Search results for: conventionally manufacturing techniques

Authors: J. A. López, J. E. Olguín, C. W. Camargo, G. A. Quijano, R. Martínez

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This paper presents an anthropometric study conducted to 300 employees in a maquiladora industry that belongs to the cluster of medical products as part of a research project to pretend simulate workplace conditions under which operators conduct their activities. This project is relevant because traditionally performed a study to design ergonomic workspaces according to anthropometric profile of users, however, this paper demonstrates the importance of making decisions when the infrastructure cannot be adapted for economic whichever put emphasis on user activity.

Keywords: anthropometry, biomechanics, design, ergonomics, productivity

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Authors: Fatemeh Nokhodchi Bonab

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Bioinformatics, in its broad sense, involves application of computer processes to solve biological problems. A wide range of computational tools are needed to effectively and efficiently process large amounts of data being generated as a result of recent technological innovations in biology and medicine. A number of computational tools have been developed or adapted to deal with the experimental riches of complex and multivariate data and transition from data collection to information or knowledge. These bioinformatics tools are being evaluated and applied in various medical areas including early detection, risk assessment, classification, and prognosis of cancer. The goal of these efforts is to develop and identify bioinformatics methods with optimal sensitivity, specificity, and predictive capabilities. The recent flood of data from genome sequences and functional genomics has given rise to new field, bioinformatics, which combines elements of biology and computer science. Bioinformatics is conceptualizing biology in terms of macromolecules (in the sense of physical-chemistry) and then applying "informatics" techniques (derived from disciplines such as applied maths, computer science, and statistics) to understand and organize the information associated with these molecules, on a large-scale. Here we propose a definition for this new field and review some of the research that is being pursued, particularly in relation to transcriptional regulatory systems.

Keywords: methods, applications, transcriptional regulatory systems, techniques

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Authors: Julie Furst-Bowe

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Over the past decade, there has been significant growth in online courses and programs at all levels of education in the United States. This study explores the growth of online and blended (or hybrid) programs offered by the sixteen technical colleges in the Wisconsin Technical College System (WTCS). The WTCS provides education and training programs to more than 300,000 students each year in career clusters including agriculture, business, energy, information technology, healthcare, human services, manufacturing, and transportation. These programs range from short-term training programs that may lead to a certificate to two-year programs that lead to an associate degree. Students vary in age from high school students who are exploring career interests to employees who are seeking to gain additional skills or enter a new career. Because there is currently a shortage of skilled workers in nearly all sectors in the state of Wisconsin, it is critical that the WTCS is providing fully educated and trained graduates to fill workforce needs in a timely manner. For this study, information on online and blended programs for the past five years was collected from the WTCS, including types of programs, course and program enrollments, course completion rates, program completion rates, time to completion and graduate employment rates. The results of this study indicate that the number of online and blended courses and programs is continuing to increase each year. Online and blended programs are most commonly found in the business, human services, and information technology areas, and they are less commonly found in agriculture, healthcare, manufacturing, and transportation programs. Overall, course and program completion rates were higher for blended programs when compared to fully online programs. Students preferred the blended programs over the fully online programs. Overall, graduates were placed into related jobs at a rate of approximately 90 percent, although there was some variation in graduate placement rates by programs and by colleges. Differences in graduate employment rate appeared to be based on geography and sector as employers did not distinguish between graduates who had completed their programs via traditional, blended or fully online instruction. Recommendations include further exploration as to the reasons that blended courses and programs appear to be more effective than fully online courses and programs. It is also recommended that those program areas that are not using blended or online delivery methods, including agriculture, health, manufacturing and transportation, explore the use of these methods to make their courses and programs more accessible to students, particularly working adults. In some instances, colleges were partnering with specific companies to ensure that groups of employees were completing online coursework leading to a certificate or a degree. Those partnerships are to be encouraged in order for the state to continue to improve the skills of its workforce. Finally, it is recommended that specific colleges specialize in the delivery of specific programs using online technology since it is not bound by geographic considerations. This approach would take advantage of the strengths of the individual colleges and avoid unnecessary duplication.

Keywords: career and technical education, online learning, skills shortage, technical colleges

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Authors: Hussein Alahmer, Amr Ahmed

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Liver cancer is one of the common diseases that cause the death. Early detection is important to diagnose and reduce the incidence of death. Improvements in medical imaging and image processing techniques have significantly enhanced interpretation of medical images. Computer-Aided Diagnosis (CAD) systems based on these techniques play a vital role in the early detection of liver disease and hence reduce liver cancer death rate.  This paper presents an automated CAD system consists of three stages; firstly, automatic liver segmentation and lesion’s detection. Secondly, extracting features. Finally, classifying liver lesions into benign and malignant by using the novel contrasting feature-difference approach. Several types of intensity, texture features are extracted from both; the lesion area and its surrounding normal liver tissue. The difference between the features of both areas is then used as the new lesion descriptors. Machine learning classifiers are then trained on the new descriptors to automatically classify liver lesions into benign or malignant. The experimental results show promising improvements. Moreover, the proposed approach can overcome the problems of varying ranges of intensity and textures between patients, demographics, and imaging devices and settings.

Keywords: CAD system, difference of feature, fuzzy c means, lesion detection, liver segmentation

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Authors: Mohammad Namazi, Mohammad Sadeghzadeh Maharluie

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Predicting earnings management is vital for the capital market participants, financial analysts and managers. The aim of this research is attempting to respond to this query: Is there a significant difference between the regression model and neural networks’ models in predicting earnings management, and which one leads to a superior prediction of it? In approaching this question, a Linear Regression (LR) model was compared with two neural networks including Multi-Layer Perceptron (MLP), and Generalized Regression Neural Network (GRNN). The population of this study includes 94 listed companies in Tehran Stock Exchange (TSE) market from 2003 to 2011. After the results of all models were acquired, ANOVA was exerted to test the hypotheses. In general, the summary of statistical results showed that the precision of GRNN did not exhibit a significant difference in comparison with MLP. In addition, the mean square error of the MLP and GRNN showed a significant difference with the multi variable LR model. These findings support the notion of nonlinear behavior of the earnings management. Therefore, it is more appropriate for capital market participants to analyze earnings management based upon neural networks techniques, and not to adopt linear regression models.

Keywords: earnings management, generalized linear regression, neural networks multi-layer perceptron, Tehran stock exchange

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Authors: Manasi Mahanty

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In the current phase of globalization, the mobility of capital facilitates outsourcing and subcontracting of production processes to the developing economies for cheap and flexible labour force. In such process, the globalization of production networks operates at multi-locational points within the nation. Under the new quota regime in the globalization period, the Indian manufacturing exporters came under the influence of corporate buyers and large retailers from the importing countries. As part of such process, the garment manufacturing sector is expected to create huge employment opportunities and to expand the export market in the country. While following these, expectations, the apparel and garment industries mostly target to hire female migrant workers with a purpose of establishing more flexible industrial relations through the casual nature of employment contract. It leads to an increasing women’s participation in the labour market as well as the rise in precarious forms of female paid employment. In the context, the main objective of the paper is to understand the wider dynamics of globalization of production and its link with informalization, feminization of labour force and internal migration process of the country. For this purpose, the study examines the changing labour relations in the KINFRA Apparel Park at Kerala’s Special Economic Zone which operates under the scheme ‘Apparel Parks for Export’ (APE) of the Government of India. The present study was based on both quantitative and qualitative analysis. In the first, the secondary sources of data were collected from the source location (SEAM centre) and destination (KINFRA Park). The official figures and data were discussed and analyzed in order to find out the various dimensions of labour relations under globalization of production. In the second, the primary survey was conducted to make a comparative analysis of local and migrant female workers. The study is executed by taking 100 workers in total. The local workers comprised of 53% of the sample whereas the outside state workers were 47%. Even personal interviews with management staff, and workers were also made for collecting the information regarding the organisational structure, nature, and mode of recruitment, work environment, etc. The study shows the enormous presence of rural women migrant workers in KINFRA Apparel Park. A Public Private Partnership (PPP) arranged migration system is found as Skills for Employment in Apparel Manufacturing (SEAM) from where young women and girls are being sent to work in garment factories of Kerala’s KINFRA International Apparel Park under the guise of an apprenticeship based recruitment. The study concludes that such arrangements try to avoid standard employment relationships and strengthen informalization, casualization and contractualization of work. In this process, the recruitment of women migrant workers is to be considered as best option for the employers of private industries which could be more easily hired and fired.

Keywords: female migration, globalization, informalization, KINFRA apparel park

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Authors: Thein Thein, Kalyar Myo San

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Lip reading system is one of the different supportive technologies for hearing impaired, or elderly people or non-native speakers. For normal hearing persons in noisy environments or in conditions where the audio signal is not available, lip reading techniques can be used to increase their understanding of spoken language. Hearing impaired persons have used lip reading techniques as important tools to find out what was said by other people without hearing voice. Thus, visual speech information is important and become active research area. Using visual information from lip movements can improve the accuracy and robustness of a speech recognition system and the need for lip reading system is ever increasing for every language. However, the recognition of lip movement is a difficult task because of the region of interest (ROI) is nonlinear and noisy. Therefore, this paper proposes method to detect the accurate lips shape and to localize lip movement towards automatic lip tracking by using the combination of Otsu global thresholding technique and Moore Neighborhood Tracing Algorithm. Proposed method shows how accurate lip localization and tracking which is useful for speech recognition. In this work of study and experiments will be carried out the automatic lip localizing the lip shape for Myanmar consonants using the only visual information from lip movements which is useful for visual speech of Myanmar languages.

Keywords: lip reading, lip localization, lip tracking, Moore neighborhood tracing algorithm

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Authors: Rahul Paul, Kedar Nath Das

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The field of machine learning (ML) is experiencing rapid development, resulting in a multitude of theoretical advancements and extensive practical implementations across various disciplines. The objective of ML is to facilitate the ability of machines to perform cognitive tasks by leveraging knowledge gained from prior experiences and effectively addressing complex problems, even in situations that deviate from previously encountered instances. Reinforcement Learning (RL) has emerged as a prominent subfield within ML and has gained considerable attention in recent times from researchers. This surge in interest can be attributed to the practical applications of RL, the increasing availability of data, and the rapid advancements in computing power. At the same time, optimization algorithms play a pivotal role in the field of ML and have attracted considerable interest from researchers. A multitude of proposals have been put forth to address optimization problems or improve optimization techniques within the domain of ML. The necessity of a thorough examination and implementation of optimization algorithms within the context of ML is of utmost importance in order to provide guidance for the advancement of research in both optimization and ML. This article provides a comprehensive overview of the application of metaheuristic evolutionary optimization algorithms in conjunction with RL to address a diverse range of scientific challenges. Furthermore, this article delves into the various challenges and unresolved issues pertaining to the optimization of RL models.

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

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Authors: Andrea Ghermandi

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Constructed wetlands have long been recognized as sources of ancillary benefits such as support for recreational activities. To date, there is a lack of quantitative understanding of the extent and welfare impact of such benefits. Here, it is shown how geotagged, passively crowdsourced data from online social networks (e.g., Flickr and Panoramio) and Geographic Information Systems (GIS) techniques can: (1) be used to infer annual recreational visits to 273 engineered wetlands worldwide; and (2) be integrated with non-market economic valuation techniques (e.g., travel cost method) to infer the monetary value of recreation in these systems. Counts of social media photo-user-days are highly correlated with the number of observed visits in 62 engineered wetlands worldwide (Pearson’s r = 0.811; p-value < 0.001). The estimated, mean willingness to pay for access to 115 wetlands ranges between $5.3 and $374. In 50% of the investigated wetlands providing polishing treatment to advanced municipal wastewater, the present value of such benefits exceeds that of the capital, operation and maintenance costs (lifetime = 45 years; discount rate = 6%), indicating that such systems are sources of net societal benefits even before factoring in benefits derived from water quality improvement and storage. Based on the above results, it is argued that recreational benefits should be taken into account in the design and management of constructed wetlands, as well as when such green infrastructure systems are compared with conventional wastewater treatment solutions.

Keywords: constructed wetlands, cultural ecosystem services, ecological engineering, social media

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Authors: Hager Elsheikh

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Context: Pancreatitis is a condition characterized by inflammation in the pancreas, which can lead to serious complications if untreated. Both acute and chronic pancreatitis are associated with immune reactions and fibrosis, which further damage the pancreas. The type 2 immune response, primarily driven by alternative activated macrophages (AAMs), plays a significant role in the development of fibrosis. The IL-4/STAT6 pathway is a crucial signaling pathway for the activation of M2 macrophages. Pancreatic fibrosis is induced by dysregulated inflammatory responses and can result in the autodigestion and necrosis of pancreatic acinar cells. Research Aim: The aim of this study is to investigate the impact of STAT6, a crucial molecule in the IL-4/STAT6 pathway, on the severity and development of fibrosis during acute and chronic pancreatitis. The research also aims to understand the influence of the JAK/STAT6 signaling pathway on the balance between fibrosis and regeneration in the presence of different macrophage populations. Methodology: The research utilizes murine models of acute and chronic pancreatitis induced by cerulean injection. Animal models will be employed to study the effect of STAT6 knockout on disease severity and fibrosis. Isolation of acinar cells and cell culture techniques will be used to assess the impact of different macrophage populations on wound healing and regeneration. Various techniques such as PCR, histology, immunofluorescence, and transcriptomics will be employed to analyze the tissues and cells. Findings: The research aims to provide insights into the mechanisms underlying tissue fibrosis and wound healing during acute and chronic pancreatitis. By investigating the influence of the JAK/STAT6 signaling pathway and different macrophage populations, the study aims to understand their impact on tissue fibrosis, disease severity, and pancreatic regeneration. Theoretical Importance: This research contributes to our understanding of the role of specific signaling pathways, macrophage polarization, and the type 2 immune response in pancreatitis. It provides insights into the molecular mechanisms underlying tissue fibrosis and the potential for targeted therapies. Data Collection and Analysis Procedures: Data will be collected through the use of murine models, isolation and culture of acinar cells, and various experimental techniques such as PCR, histology, immunofluorescence, and transcriptomics. Data will be analyzed using appropriate statistical methods and techniques, and the findings will be interpreted in the context of the research objectives. Conclusion: By investigating the mechanisms of tissue fibrosis and wound healing during acute and chronic pancreatitis, this research aims to enhance our understanding of the disease progression and potential therapeutic targets. The findings have theoretical importance in expanding our knowledge of pancreatic fibrosis and the role of macrophage polarization in the context of the type 2 immune response.

Keywords: immunity in chronic diseases, pancreatitis, macrophages, immune response

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Authors: Ajay Mandal, Jitendar Kumar Tiwari, N. Sathish, A. K. Srivastava

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A fundamental investigation is performed on the development of graphene (Gr) reinforced stainless steel 316L (SS 316L) metal matrix composite via selective laser melting (SLM) in order to improve specific strength and wear resistance property of SS 316L. Firstly, SS 316L powder and graphene were mixed in a fixed ratio using low energy planetary ball milling. The milled powder is then subjected to the SLM process to fabricate composite samples at a laser power of 320 W and exposure time of 100 µs. The prepared composite was mechanically tested (hardness and tensile test) at ambient temperature, and obtained results indicate that the properties of the composite increased significantly with the addition of 0.2 wt. % Gr. Increment of about 25% (from 194 to 242 HV) and 70% (from 502 to 850 MPa) is obtained in hardness and yield strength of composite, respectively. Raman mapping and XRD were performed to see the distribution of Gr in the matrix and its effect on the formation of carbide, respectively. Results of Raman mapping show the uniform distribution of graphene inside the matrix. Electron back scatter diffraction (EBSD) map of the prepared composite was analyzed under FESEM in order to understand the microstructure and grain orientation. Due to thermal gradient, elongated grains were observed along the building direction, and grains get finer with the addition of Gr. Most of the mechanical components are subjected to several types of wear conditions. Therefore, it is very necessary to improve the wear property of the component, and hence apart from strength and hardness, a tribological property of composite was also measured under dry sliding condition. Solid lubrication property of Gr plays an important role during the sliding process due to which the wear rate of composite reduces up to 58%. Also, the surface roughness of worn surface reduces up to 70% as measured by 3D surface profilometry. Finally, it can be concluded that SLM is an efficient method of fabricating cutting edge metal matrix nano-composite having Gr like reinforcement, which was very difficult to fabricate through conventional manufacturing techniques. Prepared composite has superior mechanical and tribological properties and can be used for a wide variety of engineering applications. However, due to the unavailability of a considerable amount of literature in a similar domain, more experimental works need to perform, such as thermal property analysis, and is a part of ongoing study.

Keywords: selective laser melting, graphene, composite, mechanical property, tribological property

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Authors: Negar Ganjouhaghighi, Amirali Dolatshahi

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The origin of most risks of a mega project usually takes place in the phases before closing the contract. As a practical point of view, using project risk management techniques for preparing a proposal is not a total solution for managing the risks of a contract. The objective of this paper is to cover all those activities associated with risk management of a mega project sale’s processes; from entrance to a new market to awarding activities and the review of contract performance. In this study, the risk management happens in six consecutive steps that are divided into three distinct but interdependent phases upstream of the award of the contract: pre-tendering, tendering and closing. In the first step, by preparing standard market risk report, risks of the new market are identified. The next step is the bid or no bid decision making based on the previous gathered data. During the next three steps in tendering phase, project risk management techniques are applied for determining how much contingency reserve must be added or reduced to the estimated cost in order to put the residual risk to an acceptable level. Finally, the last step which happens in closing phase would be an overview of the project risks and final clarification of residual risks. The sales experience of more than 20,000 MW turn-key power plant projects alongside this framework, are used to develop a software that assists the sales team to have a better project risk management.

Keywords: project marketing, risk management, tendering, project management, turn-key projects

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Authors: K. Marciniak, M. Owoc

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Managers as decision-makers present in different sectors should be supported in efficient and more and more sophisticated way. There are huge number of software tools developed for such users starting from simple registering data from business area – typical for operational level of management – up to intelligent techniques with delivering knowledge - for tactical and strategic levels of management. There is a big challenge for software developers to create intelligent management dashboards allowing to support different decisions. In more advanced solutions there is even an option for selection of intelligent techniques useful for managers in particular decision-making phase in order to deliver valid knowledge-base. Such a tool (called Intelligent Dashboard for SME Managers–InKOM) is prepared in the Business Intelligent framework of Teta products. The aim of the paper is to present solutions assumed for InKOM concerning on management of stored knowledge bases offering for business managers. The paper is managed as follows. After short introduction concerning research context the discussed supporting managers via information systems the InKOM platform is presented. In the crucial part of paper a process of knowledge transformation and validation is demonstrated. We will focus on potential and real ways of knowledge-bases acquiring, storing and validation. It allows for formulation conclusions interesting from knowledge engineering point of view.

Keywords: business intelligence, decision support systems, knowledge management, knowledge transformation, knowledge validation, managerial systems

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Authors: Osama Abdallah Mohammed Enan, Amin Babiker A/Nabi Mustafa

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The aim of this study is to evaluate and analyze different parameters of WCDMA (wideband code division multiplication). Moreover, this study also incorporates brief yet throughout analysis of WCDMA’s components as well as its internal architecture. This study also examines different power controls. These power controls may include open loop power control, closed or inner group loop power control and outer loop power control. Different handover techniques or methods of WCDMA are also illustrated in this study. These handovers may include hard handover, inter system handover and soft and softer handover. Different duplexing techniques are also described in the paper. This study has also presented an idea about different parameters of WCDMA that leads the system towards QoS issues. This may help the operator in designing and developing adequate network configuration. In addition to this, the study has also investigated various parameters including Bit Energy per Noise Spectral Density (Eb/No), Noise rise, and Bit Error Rate (BER). After simulating these parameters, using MATLAB environment, it was investigated that, for a given Eb/No value the system capacity increase by increasing the reuse factor. Besides that, it was also analyzed that, noise rise is decreasing for lower data rates and for lower interference levels. Finally, it was examined that, BER increase by using one type of modulation technique than using other type of modulation technique.

Keywords: duplexing, handover, loop power control, WCDMA

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Authors: Hasan Dalgic, Fikret Akinerdem

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This trial was made to determine effect of different plant density and weed control on yield and quality of winter sowing safflower (Carthamus tinctorius L.) in Selcuk University, Agricultural Faculty trial fields and the effective substance of Trifluran was used as herbicide. Field trial was made during the vegetation period of 2009-2010 with three replications according to 'Split Plots in Randomized Blocks' design. The weed control techniques were made on main plots and row distances was set up on sub-plots. The trial subjects were consisting from three weed control techniques as fallowing: herbicide application (Trifluran), hoeing and control beside the row distances of 15 cm and 30 cm. The results were ranged between 59.0-76.73 cm in plant height, 40.00-47.07 cm in first branch height, 5.00-7.20 in number of branch per plant, 6.00-14.73 number of head per plant, 19.57-21.87 mm in head diameter, 2125.0-3968.3 kg ha-1 in seed yield, 27.10-28.08 % in crude oil rate and 531.7-1070.3 kg ha-1. According to the results, Remzibey safflower cultivar showed the highest seed yield on 30 cm of row distance and herbicide application by means of the direct effects of plant height, first branch height, number of branch per plant, number of head per plant, table diameter, crude oil rate and crude oil yield.

Keywords: safflower, herbicide, row spacing, seed yield, oil ratio, oil yield

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Authors: Rujia Chen, Ajit Narayanan

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Convolutional neural networks (CNN), as typically applied in deep learning, use layer-wise backpropagation (BP) to construct filters and kernels for feature extraction. Such filters are 2D or 3D groups of weights for constructing feature maps at subsequent layers of the CNN and are shared across the entire input. BP as a gradient descent algorithm has well-known problems of getting stuck at local optima. The use of genetic algorithms (GAs) for evolving weights between layers of standard artificial neural networks (ANNs) is a well-established area of neuroevolution. In particular, the use of crossover techniques when optimizing weights can help to overcome problems of local optima. However, the application of GAs for evolving the weights of filters and kernels in CNNs is not yet an established area of neuroevolution. In this paper, a GA-based filter development algorithm is proposed. The results of the proof-of-concept experiments described in this paper show the proposed GA algorithm can find filter weights through evolutionary techniques rather than BP learning. For some simple classification tasks like geometric shape recognition, the proposed algorithm can achieve 100% accuracy. The results for MNIST classification, while not as good as possible through standard filter learning through BP, show that filter and kernel evolution warrants further investigation as a new subarea of neuroevolution for deep architectures.

Keywords: neuroevolution, convolutional neural network, genetic algorithm, filters, kernels

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Authors: Malik Imtiaz Ahmad

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The development of In Vitro Fertilization (IVF) has revolutionized the field of reproductive medicine, offering hope to myriad individuals and couples facing infertility issues. IVF, a process involving the fertilization of eggs with sperm outside the body, has evolved over decades from an experimental procedure to a mainstream medical practice. The study sought to understand the evolution of IVF from its early stages to its present status as a groundbreaking fertility treatment. It also aimed to analyze the legal complexities surrounding IVF, including issues like embryo ownership, surrogacy agreements, and custody disputes. This research focused on the multidisciplinary approach involving both medical and legal fields. It aimed to explore the historical evolution of IVF, its techniques, and legal challenges concerning family law, health law, and privacy policies it has given rise to in modern times. This research aimed to provide insights into the intersection of medical technology and the law, offering valuable knowledge for policymakers, legal experts, and individuals involved in IVF. The study utilized various methods, including a thorough literature review, a historical analysis of IVF’s evolution, an examination of legal cases, and a review of emerging regulations. These approaches aimed to provide a comprehensive understanding of IVF and its modern legal issues, facilitating a holistic exploration of the subject matter.

Keywords: in vitro fertilization development, IVF techniques evolution, legal issues in IVF, IVF legal frameworks, ethical dilemmas in IVF

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Authors: Purba Biswas, Priyanka Dey

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Worldwide rapid urbanisation has accelerated city expansion in both developed and developing nations. This unprecedented urbanisation trend due to the increasing population and economic growth has caused challenges for the decision-makers in city planning and urban management. Metropolitan cities, class-I towns, and major urban centres undergo a continuous process of evolution due to interaction between socio-cultural and economic attributes. This constant evolution leads to urban expansion in all directions. Understanding the patterns and dynamics of urban built-up growth is crucial for policymakers, urban planners, and researchers, as it aids in resource management, decision-making, and the development of sustainable strategies to address the complexities associated with rapid urbanisation. Identifying spatio-temporal patterns of urban growth has emerged as a crucial challenge in monitoring and assessing present and future trends in urban development. Analysing urban growth patterns and tracking changes in land use is an important aspect of urban studies. This study analyses spatio-temporal urban transformations and land-use and land cover changes using remote sensing and GIS techniques. Built-up growth analysis has been done for the city of Surat as a case example, using the GIS tools of NDBI and GIS models of the Built-up Urban Density Index and Shannon Entropy Index to identify trends and the geographical direction of transformation from 2005 to 2020. Surat is one of the fastest-growing urban centres in both the state and the nation, ranking as the 4th fastest-growing city globally. This study analyses the dynamics of urban built-up area transformations both zone-wise and geographical direction-wise, in which their trend, rate, and magnitude were calculated for the period of 15 years. This study also highlights the need for analysing and monitoring the urban growth pattern of class-I cities in India using spatio-temporal and quantitative techniques like GIS for improved urban management.

Keywords: urban expansion, built-up, geographic information system, remote sensing, Shannon’s entropy

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Authors: Yuan-Hsiang Chang, Pin-Chi Lin, Li-Der Jeng

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Advance in techniques of image and video processing has enabled the development of intelligent video surveillance systems. This study was aimed to automatically detect moving human objects and to analyze events of dual human interaction in a surveillance scene. Our system was developed in four major steps: image preprocessing, human object detection, human object tracking, and motion trajectory analysis. The adaptive background subtraction and image processing techniques were used to detect and track moving human objects. To solve the occlusion problem during the interaction, the Kalman filter was used to retain a complete trajectory for each human object. Finally, the motion trajectory analysis was developed to distinguish between the interaction and non-interaction events based on derivatives of trajectories related to the speed of the moving objects. Using a database of 60 video sequences, our system could achieve the classification accuracy of 80% in interaction events and 95% in non-interaction events, respectively. In summary, we have explored the idea to investigate a system for the automatic classification of events for interaction and non-interaction events using surveillance cameras. Ultimately, this system could be incorporated in an intelligent surveillance system for the detection and/or classification of abnormal or criminal events (e.g., theft, snatch, fighting, etc.).

Keywords: motion detection, motion tracking, trajectory analysis, video surveillance

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Authors: Abdoulaye Diop, Nahid Emad, Thierry Winter, Mohamed Hilia

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Data assets protection is a crucial issue in the cybersecurity field. Companies use logical access control tools to vault their information assets and protect them against external threats, but they lack solutions to counter insider threats. Nowadays, insider threats are the most significant concern of security analysts. They are mainly individuals with legitimate access to companies information systems, which use their rights with malicious intents. In several fields, behavior anomaly detection is the method used by cyber specialists to counter the threats of user malicious activities effectively. In this paper, we present the step toward the construction of a user and entity behavior analysis framework by proposing a behavior anomaly detection model. This model combines machine learning classification techniques and graph-based methods, relying on linear algebra and parallel computing techniques. We show the utility of an ensemble learning approach in this context. We present some detection methods tests results on an representative access control dataset. The use of some explored classifiers gives results up to 99% of accuracy.

Keywords: cybersecurity, data protection, access control, insider threat, user behavior analysis, ensemble learning, high performance computing

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Authors: M. A. Ashour

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As it is known Egypt is one of the countries having oldest sugarcane industry, which goes back to the year 710 AD. Cane plantations are the main agricultural product in five governorates in Upper Egypt (El-Menia, Sohag, Qena, Luxor, and Aswan), producing not less than 16 million tons a year. Eight factories (Abou-korkas, Gena, Nagaa-Hamadi, Deshna, Kous, Armant, Edfuo, and Komombo), located in such upper Egypt governorates generates huge amount of wastes during the manufacturing stage, the so called bagasse which is the fibrous, and cellulosic materials remaining after the era of the sugarcane and the juice extraction, presents about 30% of such wastes. The amount of bagasse generated yearly through the manufacturing stage of the above mentioned 8 factories is approximately about 2.8 million tons, getting red safely of such huge amount, presents a serious environmental problem. Storage of that material openly in the so hot climate in upper Egypt, may cause its self-ignition under air temperature reaches 50 degrees centigrade in summer, due to the remained residual content of sugar. At the same time preparing places for safely storage for such amount is very expensive with respect to the valueless of it. So the best way for getting rid of bagasse is converting it into an added value environmentally friendly material, especially till now the utilization of it is so limited. Since oil pollution became a serious concern, the issue of environmental cleaning arises. With the structure of sugarcane bagasse, which contains fiber and high content of carbon, it can be an adsorbent to adsorb the oil contamination from the water. The present study is a trail to introduce a new material for the purification of water systems to score two goals at once, the first is getting rid of that harmful waste safely, the second is converting it to a commercial valuable material for cleaning, and purifying the water from oil spills, and petroleum pollution. Introduced the new material proved very good performance, and higher efficiency than other similar materials available in the local market, in both closed and open systems. The introduced modified material can absorb 10 times its weight of oil, while don't absorb any water.

Keywords: environment, water resources, agricultural wastes, oil pollution control, sugarcane

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Authors: Gajendra Kumar Mourya, Dinesh Bhatia, Akash Handique, Sunita Warjri, Syed Achaab Amir

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Nowadays, Medical imaging has become an integral part of modern healthcare. Abdominal CT images are an invaluable mean for abdominal organ investigation and have been widely studied in the recent years. Diagnosis of liver pathologies is one of the major areas of current interests in the field of medical image processing and is still an open problem. To deeply study and diagnose the liver, segmentation of liver is done to identify which part of the liver is mostly affected. Manual segmentation of the liver in CT images is time-consuming and suffers from inter- and intra-observer differences. However, automatic or semi-automatic computer aided segmentation of the Liver is a challenging task due to inter-patient Liver shape and size variability. In this paper, we present a technique for automatic segmenting the liver from CT images using Random Forest Classifier. Random forests or random decision forests are an ensemble learning method for classification that operate by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes of the individual trees. After comparing with various other techniques, it was found that Random Forest Classifier provide a better segmentation results with respect to accuracy and speed. We have done the validation of our results using various techniques and it shows above 89% accuracy in all the cases.

Keywords: CT images, image validation, random forest, segmentation

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Authors: Mohammad Saber Eslamlou, Manouchehr Tabibian, Mahta Mirmoghtadaei

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The history of urban development and the increasing complexities of urban life have long been intertwined with different natural and man-made disasters. Sometimes, these unpleasant events have destroyed the cities forever. The growth of the urban population and the increase of social and economic resources in the cities increased the importance of developing a holistic approach to dealing with unknown urban disasters. As a result, the interest in resilience has increased in most of the scientific fields, and the urban planning literature has been enriched with the studies of the social, economic, infrastructural, and physical abilities of the cities. In this regard, different conceptual frameworks and patterns have been developed focusing on dimensions of resilience and different kinds of disasters. As the most frequent and likely natural disaster in Iran is flooding, the present study aims to develop a cause-effect model of urban resilience against flood in Karaj City. In this theoretical study, desk research and documentary studies were used to find the elements and dimensions of urban resilience. In this regard, 6 dimensions and 32 elements were found for urban resilience and a questionnaire was made by considering the requirements of TOPSIS techniques (pairwise comparison). The sample of the research consisted of 10 participants who were faculty members, academicians, board members of research centers, managers of the Ministry of Road and Urban Development, board members of New Towns Development Company, experts, and practitioners of consulting companies who had scientific and research backgrounds. The gathered data in this survey were analyzed using TOPSIS and Shannon Entropy techniques. The results show that Infrastructure/Physical, Social, Organizational/ Institutional, Structural/Physical, Economic, and Environmental dimensions are the most effective factors in urban resilience against floods in Karaj, respectively. Finally, a comprehensive model and a systematic framework of factors that affect the urban resilience of Karaj against floods was developed. This cause – effect model shows how different factors are related and influence each other, based on their connected structure and preferences.

Keywords: urban resilience, TOPSIS, Shannon entropy, cause-effect model of resilience, flood

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Authors: F. Benkaci-Ali, R. Mékaoui, G. Scholl, G. Eppe

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The new methods as accelerated steam distillation assisted by microwave (ASDAM) is a combination of microwave heating and steam distillation, performed at atmospheric pressure at very short extraction time. Isolation and concentration of volatile compounds are performed by a single stage. (ASDAM) has been compared with (ASDAM) with cryogrinding of seeds (CG) and a conventional technique, hydrodistillation assisted by microwave (HDAM), hydro-distillation (HD) for the extraction of essential oil from aromatic herb as caraway and cumin seeds. The essential oils extracted by (ASDAM) for 1 min were quantitatively (yield) and qualitatively (aromatic profile) no similar to those obtained by ASDAM-CG (1 min) and HD (for 3 h). The accelerated microwave extraction with cryogrinding inhibits numerous enzymatic reactions as hydrolysis of oils. Microwave radiations constitute the adequate mean for the extraction operations from the yields and high content in major component majority point view, and allow to minimise considerably the energy consumption, but especially heating time too, which is one of essential parameters of artifacts formation. The ASDAM and ASDAM-CG are green techniques and yields an essential oil with higher amounts of more valuable oxygenated compounds comparable to the biosynthesis compounds, and allows substantial savings of costs, in terms of time, energy and plant material.

Keywords: microwave, steam distillation, caraway, cumin, cryogrinding, GC-MS, GCxGC-MS

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Authors: Maryam Rasool, Farhan Munir, Fahad Nawaz, Saad Ahmad

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A patch antenna operating in the Ultra-Wide Band of frequency (3.1 GHz – 10.6 GHz) is designed with enhanced security from interference from other applications by incorporating the notching technique. Patch antennas in the Ultra-Wide Band are becoming widely famous due to their low power, light weight and high data rate capability. Micro strip patch antenna’s patch can be altered to increase its bandwidth and introduce UWB character in it. The designed antenna is a patch antenna consisting of a conductive sheet of metal mounted over a large sheet of metal called the ground plane with a substrate separating the two. Notched bands are public safety WLAN, WLAN and FSS. Different techniques used to implement the UWB antenna were individually implemented and there results were examined. V shaped patch was then chosen and modified to an arrow shaped patch to give the optimized results operating on the entire UWB region with considerable return loss. The frequency notch prevents the operation of the antenna at a particular range of frequency, hence minimizing interference from other systems. There are countless techniques for introducing the notch but we have used inverted C-shaped slots in the UWB patch to get the notch characteristics as output and also wavelength resonators to introduce notch in UWB band. The designed antenna is simulated in High Frequency Structural Simulator (HFSS) 13.0 by Ansoft.

Keywords: HFSS, Notch, UWB, WLAN

Procedia PDF Downloads 404

Authors: Manaranjan Pradhan, Shailaja Grover, U. Dinesh Kumar

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Farming community in India, as well as other parts of the world, is one of the highly stressed communities due to reasons such as increasing input costs (cost of seeds, fertilizers, pesticide), droughts, reduced revenue leading to farmer suicides. Lack of integrated farm advisory system in India adds to the farmers problems. Farmers need right information during the early stages of crop’s lifecycle to prevent damage and loss in revenue. In this paper, we use deep learning techniques to develop an early warning system for detection of crop diseases using images taken by farmers using their smart phone. The research work leads to building a smart assistant using analytics and big data which could help the farmers with early diagnosis of the crop diseases and corrective actions. The classical approach for crop disease management has been to identify diseases at crop level. Recently, ImageNet Classification using the convolutional neural network (CNN) has been successfully used to identify diseases at individual plant level. Our model uses convolution filters, max pooling, dense layers and dropouts (to avoid overfitting). The models are built for binary classification (healthy or not healthy) and multi class classification (identifying which disease). Transfer learning is used to modify the weights of parameters learnt through ImageNet dataset and apply them on crop diseases, which reduces number of epochs to learn. One shot learning is used to learn from very few images, while data augmentation techniques are used to improve accuracy with images taken from farms by using techniques such as rotation, zoom, shift and blurred images. Models built using combination of these techniques are more robust for deploying in the real world. Our model is validated using tomato crop. In India, tomato is affected by 10 different diseases. Our model achieves an accuracy of more than 95% in correctly classifying the diseases. The main contribution of our research is to create a personal assistant for farmers for managing plant disease, although the model was validated using tomato crop, it can be easily extended to other crops. The advancement of technology in computing and availability of large data has made possible the success of deep learning applications in computer vision, natural language processing, image recognition, etc. With these robust models and huge smartphone penetration, feasibility of implementation of these models is high resulting in timely advise to the farmers and thus increasing the farmers' income and reducing the input costs.

Keywords: analytics in agriculture, CNN, crop disease detection, data augmentation, image recognition, one shot learning, transfer learning

Procedia PDF Downloads 106

Authors: Bhim Kumar Dahal

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Transportation network development in the developing country is in rapid pace. The majority of the network belongs to railway and expressway which passes through diverse topography, landform and geological conditions despite the avoidance principle during route selection. Construction of such networks demand many low to high embankment which required improvement in the foundation soil. This paper is mainly focused on the various advanced ground improvement techniques used to improve the soft soil, modelling approach and its predictability for embankments construction. The ground improvement techniques can be broadly classified in to three groups i.e. densification group, drainage and consolidation group and reinforcement group which are discussed with some case studies.  Various methods were used in modelling of the embankments from simple 1-dimensional to complex 3-dimensional model using variety of constitutive models. However, the reliability of the predictions is not found systematically improved with the level of sophistication.  And sometimes the predictions are deviated more than 60% to the monitored value besides using same level of erudition. This deviation is found mainly due to the selection of constitutive model, assumptions made during different stages, deviation in the selection of model parameters and simplification during physical modelling of the ground condition. This deviation can be reduced by using optimization process, optimization tools and sensitivity analysis of the model parameters which will guide to select the appropriate model parameters.

Keywords: cement, improvement, physical properties, strength

Procedia PDF Downloads 161

Authors: Nihal Atif Salim

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To improve the quality of life in cities, a variety of interventions are used. Noise is a substantial and important sort of pollution that has a negative impact on the urban environment and human health. According to the complaint survey, it ranks second among environmental contamination complaints (conducted by EEAA in 2019). The most significant source of noise in the city is traffic noise. In order to improve the sound urban environment, many physical techniques are applied. In the local area, noise barriers are considered as one of the most appropriate physical techniques along existing traffic routes. Alexandria is Egypt's second-largest city after Cairo. It is located along the Mediterranean Sea, and El- Gish Road is one of the city's main arteries. It impacts the waterfront promenade that extends along with the city by a high level of traffic noise. The purpose of this paper is to clarify the design considerations for the most appropriate noise barrier type along with the promenade, with the goal of improving the Quality of Life (QOL) and the sonic urban environment specifically. The proposed methodology focuses on how noise affects human perception and the environment. Then it delves into the various physical noise control approaches. After that, the paper discusses sustainable design decisions making. Finally, look into the importance of incorporating sustainability into design decisions making. Three stages will be followed in the case study. The first stage involves doing a site inspection and using specific sound measurement equipment (a noise level meter) to measure the noise level along the promenade at many sites, and the findings will be shown on a noise map. The second step is to inquire about the site's user experience. The third step is to investigate the various types of noise barriers and their effects on QOL along existing routes in order to select the most appropriate type. The goal of this research is to evaluate the suitable design of noise barriers that fulfill environmental and social perceptions while maintaining a balanced approach to the noise issue in order to improve QOL along existing roadways in the local area.

Keywords: noise pollution, sonic urban environment, traffic noise, noise barrier, acoustic sustainability, noise reduction techniques

Procedia PDF Downloads 128

Authors: Mochamad Nuruz Zaman, Mangatur Rudolf Nababan, M. A. Djatmika

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Both society and education areas teach to have good communication for building the interpersonal skills up. Everyone has the capacity to understand something new, either well comprehension or worst understanding. Worst understanding makes the language errors when the interactions are done by someone in the first meeting, and they do not know before it because of distance area. “The Space between Us” movie delivers the love-adventure story between Mars Boy and Earth Girl. They are so many missing conversations because of the different climate and environment. As the moviegoer also must be focused on the subtitle in order to enjoy well the movie. Furthermore, Indonesia subtitle and English conversation on the movie still have overlapping understanding in the translation. Translation hereby consists of source language -SL- (English conversation) and target language -TL- (Indonesia subtitle). These research gap above is formulated in research question by how the language errors happened in that movie and their effects on translation quality which is deepest analyzed by translation study toward discourse analysis approach. The research goal is to expand the language errors and their translation qualities in order to create a good atmosphere in movie media. The research is studied by embedded research in qualitative design. The research locations consist of setting, participant, and event as focused determined boundary. Sources of datum are “The Space between Us” movie and informant (translation quality rater). The sampling is criterion-based sampling (purposive sampling). Data collection techniques use content analysis and questioner. Data validation applies data source and method triangulation. Data analysis delivers domain, taxonomy, componential, and cultural theme analysis. Data findings on the language errors happened in the movie are referential, register, society, textual, receptive, expressive, individual, group, analogical, transfer, local, and global errors. Data discussions on their effects to translation quality are concentrated by translation techniques on their data findings; they are amplification, borrowing, description, discursive creation, established equivalent, generalization, literal, modulation, particularization, reduction, substitution, and transposition.

Keywords: discourse analysis, language errors, The Space between Us movie, translation techniques, translation quality instruments

Procedia PDF Downloads 203

Authors: J. Satya Eswari, J. Sekhar Babub, Meena Murmu, Govardhan Bhat

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Electrical Discharge Machining (EDM) is an unconventional manufacturing process based on removal of material from a part by means of a series of repeated electrical sparks created by electric pulse generators at short intervals between a electrode tool and the part to be machined emmersed in dielectric fluid. In this paper, a study will be performed on the influence of the factors of peak current, pulse on time, interval time and power supply voltage. The output responses measured were material removal rate (MRR) and surface roughness. Finally, the parameters were optimized for maximum MRR with the desired surface roughness. RSM involves establishing mathematical relations between the design variables and the resulting responses and optimizing the process conditions. RSM is not free from problems when it is applied to multi-factor and multi-response situations. Design of experiments (DOE) technique to select the optimum machining conditions for machining AISI 4140 using EDM. The purpose of this paper is to determine the optimal factors of the electro-discharge machining (EDM) process investigate feasibility of design of experiment techniques. The work pieces used were rectangular plates of AISI 4140 grade steel alloy. The study of optimized settings of key machining factors like pulse on time, gap voltage, flushing pressure, input current and duty cycle on the material removal, surface roughness is been carried out using central composite design. The objective is to maximize the Material removal rate (MRR). Central composite design data is used to develop second order polynomial models with interaction terms. The insignificant coefficients’ are eliminated with these models by using student t test and F test for the goodness of fit. CCD is first used to establish the determine the optimal factors of the electro-discharge machining (EDM) for maximizing the MRR. The responses are further treated through a objective function to establish the same set of key machining factors to satisfy the optimization problem of the electro-discharge machining (EDM) process. The results demonstrate the better performance of CCD data based RSM for optimizing the electro-discharge machining (EDM) process.

Keywords: electric discharge machining (EDM), modeling, optimization, CCRD

Procedia PDF Downloads 329