Search results for: link data

Authors: Kyeong-Ri Ko, Seong Bong Bae, Jang Sik Choi, Sung Bum Pan

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A simple method for testing the posture imbalance of the human body is to check for differences in the bilateral shoulder and pelvic height of the target. In this paper, to check for spinal disorders the authors have studied ways to establish a motion capture system to obtain and express motions of 4-joints, and to acquire data based on this system. The 4 sensors are attached to the both shoulders and pelvis. To verify the established system, the normal and abnormal postures of the targets listening to a lecture were obtained using the established 4-joint based motion capture system. From the results, it was confirmed that the motions taken by the target was identical to the 3-dimensional simulation.

Keywords: inertial sensor, motion capture, motion data acquisition, posture imbalance

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Authors: Suchitra Chnadrashekhar

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Earlier looked as a support function in an organization information technology has now become a critical utility to manage their daily operations. Organizations are processing huge amount of data which was unimaginable few decades before. This has opened the opportunity for IT sector to help industries across domains to handle the data in the most intelligent manner. Presence of IT has been a leverage for the Oil & Gas industry to store, manage and process the data in most efficient way possible thus deriving the economic value in their day-to-day operations. Proper synchronization between Operational data system and Information Technology system is the need of the hour. Predictive analytics supports oil and gas companies by addressing the challenge of critical equipment performance, life cycle, integrity, security, and increase their utilization. Predictive analytics go beyond early warning by providing insights into the roots of problems. To reach their full potential, oil and gas companies need to take a holistic or systems approach towards asset optimization and thus have the functional information at all levels of the organization in order to make the right decisions. This paper discusses how the use of predictive analysis in oil and gas industry is redefining the dynamics of this sector. Also, the paper will be supported by real time data and evaluation of the data for a given oil production asset on an application tool, SAS. The reason for using SAS as an application for our analysis is that SAS provides an analytics-based framework to improve uptimes, performance and availability of crucial assets while reducing the amount of unscheduled maintenance, thus minimizing maintenance-related costs and operation disruptions. With state-of-the-art analytics and reporting, we can predict maintenance problems before they happen and determine root causes in order to update processes for future prevention.

Keywords: hydrocarbon, information technology, SAS, predictive analytics

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Authors: Shivani Jha, Klaus Baier, Rafiq Azzam, Ramakar Jha

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In India, generally people migrate from rural area to the urban area for better infra-structural facilities, high standard of living, good job opportunities and advanced transport/communication availability. In fact, unplanned urban development due to migration of people causes seriou damage to the land use, water pollution and available water resources. In the present work, an attempt has been made to use satellite data of different years for urban change detection of Chennai metropolitan city along with pattern analysis to generate future scenario of urban development using buffer zoning in GIS environment. In the analysis, SRTM (30m) elevation data and IRS-1C satellite data for the years 1990, 2000, and 2014, are used. The flow accumulation, aspect, flow direction and slope maps developed using SRTM 30 m data are very useful for finding suitable urban locations for industrial setup and urban settlements. Normalized difference vegetation index (NDVI) and Principal Component Analysis (PCA) have been used in ERDAS imagine software for change detection in land use of Chennai metropolitan city. It has been observed that the urban area has increased exponentially in Chennai metropolitan city with significant decrease in agriculture and barren lands. However, the water bodies located in the study regions are protected and being used as freshwater for drinking purposes. Using buffer zone analysis in GIS environment, it has been observed that the development has taken place in south west direction significantly and will do so in future.

Keywords: urban change, satellite data, the Chennai metropolis, change detection

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Authors: Alia Al Rayssi, Mahra Al Marar, Alyazia Alkhaili, Reem Al Dhaheri, Shayma Alkobaisi, Hoda Amer

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We present in this paper a web-based system called “HelpMeBreathe” for managing asthma. The proposed system provides analytical tools, which allow better understanding of environmental triggers of asthma, hence better support of data-driven decision making. The developed system provides warning messages to a specific asthma patient if the weather in his/her area might cause any difficulty in breathing or could trigger an asthma attack. HelpMeBreathe collects, stores, and analyzes individuals’ moving trajectories and health conditions as well as environmental data. It then processes and displays the patients’ data through an analytical tool that leads to an effective decision making by physicians and other decision makers.

Keywords: asthma, environmental triggers, map interface, web-based systems

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Authors: Ellen Nhedzi Gozo

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Unavailability of adequate hydro-meteorological data has always limited the analysis and understanding of hydrological behaviour of several dam catchments including Mazowe Dam in Zimbabwe. The problem of insufficient data for Mazowe Dam catchment analysis was solved by extracting catchment characteristics and aerial hydro-meteorological data from ASTER, LANDSAT, Shuttle Radar Topographic Mission SRTM remote sensing (RS) images using ILWIS, ArcGIS and ERDAS Imagine geographic information systems (GIS) software. Available observed hydrological as well as meteorological data complemented the use of the remotely sensed information. Ground truth land cover was mapped using a Garmin Etrex global positioning system (GPS) system. This information was then used to validate land cover classification detail that was obtained from remote sensing images. A bathymetry survey was conducted using a SONAR system connected to GPS. Hydrological modelling using the HBV model was then performed to simulate the hydrological process of the catchment in an effort to verify the reliability of the derived parameters. The model output shows a high Nash-Sutcliffe Coefficient that is close to 1 indicating that the parameters derived from remote sensing and GIS can be applied with confidence in the analysis of Mazowe Dam catchment.

Keywords: geographic information systems, hydrological modelling, remote sensing, water resources management

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Authors: Eva L. Sanjuán, Jacinto Martín, M. Isabel Parra, Mario M. Pizarro

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In Extreme Value Theory, inference estimation for the parameters of the distribution is made employing a small part of the observation values. When block maxima values are taken, many data are discarded. We developed a new Bayesian inference model to seize all the information provided by the data, introducing informative priors and using the relations between baseline and limit parameters. Firstly, we studied the accuracy of the new model for three baseline distributions that lead to a Gumbel extreme distribution: Exponential, Normal and Gumbel. Secondly, we considered mixtures of Normal variables, to simulate practical situations when data do not adjust to pure distributions, because of perturbations (noise).

Keywords: bayesian inference, extreme value theory, Gumbel distribution, highly informative prior

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Authors: Rowan P. Martnishn

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During the execution of a National Endowment of the Arts grant, approximately 55 interviews were collected from professionals across various fields. These interviews were used to create deliverables – historical connections for creations that began as art and evolved entirely into computing technology. With dozens of hours’ worth of transcripts to be analyzed by qualitative coders, a quantitative methodology was created to sift through the documents. The initial step was to both clean and format all the data. First, a basic spelling and grammar check was applied, as well as a Python script for normalized formatting which used an open-source grammatical formatter to make the data as coherent as possible. 10 documents were randomly selected to manually review, where words often incorrectly translated during the transcription were recorded and replaced throughout all other documents. Then, to remove all banter and side comments, the transcripts were spliced into paragraphs (separated by change in speaker) and all paragraphs with less than 300 characters were removed. Secondly, a keyword extractor, a form of natural language processing where significant words in a document are selected, was run on each paragraph for all interviews. Every proper noun was put into a data structure corresponding to that respective interview. From there, a Bidirectional and Auto-Regressive Transformer (B.A.R.T.) summary model was then applied to each paragraph that included any of the proper nouns selected from the interview. At this stage the information to review had been sent from about 60 hours’ worth of data to 20. The data was further processed through light, manual observation – any summaries which proved to fit the criteria of the proposed deliverable were selected, as well their locations within the document. This narrowed that data down to about 5 hours’ worth of processing. The qualitative researchers were then able to find 8 more connections in addition to our previous 4, exceeding our minimum quota of 3 to satisfy the grant. Major findings of the study and subsequent curation of this methodology raised a conceptual finding crucial to working with qualitative data of this magnitude. In the use of artificial intelligence there is a general trade off in a model between breadth of knowledge and specificity. If the model has too much knowledge, the user risks leaving out important data (too general). If the tool is too specific, it has not seen enough data to be useful. Thus, this methodology proposes a solution to this tradeoff. The data is never altered outside of grammatical and spelling checks. Instead, the important information is marked, creating an indicator of where the significant data is without compromising the purity of it. Secondly, the data is chunked into smaller paragraphs, giving specificity, and then cross-referenced with the keywords (allowing generalization over the whole document). This way, no data is harmed, and qualitative experts can go over the raw data instead of using highly manipulated results. Given the success in deliverable creation as well as the circumvention of this tradeoff, this methodology should stand as a model for synthesizing qualitative data while maintaining its original form.

Keywords: B.A.R.T.model, keyword extractor, natural language processing, qualitative coding

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Authors: Aruna Bhat

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Culture can be placed within the social structure that embodies both the creation of social groups, and the manner in which they interact with each other. As many critics have pointed out, culture in the Postmodern context has often been considered a commodity, and indeed it shares many attributes with commercial products. Popular culture follows many patterns of behavior derived from Economics, from the simple principle of supply and demand, to the creation of marketable demographics which fit certain criterion. This trend is exemplary visible in contemporary fiction, especially in contemporary science fiction; Cyberpunk fiction in particular which is an off shoot of pure science fiction. William Gibson is one such author who in his works portrays such a scenario, and in his The Bridge Trilogy he adds another level of interpretation to this state of affairs, by describing a world that is centered on industrialization of a new kind – that focuses around data in the cyberspace. In this new world, data has become the most important commodity, and man has become nothing but a nodal point in a vast ocean of raw data resulting into commodification of each thing including Culture. This paper will attempt to study the presence of above mentioned elements in William Gibson’s The Bridge Trilogy. The theories applied will be Postmodernism and Cultural studies.

Keywords: culture, commodity, cyberpunk, data, postmodern

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Authors: Saif Ul Haq

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The current study intends to examine the safety and quality considerations of clients of housing projects and their impact on the adoption of Quality Function Deployment (QFD) by the construction firm. Mixed method research technique has been used to collect and analyze the data wherein a survey was conducted to collect the data from 220 clients of housing projects in Saudi Arabia. Then, the telephonic and Skype interviews were conducted to collect data of 15 professionals working in the top ten real estate companies of Saudi Arabia. Data were analyzed by using partial least square (PLS) and thematic analysis techniques. Findings reveal that today’s customer prioritizes the safety and quality requirements of their houses and as a result, construction firms adopt QFD to address the needs of customers. The findings are of great importance for the clients of housing projects as well as for the construction firms as they could apply QFD in housing projects to address the safety and quality concerns of their clients.

Keywords: construction industry, quality considerations, quality function deployment, safety considerations

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Authors: Tahira Imtiaz, Karim Ullah

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This paper aims to incorporate the banks employees’ perspective on acceptability of Islamic banking by the customers of Peshawar. A qualitative approach is adopted for which six in-depth interviews with employees of Islamic banks are conducted. The employees were asked to share their experience regarding customers’ acceptance attitude towards acceptability of Islamic banking. Collected data was analyzed through thematic analysis technique and its synthesis with the current literature. Through data analysis a theoretical framework is developed, which highlights the factors which drive customers towards Islamic banking, as witnessed by the employees. The practical implication of analyzed data evident that a new model could be developed on the basis of four determinants of human preference namely: inner satisfaction, time, faith and market forces.

Keywords: customers’ attraction, employees’ perspective, Islamic banking, Riba

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Authors: Tom Ryan

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This paper investigates the rural mobility and accessibility challenges of a specific target group - Seniors. The target group is those over 66 years of age who are entitled to use the Public Transport (PT) Free Travel Scheme in rural Ireland. The paper explores at a high level some of the projected rural PT challenges and requirements over the next 10-15 years, noting that statistical predictions show that there will be a significant population demographic shift within the Senior's age profile. Using the PESTEL framework, the literature review explored existing research concerning mobility, accessibility challenges, and the opportunities Seniors face. Twenty-seven qualitative in-depth interviews with stakeholders within the ecosystem were undertaken. The stakeholders included: rural PT customers, Local-Link managers, NTA senior management, a Minister of State, and a European parliament policymaker. Tier 1 interviewee feedback spotlights that the PT network system does not exist for rural patients to access hospital facilities. There was no evidence from the Tier 2 research findings to show that health policymakers and transport planners are working to deliver a national solution to support patients getting access to hospital appointments. Several research interviewees discussed the theme of isolation and the perceived stigma of senior males utilising PT. The findings indicated that MaaS is potentially revolutionary in the PT arena. Finally, this paper suggests several short-, medium- and long-term recommendations based on the research findings. These recommendations are a potential springboard to ensure that rural PT is suitable for future Irish generations.

Keywords: accessibility, active ageing, car dependence, isolation, seniors health issues, behavioural changes, environmental challenges, internet of things, demand responsive, mobility as a service

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Authors: Yinghui Shang, Ziqing Zhou, Rong Han, Hang Wang, Xiaodi Liu, Yong Yang

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The design of advanced amorphous solids, such as metallic glasses, with targeted properties through artificial intelligence signifies a paradigmatic shift in physical metallurgy and materials technology. Here, we developed a machine-learning architecture that facilitates the generation of metallic glasses with targeted multifunctional properties. Our architecture integrates the state-of-the-art unsupervised generative adversarial network model with supervised models, allowing the incorporation of general prior knowledge derived from thousands of data points across a vast range of alloy compositions, into the creation of data points for a specific type of composition, which overcame the common issue of data scarcity typically encountered in the design of a given type of metallic glasses. Using our generative model, we have successfully designed copper-based metallic glasses, which display exceptionally high hardness or a remarkably low modulus. Notably, our architecture can not only explore uncharted regions in the targeted compositional space but also permits self-improvement after experimentally validated data points are added to the initial dataset for subsequent cycles of data generation, hence paving the way for the customized design of amorphous solids without human intervention.

Keywords: metallic glass, artificial intelligence, mechanical property, automated generation

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Authors: Sunghae Jun

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Technology management (TM) is important issue in a company improving the competitiveness. Among many activities of TM, technology analysis (TA) is important factor, because most decisions for management of technology are decided by the results of TA. TA is to analyze the developed results of target technology using statistics or Delphi. TA based on Delphi is depended on the experts’ domain knowledge, in comparison, TA by statistics and machine learning algorithms use objective data such as patent or paper instead of the experts’ knowledge. Many quantitative TA methods based on statistics and machine learning have been studied, and these have been used for technology forecasting, technological innovation, and management of technology. They applied diverse computing tools and many analytical methods case by case. It is not easy to select the suitable software and statistical method for given TA work. So, in this paper, we propose a methodology for quantitative TA using statistical computing software called R and data science to construct a general framework of TA. From the result of case study, we also show how our methodology is applied to real field. This research contributes to R&D planning and technology valuation in TM areas.

Keywords: technology management, R system, R data science, statistics, machine learning

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Authors: Mohd Asrul Affendi Bi Abdullah, Nyi Nyi Naing

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The purpose of this study was to identify comparable manner between negative binomial death rate (NBDR) and zero inflated negative binomial death rate (ZINBDR) with died patients with (HIV + T B+) and (HIV + T B−). HIV and TB is a serious world wide problem in the developing country. Data were analyzed with applying NBDR and ZINBDR to make comparison which a favorable model is better to used. The ZINBDR model is able to account for the disproportionately large number of zero within the data and is shown to be a consistently better fit than the NBDR model. Hence, as a results ZINBDR model is a superior fit to the data than the NBDR model and provides additional information regarding the died mechanisms HIV+TB. The ZINBDR model is shown to be a use tool for analysis death rate according age categorical.

Keywords: zero inflated negative binomial death rate, HIV and TB, AIC and BIC, death rate

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Authors: Chen Wang, Jared Evans, Yan Asmann

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With the quick evolvement of next-generation sequencing techniques, whole-exome or exome-panel data have become a cost-effective way for detection of small exonic mutations, but there has been a growing desire to accurately detect copy number variations (CNVs) as well. In order to address this research and clinical needs, we developed a sequencing coverage pattern-based method not only for copy number detections, data integrity checks, CNV calling, and visualization reports. The developed methodologies include complete automation to increase usability, genome content-coverage bias correction, CNV segmentation, data quality reports, and publication quality images. Automatic identification and removal of poor quality outlier samples were made automatically. Multiple experimental batches were routinely detected and further reduced for a clean subset of samples before analysis. Algorithm improvements were also made to improve somatic CNV detection as well as germline CNV detection in trio family. Additionally, a set of utilities was included to facilitate users for producing CNV plots in focused genes of interest. We demonstrate the somatic CNV enhancements by accurately detecting CNVs in whole exome-wide data from the cancer genome atlas cancer samples and a lymphoma case study with paired tumor and normal samples. We also showed our efficient reuses of existing exome sequencing data, for improved germline CNV calling in a family of the trio from the phase-III study of 1000 Genome to detect CNVs with various modes of inheritance. The performance of the developed method is evaluated by comparing CNV calling results with results from other orthogonal copy number platforms. Through our case studies, reuses of exome sequencing data for calling CNVs have several noticeable functionalities, including a better quality control for exome sequencing data, improved joint analysis with single nucleotide variant calls, and novel genomic discovery of under-utilized existing whole exome and custom exome panel data.

Keywords: bioinformatics, computational genetics, copy number variations, data reuse, exome sequencing, next generation sequencing

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Authors: Michael Okeke, Andrew Blyth

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Supervisory Control And Data Acquisition (SCADA) as the state of the art Industrial Control Systems (ICS) are used in many different critical infrastructures, from smart home to energy systems and from locomotives train system to planes. Security of SCADA systems is vital since many lives depend on it for daily activities and deviation from normal operation could be disastrous to the environment as well as lives. This paper describes how No-Trust-Zone (NTZ) architecture could be incorporated into SCADA Systems in order to reduce the chances of malicious intent. The architecture is made up of two distinctive parts which are; the field devices such as; sensors, PLCs pumps, and actuators. The second part of the architecture is designed following lambda architecture, which is made up of a detection algorithm based on Particle Swarm Optimization (PSO) and Hadoop framework for data processing and storage. Apache Spark will be a part of the lambda architecture for real-time analysis of packets for anomalies detection.

Keywords: industrial control system (ics, no-trust-zone (ntz), particle swarm optimisation (pso), supervisory control and data acquisition (scada), swarm intelligence (SI)

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Authors: Seongjun Kim, Jinwooung Kim, Sung-Ah Kim

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The development of information and communication technology also affects human cognition and thinking, especially in the field of design, new techniques are being tried. In architecture, new design methodologies such as machine learning or data-driven design are being applied. In particular, these methodologies are used in analyzing the factors related to the value of real estate or analyzing the feasibility in the early planning stage of the apartment housing. However, since the value of apartment buildings is often determined by external factors such as location and traffic conditions, rather than the interior elements of buildings, data is rarely used in the design process. Therefore, although the technical conditions are provided, the internal elements of the apartment are difficult to apply the data-driven design in the design process of the apartment. As a result, the designers of apartment housing were forced to rely on designer experience or modular design alternatives rather than data-driven design at the design stage, resulting in a uniform arrangement of space in the apartment house. The purpose of this study is to propose a methodology to support the designers to design the apartment unit plan with high consumer preference by deriving the correlation and importance of the floor plan elements of the apartment preferred by the consumers through the machine learning and reflecting this information from the early design process. The data on the pre-sale competition rate and the elements of the floor plan are collected as data, and the correlation between pre-sale competition rate and independent variables is analyzed through machine learning. This analytical model can be used to review the apartment unit plan produced by the designer and to assist the designer. Therefore, it is possible to make a floor plan of apartment housing with high preference because it is possible to feedback apartment unit plan by using trained model when it is used in floor plan design of apartment housing.

Keywords: apartment unit plan, data-driven design, design methodology, machine learning

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Authors: Kornelius Ronald Demu, Dewi Retno Sari Saputro, Purnami Widyaningsih

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Human Development Index (HDI) is a standard measurement for a country's human development. Several factors may have influenced it, such as life expectancy, gross domestic product (GDP) based on the province's annual expenditure, the number of poor people, and the percentage of an illiterate people. The scatter plot between HDI and the influenced factors show that the plot does not follow a specific pattern or form. Therefore, the HDI's data in Indonesia can be applied with a nonparametric regression model. The estimation of the regression curve in the nonparametric regression model is flexible because it follows the shape of the data pattern. One of the nonparametric regression's method is a truncated spline. Truncated spline regression is one of the nonparametric approach, which is a modification of the segmented polynomial functions. The estimator of a truncated spline regression model was affected by the selection of the optimal knots point. Knot points is a focus point of spline truncated functions. The optimal knots point was determined by the minimum value of generalized cross validation (GCV). In this article were applied the data of Human Development Index with a truncated spline nonparametric regression model. The results of this research were obtained the best-truncated spline regression model to the HDI's data in Indonesia with the combination of optimal knots point 5-5-5-4. Life expectancy and the percentage of an illiterate people were the significant factors depend to the HDI in Indonesia. The coefficient of determination is 94.54%. This means the regression model is good enough to applied on the data of HDI in Indonesia.

Keywords: generalized cross validation (GCV), Human Development Index (HDI), knots point, nonparametric regression, truncated spline

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Authors: Prabhashini Wijewantha

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This study looks at the impact of protean career attitude of employees on their career success and next it looks at the mediation effect of career insights on the above relationship. Career success is defined as the accomplishment of desirable work related outcomes at any point in person’s work experiences over time and it comprises of two sub variables, namely, career satisfaction and perceived employability. Protean career attitude was measured using the eight items from the Self Directedness subscale of the Protean Career Attitude scale developed by Briscoe and Hall, where as career satisfaction was measured by the three item scale developed by Martine, Eddleston, and Veiga. Perceived employability was also evaluated using three items and career insight was measured using fourteen items that were adapted and used by De Vos and Soens. Data were collected from a sample of 300 mid career executives in Sri Lanka deploying the survey strategy and data were analyzed using the SPSS and AMOS software version 20.0. A preliminary analysis of data was initially performed where data were screened and reliability and validity were ensured. Next a simple regression analysis was performed to test the direct impact of protean career attitude on career success and the hypothesis was supported. The Baron and Kenney’s four steps, three regressions approach for mediator testing was used to calculate the mediation effect of career insight on the above relationship and a partial mediation was supported by the data. Finally theoretical and practical implications are discussed.

Keywords: career success, career insight, mid career MBAs, protean career attitude

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Authors: Innocent Uzougbo Onwuegbuzie

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Wireless Sensor Networks (WSNs) are crucial for numerous applications, yet they face significant challenges due to resource constraints such as limited power and memory. Traditional routing algorithms like Dijkstra, Ad hoc On-Demand Distance Vector (AODV), and Bellman-Ford, while effective in path establishment and discovery, are not optimized for the unique demands of WSNs due to their large memory footprint and power consumption. This paper introduces the Adaptive Energy-Aware Routing (AEAR) model, a solution designed to address these limitations. AEAR integrates reactive route discovery, localized decision-making using geographic information, energy-aware metrics, and dynamic adaptation to provide a robust and efficient routing strategy. We present a detailed comparative analysis using a dataset of 50 sensor nodes, evaluating power consumption, memory footprint, and path cost across AEAR, Dijkstra, AODV, and Bellman-Ford algorithms. Our results demonstrate that AEAR significantly reduces power consumption and memory usage while optimizing path weight. This improvement is achieved through adaptive mechanisms that balance energy efficiency and link quality, ensuring prolonged network lifespan and reliable communication. The AEAR model's superior performance underlines its potential as a viable routing solution for energy-constrained WSN environments, paving the way for more sustainable and resilient sensor network deployments.

Keywords: wireless sensor networks (WSNs), adaptive energy-aware routing (AEAR), routing algorithms, energy, efficiency, network lifespan

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Authors: Nourhan A. Saad, Sara Elgazzar, Gehan Saleh

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The food industry nowadays is becoming customer-oriented and needs faster response time to deal with food incidents. There is a deep need for good traceability systems to help the supply chain (SC) partners to minimize production and distribution of unsafe or poor quality products, which in turn will enhance the food SC performance. The current food labeling systems implemented in developing countries cannot guarantee that food is authentic, safe and of good quality. Therefore, the use of origin labels, mainly the geographical indications (GIs), allows SC partners to define quality standards and defend their products' reputation. According to our knowledge there are no studies discussed the use of GIs in developing countries. This research represents a research schema about the implementation of European quality labeling system in developing countries and its impact on enhancing SC performance. An empirical study was conducted on the Egyptian traditional food sector based on a sample of seven restaurants implementing the Med-diet labeling system. First, in-depth interviews were carried out to analyze the Egyptian traditional food SC. Then, a framework was developed to link the European quality labeling system and SC performance. Finally, a structured survey was conducted based on the applied framework to investigate the impact of Med-diet labeling system on the SC performance. The research provides an applied framework linking Med-diet quality labeling system to SC performance of traditional food sector in developing countries generally and especially in the Egyptian traditional food sector. The framework can be used as a SC performance management tool to increase the effectiveness and efficiency of food industry's SC performance.

Keywords: food supply chain, med-diet labeling system, quality labeling system, supply chain performance

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Authors: Farideh Gheitasi, Amir Hossain Jaberansari, Payam Abedini

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The World Health Organization (WHO) Manifesto for Safe Communities states that "All human beings have an equal right to health and safety". The purpose of a safe Community is to minimize the damages threatening people. It seems that not sufficient attention has been given to relate environment and objectives of the safe Community. The reason for that can be assigned to the lack of enough information about environmental parameters and their relation with indices of the safe community like type and effect time of damages resulting from air pollution. Air pollution can be characterized as one of main environmental problems of Tehran. This problem is mostly due to the special geographic and climate situation, high population density and irregular growth in the number of vehicles. This paper is aimed at investigating the necessity of considering environmental factors to obtain a safe community through determining the effects of environmental pollution, particularly air pollution, on 490000 elders (+65) of Tehran. The methodology used in this study was on the basis of Random sampling and social surveying. The number of questionnaires was determined to be 321 through using Cochran method and the questionnaires were filled out by elders during personal interviews. The analysis of obtained results indicated that elders believe the major effects of air pollution include heart and respiratory diseases, obligation to stay at home on polluted days and its associated mental problems. Moreover, it was found that there is direct link between the number of polluted days and mortality frequency of elders. Having an environmental view may have an appreciable influence on the qualitative and quantitative development of activities and also facilitate obtaining the goals of the Safe Communities. In addition to reduce damages caused by pollutions, this view will encourage friends of the environment to cooperate with authorities of the safe community.

Keywords: air pollution, elderly people, environment, waste management

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Authors: Noor Abdelhamid, Donovan Nelson, Cara Prosser

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The architectural design process could be mapped out as a dialogue between designer and user that is constructed across multiple phases with the overarching goal of aligning design outcomes with user needs. Traditionally, this dialogue is bounded within a preliminary phase of determining factors that will direct the design intent, and a completion phase, of handing off the project to the client. Pre- and post-occupancy evaluations (P/POE’s) could provide an alternative process by extending this dialogue on both ends of the design process. The purpose of this research is to study the influence of systematic pre-occupancy data collection in achieving design goals by conducting post-occupancy evaluations of two case studies. In the context of this study, systematic pre-occupancy data collection is defined as the preliminary documentation of the existing conditions that helps portray stakeholders’ needs. When implemented, pre-occupancy occurs during the early phases of the architectural design process, utilizing the information to shape the design intent. Investigative POE’s are performed on two case studies with distinct early design approaches to understand how the current space is impacting user needs, establish design outcomes, and inform future strategies. The first case study underwent systematic pre-occupancy data collection and synthesis, while the other represents the traditional, uncoordinated practice of informally collecting data during an early design phase. POE’s target the dynamics between the building and its occupants by studying how spaces are serving the needs of the users. Data collection for this study consists of user surveys, audiovisual materials, and observations during regular site visits. Mixed methods of qualitative and quantitative analyses are synthesized to identify patterns in the data. The paper concludes by positioning value on both sides of the architectural design process: the integration of systematic pre-occupancy methods in the early phases and the reinforcement of a continued dialogue between building and design team after building completion.

Keywords: architecture, design process, pre-occupancy data, post-occupancy evaluation

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Authors: Niloofar Ashktorab, Negar Ashktorab

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Oil exports fund nearly half of Iran’s government expenditures, since many years other countries have been imposed different sanctions against Iran. Sanctions that primarily target Iran’s key energy sector have harmed Iran’s economy. The strategic effects of sanctions might be reduction as Iran adjusts to them economically. In this study, we evaluate the impact of oil price and sanctions against Iran on food commodity prices by using panel data method. Here, we find that the food commodity prices, the oil price and real exchange rate are stationary. The results show positive effect of oil price changes, real exchange rate and sanctions on food commodity prices.

Keywords: oil price, food basket, sanctions, panel data, Iran

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Authors: Laila Khaled Almawaldi, Hiew Khai Hang, Sugumaran A. l. Nallusamy

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Legacy systems are crucial for organizations, but their intricacy and lack of documentation pose challenges for maintenance and enhancement. Redocumentation of legacy systems is vital for automatically or semi-automatically creating documentation for software lacking sufficient records. It aims to enhance system understandability, maintainability, and knowledge transfer. However, existing redocumentation methods need improvement in data processing performance and document generation efficiency. This stems from the necessity to efficiently handle the extensive and complex code of legacy systems. This paper proposes a method for semi-automatic legacy system re-documentation using semantic parallel processing and ontology. Leveraging parallel processing and ontology addresses current challenges by distributing the workload and creating documentation with logically interconnected data. The paper outlines challenges in legacy system redocumentation and suggests a method of redocumentation using parallel processing and ontology for improved efficiency and effectiveness.

Keywords: legacy systems, redocumentation, big data analysis, parallel processing

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Authors: Meline Mesropyan

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At the beginning of the 20th century, Japan served as a transit point for Armenian refugees fleeing the 1915 Genocide. However, research on Armenian refugees in Japan is sparse, and the Armenian Diaspora has never taken root in Japan. Consequently, Japan has not been considered a relevant research site for studying Armenian refugees. The primary objective of this study is to shed light on the number of Armenian refugees who passed through Japan between 1915 and 1930. Quantitative analyses will be conducted based on newly uncovered Japanese archival documents. Subsequently, the Japanese data will be compared to American immigration data to estimate the potential number of refugees in Japan during that period. This under-researched area is relevant to both the Armenian Diaspora and refugee studies in Japan. By clarifying the number of refugees, this study aims to enhance understanding of Japan's treatment of refugees and the extent of humanitarian efforts conducted by organizations and individuals in Japan, contributing to the broader field of historical refugee studies.

Keywords: Armenian genocide, Armenian refugees, Japanese statistics, number of refugees

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Authors: Shaik Ayesha Fathima, Shaik Noor Jahan, Duvvada Rajeswara Rao

Abstract:

Earth's environment and its evolution can be seen through satellite images in near real-time. Through satellite imagery, remote sensing data provide crucial information that can be used for a variety of applications, including image fusion, change detection, land cover classification, agriculture, mining, disaster mitigation, and monitoring climate change. The objective of this project is to propose a method for classifying satellite images according to multiple predefined land cover classes. The proposed approach involves collecting data in image format. The data is then pre-processed using data pre-processing techniques. The processed data is fed into the proposed algorithm and the obtained result is analyzed. Some of the algorithms used in satellite imagery classification are U-Net, Random Forest, Deep Labv3, CNN, ANN, Resnet etc. In this project, we are using the DeepLabv3 (Atrous convolution) algorithm for land cover classification. The dataset used is the deep globe land cover classification dataset. DeepLabv3 is a semantic segmentation system that uses atrous convolution to capture multi-scale context by adopting multiple atrous rates in cascade or in parallel to determine the scale of segments.

Keywords: area calculation, atrous convolution, deep globe land cover classification, deepLabv3, land cover classification, resnet 50

Procedia PDF Downloads 141

Authors: A. Almaneea, N. Kapur, J. L. Summers, H. M. Thompson

Abstract:

Meeting the growth in demand for digital services such as social media, telecommunications, and business and cloud services requires large scale data centres, which has led to an increase in their end use energy demand. Generally, over 30% of data centre power is consumed by the necessary cooling overhead. Thus energy can be reduced by improving the cooling efficiency. Air and liquid can both be used as cooling media for the data centre. Traditional data centre cooling systems use air, however liquid is recognised as a promising method that can handle the more densely packed data centres. Liquid cooling can be classified into three methods; rack heat exchanger, on-chip heat exchanger and full immersion of the microelectronics. This study quantifies the improvements of heat transfer specifically for the case of immersed microelectronics by varying the CPU and heat sink location. Immersion of the server is achieved by filling the gap between the microelectronics and a water jacket with a dielectric liquid which convects the heat from the CPU to the water jacket on the opposite side. Heat transfer is governed by two physical mechanisms, which is natural convection for the fixed enclosure filled with dielectric liquid and forced convection for the water that is pumped through the water jacket. The model in this study is validated with published numerical and experimental work and shows good agreement with previous work. The results show that the heat transfer performance and Nusselt number (Nu) is improved by 89% by placing the CPU and heat sink on the bottom of the microelectronics enclosure.

Keywords: CPU location, data centre cooling, heat sink in enclosures, immersed microelectronics, turbulent natural convection in enclosures

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Authors: J. Fajardo, J. Guerra, E. Gonzales

Abstract:

This paper will outline a study of Brazil's industrial base of defense (IDB), through a bibliographic research method, combined with an analysis of macroeconomic data from several available public data platforms. This paper begins with a brief study about Brazilian national industry, including analyzes of productivity, income, outcome and jobs. Next, the research presents a study on the defense industry in Brazil, presenting the main national companies that operate in the aeronautical, army and naval branches. After knowing the main points of the Brazilian defense industry, data on the productivity of the defense industry of the main countries and competing companies of the Brazilian industry were analyzed, in order to summarize big cases in Brazil with a comparative analysis. Concerned the methodology, were used bibliographic research and the exploration of historical data series, in order to analyze information, to get trends and to make comparisons along the time. The research is finished with the main trends for the development of the Brazilian defense industry, comparing the current situation with the point of view of several countries.

Keywords: economics of defence, industry, trends, market

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Authors: M. Lghoul, N. El Goumi, M. Guernouche

Abstract:

In order to predict the structural and tectonic framework of the Bahira basin and to have a 3D geological modeling of the basin, an integrated multidisciplinary work has been conducted using gravity, magnetic and geological data. The objective of the current study is delineating the subsurfacefeatures, faults, and geological limits, using airborne magnetic and gravity data analysis of the Bahira basin. To achieve our goal, we have applied different enhanced techniques on magnetic and gravity data: power spectral analysis techniques, reduction to pole (RTP), upward continuation, analytical signal, tilt derivative, total horizontal derivative, 3D Euler deconvolutionand source parameter imagining. The major lineaments/faults trend are: NE–SW, NW-SE, ENE–WSW, and WNW–ESE. The 3D Euler deconvolution analysis highlighted a number of fault trend, mainly in the ENE-WSW, WNW-ESE directions. The depth tothe top of the basement sources in the study area ranges between 200 m, in the southern and northern part of the Bahira basin, to 5000 m located in the Eastern part of the basin.

Keywords: magnetic, gravity, structural trend, depth to basement

Procedia PDF Downloads 133