Search results for: hybrid inventory

Authors: Usman Qamar, Younus Javed

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Frequent pattern mining is the process of finding a pattern (a set of items, subsequences, substructures, etc.) that occurs frequently in a data set. It was proposed in the context of frequent itemsets and association rule mining. Frequent pattern mining is used to find inherent regularities in data. What products were often purchased together? Its applications include basket data analysis, cross-marketing, catalog design, sale campaign analysis, Web log (click stream) analysis, and DNA sequence analysis. However, one of the bottlenecks of frequent itemset mining is that as the data increase the amount of time and resources required to mining the data increases at an exponential rate. In this investigation a new algorithm is proposed which can be uses as a pre-processor for frequent itemset mining. FASTER (FeAture SelecTion using Entropy and Rough sets) is a hybrid pre-processor algorithm which utilizes entropy and rough-sets to carry out record reduction and feature (attribute) selection respectively. FASTER for frequent itemset mining can produce a speed up of 3.1 times when compared to original algorithm while maintaining an accuracy of 71%.

Keywords: rough-sets, classification, feature selection, entropy, outliers, frequent itemset mining

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Authors: Dimitra Sygkridou, Dimitrios Karageorgopoulos, Elias Stathatos, Evangelos Vitoratos

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Transparent nickel doped cobalt sulfide was fabricated on a SnO2:F electrode and tested as an efficient electrocatalyst and as an alternative to the expensive platinum counter electrode. In order to investigate how this electrode could affect the electrical characteristics of a dye-sensitized solar cell, we manufactured cells with the same TiO2 photoanode sensitized with dye (N719) and employing the same quasi-solid electrolyte, altering only the counter electrode used. The cells were electrically and electrochemically characterized and it was observed that the ones with the Ni doped CoS2 outperformed the efficiency of the cells with the Pt counter electrode (3.76% and 3.44% respectively). Particularly, the higher efficiency of the cells with the Ni doped CoS2 counter electrode (CE) is mainly because of the enhanced photocurrent density which is attributed to the enhanced electrocatalytic ability of the CE and the low charge transfer resistance at the CE/electrolyte interface.

Keywords: nickel doped cobalt sulfide, counter electrodes, dye-sensitized solar cells, quasi-solid state electrolyte, hybrid organic-inorganic materials

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Authors: Saima Shafiq, Najma Iqbal Malik

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This study was aimed to explore the relationship of perceived stigma, perception of burden and psychological distress among parents of intellectually disabled children. The study also aimed to explore the moderating role of perceived social support on all the variables of the study. The sample of the study comprised of (N = 250) parents of intellectually disabled children. The present study utilized the co-relational research design. It consists of two phases. Phase-I consisted of two steps which contained the translation of two scales that were used in the present study and tried out on the sample of parents (N = 70). The Affiliated Stigma Scale and Care Giver Burden Inventory were translated into Urdu for the present study. Phase-1 revealed that translated scaled entailed satisfactory psychometric properties. Phase -II of the study was carried out in order to test the hypothesis. Correlation, linear regression analysis, and t-test were computed for hypothesis testing. Hierarchical regression analysis was applied to study the moderating effect of perceived social support. Findings revealed that there was a positive relationship between perceived stigma and psychological distress, perception of burden and psychological distress. Linear regression analysis showed that perceived stigma and perception of burden were positive predictors of psychological distress. The study did not show the moderating role of perceived social support among variables of the present study. The major limitation of the study is the sample size and the major implication is awareness regarding problems of parents of intellectually disabled children.

Keywords: perceived stigma, perception of burden, psychological distress, perceived social support

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Authors: Namita Mittal, Himakshi Shekhawat, Ankit Vidyarthi

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In medical research study, doctors and radiologists face lot of complexities in analysing the brain tumors in Magnetic Resonance (MR) images. Brain tumor detection is difficult due to amorphous tumor shape and overlapping of similar tissues in nearby region. So, radiologists require one such clinically viable solution which helps in automatic segmentation of tumor inside brain MR image. Initially, segmentation methods were used to detect tumor, by dividing the image into segments but causes loss of information. In this paper, a hybrid method is proposed which detect Region of Interest (ROI) on the basis of difference in intensity values and texture values of tumor region using nearby tissues with Gradient Vector Flow (GVF) technique in the identification of ROI. Proposed approach uses both intensity and texture values for identification of abnormal section of the brain MR images. Experimental results show that proposed method outperforms GVF method without any loss of information.

Keywords: brain tumor, GVF, intensity, MR images, segmentation, texture

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Authors: Erietta-Christina Arnaoutaki, Stelios-Elion Bousi, Marinos Zachiotis, Simoni Zarkada, Alexandra Chrysagi, Mamdouh Fahad Alenazi, Dimitri Aristotle Raptis

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Objective: This review aimed to evaluate the mental health status of patients with esophageal cancer following surgical treatment, as well as the role of psychological distress screening tests in this patient population. Methods: Studies reporting psychometric screening tools used in esophageal cancer patients after esophagectomy, published before January 2024 on PubMed, Scopus, and CENTRAL databases, were searched and analyzed. Results: Six non-randomized control trials were selected for inclusion in this scoping review, which involved 1059 patients undergoing esophagectomy for esophageal cancer. Among the included studies, five employed the Hospital Anxiety and Depression Scale (HADS) for anxiety and/or depression screening, while one used the MD Anderson Symptom Inventory for gastrointestinal cancer (MDASI-GI) for sadness screening. A range of time points was used to evaluate these patients: 102 patients were evaluated at 1 month, 230 patients at 3 months, 218 patients at 6 months, 653 patients at 12 months, and 154 patients at 24 months postoperatively. Analysis of data pooled from three studies employing the HADS revealed a prevalence of 19.45% for anxiety and 17.92% for depression at the 12-month follow-up and mean scores of 3.91 (3.12) and 3.56 (3.12) for the HADS anxiety (HADS-A) and depression (HADS-D) subscales respectively, at any time postoperatively. Conclusion: The findings show a neglected concern regarding the mental health of esophageal cancer survivors following surgical treatment. The use of psychometric screening tools is essential to address psychological distress and improve the quality of life of these patients.

Keywords: esophageal cancer, esophagectomy, psychological distress, anxiety, depression, psychometric tests, HADS, MDASI-GI

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Authors: Mousa Meratizaman, Sina Monadizadeh, Majid Amidpour

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One of the most favorable thermal desalination methods used widely today is Multi Effect Desalination. High energy consumption in this method causes coupling it with high temperature power cycle like gas turbine. This combination leads to higher energy efficiency. One of the high temperature power systems which have cogeneration opportunities is Solid Oxide Fuel Cell / Gas Turbine. Integration of Multi Effect Desalination with Solid Oxide Fuel Cell /Gas Turbine power cycle in a range of 300-1000 kW is considered in this article. The exhausted heat of Solid Oxide Fuel Cell /Gas Turbine power cycle is used in Heat Recovery Steam Generator to produce needed motive steam for Desalination unit. Thermodynamic simulation and parametric studies of proposed system are carried out to investigate the system performance.

Keywords: solid oxide fuel cell, thermodynamic simulation, multi effect desalination, gas turbine hybrid cycle

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Authors: Masao Nakagawa, Toshiki Hirogaki, Eiichi Aoyama, Mohamed Ali Ben Abbes

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A planetary gear set is widely used in hybrid vehicles as the power distribution system or in electric vehicles as the high reduction system, but due to its complexity with planet gears, its dynamic characteristic is not fully understood. There are many reports on two-axes driving or displacement of the planet gears under these conditions, but only few reports deal with three-axes driving. A three-axes driving condition is tested using three-axes torque measurement and focuses on the dynamic characteristic around the planet gears in this report. From experimental result, it was confirmed that the transition forces around the planet gears were balanced and the torques were also balanced around the instantaneous rotation center. The meshing frequency under these conditions was revealed to be the harmonics of two meshing frequencies; meshing frequency of the ring gear and that of the planet gears. The input power of the ring gear is distributed to the carrier and the sun gear in the dynamic sequential change of three fixed conditions; planet, star and solar modes.

Keywords: dynamic characteristic, gear, planetary gear set, torque measuring

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Authors: Rahul Paul, Kedar Nath Das

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The paradigm of Reinforcement Learning (RL) has become prominent in training intelligent agents to make decisions in environments that are both dynamic and uncertain. The primary objective of RL is to optimize the policy of an agent in order to maximize the cumulative reward it receives throughout a given period. Nevertheless, the process of optimization presents notable difficulties as a result of the inherent trade-off between exploration and exploitation, the presence of extensive state-action spaces, and the intricate nature of the dynamics involved. Evolutionary Optimization Methods (EOMs) have garnered considerable attention as a supplementary approach to tackle these challenges, providing distinct capabilities for optimizing RL policies and value functions. The ongoing advancement of research in both RL and EOMs presents an opportunity for significant advancements in autonomous decision-making systems. The convergence of these two fields has the potential to have a transformative impact on various domains of artificial intelligence (AI) applications. This article highlights the considerable influence of EOMs in enhancing the capabilities of RL. Taking advantage of evolutionary principles enables RL algorithms to effectively traverse extensive action spaces and discover optimal solutions within intricate environments. Moreover, this paper emphasizes the practical implementations of EOMs in the field of RL, specifically in areas such as robotic control, autonomous systems, inventory problems, and multi-agent scenarios. The article highlights the utilization of EOMs in facilitating RL agents to effectively adapt, evolve, and uncover proficient strategies for complex tasks that may pose challenges for conventional RL approaches.

Keywords: machine learning, reinforcement learning, loss function, optimization techniques, evolutionary optimization methods

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Authors: Miral Selim, May Haggag, Ibrahim Abotaleb

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The aging of transportation infrastructure presents significant challenges, particularly concerning the monitoring and maintenance of bridges. This study investigates the application of Random Forest algorithms for predictive modeling of bridge conditions, utilizing data from the US National Bridge Inventory (NBI). The research is significant as it aims to improve bridge management through data-driven insights that can enhance maintenance strategies and contribute to overall safety. Random Forest is chosen for its robustness, ability to handle complex, non-linear relationships among variables, and its effectiveness in feature importance evaluation. The study begins with comprehensive data collection and cleaning, followed by the identification of key variables influencing bridge condition ratings, including age, construction materials, environmental factors, and maintenance history. Random Forest is utilized to examine the relationships between these variables and the predicted bridge conditions. The dataset is divided into training and testing subsets to evaluate the model's performance. The findings demonstrate that the Random Forest model effectively enhances the understanding of factors affecting bridge conditions. By identifying bridges at greater risk of deterioration, the model facilitates proactive maintenance strategies, which can help avoid costly repairs and minimize service disruptions. Additionally, this research underscores the value of data-driven decision-making, enabling better resource allocation to prioritize maintenance efforts where they are most necessary. In summary, this study highlights the efficiency and applicability of Random Forest in predictive modeling for bridge management. Ultimately, these findings pave the way for more resilient and proactive management of bridge systems, ensuring their longevity and reliability for future use.

Keywords: data analysis, random forest, predictive modeling, bridge management

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Authors: Shabnam Etemadi

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Background: Infertility is one of the most important issues in any society due to its psychological, medical and economic consequences that can greatly influence overall health and life. This study aims to assess the relationship between inhalation or exposing workplace pollution and dysfunction of the male reproductive system. Semen samples are male employees in south of Iran who exposed to work environmental pollutants for long hours. Method: Due to descriptive-analytical, the analysis of all interviews of all male patients of Bu Ali Medical Center and Pasteur Laboratory are conducted within 6 months. Random sampling numbered and patients signed informed consent. To analyze the data, Miller's fertility motivation questionnaires and the Miller-Smith lifestyle assessment inventory are used and Working Conditions Survey is developed. For analyzing the collecting data SPSS is used. Findings: Although sperm motility and volume had no statistically significant relationship with any of the lifestyle components, the weak relationship between sperm movement and work environment conditions (P = 0.07) lead to other factors to be investigated. * Among the factors of Working Environment Condition, smoking, work in the open environment and presence of more than 6 hours in the work environment with sperm mobility, smoking, contact with chemicals and radioactive with sperm volume at a level less than 0.05 had a statistically significant relationship. Conclusion: Finding revealed the environment pollution is one of the important factors in male infertility and strengthens this hypothesis. Working Environmental pollutants in the field of metropolitan pollution should be considered as a unifying hypothesis, possibly could interfere with male reproductive function.

Keywords: infertility, lifestyle, workplace pollution, male infertility

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Authors: Syed Tahir Shah, Fazal Muhammad, Syed Kashif Shah, Maleeha Gul

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In recent days, natural gas has become a relatively clean and quality source of energy, which is recovered from deep wells by expensive drilling activities. The recovered substance is purified by processing in multiple stages to remove the unwanted/containments like dust, dirt, crude oil and other particles. Mostly, gas utilities are concerned with essential objectives of quantity/quality of natural gas delivery, financial outcome and safe natural gas volumetric inventory in the transmission gas pipeline. Gas quantity and quality are primarily related to standards / advanced metering procedures in processing units/transmission systems, and the financial outcome is defined by purchasing and selling gas also the operational cost of the transmission pipeline. SNGPL (Sui Northern Gas Pipelines Limited) Pakistan has a wide range of diameters of natural gas transmission pipelines network of over 9125 km. This research results in answer a few of the issues in accuracy/metering procedures via multiple advanced gadgets for gas flow attributes after being utilized in the transmission system and research. The effects of good pressure management in transmission gas pipeline network in contemplation to boost the gas volume deposited in the existing network and finally curbing gas losses UFG (Unaccounted for gas) for financial benefits. Furthermore, depending on the results and their observation, it is directed to enhance the maximum allowable working/operating pressure (MAOP) of the system to 1235 PSIG from the current round about 900 PSIG, such that the capacity of the network could be entirely utilized. In gross, the results depict that the current model is very efficient and provides excellent results in the minimum possible time.

Keywords: natural gas, pipeline network, UFG, transmission pack, AGA

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Authors: Yue He, Youn Young Shim, Ji Hye Kim, Jae Youl Cho, Martin J. T. Reaney

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Recently, pulse cooking water (a.k.a. Aquafaba) has been used as an important and cost-effective alternative to eggs in gluten-free, vegan cooking and baking applications. The aquafaba (AQ) is primarily due to its excellent ability to stabilize foams and emulsions in foods. However, the functional ingredients of this excellent AQ are usually discarded with the compound release. This study developed a high-functional food material, AQ, using functional soybean AQ that has not been studied in Korea. A zero-waste and cost-effective hybrid process were used to produce oil emulsifiers from Korean soybeans. The treatment technique was implemented using a small number of efficient steps. Aquafaba from Backtae had the best emulsion properties (92%) and has the potential to produce more stable food oil emulsions. Therefore, this study is expected to be utilized in the development of the first gluten-free, vegan product for vegetarians and consumers with animal protein allergies, utilizing wastewater from cooked soybeans as a source of plant protein that can replace animal protein.

Keywords: aquafaba, soybean, chickpea, emulsifiers, egg replacer, egg-free products

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Authors: Galina Mihaleva, C. Koh

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Fashion, like many other design fields, undergoes numerous evolutions throughout the ages. This paper aims to recognize and evaluate the significance of advance technology in fashion design and examine how it changes the role of modern fashion designers by modifying the creation process. It also touches on how modern culture is involved in such developments and how it affects fashion design in terms of conceptualizing and fabrication. The methodology used is through surveying the various examples of technological applications to fashion design and drawing parallels between what was achievable then and what is achievable now. By comparing case studies, existing fashion design examples and crafting method experimentations; we then spot patterns in which to predict the direction of future developments in the field. A breakdown on the elements of technology in fashion design helps us understand the driving force behind such a trend. The results from explorations in the paper have shown that there is an observed pattern of a distinct increase in interest and progress in the field of fashion technology, which leads to the birth of hybrid crafting methods. In conclusion, it is shown that as fashion technology continues to evolve, their role in clothing crafting becomes more prominent and grows far beyond the humble sewing machine.

Keywords: fashion design, functional aesthetics, smart textiles, 3D printing

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Authors: Mbadiwe S. Benyeogor, Oladayo O. Olakanmi, Kosisochukwu P. Nnoli, Olusegun I. Lawal, Eric JJ. Gratton

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For a robot or any vehicular system to navigate in off-road terrain, its driving mechanisms and the electro-software system must be capable of generating, controlling, and moderating sufficient mechanical power with precision. This paper proposes an autonomous robot with a gyro-stabilized active suspension system in form of a hybrid quadrupedal wheel drive mechanism. This system is to serve as a miniature model for demonstrating how off-road vehicles can be robotized into efficient terramechanical mobile platforms that are capable of self-balanced autonomous navigation and maneuvering on rough and uneven topographies. Results from tests and analysis show that the developed system performs as expected. Therefore, our model and control devices can be adapted to computerizing, automating, and upgrading the operation of unmanned ground vehicles for off-road navigation.

Keywords: active suspension, autonomous robots, edge computing, navigational sensors, terramechanics

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Authors: Maurice Bilioniere, Katie Lanneau

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Suddenly appeared in 2011, invasions of sargasso seaweeds Fluitans and Natans are a climatic hazard which causes many problems in the Caribbean. Faced with the growth and frequency of the phenomenon of massive sargasso stranding on their coasts, the French West Indies are moving towards the path of industrial recovery. In this context of innovative projects, we will analyze the necessary requirements for the management and performance of the supply chain, taking into account the observed volatility of the sargasso input. Our prospective approach will consist in studying the theoretical framework of modeling a hybrid supply chain by coupling the discreet event simulation (DES) with a valuation of the process costs according to the "activity-based costing" method (ABC). The PREVA approach (PRocess EVAluation) chosen for our modeling has the advantage of evaluating the financial flows of the logistic process using an analytical model chained with an action model for the evaluation or optimization of physical flows.

Keywords: sargasso, PREVA modeling, supply chain, ABC method, discreet event simulation (DES)

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Authors: Marimuthu Gurusamy

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In vibration analysis (with accelerometers) of rotating machines with rolling element bearing, the customers are interested to know the failure of the machine well in advance to plan the spare inventory and maintenance. But in real world most of the machines fails before the prediction of vibration analyst or Expert analysis software. Presently the prediction of failure is based on ISO 10816 vibration limits only. But this is not enough to monitor the failure of machines well in advance. Because more than 50% of the machines will fail even the vibration readings are within acceptable zone as per ISO 10816.Hence it requires further detail analysis and different techniques to predict the failure well in advance. In vibration Analysis, the velocity spectrum is used to analyse the root cause of the mechanical problems like unbalance, misalignment and looseness etc. The envelope spectrum are used to analyse the bearing frequency components, hence the failure in inner race, outer race and rolling elements are identified. But so far there is no correlation made between these two concepts. The author used both velocity spectrum and Envelope spectrum to analyse the machine behaviour and bearing condition to correlated the changes in dynamic load (by unbalance, misalignment and looseness etc.) and effect of impact on the bearing. Hence we could able to predict the expected life of the machine and bearings in the rotating equipment (with rolling element bearings). Also we used process parameters like temperature, flow and pressure to correlate with flow induced vibration and load variations, when abnormal vibration occurs due to changes in process parameters. Hence by correlation of velocity spectrum, envelope spectrum and process data with 20 years of experience in vibration analysis, the author could able to predict the rotating Equipment and its component’s deterioration and expected duration for maintenance.

Keywords: vibration analysis, velocity spectrum, envelope spectrum, prediction of deterioration

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Authors: Nazish Saleem Abbas, Muhammad Haris Jamil, Hamid Sharif

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Digital watermarking is a technique that allows an individual to add and hide secret information, copyright notice, or other verification message inside a digital audio, video, or image. Today, with the advancement of technology, modern healthcare systems manage patients’ diagnostic information in a digital way in many countries. When transmitted between hospitals through the internet, the medical data becomes vulnerable to attacks and requires security and confidentiality. Digital watermarking techniques are used in order to ensure the authenticity, security and management of medical images and related information. This paper proposes a watermarking technique that embeds a watermark in medical images imperceptibly and securely. In this work, digital watermarking on medical images is carried out using the Least Significant Bit (LSB) with the Discrete Cosine Transform (DCT). The proposed methods of embedding and extraction of a watermark in a watermarked image are performed in the frequency domain using LSB by XOR operation. The quality of the watermarked medical image is measured by the Peak signal-to-noise ratio (PSNR). It was observed that the watermarked medical image obtained performing XOR operation between DCT and LSB survived compression attack having a PSNR up to 38.98.

Keywords: watermarking, image processing, DCT, LSB, PSNR

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Authors: Cinna Soltanpur, Mohammad Ghamari, Behzad Momahed Heravi, Fatemeh Zare

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Low-density parity-check (LDPC) codes have been shown to deliver capacity approaching performance; however, problematic graphical structures (e.g. trapping sets) in the Tanner graph of some LDPC codes can cause high error floors in bit-error-ratio (BER) performance under conventional sum-product algorithm (SPA). This paper presents a serial concatenation scheme to avoid the trapping sets and to lower the error floors of LDPC code. The outer code in the proposed concatenation is the LDPC, and the inner code is a high rate array code. This approach applies an interactive hybrid process between the BCJR decoding for the array code and the SPA for the LDPC code together with bit-pinning and bit-flipping techniques. Margulis code of size (2640, 1320) has been used for the simulation and it has been shown that the proposed concatenation and decoding scheme can considerably improve the error floor performance with minimal rate loss.

Keywords: concatenated coding, low–density parity–check codes, array code, error floors

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Authors: Wee Akina Sia Seng Lee, Shabeshan Rengasamy, Lim Boon Hooi, Chandrakalavaratharajoo, Mohd Ibrahim K. Azeez

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This study was conducted to examine the effectiveness of Teaching Games For Understanding (TGFU) in improving the hockey tactical skills and state self-confidence among 16-year-old students. Two hundred fifty nine (259) school students were selected for the study based on the intact sampling method. One class was used as the control group (Boys=60, Girls=70), while another as the treatment group (Boys=60, Girls=69) underwent intervention with TGFU in physical education class conducted twice a week for four weeks. The Games Performance Assessment Instrument was used to observe the hockey tactical skills and The State Self-Confidence Inventory was used to determine the state of self-confidence among the students. After four weeks, ANCOVA analysis indicated the treatment groups had significant improvement in hockey tactical skills with F (1, 118) =313.37, p < .05 for school boys, and F (1, 136) =92.62, p < .05 for school girls. The Mann Whitney U test also showed the treatment groups had significant improvement in state self-confidence with U=428.50, z= -7.22, p < .05, r=.06 for school boys. ANCOVA analysis also showed the treatment group had significant improvement in state self-confidence with F (1, 136) =74.40, p < .05 for school girls. This indicates that TGFU in a 40 minute physical education class conducted twice a week for four weeks can significantly improve the hockey tactical skills and state self-confidence among 16-year-old students. The findings give new knowledge to PE teachers to implement the TGFU method as it enhances the hockey tactical skills and state self-confidence among 16-year-old students. Some recommendation was suggested for future research.

Keywords: Teaching Games For Understanding (TGFU), traditional teaching, hockey tactical skills, state self-confidence

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Authors: Erion Luga, Aksel Seitllari, Kemal Pervanqe

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This study investigates the relation between physical and mechanical properties of concrete paving stones using neuro-fuzzy approach. For this purpose 200 samples of concrete paving stones were selected randomly from different sources. The first phase included the determination of physical properties of the samples such as water absorption capacity, porosity and unit weight. After that the indirect tensile strength test and compressive strength test of the samples were performed. İn the second phase, adaptive neuro-fuzzy approach was employed to simulate nonlinear mapping between the above mentioned physical properties and mechanical properties of paving stones. The neuro-fuzzy models uses Sugeno type fuzzy inference system. The models parameters were adapted using hybrid learning algorithm and input space was fuzzyfied by considering grid partitioning. It is concluded based on the observed data and the estimated data through ANFIS models that neuro-fuzzy system exhibits a satisfactory performance.

Keywords: paving stones, physical properties, mechanical properties, ANFIS

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Authors: Elham Serkani, Hossein Gharaee Garakani, Naser Mohammadzadeh, Elaheh Vaezpour

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Intrusion detection systems (IDS) are the main components of network security. These systems analyze the network events for intrusion detection. The design of an IDS is through the training of normal traffic data or attack. The methods of machine learning are the best ways to design IDSs. In the method presented in this article, the pruning algorithm of C5.0 decision tree is being used to reduce the features of traffic data used and training IDS by the least square vector algorithm (LS-SVM). Then, the remaining features are arranged according to the predictor importance criterion. The least important features are eliminated in the order. The remaining features of this stage, which have created the highest level of accuracy in LS-SVM, are selected as the final features. The features obtained, compared to other similar articles which have examined the selected features in the least squared support vector machine model, are better in the accuracy, true positive rate, and false positive. The results are tested by the UNSW-NB15 dataset.

Keywords: decision tree, feature selection, intrusion detection system, support vector machine

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Authors: Muthukumarasamy Govindarajan

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Detection of unwanted, unsolicited mails called spam from email is an interesting area of research. It is necessary to evaluate the performance of any new spam classifier using standard data sets. Recently, ensemble-based classifiers have gained popularity in this domain. In this research work, an efficient email filtering approach based on ensemble methods is addressed for developing an accurate and sensitive spam classifier. The proposed approach employs Naive Bayes (NB), Support Vector Machine (SVM) and Genetic Algorithm (GA) as base classifiers along with different ensemble methods. The experimental results show that the ensemble classifier was performing with accuracy greater than individual classifiers, and also hybrid model results are found to be better than the combined models for the e-mail dataset. The proposed ensemble-based classifiers turn out to be good in terms of classification accuracy, which is considered to be an important criterion for building a robust spam classifier.

Keywords: accuracy, arcing, bagging, genetic algorithm, Naive Bayes, sentiment mining, support vector machine

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Authors: Ravindra Dastikop, G. S. Thyagaraju, U. P. Kulkarni

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Even though the number of context aware applications is increasing day by day along with the users, till today there is no generic programming paradigm for context aware applications. This situation could be remedied by design and developing the appropriate context modeling and programming paradigm for context aware applications. In this paper, we are proposing the static context model and metrics for validating the expressiveness and understandability of the model. The proposed context modeling is a way of describing a situation of user using context entities , attributes and relationships .The model which is an extended and hybrid version of ER model, ontology model and Graphical model is specifically meant for expressing and understanding the user situation in context aware environment. The model is useful for understanding context aware problems, preparing documentation and designing programs and databases. The model makes use of context entity attributes relationship (CEAR) diagram for representation of association between the context entities and attributes. We have identified a new set of graphical notations for improving the expressiveness and understandability of context from the end user perspective .

Keywords: user context, context entity, context entity attributes, situation, sensors, devices, relationships, actors, expressiveness, understandability

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Authors: Anthony Schmiedeler

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Reliable measurements for body esteem and time perspective have been constructed to acquire additional knowledge into these two distinct and personal domains of individuals. The Body Esteem Scale (BES) assesses the multidimensional body self-esteems of males and females and produces a particular score. A higher BES score indicates an individual has strong positive feelings relating to particular aspects of the individual’s body. The Zimbardo Time Perspective Inventory (ZTPI) measures individuals’ time perspectives and identifies their dominant time perspective profiles. Higher scores in a time perspective profile, such as Past Positive (i.e., nostalgically remembering the past), suggest an individuals’ inclination toward that specific way of orienting oneself with respect to time. Both scales rely on measurements that are similarly grounded in personality traits and reveal valuable insight into individuals’ personalities. Studying the two scales could provide insight into a possible relationship and allow for a better comprehension and more nuanced understanding of the utilities of the instruments. In a completed study, 69 adults completed both the ZTPI and BES. Analyses show that adult females’ higher BES scores positively correlate with higher scores of the Past Positive and Present Hedonistic time perspective profiles of the ZTPI. Male participants also had higher overall BES scores positively correlate with the Present Hedonistic profile in addition to the Positive Future time perspective profile. The results of this study suggest that individuals with certain body esteem scores have a pattern of corresponding with certain time orientations. These correlations could help in explaining the rationales behind individuals’ varying levels of body esteem. With a foundation for better understanding of body esteem by incorporating these time perspectives, future research could be conducted to develop instruments that more accurately reflect individuals’ body esteem measurements.

Keywords: BES, body esteem, time perspective, ZTPI

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Authors: Hossein Kh. Bisheh, Nan Wu

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Advanced composite materials have a great importance in engineering structures due to their high specific modulus and strength and low weight. These materials can be used in design and fabrication of automotive drive shafts to reduce the weight of the structure. Hence, an optimum design of a composite drive shaft satisfying the design criteria, can be an appropriate substitution of metallic drive shafts. The aim of this study is to design and analyze a composite automotive drive shaft with high specific strength and low weight satisfying the design criteria. Tsai-Wu criterion is chosen as the failure criterion. Various designs with different lay-ups and materials are investigated based on the design requirements and finally, an optimum design satisfying the design criteria is chosen based on the weight and cost considerations. The results of this study indicate that if the weight is the main concern, a shaft made of Carbon/Epoxy can be a good option, and if the cost is a more important parameter, a hybrid shaft made of aluminum and Carbon/Epoxy can be considered.

Keywords: Bending natural frequency, Composite drive shaft, Peak torque, Torsional buckling

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Authors: A.G. S. Aldajani, N. Smida, M. G. Althobaiti, B. Zaidi

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In order to exploit the good electrical properties of anthracene and the excellent properties of fluorescein, new hybrid material has been synthesized (An-Fl). Current-voltage measurements were done on a new single-layer ITO/An-FL/Al device of typically 100 nm thickness. Atypical diode behavior is observed with a turn-on voltage of 4.4 V, a dynamic resistance of 74.07 KΩ and a rectification ratio of 2.02 due to unbalanced transport. Results show also that the current-voltage characteristics present three different regimes of the power-law (J~Vᵐ) for which the conduction mechanism is well described with space-charge-limited current conduction mechanism (SCLC) with a charge carrier mobility of 2.38.10⁻⁵cm2V⁻¹S⁻¹. Moreover, the electrical transport properties of this device have been carried out using a dependent frequency study in the range (50 Hz–1.4 MHz) for different applied biases (from 0 to 6 V). At lower frequency, the σdc values increase with bias voltage rising, supporting that the mobile ion can hop successfully to its nearest vacant site. From σac and impedance measurements, the equivalent electrical circuit is evidenced, where the conductivity process is coherent with an exponential trap distribution caused by structural defects and/or chemical impurities.

Keywords: semiconducting polymer, conductivity, SCLC, impedance spectroscopy

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Authors: Stefano Zappacosta, Cristiano Bove, Maria Carmela Marinelli, Paola di Lauro, Katarina Spasenovic, Lorenzo Ostano, Giuseppe Aiello, Marco Pietrosanto

Abstract:

This paper proposes a novel neural network approach for assessing flood hazard mapping. The core of the model is a machine learning component fed by frequency ratios, namely statistical correlations between flood event occurrences and a selected number of topographic properties. The proposed hybrid model can be used to classify four different increasing levels of hazard. The classification capability was compared with the flood hazard mapping River Basin Plans (PAI) designed by the Italian Institute for Environmental Research and Defence, ISPRA (Istituto Superiore per la Protezione e la Ricerca Ambientale). The study area of Piemonte, an Italian region, has been considered without loss of generality. The frequency ratios may be used as a standalone block to model the flood hazard mapping. Nevertheless, the mixture with a neural network improves the classification power of several percentage points, and may be proposed as a basic tool to model the flood hazard map in a wider scope.

Keywords: flood modeling, hazard map, neural networks, hydrogeological risk, flood risk assessment

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Authors: Mehmet Bulent Topkaya, Mustafa Yildirim

Abstract:

Wastewater treatment systems are designed and used to minimize adverse impacts of the wastewater on the environment before discharging. Various treatment options for wastewater treatment have been developed, and each of them has different performance characteristics and environmental impacts (e.g. material and land usage, energy consumption, greenhouse gas emission, water and soil emission) during construction, operation or maintenance phases. Assessing the environmental impacts during these phases are essential for the overall evaluation of the treatment systems. In this study, wastewater treatment options, such as vegetated land treatment, constructed wetland, rotating biological contactor, conventional activated sludge treatment, membrane bioreactor, extended aeration and stabilization pond are evaluated. The comparison of the environmental impacts is conducted under the assumption that the effluents will be discharged to sensitive and less sensitive areas respectively. The environmental impacts of each alternative are evaluated by life cycle assessment (LCA) approach. For this purpose, data related to energy usage, land requirement, raw material consumption, and released emissions from the life phases were collected with inventory studies based on field studies and literature. The environmental impacts were assessed by using SimaPro 7.1 LCA software. As the scale of the LCA results is global, an MS-Excel based decision support tool that includes the LCA result is developed in order to meet also the local demands. Using this tool, it is possible to assign weight factors on the LCA results according to local conditions by using Analytical Hierarchy Process and finally the most environmentally appropriate treatment option can be selected.

Keywords: analytical hierarchy process, decision support system, life cycle assessment, wastewater treatment

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Authors: Hans Marquez Ramos, Cesar Hernandez, Ingrid Páez

Abstract:

This paper develops a multiple channel assignment model, which allows to take advantage in most efficient way, spectrum opportunities in cognitive radio networks. Developed scheme allows make several available and frequency adjacent channel assignments, which require a bigger wide band, under an equality environment. The hybrid assignment model it is made by to algorithms, one who makes the ranking and select available frequency channels and the other one in charge of establishing an equality criteria, in order to not restrict spectrum opportunities for all other secondary users who wish to make transmissions. Measurements made were done for average bandwidth, average delay, as well fairness computation for several channel assignment. Reached results were evaluated with experimental spectrum occupational data from GSM frequency band captured. Developed model, shows evidence of improvement in spectrum opportunity use and a wider average transmit bandwidth for each secondary user, maintaining equality criteria in channel assignment.

Keywords: bandwidth, fairness, multichannel, secondary users

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Authors: Solomon Neway Jida, Jean-Francois Hetet, Pascal Chesse

Abstract:

Vehicular emission is the key source of air pollution in the urban environment. This includes both fine particles (PM_2.5) and coarse particulate matters (PM₁₀). However, particulate matter emissions from road traffic comprise emissions from exhaust tailpipe and emissions due to wear and tear of the vehicle part such as brake, tire and clutch and re-suspension of dust (non-exhaust emission). This study estimates the share of the two sources of pollutant particle emissions from on-roadside vehicles in the Addis Ababa municipality, Ethiopia. To calculate its share, two methods were applied; the exhaust-tailpipe emissions were calculated using the Europeans emission inventory Tier II method and Tier I for the non-exhaust emissions (like vehicle tire wear, brake, and road surface wear). The results show that of the total traffic-related particulate emissions in the city, 63% emitted from vehicle exhaust and the remaining 37% from non-exhaust sources. The annual roads transport exhaust emission shares around 2394 tons of particles from all vehicle categories. However, from the total yearly non-exhaust particulate matter emissions’ contribution, tire and brake wear shared around 65% and 35% emanated by road-surface wear. Furthermore, vehicle tire and brake wear were responsible for annual 584.8 tons of coarse particles (PM₁₀) and 314.4 tons of fine particle matter (PM_2.5) emissions in the city whereas surface wear emissions were responsible for around 313.7 tons of PM₁₀ and 169.9 tons of PM_2.5 pollutant emissions in the city. This suggests that non-exhaust sources might be as significant as exhaust sources and have a considerable contribution to the impact on air quality.

Keywords: Addis Ababa, automotive emission, emission estimation, particulate matters

Procedia PDF Downloads 130