Search results for: Geographic information systems (GIS)

Authors: Anant Mehrotra, Krish Phagwani

Abstract:

Democratic voting is vital for any country, but current methods like ballot papers or EVMs have drawbacks, including transparency issues, low voter turnout, and security concerns. Blockchain technology offers a potential solution by providing a secure, decentralized, and transparent platform for e-voting. With features like immutability, security, and anonymity, blockchain combined with smart contracts can enhance trust and prevent vote tampering. This paper explores an Ethereum-based e-voting application using Solidity, showcasing a web app that prevents duplicate voting through a token-based system, while also discussing the advantages and limitations of blockchain in digital voting. Voting is a crucial component of democratic decision-making, yet current methods, like paper ballots, remain outdated and inefficient. This paper reviews blockchain-based voting systems, highlighting strategies and guidelines to create a comprehensive electronic voting system that leverages cryptographic techniques, such as zero-knowledge proofs, to enhance privacy. It addresses limitations of existing e-voting solutions, including cost, identity management, and scalability, and provides key insights for organizations looking to design their own blockchain-based voting systems.

Keywords: electronic voting, smart contracts, blockchain nased voting, security

Procedia PDF Downloads 18

Authors: Guoqian Ren, Haijiang Li, Jisong Zhang

Abstract:

Over the past 40 years, urban development has undergone large-scale, high-speed expansion, beyond what was previously considered normal and in a manner not proportionally related to population growth or physical considerations. With more scientific and refined decision-making in the urban construction process, new urbanization approaches, aligned with public-private partnerships (PPPs) which evolved in the early 1990s, have become acceptable and, in some situations, even better solutions to outstanding urban municipal construction projects, especially in developing countries. However, as the main driving force to deal with urban public services, PPPs are still problematic regarding value for money (VFM) process in most large-scale construction projects. This paper therefore reviews recent PPP articles in popular project management journals and relevant toolkits, published in the last 10 years, to identify the indicators that influence VFM within PPPs across regions. With increasing concerns about profitability and environmental and social impacts, the current PPP structure requires a more integrated platform to manage multi-performance project life cycles. Building information modelling (BIM), a popular approach to the procurement process in AEC sectors, provides the potential to ensure VFM while also working in tandem with the semantic approach to holistically measure life cycle costs (LCC) and achieve better sustainability. This paper suggests that BIM applied to the entire PPP life cycle could support holistic decision-making regarding VFM processes and thus meet service targets.

Keywords: public-private partnership, value for money, building information modelling, semantic approach

Procedia PDF Downloads 215

Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan

Abstract:

This paper presents an approach for the easy creation of an institutional risk profile for endangerment analysis of file formats. The main contribution of this work is the employment of data mining techniques to support risk factors set up with just the most important values that are important for a particular organisation. Subsequently, the risk profile employs fuzzy models and associated configurations for the file format metadata aggregator to support digital preservation experts with a semi-automatic estimation of endangerment level for file formats. Our goal is to make use of a domain expert knowledge base aggregated from a digital preservation survey in order to detect preservation risks for a particular institution. Another contribution is support for visualisation and analysis of risk factors for a requried dimension. The proposed methods improve the visibility of risk factor information and the quality of a digital preservation process. The presented approach is meant to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and automatically aggregated file format metadata from linked open data sources. To facilitate decision-making, the aggregated information about the risk factors is presented as a multidimensional vector. The goal is to visualise particular dimensions of this vector for analysis by an expert. The sample risk profile calculation and the visualisation of some risk factor dimensions is presented in the evaluation section.

Keywords: digital information management, file format, endangerment analysis, fuzzy models

Procedia PDF Downloads 411

Authors: Mohd Noah A. Rahman, Afzaal H. Seyal, Sharul T. Tajuddin, Hartiny Md Azmi

Abstract:

Taking into consideration the real time situation specifically the higher academic institutions, small, medium to large companies, public to private sectors and the remaining sectors, do experience the inventory or asset shrinkages due to theft, loss or even inventory tracking errors. This happening is due to a zero or poor security systems and measures being taken and implemented in their organizations. Henceforth, implementing the Radio Frequency Identification (RFID) technology into any manual or existing web-based system or web application can simply deter and will eventually solve certain major issues to serve better data retrieval and data access. Having said, this manual or existing system can be enhanced into a mobile-based system or application. In addition to that, the availability of internet connections can aid better services of the system. Such involvement of various technologies resulting various privileges to individuals or organizations in terms of accessibility, availability, mobility, efficiency, effectiveness, real-time information and also security. This paper will look deeper into the integration of mobile devices with RFID technologies with the purpose of asset tracking and control. Next, it is to be followed by the development and utilization of MongoDB as the main database to store data and its association with RFID technology. Finally, the development of a web based system which can be viewed in a mobile based formation with the aid of Hypertext Preprocessor (PHP), MongoDB, Hyper-Text Markup Language 5 (HTML5), Android, JavaScript and AJAX programming language.

Keywords: RFID, asset tracking system, MongoDB, NoSQL

Procedia PDF Downloads 308

Authors: George Eduful, Yuanyuan Fan, Ahmed Abu-Siada

Abstract:

Ferroresonance poses a substantial threat to the quality and reliability of power distribution systems due to its inherent characteristics of sustained overvoltages and currents. This paper aims to enhance the understanding and reduce the ferroresonance threat by investigating the susceptibility of different transformer configurations using MATLAB/Simulink simulations. To achieve this, four 200 kVA transformers with different vector groups (D-Yn, Yg-Yg, Yn-Yn, and Y-D11) and core types (3-limb, 5-limb, single-phase) were systematically exposed to controlled ferroresonance conditions. The impact of varying the length of the 11 kV cable connected to the transformers was also examined. Through comprehensive voltage, current, and total harmonic distortion analyses, the performance of each configuration was evaluated and compared. The results of the study indicate that transformers with Y-D11 and Yg-Yg configurations exhibited lower susceptibility to ferroresonance, in comparison to those with D-Y11 and Yg-Yg configurations. This implies that the Y-D11 and Yg-Yg transformers are better suited for applications with high risks of ferroresonance. The insights provided by this study are of significant value for the strategic selection and deployment of transformers in power systems, particularly in settings prone to ferroresonance. By identifying and recommending transformer configurations that demonstrate better resilience, this paper contributes to enhancing the overall robustness and reliability of power grid infrastructure.

Keywords: about cable-connected, core type, ferroresonance, over voltages, power transformer, vector group

Procedia PDF Downloads 50

Authors: Jonghyuk Yoon, Hyoungwoon Song, Youngbae Kim, Eunju Kim

Abstract:

Recently, with the rapid growth of semiconductor industry, lots of interests have been focused on after treatment system that remove the polluted gas produced from semiconductor manufacturing process, and a wet scrubber is the one of the widely used system. When it comes to mechanism of removing the gas, the polluted gas is removed firstly by chemical reaction in a reactor part. After that, the polluted gas stream is brought into contact with the scrubbing liquid, by spraying it with the liquid. Effective design of the reactor part inside the wet scrubber is highly important since removal performance of the polluted gas in the reactor plays an important role in overall performance and stability. In the present study, a CFD (Computational Fluid Dynamics) analysis was performed to figure out the thermal and flow characteristics inside unit a reactor of wet scrubber. In order to verify the numerical result, temperature distribution of the numerical result at various monitoring points was compared to the experimental result. The average error rates (12~15%) between them was shown and the numerical result of temperature distribution was in good agreement with the experimental data. By using validated numerical method, the effect of the reactor geometry on heat transfer rate was also taken into consideration. Uniformity of temperature distribution was improved about 15%. Overall, the result of present study could be useful information to identify the fluid behavior and thermal performance for various scrubber systems. This project is supported by the ‘R&D Center for the reduction of Non-CO₂ Greenhouse gases (RE201706054)’ funded by the Korea Ministry of Environment (MOE) as the Global Top Environment R&D Program.

Keywords: semiconductor, polluted gas, CFD (Computational Fluid Dynamics), wet scrubber, reactor

Procedia PDF Downloads 148

Authors: Laleh Golamrej Eliasi, Mahsa Tahzibi, Mohammad Torkashvand Moradabadi

Abstract:

TheIranian Ear, Throat, Nose, Head, and Neck Research Center has estimated that three to five percent of Iran’s population has moderate to profound hearing disorders. The prevalence of hearing loss in provincial centers is equal to 4.7 per thousand live births (362 cases). The deaf community has limited access to information and health services due to language and communication barriers. Communication and language limitations isolate and limit deaf people from social media, health services, and communication with caregivers and health providers.Limitedcommunicationwith the deaf has led to a lack of knowledge and information about domestic violence against the deaf (DVAD) in this target group in Iran. To fill this knowledge gap, deaf living in Iranwere selected as the target group to assess their views on DVAD. This study is implemented in the socio-ecological approach framework to assess the impacts of individual characteristics, interpersonal relationships, community, and society components on DVAD. Semi-structured interviews with the Iranian deaf and Content analysis are used to find the participants’ point of view on DVAD, its risk factors, and the reduction approach to DVAD. The main purpose is to obtain information about participants' views on the subject. The findings can be used to improve culturally safe social work knowledge and practices with a bottom-up approach to reduce DV and increase their well-being. Therefore, this research can have important effects on the sustainable development of services and supports the welfare and inclusion of the deaf.

Keywords: domestic violence, Iranian deaf, social work, content analysis

Procedia PDF Downloads 111

Authors: Ariba Siddiqui, Amber Khan

Abstract:

The need for bio-implantable devices in the field of medical sciences has been increasing day by day; however, the charging of these devices is a major issue. Batteries, a very common method of powering the implants, have a limited lifetime and bulky nature. Therefore, as a replacement of batteries, acoustic power transfer (APT) technology is being accepted as the most suitable technique to wirelessly power the medical implants in the present scenario. The basic model of APT consists of piezoelectric transducers that work on the principle of converse piezoelectric effect at the transmitting end and direct piezoelectric effect at the receiving end. This paper provides mechanistic insight into the parameters affecting the design and efficient working of acoustic power transfer systems. The optimum design considerations have been presented that will help to compress the size of the device and augment the intensity of the pressure wave. A COMSOL model of the PZT (Lead Zirconate Titanate) transducer was developed. The model was simulated and analyzed on a frequency spectrum. The simulation results displayed that the efficiency of these devices is strongly dependent on the frequency of operation, and a wrong choice of the operating frequency leads to the high absorption of acoustic field inside the tissue (medium), poor power strength, and heavy transducers, which in effect influence the overall configuration of the acoustic systems. Considering all the tradeoffs, the simulations were performed again by determining an optimum frequency (900 kHz) that resulted in the reduction of the transducer's thickness to 1.96 mm and augmented the power strength with an intensity of 432 W/m². Thus, the results obtained after the second simulation contribute to lesser attenuation, lightweight systems, high power intensity, and also comply with safety limits provided by the U.S Food and Drug Administration (FDA). It was also found that the chosen operating frequency enhances the directivity of the acoustic wave at the receiver side.

Keywords: acoustic power, bio-implantable, COMSOL, Lead Zirconate Titanate, piezoelectric, transducer

Procedia PDF Downloads 178

Authors: Sylvie Michel, Sylvie Gerbaix, Marc Bidan

Abstract:

Artificial intelligence (AI) can be held accountable for its detrimental impacts. This question gains heightened relevance given AI's pervasive reach across various domains, magnifying its power and potential. The expanding influence of AI raises fundamental ethical inquiries, primarily centering on biases, responsibility, and transparency. This encompasses discriminatory biases arising from algorithmic criteria or data, accidents attributed to autonomous vehicles or other systems, and the imperative of transparent decision-making. This article aims to stimulate reflection on AI accountability, denoting the necessity to elucidate the effects it generates. Accountability comprises two integral aspects: adherence to legal and ethical standards and the imperative to elucidate the underlying operational rationale. The objective is to initiate a reflection on the obstacles to this "accountability," facing the challenges of the complexity of artificial intelligence's system and its effects. Then, this article proposes to mobilize Edgar Morin's complex thought to encompass and face the challenges of this complexity. The first contribution is to point out the challenges posed by the complexity of A.I., with fractional accountability between a myriad of human and non-human actors, such as software and equipment, which ultimately contribute to the decisions taken and are multiplied in the case of AI. Accountability faces three challenges resulting from the complexity of the ethical issues combined with the complexity of AI. The challenge of the non-neutrality of algorithmic systems as fully ethically non-neutral actors is put forward by a revealing ethics approach that calls for assigning responsibilities to these systems. The challenge of the dilution of responsibility is induced by the multiplicity and distancing between the actors. Thus, a dilution of responsibility is induced by a split in decision-making between developers, who feel they fulfill their duty by strictly respecting the requests they receive, and management, which does not consider itself responsible for technology-related flaws. Accountability is confronted with the challenge of transparency of complex and scalable algorithmic systems, non-human actors self-learning via big data. A second contribution involves leveraging E. Morin's principles, providing a framework to grasp the multifaceted ethical dilemmas and subsequently paving the way for establishing accountability in AI. When addressing the ethical challenge of biases, the "hologrammatic" principle underscores the imperative of acknowledging the non-ethical neutrality of algorithmic systems inherently imbued with the values and biases of their creators and society. The "dialogic" principle advocates for the responsible consideration of ethical dilemmas, encouraging the integration of complementary and contradictory elements in solutions from the very inception of the design phase. Aligning with the principle of organizing recursiveness, akin to the "transparency" of the system, it promotes a systemic analysis to account for the induced effects and guides the incorporation of modifications into the system to rectify deviations and reintroduce modifications into the system to rectify its drifts. In conclusion, this contribution serves as an inception for contemplating the accountability of "artificial intelligence" systems despite the evident ethical implications and potential deviations. Edgar Morin's principles, providing a lens to contemplate this complexity, offer valuable perspectives to address these challenges concerning accountability.

Keywords: accountability, artificial intelligence, complexity, ethics, explainability, transparency, Edgar Morin

Procedia PDF Downloads 67

Authors: Behnaz Sohani, Sahand Shahalinezhad, Amir Rahmani, Aliyu Aliyu

Abstract:

Recently, medical imaging and specifically medical image processing is becoming one of the most dynamically developing areas of medical science. It has led to the emergence of new approaches in terms of the prevention, diagnosis, and treatment of various diseases. In the process of diagnosis of lung cancer, medical professionals rely on computed tomography (CT) scans, in which failure to correctly identify masses can lead to incorrect diagnosis or sampling of lung tissue. Identification and demarcation of masses in terms of detecting cancer within lung tissue are critical challenges in diagnosis. In this work, a segmentation system in image processing techniques has been applied for detection purposes. Particularly, the use and validation of a novel lung cancer detection algorithm have been presented through simulation. This has been performed employing CT images based on multilevel thresholding. The proposed technique consists of segmentation, feature extraction, and feature selection and classification. More in detail, the features with useful information are selected after featuring extraction. Eventually, the output image of lung cancer is obtained with 96.3% accuracy and 87.25%. The purpose of feature extraction applying the proposed approach is to transform the raw data into a more usable form for subsequent statistical processing. Future steps will involve employing the current feature extraction method to achieve more accurate resulting images, including further details available to machine vision systems to recognise objects in lung CT scan images.

Keywords: lung cancer detection, image segmentation, lung computed tomography (CT) images, medical image processing

Procedia PDF Downloads 103

Authors: Kalangi Rodrigo

Abstract:

The term Neuroecology elucidates the study of customizable variation in cognition and the brain. Subject marked the birth since 1980s, when researches began to apply methods of comparative evolutionary biology to cognitive processes and the underlying neural mechanisms of cognition. In Archaeology and Anthropology, we observe behaviors such as social learning skills, innovative feeding and foraging, tool use and social manipulation to determine the cognitive processes of ancient mankind. Depending on the brainstem size was used as a control variable, and phylogeny was controlled using independent contrasts. Both disciplines need to enriched with comparative literature and neurological experimental, behavioral studies among tribal peoples as well as primate groups which will lead the research to a potential end. Neuroecology examines the relations between ecological selection pressure and mankind or sex differences in cognition and the brain. The goal of neuroecology is to understand how natural law acts on perception and its neural apparatus. Furthermore, neuroecology will eventually lead both principal disciplines to Ethology, where human behaviors and social management studies from a biological perspective. It can be either ethnoarchaeological or prehistoric. Archaeology should adopt general approach of neuroecology, phylogenetic comparative methods can be used in the field, and new findings on the cognitive mechanisms and brain structures involved mating systems, social organization, communication and foraging. The contribution of neuroecology to archaeology and anthropology is the information it provides on the selective pressures that have influenced the evolution of cognition and brain structure of the mankind. It will shed a new light to the path of evolutionary studies including behavioral ecology, primate archaeology and cognitive archaeology.

Keywords: Neuroecology, Archaeology, Brain Evolution, Cognitive Archaeology

Procedia PDF Downloads 124

Authors: Imran Dayan, Ashiqul Khan

Abstract:

Internal corporate fraud, which is fraud carried out by internal stakeholders of a company, affects the well-being of the organisation just like its external counterpart. Even if such an act is carried out for the short-term benefit of a corporation, the act is ultimately harmful to the entity in the long run. Internal fraud is often carried out by relying upon aberrations from usual business processes. Business processes are the lifeblood of a company in modern managerial context. Such processes are developed and fine-tuned over time as a corporation grows through its life stages. Modern corporations have embraced technological innovations into their business processes, and Enterprise Resource Planning (ERP) systems being at the heart of such business processes is a testimony to that. Since ERP systems record a huge amount of data in their event logs, the logs are a treasure trove for anyone trying to detect any sort of fraudulent activities hidden within the day-to-day business operations and processes. This research utilises the ERP systems in place within corporations to assess the likelihood of prospective internal fraud through developing a framework for measuring the risks of fraud through Process Mining techniques and hence finds risky designs and loose ends within these business processes. This framework helps not only in identifying existing cases of fraud in the records of the event log, but also signals the overall riskiness of certain business processes, and hence draws attention for carrying out a redesign of such processes to reduce the chance of future internal fraud while improving internal control within the organisation. The research adds value by applying the concepts of Process Mining into the analysis of data from modern day applications of business process records, which is the ERP event logs, and develops a framework that should be useful to internal stakeholders for strengthening internal control as well as provide external auditors with a tool of use in case of suspicion. The research proves its usefulness through a few case studies conducted with respect to big corporations with complex business processes and an ERP in place.

Keywords: enterprise resource planning, fraud risk framework, internal corporate fraud, process mining

Procedia PDF Downloads 340

Authors: Edna T. Bernabe, Joshua Bilolo, Sheila Mae Artillero, Catlicia Joy Caseda, Liezel Once, Donne Ynah Grace Quirante

Abstract:

Internal communication is significant for an organization to function to its full extent. A strategic communication plan builds an organization’s structure and makes it more systematic. Information is a vital part of communication inside the organization as this lays every possible outcome—be it positive or negative. It is, therefore, imperative to assess the communication structure of a particular organization to secure a better and harmonious communication environment in any organization. Thus, this research was intended to identify the internal communication channels used in Polytechnic University of the Philippines-College of Communication (PUP-COC) as an organization, to identify the flow of information specifically in downward, upward, and horizontal communication, to assess the accuracy, consistency, and timeliness of its internal communication channels; and to come up with a proposed strategic communication plan of information dissemination to improve the existing communication flow in the college. The researchers formulated a framework from Input-Throughout-Output-Feedback-Goal of General System Theory and gathered data to assess the PUP-COC’s internal communication. The communication model links the objectives of the study to know the internal organization of the college. The qualitative approach and case study as the tradition of inquiry were used to gather deeper understanding of the internal organizational communication in PUP-COC, using Interview, as the primary methods for the study. This was supported with a quantitative data which were gathered through survey from the students of the college. The researchers interviewed 17 participants: the College dean, the 4 chairpersons of the college departments, the 11 faculty members and staff, and the acting Student Council president. An interview guide and a standardized questionnaire were formulated as instruments to generate the data. After a thorough analysis of the study, it was found out that two-way communication flow exists in PUP-COC. The type of communication channel the internal stakeholders use varies as to whom a particular person is communicating with. The members of the PUP-COC community also use different types of communication channels depending on the flow of communication being used. Moreover, the most common types of internal communication are the letters and memoranda for downward communication, while letters, text messages, and interpersonal communication are often used in upward communication. Various forms of social media have been found out to be of use in horizontal communication. Accuracy, consistency, and timeliness play a significant role in information dissemination within the college. However, some problems have also been found out in the communication system. The most common problem are the delay in the dissemination of memoranda and letters and the uneven distribution of information and instruction to faculty, staff, and students. This has led the researchers to formulate a strategic communication plan which aims to propose strategies that will solve the communication problems that are being experienced by the internal stakeholders.

Keywords: communication plan, downward communication, internal communication, upward communication

Procedia PDF Downloads 522

Authors: Abhipsa Mohanty, Harit Jha

Abstract:

The world's energy demands are continuing to rise, resulting in a worldwide energy crisis and environmental pollution. Because of finite, declining supply and environmental damage, reliance on fossil fuels is unsustainable. As a result, experts are concentrating on alternative, renewable, and carbon-free energy sources. Energy sources that are both environmentally and economically sustainable are required. Microbial fuel cells (MFCs) have recently received a lot of attention due to their low operating temperatures and ability to use a variety of biodegradable substrates as fuel. There are single-chamber MFCs as well as traditional MFCs with anode and cathode compartments. Bioelectricity is produced when microorganisms actively catabolize substrate. MFCs can be used as a power source in small devices like biosensors. Understanding of its components, microbiological processes, limiting variables, and construction designs in MFC systems must be simplified, and large-scale systems must be developed for them to be cost-effective as well as increase electricity production. The purpose of this research was to review current microbiology knowledge in the field of electricity. The manufacturing process, the materials, and procedures utilized to construct the technology, as well as the applications of MFC technology, are all covered.

Keywords: bio-electricity, exoelectrogenic bacteria, microbial fuel cells, soil microorganisms

Procedia PDF Downloads 96

Authors: Chia-Feng Lu, Yuh-Jen Wang, Yu-Te Wu, Sui-Hing Yan

Abstract:

This study aimed at investigating whether the functional brain networks constructed using the initial EEG (obtained when patients first visited hospital) can be correlated with the progression of cognitive decline calculated as the changes of mini-mental state examination (MMSE) scores between the latest and initial examinations. We integrated the time–frequency cross mutual information (TFCMI) method to estimate the EEG functional connectivity between cortical regions, and the network analysis based on graph theory to investigate the organization of functional networks in aMCI. Our finding suggested that higher integrated functional network with sufficient connection strengths, dense connection between local regions, and high network efficiency in processing information at the initial stage may result in a better prognosis of the subsequent cognitive functions for aMCI. In conclusion, the functional connectivity can be a useful biomarker to assist in prediction of cognitive declines in aMCI.

Keywords: cognitive decline, functional connectivity, MCI, MMSE

Procedia PDF Downloads 389

Authors: Mansoureh Zangiabadi, Shamil Velji, Rajendra Kelkar, Neal Wade, Volker Pickert

Abstract:

The EU has set itself a long-term goal of reducing greenhouse gas emissions by 80-95% of the 1990 levels by 2050 as set in the Energy Roadmap 2050. This paper reports on the European Union H2020 funded E-Lobster project which demonstrates tools and technologies, software and hardware in integrating the grid distribution, and the railway power systems with power electronics technologies (Smart Soft Open Point - sSOP) and local energy storage. In this context this paper describes the existing policies and regulatory frameworks of the energy market at European level with a special focus then at National level, on the countries where the members of the consortium are located, and where the demonstration activities will be implemented. By taking into account the disciplinary approach of E-Lobster, the main policy areas investigated includes electricity, energy market, energy efficiency, transport and smart cities. Energy storage will play a key role in enabling the EU to develop a low-carbon electricity system. In recent years, Energy Storage System (ESSs) are gaining importance due to emerging applications, especially electrification of the transportation sector and grid integration of volatile renewables. The need for storage systems led to ESS technologies performance improvements and significant price decline. This allows for opening a new market where ESSs can be a reliable and economical solution. One such emerging market for ESS is R+G management which will be investigated and demonstrated within E-Lobster project. The surplus of energy in one type of power system (e.g., due to metro braking) might be directly transferred to the other power system (or vice versa). However, it would usually happen at unfavourable instances when the recipient does not need additional power. Thus, the role of ESS is to enhance advantages coming from interconnection of the railway power systems and distribution grids by offering additional energy buffer. Consequently, the surplus/deficit of energy in, e.g. railway power systems, is not to be immediately transferred to/from the distribution grid but it could be stored and used when it is really needed. This will assure better energy management exchange between the railway power systems and distribution grids and lead to more efficient loss reduction. In this framework, to identify the existing policies and regulatory frameworks is crucial for the project activities and for the future development of business models for the E-Lobster solutions. The projections carried out by the European Commission, the Member States and stakeholders and their analysis indicated some trends, challenges, opportunities and structural changes needed to design the policy measures to provide the appropriate framework for investors. This study will be used as reference for the discussion in the envisaged workshops with stakeholders (DSOs and Transport Managers) in the E-Lobster project.

Keywords: light railway, electrical distribution network, Electrical Energy Storage, policy

Procedia PDF Downloads 140

Authors: Yoftahe Nigussie

Abstract:

This research explores the implementation of a vapor absorption refrigeration system (VARS) in mini-bus cars to enhance air conditioning efficiency. The conventional vapor compression refrigeration system (VCRS) in vehicles relies on mechanical work from the engine, leading to increased fuel consumption. The proposed VARS aims to utilize waste heat and exhaust gas from the internal combustion engine to cool the mini-bus cabin, thereby reducing fuel consumption and atmospheric pollution. The project involves two models: Model 1, a two-fluid vapor absorption system (VAS), and Model 2, a three-fluid VAS. Model 1 uses ammonia (NH₃) and water (H₂O) as refrigerants, where water absorbs ammonia rapidly, producing a cooling effect. The absorption cycle operates on the principle that absorbing ammonia in water decreases vapor pressure. The ammonia-water solution undergoes cycles of desorption, condensation, expansion, and absorption, facilitated by a generator, condenser, expansion valve, and absorber. The objectives of this research include reducing atmospheric pollution, minimizing air conditioning maintenance costs, lowering capital costs, enhancing fuel economy, and eliminating the need for a compressor. The comparison between vapor absorption and compression systems reveals advantages such as smoother operation, fewer moving parts, and the ability to work at lower evaporator pressures without affecting the Coefficient of Performance (COP). The proposed VARS demonstrates potential benefits for mini-bus air conditioning systems, providing a sustainable and energy-efficient alternative. By utilizing waste heat and exhaust gas, this system contributes to environmental preservation while addressing economic considerations for vehicle owners. Further research and development in this area could lead to the widespread adoption of vapor absorption technology in automotive air conditioning systems.

Keywords: room, zone, space, thermal resistance

Procedia PDF Downloads 77

Authors: Aleksandra Szurlej-Kielanska, Lucyna Pilacka, Dariusz Górecki

Abstract:

The dynamic development of wind energy requires the simultaneous implementation of effective systems minimizing the risk of collisions between birds and wind turbines. Wind turbines are installed in more and more challenging locations, often close to the natural environment of birds. More and more countries and organizations are defining guidelines for the necessary functionality of such systems. The minimum bird detection distance, trajectory tracking, and shutdown time are key factors in eliminating collisions. Since 2020, we have continued the survey on the validation of the subsequent version of the BPS detection and reaction system. Bird protection system (BPS) is a fully automatic camera system which allows one to estimate the distance of the bird to the turbine, classify its size and autonomously undertake various actions depending on the bird's distance and flight path. The BPS was installed and tested in a real environment at a wind turbine in northern Poland and Central Spain. The performed validation showed that at a distance of up to 300 m, the BPS performs at least as well as a skilled ornithologist, and large bird species are successfully detected from over 600 m. In addition, data collected by BPS systems installed in Spain showed that 60% of the detections of all birds of prey were from individuals approaching the turbine, and these detections meet the turbine shutdown criteria. Less than 40% of the detections of birds of prey took place at wind speeds below 2 m/s while the turbines were not working. As shown by the analysis of the data collected by the system over 12 months, the system classified the improved size of birds with a wingspan of more than 1.1 m in 90% and the size of birds with a wingspan of 0.7 - 1 m in 80% of cases. The collected data also allow the conclusion that some species keep a certain distance from the turbines at a wind speed of over 8 m/s (Aquila sp., Buteo sp., Gyps sp.), but Gyps sp. and Milvus sp. remained active at this wind speed on the tested area. The data collected so far indicate that BPS is effective in detecting and stopping wind turbines in response to the presence of birds of prey with a wingspan of more than 1 m.

Keywords: protecting birds, birds monitoring, wind farms, green energy, sustainable development

Procedia PDF Downloads 79

Authors: Ankit Sharma, Mudit Sachan, Anurag Prakash

Abstract:

Rapid growth in data acquisition technologies through drones, have led to advances and interests in collecting high-resolution images of geological fields. Being advantageous in capturing high volume of data in short flights, a number of challenges have to overcome for efficient analysis of this data, especially while data acquisition, image interpretation and processing. We introduce a method that allows effective mapping of geological fields using photogrammetric data of surfaces, drainage area, water bodies etc, which will be captured by airborne vehicles like UAVs, we are not taking satellite images because of problems in adequate resolution, time when it is captured may be 1 yr back, availability problem, difficult to capture exact image, then night vision etc. This method includes advanced automated image interpretation technology and human data interaction to model structures and. First Geological structures will be detected from the primary photographic dataset and the equivalent three dimensional structures would then be identified by digital elevation model. We can calculate dip and its direction by using the above information. The structural map will be generated by adopting a specified methodology starting from choosing the appropriate camera, camera’s mounting system, UAVs design ( based on the area and application), Challenge in air borne systems like Errors in image orientation, payload problem, mosaicing and geo referencing and registering of different images to applying DEM. The paper shows the potential of using our method for accurate and efficient modeling of geological structures, capture particularly from remote, of inaccessible and hazardous sites.

Keywords: digital elevation model, mapping, photogrammetric data analysis, geological structures

Procedia PDF Downloads 689

Authors: Aleksandra Czubek

Abstract:

As AI systems increasingly shape content creation, existing copyright frameworks face significant challenges in determining liability for AI-generated outputs. Current legal discussions largely focus on who bears responsibility for infringing works, be it developers, users, or entities benefiting from AI outputs. This paper introduces a novel concept of algorithmic obligations, proposing that AI developers be subject to proactive duties that ensure their models prevent copyright infringement before it occurs. Building on principles of obligations law traditionally applied to human actors, the paper suggests a shift from reactive enforcement to proactive legal requirements. AI developers would be legally mandated to incorporate copyright-aware mechanisms within their systems, turning optional safeguards into enforceable standards. These obligations could vary in implementation across international, EU, UK, and U.S. legal frameworks, creating a multi-jurisdictional approach to copyright compliance. This paper explores how the EU’s existing copyright framework, exemplified by the Copyright Directive (2019/790), could evolve to impose a duty of foresight on AI developers, compelling them to embed mechanisms that prevent infringing outputs. By drawing parallels to GDPR’s “data protection by design,” a similar principle could be applied to copyright law, where AI models are designed to minimize copyright risks. In the UK, post-Brexit text and data mining exemptions are seen as pro-innovation but pose risks to copyright protections. This paper proposes a balanced approach, introducing algorithmic obligations to complement these exemptions. AI systems benefiting from text and data mining provisions should integrate safeguards that flag potential copyright violations in real time, ensuring both innovation and protection. In the U.S., where copyright law focuses on human-centric works, this paper suggests an evolution toward algorithmic due diligence. AI developers would have a duty similar to product liability, ensuring that their systems do not produce infringing outputs, even if the outputs themselves cannot be copyrighted. This framework introduces a shift from post-infringement remedies to preventive legal structures, where developers actively mitigate risks. The paper also breaks new ground by addressing obligations surrounding the training data of large language models (LLMs). Currently, training data is often treated under exceptions such as the EU’s text and data mining provisions or U.S. fair use. However, this paper proposes a proactive framework where developers are obligated to verify and document the legal status of their training data, ensuring it is licensed or otherwise cleared for use. In conclusion, this paper advocates for an obligations-centered model that shifts AI-related copyright law from reactive litigation to proactive design. By holding AI developers to a heightened standard of care, this approach aims to prevent infringement at its source, addressing both the outputs of AI systems and the training processes that underlie them.

Keywords: ip, technology, copyright, data, infringement, comparative analysis

Procedia PDF Downloads 23

Authors: Kumara Jayapathma J. H. M. S. S., Dampegama S. D. P. J.

Abstract:

Lands are valuable & limited resource which constantly changes with the growth of the population. An efficient and good land management system is essential to avoid conflicts associated with lands. This paper aims to design the prototype model of a Mobile GIS Land use and Land Information System in real-time. Homagama Divisional Secretariat Division situated in the western province of Sri Lanka was selected as the study area. The prototype model was developed after reviewing related literature. The methodology was consisted of designing and modeling the prototype model into an application running on a mobile platform. The system architecture mainly consists of a Google mapping app for real-time updates with firebase support tools. Thereby, the method of implementation consists of front-end and back-end components. Software tools used in designing applications are Android Studio with JAVA based on GeoJSON File structure. Android Studio with JAVA in GeoJSON File Synchronize to Firebase was found to be the perfect mobile solution for continuously updating Land use and Land Information System (LIS) in real-time in the present scenario. The mobile-based land use and LIS developed in this study are multiple user applications catering to different hierarchy levels such as basic users, supervisory managers, and database administrators. The benefits of this mobile mapping application will help public sector field officers with non-GIS expertise to overcome the land use planning challenges with land use updated in real-time.

Keywords: Android, Firebase, GeoJSON, GIS, JAVA, JSON, LIS, Mobile GIS, real-time, REST API

Procedia PDF Downloads 236

Authors: Nahid Banihashemi

Abstract:

An emerging important area of the life sciences is systems biology, which involves understanding the integrated behavior of large numbers of components interacting via non-linear reaction terms. A centrally important problem in this area is an understanding of the co-metabolism of protein and carbohydrate, as it has been clearly demonstrated that the ratio of these metabolites in diet is a major determinant of obesity and related chronic disease. In this regard, we have considered a systems biology model for the co-metabolism of carbon and nitrogen in colonies of the fungus Mucor mucedo. Oscillations are an important diagnostic of underlying dynamical processes of this model. The maintenance of specific patterns of oscillation and its relation to the robustness of this system are the important issues which have been targeted in this paper. In this regard, parametric sensitivity approach as a theoretical approach has been considered for the analysis of the robustness of this model. As a result, the parameters of the model which produce the largest sensitivities have been identified. Furthermore, the largest changes that can be made in each parameter of the model without losing the oscillations in biomass production have been computed. The results are obtained from the implementation of parametric sensitivity analysis in Matlab.

Keywords: system biology, parametric sensitivity analysis, robustness, carbon and nitrogen co-metabolism, Mucor mucedo

Procedia PDF Downloads 333

Authors: Vincent Andrew Cappellano

Abstract:

In the early phases of critical infrastructure system design, translating distributed computing requirements to an architecture has risk given the multitude of approaches (e.g., cloud, edge, fog). In many systems, a single requirement for system uptime / availability is used to encompass the system’s intended operations. However, when architected systems may perform to those availability requirements only during normal operations and not during component failure, or during outages caused by adversary attacks on critical infrastructure (e.g., physical, cyber). System designers lack a structured method to evaluate availability requirements against candidate system architectures through deep degradation scenarios (i.e., normal ops all the way down to significant damage of communications or physical nodes). This increases risk of poor selection of a candidate architecture due to the absence of insight into true performance for systems that must operate as a piece of critical infrastructure. This research effort proposes a process to analyze critical infrastructure system availability requirements and a candidate set of systems architectures, producing a metric assessing these architectures over a spectrum of degradations to aid in selecting appropriate resilient architectures. To accomplish this effort, a set of simulation and evaluation efforts are undertaken that will process, in an automated way, a set of sample requirements into a set of potential architectures where system functions and capabilities are distributed across nodes. Nodes and links will have specific characteristics and based on sampled requirements, contribute to the overall system functionality, such that as they are impacted/degraded, the impacted functional availability of a system can be determined. A machine learning reinforcement-based agent will structurally impact the nodes, links, and characteristics (e.g., bandwidth, latency) of a given architecture to provide an assessment of system functional uptime/availability under these scenarios. By varying the intensity of the attack and related aspects, we can create a structured method of evaluating the performance of candidate architectures against each other to create a metric rating its resilience to these attack types/strategies. Through multiple simulation iterations, sufficient data will exist to compare this availability metric, and an architectural recommendation against the baseline requirements, in comparison to existing multi-factor computing architectural selection processes. It is intended that this additional data will create an improvement in the matching of resilient critical infrastructure system requirements to the correct architectures and implementations that will support improved operation during times of system degradation due to failures and infrastructure attacks.

Keywords: architecture, resiliency, availability, cyber-attack

Procedia PDF Downloads 115

Authors: Ashish Kumar, Kaptan Singh, Amit Saxena

Abstract:

Today, it is believed that crimes have the greatest impact on a person's ability to progress financially and personally. Identifying places where individuals shouldn't go is crucial for preventing crimes and is one of the key considerations. As society and technologies have advanced significantly, so have crimes and the harm they wreak. When there is a concentration of people in one place and changes happen quickly, it is even harder to prevent. Because of this, many crime prevention strategies have been embraced as a component of the development of smart cities in numerous cities. However, crimes can occur anywhere; all that is required is to identify the pattern of their occurrences, which will help to lower the crime rate. In this paper, an analysis related to crime has been done; information related to crimes is collected from all over India that can be accessed from anywhere. The purpose of this paper is to investigate the relationship between several factors and India's crime rate. The review has covered information related to every state of India and their associated regions of the period going in between 2001- 2014. However various classes of violations have a marginally unique scope over the years.

Keywords: K-nearest neighbor, random forest, decision tree, pre-processing

Procedia PDF Downloads 98

Authors: Agoston Restas

Abstract:

Introduction: This paper describes many initiatives and shows also practical examples which happened recently using Unmanned Aerial Systems (UAS) to support disaster management. Since the operation of manned aircraft at disasters is usually not only expensive but often impossible to use as well, in many cases managers fail to use the aerial activity. UAS can be an alternative moreover cost-effective solution for supporting disaster management. Methods: This article uses thematic division of UAS applications; it is based on two key elements, one of them is the time flow of managing disasters, other is its tactical requirements. Logically UAS can be used like pre-disaster activity, activity immediately after the occurrence of a disaster and the activity after the primary disaster elimination. Paper faces different disasters, like dangerous material releases, floods, earthquakes, forest fires and human-induced disasters. Research used function analysis, practical experiments, mathematical formulas, economic analysis and also expert estimation. Author gathered international examples and used own experiences in this field as well. Results and discussion: An earthquake is a rapid escalating disaster, where, many times, there is no other way for a rapid damage assessment than aerial reconnaissance. For special rescue teams, the UAS application can help much in a rapid location selection, where enough place remained to survive for victims. Floods are typical for a slow onset disaster. In contrast, managing floods is a very complex and difficult task. It requires continuous monitoring of dykes, flooded and threatened areas. UAS can help managers largely keeping an area under observation. Forest fires are disasters, where the tactical application of UAS is already well developed. It can be used for fire detection, intervention monitoring and also for post-fire monitoring. In case of nuclear accident or hazardous material leakage, UAS is also a very effective or can be the only one tool for supporting disaster management. Paper shows some efforts using UAS to avoid human-induced disasters in low-income countries as part of health cooperation.

Keywords: disaster management, floods, forest fires, Unmanned Aerial Systems

Procedia PDF Downloads 242

Authors: Kanogkan Leerojanaprapa

Abstract:

Textile and garment industry is used to a major exporting industry of Thailand. According to lacking of the nation's price-competitiveness by stopping the EU's GSP (Generalised Scheme of Preferences) and ‘Nationwide Minimum Wage Policy’ that Thailand’s employers must pay all employees at least 300 baht (about $10) a day, the supply chains of the Thai textile and garment industry is affected and need to be reformed. Therefore, either Thai textile or garment industry will be existed or not would be concerned. This is also challenged for the government to decide which industries should be promoted the future industries of Thailand. Recently Thai government launch The Cluster-based Special Economic Development Zones Policy for promoting business cluster (effect on September 16, 2015). They define a cluster as the concentration of interconnected businesses and related institutions that operate within the same geographic areas and textiles and garment is one of target industrial clusters and 9 provinces are targeted (Bangkok, Kanchanaburi, Nakhon Pathom, Ratchaburi, Samut Sakhon, Chonburi, Chachoengsao, Prachinburi, and Sa Kaeo). The cluster zone are defined to link west-east corridor connected to manufacturing source in Cambodia and Mynmar to Bangkok where are promoted to be design, sourcing, and trading hub. The Thai government will provide tax and non-tax incentives for targeted industries within the clusters and expects these businesses are scattered to where they can get the most benefit which will identify future industrial cluster. This research will show the difference between the current cluster and future cluster following the target provinces of the textile and garment. The current cluster is analysed from secondary data. The four characteristics of the numbers of plants in Spinning, weaving and finishing of textiles, Manufacture of made-up textile articles, except apparel, Manufacture of knitted and crocheted fabrics, and Manufacture of other textiles, not elsewhere classified in particular 77 provinces (in total) are clustered by K-means cluster analysis and Hierarchical Cluster Analysis. In addition, the cluster can be confirmed and showed which variables contribute the most to defined cluster solution with ANOVA test. The results of analysis can identify 22 provinces (which the textile or garment plants are located) into 3 clusters. Plants in cluster 1 tend to be large numbers of plants which is only Bangkok, Next plants in cluster 2 tend to be moderate numbers of plants which are Samut Prakan, Samut Sakhon and Nakhon Pathom. Finally plants in cluster 3 tend to be little numbers of plants which are other 18 provinces. The same methodology can be implemented in other industries for future study.

Keywords: ANOVA, hierarchical cluster analysis, industrial clusters, K -means cluster analysis, textile and garment industry

Procedia PDF Downloads 217

Authors: Zohreh Moghaddas, Morteza Yazdani, Farhad Hosseinzadeh

Abstract:

Nowadays, data envelopment analysis (DEA) models featuring network structures have gained widespread usage for evaluating the performance of production systems and activities (Decision-Making Units (DMUs)) across diverse fields. By examining the relationships between the internal stages of the network, these models offer valuable insights to managers and decision-makers regarding the performance of each stage and its impact on the overall network. To further empower system decision-makers, the inverse data envelopment analysis (IDEA) model has been introduced. This model allows the estimation of crucial information for estimating parameters while keeping the efficiency score unchanged or improved, enabling analysis of the sensitivity of system inputs or outputs according to managers' preferences. This empowers managers to apply their preferences and policies on resources, such as inputs and outputs, and analyze various aspects like production, resource allocation processes, and resource efficiency enhancement within the system. The results obtained can be instrumental in making informed decisions in the future. The top result of this study is an analysis of infeasibility and incorrect estimation that may arise in the theory and application of the inverse model of data envelopment analysis with network structures. By addressing these pitfalls, novel protocols are proposed to circumvent these shortcomings effectively. Subsequently, several theoretical and applied problems are examined and resolved through insightful case studies.

Keywords: inverse models of data envelopment analysis, series network, estimation of inputs and outputs, efficiency, resource allocation, sensitivity analysis, infeasibility

Procedia PDF Downloads 57

Authors: Farzaneh Bayat

Abstract:

Successful and effective presence in regional and global markets along with optimal use of available utilities and proper utilization of new sources for offering desirable services based on customer satisfaction is inevitable. Commitment has a significant role in offering optimal services. Offering high quality job and desirable services to the customers are personnel’s commitment. Thus, Shiraz Chamran Hospital which is affiliated with Shiraz Medical School and is one of the orthopedic poles in southern Iran was studied. This hospital has 750 personnel and physicians which a sample of 200 of them were chosen as the statistic society for a 5 month period from June to November 2009. Main variables in this decision are: responsibility and responsiveness, job security, team work, task autonomy, gradation opportunity, information sharing, payments and commitment. The study approach is descriptive-correlative. With applied and segmental nature of the tests and statistic analysis, the 7 hypotheses were approved with 95% of certainty.

Keywords: commitment, information sharing, responsibility and responsiveness, job security, task autonomy

Procedia PDF Downloads 345

Authors: Shahad Nagoor, Lucy Hederman, Kevin Koidl, Annalina Caputo

Abstract:

Doctors’ notes reflect their impressions, attitudes, clinical sense, and opinions about patients’ conditions and progress, and other information that is essential for doctors’ daily clinical decisions. Despite their value, clinical notes are insufficiently researched within the language processing community. Automatically extracting information from unstructured text data is known to be a difficult task as opposed to dealing with structured information such as vital physiological signs, images, and laboratory results. The aim of this research is to investigate how Natural Language Processing (NLP) techniques and machine learning techniques applied to clinician notes can assist in doctors’ decision-making in Intensive Care Unit (ICU) for coronavirus disease 2019 (COVID-19) patients. The hypothesis is that clinical outcomes like survival or mortality can be useful in influencing the judgement of clinical sentiment in ICU clinical notes. This paper introduces two contributions: first, we introduce COVID_ICU_BERT, a fine-tuned version of clinical transformer models that can reliably predict clinical sentiment for notes of COVID patients in the ICU. We train the model on clinical notes for COVID-19 patients, a type of notes that were not previously seen by clinicalBERT, and Bio_Discharge_Summary_BERT. The model, which was based on clinicalBERT achieves higher predictive accuracy (Acc 93.33%, AUC 0.98, and precision 0.96 ). Second, we perform data augmentation using clinical contextual word embedding that is based on a pre-trained clinical model to balance the samples in each class in the data (survived vs. deceased patients). Data augmentation improves the accuracy of prediction slightly (Acc 96.67%, AUC 0.98, and precision 0.92 ).

Keywords: BERT fine-tuning, clinical sentiment, COVID-19, data augmentation

Procedia PDF Downloads 214

Authors: Hamid Saremi, Shida Hanafi

Abstract:

In an age of technology and economics, human capital has important and axial role in the organization and human resource accounting has a wide perception to key resources of organization i.e. human resources. Human resources accounting is new branch of accounting that has Short-lived and generally deals to a range of policies and measures that are related to various aspects of human resources and It gives importance to an organization's most important asset is its human resources and human resource management is the key to success in an organization and to achieve this important matter must review and evaluation of human resources data be with knowledge of accounting based on empirical studies and methods of measurement and reporting of human resources accounting information. Undoubtedly human resource management without information cannot be done and take decision and human resources accounting is practical way to inform the decision makers who are committed to harnessing human resources,, human resources accounting with applying accounting principles in the organization and is with conducting basic research on the extent of the of human resources accounting information" effect of employees' personal performance. In human resource accounting analysis and criteria and valuation of cost and manpower valuating is as the main resource in each Institute. Protection of human resources is a process that according to human resources accounting is for organization profitability. In fact, this type of accounting can be called as a major source in measurement and trends of costs and human resources valuation in each institution. What is the economic value of such assets? What is the amount of expenditures for education and training of professional individuals to value in asset account? What amount of funds spent should be considered as lost opportunity cost? In this paper, according to the literature of human resource accounting we have studied the human resources matter and its objectives and topic of the importance of human resource valuation on employee performance review and method of reporting of human resources according to different models.

Keywords: human resources, human resources, accounting, human capital, human resource management, valuation and cost of human resources, employees, performance, organization

Procedia PDF Downloads 552