Search results for: Network Time Protocol
Commenced in January 2007
Frequency: Monthly
Edition: International

Search results for: Network Time Protocol

Analysis of Two-Echelon Supply Chain with Perishable Items under Stochastic Demand

Authors: Saeed Poormoaied

Abstract:

Perishability and developing an intelligent control policy for perishable items are the major concerns of marketing managers in a supply chain. In this study, we address a two-echelon supply chain problem for perishable items with a single vendor and a single buyer. The buyer adopts an aged-based continuous review policy which works by taking both the stock level and the aging process of items into account. The vendor works under the warehouse framework, where its lot size is determined with respect to the batch size of the buyer. The model holds for a positive and fixed lead time for the buyer, and zero lead time for the vendor. The demand follows a Poisson process and any unmet demand is lost. We provide exact analytic expressions for the operational characteristics of the system by using the renewal reward theorem. Items have a fixed lifetime after which they become unusable and are disposed of from the buyer's system. The age of items starts when they are unpacked and ready for the consumption at the buyer. When items are held by the vendor, there is no aging process which results in no perishing at the vendor's site. The model is developed under the centralized framework, which takes the expected profit of both vendor and buyer into consideration. The goal is to determine the optimal policy parameters under the service level constraint at the retailer's site. A sensitivity analysis is performed to investigate the effect of the key input parameters on the expected profit and order quantity in the supply chain. The efficiency of the proposed age-based policy is also evaluated through a numerical study. Our results show that when the unit perishing cost is negligible, a significant cost saving is achieved.

Keywords: two-echelon supply chain, perishable items, age-based policy, renewal reward theorem

Procedia PDF Downloads 147
Optimisation Model for Maximising Social Sustainability in Construction Scheduling

Authors: Laura Florez

Abstract:

The construction industry is labour intensive, and the behaviour and management of workers have a direct impact on the performance of construction projects. One of the issues it currently faces is how to recruit and maintain its workers. Construction is known as an industry where workers face the problem of short employment durations, frequent layoffs, and periods of unemployment between jobs. These challenges not only creates pressures on the workers but also project managers have to constantly train new workers, face skills shortage, and uncertainty on the quality of the workers it will attract. To consider worker’s needs and project managers expectations, one practice that can be implemented is to schedule construction projects to maintain a stable workforce. This paper proposes a mixed integer programming (MIP) model to schedule projects with the objective of maximising social sustainability of construction projects, that is, maximise labour stability. Aside from the social objective, the model accounts for equipment and financial resources required by the projects during the construction phase. To illustrate how the solution strategy works, a construction programme comprised of ten projects is considered. The projects are scheduled to maximise labour stability while simultaneously minimising time and minimising cost. The tradeoff between the values in terms of time, cost, and labour stability allows project managers to consider their preferences and identify which solution best suits their needs. Additionally, the model determines the optimal starting times for each of the projects, working patterns for the workers, and labour costs. This model shows that construction projects can be scheduled to not only benefit the project manager, but also benefit current workers and help attract new workers to the industry. Due to its practicality, it can be a valuable tool to support decision making and assist construction stakeholders when developing schedules that include social sustainability factors.

Keywords: labour stability, mixed-integer programming (MIP), scheduling, workforce management

Procedia PDF Downloads 259
Extraction of Cellulose Nanofibrils from Pulp Using Enzymatic Pretreatment and Evaluation of Their Papermaking Potential

Authors: Ajay Kumar Singh, Arvind Kumar, S. P. Singh

Abstract:

Cellulose nanofibrils (CNF) have shown potential of their extensive use in various fields, including papermaking, due to their unique characteristics. In this study, CNF’s were prepared by fibrillating the pulp obtained from raw materials e.g. bagasse, hardwood and softwood using enzymatic pretreatment followed by mechanical refining. These nanofibrils, when examined under FE-SEM, show that partial fibrillation on fiber surface has resulted in production of nanofibers. Mixing these nanofibers with the unrefined and normally refined fibers show their reinforcing effect. This effect is manifested in observing the improvement in the physical and mechanical properties e.g. tensile index and burst index of paper. Tear index, however, was observed to decrease on blending with nanofibers. The optical properties of paper sheets made from blended fibers showed no significant change in comparison to those made from only mechanically refined pulp. Mixing of normal pulp fibers with nanofibers show increase in ºSR and consequent decrease in drainage rate. These changes observed in mechanical, optical and other physical properties of the paper sheets made from nanofibrils blended pulp have been tried to explain considering the distribution of the nanofibrils alongside microfibrils in the fibrous network. Since usually, paper/boards with higher strength are observed to have diminished optical properties which is a drawback in their quality, the present work has the potential for developing paper/boards having improved strength alongwith undiminished optical properties utilising the concepts of nanoscience and nanotechnology.

Keywords: enzymatic pretreatment, mechanical refining, nanofibrils, paper properties

Procedia PDF Downloads 355
Data Centers’ Temperature Profile Simulation Optimized by Finite Elements and Discretization Methods

Authors: José Alberto García Fernández, Zhimin Du, Xinqiao Jin

Abstract:

Nowadays, data center industry faces strong challenges for increasing the speed and data processing capacities while at the same time is trying to keep their devices a suitable working temperature without penalizing that capacity. Consequently, the cooling systems of this kind of facilities use a large amount of energy to dissipate the heat generated inside the servers, and developing new cooling techniques or perfecting those already existing would be a great advance in this type of industry. The installation of a temperature sensor matrix distributed in the structure of each server would provide the necessary information for collecting the required data for obtaining a temperature profile instantly inside them. However, the number of temperature probes required to obtain the temperature profiles with sufficient accuracy is very high and expensive. Therefore, other less intrusive techniques are employed where each point that characterizes the server temperature profile is obtained by solving differential equations through simulation methods, simplifying data collection techniques but increasing the time to obtain results. In order to reduce these calculation times, complicated and slow computational fluid dynamics simulations are replaced by simpler and faster finite element method simulations which solve the Burgers‘ equations by backward, forward and central discretization techniques after simplifying the energy and enthalpy conservation differential equations. The discretization methods employed for solving the first and second order derivatives of the obtained Burgers‘ equation after these simplifications are the key for obtaining results with greater or lesser accuracy regardless of the characteristic truncation error.

Keywords: Burgers' equations, CFD simulation, data center, discretization methods, FEM simulation, temperature profile

Procedia PDF Downloads 177
Uncontrollable Inaccuracy in Inverse Problems

Authors: Yu Menshikov

Abstract:

In this paper the influence of errors of function derivatives in initial time which have been obtained by experiment (uncontrollable inaccuracy) to the results of inverse problem solution was investigated. It was shown that these errors distort the inverse problem solution as a rule near the beginning of interval where the solution are analyzed. Several methods for remove the influence of uncontrollable inaccuracy have been suggested.

Keywords: inverse problems, filtration, uncontrollable inaccuracy

Procedia PDF Downloads 512
Creation of a Realistic Railway Simulator Developed on a 3D Graphic Game Engine Using a Numerical Computing Programming Environment

Authors: Kshitij Ansingkar, Yohei Hoshino, Liangliang Yang

Abstract:

Advances in algorithms related to autonomous systems have made it possible to research on improving the accuracy of a train’s location. This has the capability of increasing the throughput of a railway network without the need for the creation of additional infrastructure. To develop such a system, the railway industry requires data to test sensor fusion theories or implement simultaneous localization and mapping (SLAM) algorithms. Though such simulation data and ground truth datasets are available for testing automation algorithms of vehicles, however, due to regulations and economic considerations, there is a dearth of such datasets in the railway industry. Thus, there is a need for the creation of a simulation environment that can generate realistic synthetic datasets. This paper proposes (1) to leverage the capabilities of open-source 3D graphic rendering software to create a visualization of the environment. (2) to utilize open-source 3D geospatial data for accurate visualization and (3) to integrate the graphic rendering software with a programming language and numerical computing platform. To develop such an integrated platform, this paper utilizes the computing platform’s advanced sensor models like LIDAR, camera, IMU or GPS and merges it with the 3D rendering of the game engine to generate high-quality synthetic data. Further, these datasets can be used to train Railway models and improve the accuracy of a train’s location.

Keywords: 3D game engine, 3D geospatial data, dataset generation, railway simulator, sensor fusion, SLAM

Procedia PDF Downloads 18
Alternative Fuel Production from Sewage Sludge

Authors: Jaroslav Knapek, Kamila Vavrova, Tomas Kralik, Tereza Humesova

Abstract:

The treatment and disposal of sewage sludge is one of the most important and critical problems of waste water treatment plants. Currently, 180 thousand tonnes of sludge dry matter are produced in the Czech Republic, which corresponds to approximately 17.8 kg of stabilized sludge dry matter / year per inhabitant of the Czech Republic. Due to the fact that sewage sludge contains a large amount of substances that are not beneficial for human health, the conditions for sludge management will be significantly tightened in the Czech Republic since 2023. One of the tested methods of sludge liquidation is the production of alternative fuel from sludge from sewage treatment plants and paper production. The paper presents an analysis of economic efficiency of alternative fuel production from sludge and its use for fluidized bed boiler with nominal consumption of 5 t of fuel per hour. The evaluation methodology includes the entire logistics chain from sludge extraction, through mechanical moisture reduction to about 40%, transport to the pelletizing line, moisture drying for pelleting and pelleting itself. For economic analysis of sludge pellet production, a time horizon of 10 years corresponding to the expected lifetime of the critical components of the pelletizing line is chosen. The economic analysis of pelleting projects is based on a detailed analysis of reference pelleting technologies suitable for sludge pelleting. The analysis of the economic efficiency of pellet is based on the simulation of cash flows associated with the implementation of the project over the life of the project. For the entered value of return on the invested capital, the price of the resulting product (in EUR / GJ or in EUR / t) is searched to ensure that the net present value of the project is zero over the project lifetime. The investor then realizes the return on the investment in the amount of the discount used to calculate the net present value. The calculations take place in a real business environment (taxes, tax depreciation, inflation, etc.) and the inputs work with market prices. At the same time, the opportunity cost principle is respected; waste disposal for alternative fuels includes the saved costs of waste disposal. The methodology also respects the emission allowances saved due to the displacement of coal by alternative (bio) fuel. Preliminary results of testing of pellet production from sludge show that after suitable modifications of the pelletizer it is possible to produce sufficiently high quality pellets from sludge. A mixture of sludge and paper waste has proved to be a more suitable material for pelleting. At the same time, preliminary results of the analysis of the economic efficiency of this sludge disposal method show that, despite the relatively low calorific value of the fuel produced (about 10-11 MJ / kg), this sludge disposal method is economically competitive. This work has been supported by the Czech Technology Agency within the project TN01000048 Biorefining as circulation technology.

Keywords: Alternative fuel, Economic analysis, Pelleting, Sewage sludge

Procedia PDF Downloads 144
Fabrication of Durable and Renegerable Superhydrophobic Coatings on Metallic Surfaces for Potential Industrial Applications

Authors: Priya Varshney, Soumya S. Mohapatra

Abstract:

Fabrication of anti-corrosion and self-cleaning superhydrophobic coatings for metallic surfaces which are regenerable and durable in the aggressive conditions has shown tremendous interest in materials science. In this work, the superhydrophobic coatings on metallic surfaces (aluminum, steel, copper) were prepared by two-step and one-step chemical etching process. In two-step process, roughness on surface was created by chemical etching and then passivation of roughened surface with low surface energy materials whereas, in one-step process, roughness on surface by chemical etching and passivation of surface with low surface energy materials were done in a single step. Beside this, the effect of etchant concentration and etching time on wettability and morphology was also studied. Thermal, mechanical, ultra-violet stability of these coatings were also tested. Along with this, regeneration of coatings and self-cleaning, corrosion resistance and water repelling characteristics were also studied. The surface morphology shows the presence of a rough microstuctures on the treated surfaces and the contact angle measurements confirms the superhydrophobic nature. It is experimentally observed that the surface roughness and contact angle increases with increase in etching time as well as with concentration of etchant. Superhydrophobic surfaces show the excellent self-cleaning behaviour. Coatings are found to be stable and maintain their superhydrophobicity in acidic and alkaline solutions. Water jet impact, floatation on water surface, and low temperature condensation tests prove the water-repellent nature of the coatings. These coatings are found to be thermal, mechanical and ultra-violet stable. These durable superhydrophobic metallic surfaces have potential industrial applications.

Keywords: superhydrophobic, water-repellent, anti-corrosion, self-cleaning

Procedia PDF Downloads 283
Self-Organizing Maps for Credit Card Fraud Detection

Authors: ChunYi Peng, Wei Hsuan CHeng, Shyh Kuang Ueng

Abstract:

This study focuses on the application of self-organizing maps (SOM) technology in analyzing credit card transaction data, aiming to enhance the accuracy and efficiency of fraud detection. Som, as an artificial neural network, is particularly suited for pattern recognition and data classification, making it highly effective for the complex and variable nature of credit card transaction data. By analyzing transaction characteristics with SOM, the research identifies abnormal transaction patterns that could indicate potentially fraudulent activities. Moreover, this study has developed a specialized visualization tool to intuitively present the relationships between SOM analysis outcomes and transaction data, aiding financial institution personnel in quickly identifying and responding to potential fraud, thereby reducing financial losses. Additionally, the research explores the integration of SOM technology with composite intelligent system technologies (including finite state machines, fuzzy logic, and decision trees) to further improve fraud detection accuracy. This multimodal approach provides a comprehensive perspective for identifying and understanding various types of fraud within credit card transactions. In summary, by integrating SOM technology with visualization tools and composite intelligent system technologies, this research offers a more effective method of fraud detection for the financial industry, not only enhancing detection accuracy but also deepening the overall understanding of fraudulent activities.

Keywords: self-organizing map technology, fraud detection, information visualization, data analysis, composite intelligent system technologies, decision support technologies

Procedia PDF Downloads 65
Evolution of Relations among Multiple Institutional Logics: A Case Study from a Higher Education Institution

Authors: Ye Jiang

Abstract:

To examine how the relationships among multiple institutional logics vary over time and the factors that may impact this process, we conducted a 15-year in-depth longitudinal case study of a Higher Education Institution to examine its exploration in college student management. By employing constructive grounded theory, we developed a four-stage process model comprising separation, formalization, selective bridging, and embeddedness that showed how two contradictory logics become complementary, and finally become a new hybridized logic. We argue that selective bridging is an important step in changing inter-logic relations. We also found that ambidextrous leadership and situational sensemaking are two key factors that drive this process. Our contribution to the literature is threefold. First, we enhance the literature on the changing relationships among multiple institutional logics and our findings advance the understanding of relationships between multiple logics through a dynamic view. While most studies have tended to assume that the relationship among logics is static and persistently in a contentious state, we contend that the relationships among multiple institutional logics can change over time. Competitive logics can become complementary, and a new hybridized logic can emerge therefrom. The four-stage logic hybridization process model offers insights on the logic hybridization process, which is underexplored in the literature. Second, our research reveals that selective bridging is important in making conflicting logics compatible, and thus constitutes a key step in creating new hybridized logic dynamics. Our findings suggest that the relations between multiple logics are manageable and can thus be manipulated for organizational innovation. Finally, the factors influencing the variations in inter-logic relations enrich the understanding of the antecedents of these dynamics.

Keywords: institutional theory, institutional logics, ambidextrous leadership, situational sensemaking

Procedia PDF Downloads 175
Harmonic Distortion Analysis in Low Voltage Grid with Grid-Connected Photovoltaic

Authors: Hedi Dghim, Ahmed El-Naggar, Istvan Erlich

Abstract:

Power electronic converters are being introduced in low voltage (LV) grids at an increasingly rapid rate due to the growing adoption of power electronic-based home appliances in residential grid. Photovoltaic (PV) systems are considered one of the potential installed renewable energy sources in distribution power systems. This trend has led to high distortion in the supply voltage which consequently produces harmonic currents in the network and causes an inherent voltage unbalance. In order to investigate the effect of harmonic distortions, a case study of a typical LV grid configuration with high penetration of 3-phase and 1-phase rooftop mounted PV from southern Germany was first considered. Electromagnetic transient (EMT) simulations were then carried out under the MATLAB/Simulink environment which contain detailed models for power electronic-based loads, ohmic-based loads as well as 1- and 3-phase PV. Note that, the switching patterns of the power electronic circuits were considered in this study. Measurements were eventually performed to analyze the distortion levels when PV operating under different solar irradiance. The characteristics of the load-side harmonic impedances were analyzed, and their harmonic contributions were evaluated for different distortion levels. The effect of the high penetration of PV on the harmonic distortion of both positive and negative sequences was also investigated. The simulation results are presented based on case studies. The current distortion levels are in agreement with relevant standards, otherwise the Total Harmonic Distortion (THD) increases under low PV power generation due to its inverse relation with the fundamental current.

Keywords: harmonic distortion analysis, power quality, PV systems, residential distribution system

Procedia PDF Downloads 273
Time-Domain Nuclear Magnetic Resonance as a Potential Analytical Tool to Assess Thermisation in Ewe's Milk

Authors: Alessandra Pardu, Elena Curti, Marco Caredda, Alessio Dedola, Margherita Addis, Massimo Pes, Antonio Pirisi, Tonina Roggio, Sergio Uzzau, Roberto Anedda

Abstract:

Some of the artisanal cheeses products of European Countries certificated as PDO (Protected Designation of Origin) are made from raw milk. To recognise potential frauds (e.g. pasteurisation or thermisation of milk aimed at raw milk cheese production), the alkaline phosphatase (ALP) assay is currently applied only for pasteurisation, although it is known to have notable limitations for the validation of ALP enzymatic state in nonbovine milk. It is known that frauds considerably impact on customers and certificating institutions, sometimes resulting in a damage of the product image and potential economic losses for cheesemaking producers. Robust, validated, and univocal analytical methods are therefore needed to allow Food Control and Security Organisms, to recognise a potential fraud. In an attempt to develop a new reliable method to overcome this issue, Time-Domain Nuclear Magnetic Resonance (TD-NMR) spectroscopy has been applied in the described work. Daily fresh milk was analysed raw (680.00 µL in each 10-mm NMR glass tube) at least in triplicate. Thermally treated samples were also produced, by putting each NMR tube of fresh raw milk in water pre-heated at temperatures from 68°C up to 72°C and for up to 3 min, with continuous agitation, and quench-cooled to 25°C in a water and ice solution. Raw and thermally treated samples were analysed in terms of 1H T2 transverse relaxation times with a CPMG sequence (Recycle Delay: 6 s, interpulse spacing: 0.05 ms, 8000 data points) and quasi-continuous distributions of T2 relaxation times were obtained by CONTIN analysis. In line with previous data collected by high field NMR techniques, a decrease in the spin-spin relaxation constant T2 of the predominant 1H population was detected in heat-treated milk as compared to raw milk. The decrease of T2 parameter is consistent with changes in chemical exchange and diffusive phenomena, likely associated to changes in milk protein (i.e. whey proteins and casein) arrangement promoted by heat treatment. Furthermore, experimental data suggest that molecular alterations are strictly dependent on the specific heat treatment conditions (temperature/time). Such molecular variations in milk, which are likely transferred to cheese during cheesemaking, highlight the possibility to extend the TD-NMR technique directly on cheese to develop a method for assessing a fraud related to the use of a milk thermal treatment in PDO raw milk cheese. Results suggest that TDNMR assays might pave a new way to the detailed characterisation of heat treatments of milk.

Keywords: cheese fraud, milk, pasteurisation, TD-NMR

Procedia PDF Downloads 245
Effectiveness of Cold Calling on Students’ Behavior and Participation during Class Discussions: Punishment or Opportunity to Shine

Authors: Maimuna Akram, Khadija Zia, Sohaib Naseer

Abstract:

Pedagogical objectives and the nature of the course content may lead instructors to take varied approaches to selecting a student for the cold call, specifically in a studio setup where students work on different projects independently and show progress work time to time at scheduled critiques. Cold-calling often proves to be an effective tool in eliciting a response without enforcing judgment onto the recipients. While there is a mixed range of behavior exhibited by students who are cold-called, a classification of responses from anxiety-provoking to inspiring may be elicited; there is a need for a greater understanding of utilizing the exchanges in bringing about fruitful and engaging outcomes of studio discussions. This study aims to unravel the dimensions of utilizing the cold-call approach in a didactic exchange within studio pedagogy. A questionnaire survey was conducted in an undergraduate class at Arts and Design School. The impact of cold calling on students’ participation was determined through various parameters, including course choice, participation frequency, students’ comfortability, and teaching methodology. After analyzing the surveys, specific classroom teachers were interviewed to provide a qualitative perspective of the faculty. It was concluded that cold-calling increases students’ participation frequency and also increases preparation for class. Around 67% of students responded that teaching methods play an important role in learning activities and students’ participation during class discussions. 84% of participants agreed that cold calling is an effective way of learning. According to research, cold-calling can be done in large numbers without making students uncomfortable. As a result, the findings of this study support the use of this instructional method to encourage more students to participate in class discussions.

Keywords: active learning, class discussion, class participation, cold calling, pedagogical methods, student engagement

Procedia PDF Downloads 42
Development of Electric Generator and Water Purifier Cart

Authors: Luisito L. Lacatan, Gian Carlo J. Bergonia, Felipe C. Buado III, Gerald L. Gono, Ron Mark V. Ortil, Calvin A. Yap

Abstract:

This paper features the development of a Mobile Self-sustaining Electricity Generator for water distillation process with MCU- based wireless controller & indicator designed to solve the problem of scarcity of clean water. It is a fact that pure water is precious nowadays and its value is more precious to those who do not have or enjoy it. There are many water filtration products in existence today. However, none of these products fully satisfies the needs of families needing clean drinking water. All of the following products require either large sums of money or extensive maintenance, and some products do not even come with a guarantee of potable water. The proposed project was designed to alleviate the problem of scarcity of potable water in the country and part of the purpose was also to identify the problem or loopholes of the project such as the distance and speed required to produce electricity using a wheel and alternator, the required time for the heating element to heat up, the capacity of the battery to maintain the heat of the heating element and the time required for the boiler to produce a clean and potable water. The project has three parts. The first part included the researchers’ effort to plan every part of the project from the conversion of mechanical energy to electrical energy, from purifying water to potable drinking water to the controller and indicator of the project using microcontroller unit (MCU). This included identifying the problem encountered and any possible solution to prevent and avoid errors. Gathering and reviewing related studies about the project helped the researcher reduce and prevent any problems before they could be encountered. It also included the price and quantity of materials used to control the budget.

Keywords: mobile, self – sustaining, electricity generator, water distillation, wireless battery indicator, wireless water level indicator

Procedia PDF Downloads 314
Ecotourism Development as an Alternative Livelihood for Guassa Community, Ethiopia

Authors: Abraham Kidane

Abstract:

The study aims at assessing the prospects and challenges of community-based ecotourism development in and around the Guassa Community Conservation Area (GCCA) for the establishment of alternative sources of livelihood for local people and the conservation of natural resources. The Guassa area and its surrounding area are endowed with natural, cultural, and religious tourism resources. The study is descriptive in its design and uses both qualitative and quantitative research methods. Interviews and questionnaires were used as an instrument for data gathering. The interview was undertaken with government officials, NGO officials, and experts, with three local community representatives. The three Kebeles of Guassa were chosen using purposive sampling because of the fact that they are immediate neighbors to GCCA, and hence, 150 questionnaires were administered proportionally to the household numbers in each kebeles. The perspectives of the MoCT, EWCA, and some Tour Operation agencies were uncovered through questionnaires; for each of them, five questionnaires were administered, and all the returns were used in the analysis. Frequency, percentage, average mean, One Way-ANOVA, and independent t-test are used to analyze quantitative data. The findings revealed that food insecurity is commonplace in the study area. The local people's reliance on the conservation area’s resources has been increasing, and the area size is also dwindling from time to time. On the other hand, the local people's levels of awareness about Community-Based Ecotourism (CBET) are low. In addition, the local capacity in relation to conservation and CBET development is also low, even though there is inadequate training offered by the government and NGOs. In general, tourism is not yet considered an alternative source of income and a means of conserving natural resources. In addition, the challenges for CBET development apart from low awareness level about CBET and low capacity, poor infrastructure, and poor tourism facilities were also identified as challenges in the study area.

Keywords: ecotourism, CBET, alternative livelihood, conservation

Procedia PDF Downloads 107
A User Interface for Easiest Way Image Encryption with Chaos

Authors: D. López-Mancilla, J. M. Roblero-Villa

Abstract:

Since 1990, the research on chaotic dynamics has received considerable attention, particularly in light of potential applications of this phenomenon in secure communications. Data encryption using chaotic systems was reported in the 90's as a new approach for signal encoding that differs from the conventional methods that use numerical algorithms as the encryption key. The algorithms for image encryption have received a lot of attention because of the need to find security on image transmission in real time over the internet and wireless networks. Known algorithms for image encryption, like the standard of data encryption (DES), have the drawback of low level of efficiency when the image is large. The encrypting based on chaos proposes a new and efficient way to get a fast and highly secure image encryption. In this work, a user interface for image encryption and a novel and easiest way to encrypt images using chaos are presented. The main idea is to reshape any image into a n-dimensional vector and combine it with vector extracted from a chaotic system, in such a way that the vector image can be hidden within the chaotic vector. Once this is done, an array is formed with the original dimensions of the image and turns again. An analysis of the security of encryption from the images using statistical analysis is made and is used a stage of optimization for image encryption security and, at the same time, the image can be accurately recovered. The user interface uses the algorithms designed for the encryption of images, allowing you to read an image from the hard drive or another external device. The user interface, encrypt the image allowing three modes of encryption. These modes are given by three different chaotic systems that the user can choose. Once encrypted image, is possible to observe the safety analysis and save it on the hard disk. The main results of this study show that this simple method of encryption, using the optimization stage, allows an encryption security, competitive with complicated encryption methods used in other works. In addition, the user interface allows encrypting image with chaos, and to submit it through any public communication channel, including internet.

Keywords: image encryption, chaos, secure communications, user interface

Procedia PDF Downloads 496
Oxidation and Reduction Kinetics of Ni-Based Oxygen Carrier for Chemical Looping Combustion

Authors: J. H. Park, R. H. Hwang, K. B. Yi

Abstract:

Carbon Capture and Storage (CCS) is one of the important technology to reduce the CO₂ emission from large stationary sources such as a power plant. Among the carbon technologies for power plants, chemical looping combustion (CLC) has attracted much attention due to a higher thermal efficiency and a lower cost of electricity. A CLC process is consists of a fuel reactor and an air reactor which are interconnected fluidized bed reactor. In the fuel reactor, an oxygen carrier (OC) is reduced by fuel gas such as CH₄, H₂, CO. And the OC is send to air reactor and oxidized by air or O₂ gas. The oxidation and reduction reaction of OC occurs between the two reactors repeatedly. In the CLC system, high concentration of CO₂ can be easily obtained by steam condensation only from the fuel reactor. It is very important to understand the oxidation and reduction characteristics of oxygen carrier in the CLC system to determine the solids circulation rate between the air and fuel reactors, and the amount of solid bed materials. In this study, we have conducted the experiment and interpreted oxidation and reduction reaction characteristics via observing weight change of Ni-based oxygen carrier using the TGA with varying as concentration and temperature. Characterizations of the oxygen carrier were carried out with BET, SEM. The reaction rate increased with increasing the temperature and increasing the inlet gas concentration. We also compared experimental results and adapted basic reaction kinetic model (JMA model). JAM model is one of the nucleation and nuclei growth models, and this model can explain the delay time at the early part of reaction. As a result, the model data and experimental data agree over the arranged conversion and time with overall variance (R²) greater than 98%. Also, we calculated activation energy, pre-exponential factor, and reaction order through the Arrhenius plot and compared with previous Ni-based oxygen carriers.

Keywords: chemical looping combustion, kinetic, nickel-based, oxygen carrier, spray drying method

Procedia PDF Downloads 214
In situ Real-Time Multivariate Analysis of Methanolysis Monitoring of Sunflower Oil Using FTIR

Authors: Pascal Mwenge, Tumisang Seodigeng

Abstract:

The combination of world population and the third industrial revolution led to high demand for fuels. On the other hand, the decrease of global fossil 8fuels deposits and the environmental air pollution caused by these fuels has compounded the challenges the world faces due to its need for energy. Therefore, new forms of environmentally friendly and renewable fuels such as biodiesel are needed. The primary analytical techniques for methanolysis yield monitoring have been chromatography and spectroscopy, these methods have been proven reliable but are more demanding, costly and do not provide real-time monitoring. In this work, the in situ monitoring of biodiesel from sunflower oil using FTIR (Fourier Transform Infrared) has been studied; the study was performed using EasyMax Mettler Toledo reactor equipped with a DiComp (Diamond) probe. The quantitative monitoring of methanolysis was performed by building a quantitative model with multivariate calibration using iC Quant module from iC IR 7.0 software. 15 samples of known concentrations were used for the modelling which were taken in duplicate for model calibration and cross-validation, data were pre-processed using mean centering and variance scale, spectrum math square root and solvent subtraction. These pre-processing methods improved the performance indexes from 7.98 to 0.0096, 11.2 to 3.41, 6.32 to 2.72, 0.9416 to 0.9999, RMSEC, RMSECV, RMSEP and R2Cum, respectively. The R2 value of 1 (training), 0.9918 (test), 0.9946 (cross-validation) indicated the fitness of the model built. The model was tested against univariate model; small discrepancies were observed at low concentration due to unmodelled intermediates but were quite close at concentrations above 18%. The software eliminated the complexity of the Partial Least Square (PLS) chemometrics. It was concluded that the model obtained could be used to monitor methanol of sunflower oil at industrial and lab scale.

Keywords: biodiesel, calibration, chemometrics, methanolysis, multivariate analysis, transesterification, FTIR

Procedia PDF Downloads 152
Computational Investigation of V599 Mutations of BRAF Protein and Its Control over the Therapeutic Outcome under the Malignant Condition

Authors: Mayank, Navneet Kaur, Narinder Singh

Abstract:

The V599 mutations in the BRAF protein are extremely oncogenic, responsible for countless of malignant conditions. Along with wild type, V599E, V599D, and V599R are the important mutated variants of the BRAF proteins. The BRAF inhibitory anticancer agents are continuously developing, and sorafenib is a BRAF inhibitor that is under clinical use. The crystal structure of sorafenib bounded to wild type, and V599 is known, showing a similar interaction pattern in both the case. The mutated 599th residue, in both the case, is also found not interacting directly with the co-crystallized sorafenib molecule. However, the IC50 value of sorafenib was found extremely different in both the case, i.e., 22 nmol/L for wild and 38 nmol/L for V599E protein. Molecular docking study and MMGBSA binding energy results also revealed a significant difference in the binding pattern of sorafenib in both the case. Therefore, to explore the role of distinctively situated 599th residue, we have further conducted comprehensive computational studies. The molecular dynamics simulation, residue interaction network (RIN) analysis, and residue correlation study results revealed the importance of the 599th residue on the therapeutic outcome and overall dynamic of the BRAF protein. Therefore, although the position of 599th residue is very much distinctive from the ligand-binding cavity of BRAF, still it has exceptional control over the overall functional outcome of the protein. The insight obtained here may seem extremely important and guide us while designing ideal BRAF inhibitory anticancer molecules.

Keywords: BRAF, oncogenic, sorafenib, computational studies

Procedia PDF Downloads 122
Acoustic Radiation Force Impulse Elastography of the Hepatic Tissue of Canine Brachycephalic Patients

Authors: A. C. Facin, M. C. Maronezi , M. P. Menezes, G. L. Montanhim, L. Pavan, M. A. R. Feliciano, R. P. Nociti, R. A. R. Uscategui, P. C. Moraes

Abstract:

The incidence of brachycephalic syndrome (BS) in the clinical routine of small animals has increased significantly giving the higher proportion of brachycephalic pets in the last years and has been considered as an animal welfare problem. The treatment of BS is surgical and the clinical signs related can be considerably attenuated. Nevertheless, the systemic effects of the BS are still poorly reported and little is known about these when the surgical correction is not performed early. Affected dogs are more likely to develop cardiopulmonary, gastrointestinal and sleep disorders in which the chronic hypoxemia plays a major role. This syndrome is compared with the obstructive sleep apnea (OSA) in humans, both considered as causes of systemic and metabolic dysfunction. Among the several consequences of the BS little is known if the syndrome also affects the hepatic tissue of brachycephalic patients. Elastography is a promising ultrasound technique that evaluates tissue elasticity and has been recently used with the purpose of diagnosis of liver fibrosis. In medicine, it is a growing concern regarding the hepatic injury of patients affected by OSA. This prospective study hypothesizes if there is any consequence of BS in the hepatic parenchyma of brachycephalic dogs that don’t receive any surgical treatment. This study was conducted following the approval of the Animal Ethics and Welfare Committee of the Faculdade de Ciências Agrárias e Veterinárias, UNESP, Campus Jaboticabal, Brazil (protocol no 17944/2017) and funded by Sao Paulo Research Foundation (FAPESP, process no 2017/24809-4). The methodology was based in ARFI elastography using the ACUSON S2000/SIEMENS device, with convex multifrequential transducer and specific software as well as clinical evaluation of the syndrome, in order to determine if they can be used as a prognostic non-invasive tool. On quantitative elastography, it was collected three measures of shear wave velocity (meters per second) and depth in centimeters in the left lateral, left medial, right lateral, right medial and caudate lobe of the liver. The brachycephalic patients, 16 pugs and 30 french bulldogs, were classified using a previously established 4-point functional grading system based on clinical evaluation before and after a 3-minute exercise tolerance test already established and validated. The control group was based on the same features collected in 22 beagles. The software R version 3.3.0 was used for the analysis and the significance level was set at 0.05. The data were analysed for normality of residuals and homogeneity of variances by Shapiro-Wilks test. Comparisons of parametric continuous variables between breeds were performed by using ANOVA with a post hoc test for pair wise comparison. The preliminary results show significant statistic differences between the brachycephalic groups and the control group in all lobes analysed (p ≤ 0,05), with higher values of shear wave velocities in the hepatic tissue of brachycephalic dogs. In this context, the results obtained in this study contributes to the understanding of BS as well as its consequences in our patients, reflecting in evidence that one more systemic consequence of the syndrome may occur in brachycephalic patients, which was not related in the veterinary literature yet.

Keywords: airway obstruction, brachycephalic airway obstructive syndrome, hepatic injury, obstructive sleep apnea

Procedia PDF Downloads 120
A Novel Hybrid Deep Learning Architecture for Predicting Acute Kidney Injury Using Patient Record Data and Ultrasound Kidney Images

Authors: Sophia Shi

Abstract:

Acute kidney injury (AKI) is the sudden onset of kidney damage in which the kidneys cannot filter waste from the blood, requiring emergency hospitalization. AKI patient mortality rate is high in the ICU and is virtually impossible for doctors to predict because it is so unexpected. Currently, there is no hybrid model predicting AKI that takes advantage of two types of data. De-identified patient data from the MIMIC-III database and de-identified kidney images and corresponding patient records from the Beijing Hospital of the Ministry of Health were collected. Using data features including serum creatinine among others, two numeric models using MIMIC and Beijing Hospital data were built, and with the hospital ultrasounds, an image-only model was built. Convolutional neural networks (CNN) were used, VGG and Resnet for numeric data and Resnet for image data, and they were combined into a hybrid model by concatenating feature maps of both types of models to create a new input. This input enters another CNN block and then two fully connected layers, ending in a binary output after running through Softmax and additional code. The hybrid model successfully predicted AKI and the highest AUROC of the model was 0.953, achieving an accuracy of 90% and F1-score of 0.91. This model can be implemented into urgent clinical settings such as the ICU and aid doctors by assessing the risk of AKI shortly after the patient’s admission to the ICU, so that doctors can take preventative measures and diminish mortality risks and severe kidney damage.

Keywords: Acute kidney injury, Convolutional neural network, Hybrid deep learning, Patient record data, ResNet, Ultrasound kidney images, VGG

Procedia PDF Downloads 137
An Automated Magnetic Dispersive Solid-Phase Extraction Method for Detection of Cocaine in Human Urine

Authors: Feiyu Yang, Chunfang Ni, Rong Wang, Yun Zou, Wenbin Liu, Chenggong Zhang, Fenjin Sun, Chun Wang

Abstract:

Cocaine is the most frequently used illegal drug globally, with the global annual prevalence of cocaine used ranging from 0.3% to 0.4 % of the adult population aged 15–64 years. Growing consumption trend of abused cocaine and drug crimes are a great concern, therefore urine sample testing has become an important noninvasive sampling whereas cocaine and its metabolites (COCs) are usually present in high concentrations and relatively long detection windows. However, direct analysis of urine samples is not feasible because urine complex medium often causes low sensitivity and selectivity of the determination. On the other hand, presence of low doses of analytes in urine makes an extraction and pretreatment step important before determination. Especially, in gathered taking drug cases, the pretreatment step becomes more tedious and time-consuming. So developing a sensitive, rapid and high-throughput method for detection of COCs in human body is indispensable for law enforcement officers, treatment specialists and health officials. In this work, a new automated magnetic dispersive solid-phase extraction (MDSPE) sampling method followed by high performance liquid chromatography-mass spectrometry (HPLC-MS) was developed for quantitative enrichment of COCs from human urine, using prepared magnetic nanoparticles as absorbants. The nanoparticles were prepared by silanizing magnetic Fe3O4 nanoparticles and modifying them with divinyl benzene and vinyl pyrrolidone, which possesses the ability for specific adsorption of COCs. And this kind of magnetic particle facilitated the pretreatment steps by electromagnetically controlled extraction to achieve full automation. The proposed device significantly improved the sampling preparation efficiency with 32 samples in one batch within 40mins. Optimization of the preparation procedure for the magnetic nanoparticles was explored and the performances of magnetic nanoparticles were characterized by scanning electron microscopy, vibrating sample magnetometer and infrared spectra measurements. Several analytical experimental parameters were studied, including amount of particles, adsorption time, elution solvent, extraction and desorption kinetics, and the verification of the proposed method was accomplished. The limits of detection for the cocaine and cocaine metabolites were 0.09-1.1 ng·mL-1 with recoveries ranging from 75.1 to 105.7%. Compared to traditional sampling method, this method is time-saving and environmentally friendly. It was confirmed that the proposed automated method was a kind of highly effective way for the trace cocaine and cocaine metabolites analyses in human urine.

Keywords: automatic magnetic dispersive solid-phase extraction, cocaine detection, magnetic nanoparticles, urine sample testing

Procedia PDF Downloads 208
Experimental Characterisation of Composite Panels for Railway Flooring

Authors: F. Pedro, S. Dias, A. Tadeu, J. António, Ó. López, A. Coelho

Abstract:

Railway transportation is considered the most economical and sustainable way to travel. However, future mobility brings important challenges to railway operators. The main target is to develop solutions that stimulate sustainable mobility. The research and innovation goals for this domain are efficient solutions, ensuring an increased level of safety and reliability, improved resource efficiency, high availability of the means (train), and satisfied passengers with the travel comfort level. These requirements are in line with the European Strategic Agenda for the 2020 rail sector, promoted by the European Rail Research Advisory Council (ERRAC). All these aspects involve redesigning current equipment and, in particular, the interior of the carriages. Recent studies have shown that two of the most important requirements for passengers are reasonable ticket prices and comfortable interiors. Passengers tend to use their travel time to rest or to work, so train interiors and their systems need to incorporate features that meet these requirements. Among the various systems that integrate train interiors, the flooring system is one of the systems with the greatest impact on passenger safety and comfort. It is also one of the systems that takes more time to install on the train, and which contributes seriously to the weight (mass) of all interior systems. Additionally, it presents a strong impact on manufacturing costs. The design of railway floor, in the development phase, is usually made relying on a design software that allows to draw and calculate several solutions in a short period of time. After obtaining the best solution, considering the goals previously defined, experimental data is always necessary and required. This experimental phase has such great significance, that its outcome can provoke the revision of the designed solution. This paper presents the methodology and some of the results of an experimental characterisation of composite panels for railway application. The mechanical tests were made for unaged specimens and for specimens that suffered some type of aging, i.e. heat, cold and humidity cycles or freezing/thawing cycles. These conditionings aim to simulate not only the time effect, but also the impact of severe environmental conditions. Both full solutions and separated components/materials were tested. For the full solution, (panel) these were: four-point bending tests, tensile shear strength, tensile strength perpendicular to the plane, determination of the spreading of water, and impact tests. For individual characterisation of the components, more specifically for the covering, the following tests were made: determination of the tensile stress-strain properties, determination of flexibility, determination of tear strength, peel test, tensile shear strength test, adhesion resistance test and dimensional stability. The main conclusions were that experimental characterisation brings a huge contribution to understand the behaviour of the materials both individually and assembled. This knowledge contributes to the increase the quality and improvements of premium solutions. This research work was framed within the POCI-01-0247-FEDER-003474 (coMMUTe) Project funded by Portugal 2020 through the COMPETE 2020.

Keywords: durability, experimental characterization, mechanical tests, railway flooring system

Procedia PDF Downloads 159
CAD Tool for Parametric Design modification of Yacht Hull Surface Models

Authors: Shahroz Khan, Erkan Gunpinar, Kemal Mart

Abstract:

Recently parametric design techniques became a vital concept in the field of Computer Aided Design (CAD), which helps to provide sophisticated platform to the designer in order to automate the design process in efficient time. In these techniques, design process starts by parameterizing the important features of design models (typically the key dimensions), with the implementation of design constraints. The design constraints help to retain the overall shape of the model while modifying its parameters. However, the process of initializing an appropriate number of design parameters and constraints is the crucial part of parametric design techniques, especially for complex surface models such as yacht hull. This paper introduces a method to create complex surface models in favor of parametric design techniques, a method to define the right number of parameters and respective design constraints, and a system to implement design parameters in contract to design constraints schema. For this, in our proposed approach the design process starts by dividing the yacht hull into three sections. Each section consists of different shape lines, which form the overall shape of yacht hull. The shape lines are created using Cubic Bezier Curves, which allow larger design flexibility. Design parameters and constraints are defined on the shape lines in 3D design space to facilitate the designers for better and individual handling of parameters. Afterwards, shape modifiers are developed, which allow the modification of each parameter while satisfying the respective set of criteria and design constraints. Such as, geometric continuities should be maintained between the shape lines of the three sections, fairness of the hull surfaces should be preserved after modification and while design modification, effect of a single parameter should be negligible on other parameters. The constraints are defined individually on shape lines of each section and mutually between the shape lines of two connecting sections. In order to validate and visualize design results of our shape modifiers, a real time graphic interface is created.

Keywords: design parameter, design constraints, shape modifies, yacht hull

Procedia PDF Downloads 303
Comparison of Two Home Sleep Monitors Designed for Self-Use

Authors: Emily Wood, James K. Westphal, Itamar Lerner

Abstract:

Background: Polysomnography (PSG) recordings are regularly used in research and clinical settings to study sleep and sleep-related disorders. Typical PSG studies are conducted in professional laboratories and performed by qualified researchers. However, the number of sleep labs worldwide is disproportionate to the increasing number of individuals with sleep disorders like sleep apnea and insomnia. Consequently, there is a growing need to supply cheaper yet reliable means to measure sleep, preferably autonomously by subjects in their own home. Over the last decade, a variety of devices for self-monitoring of sleep became available in the market; however, very few have been directly validated against PSG to demonstrate their ability to perform reliable automatic sleep scoring. Two popular mobile EEG-based systems that have published validation results, the DREEM 3 headband and the Z-Machine, have never been directly compared one to the other by independent researchers. The current study aimed to compare the performance of DREEM 3 and the Z-Machine to help investigators and clinicians decide which of these devices may be more suitable for their studies. Methods: 26 participants have completed the study for credit or monetary compensation. Exclusion criteria included any history of sleep, neurological or psychiatric disorders. Eligible participants arrived at the lab in the afternoon and received the two devices. They then spent two consecutive nights monitoring their sleep at home. Participants were also asked to keep a sleep log, indicating the time they fell asleep, woke up, and the number of awakenings occurring during the night. Data from both devices, including detailed sleep hypnograms in 30-second epochs (differentiating Wake, combined N1/N2, N3; and Rapid Eye Movement sleep), were extracted and aligned upon retrieval. For analysis, the number of awakenings each night was defined as four or more consecutive wake epochs between sleep onset and termination. Total sleep time (TST) and the number of awakenings were compared to subjects’ sleep logs to measure consistency with the subjective reports. In addition, the sleep scores from each device were compared epoch-by-epoch to calculate the agreement between the two devices using Cohen’s Kappa. All analysis was performed using Matlab 2021b and SPSS 27. Results/Conclusion: Subjects consistently reported longer times spent asleep than the time reported by each device (M= 448 minutes for sleep logs compared to M= 406 and M= 345 minutes for the DREEM and Z-Machine, respectively; both ps<0.05). Linear correlations between the sleep log and each device were higher for the DREEM than the Z-Machine for both TST and the number of awakenings, and, likewise, the mean absolute bias between the sleep logs and each device was higher for the Z-Machine for both TST (p<0.001) and awakenings (p<0.04). There was some indication that these effects were stronger for the second night compared to the first night. Epoch-by-epoch comparisons showed that the main discrepancies between the devices were for detecting N2 and REM sleep, while N3 had a high agreement. Overall, the DREEM headband seems superior for reliably scoring sleep at home.

Keywords: DREEM, EEG, seep monitoring, Z-machine

Procedia PDF Downloads 113
An Entrepreneurial Culture Led by Creativity and Innovation: Challenges and Competencies for Sri Lanka as a Middle Income Country

Authors: Tissa Ravinda Perera

Abstract:

An open economic policy was introduced by Sri Lanka in 1977, before many other countries in Asia to align her economy to world economic trends and it was affected indigenous businesses since they had to compete with foreign products, processes, technology, innovations and businesses. The year 2010 was a milestone in Sri Lankan history to achieve the developmental goals when Foxbuisness rated Sri Lanka as the best performing global economy. However, Sri Lanka missed her chances of achieving development with the political and social chaos, consequent the regime change in 2015. This paper argues that to support the development of the country, Sri Lanka must develop an entrepreneurial culture. In this endeavor, creativity and innovation will play a pivotal role to achieve the desired level of development. In this study, it was used secondary data from various local and international sources to understand and explore the existing scenario of Sri Lankan economy, state of entrepreneurial culture and innovation, and challenges and competencies for the development of an entrepreneurial culture in Sri Lanka. The data was collected from secondary sources were depicted in tables in this paper in a meaningful manner. Based on the tables many findings were aroused and conclusions were made to support the argument in this paper. This paper revealed that the development of an entrepreneurial culture has to be associated with creativity and innovation to gain a competitive advantage over the development strategies of other countries. It is exposed that an entrepreneurial culture will help minorities, women and underprivileged societies to empower themselves. This product will help to confront and manage youth unrest which has created anarchy in the country from time to time. Throughout this paper, it was highlighted the past, present and future scenario of Sri Lankan economy along with modification to be done to it through the development of an entrepreneur culture in light of innovation and creativity to achieve the desired level of development.

Keywords: economy, industry, creativity, innovation, entrepreneurship, entrepreneurial culture

Procedia PDF Downloads 183
dynr.mi: An R Program for Multiple Imputation in Dynamic Modeling

Authors: Yanling Li, Linying Ji, Zita Oravecz, Timothy R. Brick, Michael D. Hunter, Sy-Miin Chow

Abstract:

Assessing several individuals intensively over time yields intensive longitudinal data (ILD). Even though ILD provide rich information, they also bring other data analytic challenges. One of these is the increased occurrence of missingness with increased study length, possibly under non-ignorable missingness scenarios. Multiple imputation (MI) handles missing data by creating several imputed data sets, and pooling the estimation results across imputed data sets to yield final estimates for inferential purposes. In this article, we introduce dynr.mi(), a function in the R package, Dynamic Modeling in R (dynr). The package dynr provides a suite of fast and accessible functions for estimating and visualizing the results from fitting linear and nonlinear dynamic systems models in discrete as well as continuous time. By integrating the estimation functions in dynr and the MI procedures available from the R package, Multivariate Imputation by Chained Equations (MICE), the dynr.mi() routine is designed to handle possibly non-ignorable missingness in the dependent variables and/or covariates in a user-specified dynamic systems model via MI, with convergence diagnostic check. We utilized dynr.mi() to examine, in the context of a vector autoregressive model, the relationships among individuals’ ambulatory physiological measures, and self-report affect valence and arousal. The results from MI were compared to those from listwise deletion of entries with missingness in the covariates. When we determined the number of iterations based on the convergence diagnostics available from dynr.mi(), differences in the statistical significance of the covariate parameters were observed between the listwise deletion and MI approaches. These results underscore the importance of considering diagnostic information in the implementation of MI procedures.

Keywords: dynamic modeling, missing data, mobility, multiple imputation

Procedia PDF Downloads 170
Commentary on Successful and Emerging Bullying Control Programs: A Comparison between Eighteen Bullying Interventions Applied Worldwide

Authors: Sohni Siddiqui, Anja Schultze-Krumbholz

Abstract:

Our lives now revolve more around online-related tasks, as the internet has become a necessity. One of the disturbance concerns with high internet usage is the multiplication of cyber-associated risky behaviors such as cyber aggression and/or cyberbullying. Cyber Bullying is an emerging issue that needs immediate attention from many stakeholders such as parents, doctors, school administrators, policymakers, researchers, and others, especially in the COVID-19 pandemic when online learning has been adopted as an instructional strategy, and there is a continuous rise in cyberbullying cases. The aim of the article is to review existing successful and emerging interventions designed to control bullying and cyberbullying by engaging individuals through teachers’ professional development and adopting a whole-school approach. The study identified the strengths and limitations of the programs and suggested improvements to existing interventions. Preparing interventions with a strong theoretical framework, integrating applications of emerging theories in interventions, promoting proactive and reactive strategies in combination, beginning with the baseline needs assessment surveys, reducing digital time and digital divide among parents and children, promoting the concept of lead trainer, peer trainer, and hot spots, focusing on physical activities, use of landmarks are some of the recommendations proposed by authors. In addition to face-to-face intervention, the researchers recommend updating and improving previous intervention programs with games and apps. Especially in the time of pandemic crises, when face-to-face interactions are limited and cyberbullying is triggered, the use of apps, web-based interventions, and games can be an effective way to control electronic perpetration and victimization.

Keywords: anti bullying programs, cyber bullying, individualized trainings, teachers’ professional development, whole school interventions

Procedia PDF Downloads 157
Self-Organizing Maps for Credit Card Fraud Detection and Visualization

Authors: Peng Chun-Yi, Chen Wei-Hsuan, Ueng Shyh-Kuang

Abstract:

This study focuses on the application of self-organizing maps (SOM) technology in analyzing credit card transaction data, aiming to enhance the accuracy and efficiency of fraud detection. Som, as an artificial neural network, is particularly suited for pattern recognition and data classification, making it highly effective for the complex and variable nature of credit card transaction data. By analyzing transaction characteristics with SOM, the research identifies abnormal transaction patterns that could indicate potentially fraudulent activities. Moreover, this study has developed a specialized visualization tool to intuitively present the relationships between SOM analysis outcomes and transaction data, aiding financial institution personnel in quickly identifying and responding to potential fraud, thereby reducing financial losses. Additionally, the research explores the integration of SOM technology with composite intelligent system technologies (including finite state machines, fuzzy logic, and decision trees) to further improve fraud detection accuracy. This multimodal approach provides a comprehensive perspective for identifying and understanding various types of fraud within credit card transactions. In summary, by integrating SOM technology with visualization tools and composite intelligent system technologies, this research offers a more effective method of fraud detection for the financial industry, not only enhancing detection accuracy but also deepening the overall understanding of fraudulent activities.

Keywords: self-organizing map technology, fraud detection, information visualization, data analysis, composite intelligent system technologies, decision support technologies

Procedia PDF Downloads 65
Diapause Incidence in Zygogramma bicolorata Pallister Coleoptera: Chrysomelidae

Authors: Fazil Hasan, M. Shafiq Ansari, Mohammad Muslim

Abstract:

Zygogramma bicolorata Pallister (Coleoptera: Chrysomelidae) is an exotic insect and effective biocontrol agent of Parthenium hysterophorus L. (Asteraceae). Our study aimed to determine the induction and termination of diapause, in response to abiotic (temperature and moisture) and biotic factors (age and reproductive status) and the effect of diapause on adult longevity and female fecundity. The adults burrowed into the soil about 1–6 cm below the surface for diapause at any time from July to December with a peak of 70% in the 2nd week of December at Aligarh region, India. The termination of diapause took place in May and June with the commencement of monsoon rains. Non-diapausing adults were also capable of breeding during winter under laboratory conditions. There was a significantly increased in the percentage of diapaused adults in subsequent generation i.e. 4% in F1 generation and 90% in F7 generation. The percentage of diapause was also significantly increased with age of adults. It has a positive effect on female fecundity as compared to the fecundity in pre-diapaused duration. Experiments proved that soil moisture played an important role in providing the conditions for initiation and termination of diapause. The adults which undergone diapause in January and February were continuously exposed to 35º, 40º and 45º C for one week and a daily dose of 10 and 8 hours for 6 and 5 days, respectively resulting in termination of diapause. This method may be used to initiate mass multiplication for carrying out releases early in the season. Exposure of adults to extremely low temperatures i.e. 5º and 10º C induced 94.3% and 92.5% diapause, respectively with no adult mortality. Therefore, low temperatures can also be used as a medium for the storage of mass reared beetles for a long time without having negative effect on their longevity and fecundity. Thus, our findings are of great utility in the biological suppression of P. hysterophorus as it will enhance the effectiveness of this beetle through manipulation of diapause.

Keywords: Zygogramma bicolorata, environmental factors, age, sex, diapause, Parthenium hysterophorus, biocontrol

Procedia PDF Downloads 309