Search results for: smart trash can

Authors: Kashif Laeeq, Zubair A. Shaikh

Abstract:

The paradigm of education is drastically changing from conventional to e-learning model. Due to ease of learning with various other benefits, several educational institutions are adopting the e-learning models. Some institutions are still willing to transform their educational system on to e-learning, but due to limited resources, they are still compromising on the old traditional system. The cloud computing could be one of the best solutions to overcome this problem by providing hardware, software, and infrastructure resources with cost efficient manner. The adoption of cloud computing in education will bring revolution in this paradigm. This paper introduces various positive features of e-learning and presents a way how cloud computing technology can be provisioned e-learning model. This paper also investigates the numerous challenges and opportunities that would be observed in cloud computing adoption in e-learning domain. The concept and knowledge present in this paper may create a new direction of research in the domain of cloud-based e-learning.

Keywords: cloud-based e-learning, e-learning, cloud computing application, smart learning

Procedia PDF Downloads 407

Authors: Arshia Aflaki, Hadis Karimipour, Anik Islam

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Generative Adversarial Attacks (GAAs) threaten critical sectors, ranging from fingerprint recognition to industrial control systems. Existing Deep Learning (DL) algorithms are not robust enough against this kind of cyber-attack. As one of the most critical industries in the world, the power grid is not an exception. In this study, a Deep Reinforcement Learning-based (DRL) framework assisting the DL model to improve the robustness of the model against generative adversarial attacks is proposed. Real-world smart grid stability data, as an IIoT dataset, test our method and improves the classification accuracy of a deep learning model from around 57 percent to 96 percent.

Keywords: generative adversarial attack, deep reinforcement learning, deep learning, IIoT, generative adversarial networks, power system

Procedia PDF Downloads 35

Authors: Saleh Abu Hashanah, Abirami Radhakrishnan, Dessa David

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Sustainable practices in the supply chain have been an area of focus that require consideration of environmental, economic, and social sustainability practices. This paper aims to examine the use of blockchain as a disruptive technology to promote sustainable supply chains. Content analysis was used to analyze the uses of blockchain technology in sustainable supply chains. The results showed that blockchain technology features such as traceability, transparency, smart contracts, accountability, trust, immutability, anti-fraud, and decentralization promote sustainable supply chains. It is found that these features have impacted organizational efficiency in operations, transportation, and production, minimizing costs and reducing carbon emissions. In addition, blockchain technology has been found to elicit customer trust in the products.

Keywords: blockchain technology, sustainability, supply chains, economic sustainability, environmental sustainability, social sustainability

Procedia PDF Downloads 104

Authors: Sachin Nagargoje

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Complete labeled data is often difficult to obtain in a practical scenario. Even if one manages to obtain the data, the quality of the data is always in question. In shopping vertical, offers are the input data, which is given by advertiser with or without a good quality of information. In this paper, an author investigated the possibility of using a very simple Semi-supervised learning approach to increase the recall of unhealthy offers (has badly written Offer Title or partial product details) in shopping vertical domain. The author found that the semisupervised learning method had improved the recall in the Smart Phone category by 30% on A=B testing on 10% traffic and increased the YoY (Year over Year) number of impressions per month by 33% at production. This also made a significant increase in Revenue, but that cannot be publicly disclosed.

Keywords: semi-supervised learning, clustering, recall, coverage

Procedia PDF Downloads 120

Authors: Chen Xi, Liu Xuebing, Lao Xueru, Kuan Sinman, Jiang Yike, Wang Hanwei, Yang Xiaolang, Zhou Junjie, Xie Jinpeng

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To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behavior recognition models, to provide empirical data such as 'pedestrian flow data and human behavioral characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, sustainable development

Procedia PDF Downloads 416

Authors: Tobias Wissing, Peter Burggräf, Johannes Wagner

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Cost pressure, competitiveness and the increasing turbulence of globalized saturated markets has been the driver for a variety of research activities in the field of production planning and control (PPC) during the past decades. For some time past an increasing awareness for innovative technologies in terms of Industry 4.0 can be noticed. Although there are many promising approaches a solely installation of those smart solutions will not maximize the PPC performance. To accelerate the successful digital transformation the cooperation between employee and technology also has to be adapted. The existing processes and organizational structures might be not sufficient to maximize the utilization of technological innovations. This paper presents the key results of an extensive study which was conducted by the Laboratory for Machine Tools and Production Engineering (WZL) of the RWTH Aachen University to evaluate the current situation and examine the organizational readiness for this digital transformation.

Keywords: cyber-physical production system, digital transformation, industry 4.0, production planning and control

Procedia PDF Downloads 352

Authors: A. Elnady

Abstract:

This paper presents an improved Direct Power Control (DPC) scheme applied to the multilevel inverter that forms a Distributed Generation Unit (DGU). This paper demonstrates the performance of active and reactive power injected by the DGU to the smart grid. The DPC is traditionally operated by the hysteresis controller with the Space Vector Modulation (SVM) which is applied on the 2-level inverters or 3-level inverters. In this paper, the DPC is operated by the PI controller with the Phase-Disposition Pulse Width Modulation (PD-PWM) applied to the 5-level diode clamped inverter. The new combination of the DPC, PI controller, PD-PWM and multilevel inverter proves that its performance is much better than the conventional hysteresis-SVM based DPC. Simulations results have been presented to validate the performance of the suggested control scheme in the grid-connected mode.

Keywords: direct power control, PI controller, PD-PWM, and power control

Procedia PDF Downloads 236

Authors: Mohammad Rahman, Guy Burton, Megan Mathias

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Strategic management as an organizational practice was adopted by the public sector in the New Public Management (NPM) era that began in most parts of the world in the 1980s. Strategy as a new public management concept was subscribed by governments in both developed and developing world, as they were persuaded that clearly defined vision, mission and goals, as well as programs and projects - aligned with the goals - could potentially help achieve government vision at the national level and organizational goals at the service-delivery level. The advocates for strategic management in the public sector saw an inherent link between strategy and performance, claiming that the implementation of organizational strategy has an effect on the overall performance of an organization. Arguably, many government entities that have failed in enhancing team and individual performance had poorly-designed strategy or weak strategy implementation. Another key argument about low-level performance is linked with lack of strategic sense-making and orientation by middle managers in particular. Scholars maintain that employees at all levels need to understand strategic management plan in order to facilitate its implementation. Therefore, involving employees (particularly the middle managers) from the beginning potentially helps an organization avoid the drop in performance, and on the contrary would increase their commitment. The United Arab Emirates (UAE) is well known for adopting public sector reform strategies and tools since the 1990s. This observation is contextually pertinent in the case of the Government of Dubai, which has provided a Strategy Execution Guide to all of its entities to achieve high level strategic success in service delivery. The Dubai public sector also adopts road maps for e-Government, Smart Dubai, Expo 2020, investment, environment, education, health and other sectors. Evidently, some of these strategies are bringing tangible (e.g. Smart Dubai transformation) results in a transformational manner. However, the amount of academic research and literature on the strategy process vis-à-vis staff performance in the Government of Dubai is limited. In this backdrop, this study examines how individual performance of public sector employees in Dubai is linked with their sense-making, engagement and orientation with strategy development and implementation processes. Based on a theoretical framework, this study will undertake a sample-based questionnaire survey amongst middle managers in Dubai public sector to (a) measure the level of engagement of middle managers in strategy development and implementation processes as perceived by them; (b) observe the organizational landscape in which role expectations are placed on middle managers; and (c) examine the impact of employee engagement in strategy development process and the conditions for role expectations on individual performance. The paper is expected to provide new insights on the interface between strategic sense-making and performance in order to contribute a better understanding of the current culture/practices of staff engagement in strategic management in the public sector of Dubai.

Keywords: employee performance, government of Dubai, middle managers, strategic sense-making

Procedia PDF Downloads 197

Authors: Bekkem Chakradhar Reddy, Y. Soni Priya, Mathivanan G., L. K. Joshila Grace, N. Srinivasan, Asha P.

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Currently, there are a lot of problems related to marking attendance in schools, offices, or other places. Organizations tasked with collecting daily attendance data have numerous concerns. There are different ways to mark attendance. The most commonly used method is collecting data manually by calling each student. It is a longer process and problematic. Now, there are a lot of new technologies that help to mark attendance automatically. It reduces work and records the data. We have proposed to implement attendance marking using the latest technologies. We have implemented a system based on face identification and analyzing faces. The project is developed by gathering faces and analyzing data, using deep learning algorithms to recognize faces effectively. The data is recorded and forwarded to the host through mail. The project was implemented in Python and Python libraries used are CV2, Face Recognition, and Smtplib.

Keywords: python, deep learning, face recognition, CV2, smtplib, Dlib.

Procedia PDF Downloads 55

Authors: Getaneh Berie Tarekegn, Li-Chia Tai

Abstract:

With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarms, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

Procedia PDF Downloads 41

Authors: Changfeng Fu

Abstract:

Sustainable urban development has been widely accepted a common sense in the modern urban planning and design. However, the measurement and assessment of urban sustainability, especially the quantitative assessment have been always an issue obsessing planning and design professionals. This paper will present an on-going research on the principles and technologies to develop a quantitative urban sustainability assessment principles and techniques which aim to integrate indicators, geospatial and geo-reference data, and assessment techniques together into a mechanism. It is based on the principles and techniques of geospatial analysis with GIS and statistical analysis methods. The decision-making technologies and methods such as AHP and SMART are also adopted to address overall assessment conclusions. The possible interfaces and presentation of data and quantitative assessment results are also described. This research is based on the knowledge, situations and data sources of UK, but it is potentially adaptable to other countries or regions. The implementation potentials of the mechanism are also discussed.

Keywords: urban sustainability assessment, quantitative analysis, sustainability indicator, geospatial data, big data

Procedia PDF Downloads 354

Authors: Bernard Morais Joosa

Abstract:

Kerala, the southern state of India, is known for its accomplishments in universal education and enrollments. Through this mission, the Government proposes comprehensive educational reforms including 1000 Government schools into international standards during the first phase. The idea is not only to improve the infrastructural facilities but also to reform the teaching and learning process to the present day needs by introducing ICT enabled learning and providing smart classrooms. There will be focus on creating educational programmes which are useful for differently abled students. It is also meant to reinforce the teaching–learning process by providing ample opportunities to each student to construct their own knowledge using modern technology tools. The mission will redefine the existing classroom learning process, coordinate resource mobilization efforts and develop ‘Janakeeya Vidyabhyasa Mathruka.' Special packages to support schools which are in existence for over 100 years will also be attempted. The implementation will enlist full involvement and partnership of the Parent Teacher Association. Kerala was the first state in the country to attain 100 percent literacy more than two and a half decades ago. Since then the State has not rested on its laurels. It has moved forward in leaps and bounds conquering targets that no other State could achieve. Now the government of Kerala is taking off towards new goal of comprehensive educational reforms. And it focuses on Betterment of educational surroundings, use of technology in education, renewal of learning method and 1000 schools will be uplifted as Smart Schools. Need to upgrade 1000 schools into international standards and turning classrooms from standard 9 to 12 in high schools and higher secondary into high-tech classrooms and a special unique package for the renovation of schools, which have completed 50 and 100 years. The government intends to focus on developing standards first to eighth standards in tune with the times by engaging the teachers, parents, and alumni to recapture the relevance of public schools. English learning will be encouraged in schools. The idea is not only to improve the infrastructure facilities but also reform the curriculum to the present day needs. Keeping in view the differently-abled friendly approach of the government, there will be focus on creating educational program which is useful for differently abled students. The idea is to address the infrastructural deficiencies being faced by such schools. There will be special emphasis on ensuring internet connectivity to promote IT-friendly existence. A task-force and a full-time chief executive will be in charge of managing the day to day affairs of the mission. Secretary of the Public Education Department will serve as the Mission Secretary and the Chairperson of Task Force. As the Task Force will stress on teacher training and the use of information technology, experts in the field, as well as Directors of SCERT, IT School, SSA, and RMSA, will also be a part of it.

Keywords: educational standards, methodology, pedagogy, technology

Procedia PDF Downloads 133

Authors: Mingming Guo, Xiaozan Wang

Abstract:

Introduction: The purpose of this study is to examine the correlation between the physical fitness of Chinese college students and their daily running habits (RH). Methods: A total of 718 college students from East China Normal University participated in this study (385 boys and 333 girls). Each participant participated in the Chinese Students’ Physical Fitness Test during the 2018-2019 school year. In addition, each student is also required to use the app to record all their running results during each run during the 2018-2019 school year. Researchers can query and export all running records through the app's management platform. Results: (1) The total number of kilometers run by the students showed a significant negative correlation with their vital capacity (VC), sitting body flexion (SBF), and long jump (LJ) (rᵥ

Keywords: college students, physical fitness, running habits, data mining

Procedia PDF Downloads 137

Authors: Levent Seyfi, Ertan Akman, Tuğrul C. Topak

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In this study, irrigation automation with electronic sensors and its control with smartphones were aimed. In this context, temperature and soil humidity measurements of the area irrigated were obtained by temperature and humidity sensors. A micro controller (Arduino) was utilized for accessing values of these parameters and controlling the proposed irrigation system. The irrigation system could automatically be worked according to obtained measurement values. Besides, a GSM module used together with Arduino provided that the irrigation system was in connection to smartphones. Thus, the irrigation system can be remotely controlled. Not only can we observe whether the irrigation system is working or not via developed special android application but also we can see temperature and humidity measurement values. In addition to this, if desired, the irrigation system can be remotely and manually started or stopped regardless of measured sensor vales thanks to the developed android application. In addition to smartphones, the irrigation system can be alternatively controlled via the designed website (www.sulamadenetim.com).

Keywords: smartphone, Android Operating System, sensors, irrigation System, arduino

Procedia PDF Downloads 612

Authors: Getaneh Berie Tarekegn, Li-Chia Tai

Abstract:

With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

Procedia PDF Downloads 46

Authors: Idoia Landa Oregi, Itsaso Gonzalez Ochoantesana, Olatz Nicolas Buxens, Carlo Ferretti

Abstract:

The impact of citizens in urban transformations has become increasingly important in the pursuit of creating citizen-centered cities. Citizens at the forefront of the urban transformation process are key to establishing resilient, sustainable, and inclusive cities that cater to the needs of all residents. Therefore, collecting data and information directly from citizens is crucial for the sustainable development of cities. Within this context, public participation becomes a pillar for acquiring the necessary information from citizens. Public participation in urban transformation processes establishes a more responsive, equitable, and resilient urban environment. This approach cultivates a sense of shared responsibility and collective progress in building cities that truly serve the well-being of all residents. However, the implementation of public participation practices often overlooks strategies to effectively engage citizens in the processes, resulting in non-successful participatory outcomes. Therefore, this research focuses on identifying and analyzing the critical aspects of citizen engagement during the same participatory urban transformation process in different European contexts: Ermua (Spain), Elva (Estonia) and Matera (Italy). The participatory neighborhood regeneration process is divided into three main stages, to turn social districts into inclusive and smart neighborhoods: (i) the strategic level, (ii) the design level, and (iii) the implementation level. In the initial stage, the focus is on diagnosing the neighborhood and creating a shared vision with the community. The second stage centers around collaboratively designing various action plans to foster inclusivity and intelligence while pushing local economic development within the district. Finally, the third stage ensures the proper co-implementation of the designed actions in the neighborhood. To this date, the presented results critically analyze the key aspects of engagement in the first stage of the methodology, the strategic plan, in the three above-mentioned contexts. It is a multifaceted study that incorporates three case studies to shed light on the various perspectives and strategies adopted by each city. The results indicate that despite of the various cultural contexts, all cities face similar barriers when seeking to enhance engagement. Accordingly, the study identifies specific challenges within the participatory approach across the three cities such as the existence of discontented citizens, communication gaps, inconsistent participation, or administration resistance. Consequently, key learnings of the process indicate that a collaborative sphere needs to be cultivated, educating both citizens and administrations in the aspects of co-governance, giving these practices the appropriate space and their own communication channels. This study is part of the DROP project, funded by the European Union, which aims to develop a citizen-centered urban renewal methodology to transform the social districts into smart and inclusive neighborhoods.

Keywords: citizen-centred cities, engagement, public participation, urban transformation

Procedia PDF Downloads 67

Authors: Jenn Gallup, Onur Kocaoz, Onder Islek

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In their pursuit of postsecondary transitions, individuals with disabilities tend to experience, academic, behavioral, and emotional challenges to a greater extent than their typically developing peers. These challenges result in lower rates of graduation, employment, independent living, and participation in college than their peers without disabilities. The lack of friendships and support systems has had a negative impact on those with a disability transitioning to postsecondary settings to include, employment, independent living, and university settings. Establishing friendships and support systems early on is an indicator of potential success and persistence in postsecondary education, employment, and independent living for typically developing college students. It is evident that a deficit in friendships and supports is a key deficit also for individuals with disabilities. To address the specific needs of this group, a mentor program was developed for a transition program held at the university for youth aged 18-21. Pre-service teachers enrolled in the special education program engaged with youth in the transition program in a variety of activities on campus. The mentorship program had two purposes: to assist young adults with disabilities who were transitioning to a workforce setting to help increase social skills, self-advocacy, supports and friendships, and confidence; and to give their peers without disabilities who were enrolled in a secondary special education course as a pre-service teacher the experience of interacting with and forming friendships with peers who had a disability for the purposes of career development. Additionally, according to researchers mobile technology has created a virtual world of equality and opportunity for a large segment of the population that was once marginalized due to physical and cognitive impairments. All of the participants had access to smart phones; therefore, technology was explored during this study to determine if it could be used as a compensatory tool to allow the young adults with disabilities to do things that otherwise would have been difficult because of their disabilities. Additionally, all participants were asked to incorporate technology such as smart phones to communicate beyond the activities, collaborate using virtual platform games which would support and promote social skills, soft-skills, socialization, and relationships. The findings of this study confirmed that a peer mentorship program that harnessed the power of technology supported outcomes specific to young adults with and without disabilities. Mobile technology and virtual game-based platforms, were identified as a significant contributor to personal, academic, and career growth for both groups. The technology encouraged friendships, provided an avenue for rich social interactions, and increased soft-skills. Results will be shared along with the development of the program and potential implications to the field.

Keywords: career outcomes, mentorship, soft-skills, technology, transition

Procedia PDF Downloads 167

Authors: Mustapha Benssalah, Mustapha Djeddou, Karim Drouiche

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The random number generation (RNG) presents a significant importance for the security and the privacy of numerous applications, such as RFID technology and smart cards. Since, the quality of the generated bit sequences is paramount that a weak internal generator for example, can directly cause the entire application to be insecure, and thus it makes no sense to employ strong algorithms for the application. In this paper, we propose a new pseudo random number generator (PRNG), suitable for cryptosystems ECC-based, constructed by randomly selecting points from several elliptic curves randomly selected. The main contribution of this work is the increasing of the generator internal states by extending the set of its output realizations to several curves auto-selected. The quality and the statistical characteristics of the proposed PRNG are validated using the Chi-square goodness of fit test and the empirical Special Publication 800-22 statistical test suite issued by NIST.

Keywords: PRNG, security, cryptosystem, ECC

Procedia PDF Downloads 443

Authors: Sallama Resen, Celal Öztürk

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Distance estimation between tow nodes has wide scope of surveillance and tracking applications. This paper suggests a Bluetooth Low Energy (BLE) technology as a media for transceiver and receiver signal in small indoor areas. As an example, BLE communication technologies used in child safety domains. Local network is designed to detect child position in indoor school area consisting Mobile Beacons (MB), Access Points (AP) and Smart Phones (SP) where MBs stuck in children’s shoes as wearable sensors. This paper presents a technique that can detect mobile beacons’ position and help finding children’s location within dynamic environment. By means of bluetooth beacons that are attached to child’s shoes, the distance between the MB and teachers SP is estimated with an accuracy of less than one meter. From the simulation results, it is shown that high accuracy of position coordinates are achieved for multi-mobile beacons in different environments.

Keywords: bluetooth low energy, child safety, mobile beacons, received signal strength

Procedia PDF Downloads 343

Authors: Yu-Mi Song, Sung-Ah Kim, Dongyoun Shin

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Cities are complex systems of diverse and inter-tangled activities. These activities and their complex interrelationships create diverse urban phenomena. And such urban phenomena have considerable influences on the lives of citizens. This research aimed to develop a method to reveal the causes and effects among diverse urban elements in order to enable better understanding of urban activities and, therefrom, to make better urban planning strategies. Specifically, this study was conducted to solve a data-recommendation problem found on a Korean public data homepage. First, a correlation analysis was conducted to find the correlations among random urban data. Then, based on the results of that correlation analysis, the weighted data network of each urban data was provided to people. It is expected that the weights of urban data thereby obtained will provide us with insights into cities and show us how diverse urban activities influence each other and induce feedback.

Keywords: big data, machine learning, ontology model, urban data model

Procedia PDF Downloads 416

Authors: Dereje Regasa

Abstract:

The global food system is at a crossroads, which requires prompt action to minimize the effects of the crises. Agroecology is gaining prominence due to its contributions to sustainable food systems. To support efforts in mitigating the crises, the Food and Agriculture Organization (FAO) established alternative approaches for sustainable agri-food systems. Agroecological elements and principles were developed to guide and support measures that countries need to achieve the Sustainable Development Goals (SDGs). The SDGs require the systemic integration of practices for a smart intensification or adaptation of traditional or industrial agriculture. As one of the countries working towards SDGs, the agricultural practices in Ethiopia need to be guided by these agroecological elements and principles. Aiming at the identification of challenging aspects of a sustainable agri-food system and the characterization of an enabling environment for agroecology, as well as exploring to what extent the existing policies and strategies support the agroecological transition process, five policy and strategy documents were reviewed. These documents are the Rural Development Policy and Strategy, the Environment Policy, the Biodiversity Policy, and the Soil Strategy of the Ministry of Agriculture (MoA). Using the Agroecology Criteria Tool (ACT), the contents were reviewed, focusing on agroecological requirements and the inclusion of sustainable practices. ACT is designed to support a self-assessment of elements supporting agroecology. For each element, binary values were assigned based on the inclusion of the minimum requirements index and then validated through discussion with the document owners. The results showed that the documents were well below the requirements for an agroecological transition of the agri-food system. The Rural Development Policy and Strategy only suffice to 83% in Human and Social Value. It does not support the transition concerning the other elements. The Biodiversity Policy and Soil Strategy suffice regarding the inclusion of Co-creation and Sharing of knowledge (100%), while the remaining elements were not considered sufficiently. In contrast, the Environment Policy supports the transition with three elements accounting for 100%. These are Resilience, Recycling, and Human and Social Care. However, when the four documents were combined, elements such as Synergies, Diversity, Efficiency, Human and Social value, Responsible governance, and Co-creation and Sharing of knowledge were identified as fully supportive (100%). This showed that the policies and strategies complemented one another to a certain extent. However, the evaluation results call for improvements concerning elements like Culture and food traditions, Circular and solidarity economy, Resilience, Recycling, and Regulation and balance since the majority of the elements were not sufficiently observed. Consequently, guidance for the smart intensification of local practices is needed, as well as traditional knowledge enriched with advanced technologies. Ethiopian agricultural and environmental policies and strategies should provide sufficient support and guidance for the intensification of sustainable practices and should provide a framework for an agroecological transition towards a sustainable agri-food system.

Keywords: agroecology, diversity, recycling, sustainable food system, transition

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Authors: M. M. Wagh, V. V. Kulkarni

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The rising economic activities, growing population and improving living standards of world have led to a steady growth in its appetite for quality and quantity of energy services. As the economy expands the electricity demand is going to grow further, increasing the challenges of the more generation and stresses on the utility grids. Appropriate energy model will help in proper utilization of the locally available renewable energy sources such as solar, wind, biomass, small hydro etc. to integrate in the available grid, reducing the investments in energy infrastructure. Further to these new technologies like smart grids, decentralized energy planning, energy management practices, energy efficiency are emerging. In this paper, the attempt has been made to study and review the recent energy planning models, energy forecasting models, and renewable energy integration models. In addition, various modeling techniques and tools are reviewed and discussed.

Keywords: energy modeling, integration of renewable energy, energy modeling tools, energy modeling techniques

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Authors: A. Arshad, M. Lehtonen. M. Humayun

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With the increasing Distributed Generation (DG) penetration, distribution systems are advancing towards the smart grid technology for least latency in tackling voltage control problem in a distributed manner. This paper proposes a Multi-agent based distributed voltage level control. In this method a flat architecture of agents is used and agents involved in the whole controlling procedure are On Load Tap Changer Agent (OLTCA), Static VAR Compensator Agent (SVCA), and the agents associated with DGs and loads at their locations. The objectives of the proposed voltage control model are to minimize network losses and DG curtailments while maintaining voltage value within statutory limits as close as possible to the nominal. The total loss cost is the sum of network losses cost, DG curtailment costs, and voltage damage cost (which is based on penalty function implementation). The total cost is iteratively calculated for various stricter limits by plotting voltage damage cost and losses cost against varying voltage limit band. The method provides the optimal limits closer to nominal value with minimum total loss cost. In order to achieve the objective of voltage control, the whole network is divided into multiple control regions; downstream from the controlling device. The OLTCA behaves as a supervisory agent and performs all the optimizations. At first, a token is generated by OLTCA on each time step and it transfers from node to node until the node with voltage violation is detected. Upon detection of such a node, the token grants permission to Load Agent (LA) for initiation of possible remedial actions. LA will contact the respective controlling devices dependent on the vicinity of the violated node. If the violated node does not lie in the vicinity of the controller or the controlling capabilities of all the downstream control devices are at their limits then OLTC is considered as a last resort. For a realistic study, simulations are performed for a typical Finnish residential medium-voltage distribution system using Matlab ®. These simulations are executed for two cases; simple Distributed Voltage Control (DVC) and DVC with optimized loss cost (DVC + Penalty Function). A sensitivity analysis is performed based on DG penetration. The results indicate that costs of losses and DG curtailments are directly proportional to the DG penetration, while in case 2 there is a significant reduction in total loss. For lower DG penetration, losses are reduced more or less 50%, while for higher DG penetration, loss reduction is not very significant. Another observation is that the newer stricter limits calculated by cost optimization moves towards the statutory limits of ±10% of the nominal with the increasing DG penetration as for 25, 45 and 65% limits calculated are ±5, ±6.25 and 8.75% respectively. Observed results conclude that the novel voltage control algorithm proposed in case 1 is able to deal with the voltage control problem instantly but with higher losses. In contrast, case 2 make sure to reduce the network losses through proposed iterative method of loss cost optimization by OLTCA, slowly with time.

Keywords: distributed voltage control, distribution system, multi-agent systems, smart grids

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Authors: Shaik Mohammad Samiullah Shariff, Siva Sreenath, Sai Haripriya, Prathyusha, M. Padma Lalitha

Abstract:

The Internet of Things (IoT) is the emerging technology that has been utilized to extend the possibilities for smart dairy farming (SDF). Milk consumption is continually increasing due to the world's growing population. As a result, some providers are prone to using dishonest measures to close the supply-demand imbalance, such as adding adulterants to milk. To identify the presence of adulterants in milk, traditional testing methods necessitate the use of particular chemicals and equipment. While efficient, this method has the disadvantage of yielding difficult and time-consuming qualitative results. Furthermore, same milk sample cannot be tested for other adulterants later. As a result, this study proposes an IoT-based approach for identifying adulterants in milk by measuring electrical conductivity (EC) or Total Dissolved Solids (TDS) and PH. In order to achieve this, an Arduino UNO microcontroller is used to assess the contaminants. When there is no adulteration, the pH and TDS values of milk range from 6.45 to 6.67 and 750 to 780ppm, respectively, according to this study. Finally, the data is uploaded to the cloud via an IoT device attached to the Ubidot web platform.

Keywords: internet of things (IoT), pH sensor, TDS sensor, EC sensor, industry 4.0

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Authors: Nikeshala Weerasekara, Roshan Ajward

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Contemporary business environment, given the circumstance of stringent scrutiny toward corporate behavior, organizations are under pressure to develop and implement solid overarching Corporate Social Responsibility (CSR) strategies. In that milieu, in order to differentiate themselves from competitors and maintain stakeholder confidence banks spend millions of dollars on CSR programmes. However, knowledge on how non-western bank employees perceive such activities is inconclusive. At the same time recently only researchers have shifted their focus on positive effects of compassion at work or the organizational conditions under which it arises. Nevertheless, mediation mechanisms between CSR and compassion at work have not been adequately examined leaving a vacuum to be explored. Despite finding a purpose in work that is greater than extrinsic outcomes of the work is important to employees, meaningful work has not been examined adequately. Thus, in addition to examining the direct relationship between CSR and compassion at work, this study examined the mediating capability of meaningful work between these variables. Specifically, the researcher explored how CSR enables employees to sense work as meaningful which in turn would enhance their level of compassion at work. Hypotheses were developed to examine the direct relationship between CSR and compassion at work and the mediating effect of meaningful work on the relationship between CSR and compassion at work. Both Social Identity Theory (SIT) and Social Exchange Theory (SET) were used to theoretically support the relationships. The sample comprised of 450 respondents covering different levels of the bank. A convenience sampling strategy was used to secure responses from 13 local licensed commercial banks in Sri Lanka. Data was collected using a structured questionnaire which was developed based on a comprehensive review of literature and refined using both expert opinions and a pilot survey. Structural equation modeling using Smart Partial Least Square (PLS) was utilized for data analysis. Findings indicate a positive and significant (p < .05) relationship between CSR and compassion at work. Also, it was found that meaningful work partially mediates the relationship between CSR and compassion at work. As per the findings it is concluded that bank employees’ perception of CSR engagement not only directly influence compassion at work but also impact such through meaningful work as well. This implies that employees consider working for a socially responsible bank since it creates greater meaningfulness of work to retain with the organization, which in turn trigger higher level of compassion at work. By utilizing both SIT and SET in explaining relationships between CSR and compassion at work it amounts to theoretical significance of the study. Enhance existing literature on CSR and compassion at work. Also, adds insights on mediating capability of psychologically related variables such as meaningful work. This study is expected to have significant policy implications in terms of increasing compassion at work where managers must understand the importance of including CSR activities into their strategy in order to thrive. Finally, it provides evidence of suitability of using Smart PLS to test models with mediating relationships involving non normal data.

Keywords: compassion at work, corporate social responsibility, employee commitment, meaningful work, positive affect

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Authors: Ju-Young Hwang, Hyo-Gyoung Kwak

Abstract:

This paper introduces a numerical analysis method for reinforced-concrete (RC) structures exposed to fire and compares the result with experimental results. The proposed analysis method for RC structure under the high temperature consists of two procedures. First step is to decide the temperature distribution across the section through the heat transfer analysis by using the time-temperature curve. After determination of the temperature distribution, the nonlinear analysis is followed. By considering material and geometrical nonlinearity with the temperature distribution, nonlinear analysis predicts the behavior of RC structure under the fire by the exposed time. The proposed method is validated by the comparison with the experimental results. Finally, prediction model to describe the status of after-cooling concrete can also be introduced based on the results of additional experiment. The product of this study is expected to be embedded for smart structure monitoring system against fire in u-City.

Keywords: RC, high temperature, after-cooling analysis, nonlinear analysis

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Authors: Mohammad Anwar, Hamid Ullah Khan, Shah Waliullah

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Recently, environmental education is an essential element in avoiding environmental degradation around the globe that needs new articles and policymakers’ emphasis. Hence, the present article examines the impact of environmental education on environmental knowledge, environmental behavior, and environmental attitudes in Indonesia. The present research also investigated the moderating role of government support in environmental education, environmental knowledge, environmental behavior, and environmental attitude in Indonesia. A questionnaire was used as the primary data collection method. The smart PLS was utilized to test the association among variables and the hypotheses of the study. The results revealed that environmental education had a significant and positive linkage with environmental knowledge, environmental behavior, and environmental attitude in Indonesia. The findings also exposed that government support significantly moderated environmental education, environmental knowledge, and environmental behavior in Indonesia. The findings of this research would provide help to the policymakers in establishing the policies related to environmental education and reducing environmental degradation.

Keywords: environmental education, environmental knowledge, environmental behavior, environmental attitude, government support

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Authors: Se-Han Lee, Kwang-Woo Go, Gwang-Hyun Ahn, Hee-Sung Park, Cheol-Kyu Han, Jun-Bo Shim, Geun-Chul Kang, Hyun-Jung Lee

Abstract:

In recent years, with the advent of smart cars and the expansion of the market, the announcement of 'Adventures in Automotive Networks and Control Units' at the DEFCON21 conference in 2013 revealed that cars are not safe from hacking. As a result, the HEAVENS model considering not only the functional safety of the vehicle but also the security has been suggested. However, the HEAVENS model only presents a simple process, and there are no detailed procedures and activities for each process, making it difficult to apply it to the actual vehicle security vulnerability check. In this paper, we propose an automated attack database that systematically summarizes attack vectors, attack types, and vulnerable vehicle models to prepare for various car hacking attacks, and data flow diagrams that can detect various vulnerabilities and suggest a way to materialize the HEAVENS model.

Keywords: automotive security, HEAVENS, car hacking, security model, information security

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Authors: Shazia Bano

Abstract:

Nanoconjugates that integrate photo-based therapeutics and diagnostics within a single platform promise great advances in revolutionizing cancer treatments. However, to achieve high therapeutic efficacy, designing functionally efficacious nanocarriers to tightly retain the drug, promoting selective drug localization and release, and the validation of the efficacy of these nanoconjugates is a great challenge. Here we have designed smart multiagent, liposome based targeted photoactivatable multiagent nanoconjugates, doped with a photoactivatable chromophore benzoporphyrin derivative (BPD) labelled with an active targeting ligand cetuximab to target the EGFR receptor (over expressed in various cancer cells) to deliver a combination of therapeutic agents. This study establishes a tunable nanoplatform for the delivery of the photoactivatable multiagent nanoconjugates for tumor-specific accumulation and targeted destruction of cancer cells in complex cancer model to enhance the therapeutic index of the administrated drugs.

Keywords: targeting, photodynamic therapy, photoactivatable, nanoconjugates

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Authors: Yair Bleiberg, Michael Werman

Abstract:

Coordinate-based Multi-Layer Perceptrons (MLPs) are known to have difficulty reconstructing high frequencies of the training data. A common solution to this problem is Positional Encoding (PE), which has become quite popular. However, PE has drawbacks. It has high-frequency artifacts and adds another hyper hyperparameter, just like batch normalization and dropout do. We believe that under certain circumstances, PE is not necessary, and a smarter construction of the network architecture together with a smart training method is sufficient to achieve similar results. In this paper, we show that very simple MLPs can quite easily output a frequency when given input of the half-frequency and quarter-frequency. Using this, we design a network architecture in blocks, where the input to each block is the output of the two previous blocks along with the original input. We call this a Fibonacci Network. By training each block on the corresponding frequencies of the signal, we show that Fibonacci Networks can reconstruct arbitrarily high frequencies.

Keywords: neural networks, positional encoding, high frequency intepolation, fully connected

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