Search results for: total load approach

Authors: Vinai K. Singh

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In Neural Network-based Learning techniques, there are several models of Convolutional Networks. Whenever the methods are deployed with large datasets, only then can their applicability and appropriateness be determined. Clinical and pathological pictures of lobular carcinoma are thought to exhibit a large number of random formations and textures. Working with such pictures is a difficult problem in machine learning. Focusing on wet laboratories and following the outcomes, numerous studies have been published with fresh commentaries in the investigation. In this research, we provide a framework that can operate effectively on raw photos of various resolutions while easing the issues caused by the existence of patterns and texturing. The suggested approach produces very good findings that may be used to make decisions in the diagnosis of cancer.

Keywords: lobular carcinoma, convolutional neural networks (CNN), deep learning, histopathological imagery scans

Procedia PDF Downloads 122

Authors: Ashley Hobson, Ashley Efaw

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Professionalism is an essential skill for clinicians, particularly for Occupational Therapy Providers (OTPs). The World Federation of Occupational Therapy (WFOT) Guiding Principles for Ethical Occupational Therapy and American Occupational Therapy Association (AOTA) Code of Ethics establishes expectations for professionalism among OTPs, emphasizing its importance in the field. However, the teaching and assessment of professionalism vary across OTP programs. The flexibility provided by the country standards allows programs to determine their own approaches to meeting these standards, resulting in inconsistency. Educators in both academic and fieldwork settings face challenges in objectively assessing and providing feedback on student professionalism. Although they observe instances of unprofessional behavior, there is no standardized assessment measure to evaluate professionalism in OTP students. While most students are committed to learning and applying professionalism skills, they enter OTP programs with varying levels of proficiency in this area. Consequently, they lack a uniform understanding of professionalism and lack an objective means to self-assess their current skills and identify areas for growth. It is crucial to explicitly teach professionalism, have students to self-assess their professionalism skills, and have OTP educators assess student professionalism. This approach is necessary for fostering students' professionalism journeys. Traditionally, there has been no objective way for students to self-assess their professionalism or for educators to provide objective assessments and feedback. To establish a uniform approach to professionalism, the authors incorporated professionalism content into our curriculum. Utilizing an operational definition of professionalism, the authors integrated professionalism into didactic, fieldwork, and capstone courses. The complexity of the content and the professionalism skills expected of students increase each year to ensure students graduate with the skills to practice in accordance with the WFOT Guiding Principles for Ethical Occupational Therapy Practice and AOTA Code of Ethics. Two professionalism assessments were developed based on the expectations outlined in the both documents. The Professionalism Self-Assessment allows students to evaluate their professionalism, reflect on their performance, and set goals. The Professionalism Assessment for Educators is a modified version of the same tool designed for educators. The purpose of this workshop is to provide educators with a framework and tools for assessing student professionalism. The authors discuss how to integrate professionalism content into OTP curriculum and utilize professionalism assessments to provide constructive feedback and equitable learning opportunities for OTP students in academic, fieldwork, and capstone settings. By adopting these strategies, educators can enhance the development of professionalism among OTP students, ensuring they are well-prepared to meet the demands of the profession.

Keywords: professionalism, assessments, student learning, student preparedness, ethical practice

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Authors: Seyed Esmail Seyedi Bariran, Laysheng Ewe, Amy Ling

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Since supplier selection appears as a vital decision, selecting supplier based on the best and most accurate ways has a lot of importance for enterprises. In this study, a new Artificial Intelligence approach is exerted to remove weaknesses of supplier selection. The paper has three parts. First part is choosing the appropriate criteria for assessing the suppliers’ performance. Next one is collecting the data set based on experts. Afterwards, the data set is divided into two parts, the training data set and the testing data set. By the training data set the best structure of GEP and ANN are selected and to evaluate the power of the mentioned methods the testing data set is used. The result obtained shows that the accuracy of GEP is more than ANN. Moreover, unlike ANN, a mathematical equation is presented by GEP for the supplier selection.

Keywords: supplier selection, automotive supply chains, ANN, GEP

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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

Procedia PDF Downloads 367

Authors: Xiangtuo Chen, Paul-Henry Cournéde

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Crop yield prediction is a paramount issue in agriculture. The main idea of this paper is to find out efficient way to predict the yield of corn based meteorological records. The prediction models used in this paper can be classified into model-driven approaches and data-driven approaches, according to the different modeling methodologies. The model-driven approaches are based on crop mechanistic modeling. They describe crop growth in interaction with their environment as dynamical systems. But the calibration process of the dynamic system comes up with much difficulty, because it turns out to be a multidimensional non-convex optimization problem. An original contribution of this paper is to propose a statistical methodology, Multi-Scenarios Parameters Estimation (MSPE), for the parametrization of potentially complex mechanistic models from a new type of datasets (climatic data, final yield in many situations). It is tested with CORNFLO, a crop model for maize growth. On the other hand, the data-driven approach for yield prediction is free of the complex biophysical process. But it has some strict requirements about the dataset. A second contribution of the paper is the comparison of these model-driven methods with classical data-driven methods. For this purpose, we consider two classes of regression methods, methods derived from linear regression (Ridge and Lasso Regression, Principal Components Regression or Partial Least Squares Regression) and machine learning methods (Random Forest, k-Nearest Neighbor, Artificial Neural Network and SVM regression). The dataset consists of 720 records of corn yield at county scale provided by the United States Department of Agriculture (USDA) and the associated climatic data. A 5-folds cross-validation process and two accuracy metrics: root mean square error of prediction(RMSEP), mean absolute error of prediction(MAEP) were used to evaluate the crop prediction capacity. The results show that among the data-driven approaches, Random Forest is the most robust and generally achieves the best prediction error (MAEP 4.27%). It also outperforms our model-driven approach (MAEP 6.11%). However, the method to calibrate the mechanistic model from dataset easy to access offers several side-perspectives. The mechanistic model can potentially help to underline the stresses suffered by the crop or to identify the biological parameters of interest for breeding purposes. For this reason, an interesting perspective is to combine these two types of approaches.

Keywords: crop yield prediction, crop model, sensitivity analysis, paramater estimation, particle swarm optimization, random forest

Procedia PDF Downloads 219

Authors: Kien Vu, Jien Min Soh, Mohamed Jahangir Abubacker, Piyawut Pattamanon, Soojin Lee, Suvro Banerjee

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Recent advances in Generative Artificial Intelligence (GenAI), in particular Large Language Models (LLMs) have shown promise to disrupt multiple industries at scale. However, LLMs also present unique challenges, notably, these so-called "hallucination" which is the generation of outputs that are not grounded in the input data that hinders its adoption into production. Common practice to mitigate hallucination problem is utilizing Retrieval Agmented Generation (RAG) system to ground LLMs'response to ground truth. RAG converts the grounding documents into embeddings, retrieve the relevant parts with vector similarity between user's query and documents, then generates a response that is not only based on its pre-trained knowledge but also on the specific information from the retrieved documents. However, the RAG system is not suitable for tabular data and subsequent data analysis tasks due to multiple reasons such as information loss, data format, and retrieval mechanism. In this study, we have explored a novel methodology that combines planning-and-execution and code generation agents to enhance LLMs' data analysis capabilities. The approach enables LLMs to autonomously dissect a complex analytical task into simpler sub-tasks and requirements, then convert them into executable segments of code. In the final step, it generates the complete response from output of the executed code. When deployed beta version on DataSense, the property insight tool of PropertyGuru, the approach yielded promising results, as it was able to provide market insights and data visualization needs with high accuracy and extensive coverage by abstracting the complexities for real-estate agents and developers from non-programming background. In essence, the methodology not only refines the analytical process but also serves as a strategic tool for real estate professionals, aiding in market understanding and enhancement without the need for programming skills. The implication extends beyond immediate analytics, paving the way for a new era in the real estate industry characterized by efficiency and advanced data utilization.

Keywords: large language model, reasoning, planning and execution, code generation, natural language processing, prompt engineering, data analysis, real estate, data sense, PropertyGuru

Procedia PDF Downloads 63

Authors: V. I. Chukwuemeka, S. M. Tsadu, R. O. Ojutiku, R. J. Kolo

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The food and feeding habits of Auchenoglanis occidentalis, which is commonly called the “BuBu” cat fish or the giraffe cat fish from Tagwai Lake Minna, was analysed from January to June, 2013. A total of 216 fish specimen were used for the study which were obtained from the local fishermen operating in Tagwai Lake Minna. Fishing gears used include cast nets and gills nets of various sizes. They also use hook and lines. The frequency of occurrence and dominance method were used to analyse the food in the gut. Auchenoglanis occidentalis from Tagwai Lake, Minna had a broad spectrum of food items in the gut, ranging from insects, fish, plant materials to protozoan. The percentage of insects was (31.75%), fish (12.70%), Chyme (20.63%), plant materials (20.63%), protozoa (1.59%) and soil (12.70%). The presence of different food items in the gut of the Auchenoglanis occidentalis which ranged from animal to plant and soil made it to be considered as an omnivore bottom feeder. The food habits of this fish showed no remarkable difference between the dry season months and the rainy season months. The broad food spectrum of the fish makes them a good aquaculture candidate. It also suggests that the specie feed both in surface water and near the substratum (sand).

Keywords: Auchenoglanis occidentalis, ecology, Tagwai Lake, Nigeria

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Authors: Mohamed Ali Alrabib

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This paper introduces a paleoenvironmental and hydrocarbon show in this well was identified in the interval of Dembaba formation to the Hassaona formation was poor to very poor oil show. And from palaeoenvironmental analysis there is neither particularly good reservoir nor source rock have been developed in the area. Recent palaeoenvironment work undertakes that the sedimentary succession in this area comprises the Upper Paleozoic rock of the Carboniferous and Permian and the Mesozoic (Triassic) sedimentary sequences. No early Paleozoic rocks have been found in this area, these rocks were eroding during the Late Carboniferous and Early Permian time. During Latest Permian and earliest Triassic time evidence for major marine transgression has occurred. From depths 5930-5940 feet, to 10800-10810 feet, the TAI of the Al Guidr, the Bir Al Jaja Al Uotia, Hebilia and the top varies between 3+ to 4-(mature-dry gas). This interval corporate the rest part of the Dembaba Formation. From depth 10800- 10810 feet, until total sediment depth (11944 feet Log) which corporate the rest of the Dembaba and underlying equivalents of the Assedjefar and M rar Formations and the underlying Indeterminate unit (Hassouna Formation) the TAI varies between 4 and 5 (dry gas-black& deformed).

Keywords: paleoenveronments, thermail index, carboniferous, Libya

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Authors: I. Badhrees

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This paper is an attempt to describe some of the results that had been found through a journey of study in the field of particle physics. This study consists of two parts, one about the measurement of the cross section of the decay of the Z particle in two electrons, and the other deals with the measurement of the cross section of the multi-photon absorption process using a beam of laser in the Liquid Argon Time Projection Chamber. The first part of the paper concerns the results based on the analysis of a data sample containing 8120 ee candidates to reconstruct the mass of the Z particle for each event where each event has an ee pair with PT(e) > 20GeV, and η(e) < 2.5. Monte Carlo templates of the reconstructed Z particle were produced as a function of the Z mass scale. The distribution of the reconstructed Z mass in the data was compared to the Monte Carlo templates, where the total cross section is calculated to be equal to 1432 pb. The second part concerns the Liquid Argon Time Projection Chamber, LAr TPC, the results of the interaction of the UV Laser, Nd-YAG with λ= 266mm, with LAr and through the study of the multi-photon ionization process as a part of the R&D at Bern University. The main result of this study was the cross section of the process of the multi-photon ionization process of the LAr, σe = 1.24±0.10stat±0.30sys.10 -56cm4.

Keywords: ATLAS, CERN, KACST, LArTPC, particle physics

Procedia PDF Downloads 337

Authors: Prathap S. Raghavendra, Mohamed S. Z. Shamshuddin, Thimmaraju N. Venkatesh

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The transesterification of dimethyl malonate (DMM) with phenol has been studied in vapour phase over cordierite honeycomb coated with solid acid catalysts such as ZrO2,Mo(VI)/ZrO2 and SO42-/ZrO2. The catalytic materials were prepared honeycomb coated and powder forms and characterized for their total surface acidity by NH3-TPD and crystalinity by powder XRD methods. Phenyl methyl malonate (PMM) and diphenyl malonate (DPM) were obtained as the reaction products. A good conversion of DMM (up to 82%) of MPM with 95% selectivity was observed when the reactions were carried out at a catalyst bed temperature of 200 °C and flow-rate of 10 mL/h in presence of Mo(VI)/ZrO2 as catalyst. But over SO42-/ZrO2 catalyst, the yield of DPM was found to be higher. The results have been interpreted based on the variation of acidic properties and powder XRD phases of zirconia on incorporation of Mo(VI) or SO42– ions. Transesterification reactions were also carried out over powder forms of the catalytic materials and the yield of the desired phenyl ester products were compared with that of the HC coated catalytic materials. The solid acids were found to be reusable when used for at least 5 reaction cycles.

Keywords: cordierite honeycomb, methyl phenyl malonate, vapour phase transesterification, zirconia

Procedia PDF Downloads 299

Authors: Hassan Hamidi, Fereshteh Zarei

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In this study, we compared amount of compete motivation between young and adult volleyball players. Compete motivation has three sections: success achieves score, defeat avoiding score and ability score. For measuring motivation, we used sports attitude inventory of Willis and Layne. The statistical population was elite's men volleyball players in range of young and adult and the study subjects were randomly selected from participant teams in volleyball professional league. In total, 65 adult and 75 young were selected. For collecting the required information, the research inventories were distributed in practice's locations and then were collected after being completed by players. For analyzing the data, we used descriptive statistics including mean, standard deviation and frequency tables. We also used conceptual statistics such as independent sample t-student and Pierson correlation. The results showed a significant difference between young and adult volleyball players in success achieve score and ability score. However, there was no significant difference between young and adult volleyball players in defeat avoiding score and compete motivation. In addition, there was not significant relationship between the length of activities and motivations' sections in adult and young volleyball player. The application of this study to other sports will be discussed.

Keywords: compete motivation, volleyball player, statistical analysis, sport psychology

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Authors: Chayonnat Thanamun, Kreangkrai Maneeintr

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For petroleum industry, polymer flooding is the one of the main methods in enhanced oil recovery (EOR) that is used water-soluble polymer such as partially hydrolyzed polyacrylamide (HPAM) to increase oil production. It is added to the flooding water to improve the mobility ratio in the flooding process. During the polymer flooding process, water is produced as a by-product along with oil and gas production. This produced water is a mixture of inorganic and organic compound. Moreover, produced water is more difficult to treat than that from water flooding. In this work, the effect of HPAM residue on the wastewater treatment from polymer flooding is studied. Polyaluminium chloride (PAC) is selected to use as a flocculant. Therefore, the objective of this study is to evaluate the effect of polymer residues in produced water on the wastewater treatment by using PAC. The operating parameters of this study are flocculant dosage ranging from 300,400 and 500 mg/L temperature from 30-50 Celsius degree and HPAM concentrations from 500, 1000 and 2000 mg/L. Furthermore, the turbidity, as well as total suspended solids (TSS), are also studied. The results indicated that with an increase in HPAM concentration, the TSS and turbidity increase gradually with the increasing of coagulant dosage under the same temperature. Also, the coagulation-flocculation performance is improved with the increasing temperature. This can be applied to use in the wastewater treatment from oil production before this water can be injected back to the reservoir.

Keywords: wastewater treatment, petroleum production, polyaluminium chloride, polyacrylamide

Procedia PDF Downloads 135

Authors: Faik Derya Ince, Ugur Topgul, Alp Gunay, Can Bayoglu, Dante J. Dorantes-Gonzalez

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Explosive attacks are arguably the most lethal threat that may occur in terrorist attacks. In order to counteract this issue, explosive ordnance disposal operators put their lives on the line to dispose of a possible improvised explosive device. Robots can make the disposal process more accurately and saving human lives. For this purpose, there is a demand for more accurate and dexterous manipulating robotic hands that can be teleoperated from a distance. The aim of this project is to design a robotic hand that contains two active and two passive DOF for each finger, as well as a minimum set of tools for mechanical cutting and screw driving within the same robotic hand. Both hand and toolset, are teleoperated from a distance from a haptic robotic glove in order to manipulate dangerous objects such as improvised explosive devices. SolidWorks® Computer-Aided Design, computerized dynamic simulation, and MATLAB® kinematic and static analysis were used for the robotic hand and toolset design. Novel, dexterous and robust solutions for the fingers were obtained, and six servo motors are used in total to remotely control the multi-tooled robotic hand. This project is still undergoing and presents currents results. Future research steps are also presented.

Keywords: Explosive Manipulation, Robotic Hand, Tele-Operation, Tool Integration

Procedia PDF Downloads 126

Authors: Ajit Kumar Sah, Rajesh Kumar Jha, Phoolgen Sah, Dev Kumar Shah

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Older individuals often suffer from multiple systemic diseases and are particularly more vulnerable to potentially inappropriate medicine prescribing. Inappropriate medication can cause serious medical problem for the elderly. The purpose of this study was to determine the prevalence of potentially inappropriate medicine (PIM) prescribing in older Nepalese patients in a medicine outpatient department. Beers’ criteria are the most widely used tools to assess PIM to elderly patients. Prospective observational analysis of drugs prescribed in medicine out-patient department (OPD) of a hospital of Bharatpur, Chitwan, Nepal during November 2011 to October 2012 to 869 older adults aged 65 years and above. The use of potentially inappropriate medications (PIM) in elderly patients was analyzed using Beers Criteria updated to 2013. In the 869 patients included the average number of drugs prescribed per prescription was 5.56. The most commonly used drugs were atenolol (24.3%), amlodipine (23.16%), paracetamol (17.6%), salbutamol (15.72%) and vitamin B complex (13.26%). The total number of medications prescribed was 4833. At least one instance of PIM was experienced by approximately 26.3% of patients when evaluated using the Beers criteria. Potentially inappropriate medications are highly prevalent among older patients attending medical OPD and are associated with a number of medications prescribed. Further research is warranted to study the impact of PIMs towards health-related outcomes in these elderly.

Keywords: Beers criteria, elderly, polypharmacy, potentially inappropriate medicines

Procedia PDF Downloads 551

Authors: Till Gramberg

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In the dynamic world of machine and plant engineering, stagnation in the growth of new product sales compels companies to reconsider their business models. The increasing shift toward service orientation, known as "servitization," along with challenges posed by digitalization and sustainability, necessitates an adaptation of product portfolio management (PPM). Against this backdrop, this study investigates the current challenges and requirements of PPM in this industrial context and develops a framework for the application of generative artificial intelligence (AI) to enhance agility and efficiency in PPM processes. The research approach of this study is based on a mixed-method design. Initially, qualitative interviews with industry experts were conducted to gain a deep understanding of the specific challenges and requirements in PPM. These interviews were analyzed using the Gioia method, painting a detailed picture of the existing issues and needs within the sector. This was complemented by a quantitative online survey. The combination of qualitative and quantitative research enabled a comprehensive understanding of the current challenges in the practical application of machine and plant engineering PPM. Based on these insights, a specific framework for the application of generative AI in PPM was developed. This framework aims to assist companies in implementing faster and more agile processes, systematically integrating dynamic requirements from trends such as digitalization and sustainability into their PPM process. Utilizing generative AI technologies, companies can more quickly identify and respond to trends and market changes, allowing for a more efficient and targeted adaptation of the product portfolio. The study emphasizes the importance of an agile and reactive approach to PPM in a rapidly changing environment. It demonstrates how generative AI can serve as a powerful tool to manage the complexity of a diversified and continually evolving product portfolio. The developed framework offers practical guidelines and strategies for companies to improve their PPM processes by leveraging the latest technological advancements while maintaining ecological and social responsibility. This paper significantly contributes to deepening the understanding of the application of generative AI in PPM and provides a framework for companies to manage their product portfolios more effectively and adapt to changing market conditions. The findings underscore the relevance of continuous adaptation and innovation in PPM strategies and demonstrate the potential of generative AI for proactive and future-oriented business management.

Keywords: servitization, product portfolio management, generative AI, disruptive innovation, machine and plant engineering

Procedia PDF Downloads 59

Authors: Armansyah, I. P. Almanar, M. Saiful Bahari Shaari, M. Shamil Jaffarullah, Nur’amirah Busu, M. Arif Fadzleen Zainal Abidin, M. Amlie A. Kasim

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Temperature distribution in Friction Stir Welding (FSW) of 6061-T6 Aluminum Alloy is modeled using the Finite Element Method (FEM). In order to obtain temperature distribution in the welded aluminum plates during welding operation, transient thermal finite element analyses are performed. Heat input from tool shoulder and tool pin are considered in the model. A moving heat source with a heat distribution simulating the heat generated by frictions between tool shoulder and workpiece is used in the analysis. Three-dimensional model for simulated process is carried out by using Altair HyperWork, a commercially available software. Transient thermal finite element analyses are performed in order to obtain the temperature distribution in the welded Aluminum plates during welding operation. The developed model was then used to show the effect of various input parameters such as total rate of welding speed and rotational speed on temperature distribution in the workpiece.

Keywords: frictions stir welding, temperature distribution, finite element method, altair hyperwork

Procedia PDF Downloads 526

Authors: Yuzhi Cai

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In this paper, we discuss a Bayesian approach to quantile autoregressive (QAR) time series model estimation and forecasting. Together with a combining forecasts technique, we then predict USD to GBP currency exchange rates. Combined forecasts contain all the information captured by the fitted QAR models at different quantile levels and are therefore better than those obtained from individual models. Our results show that an unequally weighted combining method performs better than other forecasting methodology. We found that a median AR model can perform well in point forecasting when the predictive density functions are symmetric. However, in practice, using the median AR model alone may involve the loss of information about the data captured by other QAR models. We recommend that combined forecasts should be used whenever possible.

Keywords: combining forecasts, MCMC, predictive density functions, quantile forecasting, quantile modelling

Procedia PDF Downloads 246

Authors: M. Tiachachat, M. Mihoubi

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The Bell polynomials are special polynomials in combinatorial analysis that have a wide range of applications in mathematics. They have interested many authors. The exponential partial Bell polynomials have been well reduced to some special combinatorial sequences. Numerous researchers had already been interested in the above polynomials, as evidenced by many articles in the literature. Inspired by this work, in this work, we propose a family of special polynomials named after the 2-successive partial Bell polynomials. Using the combinatorial approach, we prove the properties of these numbers, derive several identities, and discuss some special cases. This family includes well-known numbers and polynomials such as Stirling numbers, Bell numbers and polynomials, and so on. We investigate their properties by employing generating functions

Keywords: 2-associated r-Stirling numbers, the exponential partial Bell polynomials, generating function, combinatorial interpretation

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Authors: Wisitiporn Suksombat, Tanawat Phonkert, Chayapol Meeprom

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The aim of this experiment was to investigate the effect of calcium salt of palm oil fatty acids (Ca-POFA) supplementation on milk production and milk composition of dairy cows. Twenty-four early lactating crossbred Holstein Friesian 87.5% cows (15.4 ± 3.75 kg of milk/d; 93 ± 27 DIM; 369 ± 6 kg of BW), were assigned into 3 treatments in an RCBD. All dairy cows were fed 15.4% CP total mixed ration (TMR). The first group (control) received a basal diet and no supplement. The second group was fed the basal diet supplemented with 150 g/d calcium salt of palm oil fatty acids (Ca-POFA), and the last group was fed the basal diet supplemented with 300 g/d Ca-POFA. The experiment lasted 40 days with the first 10 days is an adaptation period, and measurements were made during the last 30 days in 6 periods with 5-days in each period for milk sample collection. The results found that supplemented calcium salt of palm oil fatty acid had no effect on milk yield, milk composition, milk composition yield, live weight and live weight change. However, Ca-POFA decreased milk protein percentage (P < 0.05).

Keywords: calcium salt of palm oil fatty acid, dairy cow, milk composition, milk production

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Authors: Jayron Sanchez, Analyn Yumang, Felicito Caluyo

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The visually impaired individual may use a cane, guide dog or ask for assistance from a person. This study implemented the RFID technology which consists of a low-cost RFID reader and passive RFID tag cards. The passive RFID tag cards served as checkpoints for the visually impaired. The visually impaired was guided through audio output from the system while traversing the path. The study implemented an ultrasonic sensor in detecting static obstacles. The system generated an alternate path based on A* algorithm to avoid the obstacles. Alternate paths were also generated in case the visually impaired traversed outside the intended path to the destination. A* algorithm generated the shortest path to the destination by calculating the total cost of movement. The algorithm then selected the smallest movement cost as a successor to the current tag card. Several trials were conducted to determine the effect of obstacles in the time traversal of the visually impaired. A dependent sample t-test was applied for the statistical analysis of the study. Based on the analysis, the obstacles along the path generated delays while requesting for the alternate path because of the delay in transmission from the laptop to the device via ZigBee modules.

Keywords: A* algorithm, RFID technology, ultrasonic sensor, ZigBee module

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Authors: Clara Theresia, Hardianto Iridiastadi

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Drowsiness is one of the main factors that contribute to the occurrence of accidents, particularly in the transportation sector. While the effects of sleep deprivation on cognitive functions have been reported, the exact relationships remain a critical issue. This study aimed at quantifying the effects of extreme sleep deprivation on vigilance, fatigue, and performance during simulated train driving. A total of 12 participants were asked to drive a train simulator continuously for 4 hours, either in a sleep deprived condition (2-hr of sleep) or normal (8-hr of sleep) condition. Dependent variables obtained during the task included Psychomotor Vigilance Task (PVT) parameters, degree of fatigue (assessed via Visual Analogue Scale/VAS) and sleepiness (reported using Karolinska Sleepiness Scale/KSS), and driving performance (the number of speed limit violations). Findings from this study demonstrated substantial decrements in vigilance in the sleep-deprived condition. This condition also resulted in 75% increase in speed violation and a two-fold increase in the degree of fatigue and sleepiness. Extreme sleep deprivation was clearly associated with substantially poorer response. The exact effects, however, were dependent upon the types of responses.

Keywords: cognitive function, psychomotor vigilance task, sleep deprivation, train simulator

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Authors: Amani Tahat, Serdal Kirmizialtin

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Trajectory fragment methods such as Markov State Models (MSM), Milestoning (MS) and Transition Path sampling are the prime choice of extending the timescale of all atom Molecular Dynamics simulations. In these approaches, a set of structures that covers the accessible phase space has to be chosen a priori using cluster analysis. Structural clustering serves to partition the conformational state into natural subgroups based on their similarity, an essential statistical methodology that is used for analyzing numerous sets of empirical data produced by Molecular Dynamics (MD) simulations. Local transition kernel among these clusters later used to connect the metastable states using a Markovian kinetic model in MSM and a non-Markovian model in MS. The choice of clustering approach in constructing such kernel is crucial since the high dimensionality of the biomolecular structures might easily confuse the identification of clusters when using the traditional hierarchical clustering methodology. Of particular interest, in the case of MS where the milestones are very close to each other, accurate determination of the milestone identity of the trajectory becomes a challenging issue. Throughout this work we present two cluster analysis methods applied to the cis–trans isomerism of dinucleotide AA. The choice of nucleic acids to commonly used proteins to study the cluster analysis is two fold: i) the energy landscape is rugged; hence transitions are more complex, enabling a more realistic model to study conformational transitions, ii) Nucleic acids conformational space is high dimensional. A diverse set of internal coordinates is necessary to describe the metastable states in nucleic acids, posing a challenge in studying the conformational transitions. Herein, we need improved clustering methods that accurately identify the AA structure in its metastable states in a robust way for a wide range of confused data conditions. The single linkage approach of the hierarchical clustering available in GROMACS MD-package is the first clustering methodology applied to our data. Self Organizing Map (SOM) neural network, that also known as a Kohonen network, is the second data clustering methodology. The performance comparison of the neural network as well as hierarchical clustering method is studied by means of computing the mean first passage times for the cis-trans conformational rates. Our hope is that this study provides insight into the complexities and need in determining the appropriate clustering algorithm for kinetic analysis. Our results can improve the effectiveness of decisions based on clustering confused empirical data in studying conformational transitions in biomolecules.

Keywords: milestoning, self organizing map, single linkage, structure clustering

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Authors: Terence Maisah Seka

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This paper examines democratic governance within the private and public sectors in economies in transition (Cameroon) by exploring how they influence development in terms of resource allocation to priorities that are locally conceptualized. The benefit of this is an improvement in indigenous and the quality of life for the local population. Using an ethnographic approach, this paper suggests that institutional corruption and state bureaucracy has limited the impact of democratic governance in influencing development. This has seen funds for developments being embezzled; local projects are not being done to satisfaction among others. The paper contributes by proposing measures to eliminate corruption to improve democratic governance, which will improve resource allocation and utilization.

Keywords: democratic governance, resource allocation, utilisation, Cameroon

Procedia PDF Downloads 174

Authors: Ozioma Beauty Nwaodu, Adebowale E Salako, Omolara Mabel Akinyemi, Nkechi Uche, Isuama Isu, Uchechi Jane Elechi

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Goats form an integral part of livestock production in the tropics. Meat potential is determined subjectively by resource poor livestock keepers, using hand to measure the rump width (RW). Objective evaluation of meat potential in different breads of goats can overcome problems associated with subjective evaluation. Hence, the objectives were to predict meatiness in Red Sokoto (RS), Sahel and the West African Dwarf (WAD) goats, using product of the body length (BL), wither height (WH) and (RW) and to indicate the inherent size of each breed, using WH: BL ratio. These three parameters were used because they are less environmentally sensitive. A total of 2849 goats were sampled purposefully from the Akinyele and Oranyan markets in Ibadan, Oyo State Nigeria. RS showed no significant difference for BL and WH but different from the RW of both sexes (p < 0.01). Similarly WAD showed no significant difference for the BL and WH, but differed (p < 0.01) between sexes for RW. Using the ANOVA, BL:WH ratio showed no significant difference between the breeds. WAD goats have the highest mean for BL:WH ratio. Western meat livestock is primarily identified using BL:WH. The combinations of these body parameters as indicator for meat type in meat animals showed that WAD goat has more potential to lay down meat, than RS and Sahel.

Keywords: quantitative, morphologial traits, descriptive analysis, goats

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Authors: Moses Oghnennyoreme Eyankware, Christian Ogubuchi Ede

Abstract:

Groundwater is the principal source for various uses in this study area. The quality and availability of groundwater depend on rock formation within the study area. To effectively study the quality of groundwater, 24 groundwater samples were collected. The study was aimed at investigating the hydrogeochemistry of groundwater, and additionally its suitability for drinking and irrigation purposes. The following parameters were analyzed using the American Public Health Association standard method: pH, turbidity, Ec, TDS, Mg2+, SO42-, NO3¯, Cl-, HCO3¯, K+, Na2+ and Ca2+. Results obtained from Water Quality Index revealed that the groundwater sample fell within good water quality that implies that groundwater is considered fit for drinking purposes. Deduced results obtained from irrigation indices revealed that Permeability Index (PI), Soluble Sodium Percentage (SSP), Sodium Percentage (Na %), Sodium Absorption Ratio (SAR), Kelly Ratio (KR), Magnesium Hazard (MH) ranges from 0.00 to 0.01, 4.04 to 412.9, 0.63 to 257.7, 0.15 to 2.34, 0.09 to 2.57 and 6.84 to 84.55 respectively. Findings from Total hardness revealed that groundwater fell within soft, moderately hard and hard categories. Estimated results obtained from CSMR, RI and LSI showed that groundwater showed corrosion tendency, salinization influenced groundwater at certain sampling points and chloride and sulfate unlikely to interfere with natural formation film.

Keywords: water, quality, suitability, anthropogenic, Nigeria

Procedia PDF Downloads 151

Authors: Yu Wang

Abstract:

Nowadays, Internet enables its users to share the information online and to interact with others. Facing with numerous information, these Internet users are confused and begin to rely on the opinion leaders’ recommendations. The online opinion leaders are the individuals who have professional knowledge, who utilize the online channels to spread word-of-mouth information and who can affect the attitudes or even the behavior of their followers to some degree. Because utilizing the online opinion leaders is seen as an important approach to affect the potential consumers, how to identify them has become one of the hottest topics in the related field. Hence, in this article, the concepts and characteristics are introduced, and the researches related to identifying opinion leaders are collected and divided into three categories. Finally, the implications for future studies are provided.

Keywords: online opinion leaders, user attributes analysis, text mining analysis, network structure analysis

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Authors: Nicholas Jobe

Abstract:

English Language Learners (ELLs) often struggle in a classroom setting, too embarrassed at their skill level to write or speak in front of peers and too lacking in confidence to practice. Storytelling is an age-old method of teaching that allows learners to remember important details while listening or sharing a narrative. In the modern world, digital storytelling through the use of technological tools such as podcasts and videos allow students to safely interact with each other to build skills in a fun and engaging way that also works as a confidence booster. Specifically using a constructionist approach to learning, digital storytelling allows ELL students to grow and build new and prior knowledge by creating stories via these technological means. Research herein suggests, through the use of case studies and mixed methodologies, that digital storytelling mainly yields positive results for effective learning in an ELL classroom setting.

Keywords: digital storytelling, ELL, narrative, podcast

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Authors: Hoda Ghavamipoor, S. Alireza Hashemi Golpayegani

Abstract:

An approach to model the customer interaction with e-commerce websites is presented. Considering the service quality level as a predictive feature, we offer an improved method based on the Customer Behavior Model Graph (CBMG), a state-transition graph model. To derive the Quality of Service sensitive-CBMG (QoS-CBMG) model, process-mining techniques is applied to pre-processed website server logs which are categorized as ‘buy’ or ‘visit’. Experimental results on an e-commerce website data confirmed that the proposed method outperforms CBMG based method.

Keywords: customer behavior model, electronic commerce, quality of service, customer behavior model graph, process mining

Procedia PDF Downloads 398

Authors: M. Lizzy Madiwani, Ignatious Ncube, Evelyn Madoroba

Abstract:

This study was designed to determine the distribution of pathogenic bacteria in household raised chickens and study their virulence and antibiotic profiles. For this purpose, 40 chickens were purchased from families in the Capricorn district and sacrificed for sampling. Tissues were cultured on different bacteriological media followed by biotyping using Matrix-assisted Laser Desorption Ionization-time of Flight (MALDI-TOF). Disk diffusion test was performed to determine the antibiotic susceptibility profiles of these bacteria. Out of a total of 160 tissue samples evaluated, E. coli and Salmonella were detected in these tissues. Furthermore, determination of the pathogenic E. coli and Salmonella strains at species level using primer sets that target selected genes of interest in the polymerase chain reaction (PCR) assay was employed. The invA gene, a confirmatory gene of Salmonella was detected in all the Salmonella isolates. The study revealed that there is a high distribution of Salmonella and pathogenic E. coli in these chickens. Therefore, further studies on identification at the species level are highly recommended to provide management and sanitation practices to lower this prevalence. The antimicrobial susceptibly data generated from this study can be a valuable reference to veterinarians for treating bacterial diseases in poultry.

Keywords: antimicrobial, Escherichia coli, pathogens, Salmonella

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Authors: Sharjeel Aslam, Vassil Vassilev, Karim Ouazzane

Abstract:

Ontologies and various semantic repositories became a convenient approach for implementing model-driven architectures of distributed systems on the Web. SPARQL is the standard query language for querying such. However, although SPARQL is well-established standard for querying semantic repositories in RDF and OWL format and there are commonly used APIs which supports it, like Jena for Java, its parallel option is not incorporated in them. This article presents a complete framework consisting of an object algebra for parallel RDF and an index-based implementation of the parallel query engine capable of dealing with the distributed RDF ontologies which share common vocabulary. It has been implemented in Java, and for validation of the algorithms has been applied to the problem of organizing virtual exhibitions on the Web.

Keywords: distributed ontologies, parallel querying, semantic indexing, shared vocabulary, SPARQL

Procedia PDF Downloads 188