Search results for: indoor network performance

Authors: Zahid Ullah, Atlas Khan

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This abstract focuses on the advancements in mathematical modeling and optimization techniques that play a crucial role in enhancing the efficiency, reliability, and performance of these systems. In this era of rapidly evolving technology, mathematical modeling and optimization offer powerful tools to tackle the complex challenges faced by control, signal processing, and energy systems. This abstract presents the latest research and developments in mathematical methodologies, encompassing areas such as control theory, system identification, signal processing algorithms, and energy optimization. The abstract highlights the interdisciplinary nature of mathematical modeling and optimization, showcasing their applications in a wide range of domains, including power systems, communication networks, industrial automation, and renewable energy. It explores key mathematical techniques, such as linear and nonlinear programming, convex optimization, stochastic modeling, and numerical algorithms, that enable the design, analysis, and optimization of complex control and signal processing systems. Furthermore, the abstract emphasizes the importance of addressing real-world challenges in control, signal processing, and energy systems through innovative mathematical approaches. It discusses the integration of mathematical models with data-driven approaches, machine learning, and artificial intelligence to enhance system performance, adaptability, and decision-making capabilities. The abstract also underscores the significance of bridging the gap between theoretical advancements and practical applications. It recognizes the need for practical implementation of mathematical models and optimization algorithms in real-world systems, considering factors such as scalability, computational efficiency, and robustness. In summary, this abstract showcases the advancements in mathematical modeling and optimization techniques for control, signal processing, and energy systems. It highlights the interdisciplinary nature of these techniques, their applications across various domains, and their potential to address real-world challenges. The abstract emphasizes the importance of practical implementation and integration with emerging technologies to drive innovation and improve the performance of control, signal processing, and energy.

Keywords: mathematical modeling, optimization, control systems, signal processing, energy systems, interdisciplinary applications, system identification, numerical algorithms

Procedia PDF Downloads 94

Authors: Hussin K. Ragb, Vijayan K. Asari

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In this paper, we present a pedestrian detection descriptor called Fused Structure and Texture (FST) features based on the combination of the local phase information with the texture features. Since the phase of the signal conveys more structural information than the magnitude, the phase congruency concept is used to capture the structural features. On the other hand, the Center-Symmetric Local Binary Pattern (CSLBP) approach is used to capture the texture information of the image. The dimension less quantity of the phase congruency and the robustness of the CSLBP operator on the flat images, as well as the blur and illumination changes, lead the proposed descriptor to be more robust and less sensitive to the light variations. The proposed descriptor can be formed by extracting the phase congruency and the CSLBP values of each pixel of the image with respect to its neighborhood. The histogram of the oriented phase and the histogram of the CSLBP values for the local regions in the image are computed and concatenated to construct the FST descriptor. Several experiments were conducted on INRIA and the low resolution DaimlerChrysler datasets to evaluate the detection performance of the pedestrian detection system that is based on the FST descriptor. A linear Support Vector Machine (SVM) is used to train the pedestrian classifier. These experiments showed that the proposed FST descriptor has better detection performance over a set of state of the art feature extraction methodologies.

Keywords: pedestrian detection, phase congruency, local phase, LBP features, CSLBP features, FST descriptor

Procedia PDF Downloads 468

Authors: Vinayambika S. Bhat, S. Shanmuga Priya, I. Thirunavukkarasu, Shreeranga Bhat

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An attempt has been made to design a decoupling controller for systems with more inputs more outputs with dead time in it. The de-coupler is designed for the chemical process industry 3×3 plant transfer function with dead time. The Quantitative Feedback Theory (QFT) based controller has also been designed here for the 2×2 distillation column transfer function. The developed control techniques were simulated using the MATLAB/Simulink. Also, the stability of the process was analyzed, together with the presence of various perturbations in it. Time domain specifications like setting time along with overshoot and oscillations were analyzed to prove the efficiency of the de-coupler method. The load disturbance rejection was tested along with its performance. The QFT control technique was synthesized based on the stability and performance specifications in the presence of uncertainty in time constant of the plant transfer function through sequential loop shaping technique. Further, the energy efficiency of the distillation column was improved by proper tuning of the controller. A distillation column consumes 3% of the total energy consumption of the world. A suitable control technique is very important from an economic point of view. The real time implementation of the process is under process in our laboratory.

Keywords: distillation, energy, MIMO process, time delay, robust stability

Procedia PDF Downloads 398

Authors: Vidhi Jain

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Communication between speakers and non-speakers of American Sign Language (ASL) can be problematic, inconvenient, and expensive. This project attempts to bridge the communication gap by designing a portable glove that captures the user’s ASL gestures and outputs the translated text on a smartphone. The glove is equipped with flex sensors, contact sensors, and a gyroscope to measure the flexion of the fingers, the contact between fingers, and the rotation of the hand. The glove’s Arduino UNO microcontroller analyzes the sensor readings to identify the gesture from a library of learned gestures. The Bluetooth module transmits the gesture to a smartphone. Using this device, one day speakers of ASL may be able to communicate with others in an affordable and convenient way.

Keywords: sign language, morse code, convolutional neural network, American sign language, gesture recognition

Procedia PDF Downloads 48

Authors: Yaser Al-Anii, Abdulmajeed Almaneea, Jonathan L. Summers, Harvey M. Thompson, Nikil Kapur

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The natural convection cooling system of a fully immersed server in a dielectric liquid is studied numerically. In the present case study, the dielectric liquid represents working fluid and it is in contact with server inside capsule. The capsule includes electronic component and fluid which can be modeled as saturated porous media. This medium follow Darcy flow regime and assumed to be in balance between its components. The study focus is on role of spatial parameters on thermal behavior of convective heat transfer. Based on server known unit, which is 1U, two parameters Ly and S are changed to test their effect. Meanwhile, wide-range of modified Rayleigh number, which is 0.5 to 300, are covered to better understand thermal performance. Navier-Stokes equations are used to model physical domain. Furthermore, successive over-relaxation and time marching techniques are used to solve momentum and energy equation. From obtained correlation, the in-between distance S is more effective on Nusselt number than distance to edge Ly by approximately 14%. In addition, as S increases, the average Nusselt number of the upper unit increases sharply, whereas the lower one keeps on the same level.

Keywords: convective cooling of server, Darcy flow, liquid-immersed server, porous media

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Authors: Kazushige Wada, Mayuko Ueda

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In the present study, we reanalyzed lapse errors in the last phase of a job, by re-counting near lapse errors and increasing the number of participants. We also examined the results of this study from the perspective of prospective memory (PM), which concerns future actions. This study was designed to investigate whether perceiving the importance of PM tasks caused lapse errors in the last phase of a job and to determine if such errors could be explained from the perspective of PM processing. Participants (N = 34) conducted a computerized clicking task, in which they clicked on 10 figures that they had learned in advance in 8 blocks of 10 trials. Participants were requested to click the check box in the start display of a block and to click the checking off box in the finishing display. This task was a PM task. As a measure of PM performance, we counted the number of omission errors caused by forgetting to check off in the finishing display, which was defined as a lapse error. The perceived importance was manipulated by different instructions. Half the participants in the highly important task condition were instructed that checking off was very important, because equipment would be overloaded if it were not done. The other half in the not important task condition was instructed only about the location and procedure for checking off. Furthermore, we controlled workload and the emotion of surprise to confirm the effect of demand capacity and attention. To manipulate emotions during the clicking task, we suddenly presented a photo of a traffic accident and the sound of a skidding car followed by an explosion. Workload was manipulated by requesting participants to press the 0 key in response to a beep. Results indicated too few forgetting induced lapse errors to be analyzed. However, there was a weak main effect of the perceived importance of the check task, in which the mouse moved to the “END” button before moving to the check box in the finishing display. Especially, the highly important task group showed more such near lapse errors, than the not important task group. Neither surprise, nor workload affected the occurrence of near lapse errors. These results imply that high perceived importance of PM tasks impair task performance. On the basis of the multiprocess framework of PM theory, we have suggested that PM task performance in this experiment relied not on monitoring PM tasks, but on spontaneous retrieving.

Keywords: prospective memory, perceived importance, lapse errors, multi process framework of prospective memory.

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Authors: Seyed Hossein Iranmanesh, Hassan Nouri, Seyed Reza Iranmanesh

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In the dynamic and complex landscape of today’s business, organizations often face challenges in impactful decision-making across multi-project settings. To efficiently allocate resources, coordinate tasks, and optimize project outcomes, establishing robust decision-making processes is essential. Furthermore, the increasing importance of information systems and their integration within organizational workflows introduces an additional layer of complexity. This research proposes the use of blockchain technology as a suitable solution to enhance decision-making in multi-project environments, particularly within the realm of information systems. The conceptual framework in this study comprises four independent variables and one dependent variable. The identified independent variables for the targeted research include: Blockchain Layer in Integrated Systems, Quality of Generated Information ,User Satisfaction with Integrated Systems and Utilization of Integrated Systems. The project’s performance, considered as the dependent variable and moderated by organizational policies and procedures, reflects the impact of blockchain technology adoption on organizational effectiveness1. The results highlight the significant influence of blockchain implementation on organizational performance.

Keywords: multi-project environments, decision support systems, information systems, blockchain technology, decentralized systems.

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Authors: Pablo Lopez Hurtado, Antroine Rouilly, Virginie Vandenbossche

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Cellulose fibre insulation is an eco-friendly building material made from recycled paper fibres, treated with borates for fungal and fire resistance. It is comparable in terms of thermal and acoustic performance to mineral wool insulation and other insulation materials based on non-renewable resources. The main method of application consists in separating and blowing the fibres in attics or closed wall cavities. Another method, known as the “wet spray method” is gaining interest. With this method the fibres are projected with pulverized water, which stick to the wall cavities. The issue with the wet spray technique is that the water dosage could be difficult to control. A high water dosage implies not only a longer drying time, depending on ambient conditions, but also a change in the performance of the material itself. In our work we studied the thermal and mechanical properties of wet spray-cellulose insulation in order to understand how water dosage could affect these properties. The material was first characterized to study the chemical and physical properties of the fibres. Then representative samples of wet sprayed cellulose with varying applied water dosage were subject to thermal conductivity and compression testing in order to better understand how changes in the fibres induced by drying can affect these properties.

Keywords: cellulose fibre, recycled paper, moisture sorption, thermal insulation

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Authors: Ming-Yeh Lu, Shiao-Shing Chen, Saikat Sinha Ray, Hung-Te Hsu

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The submerged anaerobic osmotic membrane bioreactor (AnOMBR) integrated with periodic microfiltration (MF) extraction for simultaneous phosphorus and clean water recovery from wastewater was evaluated. A laboratory-scale AnOMBR used cellulose triacetate (CTA) membranes with effective membrane area of 130 cm² was fully submerged into a 5 L bioreactor at 30-35 ℃. Active layer was orientated to feed stream for minimizing membrane fouling and scaling. Additionally, a peristaltic pump was used to circulate magnesium sulphate (MgSO₄) solution applied as draw solution (DS). Microfiltration membrane periodically extracted about 1 L solution when the TDS reaches to 5 g/L to recover phosphorus and simultaneously control the salt accumulation in the bioreactor. During experiment progress, the average water flux was around 1.6 LMH. The AnOMBR process showed greater than 95% removal of soluble chemical oxygen demand (sCOD), nearly 100% of total phosphorous whereas only partial of ammonia was removed. On the other hand, the average methane production of 0.22 L/g sCOD was obtained. Subsequently, the overall performance demonstrates that a novel submerged AnOMBR system is potential for simultaneous wastewater treatment and resource recovery from wastewater. Therefore, the new concept of this system can be used to replace for the conventional AnMBR in the future.

Keywords: anaerobic treatment, forward osmosis, phosphorus recovery, membrane bioreactor

Procedia PDF Downloads 218

Authors: O. I. Nkwonta, B. Dzwairo, J. Adeyemo, A. Jaiyola, N. Sawyerr, F. Otieno

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The effective management of water resources is of great importance to ensure the supply of water resources to support changing water requirements over a selected planning horizon and in a sustainable and cost-effective way. Essentially, the purpose of the water resources planning process is to balance the available water resources in a system with the water requirements and losses to which the system is subjected. In such situations, Water resources yield and planning model can be used to solve those difficulties. It has an advantage over other models by managing model runs, developing a representative system network, modelling incremental sub-catchments, creating a variety of standard system features, special modelling features, and run result output options.

Keywords: complex, water resources, planning, cost effective and management

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Authors: Bistra Kunovska, Kremena Ivanova, Jana Djounova, Desislava Djunakova, Zdenka Stojanovska

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The carcinogenic effects of radon as a radioactive noble gas have been studied and show a strong correlation between radon exposure and lung cancer occurrence, even in the case of low radon levels. The major part of the natural radiation dose in humans is received by inhaling radon and its progenies, which originates from the decay chain of U-238. Indoor radon poses a substantial threat to human health when build-up occurs in confined spaces such as homes, mines and caves and the risk increases with the duration of radon exposure and is proportional to both the radon concentration and the time of exposure. Tourist caves are a case of special environmental conditions that may be affected by high radon concentration. Tourist caves are a recognized danger in terms of radon exposure to cave workers (guides, employees working in shops built above the cave entrances, etc.), but due to the sensitive nature of the cave environment, high concentrations cannot be easily removed. Forced ventilation of the air in the caves is considered unthinkable due to the possible harmful effects on the microclimate, flora and fauna. The risks to human health posed by exposure to elevated radon levels in caves are not well documented. Various studies around the world often detail very high concentrations of radon in caves and exposure of employees but without a follow-up assessment of the overall impact on human health. This study was developed in the implementation of a national project to assess the potential health effects caused by exposure to elevated levels of radon in buildings with public access under the National Science Fund of Bulgaria, in the framework of grant No КП-06-Н23/1/07.12.2018. The purpose of the work is to assess the radon level in Bulgarian caves and the exposure of the visitors and workers. The number of caves (sampling size) was calculated for simple random selection from total available caves 65 (sampling population) are 13 caves with confidence level 95 % and confidence interval (margin of error) approximately 25 %. A measurement of the radon concentration in air at specific locations in caves was done by using CR-39 type nuclear track-etch detectors that were placed by the participants in the research team. Despite the fact that all of the caves were formed in karst rocks, the radon levels were rather different from each other (97–7575 Bq/m3). An assessment of the influence of the orientation of the caves in the earth's surface (horizontal, inclined, vertical) on the radon concentration was performed. Evaluation of health hazards and radon risk exposure causing by inhaling the radon and its daughter products in each surveyed caves was done. Reducing the time spent in the cave has been recommended in order to decrease the exposure of workers.

Keywords: tourist caves, radon concentration, exposure, Bulgaria

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Authors: Salman Hameed

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In this paper, a self-tuning fuzzy PI controller (STFPIC) is proposed for thyristor controlled series capacitor (TCSC) to improve power system dynamic performance. In a STFPIC controller, the output scaling factor is adjusted on-line by an updating factor (α). The value of α is determined from a fuzzy rule-base defined on error (e) and change of error (Δe) of the controlled variable. The proposed self-tuning controller is designed using a very simple control rule-base and the most natural and unbiased membership functions (MFs) (symmetric triangles with equal base and 50% overlap with neighboring MFs). The comparative performances of the proposed STFPIC and the standard fuzzy PI controller (FPIC) have been investigated on a multi-machine power system (namely, 4 machine two area system) through detailed non-linear simulation studies using MATLAB/SIMULINK. From the simulation studies it has been found out that for damping oscillations, the performance of the proposed STFPIC is better than that obtained by the standard FPIC. Moreover, the proposed STFPIC as well as the FPIC have been found to be quite effective in damping oscillations over a wide range of operating conditions and are quite effective in enhancing the power carrying capability of the power system significantly.

Keywords: genetic algorithm, power system stability, self-tuning fuzzy controller, thyristor controlled series capacitor

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Authors: Abubakar Salisu Garba

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The objective of the paper is to highlight the nature of entrepreneurial activities in the Sub Sahara Africa. Five countries in the Sub Sahara African that are participating in Global Entrepreneurship Monitor (GEM) research have been studied to understand the types of entrepreneurial activities and their socio-economic implications in the region. The importance of entrepreneurial activities in boosting socio-economic development has been recognized not only in developing countries, but across the entire global economies. Some people believe that the wealth and poverty of developing countries is associated with nature and type of entrepreneurial activity. Policy makers are not only concern about the rate of business start up, but the growth and development of those starts up is of paramount importance to the development of the country’s economy. Although, the supply of entrepreneurs is essential, sometimes it does not really matters in boosting economic performance. What is more important is having high impact entrepreneurs who could make meaningful contribution to the economy. High growth oriented entrepreneurs are more stable and contribute greatly in enhancing the economic performance. When entrepreneurs are facing difficulties in sustaining and growing their businesses, it may be unlikely for entrepreneurship to reduce unemployment and poverty. Inadequate financial supports, insufficient infrastructure, lack of enforcing laws protecting the right of entrepreneurs are some of the problems making business environment difficult in Sub-Saharan Africa.

Keywords: entrepreneurship, entrepreneurial activity, job creation, poverty reduction, Sub-Saharan Africa

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Authors: A. Khan, M. Hussain, S. Afgun

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In the present work, the effect of the surface integration on the piezoelectric properties of zinc oxide (ZnO) nanorods has been investigated. ZnO nanorods were grown by using aqueous chemical growth method on two samples of graphene coated pet plastic substrate. First substrate’s surface was integrated with ZnO nanoparticles while the other substrate was used without ZnO nanoparticles. Various important parameters were analyzed, the growth density and morphological analysis were taken into account through surface scanning electron microscopy; it was observed that the growth density of nanorods on the integrated surface was much higher than the nonintegrated substrate. The crystal quality of growth orientation was analyzed by X-ray diffraction technique. Mechanical stability of ZnO nanorods on an integrated substrate was more appropriate than the nonintegrated substrate. The generated amount of piezoelectric potential from the integrated substrate was two times higher than the nonintegrated substrate. This shows that the layer of nanoparticles plays a crucial role in the enhancement of piezoelectric potential. Besides this, it also improves the performance of fabricated devices like its mechanical stability and piezoelectric properties. Additionally, the obtained results were compared with the other two samples used for the growth of ZnO nanorods on silver coated glass substrates for similar measurement. The consistency of the results verified the importance of surface integration effect. This study will help us to fabricate improved performance devices by using surface integrated substrates.

Keywords: ZnO nanorods, surface integration, mechanical properties, harvesting piezoelectricity

Procedia PDF Downloads 119

Authors: Salisu Dahiru, Jibrin M. Kaura, Abubakar I. Jumare, Sulaiman M. Mahmood

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Reclaimed asphalt, used automobile tires and rice husk, were regarded as waste. These materials could be used in construction of new roads and for roads rehabilitation. Investigation into the production of a Green Hot Mixed Asphalt (GHMA) pavement using Reclaimed Asphalt Pavement (RAP) as partial replacement for coarse aggregate, Crumb Rubber (CR) from waste automobile tires as modifier for bitumen binder and Rice Husk Ash (RHA) as partial replacement of ordinary portland cement (OPC) filler, for roads construction and rehabilitation was presented. 30% Reclaimed asphalt of total aggregate, 15% Crumb Rubber of total binder content, 5% Rice Husk Ash of total mix, and 5.2% Crumb Rubber Modified Bitumen content were recommended for optimum performance. Loss of marshal stability was investigated on mix with the recommended optimum CRMB. The mix revealed good performance with only about 13% loss of stability after 24 hours of immersion in hot water bath, as against about 24% marshal stability lost reported in previous studies for conventional Hot Mixed Asphalt (HMA).

Keywords: rice husk, reclaimed asphalt, filler, crumb rubber, bitumen content green hot mix asphalt

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Authors: Adnan Z. Mkhelif

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The production of number forms in English tends to be problematic for Iraqi learners of English as a foreign language (EFL), even at the undergraduate level. To help better understand and consequently address this problem, it is important to identify its sources. This study aims at: (1) statistically analysing Iraqi EFL undergraduates' performance in the production of number forms in English; (2) classifying learners' errors in terms of their possible major causes; and (3) outlining some pedagogical recommendations relevant to the teaching of number forms in English. It is hypothesized in this study that (1) Iraqi EFL undergraduates still face problems in the production of number forms in English and (2) errors pertaining to the context of learning are more numerous than those attributable to the other possible causes. After reviewing the literature available on the topic, a written test comprising 50 items has been constructed and administered to a randomly chosen sample of 50 second-year college students from the Department of English, College of Education, Wasit University. The findings of the study showed that Iraqi EFL undergraduates still face problems in the production of number forms in English and that the possible major sources of learners’ errors can be arranged hierarchically in terms of the percentages of errors to which they can be ascribed as follows: (1) context of learning (50%), (2) intralingual transfer (37%), and (3) interlingual transfer (13%). It is hoped that the implications of the study findings will be beneficial to researchers, syllabus designers, as well as teachers of English as a foreign/second language.

Keywords: L2 number forms, L2 vocabulary learning, productive knowledge, proficiency

Procedia PDF Downloads 127

Authors: Christodoulou Christos, Politis Anastasios

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A large majority of users favoured to wireless LAN connection since it was so simple to use. A wireless network can be the target of numerous attacks. Class hijacking is a well-known attack that is fairly simple to execute and has significant repercussions on users. The statistical flow analysis based on machine learning (ML) techniques is a promising categorization methodology. In a given dataset, which in the context of this paper is a collection of components representing frames belonging to various flows, machine learning (ML) can offer a technique for identifying and characterizing structural patterns. It is possible to classify individual packets using these patterns. It is possible to identify fraudulent conduct, such as class hijacking, and take necessary action as a result. In this study, we explore a way to use machine learning approaches to thwart this attack.

Keywords: wireless lan, quality of service, machine learning, class hijacking, EDCA remapping

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Authors: C. Mayr, J. Periya, A. Kariminezhad

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In this paper, we developed a learning framework for the classification of vulnerable road users (VRU) by their range-Doppler signatures. The frequency-modulated continuous-wave (FMCW) radar raw data is first pre-processed to obtain robust object range-Doppler maps per coherent time interval. The complex-valued range-Doppler maps captured from our outdoor measurements are further fed into a convolutional neural network (CNN) to learn the classification. This CNN has gone through a hyperparameter optimization process for improved learning. By learning VRU range-Doppler signatures, the three classes 'pedestrian', 'dog', and 'noise' are classified with an average accuracy of almost 95%. Interestingly, this classification accuracy holds for a combined longitudinal and lateral object trajectories.

Keywords: machine learning, radar, signal processing, autonomous driving

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Authors: Shital Patil, Surendra Bhosale

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Cardiac diseases are the leading causes of mortality and morbidity in the world, from recent few decades accounting for a large number of deaths have emerged as the most life-threatening disorder globally. Machine learning and Artificial intelligence have been playing key role in predicting the heart diseases. A relevant set of feature can be very helpful in predicting the disease accurately. In this study, we proposed a comparative analysis of 4 different features selection methods and evaluated their performance with both raw (Unbalanced dataset) and sampled (Balanced) dataset. The publicly available Z-Alizadeh Sani dataset have been used for this study. Four feature selection methods: Data Analysis, minimum Redundancy maximum Relevance (mRMR), Recursive Feature Elimination (RFE), Chi-squared are used in this study. These methods are tested with 8 different classification models to get the best accuracy possible. Using balanced and unbalanced dataset, the study shows promising results in terms of various performance metrics in accurately predicting heart disease. Experimental results obtained by the proposed method with the raw data obtains maximum AUC of 100%, maximum F1 score of 94%, maximum Recall of 98%, maximum Precision of 93%. While with the balanced dataset obtained results are, maximum AUC of 100%, F1-score 95%, maximum Recall of 95%, maximum Precision of 97%.

Keywords: cardio vascular diseases, machine learning, feature selection, SMOTE

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Authors: Eda Orhun

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This paper studies the IELTS exit scores of Emirati university students before graduation and specifically compares the IELTS exit performance of the English foundation program (FP) students to direct entry (DE) students. Direct entry (DE) students are the students who were able to directly start with the undergraduate program without the need to attend English foundation program courses as they were able to prove a sufficient level of English at the university admittance. The results clearly show that the gap that existed already between these two groups of students at the start does not seem to disappear at the end of university studies, as DE students’ IELTS exit scores are significantly higher compared to FP students. Further work of a regression analysis exhibits that GPA and CMATH scores do have a positive and significant effect on IELTS exit scores. In addition, while the College of Education students are found to have the lowest performance in every sub-section of the IELTS exam across colleges, students of the College of Humanities and Social Sciences and the College of Natural and Health Sciences seem to have the best reading skills. Another important determinant of IELTS exit scores is found to be the English level of students at inception. With these results, the study offers important policy implications regarding the public education system of the UAE and sheds light on the main roots of the problem.

Keywords: English proficiency, higher education, IELTS exit scores, English foundation program, United Arab Emirates

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Authors: James M. Wakiru, Liliane Pintelon, Peter Muchiri, Peter Chemweno

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The fast-changing business and operational environment are forcing organizations to adopt asset performance management strategies, not only to reduce costs but also maintain operational and production policies while addressing demand. To attain optimal asset performance management, a framework that ensures a continuous and systematic approach to analyzing an organization’s current maturity level and expected improvement regarding asset maintenance processes, strategies, technologies, capabilities, and systems is essential. Moreover, this framework while addressing maintenance-intensive organizations should consider the diverse business, operational and technical context (often dynamic) an organization is in and realistically prescribe or relate to the appropriate tools and systems the organization can potentially employ in the respective level, to improve and attain their maturity goals. This paper proposes an asset maintenance maturity model to assess the current capabilities, strength and weaknesses of maintenance processes an organization is using and analyze gaps for improvement via structuring set levels of achievement. At the epicentre of the proposed framework is the utilization of maintenance objective selected by an organization for various maintenance optimization programs. The framework adapts the Capability Maturity Model of assessing the maintenance process maturity levels in the organization.

Keywords: asset maintenance, maturity models, maintenance objectives, optimization

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Authors: Ari Prasetyo, Taufik Faturohman

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The COVID-19 pandemic in Indonesia is part of the ongoing worldwide pandemic of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It was confirmed to have spread to Indonesia on 2 March 2020. Moreover, the government of Indonesia has been conducting a local lockdown to limit people's movement from one city to another city. Therefore, this situation has impact on business operation, especially on highway companies listed on the Indonesia stock exchange. This study evaluates and measures three companies’ financial performance and health conditions before and during the COVID-19 pandemic from 2016 – 2020. The measurement is conducted by using financial ratio analysis and the Altman Z-score method. The ratio used to measure the financial ratio analysis is taken from the decree of the Ministry of SOE’s KEP-100/MBU/2002 about the company’s health level condition. From the decree, there are eight financial ratios used such as return on equity (ROE), return on investment (ROI), current ratio, cash ratio, collection period, inventory turnover, total asset turnover, and total equity to total asset. Altman Z-score is used to calculate the financial distress condition. The result shows that the highway companies for the period 2016 – 2020 are as follows: PT Jasa Marga (Persero) Tbk (AA, BB, BB, BB, C), PT Citra Marga Nusaphala Persada Tbk (BB, AA, BB, BBB, C), and PT Nusantara Infrastructure Tbk (BB, BB, AA, BBB, C). In addition, the Altman Z-score assessment performed in 2016-2020 shows that PT Jasa Marga (Persero) Tbk was in the grey zone area for 2015-2018 and in the distress zone for 2019-2020. PT Citra Marga Nusaphala Persada Tbk was in the grey zone area for 2015-2019 and in the distress zone for 2020. PT Nusantara Infrastructure Tbk was in the grey zone area for 2015-2018 and in the distress zone for 2019-2020.

Keywords: financial performance, financial ratio, Altman Z-score, financial distress, highway company

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Authors: Saeed Ahmed, Muhammad Imran, Yasir Allah Ditta, Shahid Mehmood, Zahid Rasool

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A study was conducted to investigate the effect of different levels of microencapsulated butyric (MEB) on growth performance, gut health and immunity in commercial broiler chickens. In total, 336 day-old Hubbard classic broilers chicks were randomly assigned to 4 dietary treatments (Control, 0.25, 0.35 and 0.45g/kg of butyric acid) under completely randomized design. Each treatment was replicated 3 times with 28 birds in each replicate. Feed intake, body weight gain, feed conversion ratio, intestinal morphology, apparent ileal digestibility of protein and immunity parameters were evaluated. At the end of the experiment (35-d) 3 birds/replicate in each group were randomly selected and slaughtered to collect blood, duodenal samples and ileal digesta. The data were analyzed by using ANOVA technique. The results indicated improved body weight gain (P = 0.0222), feed conversion ratio (P = 0.0056), duodenal villus height (P = 0.0512), AID (P = 0.0098) antibody titer against Newcastle disease improved (P = 0.0326). Treatments remained unresponsive with respect to feed intake (P = 0.9685).

Keywords: butyric acid, broilers, gut health, ileal digestibility

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Authors: Ali H. Muhammad

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The present study examines some antecedents and consequences of employee job involvement in Kuwaiti business organization. The model presented in the current study suggests that job satisfaction and organizational commitments are determinates of job involvements. Employees who are satisfied with their jobs tend to be more attached to their jobs and view their jobs as an essential part of their existence. Similarly, employees who are committed to organizational goals, and identify with organizational values, tend to have high level of involvement. Furthermore, our model suggests that job involvement is positively related to work performance and organizational citizenship behavior. The negative consequences of job involvement include burnout and work family conflict. To test the hypotheses, a sample of 204 Kuwaiti employees representing 8 Kuwaiti work organizations is used. The sample covers a variety of business sectors in Kuwait, including manufacturing, services, and transportation. The data were analyzed using non-parametric tests, Pearson correlations, and structural equation modeling. Results indicate that job satisfaction and organizational commitment have significant positive effects on job involvement. Furthermore, findings reveal that job involvement is positively associated with performance, organization citizenship behavior, and work family conflict. Findings are discussed, and future areas of research are identified.

Keywords: job involvement, organizational citizenship behavior, work family conflict, burnout

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Authors: Nina N. Serdar, Jelena R. Pejović

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This paper presents seismic risk assessment of two bridge structure, based on the probabilistic performance-based seismic assessment methodology. Both investigated bridges are tree span continuous RC curved bridges with the difference in column shapes. First bridge (type A) has a wall-type pier and second (type B) has a two-column bent with circular columns. Bridges are designed according to European standards: EN 1991-2, EN1992-1-1 and EN 1998-2. Aim of the performed analysis is to compare seismic behavior of these two structures and to detect the influence of column shapes on the seismic response. Seismic risk assessment is carried out by obtaining demand fragility curves. Non-linear model was constructed and time-history analysis was performed using thirty five pairs of horizontal ground motions selected to match site specific hazard. In performance based analysis, peak column drift ratio (CDR) was selected as engineering demand parameter (EDP). For seismic intensity measure (IM) spectral displacement was selected. Demand fragility curves that give probability of exceedance of certain value for chosen EDP were constructed and based on them conclusions were made.

Keywords: RC curved bridge, demand fragility curve, wall type column, nonlinear time-history analysis, circular column

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Authors: Shan Jia, Jinbao Chen, Jinhua Zhou, Jiacheng Qian

Abstract:

In response to the functional limitations of the fixed landers, those are to expand the detection range by the use of wheeled rovers with unavoidable path-repeatability in deep space exploration currently, a movable lander based on the leg-foot walking mechanism is presented. Firstly, a quadruped landing mechanism based on pushrod-damping is proposed. The configuration is of the bionic characteristics such as hip, knee and ankle joints, and the multi-function main/auxiliary buffers based on the crumple-energy absorption and screw-nut mechanism. Secondly, the workspace of the end of the leg-foot mechanism is solved by Monte Carlo method, and the key points on the desired trajectory of the end of the leg-foot mechanism are fitted by cubic spline curve. Finally, an optimal time-jerk trajectory based on weight coefficient is planned and analyzed by an adaptive genetic algorithm (AGA). The simulation results prove the rationality and stability of walking motion of the movable leg-foot lander in the star catalogue. In addition, this research can also provide a technical solution integrating of soft-landing, large-scale inspection and material transfer for future star catalogue exploration, and can even serve as the technical basis for developing the reusable landers.

Keywords: motion performance, trajectory planning, movable, leg-foot lander

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Authors: Suniti Suparp, Panuwat Joyklad, Qudeer Hussain

Abstract:

This is a well-known fact that the actual latera forces due to natural disasters, for example, earthquakes, floods and storms are difficult to predict accurately. Among these natural disasters, so far, the highest amount of deaths and injuries have been recorded for the case of earthquakes all around the world. Therefore, there is always an urgent need to establish suitable strengthening methods for existing concrete and steel structures. This paper is investigating the structural performance of square concrete columns strengthened using low cost and easily available steel clamps. The salient features of these steel clamps are comparatively low cost, easy availability and ease of installation. To achieve research objectives, a large-scale experimental program was established in which a total number of 12 square concrete columns were constructed and tested under pure axial compression. Three square concrete columns were tested without any steel lamps to serve as a reference specimen. Whereas, remaining concrete columns were externally strengthened using steel clamps. The steel clamps were installed at a different spacing to investigate the best configuration of the steel clamps. The experimental results indicate that steel clamps are very effective in altering the structural performance of the square concrete columns. The square concrete columns externally strengthened using steel clamps demonstrate higher load carrying capacity and ductility as compared with the control specimens.

Keywords: concrete, strength, ductility, pre-stressed, steel, clamps, axial compression, columns, stress and strain

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Authors: M. Chafi, S. Akazdam, C. Asrir, L. Sebbahi, B. Gourich, N. Barka, M. Essahli

Abstract:

Fixed bed adsorption has become a frequently used industrial application in wastewater treatment processes. Various low cost adsorbents have been studied for their applicability in treatment of different types of effluents. In this work, the intention of the study was to explore the efficacy and feasibility for azo dye, Acid Orange 7 (AO7) adsorption onto fixed bed column of NaOH Treated eggshell (TES). The effect of various parameters like flow rate, initial dye concentration, and bed height were exploited in this study. The studies confirmed that the breakthrough curves were dependent on flow rate, initial dye concentration solution of AO7 and bed depth. The Thomas, Yoon–Nelson, and Adams and Bohart models were analysed to evaluate the column adsorption performance. The adsorption capacity, rate constant and correlation coefficient associated to each model for column adsorption was calculated and mentioned. The column experimental data were fitted well with Thomas model with coefficients of correlation R2 ≥0.93 at different conditions but the Yoon–Nelson, BDST and Bohart–Adams model (R2=0.911), predicted poor performance of fixed-bed column. The (TES) was shown to be suitable adsorbent for adsorption of AO7 using fixed-bed adsorption column.

Keywords: adsorption models, acid orange 7, bed depth, breakthrough, dye adsorption, fixed-bed column, treated eggshell

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Authors: Danna Jia, Bin Li

Abstract:

Background: Atopic dermatitis (AD) is a chronic and refractory inflammatory skin disease characterized by relapsing eczematous and pruritic skin lesions. The global prevalence of AD ranges from 1~ 20%, and its incidence rates are increasing. It affects individuals from infancy to adulthood, significantly impacting their daily lives and social activities. Despite its major health burden, the precise mechanisms underlying AD remain unknown. Understanding the genetic differences associated with AD is crucial for advancing diagnosis and targeted treatment development. This study aims to identify candidate genes of AD by using bioinformatics analysis. Methods: We conducted a comprehensive analysis of four pooled transcriptomic datasets (GSE16161, GSE32924, GSE130588, and GSE120721) obtained from the Gene Expression Omnibus (GEO) database. Differential gene expression analysis was performed using the R statistical language. The differentially expressed genes (DEGs) between AD patients and normal individuals were functionally analyzed using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Furthermore, a protein-protein interaction (PPI) network was constructed to identify candidate genes. Results: Among the patient-level gene expression datasets, we identified 114 shared DEGs, consisting of 53 upregulated genes and 61 downregulated genes. Functional analysis using GO and KEGG revealed that the DEGs were mainly associated with the negative regulation of transcription from RNA polymerase II promoter, membrane-related functions, protein binding, and the Human papillomavirus infection pathway. Through the PPI network analysis, we identified eight core genes: CD44, STAT1, HMMR, AURKA, MKI67, and SMARCA4. Conclusion: This study elucidates key genes associated with AD, providing potential targets for diagnosis and treatment. The identified genes have the potential to contribute to the understanding and management of AD. The bioinformatics analysis conducted in this study offers new insights and directions for further research on AD. Future studies can focus on validating the functional roles of these genes and exploring their therapeutic potential in AD. While these findings will require further verification as achieved with experiments involving in vivo and in vitro models, these results provided some initial insights into dysfunctional inflammatory and immune responses associated with AD. Such information offers the potential to develop novel therapeutic targets for use in preventing and treating AD.

Keywords: atopic dermatitis, bioinformatics, biomarkers, genes

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Authors: Harris Niavis, Dimitra Politaki

Abstract:

The manufacturing industry was collecting vast amounts of data for monitoring product quality thanks to the advances in the ICT sector and dedicated IoT infrastructure is deployed to track and trace the production line. However, industries have not yet managed to unleash the full potential of these data due to defective data collection methods and untrusted data storage and sharing. Blockchain is gaining increasing ground as a key technology enabler for Industry 4.0 and the smart manufacturing domain, as it enables the secure storage and exchange of data between stakeholders. On the other hand, AI techniques are more and more used to detect anomalies in batch and time-series data that enable the identification of unusual behaviors. The proposed scheme is based on smart contracts to enable automation and transparency in the data exchange, coupled with anomaly detection algorithms to enable reliable data ingestion in the system. Before sensor measurements are fed to the blockchain component and the smart contracts, the anomaly detection mechanism uniquely combines artificial intelligence models to effectively detect unusual values such as outliers and extreme deviations in data coming from them. Specifically, Autoregressive integrated moving average, Long short-term memory (LSTM) and Dense-based autoencoders, as well as Generative adversarial networks (GAN) models, are used to detect both point and collective anomalies. Towards the goal of preserving the privacy of industries' information, the smart contracts employ techniques to ensure that only anonymized pointers to the actual data are stored on the ledger while sensitive information remains off-chain. In the same spirit, blockchain technology guarantees the security of the data storage through strong cryptography as well as the integrity of the data through the decentralization of the network and the execution of the smart contracts by the majority of the blockchain network actors. The blockchain component of the Data Traceability Software is based on the Hyperledger Fabric framework, which lays the ground for the deployment of smart contracts and APIs to expose the functionality to the end-users. The results of this work demonstrate that such a system can increase the quality of the end-products and the trustworthiness of the monitoring process in the smart manufacturing domain. The proposed AI-enabled data traceability software can be employed by industries to accurately trace and verify records about quality through the entire production chain and take advantage of the multitude of monitoring records in their databases.

Keywords: blockchain, data quality, industry4.0, product quality

Procedia PDF Downloads 168