Search results for: generalized assignment problem
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8001

Search results for: generalized assignment problem

2451 Applied of LAWA Classification for Assessment of the Water by Nutrients Elements: Case Oran Sebkha Basin

Authors: Boualla Nabila

Abstract:

The increasing demand on water, either for the drinkable water supply, or for the agricultural and industrial custom, requires a very thorough hydrochemical study to protect better and manage this resource. Oran is relatively a city with the worst quality of the water. Recently, the growing populations may put stress on natural waters by impairing the quality of the water. Campaign of water sampling of 55 points capturing different levels of the aquifer system was done for chemical analyzes of nutriments elements. The results allowed us to approach the problem of contamination based on the largely uniform nationwide approach LAWA (LänderarbeitsgruppeWasser), based on the EU CIS guidance, has been applied for the identification of pressures and impacts, allowing for easy comparison. Groundwater samples were analyzed, also, for physico-chemical parameters such as pH, sodium, potassium, calcium, magnesium, chloride, sulphate, carbonate and bicarbonate. The analytical results obtained in this hydrochemistry study were interpreted using Durov diagram. Based on these representations, the anomaly of high groundwater salinity observed in Oran Sebkha basin was explained by the high chloride concentration and to the presence of inverse cation exchange reaction. Durov diagram plot revealed that the groundwater has been evolved from Ca-HCO3 recharge water through mixing with the pre-existing groundwater to give mixed water of Mg-SO4 and Mg-Cl types that eventually reached a final stage of evolution represented by a Na-Cl water type.

Keywords: contamination, water quality, nutrients elements, approach LAWA, durov diagram

Procedia PDF Downloads 277
2450 Sexting Phenomenon in Educational Settings: A Data Mining Approach

Authors: Koutsopoulou Ioanna, Gkintoni Evgenia, Halkiopoulos Constantinos, Antonopoulou Hera

Abstract:

Recent advances in Internet Computer Technology (ICT) and the ever-increasing use of technological equipment amongst adolescents and young adults along with unattended access to the internet and social media and uncontrolled use of smart phones and PCs have caused social problems like sexting to emerge. The main purpose of the present article is first to present an analytic theoretical framework of sexting as a recent social phenomenon based on studies that have been conducted the last decade or so; and second to investigate Greek students’ and also social network users, sexting perceptions and to record how often social media users exchange sexual messages and to retrace demographic variables predictors. Data from 1,000 students were collected and analyzed and all statistical analysis was done by the software package WEKA. The results indicate among others, that the use of data mining methods is an important tool to draw conclusions that could affect decision and policy making especially in the field and related social topics of educational psychology. To sum up, sexting lurks many risks for adolescents and young adults students in Greece and needs to be better addressed in relevance to the stakeholders as well as society in general. Furthermore, policy makers, legislation makers and authorities will have to take action to protect minors. Prevention strategies based on Greek cultural specificities are being proposed. This social problem has raised concerns in recent years and will most likely escalate concerns in global communities in the future.

Keywords: educational ethics, sexting, Greek sexters, sex education, data mining

Procedia PDF Downloads 183
2449 Igbo Art: A Reflection of the Igbo’s Visual Culture

Authors: David Osa-Egonwa

Abstract:

Visual culture is the expression of the norms and social behavior of a society in visual images. A reflection simply shows you how you look when you stand before a mirror, a clear water or stream. The mirror does not alter, improve or distort your original appearance, neither does it show you a caricature of what stands before it, this is the case with visual images created by a tribe or society. The ‘uli’ is hand drawn body design done on Igbo women and speaks of a culture of body adornment which is a practice that is appreciated by that tribe. The use of pattern of the gliding python snake ‘ije eke’ or ‘ijeagwo’ for wall painting speaks of the Igbo culture as one that appreciates wall paintings based on these patterns. Modern life came and brought a lot of change to the Igbo-speaking people of Nigeria. Change cloaked in the garment of Westernization has influenced the culture of the Igbos. This has resulted in a problem which is a break in the cultural practice that has also affected art produced by the Igbos. Before the colonial masters arrived and changed the established culture practiced by the Igbos, visual images were created that retained the culture of this people. To bring this point to limelight, this paper has adopted a historical method. A large number of works produced during pre and post-colonial era which range from sculptural pieces, paintings and other artifacts, just to mention a few, were studied carefully and it was discovered that the visual images hold the culture or aspects of the culture of the Igbos in their renditions and can rightly serve as a mirror of the Igbo visual culture.

Keywords: artistic renditions, historical method, Igbo visual culture, changes

Procedia PDF Downloads 191
2448 Convolutional Neural Networks-Optimized Text Recognition with Binary Embeddings for Arabic Expiry Date Recognition

Authors: Mohamed Lotfy, Ghada Soliman

Abstract:

Recognizing Arabic dot-matrix digits is a challenging problem due to the unique characteristics of dot-matrix fonts, such as irregular dot spacing and varying dot sizes. This paper presents an approach for recognizing Arabic digits printed in dot matrix format. The proposed model is based on Convolutional Neural Networks (CNN) that take the dot matrix as input and generate embeddings that are rounded to generate binary representations of the digits. The binary embeddings are then used to perform Optical Character Recognition (OCR) on the digit images. To overcome the challenge of the limited availability of dotted Arabic expiration date images, we developed a True Type Font (TTF) for generating synthetic images of Arabic dot-matrix characters. The model was trained on a synthetic dataset of 3287 images and 658 synthetic images for testing, representing realistic expiration dates from 2019 to 2027 in the format of yyyy/mm/dd. Our model achieved an accuracy of 98.94% on the expiry date recognition with Arabic dot matrix format using fewer parameters and less computational resources than traditional CNN-based models. By investigating and presenting our findings comprehensively, we aim to contribute substantially to the field of OCR and pave the way for advancements in Arabic dot-matrix character recognition. Our proposed approach is not limited to Arabic dot matrix digit recognition but can also be extended to text recognition tasks, such as text classification and sentiment analysis.

Keywords: computer vision, pattern recognition, optical character recognition, deep learning

Procedia PDF Downloads 96
2447 Interdisciplinary Approach for Economic Production of Oil and Gas Reserves: Application of Geothermal Energy for Enhanced Oil Recovery

Authors: Dharmit Viroja, Prerakkumar Shah, Rajanikant Gajera, Ruchit Shah

Abstract:

With present scenario of aging oil and gas fields with high water cuts, volatile oil prices and increasing greenhouse gas emission, the need for alleviating such issues has necessitated for oil and gas industry to make the maximum out of available assets, infrastructure and reserves in mother Earth. Study undertaken emphasizes on utilizing Geothermal Energy under specific reservoir conditions for Enhanced oil Recovery (EOR) to boost up production. Allied benefits of this process include mitigation of electricity problem in remote fields and controlled CO-emission. Utilization of this energy for EOR and increasing economic life of field could surely be rewarding. A new way to value oil lands would be considered if geothermal co-production is integrated in the field development program. Temperature profile of co-produced fluid across its journey is a pivotal issue which has been studied. Geo pressured reservoirs resulting from trapped brine under an impermeable bed is also a frontier for exploitation. Hot geothermal fluid is a by-product of large number of oil and gas wells, historically this hot water has been seen as an inconvenience; however, it can be looked at as a useful resource. The production of hot fluids from abandoned and co-production of hot fluids from producing wells has potential to prolong life of oil and gas fields. The study encompasses various factors which are required for use of this technology and application of this process across various phases of oil and gas value chain. Interdisciplinary approach in oil and gas value chain has shown potential for economic production of estimated oil and gas reserves.

Keywords: enhanced oil recovery, geo-pressured reservoirs, geothermal energy, oil and gas value chain

Procedia PDF Downloads 344
2446 Nitrogen/Platinum Co-Doped TiO₂ for Enhanced Visible Light Photocatalytic Degradation of Brilliant Black

Authors: Sarre Nzaba, Bulelwa Ntsendwana, Bekkie Mamba, Alex Kuvarega

Abstract:

Elimination of toxic organic compounds from wastewater is currently one of the most important subjects in water pollution control. The discharge of azo dyes such as Brilliant black (BB) into the water bodies has carcinogenic and mutagenic effects on humankind and the ecosystem. Conventional water treatment techniques fail to degrade these dyes completely thereby posing more problems. Advanced oxidation processes (AOPs) are promising technologies in solving the problem. Anatase type nitrogen-platinum (N,Pt) co-doped TiO₂ photocatalyts were prepared by a modified sol-gel method using amine terminated polyamidoamine generation 1 (PG1) as a template and source of nitrogen. SEM/ EDX, TEM, XRD, XPS, TGA, FTIR, RS, PL and UV-Vis were used to characterize the prepared nanomaterials. The synthesized photocatalysts exhibited lower band gap energies as compared to the commercial TiO₂ revealing a shift in band gap towards the visible light absorption region. Photocatalytic activity of N,Pt co-doped TiO₂ was measured by the reaction of photocatalytic degradation of BB dye. Enhanced photodegradation efficiency of BB was achieved after 180 min reaction time with initial concentration of 50 ppm BB solution. This was attributed to the rod-like shape of the materials, larger surface area, and enhanced absorption of visible light induced by N,Pt co-doping. The co-doped N,Pt also exhibited pseudo-first order kinetic behaviour with half-life and rate constant of 0.37 min 0.1984 min⁻¹ and respectively. N doped TiO₂ and N,Pt co-doped TiO₂ exhibited enhanced photocatalytic performances for the removal of BB from water.

Keywords: N, Pt co-doped TiO₂, dendrimer, photodegradation, visible-light

Procedia PDF Downloads 172
2445 Digitalisation of the Railway Industry: Recent Advances in the Field of Dialogue Systems: Systematic Review

Authors: Andrei Nosov

Abstract:

This paper discusses the development directions of dialogue systems within the digitalisation of the railway industry, where technologies based on conversational AI are already potentially applied or will be applied. Conversational AI is one of the popular natural language processing (NLP) tasks, as it has great prospects for real-world applications today. At the same time, it is a challenging task as it involves many areas of NLP based on complex computations and deep insights from linguistics and psychology. In this review, we focus on dialogue systems and their implementation in the railway domain. We comprehensively review the state-of-the-art research results on dialogue systems and analyse them from three perspectives: type of problem to be solved, type of model, and type of system. In particular, from the perspective of the type of tasks to be solved, we discuss characteristics and applications. This will help to understand how to prioritise tasks. In terms of the type of models, we give an overview that will allow researchers to become familiar with how to apply them in dialogue systems. By analysing the types of dialogue systems, we propose an unconventional approach in contrast to colleagues who traditionally contrast goal-oriented dialogue systems with open-domain systems. Our view focuses on considering retrieval and generative approaches. Furthermore, the work comprehensively presents evaluation methods and datasets for dialogue systems in the railway domain to pave the way for future research. Finally, some possible directions for future research are identified based on recent research results.

Keywords: digitalisation, railway, dialogue systems, conversational AI, natural language processing, natural language understanding, natural language generation

Procedia PDF Downloads 63
2444 Vocational Teaching Method: A Conceptual Model in Teaching Automotive Practical Work

Authors: Adnan Ahmad, Yusri Kamin, Asnol Dahar Minghat, Mohd. Khir Nordin, Dayana Farzeha, Ahmad Nabil

Abstract:

The purpose of this study is to identify the teaching method practices of the practical work subject in Vocational Secondary School. This study examined the practice of Vocational Teaching Method in Automotive Practical Work. The quantitative method used the sets of the questionnaire. 283 students and 63 teachers involved from ten VSS involved in this research. Research finding showed in conducting the introduction session teachers prefer used the demonstration method and questioning technique. While in deliver the content of practical task, teachers applied group monitoring and problem-solving approach. To conclude the task of automotive practical work, teachers choose re-explain and report writing to make sure students really understand all the process of teaching. VTM-APW also involved the competency-based concept to embed in the model. Derived from factors investigated, research produced the combination of elements in teaching skills and vocational skills which could be used as the best teaching method in automotive practical work for school level. As conclusion this study has concluded that the VTM-APW model is able to apply in teaching to make an improvement with current practices in Vocational Secondary School. Hence, teachers are suggested to use this method to enhance student's knowledge in Automotive and teachers will deliver skills to the current and future workforce relevant with the required competency skilled in workplace.

Keywords: vocational teaching method, practical task, teacher preferences, student preferences

Procedia PDF Downloads 453
2443 Study on Mitigation Measures of Gumti Hydro Power Plant Using Analytic Hierarchy Process and Concordance Analysis Techniques

Authors: K. Majumdar, S. Datta

Abstract:

Electricity is recognized as fundamental to industrialization and improving the quality of life of the people. Harnessing the immense untapped hydropower potential in Tripura region opens avenues for growth and provides an opportunity to improve the well-being of the people of the region, while making substantial contribution to the national economy. Gumti hydro power plant generates power to mitigate the crisis of power in Tripura, India. The first unit of hydro power plant (5 MW) was commissioned in June 1976 & another two units of 5 MW was commissioned simultaneously. But out of 15 MW capacity at present only 8-9 MW power is produced from Gumti hydro power plant during rainy season. But during lean season the production reduces to 0.5 MW due to shortage of water. Now, it is essential to implement some mitigation measures so that the further atrocities can be prevented and originality will be possible to restore. The decision making ability of the Analytic Hierarchy Process (AHP) and Concordance Analysis Techniques (CAT) are utilized to identify the better decision or solution to the present problem. Some related attributes are identified by the method of surveying within the experts and the available reports and literatures. Similar criteria are removed and ultimately seven relevant ones are identified. All the attributes are compared with each other and rated accordingly to their importance over the other with the help of Pair wise Comparison Matrix. In the present investigation different mitigation measures are identified and compared to find the best suitable alternative which can solve the present uncertainties involving the existence of the Gumti Hydro Power Plant.

Keywords: concordance analysis techniques, analytic hierarchy process, hydro power

Procedia PDF Downloads 355
2442 Spectral Quasi Linearization Techniques for the Solution of Time Fractional Diffusion Wave Equations in Boundary Value Problems

Authors: Kizito Ugochukwu Nwajeria

Abstract:

This paper presents a spectral quasi-linearization technique (SQLT) for solving time fractional diffusion wave equations in boundary value problems. The proposed method integrates spectral approximations for spatial derivatives with a quasi-linearization approach to address the nonlinearity introduced by fractional time derivatives. Time fractional differential equations typically formulated using Caputo or Riemann-Liouville derivatives, model complex phenomena such as anomalous diffusion and wave propagation, which are not captured by classical integer-order models. The SQLT method iteratively linearizes the nonlinear terms at each time step, transforming the original problem into a series of linear subproblems, which can be efficiently solved. Using high-order spectral methods such as Chebyshev or Legendre polynomials for spatial discretization, the technique achieves high accuracy in approximating the solution. A convergence analysis is provided, demonstrating the method's efficiency and establishing error bounds. Numerical experiments on a range of test problems confirm the effectiveness of SQLT in solving fractional diffusion wave equations with various boundary conditions. The method offers a robust framework for addressing time fractional differential equations in diverse fields, including materials science, bioengineering, and anomalous transport phenomena.

Keywords: spectral methods, quasilinearization, time-fractional diffusion-wave equations, boundary value problems, fractional calculus

Procedia PDF Downloads 14
2441 Simulation of Ammonia-Water Two Phase Flow in Bubble Pump

Authors: Jemai Rabeb, Benhmidene Ali, Hidouri Khaoula, Chaouachi Bechir

Abstract:

The diffusion-absorption refrigeration cycle consists of a generator bubble pump, an absorber, an evaporator and a condenser, and usually operates with ammonia/water/ hydrogen or helium as the working fluid. The aim of this paper is to study the stability problem a bubble pump. In fact instability can caused a reduction of bubble pump efficiency. To achieve this goal, we have simulated the behaviour of two-phase flow in a bubble pump by using a drift flow model. Equations of a drift flow model are formulated in the transitional regime, non-adiabatic condition and thermodynamic equilibrium between the liquid and vapour phases. Equations resolution allowed to define void fraction, and liquid and vapour velocities, as well as pressure and mixing enthalpy. Ammonia-water mixing is used as working fluid, where ammonia mass fraction in the inlet is 0.6. Present simulation is conducted out for a heating flux of 2 kW/m² to 5 kW/m² and bubble pump tube length of 1 m and 2.5 mm of inner diameter. Simulation results reveal oscillations of vapour and liquid velocities along time. Oscillations decrease with time and with heat flux. For sufficient time the steady state is established, it is characterised by constant liquid velocity and void fraction values. However, vapour velocity does not have the same behaviour, it increases for steady state too. On the other hand, pressure drop oscillations are studied.

Keywords: bubble pump, drift flow model, instability, simulation

Procedia PDF Downloads 263
2440 Hybrid Nano Material of Ground Egg Shells with Metal Oxide for Lead Removal

Authors: A. Threepanich, S. Youngme, P. Praipipat

Abstract:

Although ground egg shells had the ability to eliminate lead in water, their efficiency may decrease in a case of contaminating of other cations such as Na⁺, Ca²⁺ in the water. The development of ground egg shells may solve this problem in which metal oxides are a good choice for this case since they have the ability to remove any heavy metals including lead in the water. Therefore, this study attempts to use this advantage for improving ground egg shells for the specific lead removal efficiency in the water. X-ray fluorescence (XRF) technique was used for the chemical element contents analysis of ground egg shells (GES) and ground egg shells with metal oxide (GESM), and Transmission electron microscope (TEM) technique was used to examine the material sizes. The batch test studies were designed to investigate the factor effects on dose (5, 10, 15 grams), pH (5, 7, 9), and settling time (1, 3, 5 hours) for the lead removal efficiency in the water. The XRF analysis results showed GES contained calcium (Ca) 91.41% and Silicon (Si) 4.03% and GESM contained calcium (Ca) 91.41%, Silicon (Si) 4.03%, and Iron (Fe) 3.05%. TEM results confirmed the sizes of GES and GESM in the range of 1-20 nm. The batch test studies showed the best optimum conditions for the lead removal in the water of GES and GESM in dose, pH, and settling time were 10 grams, pH 9, 5 hours and 5 grams, pH 9, 3 hours, respectively. The competing ions (Na⁺ and Ca²⁺) study reported GESM had the higher % lead removal efficiency than GES at 90% and 60%, respectively. Therefore, this result can confirm that adding of metal oxide to ground egg shells helps to improve the lead removal efficiency in the water.

Keywords: nano material, ground egg shells, metal oxide, lead

Procedia PDF Downloads 136
2439 Thermo-Physical Properties and Solubility of CO2 in Piperazine Activated Aqueous Solutions of β-Alanine

Authors: Ghulam Murshid

Abstract:

Carbon dioxide is one of the major greenhouse gas (GHG) contributors. It is an obligation of the industry to reduce the amount of carbon dioxide emission to the acceptable limits. Tremendous research and studies are reported in the past and still the quest to find the suitable and economical solution of this problem needed to be explored in order to develop the most plausible absorber for carbon dioxide removal. Amino acids are reported by the researchers as a potential solvent for absorption of carbon dioxide to replace alkanolamines due to its ability to resist oxidative degradation, low volatility due to its ionic structure and higher surface tension. In addition, the introduction of promoter-like piperazine to amino acid helps to further enhance the solubility. In this work, the effect of piperazine on thermophysical properties and solubility of β-Alanine aqueous solutions were studied for various concentrations. The measured physicochemical properties data was correlated as a function of temperature using least-squares method and the correlation parameters are reported together with it respective standard deviations. The effect of activator piperazine on the CO2 loading performance of selected amino acid under high-pressure conditions (1bar to 10bar) at temperature range of (30 to 60)oC was also studied. Solubility of CO2 decreases with increasing temperature and increases with increasing pressure. Quadratic representation of solubility using Response Surface Methodology (RSM) shows that the most important parameter to optimize solubility is system pressure. The addition of promoter increases the solubility effect of the solvent.

Keywords: amino acids, co2, global warming, solubility

Procedia PDF Downloads 415
2438 Resiliency in Fostering: A Qualitative Study of Highly Experienced Foster Parents

Authors: Ande Nesmith

Abstract:

There is an ongoing shortage of foster parents worldwide to take on a growing population of children in need of out-of-home care. Currently, resources are primarily aimed at recruitment rather than retention. Retention rates are extraordinarily low, especially in the first two years of fostering. Qualitative interviews with 19 foster parents averaging 20 years of service provided insight into the challenges they faced and how they overcame them. Thematic analysis of interview transcripts identified sources of stress and resiliency. Key stressors included lack of support and responsiveness from the children’s social workers, false maltreatment allegations, and secondary trauma from children’s destructive behaviors and emotional dysregulation. Resilient parents connected with other foster parents for support, engaged in creative problem-solving, recognized that positive feedback from children usually arrives years later, and through training, understood the neurobiological impact of trauma on child behavior. Recommendations include coordinating communication between the foster parent licensing agency social workers and the children’s social workers, creating foster parent support networks and mentoring, and continuous training on trauma including effective parenting strategies. Research is needed to determine whether these resilience indicators in fact lead to long-term retention. Policies should include a mechanism to develop a cohesive line of communication and connection between foster parents and the children’s social workers as well as their respective agencies.

Keywords: foster care stability, foster parent burnout, foster parent resiliency, foster parent retention, trauma-informed fostering

Procedia PDF Downloads 353
2437 Cognitive Model of Analogy Based on Operation of the Brain Cells: Glial, Axons and Neurons

Authors: Ozgu Hafizoglu

Abstract:

Analogy is an essential tool of human cognition that enables connecting diffuse and diverse systems with attributional, deep structural, casual relations that are essential to learning, to innovation in artificial worlds, and to discovery in science. Cognitive Model of Analogy (CMA) leads and creates information pattern transfer within and between domains and disciplines in science. This paper demonstrates the Cognitive Model of Analogy (CMA) as an evolutionary approach to scientific research. The model puts forward the challenges of deep uncertainty about the future, emphasizing the need for flexibility of the system in order to enable reasoning methodology to adapt to changing conditions. In this paper, the model of analogical reasoning is created based on brain cells, their fractal, and operational forms within the system itself. Visualization techniques are used to show correspondences. Distinct phases of the problem-solving processes are divided thusly: encoding, mapping, inference, and response. The system is revealed relevant to brain activation considering each of these phases with an emphasis on achieving a better visualization of the brain cells: glial cells, axons, axon terminals, and neurons, relative to matching conditions of analogical reasoning and relational information. It’s found that encoding, mapping, inference, and response processes in four-term analogical reasoning are corresponding with the fractal and operational forms of brain cells: glial, axons, and neurons.

Keywords: analogy, analogical reasoning, cognitive model, brain and glials

Procedia PDF Downloads 186
2436 Relay-Augmented Bottleneck Throughput Maximization for Correlated Data Routing: A Game Theoretic Perspective

Authors: Isra Elfatih Salih Edrees, Mehmet Serdar Ufuk Türeli

Abstract:

In this paper, an energy-aware method is presented, integrating energy-efficient relay-augmented techniques for correlated data routing with the goal of optimizing bottleneck throughput in wireless sensor networks. The system tackles the dual challenge of throughput optimization while considering sensor network energy consumption. A unique routing metric has been developed to enable throughput maximization while minimizing energy consumption by utilizing data correlation patterns. The paper introduces a game theoretic framework to address the NP-complete optimization problem inherent in throughput-maximizing correlation-aware routing with energy limitations. By creating an algorithm that blends energy-aware route selection strategies with the best reaction dynamics, this framework provides a local solution. The suggested technique considerably raises the bottleneck throughput for each source in the network while reducing energy consumption by choosing the best routes that strike a compromise between throughput enhancement and energy efficiency. Extensive numerical analyses verify the efficiency of the method. The outcomes demonstrate the significant decrease in energy consumption attained by the energy-efficient relay-augmented bottleneck throughput maximization technique, in addition to confirming the anticipated throughput benefits.

Keywords: correlated data aggregation, energy efficiency, game theory, relay-augmented routing, throughput maximization, wireless sensor networks

Procedia PDF Downloads 85
2435 Religion and Suicide: Exploration of the Relationship Between Religiosity and Suicidal Ideation among Young Adults

Authors: Sandra D. Prewitt

Abstract:

Introduction—The purpose of the extant study was to explore the relationship between religiosity and suicidal ideation. Through this exploration, further knowledge was sought relevant to gaining a better understanding regarding the higher suicide rate continuing to be experienced by young adults. Endeavoring to discover why the suicide rate continues to increase for the subject population, depression and anxiety emerged as major contributory risk factors. Although religiosity has been shown to be related to the reduced risk of suicidal behavior, the curative value of religion relevant to suicide prevention and treatment has not been sufficiently recognized. Considering the enormity of the current suicide problem, pursuits relevant to discovering effective tools enabling impactful prevention and treatment strategies remain essential to reducing suicide deaths. Methodology—The subject study was conducted utilizing a systematic literature review (SLR) which required the researcher to perform searches of appropriate databases, toward the goal of acquiring advanced knowledge based upon existing studies relevant to the subject matter under consideration. Major Findings—Depression and anxiety have been identified as two potential pathways leading to increased suicidal behavior. On the contrary, religiosity emerged as an important protective factor associated with less depression and therefore, fewer instances of suicidal thoughts. The protective nature of religion has been shown to extend to young adults without regard to the presence of identified potential suicidal behavior pathways.

Keywords: anxiety, depression, religion, suicide

Procedia PDF Downloads 221
2434 Development of a Flexible Lora-Based Wireless Sensory System for Long-Time Health Monitoring of Civil Structures

Authors: Hui Zhang, Sherif Beskhyroun

Abstract:

In this study, a highly flexible LoRa-Based wireless sensing system was used to assess the strain state performance of building structures. The system was developed to address the local damage limitation of structural health monitoring (SHM) systems. The system is part of an intelligent SHM system designed to monitor, collect and transmit strain changes in key structural components. The main purpose of the wireless sensor system is to reduce the development and installation costs, and reduce the power consumption of the system, so as to achieve long-time monitoring. The highly stretchable flexible strain gauge is mounted on the surface of the structure and is waterproof, heat resistant, and low temperature resistant, greatly reducing the installation and maintenance costs of the sensor. The system was also developed with the aim of using LoRa wireless communication technology to achieve both low power consumption and long-distance transmission, therefore solving the problem of large-scale deployment of sensors to cover more areas in large structures. In the long-term monitoring of the building structure, the system shows very high performance, very low actual power consumption, and wireless transmission stability. The results show that the developed system has a high resolution, sensitivity, and high possibility of long-term monitoring.

Keywords: LoRa, SHM system, strain measurement, civil structures, flexible sensing system

Procedia PDF Downloads 103
2433 Hybrid Thresholding Lifting Dual Tree Complex Wavelet Transform with Wiener Filter for Quality Assurance of Medical Image

Authors: Hilal Naimi, Amelbahahouda Adamou-Mitiche, Lahcene Mitiche

Abstract:

The main problem in the area of medical imaging has been image denoising. The most defying for image denoising is to secure data carrying structures like surfaces and edges in order to achieve good visual quality. Different algorithms with different denoising performances have been proposed in previous decades. More recently, models focused on deep learning have shown a great promise to outperform all traditional approaches. However, these techniques are limited to the necessity of large sample size training and high computational costs. This research proposes a denoising approach basing on LDTCWT (Lifting Dual Tree Complex Wavelet Transform) using Hybrid Thresholding with Wiener filter to enhance the quality image. This research describes the LDTCWT as a type of lifting wavelets remodeling that produce complex coefficients by employing a dual tree of lifting wavelets filters to get its real part and imaginary part. Permits the remodel to produce approximate shift invariance, directionally selective filters and reduces the computation time (properties lacking within the classical wavelets transform). To develop this approach, a hybrid thresholding function is modeled by integrating the Wiener filter into the thresholding function.

Keywords: lifting wavelet transform, image denoising, dual tree complex wavelet transform, wavelet shrinkage, wiener filter

Procedia PDF Downloads 163
2432 People Experiencing Economic Disadvantages and Access to Justice System: The Case of Unemployed People in Australia

Authors: M. Shahadat Hossain

Abstract:

People experiencing economic disadvantages have limited access to justice system. Employment status is a key indicator of economic disadvantage. There is a link between employment status and vulnerability to legal problems. This paper addresses the obstacles unemployed people experience to secure justice in Australia. This paper further explores exiting services for economically disadvantaged people to secure justice where these unemployment people can get access. It reveals that unemployed people are vulnerable to multifaced crime and violence. Due to high cost of legal services, these unemployed people are unable to afford legal services to access justice. They are often found higher levels of nonactions in terms of access to justice also due to lack of their initiatives. This paper further reveals that legal aid commissions are state and territory statutory agencies in Australia which provide free legal information, advice, duty lawyers, and legal representation services. Community legal centres are independent, non-profit government organizations with a focus of early advice, problem solving, and working with other agencies to address connected, financial, and health problems. Moreover, the private profession helps people who cannot afford to pay for a lawyer in several ways. But there are problems of shortage of funding for these legal services and making available to economically disadvantaged people. However, this paper argues that people experiencing long-term unemployment face barriers to secure justice due to their economic disadvantages. It further argues that services available for them to access to justice is inadequate.

Keywords: economic disadvantages, unemployment, access to justice, Australia

Procedia PDF Downloads 141
2431 Adsorption of 17a-Ethinylestradiol on Activated Carbon Based on Sewage Sludge in Aqueous Medium

Authors: Karoline Reis de Sena

Abstract:

Endocrine disruptors are unregulated or not fully regulated compounds, even in the most developed countries, and which can be a danger to the environment and human health. They pass untreated through the secondary stage of conventional wastewater treatment plants, then the effluent from the wastewater treatment plants is discharged into the rivers, upstream and downstream from the drinking water treatment plants that use the same river water as the tributary. Long-term consumption of drinking water containing low concentrations of these compounds can cause health problems; these are persistent in nature and difficult to remove. In this way, research on emerging pollutants is expanding and is fueled by progress in finding the appropriate method for treating wastewater. Adsorption is the most common separation process, it is a simple and low-cost operation, but it is not eco-efficient. Concomitant to this, biosorption arises, which is a subcategory of adsorption where the biosorbent is biomass and which presents numerous advantages when compared to conventional treatment methods, such as low cost, high efficiency, minimization of the use of chemicals, absence of need for additional nutrients, biosorbent regeneration capacity and the biomass used in the production of biosorbents are found in abundance in nature. Thus, the use of alternative materials, such as sewage sludge, for the synthesis of adsorbents has proved to be an economically viable alternative, together with the importance of valuing the generated by-product flows, as well as managing the problem of their correct disposal. In this work, an alternative for the management of sewage sludge is proposed, transforming it into activated carbon and using it in the adsorption process of 17a-ethinylestradiol.

Keywords: 17α-ethinylestradiol, adsorption, activated carbon, sewage sludge, micropollutants

Procedia PDF Downloads 96
2430 Evaluation of Security and Performance of Master Node Protocol in the Bitcoin Peer-To-Peer Network

Authors: Muntadher Sallal, Gareth Owenson, Mo Adda, Safa Shubbar

Abstract:

Bitcoin is a digital currency based on a peer-to-peer network to propagate and verify transactions. Bitcoin is gaining wider adoption than any previous crypto-currency. However, the mechanism of peers randomly choosing logical neighbors without any knowledge about underlying physical topology can cause a delay overhead in information propagation, which makes the system vulnerable to double-spend attacks. Aiming at alleviating the propagation delay problem, this paper introduces proximity-aware extensions to the current Bitcoin protocol, named Master Node Based Clustering (MNBC). The ultimate purpose of the proposed protocol, that are based on how clusters are formulated and how nodes can define their membership, is to improve the information propagation delay in the Bitcoin network. In MNBC protocol, physical internet connectivity increases, as well as the number of hops between nodes, decreases through assigning nodes to be responsible for maintaining clusters based on physical internet proximity. We show, through simulations, that the proposed protocol defines better clustering structures that optimize the performance of the transaction propagation over the Bitcoin protocol. The evaluation of partition attacks in the MNBC protocol, as well as the Bitcoin network, was done in this paper. Evaluation results prove that even though the Bitcoin network is more resistant against the partitioning attack than the MNBC protocol, more resources are needed to be spent to split the network in the MNBC protocol, especially with a higher number of nodes.

Keywords: Bitcoin network, propagation delay, clustering, scalability

Procedia PDF Downloads 116
2429 A Script for Presentation to the Management of a Teaching Hospital on MYCIN: A Clinical Decision Support System

Authors: Rashida Suleiman, Asamoah Jnr. Boakye, Suleiman Ahmed Ibn Ahmed

Abstract:

In recent years, there has been an enormous success in discoveries of scientific knowledge in medicine coupled with the advancement of technology. Despite all these successes, diagnoses and treatment of diseases have become complex. MYCIN is a groundbreaking illustration of a clinical decision support system (CDSS), which was developed to assist physicians in the diagnosis and treatment of bacterial infections by providing suggestions for antibiotic regimens. MYCIN was one of the earliest expert systems to demonstrate how CDSSs may assist human decision-making in complicated areas. Relevant databases were searched using google scholar, PubMed and general Google search, which were peculiar to clinical decision support systems. The articles were then screened for a comprehensive overview of the functionality, consultative style and statistical usage of MYCIN, a clinical decision support system. Inferences drawn from the articles showed some usage of MYCIN for problem-based learning among clinicians and students in some countries. Furthermore, the data demonstrated that MYCIN had completed clinical testing at Stanford University Hospital following years of research. The system (MYCIN) was shown to be extremely accurate and effective in diagnosing and treating bacterial infections, and it demonstrated how CDSSs might enhance clinical decision-making in difficult circumstances. Despite the challenges MYCIN presents, the benefits of its usage to clinicians, students and software developers are enormous.

Keywords: clinical decision support system, MYCIN, diagnosis, bacterial infections, support systems

Procedia PDF Downloads 150
2428 The Perceptions of Students in Tourism and Hospitality in Relation to the Pursuit of Higher Degrees: A Case of Walter Sisulu University

Authors: Adelaide Rethabile Motshabi Pitso-Mbili

Abstract:

Higher education institutions (HEIs) are under pressure in producing PhD graduates so that they can position themselves higher in terms of rankings. However, hospitality and tourism higher degree enrolment numbers are very low within South African universities. Furthermore, hospitality and tourism students choose these fields of study because they want to travel, be social, and have fun. Students in higher education are anxious about their future after studies as they are particularly worried about the job conditions in the hospitality and tourism sector, the remuneration, and the status perceptions of many jobs in the sector. Hence, there is a need for a continuous increase in the level of education with the formation of professional aptitudes and personnel quality. In order to understand the reasons for low enrolments, this study aims to explore the perceptions of the final year in tourism and hospitality diploma students towards enrolling for higher degree qualifications after their graduation. This paper utilised a quantitative research method, and data was gathered through questionnaires. In addition, the Linkert scale design was used for questionnaires. The questionnaires were distributed to 137 hospitality and tourism students who are on their exit level at Walter Sisulu University. SPSS was used to analyse data. The findings revealed that students do not wish to continue studying for higher degrees as they believe higher degrees are not important for the industry. Furthermore, families already have financial expectations as they think one qualification is enough. In addition, some students mentioned that they would love to study further, but lack of funding is a problem since NSFAS only funds the first qualification. Thus, it is recommended that students are made aware of the benefits and opportunities available after obtaining higher degrees.

Keywords: hospitality and tourism education, higher degrees, higher education, student’s perceptions, hospitality and tourism sector

Procedia PDF Downloads 120
2427 Comparison of the Factor of Safety and Strength Reduction Factor Values from Slope Stability Analysis of a Large Open Pit

Authors: James Killian, Sarah Cox

Abstract:

The use of stability criteria within geotechnical engineering is the way the results of analyses are conveyed, and sensitivities and risk assessments are performed. Historically, the primary stability criteria for slope design has been the Factor of Safety (FOS) coming from a limit calculation. Increasingly, the value derived from Strength Reduction Factor (SRF) analysis is being used as the criteria for stability analysis. The purpose of this work was to study in detail the relationship between SRF values produced from a numerical modeling technique and the traditional FOS values produced from Limit Equilibrium (LEM) analyses. This study utilized a model of a 3000-foot-high slope with a 45-degree slope angle, assuming a perfectly plastic mohr-coulomb constitutive model with high cohesion and friction angle values typical of a large hard rock mine slope. A number of variables affecting the values of the SRF in a numerical analysis were tested, including zone size, in-situ stress, tensile strength, and dilation angle. This paper demonstrates that in most cases, SRF values are lower than the corresponding LEM FOS values. Modeled zone size has the greatest effect on the estimated SRF value, which can vary as much as 15% to the downside compared to FOS. For consistency when using SRF as a stability criteria, the authors suggest that numerical model zone sizes should not be constructed to be smaller than about 1% of the overall problem slope height and shouldn’t be greater than 2%. Future work could include investigations of the effect of anisotropic strength assumptions or advanced constitutive models.

Keywords: FOS, SRF, LEM, comparison

Procedia PDF Downloads 312
2426 Modified Model-Based Systems Engineering Driven Approach for Defining Complex Energy Systems

Authors: Akshay S. Dalvi, Hazim El-Mounayri

Abstract:

The internal and the external interactions between the complex structural and behavioral characteristics of the complex energy system result in unpredictable emergent behaviors. These emergent behaviors are not well understood, especially when modeled using the traditional top-down systems engineering approach. The intrinsic nature of current complex energy systems has called for an elegant solution that provides an integrated framework in Model-Based Systems Engineering (MBSE). This paper mainly presents a MBSE driven approach to define and handle the complexity that arises due to emergent behaviors. The approach provides guidelines for developing system architecture that leverages in predicting the complexity index of the system at different levels of abstraction. A framework that integrates indefinite and definite modeling aspects is developed to determine the complexity that arises during the development phase of the system. This framework provides a workflow for modeling complex systems using Systems Modeling Language (SysML) that captures the system’s requirements, behavior, structure, and analytical aspects at both problem definition and solution levels. A system architecture for a district cooling plant is presented, which demonstrates the ability to predict the complexity index. The result suggests that complex energy systems like district cooling plant can be defined in an elegant manner using the unconventional modified MBSE driven approach that helps in estimating development time and cost.

Keywords: district cooling plant, energy systems, framework, MBSE

Procedia PDF Downloads 131
2425 Distributed System Computing Resource Scheduling Algorithm Based on Deep Reinforcement Learning

Authors: Yitao Lei, Xingxiang Zhai, Burra Venkata Durga Kumar

Abstract:

As the quantity and complexity of computing in large-scale software systems increase, distributed system computing becomes increasingly important. The distributed system realizes high-performance computing by collaboration between different computing resources. If there are no efficient resource scheduling resources, the abuse of distributed computing may cause resource waste and high costs. However, resource scheduling is usually an NP-hard problem, so we cannot find a general solution. However, some optimization algorithms exist like genetic algorithm, ant colony optimization, etc. The large scale of distributed systems makes this traditional optimization algorithm challenging to work with. Heuristic and machine learning algorithms are usually applied in this situation to ease the computing load. As a result, we do a review of traditional resource scheduling optimization algorithms and try to introduce a deep reinforcement learning method that utilizes the perceptual ability of neural networks and the decision-making ability of reinforcement learning. Using the machine learning method, we try to find important factors that influence the performance of distributed system computing and help the distributed system do an efficient computing resource scheduling. This paper surveys the application of deep reinforcement learning on distributed system computing resource scheduling proposes a deep reinforcement learning method that uses a recurrent neural network to optimize the resource scheduling, and proposes the challenges and improvement directions for DRL-based resource scheduling algorithms.

Keywords: resource scheduling, deep reinforcement learning, distributed system, artificial intelligence

Procedia PDF Downloads 114
2424 Hybrid Graphene Based Nanomaterial as Highly Efficient Catalyst for the Electrochemical Determination of Ciprofloxacin

Authors: Tien S. H. Pham, Peter J. Mahon, Aimin Yu

Abstract:

The detection of drug molecules by voltammetry has attracted great interest over the past years. However, many drug molecules exhibit poor electrochemical signals at common electrodes which result in low sensitivity in detection. An efficient way to overcome this problem is to modify electrodes with functional materials. Since discovered in 2004, graphene (or reduced graphene oxide) has emerged as one of the most studied two-dimensional carbon materials in condensed matter physics, electrochemistry, and so on due to its exceptional physicochemical properties. Additionally, the continuous development of technology has opened the new window for the successful fabrications of many novel graphene-based nanomaterials to serve in electrochemical analysis. This research aims to synthesize and characterize gold nanoparticle coated beta-cyclodextrin functionalized reduced graphene oxide (Au NP–β-CD–RGO) nanocomposites with highly conductive and strongly electro-catalytic properties as well as excellent supramolecular recognition abilities for the modification of electrodes. The electrochemical responses of ciprofloxacin at the as-prepared nanocomposite modified electrode was effectively amplified was much higher in comparison with that at the bare electrode. The linear concentration range was from 0.01 to 120 µM, with a detection limit of 2.7 nM using differential pulse voltammetry. Thus, Au NP–β-CD–RGO nanocomposite has great potential as an ideal material to construct sensitive sensors for the electrochemical determination of ciprofloxacin or similar antibacterial drugs in the future based on its excellent stability, selectivity, and reproducibility.

Keywords: Au nanoparticles, β-CD, ciprofloxacin, electrochemical determination, graphene based nanomaterials

Procedia PDF Downloads 189
2423 Controlling the Process of a Chicken Dressing Plant through Statistical Process Control

Authors: Jasper Kevin C. Dionisio, Denise Mae M. Unsay

Abstract:

In a manufacturing firm, controlling the process ensures that optimum efficiency, productivity, and quality in an organization are achieved. An operation with no standardized procedure yields a poor productivity, inefficiency, and an out of control process. This study focuses on controlling the small intestine processing of a chicken dressing plant through the use of Statistical Process Control (SPC). Since the operation does not employ a standard procedure and does not have an established standard time, the process through the assessment of the observed time of the overall operation of small intestine processing, through the use of X-Bar R Control Chart, is found to be out of control. In the solution of this problem, the researchers conduct a motion and time study aiming to establish a standard procedure for the operation. The normal operator was picked through the use of Westinghouse Rating System. Instead of utilizing the traditional motion and time study, the researchers used the X-Bar R Control Chart in determining the process average of the process that is used for establishing the standard time. The observed time of the normal operator was noted and plotted to the X-Bar R Control Chart. Out of control points that are due to assignable cause were removed and the process average, or the average time the normal operator conducted the process, which was already in control and free form any outliers, was obtained. The process average was then used in determining the standard time of small intestine processing. As a recommendation, the researchers suggest the implementation of the standard time established which is with consonance to the standard procedure which was adopted from the normal operator. With that recommendation, the whole operation will induce a 45.54 % increase in their productivity.

Keywords: motion and time study, process controlling, statistical process control, X-Bar R Control chart

Procedia PDF Downloads 217
2422 Numerical Investigation of Pressure Drop and Erosion Wear by Computational Fluid Dynamics Simulation

Authors: Praveen Kumar, Nitin Kumar, Hemant Kumar

Abstract:

The modernization of computer technology and commercial computational fluid dynamic (CFD) simulation has given better detailed results as compared to experimental investigation techniques. CFD techniques are widely used in different field due to its flexibility and performance. Evaluation of pipeline erosion is complex phenomenon to solve by numerical arithmetic technique, whereas CFD simulation is an easy tool to resolve that type of problem. Erosion wear behaviour due to solid–liquid mixture in the slurry pipeline has been investigated using commercial CFD code in FLUENT. Multi-phase Euler-Lagrange model was adopted to predict the solid particle erosion wear in 22.5° pipe bend for the flow of bottom ash-water suspension. The present study addresses erosion prediction in three dimensional 22.5° pipe bend for two-phase (solid and liquid) flow using finite volume method with standard k-ε turbulence, discrete phase model and evaluation of erosion wear rate with varying velocity 2-4 m/s. The result shows that velocity of solid-liquid mixture found to be highly dominating parameter as compared to solid concentration, density, and particle size. At low velocity, settling takes place in the pipe bend due to low inertia and gravitational effect on solid particulate which leads to high erosion at bottom side of pipeline.

Keywords: computational fluid dynamics (CFD), erosion, slurry transportation, k-ε Model

Procedia PDF Downloads 409