Search results for: current vector

Authors: R. B. Mishra, Sudhakar Tripathi

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In this paper, the cable model of dendrites have been considered. The dendrites are cylindrical cables of various segments having variable length and reducing radius from start point at synapse and end points. For a particular event signal being received by a neuron in response only some dendrite are active at a particular instance. Initial current signals with different current flows in dendrite are assumed. Due to overlapping and coupling of active dendrite, they induce currents in the dendrite segments of each other at a particular instance. But how these currents are induced in the various segments of active dendrites due to coupling between these dendrites, It is not presented in the literature. Here the paper presents a model for induced currents in active dendrite segments due to mutual coupling at the starting instance of an activity in dendrite. The model is as discussed further.

Keywords: currents, dendrites, induction, simulation

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Authors: Jyh-Yang Wu, Sheng-Gwo Chen

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In this paper, we present a simple effective numerical geometric method to estimate the divergence of a vector field over a curved surface. The conservation law is an important principle in physics and mathematics. However, many well-known numerical methods for solving diffusion equations do not obey conservation laws. Our presented method in this paper combines the divergence theorem with a generalized finite difference method and obeys the conservation law on discrete closed surfaces. We use the similar method to solve the Cahn-Hilliard equations on evolving spherical surfaces and observe stability results in our numerical simulations.

Keywords: conservation laws, diffusion equations, Cahn-Hilliard equations, evolving surfaces

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Authors: Vivek Kumar Singh, Tripti Singh

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An ad hoc wireless network consists of mobile networks which creates an underlying architecture for communication without the help of traditional fixed-position routers. Ad-hoc On-demand Distance Vector (AODV) is a routing protocol used for Mobile Ad hoc Network (MANET). Nevertheless, the architecture must maintain communication routes although the hosts are mobile and they have limited transmission range. There are different protocols for handling the routing in the mobile environment. Routing protocols used in fixed infrastructure networks cannot be efficiently used for mobile ad-hoc networks, so that MANET requires different protocols. This paper presents the performance analysis of the routing protocols used various parameter-patterns with Two-ray model.

Keywords: AODV, packet transmission rate, pause time, ZRP, QualNet 6.1

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Authors: Molly Meadows

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Following the presidency of Donald J. Trump, Americans have become hyperaware of ethnocentrisms that plague the culture. The president's egoist ethics encouraged a divide between what the citizens of the US identified as just or unjust. In the race for global supremacy and leading ideology, fears have arisen, exacerbated by the ethnocentricity of the country's leader, pointing to the possible harmful ethical standards of competing nations. Due to the concept of ethical absolutism, an international code of ethics would not be possible, and the changes needed to eliminate the stigma surrounding other cultures of thought would need to come from the governing body of the US. As the current leading global ideology, the US would need its government to embody a transformational leadership style in order to unite the motivations of the citizens and encourage intercultural tolerance.

Keywords: ethics, transformational leadership, American politics, egoism, cultural intelligence, ethical relativism

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Authors: Rahman Dashti, Ehsan Gord

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In this paper, an improved impedance based fault location method is proposed. In this method, online fault locating is performed using voltage and current information at the beginning of the feeder. Determining precise fault location in a short time increases reliability and efficiency of the system. The proposed method utilizes information about main component of voltage and current at the beginning of the feeder and distributed generation unit (DGU) in order to precisely locate different faults in acceptable time. To evaluate precision and accuracy of the proposed method, a 13-node is simulated and tested using MATLAB.

Keywords: distribution network, fault section determination, distributed generation units, distribution protection equipment

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Authors: Oluwafunmibi Omotayo Fasanya, Augustine Kena Adjei

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To develop a machine learning model to predict diabetes (DM) prevalence in the U.S. population using demographic characteristics, physical indicators, and lifestyle habits, and to analyze how these factors contribute to the likelihood of diabetes. We analyzed data from 23,546 participants aged 20 and older, who were non-pregnant, from the 2009-2018 National Health and Nutrition Examination Survey (NHANES). The dataset included key demographic (age, sex, ethnicity), physical (BMI, leg length, total cholesterol [TCHOL], fasting plasma glucose), and lifestyle indicators (smoking habits). A weighted sample was used to account for NHANES survey design features such as stratification and clustering. A classification machine learning model was trained to predict diabetes status. The target variable was binary (diabetes or non-diabetes) based on fasting plasma glucose measurements. The following models were evaluated: Logistic Regression (baseline), Random Forest Classifier, Gradient Boosting Machine (GBM), Support Vector Machine (SVM). Model performance was assessed using accuracy, F1-score, AUC-ROC, and precision-recall metrics. Feature importance was analyzed using SHAP values to interpret the contributions of variables such as age, BMI, ethnicity, and smoking status. The Gradient Boosting Machine (GBM) model outperformed other classifiers with an AUC-ROC score of 0.85. Feature importance analysis revealed the following key predictors: Age: The most significant predictor, with diabetes prevalence increasing with age, peaking around the 60s for males and 70s for females. BMI: Higher BMI was strongly associated with a higher risk of diabetes. Ethnicity: Black participants had the highest predicted prevalence of diabetes (14.6%), followed by Mexican-Americans (13.5%) and Whites (10.6%). TCHOL: Diabetics had lower total cholesterol levels, particularly among White participants (mean decline of 23.6 mg/dL). Smoking: Smoking showed a slight increase in diabetes risk among Whites (0.2%) but had a limited effect in other ethnic groups. Using machine learning models, we identified key demographic, physical, and lifestyle predictors of diabetes in the U.S. population. The results confirm that diabetes prevalence varies significantly across age, BMI, and ethnic groups, with lifestyle factors such as smoking contributing differently by ethnicity. These findings provide a basis for more targeted public health interventions and resource allocation for diabetes management.

Keywords: diabetes, NHANES, random forest, gradient boosting machine, support vector machine

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Authors: Younghyun Jeon, Seungjoo Maeng

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In the Ad-hoc network, the great interests regarding MIMO scheme leads to their combination, which is also utilized into its applicable network. We manage the field of the problem into Reverse-link MIMO Ad-hoc Network (RMAN) and propose the methodology to maximize the data rate with its power consumption using Node-Cooperative beamforming technique. Based on the result of mathematical optimization formulation, we design the algorithm to construct optimal orthogonal weight vector according to channel feedback and control its transmission power according to QoS-pricing value level. In simulation results, we show the validity of the proposed mathematical optimization result and algorithm which mean that the sum-rate of each link is converged into some point.

Keywords: ad-hoc network, MIMO, cooperative beamforming, transmit power

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Authors: Levi Corallo

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Typed language made by humans on computers and cell phones has made a significant distinction from previous modes of written language exchanges. While acronyms remain one of the most predominant markings of typed language, another and perhaps more recent revolution in the way humans communicate has been with the use of symbols or glyphs, primarily Emojis—globally introduced on the iPhone keyboard by Apple in 2008. This paper seeks to analyze the use of symbols in typed communication from both a linguistic and machine learning perspective. The Unicode system will be explored and methods of encoding will be juxtaposed with the current machine and human perception. Topics in how typed symbol usage exists in conversation will be explored as well as topics across current research methods dealing with Emojis like sentiment analysis, predictive text models, and so on. This study proposes that sequential analysis is a significant feature for analyzing unicode characters in a corpus with machine learning. Current models that are trying to learn or translate the meaning of Emojis should be starting to learn using bi- and tri-grams of Emoji, as well as observing the relationship between combinations of different Emoji in tandem. The sociolinguistics of an entire new vernacular of language referred to here as ‘typed language’ will also be delineated across my analysis with unicode glyphs from both a semantic and technical perspective.

Keywords: unicode, text symbols, emojis, glyphs, communication

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Authors: Leila Momenzadeh, Alexander V. Evteev, Elena V. Levchenko, Tanvir Ahmed, Irina Belova, Graeme Murch

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In this work, the phonon thermal conductivity of f.c.c. Al is investigated in detail in the temperature range 100 – 900 K within the framework of equilibrium molecular dynamics simulations making use of the Green-Kubo formalism and one of the most reliable embedded-atom method potentials. It is found that the heat current auto-correlation function of the f.c.c. Al model demonstrates a two-stage temporal decay similar to the previously observed for f.c.c Cu model. After the first stage of decay, the heat current auto-correlation function of the f.c.c. Al model demonstrates a peak in the temperature range 100-800 K. The intensity of the peak decreases as the temperature increases. At 900 K, it transforms to a shoulder. To describe the observed two-stage decay of the heat current auto-correlation function of the f.c.c. Al model, we employ decomposition model recently developed for phonon-mediated thermal transport in a monoatomic lattice. We found that the electronic contribution to the total thermal conductivity of f.c.c. Al dominates over the whole studied temperature range. However, the phonon contribution to the total thermal conductivity of f.c.c. Al increases as temperature decreases. It is about 1.05% at 900 K and about 12.5% at 100 K.

Keywords: aluminum, gGreen-Kubo formalism, molecular dynamics, phonon thermal conductivity

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Authors: Mehran Nasiri, Ardeshir Poornemat

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The aim of this study was to investigate the current and ideal situations of the process of talent identification in Iranian football from the point of view of Iranian instructors of the Asian Football Confederation (AFC). This research was a descriptive-analytical study; in data collection phase a questionnaire was used, whose face validity was confirmed by experts of Physical Education and Sports Science. The reliability of questionnaire was estimated through the use of Cronbach's alpha method (0.91). This study involved 122 participants of Iranian instructors of the AFC who were selected based on stratified random sampling method. Descriptive statistics were used to describe the variables and inferential statistics (Chi-square) were used to test the hypotheses of the study at significant level (p ≤ 0.05). The results of Chi-square test related to the point of view of Iranian instructors of the AFC showed that the grass-roots scientific method was the best way to identify football players (0.001), less than 10 years old were the best ages for talent identification (0.001), the Football Federation was revealed to be the most important organization in talent identification (0.002), clubs were shown to be the most important institution in developing talents (0.001), trained scouts of Football Federation were demonstrated to be the best and most appropriate group for talent identification (0.001), and being referred by the football academy coaches was shown to be the best way to attract talented football players in Iran (0.001). It was also found that there was a huge difference between the current and ideal situation of the process of talent identification in Iranian football from the point of view of Iranian instructors of the AFC. Hence, it is recommended that the policy makers of talent identification for Iranian football provide a comprehensive, clear and systematic model of talent identification and development processes for the clubs and football teams, so that the talent identification process helps to nurture football talents more efficiently.

Keywords: current situation, talent finding, ideal situation, instructors (AFC)

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Authors: Ryan Maclellan

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The nEXO Collaboration is designing a very large detector for neutrinoless double beta decay of Xe-136. The nEXO detector is rooted in the current EXO-200 program, which has reached a sensitivity for the half-life of the decay of 1.9x10^25 years with an exposure of 99.8 kg-y. The baseline nEXO design assumes 5 tonnes of liquid xenon, enriched in the mass 136 isotope, within a time projection chamber. The detector is being designed to reach a half-life sensitivity of > 5x10^27 years covering the inverted neutrino mass hierarchy, with 5 years of data. We present the nEXO detector design, the current status of R&D efforts, and the physics case for the experiment.

Keywords: double-beta, Majorana, neutrino, neutrinoless

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Authors: Yu-Jen Shih, Juan-Zhang Lou

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Nitrogenous compounds, such as NH4+/NH3 and NO3-, have become important contaminants in water resources. Excessive concentration of NH3 leads to eutrophication, which poses a threat to aquatic organisms in the environment. Electrochemical oxidation emerged as a promising water treatment technology, offering advantages such as simplicity, small-scale operation, and minimal reliance on additional chemicals. In this study, a nickel-based metal-organic framework (Ni-MOF) was synthesized using 2-amino terephthalic acid (BDC-NH2) and nickel nitrate. The Ni-MOF was further carbonized as derived nickel oxide and nitrogen-carbon composite, Ni/NiOx/NC. The nickel oxide within the 2D porous carbon texture served as active sites for ammonia oxidation. Results of characterization showed that the Ni-MOF was a hexagonal and flaky nanoparticle. With increasing carbonization temperature, the nickel ions in the organic framework re-crystallized as NiO clusters on the surfaces of the 2D carbon. The electrochemical surface area of Ni/NiOx/NC significantly increased as to improve the efficiency of ammonia oxidation. The phase transition of Ni(OH)2⇌NiOOH at around +0.8 V was the primary mediator of electron transfer. Batch electrolysis was conducted under constant current and constant potential modes. The electrolysis parameters included pyrolysis temperatures, pH, current density, initial feed concentration, and electrode potential. The constant current batch experiments indicated that via carbonization at 800 °C, Ni/NiOx/NC(800) was able to decrease the ammonium nitrogen of 50 mg-N/L to below 1 ppm within 4 hours at a current density of 3 mA/cm2 and pH 11 with negligible oxygenated nitrogen formation. The constant potential experiments confirmed that N2 nitrogen selectivity was enhanced up to 90% at +0.8 V.

Keywords: electrochemical oxidation, nickel oxyhydroxide, metal-organic framework, ammonium, nitrate

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Authors: Afif Saleh Abugharsa

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The IEEE 802.15.4 standard is designed for low-rate wireless personal area networks (LR-WPAN) with focus on enabling wireless sensor networks. It aims to give a low data rate, low power consumption, and low cost wireless networking on the device-level communication. The objective of this study is to investigate the performance of IEEE 802.15.4 based networks using simulation tool. In this project the network simulator 2 NS2 was used to several performance measures of wireless sensor networks. Three scenarios were considered, multi hop network with a single coordinator, star topology, and an ad hoc on demand distance vector AODV. Results such as packet delivery ratio, hop delay, and number of collisions are obtained from these scenarios.

Keywords: ZigBee, wireless sensor networks, IEEE 802.15.4, low power, low data rate

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Authors: Hussein Al-bayaty

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This paper presents a novel idea to show the ability to benefit of the harmonic currents which are produced on the load side of the power grid. The proposed circuit contributes in reduction of the total harmonic distortion (THD) percentage through adding a high pass filter to draw harmonic currents with 150 Hz and multiple frequencies a and convert them to DC current and then reconvert it to AC current with 50 Hz frequency in order to feed different loads. The circuit has been designed, investigated and simulated in the MATLAB, Simulink program; the results will be assessed and compared the two cases: firstly, the system without adding the new circuit. Secondly, with adding the high pas filter circuit to the power system.

Keywords: harmonics elimination, passive filters, Total Harmonic Distortion (THD), filter circuit

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Authors: Jamie Sundvall, Lisa Jennings

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Site based field internship learning (SBL) is an educational approach within a Master’s of Social Work (MSW) university field placement department that promotes a more streamlined approach to the integration of theory and evidence based practices for social work students. The SBL model is founded on research in the field, consideration of current work force needs, United States national trends of MSW graduate skill and knowledge deficits, educational trends in students pursing a master’s degree in social work, and current social problems that require unique problem solving skills. This study explores the use of site-based learning in a hybrid social work program. In this setting, site based learning pairs online education courses and social work field education to create training opportunities for social work students within their own community and cultural context. Students engage in coursework in an online setting with both synchronous and asynchronous features that facilitate development of core competencies for MSW students. Through the SBL model, students are then partnered with faculty in a virtual course room and a university vetted site within their community. The study explores how this model of learning creates community partnerships, through which students engage in a learning loop to develop social work skills, while preparing students to address current community, social, and global issues with the engagement of technology. The goal of SBL is to more effectively equip social work students for practice according to current workforce demands, provide access to education and care to populations who have limited access, and create self-sustainable partnerships. Further, the model helps students learn integration of evidence based practices and helps instructors more effectively teach integration of ethics into practice. The study found that the SBL model increases the influence and professional relevance of the social work profession, and ultimately facilitates stronger approaches to integrating theory into practice. Current implementation of the practice in the United States will be presented in the study. dditionally, future research conceptualization of SBL models will be presented, in order to collaborate on advancing best approaches of translating theory into practice, according to the current needs of the profession and needs of social work students.

Keywords: collaboration, fieldwork, research, site-based learning, technology

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Authors: Nuwan Kuruwitaarachchi, M. K. M. Peiris, C. N. Madawala, K. M. A. R. Perera, V. U. N Perera

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Dealing with businesses with the foreign market always took a special place in a country’s economy. Political and social factors came into play making currency rate changes fluctuate rapidly. Currency rate prediction has become an important factor for larger international businesses since large amounts of money exchanged between countries. This research focuses on comparing the accuracy of mainly three models; Autoregressive Integrated Moving Average (ARIMA), Artificial Neural Networks(ANN) and Support Vector Machines(SVM). series of data import, export, USD currency exchange rate respect to LKR has been selected for training using above mentioned algorithms. After training the data set and comparing each algorithm, it was able to see that prediction in SVM performed better than other models. It was improved more by combining SVM and SVR models together.

Keywords: ARIMA, ANN, FFNN, RMSE, SVM, SVR

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Authors: Mohammad Nadeem, Haider Banka, R. Venugopal

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Granulation or agglomeration is a size enlargement process to transform the fine particulates into larger aggregates since the fine size of available materials and minerals poses difficulty in their utilization. Though a long list of methods is available in the literature for the modeling of granulation process to facilitate the in-depth understanding and interpretation of the system, there is still scope of improvements using novel tools and techniques. Intelligent techniques, such as artificial neural network, fuzzy logic, self-organizing map, support vector machine and others, have emerged as compelling alternatives for dealing with imprecision and complex non-linearity of the systems. The present study tries to review the applications of intelligent techniques in the modeling of size enlargement process for fine materials.

Keywords: fine material, granulation, intelligent technique, modelling

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Authors: Ishak Suleiman, Ahmad Kamsani Samingan, Yeoh Chun Yeow, Abdul Aziz Bin Abdul Rahman

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In this paper, we evaluate the benefits of distributed 4x4 MIMO LTE downlink systems compared to that of the co-located 4x4 MIMO LTE downlink system. The performance evaluation was carried out experimentally by using Wireless Open-Access Research Platform (WARP), where the comparison between the 4x4 MIMO LTE transmission downlink system in distributed and co-located techniques was examined. The measured Error Vector Magnitude (EVM) results showed that the distributed technique achieved better system performance compared to the co-located arrangement.

Keywords: multiple-input-multiple-output (MIMO), distributed MIMO, co-located MIMO, LTE

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Authors: Ramin Mirzada, Takuya Maruyama

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Kabul is the heart of political, commercial, cultural, educational and social life in Afghanistan and the fifth fastest growing city in the world. Minimum income inclined most of Kabul residents to use public transport, especially buses, although there is no proper bus system, beside that there is no proper fare exist in Kabul city Due to wars. From 1992 to 2001 during civil wars, Kabul suffered damage and destruction of its transportation facilities including pavements, sidewalks, traffic circles, drainage systems, traffic signs and signals, trolleybuses and almost all of the public transport system (e.g. Millie bus). This research is mainly focused on Kabul city’s transportation system. In this research, the data used have been gathered by Japan International Cooperation Agency (JICA) in 2008 and this data will be used to find demand and fare structure, additionally a survey was done in 2016 to find satisfaction level of Kabul residents for fare structure. Aim of this research is to observe the demand for Large Buses, compare to the actual supply from the government, analyze the current fare structure and compare it with the proposed fare (distance based fare) structure which has already been analyzed. Outcome of this research shows that the demand of Kabul city residents for the public transport (Large Buses) exceeds from the current supply, so that current public transportation (Large Buses) is not sufficient to serve public transport in Kabul city, worth to be mentioned, that in order to overcome this problem, there is no need to build new roads or exclusive way for buses. This research proposes government to change the fare from fixed fare to distance based fare, invest on public transportation and increase the number of large buses so that the current demand for public transport is met.

Keywords: transportation, planning, public transport, large buses, Kabul, Afghanistan

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Authors: Saahith M. S., Sivakami R.

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In the realm of football analytics, particularly focusing on predicting football player performance, the ability to forecast player success accurately is of paramount importance for teams, managers, and fans. This study introduces an elaborate examination of predicting football player performance through the integration of data visualization methods and machine learning algorithms. The research entails the compilation of an extensive dataset comprising player attributes, conducting data preprocessing, feature selection, model selection, and model training to construct predictive models. The analysis within this study will involve delving into feature significance using methodologies like Select Best and Recursive Feature Elimination (RFE) to pinpoint pertinent attributes for predicting player performance. Various machine learning algorithms, including Random Forest, Decision Tree, Linear Regression, Support Vector Regression (SVR), and Artificial Neural Networks (ANN), will be explored to develop predictive models. The evaluation of each model's performance utilizing metrics such as Mean Squared Error (MSE) and R-squared will be executed to gauge their efficacy in predicting player performance. Furthermore, this investigation will encompass a top player analysis to recognize the top-performing players based on the anticipated overall performance scores. Nationality analysis will entail scrutinizing the player distribution based on nationality and investigating potential correlations between nationality and player performance. Positional analysis will concentrate on examining the player distribution across various positions and assessing the average performance of players in each position. Age analysis will evaluate the influence of age on player performance and identify any discernible trends or patterns associated with player age groups. The primary objective is to predict a football player's overall performance accurately based on their individual attributes, leveraging data-driven insights to enrich the comprehension of player success on the field. By amalgamating data visualization and machine learning methodologies, the aim is to furnish valuable tools for teams, managers, and fans to effectively analyze and forecast player performance. This research contributes to the progression of sports analytics by showcasing the potential of machine learning in predicting football player performance and offering actionable insights for diverse stakeholders in the football industry.

Keywords: football analytics, player performance prediction, data visualization, machine learning algorithms, random forest, decision tree, linear regression, support vector regression, artificial neural networks, model evaluation, top player analysis, nationality analysis, positional analysis

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Authors: Ravi Kiran Jaladi, Ezz I. El-Masry

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Emerging technologies such as ultra-wide band wireless access technology that operate at ultra-low power present several challenges due to their inherent design that limits the use of voltage-mode filters. Therefore, Continuous-time current-mode (CTCM) filters have become very popular in recent times due to the fact they have a wider dynamic range, improved linearity, and extended bandwidth compared to their voltage-mode counterparts. The goal of this research is to develop analog filters which are suitable for the current scaling CMOS technologies. Bulk-driven MOSFET is one of the most popular low power design technique for the existing challenges, while other techniques have obvious shortcomings. In this work, a CTCM Gate-driven (GD) differentiator has been presented with a frequency range from dc to 100MHz which operates at very low supply voltage of 0.7 volts. A novel CTCM Bulk-driven (BD) differentiator has been designed for the first time which reduces the power consumption multiple times that of GD differentiator. These GD and BD differentiator has been simulated using CADENCE TSMC 65nm technology for all the bilinear and biquadratic band-pass frequency responses. These basic building blocks can be used to implement the higher order filters. A 6th order cascade CTCM Chebyshev band-pass filter has been designed using the GD and BD techniques. As a conclusion, a low power GD and BD 6th order chebyshev stagger-tuned band-pass filter was simulated and all the parameters obtained from all the resulting realizations are analyzed and compared. Monte Carlo analysis is performed for both the 6th order filters and the results of sensitivity analysis are presented.

Keywords: bulk-driven (BD), continuous-time current-mode filters (CTCM), gate-driven (GD)

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Authors: Saleh Alshehri

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Thermoelectric technology is currently being used in many industrial applications for cooling, heating and generating electricity. This research mainly focuses on using thermoelectric to cool down high-speed computer chips at different operating conditions. A previously developed and validated three-dimensional model for optimizing and assessing the performance of cascaded thermoelectric and non-cascaded thermoelectric is used in this study to investigate the possibility of decreasing the hotspot temperature of computer chip. Additionally, a test assembly is built and tested at steady-state and transient conditions. The obtained optimum thermoelectric current at steady-state condition is used to conduct a number of pulsed tests (i.e. transient tests) with different shapes to cool the computer chips hotspots. The results of the steady-state tests showed that at hotspot heat rate of 15.58 W (5.97 W/cm²), using thermoelectric current of 4.5 A has resulted in decreasing the hotspot temperature at open circuit condition (89.3 °C) by 50.1 °C. Maximum and minimum hotspot temperatures have been affected by ON and OFF duration of the electrical current pulse. Maximum hotspot temperature was resulted by longer OFF pulse period. In addition, longer ON pulse period has generated the minimum hotspot temperature.

Keywords: thermoelectric generator, TEG, thermoelectric cooler, TEC, chip hotspots, electronic cooling

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Authors: Ashish Jain, Satish Nayak

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Transdermal iontophoretic drug delivery system is viable drug delivery platform technology and has a strong market worldwide. Transdermal drug delivery system is particularly desirable for therapeutic agents that need prolonged administration at controlled plasma level. This makes appropriateness to antihypertensive and anti-diabetic agents for their transdermal development. Controlled zero order absorption, easily termination of drug delivery and easy to administration also support for popularity of transdermal delivery. In this current research iontophoretic delivery of various anti diabetic agents like glipizide, glibenclamide and glimepiride were carried out. The experiments were carried out at different drug concentrations and different current densities using cathodal iontophoresis. Diffusion cell for iontophoretic permeation study was modified according to Glikfield Design. Pig skin was used for in vitro permeation study and for the in-vivo study New Zealand rabbits were used. At all concentration level iontophoresis showed enhanced permeation rate compared to passive controls. Iontophoretic transports of selected drugs were found to be increased with the current densities. Results showed that target permeation rate for selected drugs could be achieved with the aid of iontophoresis by increasing the area in an appreciable range.

Keywords: transdermal, iontophoresis, pig skin, rabbits, glipizide, glibeclamide

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Authors: Barzin Rajabloo, Martin Desilets

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First, an electrochemical model for the reduction of CO₂ into CH₃OH is developed in which mass and charge transfer, reactions at the surface of the electrodes and fluid flow of the electrolyte are considered. This mathematical model is developed in COMSOL Multiphysics® where both secondary and tertiary current distribution interfaces are coupled to consider concentrations and potentials inside different parts of the cell. Constant reaction rates are assumed as the fitted parameters to minimize the error between experimental data and modeling results. The model is validated through a comparison with experimental data in terms of faradaic efficiency for production of CH₃OH, the current density in different applied cathode potentials as well as current density in different electrolyte flow rates. The comparison between model outputs and experimental measurements shows a good agreement. The model indicates the higher hydrogen evolution in comparison with CH₃OH production as well as mass transfer limitation caused by CO₂ concentration, which are consistent with findings in the literature. After validating the model, in the second part of the study, some design parameters of the cell, such as cathode geometry and catholyte/anolyte channel widths, are modified to reach better performance and higher faradaic efficiency of methanol production.

Keywords: carbon dioxide, electrochemical reduction, methanol, modeling

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Authors: John Davidson, Matteo Castelletti, Ismael Torres, Victor Terente, Jamie Irvine, Sylvie Raymackers

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The current industry approach to pile driving predictions consists of developing a model of the hammer-pile-soil system which simulates the relationship between soil resistance to driving (SRD) and blow counts (or pile penetration per blow). The SRD methods traditionally used are broadly based on static pile capacity calculations. The SRD is used in combination with the one-dimensional wave equation model to indicate the anticipated blowcounts with depth for specific hammer energy settings. This approach has predominantly been calibrated on relatively long slender piles used in the oil and gas industry but is now being extended to allow calculations to be undertaken for relatively short rigid large diameter monopile foundations. This paper evaluates the accuracy of current industry practice when applied to a site where large diameter monopiles were installed in predominantly stiff fissured clay. Actual geotechnical and pile installation data, including pile driving records and signal matching analysis (based upon pile driving monitoring techniques), were used for the assessment on the case study site.

Keywords: driven piles, fissured clay, London clay, monopiles, offshore foundations

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Authors: Achim Kampker, Peter Burggräf, Moritz Krunke, Hanno Voet

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As a reaction to current challenges in factory planning, many companies think about introducing factory standards to lower planning times and decrease planning costs. If these factory standards are set-up with a high level of modularity, they are defined as modular factory systems. This paper deals with the main current problems in the application of modular factory systems in practice and presents a solution approach with its basic models. The methodology is based on methods from factory planning but also uses the tools of other disciplines like product development or technology management to deal with the high complexity, which the development of modular factory systems implies. The four basic models that such a methodology has to contain are introduced and pointed out.

Keywords: factory planning, modular factory systems, factory standards, cost-benefit analysis

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Authors: Anwar Jarndal

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In this paper, a genetic-neural-network (GNN) based large-signal model for GaN HEMTs is presented along with its parameters extraction procedure. The model is easy to construct and implement in CAD software and requires only DC and S-parameter measurements. An improved decomposition technique is used to model self-heating effect. Two GNN models are constructed to simulate isothermal drain current and power dissipation, respectively. The two model are then composed to simulate the drain current. The modeling procedure was applied to a packaged GaN-on-Si HEMT and the developed model is validated by comparing its large-signal simulation with measured data. A very good agreement between the simulation and measurement is obtained.

Keywords: GaN HEMT, computer-aided design and modeling, neural networks, genetic optimization

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Authors: Martin Hewing, Katharina Hölzle

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Organizations increasingly use environmental stimuli and ideas from users within participatory innovation processes in order to tap new sources of knowledge. The research presented in this article focuses on users who shape the distant edges of markets and currently are not using products and services from a domain– so called potential users. Those users at the peripheries are perceived to contribute more novel information, by which they better reflect shifts in needs and behavior than current users in the core market. Their contributions in collaborative and creative problem-solving processes and how they generate ideas for discontinuous innovations are of particular interest. With an experimental design, we compare ideas from potential and current users and analyze the effects of cognitive distance in collaboration and the utilization of explicit and tacit knowledge. We find potential users to generate more original ideas, particularly when they collaborate with someone experienced within the domain. Their ideas are most obviously characterized by an increased level of surprise and unusualness compared to dominant designs, which is rooted in contexts and does not require technological leaps. Collaboration with potential users can therefore result in new ways to leverage technological competences. Furthermore, the cross-fertilization arising from cognitive distance between a potential and a current user is asymmetric due to differences in the nature of their utilized knowledge and personal objectives. This paper discusses implications for innovation research and the management of early innovation processes.

Keywords: user collaboration, co-creation, discontinuous innovation, innovation research

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Authors: Veronica Kah Jo Wong, Yoke Mui Lim, Nurul Sakina Mokhtar Azizi

Abstract:

The impact on the construction industry in Malaysia is unprecedented, as the government implemented a lockdown to restrict human movement in an effort to stop COVID-19 from spreading. Quantity surveyor (QS), as one of the key construction professionals, found that the working practices and environments for quantity surveyors today have changed due to the current pandemic. The QS profession must deal not only with changes in project issues but also with a different working environment in which most people are required to work from home and follow the standard operating procedures. Therefore, QS should be flexible, agile, and have the capability to adapt to the current working practices by strengthening their competencies. Adapting to the current and recovering environment of COVID-19 may result in the emergence of a new competence such as skill and knowledge for QS in order to maintain the quality of performance in the delivery of their professional services. Thus, this paper's objective is to investigate the changes in knowledge and skills in quantity surveyors. The data will be collected through interviews with registered professional QS to gain better insights that are specific in this industry, and the findings will be verified using the Delphi method. It is hoped that new knowledge and skill will be found from the study and will not only contribute to the betterment of the professional QS but also in guiding higher learning institutions to incorporate the new competencies into their curriculum.

Keywords: competency, COVID-19 pandemic, Malaysia, quantity surveying

Procedia PDF Downloads 129

Authors: Yung-Shan Lu, Chia-Fone Lee, Shang-Hsuan Li, Chien-Hao Liu

Abstract:

Recently, various bioelectronic devices have been developed for neurologic disease treatments via electro-stimulations such as cochlear implants and retinal prosthesis. Since the electric signal needs electrodes to be transmitted to an organism, electrodes play an important role of stimulations. The materials of stimulation electrodes affect the efficiency of the delivered currents. The higher the efficiency of the electrodes, the lower the threshold current can be used to stimulate the organism which minimizes the potential damages to the adjacent tissues. In this study, we proposed a biocompatible composite electrode composed of high-charge-capacity iridium oxide (IrOₓ) film for a bone-guide extra-cochlear implant. IrOₓ was exploited to decrease the threshold current due to its high capacitance and low impedance. The IrOₓ electrode was fabricated via microelectromechanical systems (MEMS) photolithography and examined with in-vivo tests with guinea pigs. Based on the measured responses of brain waves to sound, the results demonstrated that IrOₓ electrodes have a lower threshold current compared with the Platinum (Pt) electrodes. The research results are expected to be beneficial for implantable and biocompatible electrodes for electrical stimulations.

Keywords: cochlear implants, electrode, electrical stimulation, iridium oxide

Procedia PDF Downloads 189