Search results for: flexible variance

Authors: Samane Maroufi, Rasoul Khayyam Nekouei, Sajjad Mofarah

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Fabrication of the state-of-the-art portable pseudocapacitors with the desired transparency, mechanical flexibility, capacitance, and durability is challenging. In most cases, the fabrication of such devices requires critical elements which are either under the crisis of depletion or their extraction from virgin mineral ores have sever environmental impacts. This urges the use of secondary resources instead of virgin resources in fabrication of advanced devices. In this research, ultrathin films of defect-rich Mn1−x−y(CexLay)O2−δ with controllable thicknesses in the range between 5 nm to 627 nm and transmittance (≈29–100%) have been fabricated via an electrochemical chronoamperometric deposition technique using an aqueous precursor derived during the selective purification of rare earth oxide (REOs) isolated from end-of-life nickel-metal hydride (Ni-MH) batteries. Intercalation/de-intercalation of anionic O2− through the atomic tunnels of the stratified Mn1−x−y(CexLay)O2−δ crystallites was found to be responsible for outstanding areal capacitance of 3.4 mF cm−2 of films with 86% transmittance. The intervalence charge transfer among interstitial Ce/La cations and Mn oxidation states within the Mn1−x−y(CexLay)O2−δ structure resulted in excellent capacitance retention of ≈90% after 16 000 cycles. The synthesised transparent flexible Mn1−x−y(CexLay)O2−δ full-cell pseudocapacitor device possessed the energy and power densities of 0.088 μWh cm⁻² and 843 µW cm⁻², respectively. These values show insignificant changes under vigorous twisting and bending to 45–180° confirming these value-added materials are intriguing alternatives for size-sensitive energy storage devices. This research confirms the feasibility of utilisation of secondary waste resources for the fabrication of high-quality pseudocapacitors with engineered defects with the desired flexibility, transparency, and cycling stability suitable for size-sensitive portable electronic devices.

Keywords: pseudocapacitors, energy storage devices, flexible and transparent, sustainability

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Authors: Chin-Hsien Yeh, Shao-Wen Chen, Wen-Shu Huang, Chun-Fu Huang, Jong-Rong Wang, Jung-Hua Yang, Yuh-Ming Ferng, Chunkuan Shih

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In this research, a Fukushima-like conditions is simulated with TRACE and RELAP5. Fukushima Daiichi Nuclear Power Plant (NPP) occurred the disaster which caused by the earthquake and tsunami. This disaster caused extended loss of all AC power (ELAP). Hence, loss of ultimate heat sink (LUHS) happened finally. In order to handle Fukushima-like conditions, Taiwan Atomic Energy Council (AEC) commanded that Taiwan Power Company should propose strategies to ensure the nuclear power plant safety. One of the diverse and flexible coping strategies (FLEX) is a different water injection strategy. It can execute core injection at 20 Kg/cm2 without depressurization. In this study, TRACE and RELAP5 were used to simulate Maanshan nuclear power plant, which is a three loops PWR in Taiwan, under Fukushima-like conditions and make sure the success criteria of FLEX. Reducing core cooling ability is due to failure of emergency core cooling system (ECCS) in extended loss of all AC power situation. The core water level continues to decline because of the seal leakage, and then FLEX is used to save the core water level and make fuel rods covered by water. The result shows that this mitigation strategy can cool the reactor pressure vessel (RPV) as soon as possible under Fukushima-like conditions, and keep the core water level higher than Top of Active Fuel (TAF). The FLEX can ensure the peak cladding temperature (PCT) below than the criteria 1088.7 K. Finally, the FLEX can provide protection for nuclear power plant and make plant safety.

Keywords: TRACE, RELAP5/MOD3.3, ELAP, FLEX

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Authors: Chih-Ping Chen

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Today, technology does not necessitate change; rather, social media has afforded a new arena and digital tools for users/individuals to be symbolized and marketed in meaningful exchanges of digital identities. We argue that these symbolic interactions may afford individuals the ability to create and present less restricted Line person-to-person (P2P) chats than would be possible in face-to-face communications. Individuals can select flexible influence strategies to market themselves, which enables them to create and present their digital identities and impressions in alternative ways within a dynamic sociocultural context. Therefore, this paper aims to explore the novel phenomenon of how individuals market themselves to manage their digital identities and impressions to connect with other users through the symbolic interactions created by new digital tools (e.g., stickers). A netnographic approach was developed by applying a triangulated methodology consisting of user self-diary reports, in-depth interviews, and observations. Totally, 20 participants (10 females and 10 males) were of Taiwanese origin, and their ages ranged from 20–47 years old. The findings of this research showed that individuals on Line P2P social media where traditional cultural gender norms have shifted. Both male and female participants market their modern digital identities by adopting a combination of flexible influence tactics/strategies when using digital stickers. Some findings showed that their influence tactics/strategies often flouted Taiwanese cultural gender norms or skirted traditional rules to fit individual or P2P needs. Finally, these findings potentially contributed to the literature regarding the consumer culture theory and symbolic interaction theory in digital marketing and social media fields.

Keywords: Consumer culture theory, Digital sticker, Self-marketing, Impression, Symbolic interaciton

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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

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Authors: Alireza Alesaadi

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Flexible AC transmission system (FACTS) devices have an important rule on expnded electrical transmission networks. In this paper, the effect of these diveces on reliability of electrical networks is studied and it is shown that using of FACTS devices can improve the relibiability of power networks, significantly.

Keywords: FACTS devices, power networks, reliability

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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

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Authors: Abdulraaof H. Alqaili, Hamad A. Alsoliman

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Through progress in pavement design developments, a pavement design method was developed, which is titled the Mechanistic Empirical Pavement Design Guide (MEPDG). Nowadays, the evolution in roads network and highways is observed in Saudi Arabia as a result of increasing in traffic volume. Therefore, the MEPDG currently is implemented for flexible pavement design by the Saudi Ministry of Transportation. Implementation of MEPDG for local pavement design requires the calibration of distress models under the local conditions (traffic, climate, and materials). This paper aims to prepare data for calibration of MEPDG in Central Saudi Arabia. Thus, the first goal is data collection for the design of flexible pavement from the local conditions of the Riyadh region. Since, the modifying of collected data to input data is needed; the main goal of this paper is the analysis of collected data. The data analysis in this paper includes processing each: Trucks Classification, Traffic Growth Factor, Annual Average Daily Truck Traffic (AADTT), Monthly Adjustment Factors (MAFi), Vehicle Class Distribution (VCD), Truck Hourly Distribution Factors, Axle Load Distribution Factors (ALDF), Number of axle types (single, tandem, and tridem) per truck class, cloud cover percent, and road sections selected for the local calibration. Detailed descriptions of input parameters are explained in this paper, which leads to providing of an approach for successful implementation of MEPDG. Local calibration of MEPDG to the conditions of Riyadh region can be performed based on the findings in this paper.

Keywords: mechanistic-empirical pavement design guide (MEPDG), traffic characteristics, materials properties, climate, Riyadh

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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

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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

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Authors: Rui He, Seung-Eun Baik, Min-Jae Lee, Myong-Hoon Lee

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The polarizer is one of the most essential optical elements in LCDs. Currently, the most widely used polarizers for LCD is the derivatives of the H-sheet polarizer. There is a need for coatable polarizers which are much thinner and more stable than H-sheet polarizers. One possible approach to obtain thin, stable, and coatable polarizers is based on the use of highly ordered guest-host system. In our research, we aimed to fabricate coatable polarizer based on highly ordered liquid crystalline monomer and dichroic dye ‘guest-host’ system, in which the anisotropic absorption of light could be achieved by aligning a dichroic dye (guest) in the cooperative motion of the ordered liquid crystal (host) molecules. Firstly, we designed and synthesized a new reactive liquid crystalline monomer containing polymerizable acrylate groups as the ‘host’ material. The structure was confirmed by 1H-NMR and IR spectroscopy. The liquid crystalline behavior was studied by differential scanning calorimetry (DSC) and polarized optical microscopy (POM). It was confirmed that the monomers possess highly ordered smectic phase at relatively low temperature. Then, the photocurable ‘guest-host’ system was prepared by mixing the liquid crystalline monomer, dichroic dye and photoinitiator. Coatable polarizers were fabricated by spin-coating above mixture on a substrate with alignment layer. The in-situ photopolymerization was carried out at room temperature by irradiating UV light, resulting in the formation of crosslinked structure that stabilized the aligned dichroic dye molecules. Finally, the dichroic ratio (DR), order parameter (S) and polarization efficiency (PE) were determined by polarized UV/Vis spectroscopy. We prepared the coatable polarizers by using different type of dichroic dyes to meet the requirement of display application. The results reveal that the coatable polarizers at a thickness of 8μm exhibited DR=12~17 and relatively high PE (>96%) with the highest PE=99.3%, which possess potential for the LCD or flexible display applications.

Keywords: coatable polarizer, display, guest-host, liquid crystal

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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: Zahrul Faizi M. S., Ali A., Norhuda A. M.

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Emission of greenhouse gases (GHG) from solid waste treatment and dependency on fossil fuel to produce electricity are the major concern in Malaysia as well as global. Innovation in downdraft gasification with combined heat and power (CHP) systems has the potential to minimize solid waste and reduce the emission of anthropogenic GHG from conventional fossil fuel power plants. However, the efficiency and capability of downdraft gasification to generate electricity from various alternative fuels, for instance, agriculture residues (i.e., woodchip, coconut shell) and municipal solid waste (MSW), are still controversial, on top of the toxicity level from the produced bottom ash. Thus this study evaluates the adaptability and reliability of the 20 kW downdraft gasification system to generate electricity (while considering environmental sustainability from the bottom ash) using flexible local feedstock at 20, 40, and 60% mixed ratio of MSW: agriculture residues. Feedstock properties such as feed particle size, moisture, and ash contents are also analyzed to identify optimal characteristics for the combination of feedstock (feedstock flexibility) to obtain maximum energy generation. Results show that the gasification system is capable to flexibly accommodate different feedstock compositions subjected to specific particle size (less than 2 inches) at a moisture content between 15 to 20%. These values exhibit enhance gasifier performance and provide a significant effect to the syngas composition utilizes by the internal combustion engine, which reflects energy production. The result obtained in this study is able to provide a new perspective on the transition of the conventional gasification system to a future reliable carbon-negative energy technology. Subsequently, promoting commercial scale-up of the downdraft gasification system.

Keywords: carbon-negative energy, feedstock flexibility, gasification, renewable energy

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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: Paolo Di Pietro, Matteo Lelli, Kinjal Parmar

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Water hazards are consistently identified as among the highest global risks in terms of impact. Riverbank protection plays a key role in flood risk management. For erosion control and scour protection, flexible solutions like gabions & mattresses are being used since quite some time now. The efficacy of erosion control systems depends both on the ability to prevent soil loss underneath, as well as to maintain their integrity under the effects of the water flow. The paper presents the results of a research carried out at the Colorado State University on the performance of double twisted wire mesh products, known as Reno Mattresses, used as soil erosion control system. Mattresses were subjected to various flow conditions on a 10m long flume where they were placed on a 0.30 m thick soil layer. The performance against erosion was evaluated by assessing the effect of the stone motion inside the mattress combined with the condition of incipient soil erosion underneath, in relationship to the mattress thickness, the filling stone properties and under variable hydraulic flow regimes. While confirming the stability obtained using a conventional design approach (commonly referred to tractive force theories), the results of the research allowed to introduce a new performance limit based on incipient soil erosion underneath the revetment. Based on the research results, the authors propose to express the shear resistance of mattresses used as soil erosion control system as a function of the size of the filling stones, their uniformity, their unit weight, the thickness of the mattress, and the presence of vertical connecting elements between the mattress lid and bottom.

Keywords: Reno Mattress, riverbank protection, hydraulics, full scale tests

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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: 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

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Authors: Seppo Sirkemaa

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Information systems infrastructure is the basis of business systems and processes in the company. It should be a reliable platform for business processes and activities but also have the flexibility to change business needs. The development of an infrastructure that is robust, reliable, and flexible is a challenge. Understanding technological capabilities and business needs is a key element in the development of successful information systems infrastructure.

Keywords: development, information technology, networks, technology

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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: Ezgi Ismar

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Carbon nanotubes (CNTs) are different from other allotropes of carbon, such as graphite, diamond and fullerene. Replacement of metals in flexible textiles has an advantage. Particularly in the last decade, both their electrical and mechanical properties have become an area of interest for Li-ion battery applications where the conductivity has a major importance. While carbon nanotubes are conductive, they are also less in weight compared to convectional conductive materials. Carbon nanotubes can be used inside the fiber so they can offer to create 3-D structures. In this review, you can find some examples of how carbon nanotubes adapted to textile products.

Keywords: carbon nanotubes, conductive textiles, nanotechnology, nanotextiles

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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: Ahmed E. Hodaib, Mohamed A. Hashem

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Dissimilar to pneumatic tyres, airless tyres or flat-proof tyres (also known as tweel) is designed to have poly-composite compound treaded around a hub of flexible spokes. The main advantage of this design is its robustness as airless tyres are impossible to deflate or to blowout at highway speeds like conventional tyres so the driver does not have to be restless about having a spare tire. A summary of the study on manufacturing of airless tyres’ mold is given. Moreover, we have proposed some advantages and disadvantages of using tweel tyres.

Keywords: airless tyres, tweel, non-pneumatic tyres, manufacturing

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Authors: Apurva Patil, Ashay Aswale, Akshay Kulkarni, Shubham Bharadiya

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The potential benefit of gravity compensation of linkages in mechanisms using springs to reduce actuator requirements is well recognized, but practical applications have been elusive. Although existing methods provide exact spring balance, they require additional masses or auxiliary links, or all the springs used originate from the ground, which makes the resulting device bulky and space-inefficient. This paper uses a method of static balancing of mechanisms with conservative loads such as gravity and spring loads using non-zero-free-length springs with child–parent connections and no auxiliary links. Application of this method to the developed arm of a humanoid robot is presented here. Spring balancing is particularly important in this case because the serial chain of linkages has to work against gravity.This work involves approximate spring balancing of the open-loop chain of linkages using minimization of potential energy variance. It uses the approach of flattening the potential energy distribution over the workspace and fuses it with numerical optimization. The results show the considerable reduction in actuator torque requirement with practical spring design and arrangement. Reduced actuator torque facilitates the use of lower end actuators which are generally smaller in weight and volume thereby lowering the space requirements and the total weight of the arm. This is particularly important for humanoid robots where the parent actuator has to handle the weight of the subsequent actuators as well. Actuators with lower actuation requirements are more energy efficient, thereby reduce the energy consumption of the mechanism. Lower end actuators are lower in cost and facilitate the development of low-cost devices. Although the method provides only an approximate balancing, it is versatile, flexible in choosing appropriate control variables that are relevant to the design problem and easy to implement. The true potential of this technique lies in the fact that it uses a very simple optimization to find the spring constant, free-length of the spring and the optimal attachment points subject to the optimization constraints. Also, it uses physically realizable non-zero-free-length springs directly, thereby reducing the complexity involved in simulating zero-free-length springs from non-zero-free-length springs. This method allows springs to be attached to the preceding parent link, which makes the implementation of spring balancing practical. Because auxiliary linkages can be avoided, the resultant arm of the humanoid robot is compact. The cost benefits and reduced complexity can be significant advantages in the development of this arm of the humanoid robot.

Keywords: actuator torque, child-parent connections, spring balancing, the arm of a humanoid robot

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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

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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

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Authors: Norman Sinnigen, Igor Izyurov, Marina Krylova, Hamidreza Jamalabadi, Sarah Alizadeh, Martin Walter

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Background: EEG is a non-invasive brain activity recording technique with a high temporal resolution that allows the use of real-time applications, such as neurofeedback. However, EEG data are susceptible to electrooculographic (EOG) and electromyography (EMG) artifacts (i.e., jaw clenching, teeth squeezing and forehead movements). Due to their non-stationary nature, these artifacts greatly obscure the information and power spectrum of EEG signals. Many EEG artifact correction methods are too time-consuming when applied to low-density EEG and have been focusing on offline processing or handling one single type of EEG artifact. A software-only real-time method for correcting multiple types of EEG artifacts of high-density EEG remains a significant challenge. Methods: We demonstrate an improved approach for automatic real-time EEG artifact correction of EOG and EMG artifacts. The method was tested on three healthy subjects using 64 EEG channels (Brain Products GmbH) and a sampling rate of 1,000 Hz. Captured EEG signals were imported in MATLAB with the lab streaming layer interface allowing buffering of EEG data. EMG artifacts were detected by channel variance and adaptive thresholding and corrected by using channel interpolation. Real-time independent component analysis (ICA) was applied for correcting EOG artifacts. Results: Our results demonstrate that the algorithm effectively reduces EMG artifacts, such as jaw clenching, teeth squeezing and forehead movements, and EOG artifacts (horizontal and vertical eye movements) of high-density EEG while preserving brain neuronal activity information. The average computation time of EOG and EMG artifact correction for 80 s (80,000 data points) 64-channel data is 300 – 700 ms depending on the convergence of ICA and the type and intensity of the artifact. Conclusion: An automatic EEG artifact correction algorithm based on channel variance, adaptive thresholding, and ICA improves high-density EEG recordings contaminated with EOG and EMG artifacts in real-time.

Keywords: EEG, muscle artifacts, ocular artifacts, real-time artifact correction, real-time ICA

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Authors: Gebreslassie Gebru, Gurja Belay, Minister Birhanie, Mulalem Zenebe, Tadelle Dessie, Adriana Vallejo-Trujillo, Olivier Hanotte

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Livestock must adapt to changing environmental conditions, which can result in either phenotypic plasticity or irreversible phenotypic change. In this study, we combine Ecological Niche Modelling (ENM) and Phenotypic Distribution Modelling (PDM) to provide a comprehensive framework for understanding the ecological and phenotypic characteristics of indigenous chicken (Gallus gallus domesticus) ecotypes. This approach helped us to classify these ecotypes, differentiate their phenotypic traits, and identify associations between environmental variables and adaptive traits. We measured 297 adult indigenous chickens from various agro-ecologies, including 208 females and 89 males. A subset of the 22 measured traits was selected using stepwise selection, resulting in seven traits for each sex. Using ENM, we identified four agro-ecologies potentially harbouring distinct phenotypes of indigenous Tigray chickens. However, PDM classified these chickens into three phenotypical ecotypes. Chickens grouped in ecotype-1 and ecotype-3 exhibited superior adaptive traits compared to those in ecotype-2, with significant variance observed. This high variance suggests a broader range of trait expression within these ecotypes, indicating greater adaptation capacity and potentially more diverse genetic characteristics. Several environmental variables, such as soil clay content, forest cover, and mean temperature of the wettest quarter, were strongly associated with most phenotypic traits. This suggests that these environmental factors play a role in shaping the observed phenotypic variations. By integrating ENM and PDM, this study enhances our understanding of indigenous chickens' ecological and phenotypic diversity. It also provides valuable insights into their conservation and management in response to environmental changes.

Keywords: adaptive traits, agro-ecology, appendage, climate, environment, imagej, morphology, phenotypic variation

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Authors: Gurcharan Singh Buttar

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It has been discovered that although these two areas, statistics, and information theory, are independent in their nature, they can be combined to create applications in multidisciplinary mathematics. This is due to the fact that where in the field of statistics, statistical parameters (measures) play an essential role in reference to the population (distribution) under investigation. Information measure is crucial in the study of ambiguity, assortment, and unpredictability present in an array of phenomena. The following communication is a link between the two, and it has been demonstrated that the well-known conventional statistical measures can be used as a measure of information.

Keywords: probability distribution, entropy, concavity, symmetry, variance, central tendency

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Authors: Wang Xiaoqing, Fang Youyuan, Zheng Yanxing, Gu Tianyang, Zong Jianjian, Tong Jinrong

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Compared with traditional distributed environment, the net-centric environment brings on more demanding challenges for information sharing with the characteristics of ultra-large scale and strong distribution, dynamic, autonomy, heterogeneity, redundancy. This paper realizes an information sharing model and a series of core services, through which provides an open, flexible and scalable information sharing platform.

Keywords: net-centric environment, information sharing, metadata registry and catalog, cross-domain data access control

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