Search results for: binary decision diagram
2695 An Output Oriented Super-Efficiency Model for Considering Time Lag Effect
Authors: Yanshuang Zhang, Byungho Jeong
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There exists some time lag between the consumption of inputs and the production of outputs. This time lag effect should be considered in calculating efficiency of decision making units (DMU). Recently, a couple of DEA models were developed for considering time lag effect in efficiency evaluation of research activities. However, these models can’t discriminate efficient DMUs because of the nature of basic DEA model in which efficiency scores are limited to ‘1’. This problem can be resolved a super-efficiency model. However, a super efficiency model sometimes causes infeasibility problem. This paper suggests an output oriented super-efficiency model for efficiency evaluation under the consideration of time lag effect. A case example using a long term research project is given to compare the suggested model with the MpO modelKeywords: DEA, Super-efficiency, Time Lag, research activities
Procedia PDF Downloads 6582694 Toward Indoor and Outdoor Surveillance using an Improved Fast Background Subtraction Algorithm
Authors: El Harraj Abdeslam, Raissouni Naoufal
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The detection of moving objects from a video image sequences is very important for object tracking, activity recognition, and behavior understanding in video surveillance. The most used approach for moving objects detection / tracking is background subtraction algorithms. Many approaches have been suggested for background subtraction. But, these are illumination change sensitive and the solutions proposed to bypass this problem are time consuming. In this paper, we propose a robust yet computationally efficient background subtraction approach and, mainly, focus on the ability to detect moving objects on dynamic scenes, for possible applications in complex and restricted access areas monitoring, where moving and motionless persons must be reliably detected. It consists of three main phases, establishing illumination changes in variance, background/foreground modeling and morphological analysis for noise removing. We handle illumination changes using Contrast Limited Histogram Equalization (CLAHE), which limits the intensity of each pixel to user determined maximum. Thus, it mitigates the degradation due to scene illumination changes and improves the visibility of the video signal. Initially, the background and foreground images are extracted from the video sequence. Then, the background and foreground images are separately enhanced by applying CLAHE. In order to form multi-modal backgrounds we model each channel of a pixel as a mixture of K Gaussians (K=5) using Gaussian Mixture Model (GMM). Finally, we post process the resulting binary foreground mask using morphological erosion and dilation transformations to remove possible noise. For experimental test, we used a standard dataset to challenge the efficiency and accuracy of the proposed method on a diverse set of dynamic scenes.Keywords: video surveillance, background subtraction, contrast limited histogram equalization, illumination invariance, object tracking, object detection, behavior understanding, dynamic scenes
Procedia PDF Downloads 2562693 [Keynote Talk]: Aerodynamic Effects of Ice and Its Influences on Flight Characteristics of Low Speed Unmanned Aerial Vehicles
Authors: I. McAndrew, K. L. Witcher, E. Navarro
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This paper presents the theory and application of low speed flight for unmanned aerial vehicles when subjected to surface environmental conditions such as ice on the leading edge and upper surface. A model was developed and tested in a wind tunnel to see how theory compares with practice at various speed including take-off, landing and operational applications where head winds substantially alter parameters. Furthermore, a comparison is drawn with maned operations and how that this subject is currently under supported with accurate theory or knowledge for designers or operators to make informed decision or accommodate individual applications. The effects of ice formation for lift and drag are determined for a range of different angles of attacks.Keywords: aerodynamics, low speed flight, unmanned vehicles, environmental influences
Procedia PDF Downloads 4372692 Human Trafficking and Prostitution in Amsterdam
Authors: Isabel Roiz, Alejandra Cossio
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This essay will talk about the problems of forced prostitution, human trafficking, and sexual exploitation in the Netherlands. This work conveys information from different sources stating the numbers and statistics of human trafficking throughout Europe and the different types of sexual exploitation as well as the means used for coercing victims into this illegal net. The research aims to inform and compare the way this business is handled and the ways used by criminals to lure and retain victims in spite of the law. It also tries to compare the laws in the Netherlands and Sweden regarding prostitution affects the illegal migration problems and how they change the ways those who work as prostitutes are treated. The aim of the paper is to take all of these aspects into consideration and reach a decision of what laws would most beneficiate the victims.Keywords: human trafficking, prostitution, laws of migration, Amsterdam
Procedia PDF Downloads 3482691 Spatial Distribution of Heavy Metals in Khark Island-Iran Using Geographic Information System
Authors: Abbas Hani, Maryam Jassasizadeh
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The concentrations of Cd, Pb, and Ni were determined from 40 soil samples collected in surface soils of Khark Island. Geostatistic methods and GIS were used to identify heavy metal sources and their spatial pattern. Principal component analysis coupled with correlation between heavy metals showed that level of mentioned heavy metal was lower than the standard level. Then the data obtained from the soil analyzing were studied for the purposes of normal distribution. The best way of interior finding for cadmium and nickel was ordinary kriging and the best way of interpolation of lead was inverse distance weighted. The result of this study help us to understand heavy metals distribution and make decision for remediation of soil pollution.Keywords: geostatistics, ordinary kriging, heavy metals, GIS, Khark
Procedia PDF Downloads 1672690 The Use of AI to Measure Gross National Happiness
Authors: Riona Dighe
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This research attempts to identify an alternative approach to the measurement of Gross National Happiness (GNH). It uses artificial intelligence (AI), incorporating natural language processing (NLP) and sentiment analysis to measure GNH. We use ‘off the shelf’ NLP models responsible for the sentiment analysis of a sentence as a building block for this research. We constructed an algorithm using NLP models to derive a sentiment analysis score against sentences. This was then tested against a sample of 20 respondents to derive a sentiment analysis score. The scores generated resembled human responses. By utilising the MLP classifier, decision tree, linear model, and K-nearest neighbors, we were able to obtain a test accuracy of 89.97%, 54.63%, 52.13%, and 47.9%, respectively. This gave us the confidence to use the NLP models against sentences in websites to measure the GNH of a country.Keywords: artificial intelligence, NLP, sentiment analysis, gross national happiness
Procedia PDF Downloads 1192689 A Study of Classification Models to Predict Drill-Bit Breakage Using Degradation Signals
Authors: Bharatendra Rai
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Cutting tools are widely used in manufacturing processes and drilling is the most commonly used machining process. Although drill-bits used in drilling may not be expensive, their breakage can cause damage to expensive work piece being drilled and at the same time has major impact on productivity. Predicting drill-bit breakage, therefore, is important in reducing cost and improving productivity. This study uses twenty features extracted from two degradation signals viz., thrust force and torque. The methodology used involves developing and comparing decision tree, random forest, and multinomial logistic regression models for classifying and predicting drill-bit breakage using degradation signals.Keywords: degradation signal, drill-bit breakage, random forest, multinomial logistic regression
Procedia PDF Downloads 3522688 Ethnic and National Determinants in the Process of Building Peace in Afghanistan After the Withdrawal of Western Forces in 2021
Authors: Małgorzata Cichy
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Afghanistan is a source of conflicts that affect security on a global scale. The role of ethnic and national determinants in the peacebuilding process in this country remains an extremely important factor in this respect. Research methods include literature and data analysis (scientific literature, documents of governmental and non-governmental organizations, statistical data and media reports), institutional and legal analysis, as well as decision-making method. The main objective of the research is a comprehensive answer to the question of how ethnic and national factors affect the process of building peace in Afghanistan after 2021 and what impact it has on international security.Keywords: Afghanistan, pashtuns, peace, taliban
Procedia PDF Downloads 952687 Evolution of the Environmental Justice Concept
Authors: Zahra Bakhtiari
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This article explores the development and evolution of the concept of environmental justice, which has shifted from being dominated by white and middle-class individuals to a civil struggle by marginalized communities against environmental injustices. Environmental justice aims to achieve equity in decision-making and policy-making related to the environment. The concept of justice in this context includes four fundamental aspects: distribution, procedure, recognition, and capabilities. Recent scholars have attempted to broaden the concept of justice to include dimensions of participation, recognition, and capabilities. Focusing on all four dimensions of environmental justice is crucial for effective planning and policy-making to address environmental issues. Ignoring any of these aspects can lead to the failure of efforts and the waste of resources.Keywords: environmental justice, distribution, procedure, recognition, capabilities
Procedia PDF Downloads 932686 Autonomy in Pregnancy and Childbirth: The Next Frontier of Maternal Health Rights Advocacy
Authors: Alejandra Cardenas, Ona Flores, Fabiola Gretzinger
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Since the 1990s, legal strategies for the promotion and protection of maternal health rights have achieved significant gains. Successful litigation in courts around the world have shown that these rights can be judicially enforceable. Governments and international organizations have acknowledged the importance of a human rights-based approach to maternal mortality and morbidity, and obstetric violence has been recognized as a human rights issue. Despite the progress made, maternal mortality has worsened in some regions of the world, while progress has stagnated elsewhere, and mistreatment in maternal care is reported almost universally. In this context, issues of maternal autonomy and decision-making during pregnancy, labor, and delivery as a critical barrier to access quality maternal health have been largely overlooked. Indeed, despite the principles of autonomy and informed consent in medical interventions being well-established in international and regional norms, how they are applied particularly during childbirth and pregnancy remains underdeveloped. National and global legal standards and decisions related to maternal health were reviewed and analyzed to determine how maternal autonomy and decision-making during pregnancy, labor, and delivery have been protected (or not) by international and national courts. The results of this legal research and analysis lead to the conclusion that a few standards have been set by courts regarding pregnant people’s rights to make choices during pregnancy and birth; however, most undermine the agency of pregnant people. These decisions recognize obstetric violence and gender-based discrimination, but fail to protect pregnant people’s autonomy, privacy, and their right to informed consent. As current human rights standards stand today, maternal health is the only field in medicine and law in which informed consent can be overridden, and patients can be forced to submit to treatments against their will. Unconsented treatment and loss of agency during pregnancy and childbirth can have long-term physical and mental impacts, reduce satisfaction and trust in health systems, and may deter future health-seeking behaviors. This research proposes a path forward that focuses on the pregnant person as an independent agent, relying on the doctrine of self-determination during pregnancy and childbirth, which includes access to the necessary conditions to enable autonomy and choice throughout pregnancy and childbirth as a critical step towards our approaches to reduce maternal mortality, morbidity, and mistreatment, and realize the promise of access to quality maternal health as a human right.Keywords: autonomy in childbirth and pregnancy, choice, informed consent, jurisprudential analysis
Procedia PDF Downloads 522685 Rural Women in Serbia: Key Challenges in Enjoyment of Economic and Social Rights
Authors: Mirjana Dokmanovic
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In recent years, the disadvantaged and marginalised position of rural women in the Republic of Serbia has been recognised in a number of national strategies and policy papers. A number of measures have been adopted by the government aimed at economic empowerment of rural women and eliminating barriers to accessing decision making and economic and social opportunities. However, their implementation pace is still slow. The aim of the paper is to indicate the necessity of a comprehensive policy approach to eliminating discrimination against rural women that would include policy and financial commitments for enhancing agricultural and rural development as a whole, instead of taking fragmented measures targeting consequences instead of causes. The paper introduces main findings of the study of challenges, constraints, and opportunities of rural women in Serbia to enjoy their economic and social rights. The research methodology included the desk research and the qualitative analysis of the available data, statistics, policy papers, studies, and reports produced by the government, ministries and other governmental bodies, independent human rights bodies, and civil society organizations (CSOs). The findings of the study reveal that rural women are at great risk of poverty, particularly in remote areas, and when getting old or widowed. Young rural women working in agriculture are also in unfavorable position, as they do not have opportunities to enjoy their rights during pregnancy and maternity leave, childcare leave and leave due to the special care of a child. The study indicates that the main causes of their unfavorable position are related to the prevalent patriarchal surrounding and economic and social underdevelopment of rural areas in Serbia. Gender inequalities have been particularly present in accessing land and property rights, inheritance, education, social protection, healthcare, and decision making. Women living in the rural areas are exposed at high risk of discrimination in all spheres of public and private life that undermine their enjoyment of basic economic, social and cultural rights. The vulnerability of rural women to discrimination increases in cases of the intersectionality of other grounds of discrimination, such as disability, ethnicity, age, health condition and sexual discrimination. If they are victims of domestic violence, their experience lack of access to shelters and protection services. Despite the State’s recognition of the marginalized position of rural women, there is still a lack of a comprehensive policy approach to improving the economic and social position of rural women.Keywords: agricultural and rural development, care economy, discrimination against women, economic and social rights, feminization of poverty, Republic of Serbia, rural women
Procedia PDF Downloads 2612684 Gender and Sexual Education in Morocco
Authors: Zouhair Gassim
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The reconfiguration of representations of women's bodies as a "chest of pregnancies", the growing commitment of their bodies to the decision of pregnancies previously monopolized by men, the emergence of new practices of the bodies of men and women suggest that the borders between the masculine and the feminine in Morocco are moving. However, the persistence of sexual violence against girls/women indicates that these changes did not contribute to the lifting of the men's control over the bodies of women. This paper aims to analyze the lessons learned about sex education as a discourse related to the fabric of bodies in relation to sexuality in school in order to understand to what extent this institution contributes to the (re) production of gender inequalities. As a result, the educational discourse on sexuality still remains one of the spaces of resistance against gender equality and thus contributes to the (re) production of gender inequalities.Keywords: gender, sexual education, Morocco, educational system
Procedia PDF Downloads 1492683 Smart Structures for Cost Effective Cultural Heritage Preservation
Authors: Tamara Trček Pečak, Andrej Mohar, Denis Trček
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This article investigates the latest technological means, which deploy smart structures that are based on (advanced) wireless sensors technologies and ubiquitous computing in general in order to support the above mentioned decision making. Based on two years of in-field research experiences it gives their analysis for these kinds of purposes and provides appropriate architectures and architectural solutions. Moreover, the directions for future research are stated, because these technologies are currently the most promising ones to enable cost-effective preservation of cultural heritage not only in uncontrolled places, but also in general.Keywords: smart structures, wireless sensors, sensors networks, green computing, cultural heritage preservation, monitoring, cost effectiveness
Procedia PDF Downloads 4462682 Radar Track-based Classification of Birds and UAVs
Authors: Altilio Rosa, Chirico Francesco, Foglia Goffredo
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In recent years, the number of Unmanned Aerial Vehicles (UAVs) has significantly increased. The rapid development of commercial and recreational drones makes them an important part of our society. Despite the growing list of their applications, these vehicles pose a huge threat to civil and military installations: detection, classification and neutralization of such flying objects become an urgent need. Radar is an effective remote sensing tool for detecting and tracking flying objects, but scenarios characterized by the presence of a high number of tracks related to flying birds make especially challenging the drone detection task: operator PPI is cluttered with a huge number of potential threats and his reaction time can be severely affected. Flying birds compared to UAVs show similar velocity, RADAR cross-section and, in general, similar characteristics. Building from the absence of a single feature that is able to distinguish UAVs and birds, this paper uses a multiple features approach where an original feature selection technique is developed to feed binary classifiers trained to distinguish birds and UAVs. RADAR tracks acquired on the field and related to different UAVs and birds performing various trajectories were used to extract specifically designed target movement-related features based on velocity, trajectory and signal strength. An optimization strategy based on a genetic algorithm is also introduced to select the optimal subset of features and to estimate the performance of several classification algorithms (Neural network, SVM, Logistic regression…) both in terms of the number of selected features and misclassification error. Results show that the proposed methods are able to reduce the dimension of the data space and to remove almost all non-drone false targets with a suitable classification accuracy (higher than 95%).Keywords: birds, classification, machine learning, UAVs
Procedia PDF Downloads 2222681 Performing Marginality and Contestation of Ethnic Identity: Dynamics of Identity Politics in Assam, India
Authors: Hare Krishna Doley
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Drawing upon empirical data, this paper tries to examine how ethnic groups like Ahom, Moran, Motok, and Chutia creates and recreates ethnic boundaries while making claims for recognition as Scheduled Tribes (STs) under the Sixth Schedule of the Constitution of India, in the state of Assam. Underlying such claim is the distinct identity consciousness amongst these groups as they assert themselves originally as tribe drawing upon primordial elements. For them, tribal identity promises social justice and give credence to their claims of indigeneity while preserving their exclusivity within the multifarious society of Assam. Having complex inter-group relationships, these groups under study displays distinct as well as overlapping identities, which demonstrate fluidity of identities across groups while making claims for recognition. In this process, the binary of ‘us’ and ‘them’ are often constructed amongst these groups, which are in turn difficult to grasp as they share common historical linkages. This paper attempts to grapple with such complex relationships the studied groups and their assertion as distinct cultural entities while making ethnic boundaries on the basis of socio-cultural identities. Such claims also involve frequent negotiation with the Sate as well as with other ethnic groups, which further creates strife among indigenous groups for tribal identity. The paper argues that identity consciousnesses amongst groups have persisted since the introduction of resource distribution on ethnic lines; therefore, issues of exclusive ethnic identity in the state of Assam can be contextualised within the colonial and post-colonial politics of redrawing ethnic and spatial boundaries. Narrative of the ethnic leaders who are in the forefront of struggle for ST status revealed that it is not merely to secure preferential treatment, but it also encompasses entitlement to land and their socio-cultural identity as aboriginal. While noting the genesis of struggle by the ethnic associations for ST status, this paper will also delineate the interactions among ethnic groups and how the identity of tribe is being performed by them to be included in the official categories of ST.Keywords: ethnic, identity, sixth schedule, tribe
Procedia PDF Downloads 2022680 Credit Risk Evaluation of Dairy Farming Using Fuzzy Logic
Authors: R. H. Fattepur, Sameer R. Fattepur, D. K. Sreekantha
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Dairy Farming is one of the key industries in India. India is the leading producer and also the consumer of milk, milk-based products in the world. In this paper, we have attempted to the replace the human expert system and to develop an artificial expert system prototype to increase the speed and accuracy of decision making dairy farming credit risk evaluation. Fuzzy logic is used for dealing with uncertainty, vague and acquired knowledge, fuzzy rule base method is used for representing this knowledge for building an effective expert system.Keywords: expert system, fuzzy logic, knowledge base, dairy farming, credit risk
Procedia PDF Downloads 3622679 Terraria AI: YOLO Interface for Decision-Making Algorithms
Authors: Emmanuel Barrantes Chaves, Ernesto Rivera Alvarado
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This paper presents a method to enable agents for the Terraria game to evaluate algorithms commonly used in general video game artificial intelligence competitions. The usage of the ‘You Only Look Once’ model in the first layer of the process obtains information from the screen, translating this information into a video game description language known as “Video Game Description Language”; the agents take that as input to make decisions. For this, the state-of-the-art algorithms were tested and compared; Monte Carlo Tree Search and Rolling Horizon Evolutionary; in this case, Rolling Horizon Evolutionary shows a better performance. This approach’s main advantage is that a VGDL beforehand is unnecessary. It will be built on the fly and opens the road for using more games as a framework for AI.Keywords: AI, MCTS, RHEA, Terraria, VGDL, YOLOv5
Procedia PDF Downloads 962678 Frequency Interpretation of a Wave Function, and a Vertical Waveform Treated as A 'Quantum Leap'
Authors: Anthony Coogan
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Born’s probability interpretation of wave functions would have led to nearly identical results had he chosen a frequency interpretation instead. Logically, Born may have assumed that only one electron was under consideration, making it nonsensical to propose a frequency wave. Author’s suggestion: the actual experimental results were not of a single electron; rather, they were groups of reflected x-ray photons. The vertical waveform used by Scrhödinger in his Particle in the Box Theory makes sense if it was intended to represent a quantum leap. The author extended the single vertical panel to form a bar chart: separate panels would represent different energy levels. The proposed bar chart would be populated by reflected photons. Expansion of basic ideas: Part of Scrhödinger’s ‘Particle in the Box’ theory may be valid despite negative criticism. The waveform used in the diagram is vertical, which may seem absurd because real waves decay at a measurable rate, rather than instantaneously. However, there may be one notable exception. Supposedly, following from the theory, the Uncertainty Principle was derived – may a Quantum Leap not be represented as an instantaneous waveform? The great Scrhödinger must have had some reason to suggest a vertical waveform if the prevalent belief was that they did not exist. Complex wave forms representing a particle are usually assumed to be continuous. The actual observations made were x-ray photons, some of which had struck an electron, been reflected, and then moved toward a detector. From Born’s perspective, doing similar work the years in question 1926-7, he would also have considered a single electron – leading him to choose a probability distribution. Probability Distributions appear very similar to Frequency Distributions, but the former are considered to represent the likelihood of future events. Born’s interpretation of the results of quantum experiments led (or perhaps misled) many researchers into claiming that humans can influence events just by looking at them, e.g. collapsing complex wave functions by 'looking at the electron to see which slit it emerged from', while in reality light reflected from the electron moved in the observer’s direction after the electron had moved away. Astronomers may say that they 'look out into the universe' but are actually using logic opposed to the views of Newton and Hooke and many observers such as Romer, in that light carries information from a source or reflector to an observer, rather the reverse. Conclusion: Due to the controversial nature of these ideas, especially its implications about the nature of complex numbers used in applications in science and engineering, some time may pass before any consensus is reached.Keywords: complex wave functions not necessary, frequency distributions instead of wave functions, information carried by light, sketch graph of uncertainty principle
Procedia PDF Downloads 1992677 Investigation of the Growth Kinetics of Phases in Ni–Sn System
Authors: Varun A Baheti, Sanjay Kashyap, Kamanio Chattopadhyay, Praveen Kumar, Aloke Paul
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Ni–Sn system finds applications in the microelectronics industry, especially with respect to flip–chip or direct chip, attach technology. Here the region of interest is under bump metallization (UBM), and solder bump (Sn) interface due to the formation of brittle intermetallic phases there. Understanding the growth of these phases at UBM/Sn interface is important, as in many cases it controls the electro–mechanical properties of the product. Cu and Ni are the commonly used UBM materials. Cu is used for good bonding because of fast reaction with solder and Ni often acts as a diffusion barrier layer due to its inherently slower reaction kinetics with Sn–based solders. Investigation on the growth kinetics of phases in Ni–Sn system is reported in this study. Just for simplicity, Sn being major solder constituent is chosen. Ni–Sn electroplated diffusion couples are prepared by electroplating pure Sn on Ni substrate. Bulk diffusion couples prepared by the conventional method are also studied along with Ni–Sn electroplated diffusion couples. Diffusion couples are annealed for 25–1000 h at 50–215°C to study the phase evolutions and growth kinetics of various phases. The interdiffusion zone was analysed using field emission gun equipped scanning electron microscope (FE–SEM) for imaging. Indexing of selected area diffraction (SAD) patterns obtained from transmission electron microscope (TEM) and composition measurements done in electron probe micro−analyser (FE–EPMA) confirms the presence of various product phases grown across the interdiffusion zone. Time-dependent experiments indicate diffusion controlled growth of the product phase. The estimated activation energy in the temperature range 125–215°C for parabolic growth constants (and hence integrated interdiffusion coefficients) of the Ni₃Sn₄ phase shed light on the growth mechanism of the phase; whether its grain boundary controlled or lattice controlled diffusion. The location of the Kirkendall marker plane indicates that the Ni₃Sn₄ phase grows mainly by diffusion of Sn in the binary Ni–Sn system.Keywords: diffusion, equilibrium phase, metastable phase, the Ni-Sn system
Procedia PDF Downloads 3072676 Partial Differential Equation-Based Modeling of Brain Response to Stimuli
Authors: Razieh Khalafi
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The brain is the information processing centre of the human body. Stimuli in the form of information are transferred to the brain and then brain makes the decision on how to respond to them. In this research, we propose a new partial differential equation which analyses the EEG signals and make a relationship between the incoming stimuli and the brain response to them. In order to test the proposed model, a set of external stimuli applied to the model and the model’s outputs were checked versus the real EEG data. The results show that this model can model the EEG signal well. The proposed model is useful not only for modelling of EEG signal in case external stimuli but it can be used for modelling of brain response in case of internal stimuli.Keywords: brain, stimuli, partial differential equation, response, EEG signal
Procedia PDF Downloads 5542675 Transition Pathways of Commercial-Urban Fleet Electrification
Authors: Emily Gould, Walter Wehremeyer, David Greaves, Rodney Turtle
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This paper considers current thinking on the pathway for electric vehicles, identifying the development blocks of alternative innovation within the market and analyse technological lock-in. The relationship between transition pathways and technological lock-in is largely under-researched particularly in the field of e-mobility. This paper is based on a study with three commercial-urban fleets that examines strategic decisions in new technology adaption alongside vehicle procurement and driver perspective. The paper will analyse the fleet’s decision matrix upon electric vehicles and seek to understand the influence of company culture, strategy and technology applicability, within the context of transition pathways.Keywords: electric vehicles, fleets, path dependencies, transition pathways
Procedia PDF Downloads 5682674 Predicting the Impact of Scope Changes on Project Cost and Schedule Using Machine Learning Techniques
Authors: Soheila Sadeghi
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In the dynamic landscape of project management, scope changes are an inevitable reality that can significantly impact project performance. These changes, whether initiated by stakeholders, external factors, or internal project dynamics, can lead to cost overruns and schedule delays. Accurately predicting the consequences of these changes is crucial for effective project control and informed decision-making. This study aims to develop predictive models to estimate the impact of scope changes on project cost and schedule using machine learning techniques. The research utilizes a comprehensive dataset containing detailed information on project tasks, including the Work Breakdown Structure (WBS), task type, productivity rate, estimated cost, actual cost, duration, task dependencies, scope change magnitude, and scope change timing. Multiple machine learning models are developed and evaluated to predict the impact of scope changes on project cost and schedule. These models include Linear Regression, Decision Tree, Ridge Regression, Random Forest, Gradient Boosting, and XGBoost. The dataset is split into training and testing sets, and the models are trained using the preprocessed data. Cross-validation techniques are employed to assess the robustness and generalization ability of the models. The performance of the models is evaluated using metrics such as Mean Squared Error (MSE) and R-squared. Residual plots are generated to assess the goodness of fit and identify any patterns or outliers. Hyperparameter tuning is performed to optimize the XGBoost model and improve its predictive accuracy. The feature importance analysis reveals the relative significance of different project attributes in predicting the impact on cost and schedule. Key factors such as productivity rate, scope change magnitude, task dependencies, estimated cost, actual cost, duration, and specific WBS elements are identified as influential predictors. The study highlights the importance of considering both cost and schedule implications when managing scope changes. The developed predictive models provide project managers with a data-driven tool to proactively assess the potential impact of scope changes on project cost and schedule. By leveraging these insights, project managers can make informed decisions, optimize resource allocation, and develop effective mitigation strategies. The findings of this research contribute to improved project planning, risk management, and overall project success.Keywords: cost impact, machine learning, predictive modeling, schedule impact, scope changes
Procedia PDF Downloads 392673 Photophysics and Photochemistry of Cross-Conjugated Y-Shaped Enediyne Fluorophores
Authors: Anuja Singh, Avik K. Pati, Ashok K. Mishra
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Organic fluorophores with π-conjugated scaffolds are important because of their interesting optoelectronic properties. In recent years, our lab has been engaged in understanding the photophysics of small diacetylene bridged fluorophores and found the diynes as a promising class of π-conjugated fluorophores. Building on this understanding, recently we have focused on the photophysics of a less explored class of cross-conjugated Y-shaped enediynes (one double and two triple bonds). Here we present the photophysical properties of such enediynes which show interesting photophysical properties that include dual emissions from locally excited (LE) and intramolecular charge transfer (ICT) states and ring size dependent aggregate fluorescence in non-aqueous media. The dyes also show prominent aggregate fluorescence in mixed-aqueous solvents and solid powder form. We further show that the solid state fluorescence can be reversibly switched multiple of cycles by external stimuli, highlighting their potential applications in solid states. The enediynes with push-pull electronic substituents/moieties exhibit high contrast fluorescence color switching upon continuous photon illumination. The intriguing photophysical outcomes of the enediynyl fluorophores are judiciously exploited to generate single-component white light emission in binary solvent mixtures and sense polar aprotic vapor in polymer film matrices. The photophysical behavior of the dyes is further successfully utilized to monitor the microenvironment changes of biologically relevant anisotropic media such as bile salts. In summary, the newly introduced cross-conjugated enediynes enrich the toolbox of organic fluorophores and vouch to display versatile applications.Keywords: aggregation in solution and solid state, enediynes, physical photochemistry and photophysics, vapor sensing and white light emission
Procedia PDF Downloads 4802672 A Study on Big Data Analytics, Applications and Challenges
Authors: Chhavi Rana
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The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, Healthcare, and business intelligence contain voluminous and incremental data, which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organization's decision-making strategy can be enhanced using big data analytics and applying different machine learning techniques and statistical tools on such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates on various frameworks in the process of Analysis using different machine-learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.Keywords: big data, big data analytics, machine learning, review
Procedia PDF Downloads 832671 A Study on Big Data Analytics, Applications, and Challenges
Authors: Chhavi Rana
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The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, healthcare, and business intelligence contain voluminous and incremental data which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organisation decision-making strategy can be enhanced by using big data analytics and applying different machine learning techniques and statistical tools to such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates various frameworks in the process of analysis using different machine learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.Keywords: big data, big data analytics, machine learning, review
Procedia PDF Downloads 952670 Features Dimensionality Reduction and Multi-Dimensional Voice-Processing Program to Parkinson Disease Discrimination
Authors: Djamila Meghraoui, Bachir Boudraa, Thouraya Meksen, M.Boudraa
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Parkinson's disease is a pathology that involves characteristic perturbations in patients’ voices. This paper describes a proposed method that aims to diagnose persons with Parkinson (PWP) by analyzing on line their voices signals. First, Thresholds signals alterations are determined by the Multi-Dimensional Voice Program (MDVP). Principal Analysis (PCA) is exploited to select the main voice principal componentsthat are significantly affected in a patient. The decision phase is realized by a Mul-tinomial Bayes (MNB) Classifier that categorizes an analyzed voice in one of the two resulting classes: healthy or PWP. The prediction accuracy achieved reaching 98.8% is very promising.Keywords: Parkinson’s disease recognition, PCA, MDVP, multinomial Naive Bayes
Procedia PDF Downloads 2782669 Psychological Capital and Intention for Self-Employment among Students in HEIs: A Multi-group Analysis Approach
Authors: Ugur Choban, Aruzhan Zhaksylyk, Assylbek Nurgabdeshov
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In recent years, there has been an increasing understanding of the value of encouraging entrepreneurial attitudes in university students. This is motivated by the belief that stimulating entrepreneurship not only promotes economic growth but also fosters innovation. This study looks at the complex link and addresses critical gaps between psychological capital and entrepreneurial intention among university students, with a specific emphasis on how contextual factors like academic support and past business experience impact this dynamic. Using a quantitative research method, data were gathered from a broad sample of 300 university students drawn from several faculties. The study used a questionnaire that included the Psychological Capital Questionnaire (PCQ) to assess psychological capital and a validated scale for entrepreneurial intention, as well as binary measures of academic support and prior entrepreneurial experience. Statistical investigations, including multigroup analyses performed with SmartPLS software, provided interesting insights into the effect of contextual factors on the relationship between psychological capital and entrepreneurial intention. The findings highlight that psychological capital had a strong favorable influence on university students' entrepreneurial inclinations. Furthermore, the study found that academic support enhances the influence of psychological capital on entrepreneurial intentions, emphasizing the significance of institutional backing in fostering entrepreneurial mindsets. Furthermore, students with prior entrepreneurial experience had a stronger propensity for entrepreneurship, showing a synergistic link between psychological capital and entrepreneurial background. These findings have both theoretical and practical implications. By explaining the mechanisms by which psychological capital promotes entrepreneurial intentions, the study contributes to the establishment of focused entrepreneurship education programs and support activities that are suited to student requirements. Policymakers may use these findings to create policies that encourage student entrepreneurship, ultimately encouraging economic development and innovation.Keywords: academic support, entrepreneurial intentions, higher education institutions, psychological capital, prior entrepreneurial experience
Procedia PDF Downloads 562668 Assessing the Spatial Distribution of Urban Parks Using Remote Sensing and Geographic Information Systems Techniques
Authors: Hira Jabbar, Tanzeel-Ur Rehman
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Urban parks and open spaces play a significant role in improving physical and mental health of the citizens, strengthen the societies and make the cities more attractive places to live and work. As the world’s cities continue to grow, continuing to value green space in cities is vital but is also a challenge, particularly in developing countries where there is pressure for space, resources, and development. Offering equal opportunity of accessibility to parks is one of the important issues of park distribution. The distribution of parks should allow all inhabitants to have close proximity to their residence. Remote sensing and Geographic information systems (GIS) can provide decision makers with enormous opportunities to improve the planning and management of Park facilities. This study exhibits the capability of GIS and RS techniques to provide baseline knowledge about the distribution of parks, level of accessibility and to help in identification of potential areas for such facilities. For this purpose Landsat OLI imagery for year 2016 was acquired from USGS Earth Explorer. Preprocessing models were applied using Erdas Imagine 2014v for the atmospheric correction and NDVI model was developed and applied to quantify the land use/land cover classes including built up, barren land, water, and vegetation. The parks amongst total public green spaces were selected based on their signature in remote sensing image and distribution. Percentages of total green and parks green were calculated for each town of Lahore City and results were then synchronized with the recommended standards. ANGSt model was applied to calculate the accessibility from parks. Service area analysis was performed using Network Analyst tool. Serviceability of these parks has been evaluated by employing statistical indices like service area, service population and park area per capita. Findings of the study may contribute in helping the town planners for understanding the distribution of parks, demands for new parks and potential areas which are deprived of parks. The purpose of present study is to provide necessary information to planners, policy makers and scientific researchers in the process of decision making for the management and improvement of urban parks.Keywords: accessible natural green space standards (ANGSt), geographic information systems (GIS), remote sensing (RS), United States geological survey (USGS)
Procedia PDF Downloads 3412667 Exploring the Dark Side of IT Security: Delphi Study on Business’ Influencing Factors
Authors: Tizian Matschak, Ilja Nastjuk, Stephan Kühnel, Simon Trang
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We argue that besides well-known primary effects of information security controls (ISCs), namely confidentiality, integrity, and availability, ISCs can also have secondary effects. For example, while IT can add business value through impacts on business processes, ISCs can be a barrier and distort the relationship between IT and organizational value through the impact on business processes. By applying the Delphi method with 28 experts, we derived 27 business process influence dimensions of ISCs. Defining and understanding these mechanisms can change the common understanding of the cost-benefit valuation of IT security investments and support managers' effective and efficient decision-making.Keywords: business process dimensions, dark side of information security, Delphi study, IT security controls
Procedia PDF Downloads 1122666 The Value of Store Choice Criteria on Perceived Patronage Intentions
Authors: Susana Marques
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Research on how store environment cues influence consumers’ store choice decision criteria, such as store operations, product quality, monetary price, store image and sales promotion, is sparse. Especially absent research on the simultaneous impact of multiple store environment cues. The authors propose a comprehensive store choice model that includes: three types of store environment cues as exogenous constructs; various store choice criteria as possible mediating constructs, and store patronage intentions as an endogenous construct. On the basis of testing with a sample of 561 customers of hypermarkets, the model is partially supported. This study used structural equation modelling to test the proposed model.Keywords: store choice, store patronage, structural equation modelling, retailing
Procedia PDF Downloads 272