Search results for: sustainable supply chain performance
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 18916

Search results for: sustainable supply chain performance

4966 Impact of Implementation of 5S and TPM in Industrial Organizations: A Review

Authors: Jamal Ahmed Hama Kareem, Noraini Abu Talib

Abstract:

The purpose of this paper is to explore the literature on 5S and Total Productive Maintenance (TPM) and the benefits that are to be derived from their implementation. It also seeks to highlight the main phases for implementing both the 5S and the TPM successfully, along with highlighting aspects that are needed for successful implementation of these two techniques simultaneously in the contemporary manufacturing scenario. The literature on classification of 5S and TPM has so far been very limited. The paper reviews a large number of papers in this field and presents the overview of several of implementation practices of 5S and TPM, and the benefits that can be achieved by the implementation of 5S and TPM as a one system by industrial organizations globally. The paper systematically categorizes the published literature and reveals important issues that influence the successful implementation of 5S and TPM in organizations to improve production effectiveness for competitiveness. Further, the paper also highlights various phases suggested by researchers and practitioners, which ensure smooth and effective implementation of the 5S and TPM in industrial organizations. In the end, study puts forth propositions based on the model of the study after extensive review of literature. The paper will be useful to researchers, maintenance professionals and other concerned officials with improving the performance of production processes effectiveness in industrial organizations.

Keywords: 5S, Total Productive Maintenance (TPM), phases of implementation of 5S and TPM, industrial organizations

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4965 The Emancipation of the Inland Areas Between Depopulation, Smart Community and Living Labs: A Case Study of Sardinia

Authors: Daniela Pisu

Abstract:

The paper deals with the issue of territorial inequalities focused on the gap of the marginalization of inland areas with respect to the centrality of urban centers as they are subjected to an almost unstoppable demographic hemorrhage in a context marked by the tendency to depopulation such as the Sardinian territory, to which are added further and intense phenomena of de-anthropization. The research question is aimed at exploring the functionality of the interventions envisaged by the Piano Nazionale Ripresa Resilienza for the reduction of territorial imbalances in these areas to the extent that it is possible to identify policy strategies aimed at increasing the relational expertise of citizenship, functional to the consolidation of results in a long-term perspective. In order to answer this question, the qualitative case study on the Municipality of Ulàssai (province of Nuoro) is highlighted as the only winner on the island, with the Pilot Project ‘Where nature meets art’, intended for the cultural and social regeneration of small towns. The main findings, which emerged from the analysis of institutional sources and secondary data, highlight the socio-demographic fragility of the territory in the face of the active institutional commitment to make Ulàssai a smart community, starting from the enhancement of natural resources and the artistic heritage of fellow citizen Maria Lai. The findings drawn from the inspections and focus groups with the youth population present the aforementioned project as a generative opportunity for both the economic and social fabric, leveraging the public debates of the living labs, where the process of public communication becomes the main vector for the exercise of the rights of participatory democracy. The qualitative lunge leads to the conclusion that the repercussions envisaged by the PNRR in internal areas will be able to show their self-sustainable effect through colloquial administrations such as that of Ulàssai, capable of seeing in the interactive paradigm of public communication that natural process with which to reduce that historical sense of extraneousness attributed to the institution-citizenship relationship.

Keywords: social labs, smart community, depopulation, Sardinia, Piano Nazionale di Ripresa e Resilienza

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4964 Protein Remote Homology Detection by Using Profile-Based Matrix Transformation Approaches

Authors: Bin Liu

Abstract:

As one of the most important tasks in protein sequence analysis, protein remote homology detection has been studied for decades. Currently, the profile-based methods show state-of-the-art performance. Position-Specific Frequency Matrix (PSFM) is widely used profile. However, there exists noise information in the profiles introduced by the amino acids with low frequencies. In this study, we propose a method to remove the noise information in the PSFM by removing the amino acids with low frequencies called Top frequency profile (TFP). Three new matrix transformation methods, including Autocross covariance (ACC) transformation, Tri-gram, and K-separated bigram (KSB), are performed on these profiles to convert them into fixed length feature vectors. Combined with Support Vector Machines (SVMs), the predictors are constructed. Evaluated on two benchmark datasets, and experimental results show that these proposed methods outperform other state-of-the-art predictors.

Keywords: protein remote homology detection, protein fold recognition, top frequency profile, support vector machines

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4963 Surface Geodesic Derivative Pattern for Deformable Textured 3D Object Comparison: Application to Expression and Pose Invariant 3D Face Recognition

Authors: Farshid Hajati, Soheila Gheisari, Ali Cheraghian, Yongsheng Gao

Abstract:

This paper presents a new Surface Geodesic Derivative Pattern (SGDP) for matching textured deformable 3D surfaces. SGDP encodes micro-pattern features based on local surface higher-order derivative variation. It extracts local information by encoding various distinctive textural relationships contained in a geodesic neighborhood, hence fusing texture and range information of a surface at the data level. Geodesic texture rings are encoded into local patterns for similarity measurement between non-rigid 3D surfaces. The performance of the proposed method is evaluated extensively on the Bosphorus and FRGC v2 face databases. Compared to existing benchmarks, experimental results show the effectiveness and superiority of combining the texture and 3D shape data at the earliest level in recognizing typical deformable faces under expression, illumination, and pose variations.

Keywords: 3D face recognition, pose, expression, surface matching, texture

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4962 LES Investigation of the Natural Vortex Length in a Small-Scale Gas Cyclone

Authors: Dzmitry Misiulia, Sergiy Antonyuk

Abstract:

Small-scale cyclone separators are widely used in aerosol sampling. The flow field in a cyclone sampler is very complex, especially the vortex behavior. Most of the existing models for calculating cyclone efficiency use the same stable vortex structure while the vortex demonstrates dynamic variations rather than the steady-state picture. It can spontaneously ‘end’ at some point within the body of the separator. Natural vortex length is one of the most critical issues when designing and operating gas cyclones and is crucial to proper cyclone performance. The particle transport along the wall to the grid pot is not effective beyond this point. The flow field and vortex behavior inside the aerosol sampler have been investigated for a wide range of Reynolds numbers using Large Eddy Simulations. Two characteristics types of vortex behavior have been found with simulations. At low flow rates the vortex created in the cyclone dissipates in free space (without attaching to a surface) while at higher flow rates it attaches to the cyclone wall. The effects of the Reynolds number on the natural vortex length and the rotation frequency of the end of the vortex have been revealed.

Keywords: cyclone, flow field, natural vortex length, pressure drop

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4961 Modeling and Energy Analysis of Limestone Decomposition with Microwave Heating

Authors: Sofia N. Gonçalves, Duarte M. S. Albuquerque, José C. F. Pereira

Abstract:

The energy transition is spurred by structural changes in energy demand, supply, and prices. Microwave technology was first proposed as a faster alternative for cooking food. It was found that food heated instantly when interacting with high-frequency electromagnetic waves. The dielectric properties account for a material’s ability to absorb electromagnetic energy and dissipate this energy in the form of heat. Many energy-intense industries could benefit from electromagnetic heating since many of the raw materials are dielectric at high temperatures. Limestone sedimentary rock is a dielectric material intensively used in the cement industry to produce unslaked lime. A numerical 3D model was implemented in COMSOL Multiphysics to study the limestone continuous processing under microwave heating. The model solves the two-way coupling between the Energy equation and Maxwell’s equations as well as the coupling between heat transfer and chemical interfaces. Complementary, a controller was implemented to optimize the overall heating efficiency and control the numerical model stability. This was done by continuously matching the cavity impedance and predicting the required energy for the system, avoiding energy inefficiencies. This controller was developed in MATLAB and successfully fulfilled all these goals. The limestone load influence on thermal decomposition and overall process efficiency was the main object of this study. The procedure considered the Verification and Validation of the chemical kinetics model separately from the coupled model. The chemical model was found to correctly describe the chosen kinetic equation, and the coupled model successfully solved the equations describing the numerical model. The interaction between flow of material and electric field Poynting vector revealed to influence limestone decomposition, as a result from the low dielectric properties of limestone. The numerical model considered this effect and took advantage from this interaction. The model was demonstrated to be highly unstable when solving non-linear temperature distributions. Limestone has a dielectric loss response that increases with temperature and has low thermal conductivity. For this reason, limestone is prone to produce thermal runaway under electromagnetic heating, as well as numerical model instabilities. Five different scenarios were tested by considering a material fill ratio of 30%, 50%, 65%, 80%, and 100%. Simulating the tube rotation for mixing enhancement was proven to be beneficial and crucial for all loads considered. When uniform temperature distribution is accomplished, the electromagnetic field and material interaction is facilitated. The results pointed out the inefficient development of the electric field within the bed for 30% fill ratio. The thermal efficiency showed the propensity to stabilize around 90%for loads higher than 50%. The process accomplished a maximum microwave efficiency of 75% for the 80% fill ratio, sustaining that the tube has an optimal fill of material. Electric field peak detachment was observed for the case with 100% fill ratio, justifying the lower efficiencies compared to 80%. Microwave technology has been demonstrated to be an important ally for the decarbonization of the cement industry.

Keywords: CFD numerical simulations, efficiency optimization, electromagnetic heating, impedance matching, limestone continuous processing

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4960 The Consumers' Attitudes in Front of Organizations' Environmental Management

Authors: Vera Lucia da S. Ventura, Valmir Alves Ventura, Marcelo E. Fernandes, Marcelo T. Okano, Osmildo S. Santos, Heide Landi

Abstract:

The paper aims to present the attitude of consumers regarding the environmental practices adopted by Brazilian organizations. It is understood organizations adopt practices about environment is essential, as their internal processes as external actions, the corporative and social changes are considered in this scene. It is observed consumers are important, therefore, more and more they analyze the responsible performance of Brazilian organizations. It was performed a quantitative research through questionnaire for achieving the objectives of this study. The sample was composed by 336 people at capacity consumption fully. The survey results demonstrate environmental management can be an excellent tool for conquering consumers, because consumers realize the great responsibility assumed by organizations regarding to the environment, nowadays. This finding was possible because most of the respondents answered the environmentally responsible behavior of organizations is decisive factor at the purchase’s moment. However, the data revealed consumers do not realize the practices adopted by companies. This lack of awareness may prejudice environmentally responsible organizations’ worth by consumers.

Keywords: environmental management, sustainability, conscious consumption, Brazilian organizations

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4959 Organizing Diabetes Care in a Resource Constrained Country: Bangladesh as an Example

Authors: Liaquat Ali, Khurshid Natasha

Abstract:

Low resource countries are not usually equipped with the organizational tools to implement health care for chronic diseases, and thus, providing effective diabetes care in such countries is a challenging task. Diabetic Association of Bangladesh (BADAS in Bengali acronym) has created a stimulating example to meet this challenge. Starting its journey in 1956 with 39 patients in a small tin shed clinic BADAS, and its affiliated associations now operate 90 hospitals and health centres all over the country. Together, these facilities provide integrated health care to about 1.5 million registered diabetic patients which constitute about 20% of the estimated diabetic population in the country. BADAS has also become a pioneer in health manpower generation in Bangladesh. Along with its affiliates, it now runs 3 Medical Colleges (to generate graduate physicians), 2 Nursing Institutes, and 2 Postgraduate Institutes which conduct 25 postgraduate courses (under the University of Dhaka) in various basic, clinical and public health disciplines. BADAS gives great emphasis on research, which encompasses basic, clinical as well as public health areas. BADAS is an ideal example of public-private partnership in health as most of its infrastructure has been created through government support but it is almost self-reliant in managing its revenue budget which approached approximately 40 million US dollar during 2010. BADAS raises resources by providing high-quality services to the people, both diabetic and non-diabetic. At the same time, BADAS has developed a cross financing model, to support diabetic patients in general and poor diabetic patients (identified through a social welfare network) in particular, through redistribution of the resources. Along with financial sustainability BADAS ensure organizational sustainability through a process of decentralization, community ownership, and democratic management. Presently a large scale pilot project (named as a Health Care Development Project or HCDP) is under implementation under BADAS umbrella with an objective to transform the diabetes care model to a health care model in general. It is expected to create further evidence on providing sustainable (with social safety net) health care delivery for diabetes, and other chronic illnesses as an integral part of general health care delivery in a resource constrained setting.

Keywords: Bangladesh, self sustain, health care, constrain

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4958 Semi-Supervised Learning for Spanish Speech Recognition Using Deep Neural Networks

Authors: B. R. Campomanes-Alvarez, P. Quiros, B. Fernandez

Abstract:

Automatic Speech Recognition (ASR) is a machine-based process of decoding and transcribing oral speech. A typical ASR system receives acoustic input from a speaker or an audio file, analyzes it using algorithms, and produces an output in the form of a text. Some speech recognition systems use Hidden Markov Models (HMMs) to deal with the temporal variability of speech and Gaussian Mixture Models (GMMs) to determine how well each state of each HMM fits a short window of frames of coefficients that represents the acoustic input. Another way to evaluate the fit is to use a feed-forward neural network that takes several frames of coefficients as input and produces posterior probabilities over HMM states as output. Deep neural networks (DNNs) that have many hidden layers and are trained using new methods have been shown to outperform GMMs on a variety of speech recognition systems. Acoustic models for state-of-the-art ASR systems are usually training on massive amounts of data. However, audio files with their corresponding transcriptions can be difficult to obtain, especially in the Spanish language. Hence, in the case of these low-resource scenarios, building an ASR model is considered as a complex task due to the lack of labeled data, resulting in an under-trained system. Semi-supervised learning approaches arise as necessary tasks given the high cost of transcribing audio data. The main goal of this proposal is to develop a procedure based on acoustic semi-supervised learning for Spanish ASR systems by using DNNs. This semi-supervised learning approach consists of: (a) Training a seed ASR model with a DNN using a set of audios and their respective transcriptions. A DNN with a one-hidden-layer network was initialized; increasing the number of hidden layers in training, to a five. A refinement, which consisted of the weight matrix plus bias term and a Stochastic Gradient Descent (SGD) training were also performed. The objective function was the cross-entropy criterion. (b) Decoding/testing a set of unlabeled data with the obtained seed model. (c) Selecting a suitable subset of the validated data to retrain the seed model, thereby improving its performance on the target test set. To choose the most precise transcriptions, three confidence scores or metrics, regarding the lattice concept (based on the graph cost, the acoustic cost and a combination of both), was performed as selection technique. The performance of the ASR system will be calculated by means of the Word Error Rate (WER). The test dataset was renewed in order to extract the new transcriptions added to the training dataset. Some experiments were carried out in order to select the best ASR results. A comparison between a GMM-based model without retraining and the DNN proposed system was also made under the same conditions. Results showed that the semi-supervised ASR-model based on DNNs outperformed the GMM-model, in terms of WER, in all tested cases. The best result obtained an improvement of 6% relative WER. Hence, these promising results suggest that the proposed technique could be suitable for building ASR models in low-resource environments.

Keywords: automatic speech recognition, deep neural networks, machine learning, semi-supervised learning

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4957 Understanding and Addressing the Tuberculosis Notification Gap in Nepal

Authors: Lok Raj Joshi, Naveen Prakash Shah, Sharad Kumar Sharma, I. Ratna Bhattarai, Rajendra Basnet, Deepak Dahal, Bahagwan Maharjan, Seraphine Kaminsa

Abstract:

Context: Tuberculosis (TB) is a significant health issue in Nepal, a country with a high burden of the disease. Despite efforts to control TB, there is still a gap in the notification of TB cases, which hinders effective control and treatment. This paper aims to address this notification gap and proposes strategies to improve TB control in Nepal. Research Aim: The aim of this research is to understand and address the tuberculosis notification gap in Nepal. The focus is on enhancing the healthcare system, involving the private sector and communities, raising awareness, and addressing social determinants to achieve sustainable TB control. Methodology: The research methodology involved a review of existing epidemiological data and research studies related to TB in Nepal. Additionally, consultation with an expert group from the TB control program in Nepal provided insights into the current state of TB control and challenges in addressing the notification gap. Findings: The findings reveal that only 55% of TB cases were reported in 2022, indicating a significant notification gap. Of the reported cases, only 32% and 19% were referred by the private sector and community, respectively. Furthermore, 20% of diagnosed cases were not treated in the initial phase. The estimated number of cases of multidrug-resistant TB (MDR TB) was 2,800, suggesting a low diagnosis rate. Among the diagnosed MDR TB cases, only 60% were receiving treatment. Additionally, it was observed that 20% of diagnosed MDR TB cases were from India and not enrolling in TB treatment in Nepal, indicating a high rate of defaulters. Theoretical Importance: The study highlights the importance of adopting a holistic strategy to address the notification gap in TB cases in Nepal. It emphasizes the need to enhance healthcare infrastructure, raise awareness, involve the private sector and local communities, establish effective methods to trace initial defaulters, implement TB interventions in border regions, and mitigate the social stigma associated with the disease. Data Collection and Analysis Procedures: Data for this study was collected through a review of existing epidemiological data and research studies. The data were then analyzed to identify patterns, trends, and gaps in TB case notification in Nepal.

Keywords: TB, tuberculosis, private sector, community, migrants, nepal

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4956 Closing the Gap: Efficient Voxelization with Equidistant Scanlines and Gap Detection

Authors: S. Delgado, C. Cerrada, R. S. Gómez

Abstract:

This research introduces an approach to voxelizing the surfaces of triangular meshes with efficiency and accuracy. Our method leverages parallel equidistant scan-lines and introduces a Gap Detection technique to address the limitations of existing approaches. We present a comprehensive study showcasing the method's effectiveness, scalability, and versatility in different scenarios. Voxelization is a fundamental process in computer graphics and simulations, playing a pivotal role in applications ranging from scientific visualization to virtual reality. Our algorithm focuses on enhancing the voxelization process, especially for complex models and high resolutions. One of the major challenges in voxelization in the Graphics Processing Unit (GPU) is the high cost of discovering the same voxels multiple times. These repeated voxels incur in costly memory operations with no useful information. Our scan-line-based method ensures that each voxel is detected exactly once when processing the triangle, enhancing performance without compromising the quality of the voxelization. The heart of our approach lies in the use of parallel, equidistant scan-lines to traverse the interiors of triangles. This minimizes redundant memory operations and avoids revisiting the same voxels, resulting in a significant performance boost. Moreover, our method's computational efficiency is complemented by its simplicity and portability. Written as a single compute shader in Graphics Library Shader Language (GLSL), it is highly adaptable to various rendering pipelines and hardware configurations. To validate our method, we conducted extensive experiments on a diverse set of models from the Stanford repository. Our results demonstrate not only the algorithm's efficiency, but also its ability to produce 26 tunnel free accurate voxelizations. The Gap Detection technique successfully identifies and addresses gaps, ensuring consistent and visually pleasing voxelized surfaces. Furthermore, we introduce the Slope Consistency Value metric, quantifying the alignment of each triangle with its primary axis. This metric provides insights into the impact of triangle orientation on scan-line based voxelization methods. It also aids in understanding how the Gap Detection technique effectively improves results by targeting specific areas where simple scan-line-based methods might fail. Our research contributes to the field of voxelization by offering a robust and efficient approach that overcomes the limitations of existing methods. The Gap Detection technique fills a critical gap in the voxelization process. By addressing these gaps, our algorithm enhances the visual quality and accuracy of voxelized models, making it valuable for a wide range of applications. In conclusion, "Closing the Gap: Efficient Voxelization with Equidistant Scan-lines and Gap Detection" presents an effective solution to the challenges of voxelization. Our research combines computational efficiency, accuracy, and innovative techniques to elevate the quality of voxelized surfaces. With its adaptable nature and valuable innovations, this technique could have a positive influence on computer graphics and visualization.

Keywords: voxelization, GPU acceleration, computer graphics, compute shaders

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4955 Investigation of Dry-Blanching and Freezing Methods of Fruits

Authors: Epameinondas Xanthakis, Erik Kaunisto, Alain Le-Bail, Lilia Ahrné

Abstract:

Fruits and vegetables are characterized as perishable food matrices due to their short shelf life as several deterioration mechanisms are being involved. Prior to the common preservation methods like freezing or canning, fruits and vegetables are being blanched in order to inactivate deteriorative enzymes. Both conventional blanching pretreatments and conventional freezing methods hide drawbacks behind their beneficial impacts on the preservation of those matrices. Conventional blanching methods may require longer processing times, leaching of minerals and nutrients due to the contact with the warm water which in turn leads to effluent production with large BOD. An important issue of freezing technologies is the size of the formed ice crystals which is also critical for the final quality of the frozen food as it can cause irreversible damage to the cellular structure and subsequently to degrade the texture and the colour of the product. Herein, the developed microwave blanching methodology and the results regarding quality aspects and enzyme inactivation will be presented. Moreover, heat transfer phenomena, mass balance, temperature distribution, and enzyme inactivation (such as Pectin Methyl Esterase and Ascorbic Acid Oxidase) of our microwave blanching approach will be evaluated based on measurements and computer modelling. The present work is part of the COLDμWAVE project which aims to the development of an innovative environmentally sustainable process for blanching and freezing of fruits and vegetables with improved textural and nutritional quality. In this context, COLDµWAVE will develop tailored equipment for MW blanching of vegetables that has very high energy efficiency and no water consumption. Furthermore, the next steps of this project regarding the development of innovative pathways in MW assisted freezing to improve the quality of frozen vegetables, by exploring in depth previous results acquired by the authors, will be presented. The application of MW assisted freezing process on fruits and vegetables it is expected to lead to improved quality characteristics compared to the conventional freezing. Acknowledgments: COLDμWAVE has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grand agreement No 660067.

Keywords: blanching, freezing, fruits, microwave blanching, microwave

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4954 Medical Knowledge Management since the Integration of Heterogeneous Data until the Knowledge Exploitation in a Decision-Making System

Authors: Nadjat Zerf Boudjettou, Fahima Nader, Rachid Chalal

Abstract:

Knowledge management is to acquire and represent knowledge relevant to a domain, a task or a specific organization in order to facilitate access, reuse and evolution. This usually means building, maintaining and evolving an explicit representation of knowledge. The next step is to provide access to that knowledge, that is to say, the spread in order to enable effective use. Knowledge management in the medical field aims to improve the performance of the medical organization by allowing individuals in the care facility (doctors, nurses, paramedics, etc.) to capture, share and apply collective knowledge in order to make optimal decisions in real time. In this paper, we propose a knowledge management approach based on integration technique of heterogeneous data in the medical field by creating a data warehouse, a technique of extracting knowledge from medical data by choosing a technique of data mining, and finally an exploitation technique of that knowledge in a case-based reasoning system.

Keywords: data warehouse, data mining, knowledge discovery in database, KDD, medical knowledge management, Bayesian networks

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4953 Human Intelligence: A Corollary of Genotype and Habitat

Authors: Tripureshwari Paul

Abstract:

We are born with nature molded by nurture. Studies have confirmed the productive role of genes and environment on an individual. This study examines the relationship of parental genotype values on the intellectual ability of their children. Keeping in mind that academic achievement-learning capacity of student through normative education, a function of exposure to family environment and pathology with intellectual quotient of the individual. Purposive sampling was used and children between ages 11 and 12 years and their respective parents were involved. Raven’s Standard Progressive Matrices (RSPM), Family Pathology Scale (FPS) and Family Environment Scale (FES) were administered. The results found significant relationship of Offspring IQ to Parental IQ, maternal IQ demonstrating higher values of correlation. Female IQ was significant to maternal IQ and male IQ was significant to paternal IQ. With Academic Achievement not significantly correlated to IQ, it was determined that Competitive framework, freedom to expression and Recreational Orientation in family affect a child’s intellectual performance.

Keywords: academic achievement, environment, family environment, family pathology, genotype, intelligence quotient, maternal IQ, paternal IQ

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4952 Clustering Performance Analysis using New Correlation-Based Cluster Validity Indices

Authors: Nathakhun Wiroonsri

Abstract:

There are various cluster validity measures used for evaluating clustering results. One of the main objectives of using these measures is to seek the optimal unknown number of clusters. Some measures work well for clusters with different densities, sizes and shapes. Yet, one of the weaknesses that those validity measures share is that they sometimes provide only one clear optimal number of clusters. That number is actually unknown and there might be more than one potential sub-optimal option that a user may wish to choose based on different applications. We develop two new cluster validity indices based on a correlation between an actual distance between a pair of data points and a centroid distance of clusters that the two points are located in. Our proposed indices constantly yield several peaks at different numbers of clusters which overcome the weakness previously stated. Furthermore, the introduced correlation can also be used for evaluating the quality of a selected clustering result. Several experiments in different scenarios, including the well-known iris data set and a real-world marketing application, have been conducted to compare the proposed validity indices with several well-known ones.

Keywords: clustering algorithm, cluster validity measure, correlation, data partitions, iris data set, marketing, pattern recognition

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4951 Asymptotic Confidence Intervals for the Difference of Coefficients of Variation in Gamma Distributions

Authors: Patarawan Sangnawakij, Sa-Aat Niwitpong

Abstract:

In this paper, we proposed two new confidence intervals for the difference of coefficients of variation, CIw and CIs, in two independent gamma distributions. These proposed confidence intervals using the close form method of variance estimation which was presented by Donner and Zou (2010) based on concept of Wald and Score confidence interval, respectively. Monte Carlo simulation study is used to evaluate the performance, coverage probability and expected length, of these confidence intervals. The results indicate that values of coverage probabilities of the new confidence interval based on Wald and Score are satisfied the nominal coverage and close to nominal level 0.95 in various situations, particularly, the former proposed confidence interval is better when sample sizes are small. Moreover, the expected lengths of the proposed confidence intervals are nearly difference when sample sizes are moderate to large. Therefore, in this study, the confidence interval for the difference of coefficients of variation which based on Wald is preferable than the other one confidence interval.

Keywords: confidence interval, score’s interval, wald’s interval, coefficient of variation, gamma distribution, simulation study

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4950 Anomalous Behaviors of Visible Luminescence from Graphene Quantum Dots

Authors: Hyunho Shin, Jaekwang Jung, Jeongho Park, Sungwon Hwang

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For the application of graphene quantum dots (GQDs) to optoelectronic nanodevices, it is of critical importance to understand the mechanisms which result in novel phenomena of their light absorption/emission. The optical transitions are known to be available up to ~6 eV in GQDs, especially useful for ultraviolet (UV) photodetectors (PDs). Here, we present size-dependent shape/edge-state variations of GQDs and visible photoluminescence (PL) showing anomalous size dependencies. With varying the average size (da) of GQDs from 5 to 35 nm, the peak energy of the absorption spectra monotonically decreases, while that of the visible PL spectra unusually shows nonmonotonic behaviors having a minimum at diameter ∼17 nm. The PL behaviors can be attributed to the novel feature of GQDs, that is, the circular-to-polygonal-shape and corresponding edge-state variations of GQDs at diameter ∼17 nm as the GQD size increases, as demonstrated by high resolution transmission electron microscopy. We believe that such a comprehensive scheme in designing device architecture and the structural formulation of GQDs provides a device for practical realization of environmentally benign, high performance flexible devices in the future.

Keywords: graphene, quantum dot, size, photoluminescence

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4949 Efficiency Enhancement of Photovoltaic Panels Using an Optimised Air Cooled Heat Sink

Authors: Wisam K. Hussam, Ali Alfeeli, Gergory J. Sheard

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Solar panels that use photovoltaic (PV) cells are popular for converting solar radiation into electricity. One of the major problems impacting the performance of PV panels is the overheating caused by excessive solar radiation and high ambient temperatures, which degrades the efficiency of the PV panels remarkably. To overcome this issue, an aluminum heat sink was used to dissipate unwanted heat from PV cells. The dimensions of the heat sink were determined considering the optimal fin spacing that fulfils hot climatic conditions. In this study, the effects of cooling on the efficiency and power output of a PV panel were studied experimentally. Two PV modules were used: one without and one with a heat sink. The experiments ran for 11 hours from 6:00 a.m. to 5:30 p.m. where temperature readings in the rear and front of both PV modules were recorded at an interval of 15 minutes using sensors and an Arduino microprocessor. Results are recorded for both panels simultaneously for analysis, temperate comparison, and for power and efficiency calculations. A maximum increase in the solar to electrical conversion efficiency of 35% and almost 55% in the power output were achieved with the use of a heat sink, while temperatures at the front and back of the panel were reduced by 9% and 11%, respectively.

Keywords: photovoltaic cell, natural convection, heat sink, efficiency

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4948 Scalable Cloud-Based LEO Satellite Constellation Simulator

Authors: Karim Sobh, Khaled El-Ayat, Fady Morcos, Amr El-Kadi

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Distributed applications deployed on LEO satellites and ground stations require substantial communication between different members in a constellation to overcome the earth coverage barriers imposed by GEOs. Applications running on LEO constellations suffer the earth line-of-sight blockage effect. They need adequate lab testing before launching to space. We propose a scalable cloud-based net-work simulation framework to simulate problems created by the earth line-of-sight blockage. The framework utilized cloud IaaS virtual machines to simulate LEO satellites and ground stations distributed software. A factorial ANOVA statistical analysis is conducted to measure simulator overhead on overall communication performance. The results showed a very low simulator communication overhead. Consequently, the simulation framework is proposed as a candidate for testing LEO constellations with distributed software in the lab before space launch.

Keywords: LEO, cloud computing, constellation, satellite, network simulation, netfilter

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4947 Short-Term Effects of Seed Dressing With Azorhizobium Caulinodans on Establishment, Development and Yield of Early Maturing Maize ( Zea Mays L.) In Zimbabwe

Authors: Gabriel Vusanimuzi Nkomo

Abstract:

The majority of soils in communal areas of Zimbabwe are sandy and inherently infertile and sustainable cultivation is not feasible without addition of plant nutrients. Most farmers find it difficult to raise the capital required for investments in mineral fertilizer and find it cheaper to use low nutrition animal manure. An experiment was conducted to determine the effects of nitrokara biofertiliser on early growth, development and maize yield while also comparing nitrokara biofertiliser on availability of nitrogen and phosphorous in soil. The experiment was conducted at Africa University Farm. The experiment had six treatments (nitrokara +300kg/ha Compound D, nitrokara+ 300kg/ha Compound D(7N;14P;7K) + 75kg/ha Ammonium Nitrate(AN), nitrokara +300kg/ha Compound D +150kg AN, nitrokara +300kg/ha Compound D +225kg/ha AN, nitrokara +300kg/ha Compound D + 300 kg/ha AN and 0 nitrokara+300kg/ha Compound D +0 AN). Early maturing SC 403 maize (Zea mays) was inoculated with nitrokara and a compound mineral fertilizer at 300 kg/ha at planting while ammonium nitrate was applied at 45 days after planting. There were no significant differences (P > 0.05) on emergence % from 5days up to 10 days after planting using maize seed inoculated with nitrokara. Emergence percentage varied with the number of days. At 5 days the emergence % was 62% to a high of 97 % at 10 days after emergence among treatments. There were no significant differences (P > 0.05) on plant biomass on treatments 1 to 6 at 4 weeks after planting as well as at 8 weeks after planting. There were no significant differences among the treatments on the availability of nitrogen after 6 weeks (P > 0.05). However at 8 and 10 weeks after planting there were significant differences among treatments on nitrogen availability (P < 0.05). There were no significant differences among the treatments at week 6 after planting on soil pH (p > 0.05). However there were significant differences among treatments pH at weeks 9 and 12 (p < 0.05). There were significant differences among treatments on phosphorous availability at 6, 8 and 10 weeks after planting (p < 0.05). There were no significant differences among treatments on stem diameter at 3 and 6 weeks after planting (p > 0.05).However at 9 and 12 weeks after planting there were significant differences among treatments on stem diameter (p < 0.05).There were no significant differences among treatments on plant height from week 3 up to week 6 on plant height (P > 0.05).However there were significant differences among treatments at week 9 and 12 (p < 0.05). There were significant differences among treatments on days to early, 50% and 100% anthesis (P < 0.05). There were significant differences during early, 50% and 100% days to silking among the treatments (P < 0.05).Also there were significant differences during early, 50% and 100% days to silking among the treatments (P < 0.05).The study revealed that inoculation of nitrokara biofertiliser at planting with subsequent addition of ammonium nitrate has a positive effect on maize crop development and yield.

Keywords: nitrokara, biofertiliser, symbiotic, plant biomass, inoculated

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4946 Groundwater Flow Dynamics in Shallow Coastal Plain Sands Aquifer, Abesan Area, Eastern Dahomey Basin, Southwestern Nigeria

Authors: Anne Joseph, Yinusa Asiwaju-Bello, Oluwaseun Olabode

Abstract:

Sustainable administration of groundwater resources tapped in Coastal Plain Sands aquifer in Abesan area, Eastern Dahomey Basin, Southwestern Nigeria necessitates the knowledge of the pattern of groundwater flow in meeting a suitable environmental need for habitation. Thirty hand-dug wells were identified and evaluated to study the groundwater flow dynamics and anionic species distribution in the study area. Topography and water table levels method with the aid of Surfer were adopted in the identification of recharge and discharge zones where six recharge and discharge zones were delineated correspondingly. Dissolved anionic species of HCO3-, Cl-, SO42-and NO3- were determined using titrimetric and spectrophotometric method. The trend of significant anionic concentrations of groundwater samples are in the order Cl- > HCO3-> SO42- > NO3-. The prominent anions in the discharge and recharge area are Cl- and HCO3- ranging from 0.22ppm to 3.67ppm and 2.59ppm to 0.72ppm respectively. Analysis of groundwater head distribution and the groundwater flow vector in Abesan area confirmed that Cl- concentration is higher than HCO3- concentration in recharge zones. Conversely, there is a high concentration of HCO3- than Cl- inland towards the continent; therefore, HCO3-concentration in the discharge zones is higher than the Cl- concentration. The anions were to be closely related to the recharge and discharge areas which were confirmed by comparison of activities such as rainfall regime and anthropogenic activities in Abesan area. A large percentage of the samples showed that HCO3-, Cl-, SO42-and NO3- falls within the permissible limit of the W.H.O standard. Most of the samples revealed Cl- / (CO3- + HCO3-) ratio higher than 0.5 indicating that there is saltwater intrusion imprints in the groundwater of the study area. Gibbs plot shown that most of the samples is from rock dominance, some from evaporation dominance and few from precipitation dominance. Potential salinity and SO42/ Cl- ratios signifies that most of the groundwater in Abesan is saline and falls in a water class found to be insuitable for irrigation. Continuous dissolution of these anionic species may pose a significant threat to the inhabitants of Abesan area in the nearest future.

Keywords: Abessan, Anionic species, Discharge, Groundwater flow, Recharge

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4945 Three Dimensional Simulation of the Transient Modeling and Simulation of Different Gas Flows Velocity and Flow Distribution in Catalytic Converter with Porous Media

Authors: Amir Reza Radmanesh, Sina Farajzadeh Khosroshahi, Hani Sadr

Abstract:

The transient catalytic converter performance is governed by complex interactions between exhaust gas flow and the monolithic structure of the catalytic converter. Stringent emission regulations around the world necessitate the use of highly-efficient catalytic converters in vehicle exhaust systems. Computational fluid dynamics (CFD) is a powerful tool for calculating the flow field inside the catalytic converter. Radial velocity profiles, obtained by a commercial CFD code, present very good agreement with respective experimental results published in the literature. However the applicability of CFD for transient simulations is limited by the high CPU demands. In the present work, Geometric modeling ceramic monolith substrate is done with square shaped channel type of Catalytic converter and it is coated platinum and palladium. This example illustrates the effect of flow distribution on thermal response of a catalytic converter and different gas flow velocities, during the critical phase of catalytic converter warm up.

Keywords: catalytic converter, computational fluid dynamic, porous media, velocity distribution

Procedia PDF Downloads 843
4944 The Effect of Glass Thickness on Stress in Vacuum Glazing

Authors: Farid Arya, Trevor Hyde, Andrea Trevisi, Paolo Basso, Danilo Bardaro

Abstract:

Heat transfer through multiple pane windows can be reduced by creating a vacuum pressure less than 0.1 Pa between the glass panes, with low emittance coatings on one or more of the internal surfaces. Fabrication of vacuum glazing (VG) requires the formation of a hermetic seal around the periphery of the glass panes together with an array of support pillars between the panes to prevent them from touching under atmospheric pressure. Atmospheric pressure and temperature differentials induce stress which can affect the integrity of the glazing. Several parameters define the stresses in VG including the glass thickness, pillar specifications, glazing dimensions and edge seal configuration. Inherent stresses in VG can result in fractures in the glass panes and failure of the edge seal. In this study, stress in VG with different glass thicknesses is theoretically studied using Finite Element Modelling (FEM). Based on the finding in this study, suggestions are made to address problems resulting from the use of thinner glass panes in the fabrication of VG. This can lead to the development of high performance, light and thin VG.

Keywords: vacuum glazing, stress, vacuum insulation, support pillars

Procedia PDF Downloads 176
4943 Generative Adversarial Network for Bidirectional Mappings between Retinal Fundus Images and Vessel Segmented Images

Authors: Haoqi Gao, Koichi Ogawara

Abstract:

Retinal vascular segmentation of color fundus is the basis of ophthalmic computer-aided diagnosis and large-scale disease screening systems. Early screening of fundus diseases has great value for clinical medical diagnosis. The traditional methods depend on the experience of the doctor, which is time-consuming, labor-intensive, and inefficient. Furthermore, medical images are scarce and fraught with legal concerns regarding patient privacy. In this paper, we propose a new Generative Adversarial Network based on CycleGAN for retinal fundus images. This method can generate not only synthetic fundus images but also generate corresponding segmentation masks, which has certain application value and challenge in computer vision and computer graphics. In the results, we evaluate our proposed method from both quantitative and qualitative. For generated segmented images, our method achieves dice coefficient of 0.81 and PR of 0.89 on DRIVE dataset. For generated synthetic fundus images, we use ”Toy Experiment” to verify the state-of-the-art performance of our method.

Keywords: retinal vascular segmentations, generative ad-versarial network, cyclegan, fundus images

Procedia PDF Downloads 128
4942 Use of Social Media Among University Student and Its Effect on the Achievement of Students

Authors: Saba Latif

Abstract:

The use of social media among university students is a topic of ongoing debate, with conflicting views on its impact on academic achievement. This study aimed to explore the relationship between social media use and academic achievement among university students and to identify factors that may contribute to positive or negative effects. The study used a mixed-methods design, including a survey of 500 university students and qualitative interviews with a subset of participants. The survey results showed that social media use was prevalent among students, with Facebook and Instagram are the most commonly used platforms. The findings also indicated a positive relationship between social media use and academic achievement, with students who reported higher levels of social media use also reporting higher GPAs. However, the qualitative interviews revealed that excessive use of social media could be a distraction that hinders academic performance, especially when students use it to procrastinate or to stay up late at night. Overall, the findings suggest that social media use can have both positive and negative effects on academic achievement among university students. Responsible and balanced use of social media, such as setting limits on usage and avoiding procrastination, may help students maximize the benefits while minimizing the risks.

Keywords: social media, university, achievement, effective, learning

Procedia PDF Downloads 64
4941 A General Variable Neighborhood Search Algorithm to Minimize Makespan of the Distributed Permutation Flowshop Scheduling Problem

Authors: G. M. Komaki, S. Mobin, E. Teymourian, S. Sheikh

Abstract:

This paper addresses minimizing the makespan of the distributed permutation flow shop scheduling problem. In this problem, there are several parallel identical factories or flowshops each with series of similar machines. Each job should be allocated to one of the factories and all of the operations of the jobs should be performed in the allocated factory. This problem has recently gained attention and due to NP-Hard nature of the problem, metaheuristic algorithms have been proposed to tackle it. Majority of the proposed algorithms require large computational time which is the main drawback. In this study, a general variable neighborhood search algorithm (GVNS) is proposed where several time-saving schemes have been incorporated into it. Also, the GVNS uses the sophisticated method to change the shaking procedure or perturbation depending on the progress of the incumbent solution to prevent stagnation of the search. The performance of the proposed algorithm is compared to the state-of-the-art algorithms based on standard benchmark instances.

Keywords: distributed permutation flow shop, scheduling, makespan, general variable neighborhood search algorithm

Procedia PDF Downloads 343
4940 A Comparative Study on Optimized Bias Current Density Performance of Cubic ZnB-GaN with Hexagonal 4H-SiC Based Impatts

Authors: Arnab Majumdar, Srimani Sen

Abstract:

In this paper, a vivid simulated study has been made on 35 GHz Ka-band window frequency in order to judge and compare the DC and high frequency properties of cubic ZnB-GaN with the existing hexagonal 4H-SiC. A flat profile p+pnn+ DDR structure of impatt is chosen and is optimized at a particular bias current density with respect to efficiency and output power taking into consideration the effect of mobile space charge also. The simulated results obtained reveals the strong potentiality of impatts based on both cubic ZnB-GaN and hexagonal 4H-SiC. The DC-to-millimeter wave conversion efficiency for cubic ZnB-GaN impatt obtained is 50% with an estimated output power of 2.83 W at an optimized bias current density of 2.5×108 A/m2. The conversion efficiency and estimated output power in case of hexagonal 4H-SiC impatt obtained is 22.34% and 40 W respectively at an optimum bias current density of 0.06×108 A/m2.

Keywords: cubic ZnB-GaN, hexagonal 4H-SiC, double drift impatt diode, millimetre wave, optimised bias current density, wide band gap semiconductor

Procedia PDF Downloads 345
4939 Antibacterial Effects of Some Medicinal and Aromatic Plant Extracts on Pathogenic Bacteria Isolated from Pear Orchards

Authors: Kubilay Kurtulus Bastas

Abstract:

Bacterial diseases are very destructive and cause economic losses on pears. Promising plant extracts for the management of plant diseases are environmentally safe, long-lasting and extracts of certain plants contain alkaloids, tannins, quinones, coumarins, phenolic compounds, and phytoalexins. In this study, bacteria were isolated from different parts of pear exhibiting characteristic symptoms of bacterial diseases from the Central Anatolia, Turkey. Pathogenic bacteria were identified by morphological, physiological, biochemical and molecular methods as fire blight (Erwinia amylovora (39%)), bacterial blossom blast and blister bark (Pseudomonas syringae pv. syringae (22%)), crown gall (Rhizobium radiobacter (1%)) from different pear cultivars, and determined virulence levels of the pathogens with pathogenicity tests. The air-dried 25 plant material was ground into fine powder and extraction was performed at room temperature by maceration with 80% (v/v) methanol/distilled water. The minimum inhibitory concentration (MIC) values were determined by using modified disc diffusion method at five different concentrations and streptomycin sulphate was used as control chemical. Bacterial suspensions were prepared as 108 CFU ml⁻¹ densities and 100 µl bacterial suspensions were spread to TSA medium. Antimicrobial activity was evaluated by measuring the inhibition zones in reference to the test organisms. Among the tested plants, Origanum vulgare, Hedera helix, Satureja hortensis, Rhus coriaria, Eucalyptus globulus, Rosmarinus officinalis, Ocimum basilicum, Salvia officinalis, Cuminum cyminum and Thymus vulgaris showed a good antibacterial activity and they inhibited the growth of the pathogens with inhibition zone diameter ranging from 7 to 27 mm at 20% (w/v) in absolute methanol in vitro conditions. In vivo, the highest efficacy was determined as 27% on reducing tumor formation of R. radiobacter, and 48% and 41% on reducing shoot blight of E. amylovora and P. s. pv. syringae on pear seedlings, respectively. Obtaining data indicated that some plant extracts may be used against the bacterial diseases on pome fruits within sustainable and organic management programs.

Keywords: bacteria, eco-friendly management, organic, pear, plant extract

Procedia PDF Downloads 309
4938 Dynamic Effects of Energy Consumption, Economic Growth, International Trade and Urbanization on Environmental Degradation in Nigeria

Authors: Abdulkarim Yusuf

Abstract:

Motivation: A crucial but difficult goal for governments and policymakers in Nigeria in recent years has been the sustainability of economic growth. This goal must be accomplished by regulating or lowering greenhouse gas emissions, which calls for switching to a low- or zero-carbon production system. The lack of in-depth empirical studies on the environmental impact of socioeconomic variables on Nigeria and a number of unresolved issues from earlier research is what led to the current study. Objective: This study fills an important empirical gap by investigating the existence of an Environmental Kuznets Curve hypothesis and the long and short-run dynamic impact of socioeconomic variables on ecological sustainability in Nigeria. Data and method: Annual time series data covering the period 1980 to 2020 and the Autoregressive Distributed Lag technique in the presence of structural breaks were adopted for this study. Results: The empirical findings support the existence of the environmental Kuznets curve hypothesis for Nigeria in the long and short run. Energy consumption and total import exacerbate environmental deterioration in the long and short run, whereas total export improves environmental quality in the long and short run. Financial development, which contributed to a conspicuous decrease in the level of environmental destruction in the long run, escalated it in the short run. In contrast, urbanization caused a significant increase in environmental damage in the long run but motivated a decrease in biodiversity loss in the short run. Implications: The government, policymakers, and all energy stakeholders should take additional measures to ensure the implementation and diversification of energy sources to accommodate more renewable energy sources that emit less carbon in order to promote efficiency in Nigeria's production processes and lower carbon emissions. In order to promote the production and trade of environmentally friendly goods, they should also revise and strengthen environmental policies. With affordable, dependable, and sustainable energy use for higher productivity and inclusive growth, Nigeria will be able to achieve its long-term development goals of good health and wellbeing.

Keywords: economic growth, energy consumption, environmental degradation, environmental Kuznets curve, urbanization, Nigeria

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4937 Feature-Based Summarizing and Ranking from Customer Reviews

Authors: Dim En Nyaung, Thin Lai Lai Thein

Abstract:

Due to the rapid increase of Internet, web opinion sources dynamically emerge which is useful for both potential customers and product manufacturers for prediction and decision purposes. These are the user generated contents written in natural languages and are unstructured-free-texts scheme. Therefore, opinion mining techniques become popular to automatically process customer reviews for extracting product features and user opinions expressed over them. Since customer reviews may contain both opinionated and factual sentences, a supervised machine learning technique applies for subjectivity classification to improve the mining performance. In this paper, we dedicate our work is the task of opinion summarization. Therefore, product feature and opinion extraction is critical to opinion summarization, because its effectiveness significantly affects the identification of semantic relationships. The polarity and numeric score of all the features are determined by Senti-WordNet Lexicon. The problem of opinion summarization refers how to relate the opinion words with respect to a certain feature. Probabilistic based model of supervised learning will improve the result that is more flexible and effective.

Keywords: opinion mining, opinion summarization, sentiment analysis, text mining

Procedia PDF Downloads 318