Search results for: secure mean and variance

Authors: N. Nalini, Bhanu Prakash Gopularam

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The term data security refers to the degree of resistance or protection given to information from unintended or unauthorized access. The core principles of information security are the confidentiality, integrity and availability, also referred as CIA triad. Cloud computing services are classified as SaaS, IaaS and PaaS services. With cloud adoption the confidential enterprise data are moved from organization premises to untrusted public network and due to this the attack surface has increased manifold. Several cloud computing platforms like OpenStack, Eucalyptus, Amazon EC2 offer users to build and configure public, hybrid and private clouds. While the traditional encryption based on PKI infrastructure still works in cloud scenario, the management of public-private keys and trust certificates is difficult. The Identity based Public Key Cryptography (also referred as ID-PKC) overcomes this problem by using publicly identifiable information for generating the keys and works well with decentralized systems. The users can exchange information securely without having to manage any trust information. Another advantage is that access control (role based access control policy) information can be embedded into data unlike in PKI where it is handled by separate component or system. In OpenStack cloud platform the keystone service acts as identity service for authentication and authorization and has support for public key infrastructure for auto services. In this paper, we explain OpenStack security architecture and evaluate the PKI infrastructure piece for data confidentiality. We provide method to integrate ID-PKC schemes for securing data while in transit and stored and explain the key measures for safe guarding data against security attacks. The proposed approach uses JPBC crypto library for key-pair generation based on IEEE P1636.3 standard and secure communication to other cloud services.

Keywords: data confidentiality, identity based cryptography, secure communication, open stack key stone, token scoping

Procedia PDF Downloads 384

Authors: Saransh Sharma, Atharv Dekhne

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Passwords stored on central services and hashed are prone to cyberattacks and hacks. Hence, given all these nuisances, there’s a need to eliminate character-based authentication protocols, which would ultimately benefit all developers as well as end-users.To replace this conventional but antiquated protocol with a secure alternative would be Passwordless Authentication. The meta root.id system creates a public and private key, of which the user is only able to access the private key. Further, after signing the key, the user sends the information over the API to the server, which checks its validity with the public key and grants access accordingly.

Keywords: passwordless, OAuth, bitcoin, ZKP, SIN, BIP

Procedia PDF Downloads 95

Authors: V. Churkin, M. Lopatin

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The purpose of the paper is to estimate the US small wind turbines market potential and forecast the small wind turbines sales in the US. The forecasting method is based on the application of the Bass model and the generalized Bass model of innovations diffusion under replacement purchases. In the work an exponential distribution is used for modeling of replacement purchases. Only one parameter of such distribution is determined by average lifetime of small wind turbines. The identification of the model parameters is based on nonlinear regression analysis on the basis of the annual sales statistics which has been published by the American Wind Energy Association (AWEA) since 2001 up to 2012. The estimation of the US average market potential of small wind turbines (for adoption purchases) without account of price changes is 57080 (confidence interval from 49294 to 64866 at P = 0.95) under average lifetime of wind turbines 15 years, and 62402 (confidence interval from 54154 to 70648 at P = 0.95) under average lifetime of wind turbines 20 years. In the first case the explained variance is 90,7%, while in the second - 91,8%. The effect of the wind turbines price changes on their sales was estimated using generalized Bass model. This required a price forecast. To do this, the polynomial regression function, which is based on the Berkeley Lab statistics, was used. The estimation of the US average market potential of small wind turbines (for adoption purchases) in that case is 42542 (confidence interval from 32863 to 52221 at P = 0.95) under average lifetime of wind turbines 15 years, and 47426 (confidence interval from 36092 to 58760 at P = 0.95) under average lifetime of wind turbines 20 years. In the first case the explained variance is 95,3%, while in the second –95,3%.

Keywords: bass model, generalized bass model, replacement purchases, sales forecasting of innovations, statistics of sales of small wind turbines in the United States

Procedia PDF Downloads 348

Authors: Ashwinder K. Dhaliwal, G. P. S. Dhillon

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Eucalyptus is one of the most important forest tree species that can tolerate and grow well on degraded and unfertile soils which are not suitable for other tree species. Besides this, these trees have a short rotation and good economic value. However, the gall inducing wasp Leptocybe invasa Fisher and La Salle has been reported from many countries throughout the world. The spread of L. invasa is of huge economic concern as more than 20,000 ha of young Eucalyptus trees have already been affected in southern states of India. The host plant resistance being the first line of defense against insect pests demands the screening of different germplasm source against L. invasa. Keeping this in view, fourteen different clones of Eucalyptus spp. were evaluated for their susceptibility to L. invasa from a replicated clonal trial planted at Punjab Agricultural University, Ludhiana. The degree of gall infestation was recorded from three plants of each clone in each replication. Three branches selected from the lower, middle and upper canopy of the trees were selected for recording the total number of galls induced by L. invasa. The statistical analysis was done as per the procedure laid down for completely randomised block design (CRBD), analysis of variance (ANOVA), critical difference (CD) and variance components using Proc GLM (SAS software 9.3, SAS Institute Ltd. U.S.A). All possible treatment means were compared with Duncan’s multiple range test (DMRT) at 1 % probability level. The results showed that the clones C-9, C-45 and C-42 were completely free from the infestation of L. invasa. However, there was minor infestation of L. invasa on C-2135, C-413, C-407, C-35, C-72 and C-37 clones. The clone C-6 was severely infested by L. invasa followed by C-11, C-12, F-316 and C-25 clones. The information generated by this study will be helpful for future breeding and use in afforestation programmes.

Keywords: eucalyptus clones, gall wasp, Leptocybe invasa, screening, susceptibility

Procedia PDF Downloads 221

Authors: Nasibeh Mohammadpour, Ali Rajabzadeh, Adel Azar, Hamid Zargham Borujeni,

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Generally, various industries development depends on their stakeholders and beneficiaries supports. One of the most important stakeholders in tourism industry ( which has become one of the most important lucrative and employment-generating activities at the international level these days) are host communities in tourist destination which are affected and effect on this industry development. Recognizing host community and its segmentations can be important to get their support for future decisions and policy making. In order to identify these segments, in this study, clustering of the residents has been done by using some tools that are designed to encounter human complexities and have ability to model and generalize complex systems without any needs for the initial clusters’ seeds like classic methods. Neural networks can help to meet these expectations. The research have been planned to design neural networks-based mathematical model for clustering the host community effectively according to multi criteria, and identifies differences among segments. In order to achieve this goal, the residents’ segmentation has been done by demographic characteristics, their attitude towards the tourism development, the level of satisfaction and the type of their support in this field. The applied method is self-organized neural networks and the results have compared with K-means. As the results show, the use of Self- Organized Map (SOM) method provides much better results by considering the Cophenetic correlation and between clusters variance coefficients. Based on these criteria, the host community is divided into five sections with unique and distinctive features, which are in the best condition (in comparison other modes) according to Cophenetic correlation coefficient of 0.8769 and between clusters variance of 0.1412.

Keywords: Artificial Nural Network, Clustering , Resident, SOM, Tourism

Procedia PDF Downloads 183

Authors: Fatih Ercin Guney, Hami Karagol

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Day by day, humanity's energy needs increase, to facilitate access to energy sources by energy importing countries is of great importance in terms of issues both in terms of economic security and political security. The geographical location of the oil exporting countries in the Middle East (Iran, Iraq, Kuwait, Libya, Saudi Arabia, United Arab Emirates, Qatar) today, it is observed that evaluated by emerging Arab Spring(from Tunisia to Egypt) and freedom battles(in Syria) with security issues arise sourced from terrorist activities(ISIS). Progresses related with limited natural resources, energy and it's transportation issues which worries the developing countries, the energy in the region is considered to how to transfer safely. North Region of the Black Sea , the beginning of the conflict in the regional nature formed between Russia and Ukraine (2010), followed by the relevant regions of the power transmission line (From Russia to Europe) the discovery is considered to be the east's hand began to strengthen in terms of both the economical and political sides. With the growing need for safe access to the west of the new energy transmission lines are followed by Turkey, re-interest is considered to be shifted to the Mediterranean and the Middle East by West. Also, Russia, Iran and China (three axis of east) are generally performing as carry out parallel policies about energy , economical side and security in both United Nations Security Council (Two of Five Permanent Members are Russia and China) and Shanghai Cooperation Organization. In addition, Eastern Mediterranean Region Tension are rapidly increasing about research new oil and natural gas sources by Israel, Egypt, Cyprus, Lebanon. This paper provides, new energy corridor(s) are needed to transfer sources (Oil&Natural Gas) by Europe from East to West. So The West needs either safe bridge country to transfer natural sources to Europe in region or is needed to discovery new natural sources in extraterritorial waters of Eastern Mediterranean Region. But in two opportunities are evaluated with secure transfer corridors form region to Europe in safely. Even if the natural sources can be discovered, they are considered to transfer in safe manner. This paper involved, Turkey’s importance as a leader country in region over both of political and safe energy transfer sides as bridge country between south and north of Turkey why natural sources shall be transferred over Turkey, Even if diplomatic issues-For Example; Cyprus membership in European Union, Turkey membership candidate duration, Israel-Cyprus- Egypt-Lebanon researches about new natural sources in Mediterranean - occurred. But politic balance in Middle-East is changing quickly because of lack of democratic governments in region. So it is evaluated that the alliance of natural sources researches may not be long-time relations due to share sources after discoveries. After evaluating over causes and reasons, aim to reach finding foresight about future of region for energy transfer periods in secure manner.

Keywords: Middle East, natural gas, oil, Turkey

Procedia PDF Downloads 297

Authors: Vahab Behmanesh

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Metabolic syndrome is defined as having at least three of the five metabolic risk factors, including abdominal obesity, high blood pressure, high triglycerides, low HDL, and insulin resistance. Lifestyle changes towards reducing physical activity, unhealthy eating habits Especially the high-fat and high-carbohydrate diet is directly related to metabolic syndrome, and due to the epidemic of overweight and sedentary life, metabolic syndrome is a serious problem worldwide. On the other hand, vitamin D deficiency is considered as one of the most common problems in the world, which is related to the dysfunction of beta cells and insulin resistance, and therefore, vitamin D deficiency is considered as a factor in the occurrence of metabolic syndrome. 40 subjects (age: 16.12 ± 4.4 years and body mass index 25.61 ± 4.4 kg/m2) were randomly assigned to groups of aerobic exercise and placebo, aerobic exercise and vitamin D and placebo (no exercise) were divided. Vitamin D was taken at a dose of 50,000 units per week in a double-blind format for eight weeks, and the daily aerobic exercise program was performed for 50 to 60 minutes, three doses per week, with an intensity of 50-60% of the maximum heart rate. From one-way analysis of variance, Factorial variance analysis (2x2) repeated measurement and correlated t-test were used for data analysis. Aerobic exercise and vitamin D intake reduced all metabolic risk indicators and blood insulin (P < 0.05). However, the subjective feeling of hunger did not change significantly (P < 0.05). Regarding waist circumference and blood glucose, the effect of exercise combined with vitamin D consumption was greater than the corresponding effect in the vitamin D group (P < 0.05). Aerobic exercises and vitamin D intake are safe and effective for improving cardiometabolic health, Imam adds vitamin D to the exercise program has more benefits for weight and blood sugar control, which suggests prescribing it for patients with metabolic syndrome.

Keywords: vitamin D, aerobic exercise, metabolic control, adolescents

Procedia PDF Downloads 101

Authors: Hind Bouami, Patrick Millot

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Medication dispensing system is a life-critical system whose failure may result in preventable adverse events leading to longer patient stays in hospitals or patient death. Automation has led to great improvements in life-critical systems as it increased safety, efficiency, and comfort. However, critical risks related to medical organization complexity and automated solutions integration can threaten drug dispensing security and performance. Knowledge about the system’s complexity aspects and human machine parameters to control for automated equipment’s security and performance will help operators to secure their automation process and to optimize their system’s reliability. In this context, this study aims to document the operator’s situation awareness about automation risks and parameters involved in automation security and performance. Our risk management approach has been deployed in the North Luxembourg hospital center’s pharmacy, which is equipped with automated drug dispensing systems since 2009. With more than 4 million euros of gains generated, North Luxembourg hospital center’s success story was enabled by the management commitment, pharmacy’s involvement in the implementation and improvement of the automation project, and the close collaboration between the pharmacy and Sinteco’s firm to implement the necessary innovation and organizational actions for automated solutions integration security and performance. An analysis of the actions implemented by the hospital and the parameters involved in automated equipment’s integration security and performance has been made. The parameters to control for automated equipment’s integration security and performance are human aspects (6.25%), technical aspects (50%), and human-machine interaction (43.75%). The implementation of an anthropocentric analysis system before automation would have prevented and optimized the control of risks related to automation.

Keywords: Automated drug delivery systems, Hospitals, Human-centered automated system, Risk management

Procedia PDF Downloads 137

Authors: Wajeeha Shahid

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The study was designed to assess the impact of transformational and transactional leadership styles on work motivation and organizational commitment among faculty members of universities of Punjab. 713 faculty members were selected as sample through convenient random sampling technique. Three self-constructed questionnaires namely Leadership Styles Questionnaire (LSQ), Work Motivation Questionnaire (WMQ) and Organizational Commitment Questionnaire (OCMQ) were used as research instruments. Major objectives of the study included assessing the effect and impact of transformational and transactional leadership styles on work motivation and organizational commitment. Theoretical frame work of the study included Idealized Influence, Inspirational Motivation, Intellectual Stimulation, Individualized Consideration, Contingent Rewards and Management by Exception as independent variables and Extrinsic motivation, Intrinsic motivation, Affective commitment, Continuance commitment and Normative commitment as dependent variables. SPSS Version 21 was used to analyze and tabulate data. Cronbach's Alpha reliability, Pearson Correlation and Multiple regression analysis were applied as statistical treatments for the analysis. Results revealed that Idealized Influence correlated significantly with intrinsic motivation and Affective commitment whereas Contingent rewards had a strong positive correlation with extrinsic motivation and affective commitment. Multiple regression models revealed a variance of 85% for transformational leadership style over work motivation and organizational commitment. Whereas transactional style as a predictor manifested a variance of 79% for work motivation and 76% for organizational commitment. It was suggested that changing organizational cultures are demanding more from their leadership. All organizations need to consider transformational leadership style as an important part of their equipment in leveraging both soft and hard organizational targets.

Keywords: leadership styles, work motivation, organizational commitment, faculty member

Procedia PDF Downloads 308

Authors: Carlos Gonzalez

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When communicating using private and secure keys, there is always the doubt as to the identity of the message creator. We introduce an algorithm that uses the personal typing rhythm (keystroke dynamics) of the message originator to increase the trust of the authenticity of the message originator by the message recipient. The methodology proposes the use of a Rhythm Certificate Authority (RCA) to validate rhythm information. An illustrative example of the communication between Bob and Alice and the RCA is included. An algorithm of how to communicate with the RCA is presented. This RCA can be an independent authority or an enhanced Certificate Authority like the one used in public key infrastructure (PKI).

Keywords: authentication, digital signature, keystroke dynamics, personal rhythm, public-key encryption

Procedia PDF Downloads 304

Authors: Akhtar Nawaz, Sahar Noor, Iftikhar Hussain

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This paper considers advanced hybrid manufacturing planning both push and pull system in which each customer order has a due date by demand forecast and customer orders. We present a tool for model for tool development that requires an absolute due dates and customer orders in a manufacturing supply chain. It is vital for the manufacturing companies to face the problem of variations in demands, increase in varieties by maintaining safety stock and to minimize components obsolescence and uselessness. High inventory cost and low delivery lead time is expected in push type of system and on contrary high delivery lead time and low inventory cost is predicted in the pull type. For this tool for model we need an MRP system for the push and pull environment and control of inventories in push parts and lead time in the pull part. To retain process data quickly, completely and to improve responsiveness and minimize inventory cost, a tool is required to deal with the high product variance and short cycle parts. In practice, planning and scheduling are interrelated and should be solved simultaneously with supply chain to ensure that the due dates of customer orders are met. The proposed tool for model considers alternative process plans for job types, with precedence constraints for job operations. Such a tool for model has not been treated in the literature. To solve the model, tool was developed, so a new technique was required to deal with the issue of high product variance and short life cycles in assemble to order.

Keywords: hybrid manufacturing system, supply chain system, make to order, make to stock, assemble to order

Procedia PDF Downloads 564

Authors: Sharon Jackson White

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Purpose: Nurse practitioners (NPs) practicing within hospital medicine play a significant role in caring for patients who might benefit from palliative care (PC) services. Using the Theory of Planned Behavior, the purpose of this study was to examine the relationships among facilitators to referral, barriers to referral, self-efficacy with end-of-life discussions, history of referral, and referring to PC among NPs in hospital medicine. Hypotheses: 1) Perceived facilitators to referral will be associated with a higher history of referral and a higher number of referrals to PC. 2) Perceived barriers to referral will be associated with a lower history of referral and a lower number of referrals to PC. 3) Increased self-efficacy with end-of-life discussions will be associated with a higher history of referral and a higher number of referrals to PC. 4) Perceived facilitators to referral, perceived barriers to referral, and self–efficacy with end-of-life discussions will contribute to a significant variance in the history of referral to PC. 5) Perceived facilitators to referral, perceived barriers to referral, and self–efficacy with end-of-life discussions will contribute to a significant variance in the number of referrals to PC. Significance: Previous studies of referring patients to PC within the hospital setting care have focused on physician practices. Identifying factors that influence NPs referring hospitalized patients to PC is essential to ensure that patients have access to these important services. This study incorporates the SNRS mission of advancing nursing research through the dissemination of research findings and the promotion of nursing science. Methods: A cross-sectional, predictive correlational study was conducted. History of referral to PC, facilitators to referring to PC, barriers to referring to PC, self-efficacy in end-of-life discussions, and referral to PC were measured using the PC referral case study survey, facilitators and barriers to PC referral survey, and self-assessment with end-of-life discussions survey. Data were analyzed descriptively and with Pearson’s Correlation, Spearman’s Rho, point-biserial correlation, multiple regression, logistic regression, Chi-Square test, and the Mann-Whitney U test. Results: Only one facilitator (PC team being helpful with establishing goals of care) was significantly associated with referral to PC. Three variables were statistically significant in relation to the history of referring to PC: “Inclined to refer: PC can help decrease the length of stay in hospital”, “Most inclined to refer: Patients with serious illnesses and/or poor prognoses”, and “Giving bad news to a patient or family member”. No predictor variables contributed a significant variance in the number of referrals to PC for all three case studies. There were no statistically significant results showing a relationship between the history of referral and referral to PC. All five hypotheses were partially supported. Discussion: Findings from this study emphasize the need for further research on NPs who work in hospital settings and what factors influence their behaviors of referring to PC. Since there is an increase in NPs practicing within hospital settings, future studies should use a larger sample size and incorporate hospital medicine NPs and other types of NPs that work in hospitals.

Keywords: palliative care, nurse practitioners, hospital medicine, referral

Procedia PDF Downloads 73

Authors: Iffat Ara Ebu, Fahmida Islam, Mohammad Abdus Shahid Rafi, Mahfuzur Rahman, Umar Iqbal, John Ball

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The application of multi-sensor fusion for enhanced distance estimation accuracy in dynamic environments is crucial for advanced driver assistance systems (ADAS) and autonomous vehicles. Limitations of single sensors such as cameras or radar in adverse conditions motivate the use of combined camera and radar data to improve reliability, adaptability, and object recognition. A multi-sensor fusion approach using an extended Kalman filter (EKF) is proposed to combine sensor measurements with a dynamic system model, achieving robust and accurate distance estimation. The research utilizes the Mississippi State University Autonomous Vehicular Simulator (MAVS) to create a controlled environment for data collection. Data analysis is performed using MATLAB. Qualitative (visualization of fused data vs ground truth) and quantitative metrics (RMSE, MAE) are employed for performance assessment. Initial results with simulated data demonstrate accurate distance estimation compared to individual sensors. The optimal sensor measurement noise variance and plant noise variance parameters within the EKF are identified, and the algorithm is validated with real-world data from a Chevrolet Blazer. In summary, this research demonstrates that multi-sensor fusion with an EKF significantly improves distance estimation accuracy in dynamic environments. This is supported by comprehensive evaluation metrics, with validation transitioning from simulated to real-world data, paving the way for safer and more reliable autonomous vehicle control.

Keywords: sensor fusion, EKF, MATLAB, MAVS, autonomous vehicle, ADAS

Procedia PDF Downloads 43

Authors: Rasaq Bolakale Salau, Maimuna Muhammad Abubakar, Jonathan Yisa, Muhammad Tauheed Bisiriyu, Jimoh Oladejo Tijani, Alexander Ifeanyi Ajai

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Vegetables oils are widely consumed in Nigeria. This has led to competitive manufacture of various oil brands. This leads increasing tendencies for fraud, labelling misinformation and other unwholesome practices. A total of thirty samples including raw and corresponding branded samples of vegetable oils were collected. The Oils were extracted from raw ground nut, soya bean and oil palm fruits. The GC-MS data was subjected to chemometric techniques of PCA and HCA. The SOLO 8.7 version of the standalone chemometrics software developed by Eigenvector research incorporated and powered by PLS Toolbox was used. The GCMS fingerprint gave basis for discrimination as it reveals four predominant but unevenly distributed fatty acids: Hexadecanoic acid methyl ester (10.27- 45.21% PA), 9,12-octadecadienoic acid methyl ester (10.9 - 45.94% PA), 9-octadecenoic acid methyl ester (18.75 - 45.65%PA), and Eicosanoic acid methyl ester (1.19% - 6.29%PA). In PCA modelling, two PCs are retained at cumulative variance captured at 73.15%. The score plots indicated that palm oil brands are most aligned with raw palm oil. PCA loading plot reveals the signature retention times between 4.0 and 6.0 needed for quality assurance and authentication of the oils samples. They are of aromatic hydrocarbons, alcohols and aldehydes functional groups. HCA dendrogram which was modeled using Euclidian distance through Wards method, indicated co-equivalent samples. HCA revealed the pair of raw palm oil brand and palm oil brand in the closest neighbourhood (± 1.62 % A difference) based on variance weighted distance. It showed Palm olein brand to be most authentic. In conclusion, based on the GCMS data with chemometrics, the authenticity of the branded samples is ranked as: Palm oil > Soya oil > groundnut oil.

Keywords: vegetable oil, authenticity, chemometrics, PCA, HCA, GC-MS

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Authors: Osman Zorbaz, Selen Demirtas-Zorbaz, Ozlem Ulas

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The factors that cause adolescents to drop out school were several. One of the frameworks about school dropout focuses on the contextual factors around the adolescents whereas the other one focuses on individual factors. It can be said that both factors are important equally. In this study, both adolescent’s individual factors (anti-social behaviors, academic success) and contextual factors (parent academic involvement, parent academic support, number of siblings, living with parent) were examined in the term of school dropout. The study sample consisted of 346 high school students in the public schools in Ankara who continued their education in 2015-2016 academic year. One hundred eighty-five the students (53.5%) were girls and 161 (46.5%) were boys. In addition to this 118 of them were in ninth grade, 122 of them in tenth grade and 106 of them were in eleventh grade. Multiple regression and one-way ANOVA statistical methods were used. First, it was examined if the data meet the assumptions and conditions that are required for regression analysis. After controlling the assumptions, regression analysis was conducted. Parent academic involvement, parent academic support, number of siblings, anti-social behaviors, academic success variables were taken into the regression model and it was seen that parent academic involvement (t=-3.023, p < .01), anti-social behaviors (t=7.038, p < .001), and academic success (t=-3.718, p < .001) predicted school dropout whereas parent academic support (t=-1.403, p > .05) and number of siblings (t=-1.908, p > .05) didn’t. The model explained 30% of the variance (R=.557, R2=.300, F5,345=30.626, p < .001). In addition to this the variance, results showed there was no significant difference on high school students school dropout levels according to living with parents or not (F2;345=1.183, p > .05). Results discussed in the light of the literature and suggestion were made. As a result, academic involvement, academic success and anti-social behaviors will be considered as an important factors for preventing school drop-out.

Keywords: adolescents, anti-social behavior, parent academic involvement, parent academic support, school dropout

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Authors: Utkarsh A. Mishra, Ankit Bansal

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At high temperature, radiative heat transfer is the dominant mode of heat transfer. It is governed by various phenomena such as photon emission, absorption, and scattering. The solution of the governing integrodifferential equation of radiative transfer is a complex process, more when the effect of participating medium and wavelength properties are taken into consideration. Although a generic formulation of such radiative transport problem can be modeled for a wide variety of problems with non-gray, non-diffusive surfaces, there is always a trade-off between simplicity and accuracy of the problem. Recently, solutions of complicated mathematical problems with statistical methods based on randomization of naturally occurring phenomena have gained significant importance. Photon bundles with discrete energy can be replicated with random numbers describing the emission, absorption, and scattering processes. Photon Monte Carlo (PMC) is a simple, yet powerful technique, to solve radiative transfer problems in complicated geometries with arbitrary participating medium. The method, on the one hand, increases the accuracy of estimation, and on the other hand, increases the computational cost. The participating media -generally a gas, such as CO₂, CO, and H₂O- present complex emission and absorption spectra. To model the emission/absorption accurately with random numbers requires a weighted sampling as different sections of the spectrum carries different importance. Importance sampling (IS) was implemented to sample random photon of arbitrary wavelength, and the sampled data provided unbiased training of MC estimators for better results. A better replacement to uniform random numbers is using deterministic, quasi-random sequences. Halton, Sobol, and Faure Low-Discrepancy Sequences are used in this study. They possess better space-filling performance than the uniform random number generator and gives rise to a low variance, stable Quasi-Monte Carlo (QMC) estimators with faster convergence. An optimal supervised learning scheme was further considered to reduce the computation costs of the PMC simulation. A one-dimensional plane-parallel slab problem with participating media was formulated. The history of some randomly sampled photon bundles is recorded to train an Artificial Neural Network (ANN), back-propagation model. The flux was calculated using the standard quasi PMC and was considered to be the training target. Results obtained with the proposed model for the one-dimensional problem are compared with the exact analytical and PMC model with the Line by Line (LBL) spectral model. The approximate variance obtained was around 3.14%. Results were analyzed with respect to time and the total flux in both cases. A significant reduction in variance as well a faster rate of convergence was observed in the case of the QMC method over the standard PMC method. However, the results obtained with the ANN method resulted in greater variance (around 25-28%) as compared to the other cases. There is a great scope of machine learning models to help in further reduction of computation cost once trained successfully. Multiple ways of selecting the input data as well as various architectures will be tried such that the concerned environment can be fully addressed to the ANN model. Better results can be achieved in this unexplored domain.

Keywords: radiative heat transfer, Monte Carlo Method, pseudo-random numbers, low discrepancy sequences, artificial neural networks

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Authors: Dibakar Sahoo, Sridevi Gummadi

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The focus of the study is to empirically analyse the climatic impacts on foodgrain yield and its variability across seasons and altitudes in Odisha, one of the most vulnerable states in India. The study uses Just-Pope Stochastic Production function by using two-step Feasible Generalized Least Square (FGLS): mean equation estimation and variance equation estimation. The study uses the panel data on foodgrain yield, rainfall and temperature for 13 districts during the period 1984-2013. The study considers four seasons: winter (December-February), summer (March-May), Rainy (June-September) and autumn (October-November). The districts under consideration have been categorized under three altitude regions such as low (< 70 masl), middle (153-305 masl) and high (>305 masl) altitudes. The results show that an increase in the standard deviations of monthly rainfall during rainy and autumn seasons have an adversely significant impact on the mean yield of foodgrains in Odisha. The summer temperature has beneficial effects by significantly increasing mean yield as the summer season is associated with harvesting stage of Rabi crops. The changing pattern of temperature has increasing effect on the yield variability of foodgrains during the summer season, whereas it has a decreasing effect on yield variability of foodgrains during the Rainy season. Moreover, the positive expected signs of trend variable in both mean and variance equation suggests that foodgrain yield and its variability increases with time. On the other hand, a change in mean levels of rainfall and temperature during different seasons has heterogeneous impacts either harmful or beneficial depending on the altitudes. These findings imply that adaptation strategies should be tailor-made to minimize the adverse impacts of climate change and variability for sustainable development across seasons and altitudes in Odisha agriculture.

Keywords: altitude, adaptation strategies, climate change, foodgrain

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Authors: Diego Luján Villarreal

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Visual prostheses are designed to repair some eyesight in patients blinded by photoreceptor diseases, such as retinitis pigmentosa (RP) and age-related macular degeneration (AMD). Electrode-to-cell proximity has drawn attention due to its implications on secure single-localized stimulation. Yet, few techniques are available for understanding the relationship between the number of cells activated and the current injection. We propose an answering technique by solving the governing equation for time-dependent electrical currents using finite element discretization to obtain the volume of stimulation.

Keywords: visual prosthetic devices, volume for stimulation, FEM discretization, 3D simulation

Procedia PDF Downloads 73

Authors: Mukisa Simon Peter Turker, Etomaru Irene

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This study examined factors determining the success of University-Industry Collaboration (UIC) in the science academic units (SAUs) at Makerere University. This was prompted by concerns about weak linkages between industry and the academic units at Makerere University. The study examined institutional, relational, output, and framework factors determining the success of UIC in the science academic units at Makerere University. The study adopted a predictive cross-sectional survey design. Data was collected using a questionnaire survey from 172 academic staff from the six SAUs at Makerere University. Stratified, proportionate, and simple random sampling techniques were used to select the samples. The study used descriptive statistics and linear multiple regression analysis to analyze data. The study findings reveal a coefficient of determination (R-square) of 0.403 at a significance level of 0.000, suggesting that UIC success was 40.3% at a standardized error of estimate of 0.60188. The strength of association between Institutional factors, Relational factors, Output factors, and Framework factors, taking into consideration all interactions among the study variables, was at 64% (R= 0.635). Institutional, Relational, Output and Framework factors accounted for 34% of the variance in the level of UIC success (adjusted R2 = 0.338). The remaining variance of 66% is explained by factors other than Institutional, Relational, Output, and Framework factors. The standardized coefficient statistics revealed that Relational factors (β = 0.454, t = 5.247, p = 0.000) and Framework factors (β = 0.311, t = 3.770, p = 0.000) are the only statistically significant determinants of the success of UIC in the SAU in Makerere University. Output factors (β = 0.082, t =1.096, p = 0.275) and Institutional factors β = 0.023, t = 0.292, p = 0.771) turned out to be statistically insignificant determinants of the success of UIC in the science academic units at Makerere University. The study concludes that Relational Factors and Framework Factors positively and significantly determine the success of UIC, but output factors and institutional factors are not statistically significant determinants of UIC in the SAUs at Makerere University. The study recommends strategies to consolidate Relational and Framework Factors to enhance UIC at Makerere University and further research on the effects of Institutional and Output factors on the success of UIC in universities.

Keywords: university-industry collaboration, output factors, relational factors, framework factors, institutional factors

Procedia PDF Downloads 61

Authors: Julia Yi

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Using the Household Pulse Survey conducted by the U.S Census Bureau, this study finds that the pandemic increased the prevalence and inequality of food insecurity among US households. About 28% of households were food secure, which doubled the 2019 level. Hispanic and black, low-income households, households lost income, and households with children were impacted most. Food banks provided most free groceries and meals. This study recommends mobilizing emergency food organizations, improving food assistance programs and supply chains, and creating innovative community support.

Keywords: covid-19 pandemic, food insecurity, US, inequality

Procedia PDF Downloads 142

Authors: Hailye Tekleselassie

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Edge computing is a spread computing outline that transports initiative applications closer to data sources such as IoT devices or local edge servers, and possible happenstances would skull the action of new technologies. However, this investigation was attained to investigation the consciousness of technology and communications organization workers and computer users who support the service cloud. Surveys were used to achieve these objectives. Surveys were intended to attain these aims, and it is the functional using survey. Enquiries about confidence are also a key question. Problems like data privacy, integrity, and availability are the factors affecting the company’s acceptance of the service cloud.

Keywords: IoT, data, security, edge computing

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Authors: Yavuz Erdoğan, Hidayet Çiftçi

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Cyberbullying, a phenomenon among adolescents, is defined as actions that use information and communication technologies such as social media to support deliberate, repeated, and hostile behaviour by an individual or group. With the advancement in communication and information technology, cyberbullying has expanded its boundaries among students in schools. Thus, parents, psychologists, educators, and lawmakers must become aware of the potential risks of this phenomenon. In the light of these perspectives, this study aims to investigate the relationships between cyberbullying perception and Facebook attitudes of Turkish students. A survey method was used for the study and the data were collected by “Cyberbullying Perception Scale”, “Facebook Attitude Scale” and “Personal Information Form”. For this purpose, study has been conducted during 2014-2015 academic year, with a total of 748 students with 493 male (%65.9) and 255 female (%34.1) from randomly selected high schools. In the analysis of data Pearson correlation and multiple regression analysis, multivariate analysis of variance (MANOVA) and Scheffe post hoc test has been used. At the end of the study, the results displayed a negative correlation between Turkish students’ Facebook attitudes and cyberbullying perception (r=-.210; p<0.05). In order to identify the predictors of students’ cyberbullying perception, multiple regression analysis was used. As a result, significant relations were detected between cyberbullying perception and independent variables (F=5.102; p<0.05). Independent variables together explain 11.0% of the total variance in cyberbullying scores. The variables that significantly predict the students’ cyberbullying perception are Facebook attitudes (t=-5.875; p<0.05), and gender (t=3.035; p<0.05). In order to calculate the effects of independent variables on students’ Facebook attitudes and cyberbullying perception MANOVA was conducted. The results of the MANOVA indicate that the Facebook attitudes and cyberbullying perception were significantly differed according to students’ gender, age, educational attainment of the mother, educational attainment of the father, income of the family and daily usage of internet.

Keywords: facebook, cyberbullying, attitude, internet usage

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Authors: Aneesh Mathew, Arunab K. S., Atul Kumar Sharma

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The uncontrolled rise in population has led to unplanned, swift, and unsustainable urban expansion, causing detrimental environmental impacts on both local and global ecosystems. This research delves into a comprehensive examination of the Urban Heat Island (UHI) phenomenon in Bengaluru and Hyderabad, India. It centers on the spatial and temporal distribution of UHI and its correlation with air pollutants. Conducted across summer and winter seasons from 2001 to 2021 in Bangalore and Hyderabad, this study discovered that UHI intensity varies seasonally, peaking in summer and decreasing in winter. The annual maximum UHI intensities range between 4.65 °C to 6.69 °C in Bengaluru and 5.74 °C to 6.82 °C in Hyderabad. Bengaluru particularly experiences notable fluctuations in average UHI intensity. Introducing the Urban Thermal Field Variance Index (UTFVI), the study indicates a consistent strong UHI effect in both cities, significantly impacting living conditions. Moreover, hotspot analysis demonstrates a rising trend in UHI-affected areas over the years in Bengaluru and Hyderabad. This research underscores the connection between air pollutant concentrations and land surface temperature (LST), highlighting the necessity of comprehending UHI dynamics for urban environmental management and public health. It contributes to a deeper understanding of UHI patterns in swiftly urbanizing areas, providing insights into the intricate relationship between urbanization, climate, and air quality. These findings serve as crucial guidance for policymakers, urban planners, and researchers, facilitating the development of innovative, sustainable strategies to mitigate the adverse impacts of uncontrolled expansion while promoting the well-being of local communities and the global environment.

Keywords: urban heat island effect, land surface temperature, air pollution, urban thermal field variance index

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Authors: Mathew Wakefield, Matthew Mitchell, Lisa Wise, Christopher McCarthy

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The properties of memory representations in artificial neural networks have cognitive implications. Distributed representations that encode instances as a pattern of activity across layers of nodes afford memory compression and enforce the selection of a single point in instance space. These encoding schemes also appear to distort the representational space, as well as trading off the ability to validate that input information is within the bounds of past experience. In contrast, a localist representation which encodes some meaningful information into individual nodes in a network layer affords less memory compression while retaining the integrity of the representational space. This allows the validity of an input to be determined. The validity (or familiarity) of input along with the capacity of localist representation for multiple instance selections affords a memory sampling approach that dynamically balances the bias-variance trade-off. When the input is familiar, bias may be high by referring only to the most similar instances in memory. When the input is less familiar, variance can be increased by referring to more instances that capture a broader range of features. Using this approach in a localist instance memory network, an experiment demonstrates a relationship between representational conflict, generalization performance, and memorization demand. Relatively small sampling ranges produce the best performance on a classic machine learning dataset of visual objects. Combining memory validity with conflict detection produces a reliable confidence judgement that can separate responses with high and low error rates. Confidence can also be used to signal the need for supervisory input. Using this judgement, the need for supervised learning as well as memory encoding can be substantially reduced with only a trivial detriment to classification performance.

Keywords: artificial neural networks, representation, memory, conflict monitoring, confidence

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Authors: Alexander Rych

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Piql Preservation Services (“Piql”) is a turnkey solution designed for secure, migration-free long- term preservation of digital data. Piql sets an open standard for long- term preservation for the future. It consists of equipment and processes needed for writing and retrieving digital data. Exponentially growing amounts of data demand for logistically effective and cost effective processes. Digital storage media (hard disks, magnetic tape) exhibit limited lifetime. Repetitive data migration to overcome rapid obsolescence of hardware and software bears accelerated risk of data loss, data corruption or even manipulation and adds significant repetitive costs for hardware and software investments. Piql stores any kind of data in its digital as well as analog form securely for 500 years. The medium that provides this is a film reel. Using photosensitive film polyester base, a very stable material that is known for its immutability over hundreds of years, secure and cost-effective long- term preservation can be provided. The film reel itself is stored in a packaging capable of protecting the optical storage medium. These components have undergone extensive testing to ensure longevity of up to 500 years. In addition to its durability, film is a true WORM (write once- read many) medium. It therefore is resistant to editing or manipulation. Being able to store any form of data onto the film makes Piql a superior solution for long-term preservation. Paper documents, images, video or audio sequences – all of those file formats and documents can be preserved in its native file structure. In order to restore the encoded digital data, only a film scanner, a digital camera or any appropriate optical reading device will be needed in the future. Every film reel includes an index section describing the data saved on the film. It also contains a content section carrying meta-data, enabling users in the future to rebuild software in order to read and decode the digital information.

Keywords: digital data, long-term preservation, migration-free, photosensitive film

Procedia PDF Downloads 392

Authors: Jaemyoung Lee

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We present a method to set up system functions through a near filed communication (NFC) of a smartphone. The short communication distance of the NFC which is usually less than 4 cm could prevent any interferences from other devices and establish a secure communication channel between a system and the smartphone. The proposed set-up method for system function values is demonstrated for a blacbox system in a car. In demonstration, system functions of a blackbox which is manipulated through NFC of a smartphone are controls of image quality, sound level, shock sensing level to store images, etc. The proposed set-up method for system function values can be used for any devices with NFC.

Keywords: system set-up, near field communication, smartphone, android

Procedia PDF Downloads 336

Authors: Yildiz Stella Dak, Jale Tezcan

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Ground motion models that relate a strong motion parameter of interest to a set of predictive seismological variables describing the earthquake source, the propagation path of the seismic wave, and the local site conditions constitute a critical component of seismic hazard analyses. When a sufficient number of strong motion records are available, ground motion relations are developed using statistical analysis of the recorded ground motion data. In regions lacking a sufficient number of recordings, a synthetic database is developed using stochastic, theoretical or hybrid approaches. Regardless of the manner the database was developed, ground motion relations are developed using regression analysis. Development of a ground motion relation is a challenging process which inevitably requires the modeler to make subjective decisions regarding the inclusion criteria of the recordings, the functional form of the model and the set of seismological variables to be included in the model. Because these decisions are critically important to the validity and the applicability of the model, there is a continuous interest on procedures that will facilitate the development of ground motion models. This paper proposes the use of the Least Absolute Shrinkage and Selection Operator (LASSO) in selecting the set predictive seismological variables to be used in developing a ground motion relation. The LASSO can be described as a penalized regression technique with a built-in capability of variable selection. Similar to the ridge regression, the LASSO is based on the idea of shrinking the regression coefficients to reduce the variance of the model. Unlike ridge regression, where the coefficients are shrunk but never set equal to zero, the LASSO sets some of the coefficients exactly to zero, effectively performing variable selection. Given a set of candidate input variables and the output variable of interest, LASSO allows ranking the input variables in terms of their relative importance, thereby facilitating the selection of the set of variables to be included in the model. Because the risk of overfitting increases as the ratio of the number of predictors to the number of recordings increases, selection of a compact set of variables is important in cases where a small number of recordings are available. In addition, identification of a small set of variables can improve the interpretability of the resulting model, especially when there is a large number of candidate predictors. A practical application of the proposed approach is presented, using more than 600 recordings from the National Geospatial-Intelligence Agency (NGA) database, where the effect of a set of seismological predictors on the 5% damped maximum direction spectral acceleration is investigated. The set of candidate predictors considered are Magnitude, Rrup, Vs30. Using LASSO, the relative importance of the candidate predictors has been ranked. Regression models with increasing levels of complexity were constructed using one, two, three, and four best predictors, and the models’ ability to explain the observed variance in the target variable have been compared. The bias-variance trade-off in the context of model selection is discussed.

Keywords: ground motion modeling, least absolute shrinkage and selection operator, penalized regression, variable selection

Procedia PDF Downloads 330

Authors: Leonard Chimaobi Agim, Charles Arinzechukwu Igwe, Emmanuel Uzoma Onweremadu, Gabreil Osuji

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Soil erosion has been linked to stream sedimentation, ecosystem degradation, and loss of soil nutrients. A study was conducted to evaluate the effect of some organic amendment on sediment yield, splash loss, and runoff of soils of selected parent materials in southeastern Nigeria. A total of 20 locations, five from each of four parent materials namely: Asu River Group (ARG), Bende Ameki Group (BAG), Coastal Plain Sand (CPS) and Falsebedded Sandstone (FBS) were used for the study. Collected soil samples were analyzed with standard methods for the initial soil properties. Rainfall simulation at an intensity of 190 mm hr-1was conducted for 30 minutes on the soil samples at both the initial stage and after amendment to obtain erosion parameters. The influence of parent material on sediment yield, splash loss and runoff based on rainfall simulation was tested for using one way analyses of variance, while the influence of organic material and their combinations were a factorially fitted in a randomized complete block design. The organic amendments include; goat dropping (GD), poultry dropping (PD), municipal solid waste (MSW) and their combinations (COA) applied at four rates of 0, 10, 20 and 30 t ha-1 respectively. Data were analyzed using analyses of variance suitable for a factorial experiment. Significant means were separated using LSD at 5 % probability levels. Result showed significant (p ≤ 0.05) lower values of sediment yield, splash loss and runoff following amendment. For instance, organic amendment reduced sediment yield under wet and dry runs by 12.91 % and 26.16% in Ishiagu, 40.76% and 45.67%, in Bende, 16.17% and 50% in Obinze and 22.80% and 42.35% in Umulolo respectively. Goat dropping and combination of amendment gave the best results in reducing sediment yield.

Keywords: organic amendment, parent material, rainfall simulation, soil erosion

Procedia PDF Downloads 343

Authors: Ji Young Lee, Jong Woon Kim

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It is essential to secure high availability of railway vehicles to realize high quality and efficiency of railway service. Once the availability decreased, planned railway service could not be provided or more cars need to be reserved. additional cars need to be purchased or the frequency of railway service could be decreased. Such situation would be a big loss in terms of quality and cost related to railway service. Therefore, we make various efforts to get high availability of railway vehicles. Because it is a big loss to operators, we make various efforts to get high availability of railway vehicles. To secure high availability, the idle time of the vehicle needs to be reduced and the following methods are applied to railway vehicles. First, through modularization design, exchange time for line replaceable units is reduced which makes railway vehicles could be put into the service quickly. Second, to reduce periodic preventive maintenance time, preventive maintenance with short period would be proceeded test oriented to minimize the maintenance time, and reliability is secured through overhauls for each main component. With such design changes for railway vehicles, modularized components are exchanged first at the time of vehicle failure or overhaul so that vehicles could be put into the service quickly and exchanged components are repaired or overhauled. Therefore, spare components are required for any future failures or overhauls. And, as components are modularized and costs for components are high, it is considerably important to get reasonable quantities of spare components. Especially, when a number of railway vehicles were put into the service simultaneously, the time of overhauls come almost at the same time. Thus, for some vehicles, components need to be exchanged and overhauled before appointed overhaul period so that these components could be secured as spare parts for the next vehicle’s component overhaul. For this reason, components overhaul time and spare parts quantities should be decided at the same time. This study deals with the time of overhauls for repairable components of railway vehicles and the calculation of spare parts quantities in consideration of future failure/overhauls. However, as railway vehicles are used according to the service schedule, maintenance work cannot be proceeded after the service was closed thus it is quite difficult to resolve this situation mathematically. In this study, Simulation software system is used in this study for analyzing the time of overhauls for repairable components of railway vehicles and the spare parts for the railway systems.

Keywords: overhaul time, rolling stocks, simulation, spare parts

Procedia PDF Downloads 337

Authors: Samia Hassan, Fouzia Latif

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In many countries, education is still far from being a knowledge industry in the sense of own practices that are not yet being transformed by knowledge about the efficacy of those practices. The core question of this paper is why students get bored in class? Have we balanced between the creation and advancement of an engaging learning community and effective learning environment? And between, giving kids confidence to achieve their maximum and potential goals, we sand managing student’s behavior. We conclude that creating a positive learning environment enhances opportunities for young children to feel safe, secure, and to supported in order to do their best learning. Many factors can use in classrooms aid to the positive environment like course content, class preparation, and behavior.

Keywords: effective, environment, learning, positive

Procedia PDF Downloads 574