, Kolkata get more attention from the urban planners and similarly, older slums in a city receives greater political attention compare to the slums of smaller cities and newly emerged slums of the peripheral parts.

Keywords: urbanisation, slum, spatial variation, India

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Authors: Mingxin Li, Liya Ni

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Autonomous parking is a valuable feature applicable to many robotics applications such as tour guide robots, UV sanitizing robots, food delivery robots, and warehouse robots. With auto-parking, the robot will be able to park at the charging zone and charge itself without human intervention. As compared to self-driving vehicles, auto-parking is more challenging for a small-scale mobile robot only equipped with a front camera due to the camera view limited by the robot’s height and the narrow Field of View (FOV) of the inexpensive camera. In this research, auto-parking of a small-scale mobile robot with a front camera only was achieved in a four-step process: Firstly, transfer learning was performed on the AlexNet, a popular pre-trained convolutional neural network (CNN). It was trained with 150 pictures of empty parking slots and 150 pictures of occupied parking slots from the view angle of a small-scale robot. The dataset of images was divided into a group of 70% images for training and the remaining 30% images for validation. An average success rate of 95% was achieved. Secondly, the image of detected empty parking space was processed with edge detection followed by the computation of parametric representations of the boundary lines using the Hough Transform algorithm. Thirdly, the positions of the entrance point and center of available parking space were predicted based on the robot kinematic model as the robot was driving closer to the parking space because the boundary lines disappeared partially or completely from its camera view due to the height and FOV limitations. The robot used its wheel speeds to compute the positions of the parking space with respect to its changing local frame as it moved along, based on its kinematic model. Lastly, the predicted entrance point of the parking space was used as the reference for the motion control of the robot until it was replaced by the actual center when it became visible again by the robot. The linear and angular velocities of the robot chassis center were computed based on the error between the current chassis center and the reference point. Then the left and right wheel speeds were obtained using inverse kinematics and sent to the motor driver. The above-mentioned four subtasks were all successfully accomplished, with the transformed learning, image processing, and target prediction performed in MATLAB, while the motion control and image capture conducted on a self-built small scale differential drive mobile robot. The small-scale robot employs a Raspberry Pi board, a Pi camera, an L298N dual H-bridge motor driver, a USB power module, a power bank, four wheels, and a chassis. Future research includes three areas: the integration of all four subsystems into one hardware/software platform with the upgrade to an Nvidia Jetson Nano board that provides superior performance for deep learning and image processing; more testing and validation on the identification of available parking space and its boundary lines; improvement of performance after the hardware/software integration is completed.

Keywords: autonomous parking, convolutional neural network, image processing, kinematics-based prediction, transfer learning

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Authors: Parashram Jakappa Patil

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India is the global leader in world cashew business and cashew-nut industry is one of the important food processing industries in world. However India is the largest producer, processor, exporter and importer eschew in the world. India is providing cashew to the rest of the world. India is meeting world demand of cashew. India has a tremendous potential of cashew production and export to other countries. Every year India earns more than 2000 cores rupees through cashew trade. Cashew industry is one of the important small scale industries in the country which is playing significant role in rural development. It is generating more than 400000 jobs at remote area and 95% cashew worker are women, it is giving income to poor cashew farmers, majority cashew processing units are small and cottage, it is helping to stop migration from young farmers for employment opportunities, it is motivation rural entrepreneurship development and it is also helping to environment protection etc. Hence India cashew business is very important agribusiness in India which has potential make inclusive development. World Bank and IMF recognized cashew-nut industry is one the important tool for poverty eradication at global level. It shows important of cashew business and its strong existence in India. In spite of such huge potential cashew processing industry is facing different problems such as lack of infrastructure ability, lack of supply of raw cashew, lack of availability of finance, collection of raw cashew, unavailability of warehouse, marketing of cashew kernels, lack of technical knowledge and especially processing technology and packaging of finished products. This industry has great prospects such as scope for more cashew cultivation and cashew production, employment generation, formation of cashew processing units, alcohols production from cashew apple, shield oil production, rural development, poverty elimination, development of social and economic backward class and environment protection etc. This industry has domestic as well as foreign market; India has tremendous potential in this regard. The cashew is a poor men’s crop but rich men’s food. The cashew is a source of income and livelihood for poor farmers. Cashew-nut industry may play very important role in the development of hilly region. The objectives of this paper are to identify problems of cashew processing and use of processing technology, problems of cashew kernel packaging, evolving of cashew processing technology over the year and its impact on final product and impact of good processing by adopting appropriate technology packaging on international trade of cashew-nut. The most important problem of cashew processing industry is that is processing and packaging. Bad processing reduce the quality of cashew kernel at large extent especially broken of cashew kernel which has very less price in market compare to whole cashew kernel and not eligible for export. On the other hand if there is no good packaging of cashew kernel will get moisture which destroy test of it. International trade of cashew-nut is depend of two things one is cashew processing and other is packaging. This study has strong relevance because cashew-nut industry is the labour oriented, where processing technology is not playing important role because 95% processing work is manual. Hence processing work was depending on physical performance of worker which makes presence of large workforce inevitable. There are many cashew processing units closed because they are not getting sufficient work force. However due to advancement in technology slowly this picture is changing and processing work get improve. Therefore it is interesting to explore all the aspects in context of cashew processing and packaging of cashew business.

Keywords: cashew, processing technology, packaging, international trade, change

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Authors: Rajkumar Ghosh, Ananya Mukhopadhyay

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This scientific paper presents a thorough investigation into the integration of roof-mounted photovoltaic (PV) array systems and home rooftop rainwater collection systems in a remote community in Himachal Pradesh, India, with the goal of optimum utilization of natural resources for attaining sustainable living conditions by 2030. The study looks into the technical feasibility, environmental benefits, and socioeconomic impacts of this integrated method, emphasizing its ability to handle energy and water concerns in remote rural regions. This comprehensive method not only provides a sustainable source of electricity but also ensures a steady supply of clean water, promoting resilience and improving the quality of life for the village's residents. This research highlights the potential of such integrated systems in supporting sustainable conditions in rural areas through a combination of technical feasibility studies, economic analysis, and community interaction. There would be 20690 villages and 1.48 million homes (23.79% annual growth rate) in Himachal Pradesh if all residential buildings in the state had roof-mounted photovoltaic arrays to capture solar energy for power generation. The energy produced is utilized to power homes, lessening dependency on traditional fossil fuels. The same residential buildings housed domestic rooftop rainwater collection systems. Rainwater runoff from rooftops is collected and stored in tanks for use in a number of residential purposes, such as drinking, cooking, and irrigation. The gathered rainfall enhances the region's limited groundwater resources, easing the strain on local wells and aquifers. Although Himachal Pradesh of India is a Power state, the PV arrays have reduced the reliance of village on grid power and diesel generators by providing a steady source of electricity. Rooftop rainwater gathering has not only increased residential water supply but it has also lessened the burden on local groundwater resources. This helps to replenish groundwater and offers a more sustainable water supply for the town. The neighbourhood has saved money by utilizing renewable energy and rainwater gathering. Furthermore, lower fossil fuel consumption reduces greenhouse gas emissions, which helps to mitigate the effects of climate change. The integrated strategy of installing grid connected rooftop photovoltaic arrays and home rooftop rainwater collecting systems in Himachal Pradesh rural community demonstrates a feasible model for sustainable development. According to “Swaran Jayanti Energy Policy of Himachal Pradesh”, Himachal Pradesh is planned 10 GW from rooftop mode from Solar Power. Government of India provides 40% subsidy on solar panel of 1-3 kw and subsidy of Rs 6,000 per kw per year to encourage domestic consumers of Himachal Pradesh. This effort solves energy and water concerns, improves economic well-being, and helps to conserve the environment. Such integrated systems can serve as a model for sustainable development in rural areas not only in Himachal Pradesh, but also in other parts of the world where resource scarcity is a major concern. Long-term performance and scalability of such integrated systems should be the focus of future study. Efforts should also be made to duplicate this approach in other rural areas and examine its socioeconomic and environmental implications over time.

Keywords: renewable energy, photovoltaic arrays, rainwater harvesting, sustainability, rural development, Himachal Pradesh, India

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Authors: Varinder Kaur Gambhir, Neema Gupta, Sonal Tickoo Chaudhuri

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Bengaluru, a rapidly growing metropolis in India, with a population of 12.5 million citizens, generates 5,757 metric tonnes of solid waste per day. Despite their invaluable contribution to waste management, society and the economy, waste pickers face significant stigma, suspicion and contempt and are left with a sense of shame about their work. In this context, BBC Media Action was funded by the H&M Foundation to develop a 3-year multi-phase social media campaign to shift perceptions of waste picking and informal waste pickers amongst the Bengaluru population. Research has been used to inform project strategy and adaptation, at all stages. Formative research to inform campaign strategy used mixed methods– 14 focused group discussions followed by 406 online surveys – to explore people’s knowledge of, and attitudes towards waste pickers, and identify potential barriers and motivators to changing perceptions. Use of qualitative techniques like metaphor maps (using bank of pictures rather than direct questions to understand mindsets) helped establish the invisibility of informal waste pickers, and the quantitative research enabled audience segmentation based on attitudes towards informal waste pickers. To pretest the campaign idea, eight I-GDs (individual interaction followed by group discussions) were conducted to allow interviewees to first freely express their feelings individually, before discussing in a group. Robert Plucthik’s ‘wheel of emotions’ was used to understand audience’s emotional response to the content. A robust monitoring and evaluation is being conducted (baseline and first phase of monitoring already completed) using a rotating longitudinal panel of 1,800 social media users (exposed and unexposed to the campaign), recruited face to face and representative of the social media universe of Bengaluru city. In addition, qualitative in-depth interviews are being conducted after each phase to better understand change drivers. The research methodology and ethical protocols for impact evaluation have been independently reviewed by an Institutional Review Board. Formative research revealed that while waste on the streets is visible and is of concern to the public, informal waste pickers are virtually ‘invisible’, for most people in Bengaluru Pretesting research revealed that the creative outputs evoked emotions like acceptance and gratitude towards waste-pickers, suggesting that the content had the potential to encourage attitudinal change. After the first phase of campaign, social media analytics show that #Invaluables content reached at least 2.6 million unique people (21% of the Bengaluru population) through Facebook and Instagram. Further, impact monitoring results show significant improvements in spontaneous awareness of different segments of informal waste pickers ( such as sorters at scrap shops or dry waste collection centres -from 10% at baseline to 16% amongst exposed and no change amongst unexposed), recognition that informal waste pickers help the environment (71% at baseline to 77% among exposed and no change among unexposed) and greater discussion about informal waste pickers among those exposed (60%) as against not exposed (49%). Using the insights from this research, the planned social media intervention is designed to increase the visibility of and appreciation for the work of waste pickers in Bengaluru, supporting a more inclusive society.

Keywords: awareness, discussion, discrimination, informal waste pickers, invisibility, social media campaign, waste management

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Authors: M. Reza Hashemi, Chris Small, Scott Hayward

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The Northeast Coast of the US faces damaging effects of coastal flooding and winds due to Atlantic tropical and extratropical storms each year. Historically, several large storm events have produced substantial levels of damage to the region; most notably of which were the Great Atlantic Hurricane of 1938, Hurricane Carol, Hurricane Bob, and recently Hurricane Sandy (2012). The objective of this study was to develop an integrated modeling system that could be used as a forecasting/hindcasting tool to evaluate and communicate the risk coastal communities face from these coastal storms. This modeling system utilizes the ADvanced CIRCulation (ADCIRC) model for storm surge predictions and the Simulating Waves Nearshore (SWAN) model for the wave environment. These models were coupled, passing information to each other and computing over the same unstructured domain, allowing for the most accurate representation of the physical storm processes. The coupled SWAN-ADCIRC model was validated and has been set up to perform real-time forecast simulations (as well as hindcast). Modeled storm parameters were then passed to a coastal risk assessment tool. This tool, which is generic and universally applicable, generates spatial structural damage estimate maps on an individual structure basis for an area of interest. The required inputs for the coastal risk model included a detailed information about the individual structures, inundation levels, and wave heights for the selected region. Additionally, calculation of wind damage to structures was incorporated. The integrated coastal risk assessment system was then tested and applied to Charlestown, a small vulnerable coastal town along the southern shore of Rhode Island. The modeling system was applied to Hurricane Sandy and a synthetic storm. In both storm cases, effect of natural dunes on coastal risk was investigated. The resulting damage maps for the area (Charlestown) clearly showed that the dune eroded scenarios affected more structures, and increased the estimated damage. The system was also tested in forecast mode for a large Nor’Easters: Stella (March 2017). The results showed a good performance of the coupled model in forecast mode when compared to observations. Finally, a nearshore model XBeach was then nested within this regional grid (ADCIRC-SWAN) to simulate nearshore sediment transport processes and coastal erosion. Hurricane Irene (2011) was used to validate XBeach, on the basis of a unique beach profile dataset at the region. XBeach showed a relatively good performance, being able to estimate eroded volumes along the beach transects with a mean error of 16%. The validated model was then used to analyze the effectiveness of several erosion mitigation methods that were recommended in a recent study of coastal erosion in New England: beach nourishment, coastal bank (engineered core), and submerged breakwater as well as artificial surfing reef. It was shown that beach nourishment and coastal banks perform better to mitigate shoreline retreat and coastal erosion.

Keywords: ADCIRC, coastal flooding, storm surge, coastal risk assessment, living shorelines

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Authors: Enoch Ocran

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Film Pertinence maintains consistency in storytelling by sustaining the natural flow of action while evoking a particular feeling or emotion from the viewers with selected motion pictures. This study presents a thorough investigation of "Film Pertinence" in videography that examines its influence in Africa and around the world. This research delves into the dynamic realm of visual storytelling through film, with a specific focus on the concept of Film Pertinence (FP). The study’s primary objectives are to conduct a comparative analysis of videography tools and techniques employed in both African and international contexts, examining how they contribute to the achievement of organizational goals and the enhancement of cultural awareness. The research methodology includes a comprehensive literature review, interviews with videographers from diverse backgrounds in Africa and the international arena, and the examination of pertinent case studies. The investigation aims to elucidate the multifaceted nature of videographic practices, with particular attention to equipment choices, visual storytelling techniques, cultural sensitivity, and adaptability. This study explores the impact of cultural differences on videography choices, aiming to promote understanding between African and foreign filmmakers and create more culturally sensitive films. It also explores the role of technology in advancing videography practices, resource allocation, and the influence of globalization on local filmmaking practices. The research also contributes to film studies by analyzing videography's impact on storytelling, guiding filmmakers to create more compelling narratives. The findings can inform film education, tailoring curricula to regional needs and opportunities. The study also encourages cross-cultural collaboration in the film industry by highlighting convergence and divergence in videography practices. At its core, this study seeks to explore the implications of film pertinence as a framework for videographic practice. It scrutinizes how cultural expression, education, and storytelling transcend geographical boundaries on a global scale. By analyzing the interplay between tools, techniques, and context, the research illuminates the ways in which videographers in Africa and worldwide apply film Pertinence principles to achieve cross-cultural communication and effectively capture the objectives of their clients. One notable focus of this paper is on the techniques employed by videographers in West Africa to emphasize storytelling and participant engagement, showcasing the relevance of FP in highlighting cultural awareness in visual storytelling. Additionally, the study highlights the prevalence of film pertinence in African agricultural documentaries produced for esteemed organizations such as the Roundtable on Sustainable Palm Oil (RSPO), Proforest, World Food Program, Fidelity Bank Ghana, Instituto BVRio, Aflatoun International, and the Solidaridad Network. These documentaries serve to promote prosperity, resilience, human rights, sustainable farming practices, community respect, and environmental preservation, underlining the vital role of film in conveying these critical messages. In summary, this research offers valuable insights into the evolving landscape of videography in different contexts, emphasizing the significance of film pertinence as a unifying principle in the pursuit of effective visual storytelling and cross-cultural communication.

Keywords: film pertinence, Africa, cultural awareness, videography tools

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Authors: Wafaa Hasan

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In May of 2022, Palestinian parents in Toronto, Canada, became aware that educators and staff in the Toronto District School Board were attempting to include the International Holocaust and Remembrance Definition of Antisemitism (IHRA) in The Child Abuse and Neglect Policy of the largest school board in Canada, The Toronto District School Board (TDSB). The idea was that if students were to express any form of antisemitism, as defined by the IHRA, then an investigation could follow with Child Protective Services (CPS). That is, the student’s parents could be reported to the state and investigated for custodial rights to their children. The TDSB has set apparent goals for “Decolonizing Pedagogy” (“TDSB Equity Leadership Competencies”), Culturally Responsive and Relevant Practices (CRRP) and inclusive education. These goals promote the centering of colonized, racialized and marginalized voices. CRRP cannot be effective without the application of anti-racist and settler colonial analyses. In order for CRRP to be effective, school boards need a comprehensive understanding of the ways in which the vilification of Palestinians operates through anti-indigenous and white supremacist systems and logic. Otherwise, their inclusion will always be in tension with the inclusion of settler colonial agendas and worldviews. Feminist maternalism frames racial mothering as degenerate (viewing the contributions of racialized students and their parents as products of primitive and violent cultures) and also indirectly inhibits the actualization of the tenets of CRRP and inclusive education through its extensions into the welfare state and public education. The contradiction between the tenets of CRRP and settler colonial systems of erasure and repression is resolved by the continuation of tactics to 1) force assimilation, 2) punish those who push back on that assimilation and 3) literally fragment familial and community structures of racialized students, educators and parents. This paper draws on interdisciplinary (history, philosophy, anthropology) critiques of white feminist “maternalism” from the 19th century onwards in North America and Europe (Jacobs, Weber), as well as “anti-racist education” theory (Dei), and more specifically,” culturally responsive learning,” (Muhammad) and “bandwidth” pedagogy theory (Verschelden) to make its claims. This research contributes to vibrant debates about anti-racist and decolonial pedagogies in public education systems globally. This paper also documents first-hand interviews and experiences of diasporic Palestinian mothers and motherhoods and situates their experiences within longstanding histories of white feminist maternalist (and eugenicist) politics. This informal qualitative data from "participatory conversations" (Swain) is situated within a set of formal interview data collected with Palestinian women in the West Bank (approved by the McMaster University Humanities Research Ethics Board) relating to white feminist maternalism in the peace and dialogue industry.

Keywords: decolonial feminism, maternal feminism, anti-racist pedagogies, settler colonial studies, motherhood studies, pedagogy theory, cultural theory

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Authors: Murat Arıbaş, Uğur Özcan

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Due to the increasing number of universities and academics, the fund of the universities for research activities and grants/supports given by government institutions have increased number and quality of academic research projects. Although every academic research project has a specific purpose and importance, limited resources (money, time, manpower etc.) require choosing the best ones from all (Amiri, 2010). It is a pretty hard process to compare and determine which project is better such that the projects serve different purposes. In addition, the evaluation process has become complicated since there are more than one evaluator and multiple criteria for the evaluation (Dodangeh, Mojahed and Yusuff, 2009). Mehrez and Sinuany-Stern (1983) determined project selection problem as a Multi Criteria Decision Making (MCDM) problem. If a decision problem involves multiple criteria and objectives, it is called as a Multi Attribute Decision Making problem (Ömürbek & Kınay, 2013). There are many MCDM methods in the literature for the solution of such problems. These methods are AHP (Analytic Hierarchy Process), ANP (Analytic Network Process), TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation), UTADIS (Utilities Additives Discriminantes), ELECTRE (Elimination et Choix Traduisant la Realite), MAUT (Multiattribute Utility Theory), GRA (Grey Relational Analysis) etc. Teach method has some advantages compared with others (Ömürbek, Blacksmith & Akalın, 2013). Hence, to decide which MCDM method will be used for solution of the problem, factors like the nature of the problem, types of choices, measurement scales, type of uncertainty, dependency among the attributes, expectations of decision maker, and quantity and quality of the data should be considered (Tavana & Hatami-Marbini, 2011). By this study, it is aimed to develop a systematic decision process for the grant support applications that are expected to be evaluated according to their scientific adequacy by multiple evaluators under certain criteria. In this context, project evaluation process applied by The Scientific and Technological Research Council of Turkey (TÜBİTAK) the leading institutions in our country, was investigated. Firstly in the study, criteria that will be used on the project evaluation were decided. The main criteria were selected among TÜBİTAK evaluation criteria. These criteria were originality of project, methodology, project management/team and research opportunities and extensive impact of project. Moreover, for each main criteria, 2-4 sub criteria were defined, hence it was decided to evaluate projects over 13 sub-criterion in total. Due to superiority of determination criteria weights AHP method and provided opportunity ranking great number of alternatives TOPSIS method, they are used together. AHP method, developed by Saaty (1977), is based on selection by pairwise comparisons. Because of its simple structure and being easy to understand, AHP is the very popular method in the literature for determining criteria weights in MCDM problems. Besides, the TOPSIS method developed by Hwang and Yoon (1981) as a MCDM technique is an alternative to ELECTRE method and it is used in many areas. In the method, distance from each decision point to ideal and to negative ideal solution point was calculated by using Euclidian Distance Approach. In the study, main criteria and sub-criteria were compared on their own merits by using questionnaires that were developed based on an importance scale by four relative groups of people (i.e. TUBITAK specialists, TUBITAK managers, academics and individuals from business world ) After these pairwise comparisons, weight of the each main criteria and sub-criteria were calculated by using AHP method. Then these calculated criteria’ weights used as an input in TOPSİS method, a sample consisting 200 projects were ranked on their own merits. This new system supported to opportunity to get views of the people that take part of project process including preparation, evaluation and implementation on the evaluation of academic research projects. Moreover, instead of using four main criteria in equal weight to evaluate projects, by using weighted 13 sub-criteria and decision point’s distance from the ideal solution, systematic decision making process was developed. By this evaluation process, new approach was created to determine importance of academic research projects.

Keywords: Academic projects, Ahp method, Research projects evaluation, Topsis method.

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Authors: Atish Bagchi, Siva Chandrasekaran

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Background: According to World Bank national accounts data, the estimated global manufacturing value-added output in 2020 was 13.74 trillion USD. These manufacturing processes are monitored, modelled, and controlled by advanced, real-time, computer-based systems, e.g., Industrial IoT, PLC, SCADA, etc. These systems measure and manipulate a set of physical variables, e.g., temperature, pressure, etc. Despite the use of IoT, SCADA etc., in manufacturing, studies suggest that unplanned downtime leads to economic losses of approximately 864 billion USD each year. Therefore, real-time, accurate detection, classification and prediction of machine behaviour are needed to minimise financial losses. Although vast literature exists on time-series data processing using machine learning, the challenges faced by the industries that lead to unplanned downtimes are: The current algorithms do not efficiently handle the high-volume streaming data from industrial IoTsensors and were tested on static and simulated datasets. While the existing algorithms can detect significant 'point' outliers, most do not handle contextual outliers (e.g., values within normal range but happening at an unexpected time of day) or subtle changes in machine behaviour. Machines are revamped periodically as part of planned maintenance programmes, which change the assumptions on which original AI models were created and trained. Aim: This research study aims to deliver a Graph Neural Network(GNN)based hybrid forecasting model that interfaces with the real-time machine control systemand can detect, predict machine behaviour and behavioural changes (anomalies) in real-time. This research will help manufacturing industries and utilities, e.g., water, electricity etc., reduce unplanned downtimes and consequential financial losses. Method: The data stored within a process control system, e.g., Industrial-IoT, Data Historian, is generally sampled during data acquisition from the sensor (source) and whenpersistingin the Data Historian to optimise storage and query performance. The sampling may inadvertently discard values that might contain subtle aspects of behavioural changes in machines. This research proposed a hybrid forecasting and classification model which combines the expressive and extrapolation capability of GNN enhanced with the estimates of entropy and spectral changes in the sampled data and additional temporal contexts to reconstruct the likely temporal trajectory of machine behavioural changes. The proposed real-time model belongs to the Deep Learning category of machine learning and interfaces with the sensors directly or through 'Process Data Historian', SCADA etc., to perform forecasting and classification tasks. Results: The model was interfaced with a Data Historianholding time-series data from 4flow sensors within a water treatment plantfor45 days. The recorded sampling interval for a sensor varied from 10 sec to 30 min. Approximately 65% of the available data was used for training the model, 20% for validation, and the rest for testing. The model identified the anomalies within the water treatment plant and predicted the plant's performance. These results were compared with the data reported by the plant SCADA-Historian system and the official data reported by the plant authorities. The model's accuracy was much higher (20%) than that reported by the SCADA-Historian system and matched the validated results declared by the plant auditors. Conclusions: The research demonstrates that a hybrid GNN based approach enhanced with entropy calculation and spectral information can effectively detect and predict a machine's behavioural changes. The model can interface with a plant's 'process control system' in real-time to perform forecasting and classification tasks to aid the asset management engineers to operate their machines more efficiently and reduce unplanned downtimes. A series of trialsare planned for this model in the future in other manufacturing industries.

Keywords: GNN, Entropy, anomaly detection, industrial time-series, AI, IoT, Industry 4.0, Machine Learning

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