Search results for: improved Canny algorithm

Authors: Yasaman Sanayei, Alireza Bahiraie

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This paper presents a systematic methodology based on the application of artificial neural networks for sequencing batch reactor (SBR). The SBR is a fill-and-draw biological wastewater technology, which is specially suited for nutrient removal. Employing reactive dye by Sphingomonas paucimobilis bacteria at sequence batch reactor is a novel approach of dye removal. The influent COD, MLVSS, and reaction time were selected as the process inputs and the effluent COD and BOD as the process outputs. The best possible result for the discrete pole parameter was a= 0.44. In orderto adjust the parameters of ANN, the Levenberg-Marquardt (LM) algorithm was employed. The results predicted by the model were compared to the experimental data and showed a high correlation with R2> 0.99 and a low mean absolute error (MAE). The results from this study reveal that the developed model is accurate and efficacious in predicting COD and BOD parameters of the dye-containing wastewater treated by SBR. The proposed modeling approach can be applied to other industrial wastewater treatment systems to predict effluent characteristics. Note that SBR are normally operated with constant predefined duration of the stages, thus, resulting in low efficient operation. Data obtained from the on-line electronic sensors installed in the SBR and from the control quality laboratory analysis have been used to develop the optimal architecture of two different ANN. The results have shown that the developed models can be used as efficient and cost-effective predictive tools for the system analysed.

Keywords: artificial neural network, COD removal, SBR, Sphingomonas paucimobilis

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Authors: Gabriela Kloudova, Miloslav Stehlik, Peter Sos

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The quality of sleep can affect combat performance where the vigilance, accuracy and reaction time are a decisive factor. In the present study, airborne and special units are measured on duty using actigraphy fingerprint scoring algorithm and QEEG (quantitative EEG). Actigraphic variables of interest will be: mean nightly sleep duration, mean napping duration, mean 24-h sleep duration, mean sleep latency, mean sleep maintenance efficiency, mean sleep fragmentation index, mean sleep onset time, mean sleep offset time and mean midpoint time. In an attempt to determine the individual somnotype of each subject, the data like sleep pattern, chronotype (morning and evening lateness), biological need for sleep (daytime and anytime sleepability) and trototype (daytime and anytime wakeability) will be extracted. Subsequently, a series of recommendations will be included in the training plan based on daily routine, timing of the day and night activities, duration of sleep and the number of sleeping blocks in a defined time. The aim of these modifications in the training plan is to reduce day-time sleepiness, improve vigilance, attention, accuracy, speed of the conducted tasks and to optimize energy supplies. Regular improvement of the training supposed to have long-term neurobiological consequences including neuronal activity changes measured by QEEG. Subsequently, that should enhance cognitive functioning in subjects assessed by the digital cognitive test batteries and improve their overall performance.

Keywords: sleep quality, combat performance, actigraph, somnotype

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Authors: Christia C. Baltar

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Everybody goes to primary education but not all proceed to secondary education because of poverty and it is evident in the Philippines. Moreover, the number goes down when they reach higher education. The researcher believes that higher education may improve the standard of living of the family looking at the economic benefits of it. Once one graduated from a particular degree, one may employ with higher wage than those who are non-degree holder. Every year the Philippines produce more than five hundred thousand graduates of higher education and it keeps on increasing every year. Thus, the competition in the employment is really high. It is then important to pursue higher education than settling to a high school graduate because a degree is what most of the employer is looking for. The Philippine government through the Department of Labor and Employment is offering job fairs to all cities as much as possible just to cater employment for those graduates away from urban areas like in Manila and even the privates sectors also proposing for job fairs. Researcher conducted a survey in her institution and she further used secondary information to strengthen the findings of her survey. Researcher used descriptive measures, chi-square test for independence, and the correlation coefficient to analyze the data in her survey. In the survey conducted results show that there was an increase on the income of the family of the graduates of higher education. The graduates believed that their standard of living improved because they were able to work in a better job. The data were analyzed and the results show that there was no significant relationship on sex, age and marital status of the graduates to their economic status but the degree program they enrolled in the tertiary education affects their economic status. The impact of earning higher education can be seen indirectly to the economic growth of the Philippines. Finally, researcher concludes that there is direct and indirect impact of the higher education to the economic status of the graduates.

Keywords: economic benefits, economic status, graduate, higher education

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Authors: Neha Ahirwar

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In the contemporary digital era, the rise of credit card fraud poses a significant threat to both financial institutions and consumers. As fraudulent activities become more sophisticated, there is an escalating demand for robust and effective fraud detection mechanisms. Advanced machine learning algorithms have become crucial tools in addressing this challenge. This paper conducts a thorough examination of the design and evaluation of a credit card fraud detection system, utilizing four prominent machine learning algorithms: random forest, logistic regression, decision tree, and XGBoost. The surge in digital transactions has opened avenues for fraudsters to exploit vulnerabilities within payment systems. Consequently, there is an urgent need for proactive and adaptable fraud detection systems. This study addresses this imperative by exploring the efficacy of machine learning algorithms in identifying fraudulent credit card transactions. The selection of random forest, logistic regression, decision tree, and XGBoost for scrutiny in this study is based on their documented effectiveness in diverse domains, particularly in credit card fraud detection. These algorithms are renowned for their capability to model intricate patterns and provide accurate predictions. Each algorithm is implemented and evaluated for its performance in a controlled environment, utilizing a diverse dataset comprising both genuine and fraudulent credit card transactions.

Keywords: efficient credit card fraud detection, random forest, logistic regression, XGBoost, decision tree

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Authors: Flavia Laffleur

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Summary: Biomaterials have gained immense interest in the pharmaceutical research in the last decades. Hyaluronic acid a carbohydrate and mucopolysaccharide was chemically modified in order to achieve and establish a promising platform for buccal drug delivery. Aim: Novel biomaterial was tested for its potential for buccal drug delivery. Background: Polysaccharide hyaluronic acid (HA) was chemically modified with cysteine ethyl ether (CYS). By immobilization of the thiol-bearing ligand on the polymeric backbone the thiolated bioconjugate HA-CYS was obtained. Methodology: Mucoadhesive, permeation enhancing and stability potential as well as mechanical, physicochemical properties further mucoadhesive strength, swelling index and residence time were investigated. The developed thiolated bioconjugate displayed enhanced mucoadhesiveness on buccal mucosa as well as permeation behavior and polymer stability. The near neutral pH and negative cytotoxicity studies indicated their non-irritability and biocompatible nature with biological tissues. Further, the model drug sulforhodamine 101 was incorporated to determine its drug release profiles. Results: The synthesized thiomer showed no toxicity. The mucoadhesion of thiolated hyaluronic acid on buccal mucosa was significantly improved in comparison to unmodified one. The biomaterial showed 2.5-fold higher stability in polymer structure. The release of sulforhodamine in the presence of thiolated hyaluronic acid was 2.3-fold increased compared to hyaluronic acid. Conclusion: Thus, the promising results encourage further investigations and exploitation of this versatile polysaccharide. So far, hyaluronic acid was not evaluated for buccal drug delivery.

Keywords: buccal delivery, hyaluronic acid, mucoadhesion, thiomers

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Authors: Shabeer Khan

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The main objective of Islamic Finance is to promote social justice thorough financial inclusion and redistribution of economic resources between rich and poor. The approach of Islamic finance is more comprehensive in nature and covers both formal and informal sectors of the economy, first, through reducing the gap between both sectors, and second by using specific Islamic values to reallocate the wealth between formal and informal sectors. Applying Generalized Method of Movements (GMM) to the annual data spanning from 1995-2015 for 141 countries, this study explores the determinants of informal business sector in Organization of Islamic Cooperation (OIC) countries and then compares with Non-OIC countries. Economic freedom and institutions variables as well as economic growth and money supply are found to reduce informal business sector in both OIC and Non-OIC nations while government expenditure are found to increase informal business sector in both group of nations. Informal Business sector remain the same in both types of countries but still the majority Muslim population in OIC economies create main difference between both groups of nations and justify the potential role of Islamic Finance in informal business sector in OIC nations. The study suggests that institutions quality should be improved and entrepreneurs’ friendly business environment must be provided. This study refines the main features of informal business sector and discuss their implications on policy designing and implementation, particularly in the context of Islamic finance fight against poverty, inequality and improving living standards of informal sector participants in OIC countries.

Keywords: Islamic finance, informal Business Sector, Generalized Method of Movements (GMM) and OIC

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Authors: Jason Ting Jing Cheng, Lee Foo Wei, Yew Ming Kun, Chin Ren Jie, Yip Chun Chieh

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The utilization of industrial by-products, such as steel slag in cementitious materials, not only mitigates environmental impact but also enhances material properties. This study investigates the dual influence of steel slag particle size on the compressive strength and carbonation efficiency of cementitious composites. Through a systematic experimental approach, steel slag particles were incorporated into cement at varying sizes, and the resulting composites were subjected to mechanical and carbonation tests. Scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX) are conducted in this paper. The findings reveal a positive correlation between increased particle size and compressive strength, attributed to the improved interfacial transition zone and packing density. Conversely, smaller particle sizes exhibited enhanced carbonation efficiency, likely due to the increased surface area facilitating the carbonation reaction. The presence of higher silica and calcium content in finer particles was confirmed by EDX, which contributed to the accelerated carbonation process. This study underscores the importance of particle size optimization in designing sustainable cementitious materials with balanced mechanical performance and carbon sequestration potential. The insights gained from the advanced analytical techniques offer a comprehensive understanding of the mechanisms at play, paving the way for the strategic use of steel slag in eco-friendly construction practices.

Keywords: steel slag, carbonation efficiency, particle size enhancement, compressive strength

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Authors: Alimohamad Asghari, Ahmad Daneshi, Mohammad Farhadi, Arash Bayat, Mohammad Ajalloueyan, Marjan Mirsalehi, Mohsen Rajati, Seyed Basir Hashemi, Nader Saki, Ali Omidvari

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Evidence suggests that Cochlear Implantation (CI) is a beneficial approach for auditory and speech skills improvement in children with severe to profound hearing loss. However, it remains controversial if implantation in children <12 months is safe and effective compared to older children. The present study aimed to determine whether children's ages affect surgical complications and auditory and speech development. The current multicenter study enrolled 86 children who underwent CI surgery at <12 months of age (group A) and 362 children who underwent implantation between 12 and 24 months of age (group B). The Categories of Auditory Performance (CAP) and Speech Intelligibility Rating (SIR) scores were determined pre-impanation, and "one-year" and "two-year" post-implantation. Four complications (overall rate: 4.65%; three minor) occurred in group A and 12 complications (overall rate: 4.41%; nine minor) occurred in group B. We found no statistically significant difference in the complication rates between the groups (p>0.05). The mean SIR and CAP scores improved over time following CI activation in both groups. However, we did not find significant differences in CAP and SIR scores between the groups across different time points. Cochlear implantation is a safe and efficient procedure in children younger than 12 months, providing substantial auditory and speech benefits comparable to children undergoing implantation at 12 to 24 months of age. Furthermore, surgical complications in younger children are similar to those of children undergoing the CI at an older age.

Keywords: cochlear implant, Infant, complications, outcome

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Authors: Sana Masmoudi Mardassi, Yosra Makni Fourati

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Regulators highlight the importance of the Audit Committee (AC) as a key internal corporate governance mechanism. One of the most important roles of this committee is to oversee the financial reporting process. The purpose of this paper is to examine the link between the characteristics of an audit committee and the financial reporting quality by investigating whether the characteristics of audit committees are associated with improved financial reporting quality, especially the Real Earnings Management. In the current study, a panel data from 80 nonfinancial companies listed on the Amsterdam Stock Exchange during the period between 2010 and 2017 were used. To measure audit committee characteristics, four proxies have been used, specifically, audit committee independence, financial expertise, gender diversity and AC meetings. For this research, a linear regression model was used to identify the influence of a set of board characteristics of the audit committee on real earnings management after controlling for firm audit committee size, leverage, size, loss, growth and board size. This research provides empirical evidence of the association between audit committee independence, financial expertise, gender diversity and meetings and Real Earnings Management (REM) as a proxy of financial reporting quality. The study finds that independence and AC Gender diversity are strongly related to financial reporting quality. In fact, these two characteristics constrain REM. The results also suggest that AC- financial expertise reduces to some extent, the likelihood of engaging in REM. These conclusions provide support then to the audit committee requirement under the Dutch Corporate Governance Code rules regarding gender diversity and AC meetings.

Keywords: audit committee, financial expertise, independence, real earnings management

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Authors: U. S. Babuga, A. H. Danwanka, A. Garba

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The research was carried out to compare the yield of respondents before and after access to extension services on crop production technologies in the study area. Data were collected from the study area through questionnaires administered to seventy-five randomly selected respondents. Data were analyzed using descriptive statistics, t-test and regression models. The result disclosed that majority (97%) of the respondent attended one form of school or the other. The majority (78.67%) of the respondents had farm size ranging between 1-3 hectares. The majority of the respondent adopt improved variety of crops, plant spacing, herbicide, fertilizer application, land preparation, crop protection, crop processing and storage of farm produce. The result of the t-test between the yield of respondents before and after access to extension services shows that there was a significant (p<0.001) difference in yield before and after access to extension. It also indicated that farm size was significant (p<0.001) while household size, years of farming experience and extension contact were significant at (p<0.005). The major constraint to adoption of crop production technologies were shortage of extension agents, high cost of technology and lack of access to credit facility. The major pre-requisite for the improvement of extension service are employment of more extension agents or workers and adequate training. Adequate agricultural credit to farmers at low interest rates will enhance their adoption of crop production technologies.

Keywords: comparative, analysis, yield, access, extension

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Authors: Jingjie Li, Wenjie Hu

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Phraseological units in academic English texts have been a central focus in recent corpus linguistic research. A wide variety of phraseological units have been explored, including collocations, chunks, lexical bundles, patterns, semantic sequences, etc. This paper describes a special category of clause-level phraseological units, namely, Characteristic Sentence Stems (CSSs), with a view to describing their defining criteria and extraction method. CSSs are contiguous lexico-grammatical sequences which contain a subject-predicate structure and which are frame expressions characteristic of academic writing. The extraction of CSSs consists of six steps: Part-of-speech tagging, n-gram segmentation, structure identification, significance of occurrence calculation, text range calculation, and overlapping sequence reduction. Significance of occurrence calculation is the crux of this study. It includes the computing of both the internal association and the boundary independence of a CSS and tests the occurring significance of the CSS from both inside and outside perspectives. A new normalization algorithm is also introduced into the calculation of LocalMaxs for reducing overlapping sequences. It is argued that many sentence stems are so recurrent in academic texts that the most typical of them have become the habitual ways of making meaning in academic writing. Therefore, studies of CSSs could have potential implications and reference value for academic discourse analysis, English for Academic Purposes (EAP) teaching and writing.

Keywords: characteristic sentence stem, extraction method, phraseological unit, the statistical measure

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Authors: H. Shola Adeosun, F. Ajoke Adebiyi

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This study appraises the impact of television on the coverage of Lassa Fever disease. The objectives of the study are to find out whether television is an effective tool for raising awareness about Lassa fever shapes the perception of members of the public. The research work was based on the theoretical foundation of Agenda – setting and reinforcement theory. Survey research method was adopted in the study to elicit data from the residents of Obafemi Owode Local Government, area of Ogun state. Questionnaire and oral interview were adopted as a tool for data gathering. Simple random sampling techniques were used to draw a sample for this study. Out of filled 400 questionnaires distributed to the respondents. 37 of them were incorrectly filled and returned at the stipulated time. This is about (92.5% Tables, percentages, and figures were used to analyse and interpret the data and hypothesis formulation for this study revealed that Lassa fever diseases with higher media coverage were considered more serious and more representative of a disease and estimated to have lower incidents, than diseases less frequently found in the media. Thus, 92% of the respondents agree that they have access to television coverage of Lassa fever disease led to exaggerated perceptions of personal vulnerability. It, therefore, concludes that there is a need for relevant stakeholders to ensure better community health education and improved housing conditions in southwestern Nigeria, with an emphasis on slum areas and that Nigeria need to focus on the immediate response, while preparing for the future because a society or community is all about the people who inhabit. Therefore every effort must be geared towards their society and survival.

Keywords: impact, television, coverage, Lassa fever disease

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Authors: Ahmed Fradi

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Nowadays, recent technological advances in the acquisition, modeling, and processing of three-dimensional (3D) objects data lead to the creation of models stored in huge databases, which are used in various domains such as computer vision, augmented reality, game industry, medicine, CAD (Computer-aided design), 3D printing etc. On the other hand, the industry is currently benefiting from powerful modeling tools enabling designers to easily and quickly produce 3D models. The great ease of acquisition and modeling of 3D objects make possible to create large 3D models databases, then, it becomes difficult to navigate them. Therefore, the indexing of 3D objects appears as a necessary and promising solution to manage this type of data, to extract model information, retrieve an existing model or calculate similarity between 3D objects. The objective of the proposed research is to develop a framework allowing easy and fast access to 3D objects in a CAD models database with specific indexing algorithm to find objects similar to a reference model. Our main objectives are to study existing methods of similarity calculation of 3D objects (essentially shape-based methods) by specifying the characteristics of each method as well as the difference between them, and then we will propose a new approach for indexing and comparing 3D models, which is suitable for our case study and which is based on some previously studied methods. Our proposed approach is finally illustrated by an implementation, and evaluated in a professional context.

Keywords: CAD, 3D object retrieval, shape based retrieval, similarity calculation

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Authors: Aderonke Oluseun Akinwumi, Olusola A. Komolaf

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This paper gives information about the wide array of challenges facing both the electric utilities and consumers in the distribution system in developing countries, using Obafemi Awolowo University, Ile-Ife Nigeria as a case study. It also proffers cost-effective solution through remote monitoring, diagnostic and operation of distribution networks without compromising the system reliability. As utilities move from manned and unintelligent networks to completely unmanned smart grids, switching activities at substations and feeders will be managed and controlled remotely by dedicated systems hence this design. The Substation Remote Diagnostic and Operation Solution (sRDOs) would remotely monitor the load on Medium Voltage (MV) and Low Voltage (LV) feeders as well as distribution transformers and allow the utility disconnect non-paying customers with absolutely no extra resource deployment and without interrupting supply to paying customers. The aftermath of the implementation of this design improved the lifetime of key distribution infrastructure by automatically isolating feeders during overload conditions and more importantly erring consumers. This increased the ratio of revenue generated on electricity bills to total network load.

Keywords: electric utility, consumers, remote monitoring, diagnostic, system reliability, manned and unintelligent networks, unmanned smart grids, switching activities, medium voltage, low voltage, distribution transformer

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Authors: Azita Ramezani, Ghazal Mashhadiagha, Bahareh Sanabakhsh

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This study researches the combination of Random. Forest classifiers with large language models (LLMs) and natural language processing (NLP) to improve diagnostic accuracy in chest X-ray analysis using the Indiana University dataset. Utilizing advanced NLP techniques, the research preprocesses textual data from radiological reports to extract key features, which are then merged with image-derived data. This improved dataset is analyzed with Random Forest classifiers to predict specific clinical results, focusing on the identification of health issues and the estimation of case urgency. The findings reveal that the combination of NLP, LLMs, and machine learning not only increases diagnostic precision but also reliability, especially in quickly identifying critical conditions. Achieving an accuracy of 99.35%, the model shows significant advancements over conventional diagnostic techniques. The results emphasize the large potential of machine learning in medical imaging, suggesting that these technologies could greatly enhance clinician judgment and patient outcomes by offering quicker and more precise diagnostic approximations.

Keywords: natural language processing (NLP), large language models (LLMs), random forest classifier, chest x-ray analysis, medical imaging, diagnostic accuracy, indiana university dataset, machine learning in healthcare, predictive modeling, clinical decision support systems

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Authors: Lourdes Gutierrez, Eric Williams

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Post-occupancy research shows that only 11% of commercial buildings met the ASHRAE thermal comfort standard. Many buildings are too warm in winter and/or too cool in summer, wasting energy and not providing comfort. In this paper, potential energy savings in U.S. offices and restaurants if thermostat settings are calculated according the updated ASHRAE 55-2013 comfort model that accounts for outdoor temperature and clothing choice for different climate zones. eQUEST building models are calibrated to reproduce aggregate energy consumption as reported in the U.S. Commercial Building Energy Consumption Survey. Changes in energy consumption due to the new settings are analyzed for 14 cities in different climate zones and then the results are extrapolated to estimate potential national savings. It is found that, depending on the climate zone, each degree increase in the summer saves 0.6 to 1.0% of total building electricity consumption. Each degree the winter setting is lowered saves 1.2% to 8.7% of total building natural gas consumption. With new thermostat settings, national savings are 2.5% of the total consumed in all office buildings and restaurants, summing up to national savings of 69.6 million GJ annually, comparable to all 2015 total solar PV generation in US. The goals of improved comfort and energy/economic savings are thus co-aligned, raising the importance of thermostat management as an energy efficiency strategy.

Keywords: energy savings quantifications, commercial building stocks, dynamic clothing insulation model, operation-focused interventions, energy management, thermal comfort, thermostat settings

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Authors: Lethamaga Tladi, Ray Kekwaletswe

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This study sought to conceptualise a multi-level framework for the effective use of stock ordering system in small enterprises in a rural area context. The interpretive research methodology has been used to enable the researcher to analyse, in-depth, and the subjective meanings of small enterprises’ employees in using the stock ordering system. The empirical data was collected from 13 small enterprises’ employees as participants through semi-structured interviews and observations. Interpretive Phenomenological Analysis (IPA) approach was used to analyse the small enterprises’ employee’s own account of lived experiences in relations to stock ordering system use in terms of their relatedness to, and cognitive engagement with. A case study of Kgautswane, a rural area in Limpopo Province, South Africa, served as a social context where the phenomenon manifested. Technology-Organisation-Environment Theory (TOE), Technology-to-Performance Chain Model (TPC), and Representation Theory (RT) underpinned this study. In this multi-level study, the findings revealed that; At the organisational level, the effective use of stock ordering system was found to be associated with the organisational performance gains such as efficiency, productivity, quality, competitiveness, and market share. Equally so, at the individual level, the effective use of stock ordering system minimised the end-user’s efforts and time to accomplish their tasks, which yields improved individual performance. The Multi-level framework for effective use of stock ordering system was presented.

Keywords: effective use, multi-dimensions of use, multi-level of use, multi-level research, small enterprises, stock ordering system

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Authors: Lu-Yin Lin

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The morphology of electroactive material is highly related to energy storage ability. Structure-directing agent (SDA) can design electroactive materials with favorable surface properties. Zeolitic imidazolate framework 67 (ZIF67) is one of the potential electroactive materials for energy storage devices. The SDA concept is less applied to designing ZIF67 derivatives in previous studies. An in-situ technique with ammonium fluoride (NH₄F) as SDA is proposed to produce a ZIF67 derivative with highly improved energy storage ability. Attracted by the effective in-situ technique, the NH₄F, ammonium bifluoride (NH₄HF₂), and ammonium tetrafluoroborate (NH₄BF₄) are first used as SDA to synthesize ZIF67 derivatives in one-step solution process as electroactive material of energy storage devices. The mechanisms of forming ZIF67 derivatives synthesized with different SDAs are discussed to explain the SDA effects on physical and electrochemical properties. The largest specific capacitance (CF) of 1527.0 Fg-¹ and the capacity of 296.9 mAhg-¹ are obtained for the ZIF67 derivative prepared using NH₄BF₄ as SDA. The energy storage device composed of the optimal ZIF67 derivative and carbon electrodes presents a maximum energy density of 15.1 Whkg-¹ at the power density of 857 Wkg-¹. The CF retention of 90% and Coulombic efficiency larger than 98% are also obtained after 5000 cycles.

Keywords: ammonium bifluoride, ammonium tetrafluoroborate, energy storage device, one-step solution process, structure-directing agent, zeolitic imidazolate framework 67

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Authors: Fred N. H. Parker, Nicola T. Fear, S. A. M. Stevelink, L. Rafferty

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Purpose Auditory problems, such as hearing loss and tinnitus, have been associated with mental health problems and alcohol misuse in the UK general population and in the US Armed Forces; however, few studies have examined these associations within the UK Armed Forces. The present study examined the association between auditory problems and probable common mental disorders, post-traumatic stress disorder and alcohol misuse. Methods 5474 serving and ex-service personnel from the UK Armed Forces were examined, selected from those who responded to phase two (data collection 2007–09) and phase three (2014–16) of a military cohort study. Multivariable logistic regression was used to examine the association between auditory problems at phase two and mental health problems at phase three. Results 9.7% of participants reported ever experiencing hearing problems alone, 7.9% reported tinnitus within the last month alone, and 7.8% reported hearing problems with tinnitus. After adjustment, hearing problems with tinnitus at phase two was associated with increased odds of probable common mental disorders (AOR = 1.50, 95% CI 1.09–2.08), post-traumatic stress disorder (AOR = 2.30, 95% CI 1.41–3.76), and alcohol misuse (AOR = 1.94, 95% CI 1.28–2.96) at phase three. Tinnitus alone was associated with probable post-traumatic stress disorder (AOR = 1.80, 95% CI 1.03–3.15); however, hearing problems alone were not associated with any outcomes of interest. Conclusions The association between auditory problems and mental health problems emphasizes the importance of the prevention of auditory problems in the Armed Forces: through enhanced audiometric screening, improved hearing protection equipment, and greater levels of utilization of such equipment.

Keywords: armed forces, hearing problems, tinnitus, mental health, alcohol misuse

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Authors: Masoud Rabbani, Majede Smizadeh, Hamed Farrokhi-Asl

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We study jointly determining prices and production in a multiple period horizon under a general non-stationary stochastic demand with continuous prices. In some periods we need to increase capacity of production to satisfy demand. This paper presents a model to aid multi-period production capacity planning by quantifying the trade-off between product quality and production cost. The product quality is estimated as the statistical variation from the target performances obtained from the output tolerances of the production machines that manufacture the components. We consider different tolerance for different machines that use to increase capacity. The production cost is estimated as the total cost of owning and operating a production facility during the planning horizon.so capacity planning has cost that impact on price. Pricing products often turns out to be difficult to measure them because customers have a reservation price to pay that impact on price and demand. We decide to determine prices and production for periods after enhance capacity and consider reservation price to determine price. First we use an algorithm base on fuzzy set of the optimal objective function values to determine capacity planning by determine maximize interval from upper bound in minimum objectives and define weight for objectives. Then we try to determine inventory and pricing policies. We can use a lemma to solve a problem in MATLAB and find exact answer.

Keywords: price policy, inventory policy, capacity planning, product quality, epsilon -constraint

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Authors: Redouane Larbi Boufeniza, Jing-Jia Luo

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This study assesses the suitability of deep learning (DL) for downscaling sea surface temperature (SST) over the Mediterranean Sea in the context of seasonal forecasting. We design a set of experiments that compare different DL configurations and deploy the best-performing architecture to downscale one-month lead forecasts of June–September (JJAS) SST from the Nanjing University of Information Science and Technology Climate Forecast System version 1.0 (NUIST-CFS1.0) for the period of 1982–2020. We have also introduced predictors over a larger area to include information about the main large-scale circulations that drive SST over the Mediterranean Sea region, which improves the downscaling results. Finally, we validate the raw model and downscaled forecasts in terms of both deterministic and probabilistic verification metrics, as well as their ability to reproduce the observed precipitation extreme and spell indicator indices. The results showed that the convolutional neural network (CNN)-based downscaling consistently improves the raw model forecasts, with lower bias and more accurate representations of the observed mean and extreme SST spatial patterns. Besides, the CNN-based downscaling yields a much more accurate forecast of extreme SST and spell indicators and reduces the significant relevant biases exhibited by the raw model predictions. Moreover, our results show that the CNN-based downscaling yields better skill scores than the raw model forecasts over most portions of the Mediterranean Sea. The results demonstrate the potential usefulness of CNN in downscaling seasonal SST predictions over the Mediterranean Sea, particularly in providing improved forecast products.

Keywords: Mediterranean Sea, sea surface temperature, seasonal forecasting, downscaling, deep learning

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Authors: Naydelis Brito Suárez, Deni Librado Torres Román, Fernando Hermosillo Reynoso

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Automatic detection and generation of a dynamic ROI (Region of Interest) in vehicle traffic surveillance videos based on a static camera in Intelligent Transportation Systems is challenging for computer vision-based systems. The dynamic ROI, being a changing ROI, should capture any other moving object located outside of a static ROI. In this work, the video is represented by a Tensor model composed of a Background and a Foreground Tensor, which contains all moving vehicles or objects. The values of each pixel over a time interval are represented by time series, and some pixel rows were selected. This paper proposes a pixel entropy-based algorithm for automatic detection and generation of a dynamic ROI in traffic videos under the assumption of two types of theoretical pixel entropy behaviors: (1) a pixel located at the road shows a high entropy value due to disturbances in this zone by vehicle traffic, (2) a pixel located outside the road shows a relatively low entropy value. To study the statistical behavior of the selected pixels, detecting the entropy changes and consequently moving objects, Shannon, Tsallis, and Approximate entropies were employed. Although Tsallis entropy achieved very high results in real-time, Approximate entropy showed results slightly better but in greater time.

Keywords: convex hull, dynamic ROI detection, pixel entropy, time series, moving objects

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Authors: P. Bharathiraja

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Computer Aided decision making system is used to enhance diagnosis and prognosis of diseases and also to assist clinicians and junior doctors in clinical decision making. Medical Data used for decision making should be definite and consistent. Data Mining and soft computing techniques are used for cleaning the data and for incorporating human reasoning in decision making systems. Fuzzy rule based inference technique can be used for classification in order to incorporate human reasoning in the decision making process. In this work, missing values are imputed using the mean or mode of the attribute. The data are normalized using min-ma normalization to improve the design and efficiency of the fuzzy inference system. The fuzzy inference system is used to handle the uncertainties that exist in the medical data. Equal-width-partitioning is used to partition the attribute values into appropriate fuzzy intervals. Fuzzy rules are generated using Class Based Associative rule mining algorithm. The system is trained and tested using heart disease data set from the University of California at Irvine (UCI) Machine Learning Repository. The data was split using a hold out approach into training and testing data. From the experimental results it can be inferred that classification using fuzzy inference system performs better than trivial IF-THEN rule based classification approaches. Furthermore it is observed that the use of fuzzy logic and fuzzy inference mechanism handles uncertainty and also resembles human decision making. The system can be used in the absence of a clinical expert to assist junior doctors and clinicians in clinical decision making.

Keywords: decision making, data mining, normalization, fuzzy rule, classification

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Authors: Teresa Azevedo PerdicoúLis, Paulo Lopes Dos Santos

Abstract:

The conceptualisation of the problem of network optimisation as a noncooperative game sets up a holistic interactive approach that brings together different network features (e.g., com-pressor stations, sources, and pipelines, in the gas context) where the optimisation objectives are different, and a single optimisation procedure becomes possible without having to feed results from diverse software packages into each other. A mathematical model of this type, where independent entities take action, offers the ideal modularity and subsequent problem decomposition in view to design a decentralised algorithm to optimise the operation and management of the network. In a game framework, compressor stations and sources are under-stood as players which communicate through network connectivity constraints–the pipeline model. That is, in a scheme similar to tatonnementˆ, the players appoint their best settings and then interact to check for network feasibility. The devolved degree of network unfeasibility informs the players about the ’quality’ of their settings, and this two-phase iterative scheme is repeated until a global optimum is obtained. Due to network transients, its optimisation needs to be assessed at different points of the control interval. For this reason, the proposed approach to optimisation has two stages: (i) the first stage computes along the period of optimisation in order to fulfil the requirement just mentioned; (ii) the second stage is initialised with the solution found by the problem computed at the first stage, and computes in the end of the period of optimisation to rectify the solution found at the first stage. The liability of the proposed scheme is proven correct on an abstract prototype and three example networks.

Keywords: connectivity matrix, gas network optimisation, large-scale, noncooperative game, system decomposition

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Authors: Syed Toqueer Akhter, Muhammad Awais

Abstract:

Pakistan is a country which is gifted by naturally abundant resources these resources are a pioneer towards a prospect and developed country. Pakistan is the fourth largest exporter of the textile in the world and with the passage of time the competitiveness of these exports is subject to a decline. With a lot of International players in the textile world like China, Bangladesh, India, and Sri Lanka, Pakistan needs to put up a lot of effort to compete with these countries. This research paper would determine the impact of Foreign Direct Investment upon technological diffusion and that how significantly it may be affecting on export performance of the country. It would also demonstrate that with the increase in Foreign Direct Investment, technological diffusion, strong property rights, and using different policy tools, export competitiveness of the country could be improved. The research has been carried out using time series data from 1995 to 2013 and the results have been estimated by using competing Econometrics modes such as Robust regression and Generalized least squares so that to consolidate the impact of the Foreign Investments and Technological diffusion upon export competitiveness comprehensively. Distributed Lag model has also been used to encompass the lagged effect of policy tools variables used by the government. Model estimates entail that 'FDI' and 'Technological Diffusion' do have a significant impact on the competitiveness of the exports of Pakistan. It may also be inferred that competitiveness of Textile Sector requires integrated policy framework, primarily including the reduction in interest rates, providing subsides, and manufacturing of value added products.

Keywords: high technology export, robust regression, patents, technological diffusion, export competitiveness

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Authors: Sebai Amal, Massuel Sylvain

Abstract:

Groundwater is the key element of the development of most of the semi-arid areas where water resources are increasingly scarce due to an irregularity of precipitation, on the one hand, and an increasing demand on the other hand. This is the case of the watershed of the Central Tunisia Merguellil, object of the present study, which focuses on an implementation of an underground flows hydrodynamic model to understand the recharge processes of the Kairouan’s plain groundwater by aquifers boundary through the hydraulic threshold of El Haouareb. The construction of a conceptual geological 3D model by the Hydro GeoBuilder software has led to a definition of the aquifers geometry in the studied area thanks to the data acquired by the analysis of geologic sections of drilling and piezometers crossed shells partially or in full. Overall analyses of the piezometric Chronicles of different piezometers located at the level of the dam indicate that the influence of the dam is felt especially in the aquifer carbonate which confirms that the dynamics of this aquifer are highly correlated to the dam’s dynamic. Groundwater maps, high and low-water dam, show a flow that moves towards the threshold of El Haouareb to the discharge of the waters of Ain El Beidha discharge towards the plain of Kairouan. Software FEFLOW 5.2 steady hydrodynamic modeling to simulate the hydraulic threshold at the level of the dam El Haouareb in a satisfactory manner. However, the sensitivity study to the different parameters shows equivalence problems and a fix to calibrate the limestones’ permeability. This work could be improved by refining the timing steady and amending the representation of limestones in the model.

Keywords: Hydrodynamic modeling, lithological modeling, hydraulic, semi-arid, merguellil, central Tunisia

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Authors: Maryam Ghoreishi, Christian Larsen

Abstract:

In this paper, we investigate the effect of stochastic inputs on problem of joint optimal pricing and lot-sizing decisions where the inventory cycle is divided into advance and spot sales periods. During the advance sales period, customer can make reservations while customer with reservations can cancel their order. However, during the spot sales period customers receive the order as soon as the order is placed, but they cannot make any reservation or cancellation during that period. We assume that the inter arrival times during the advance sales and spot sales period are exponentially distributed where the arrival rate is decreasing function of price. Moreover, we assume that the number of cancelled reservations is binomially distributed. In addition, we assume that deterioration process follows an exponential distribution. We investigate two cases. First, we consider two-state case where we find the optimal price during the spot sales period and the optimal price during the advance sales period. Next, we develop a generalized case where we extend two-state case also to allow dynamic prices during the spot sales period. We apply the Markov decision theory in order to find the optimal solutions. In addition, for the generalized case, we apply the policy iteration algorithm in order to find the optimal prices, the optimal lot-size and maximum advance sales amount.

Keywords: inventory control, pricing, Markov decision theory, advance sales system

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Authors: Erez Yerushalmi, Sani Ziv

Abstract:

The rising demand for healthcare services, without a corresponding rise in public supply, led to a debate on whether to increase private healthcare provision - especially in hospital services and second-tier healthcare. Proponents for increasing private healthcare highlight gains in efficiency, while opponents its risk to social welfare. None, however, provide a measure of the social value and its impact on the economy in terms of a monetary value. In this paper, we impute a minimum social value of public healthcare that corresponds to indifference between gains in efficiency, with losses to social welfare. Our approach resembles contingent valuation methods that introduce a hypothetical market for non-commodities, but is different from them because we use numerical simulation techniques to exploit certain market failure conditions. In this paper, we develop a general equilibrium model that distinguishes between public-private healthcare services and public-private financing. Furthermore, the social value is modelled as a by product of healthcare services. The model is then calibrated to our unique health focused Social Accounting Matrix of Israel, and simulates the introduction of a hypothetical health-labour market - given that it is heavily regulated in the baseline (i.e., the true situation in Israel today). For baseline parameters, we estimate the minimum social value at around 18% public healthcare financing. The intuition is that the gain in economic welfare from improved efficiency, is offset by the loss in social welfare due to a reduction in available social value. We furthermore simulate a deregulated healthcare scenario that internalizes the imputed value of social value and searches for the optimal weight of public and private healthcare provision.

Keywords: contingent valuation method (CVM), general equilibrium model, hypothetical market, private-public healthcare, social value of public healthcare

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Authors: Brian Marsh

Abstract:

Nitrogen fertilizer is the most used and often the most mismanaged nutrient input. Nitrogen management has tremendous implications on crop productivity, quality and environmental stewardship. Sufficient nitrogen is needed to optimum yield and quality. Soil and in-season plant tissue testing for nitrogen status are a time consuming and expensive process. Real time sensing of plant nitrogen status can be a useful tool in managing nitrogen inputs. The objectives of this project were to assess the reliability of remotely sensed non-destructive plant nitrogen measurements compared to wet chemistry data from sampled plant tissue, develop in-season nitrogen recommendations based on remotely sensed data for improved nitrogen use efficiency and assess the potential for determining yield and quality from remotely sensed data. Very good correlations were observed between early-season remotely sensed crop nitrogen status and plant nitrogen concentrations and subsequent in-season fertilizer recommendations. The transmittance/absorbance type meters gave the most accurate readings. Early in-season fertilizer recommendation would be to apply 40 kg nitrogen per hectare plus 16 kg nitrogen per hectare for each unit difference measured with the SPAD meter between the crop and reference area or 25 kg plus 13 kg per hectare for each unit difference measured with the CCM 200. Once the crop was sufficiently fertilized meter readings became inconclusive and were of no benefit for determining nitrogen status, silage yield and quality and grain yield and protein.

Keywords: wheat, nitrogen fertilization, chlorophyll meter

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Authors: Tigist Girma Kidane, Yalew Dessalegn Asfaw

Abstract:

Abstract: The current investigation aims to measure the longitudinal and transversal three-point bending tests of bamboo fibres polypropylene composites (BFPPCs) for the application of the automobile industry. Research has not been done on the properties of Ethiopian bamboo fibres for the utilization of composite development. The samples of bamboo plants have been harvested in 3–groups of age, 2–harvesting seasons, and 3–regions of bamboo species. Roll milling machine used for the extraction of bamboo fibres which has been developed by the authors. Chemical constituents measured using gravimetric methods. Unidirectional bamboo fibres prepreg has been produced using PP and hot press machine, then BFPPCs were produced using 6 layers of prepregs at automatic hot press machine. Age, harvesting month, and bamboo species have a statistically significant effect on the longitudinal and transverse flexural strength (FS), modulus of elasticity (MOE), and failure strain at α = 0.05 as evaluated by one-way ANOVA. 2–yrs old of BFPPCs have the highest FS and MOE, whereas November has the highest value of flexural properties. The highest to the lowest FS and MOE of BFPPCs has measured in Injibara, Mekaneselam, and Kombolcha, respectively. The transverse 3-point bending test has a lower FS and MOE compared to the longitudinal direction. The chemical constituents of Injibara, Mekaneselam, and Kombolcha have the highest to the lowest, respectively. 2-years old of bamboo fibres has the highest chemical constituent. The chemical constituents improved the flexural properties. Bamboo fibres in Ethiopia can be relevant for composite development, which has been applied in the area of requiring higher flexural properties.

Keywords: age, bamboo species, flexural properties, harvesting season, polypropylene

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