Search results for: feed forward network

Authors: Mardiana Ahamad Zabidi, Akmalluddin Md. Yunus

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Soursop (Anona muricata) is one of the underutilized tropical fruits containing nutrients, particularly dietary fibre and antioxidant properties that are beneficial to human health. This objective of this study is to investigate the feasibility of matured soursop pulp flour (SPF) to be substituted with high-protein wheat flour in bread. Bread formulation was substituted with different levels of SPF (0%, 5%, 10% and 15%). The effect on physicochemical properties and sensory attributes were evaluated. Higher substitution level of SPF resulted in significantly higher (p<0.05) fibre, protein and ash content, while fat and carbohydrate content reduced significantly (p<0.05). FESEM showed that the bread crumb surface of control and 5% SPF appeared to distribute evenly and coalesced by thin gluten film. However, higher SPF substitution level in bread formulation exhibited a deleterious effect by formation of discontinuous gluten network. For texture profile analysis, 5% SPF bread resulted in the lowest value of hardness. The score of sensory evaluation showed that 5% SPF bread received good acceptability and is comparable with control bread.

Keywords: soursop pulp flour, bread, physicochemical properties, sensory attributes, scanning electron microscopy (SEM)

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Authors: Stuti Modi, Aditi Kambli

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This paper addresses the need for intelligent water management and distribution system in smart cities to ensure optimal consumption and distribution of water for drinking and sanitation purposes. Water being a limited resource in cities require an effective system for collection, storage and distribution. In this paper, applications of two mostly widely used particular types of data-driven models, namely artificial neural networks (ANN) and fuzzy logic-based models, to modelling in the water resources management field are considered. The objective of this paper is to review the principles of various types and architectures of neural network and fuzzy adaptive systems and their applications to integrated water resources management. Final goal of the review is to expose and formulate progressive direction of their applicability and further research of the AI-related and data-driven techniques application and to demonstrate applicability of the neural networks, fuzzy systems and other machine learning techniques in the practical issues of the regional water management. Apart from this the paper will deal with water storage, using ANN to find optimum reservoir level and predicting peak daily demands.

Keywords: artificial neural networks, fuzzy systems, peak daily demand prediction, water management and distribution

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Authors: Peter Palasti, Eva Kerepeczki

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Extensive fish farming is one of the most traditional forms of aquaculture in Europe, usually practiced in large pond systems with earthen beds, where the growth of fish is based on natural feed and supplementary foraging. These farms have semi-natural environmental conditions, sustaining diverse wildlife communities that have complex effects on fish production and also provide a livelihood for many wetland related taxa. Based on their characteristics, these communities could be sources of various ecosystem services (ESs), that could also enhance the value and enable the multifunctional use of these artificially constructed and maintained production zones. To identify and estimate the whole range of wildlife’s contribution we have conducted an integrated assessment in an extensively managed pond system in Biharugra, Hungary, where we studied 14 previously revealed ESs: fish and reed production, water storage, water and air quality regulation, CO2 absorption, groundwater recharge, aesthetics, recreational activities, inspiration, education, scientific research, presence of semi-natural habitats and useful/protected species. ESs were collected through structured interviews with the local experts of all major stakeholder groups, where we have also gathered information about the known forms, levels (none, low, high) and orientations (positive, negative) of the contributions of the wildlife community. After that, a quantitative analysis was carried out: we calculated the total mean value of the services being used between 2014-16, then we estimated the value and percentage of contributions. For the quantification, we mainly used biophysical indicators with the available data and empirical knowledge of the local experts. During the interviews, 12 of the previously listed services (85%) were mentioned to be related to wildlife community, consisting of 5 fully (e.g., recreation, reed production) and seven partially dependent ESs (e.g., inspiration, CO2 absorption) from our list. The orientation of the contributions was said to be positive almost every time; however, in the case of fish production, the feeding habit of some wild species (Phalacrocorax carbo, Lutra lutra) caused significant losses in fish stocks in the study period. During the biophysical assessment, we calculated the total mean value of the services and quantified the aid of wildlife community at the following services: fish and reed production, recreation, CO2 absorption, and the presence of semi-natural habitats and wild species. The combined results of our interviews and biophysical evaluations showed that the presence of wildlife community not just greatly increased the productivity of the fish farms in Biharugra (with ~53% of natural yield generated by planktonic and benthic communities) but also enhanced the multifunctionality of the system through expanding the quality and number of its services. With these abilities, extensively managed fishponds could play an important role in the future as refugia for wetland related services and species threatened by the effects of global warming.

Keywords: ecosystem services, fishpond systems, integrated assessment, wildlife community

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Authors: Lindani Mbatha, Suvendi Rimer, Mpho Gololo

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Image segmentation is the process of dividing an image into several sections, such as the object's background and the foreground. It is a critical technique in both image-processing tasks and computer vision. Most of the image segmentation algorithms have been developed for gray-scale images and little research and algorithms have been developed for the color images. Most image segmentation algorithms or techniques vary based on the input data and the application. Nearly all of the techniques are not suitable for noisy environments. Most of the work that has been done uses the Markov Random Field (MRF), which involves the computations and is said to be robust to noise. In the past recent years' image segmentation has been brought to tackle problems such as easy processing of an image, interpretation of the contents of an image, and easy analysing of an image. This article reviews and summarizes some of the image segmentation techniques and algorithms that have been developed in the past years. The techniques include neural networks (CNN), edge-based techniques, region growing, clustering, and thresholding techniques and so on. The advantages and disadvantages of medical ultrasound image segmentation techniques are also discussed. The article also addresses the applications and potential future developments that can be done around image segmentation. This review article concludes with the fact that no technique is perfectly suitable for the segmentation of all different types of images, but the use of hybrid techniques yields more accurate and efficient results.

Keywords: clustering-based, convolution-network, edge-based, region-growing

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Authors: Rahul Agarwal, Ashutosh Singh

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Cervical cancer is one of the women related cancers which starts from the pre-cancerous cells and a fraction of women with pre-cancers of the cervix will develop cervical cancer. Cervical pre-cancers if treated in pre-invasive stage can prevent almost all true cervical squamous cell carcinoma. The present study investigates the genes and pathways that are involved in the progression of cervical cancer and are responsible in transition from pre-invasive stage to other advanced invasive stages. The study used GDS3292 microarray data to identify the stage specific genes in cervical cancer and further to generate the network of the significant genes. The microarray data GDS3292 consists of the expression profiling of 10 normal cervices, 7 HSILs and 21 SCCs samples. The study identifies 70 upregulated and 37 downregulated genes in HSIL stage while 95 upregulated and 60 downregulated genes in SCC stages. Biological process including cell communication, signal transduction are highly enriched in both HSIL and SCC stages of cervical cancer. Further, the ppi interaction of genes involved in HSIL and SCC stages helps in identifying the interacting partners. This work may lead to the identification of potential diagnostic biomarker which can be utilized for early stage detection.

Keywords: cervical cancer, HSIL, microarray, SCC

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Authors: Maria Areias, Diogo Simões, Ana Figueiredo, Anishur Rahman, Filipa Figueiredo, João Nunes

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It is expected that close to 7 billion people will live in urban areas by 2050. In order to improve the sustainability of the territories and its transition towards circular economy, it’s necessary to understand its metabolism and promote and guide the entrepreneurship answer. The study of a macroeconomic metabolism involves the quantification of the inputs, outputs and storage of energy, water, materials and wastes for an urban region. This quantification and analysis representing one opportunity for the promotion of green entrepreneurship. There are several methods to assess the environmental impacts of an urban territory, such as human and environmental risk assessment (HERA), life cycle assessment (LCA), ecological footprint assessment (EF), material flow analysis (MFA), physical input-output table (PIOT), ecological network analysis (ENA), multicriteria decision analysis (MCDA) among others. However, no consensus exists about which of those assessment methods are best to analyze the sustainability of these complex systems. Taking into account the weaknesses and needs identified, the CiiM - Circular Innovation Inter-Municipality project aims to define an uniform and globally accepted methodology through the integration of various methodologies and dynamic approaches to increase the efficiency of macroeconomic metabolisms and promoting entrepreneurship in a circular economy. The pilot territory considered in CiiM project has a total area of 969,428 ha, comprising a total of 897,256 inhabitants (about 41% of the population of the Center Region). The main economic activities in the pilot territory, which contribute to a gross domestic product of 14.4 billion euros, are: social support activities for the elderly; construction of buildings; road transport of goods, retailing in supermarkets and hypermarkets; mass production of other garments; inpatient health facilities; and the manufacture of other components and accessories for motor vehicles. The region's business network is mostly constituted of micro and small companies (similar to the Central Region of Portugal), with a total of 53,708 companies identified in the CIM Region of Coimbra (39 large companies), 28,146 in the CIM Viseu Dão Lafões (22 large companies) and 24,953 in CIM Beiras and Serra da Estrela (13 large companies). For the construction of the database was taking into account data available at the National Institute of Statistics (INE), General Directorate of Energy and Geology (DGEG), Eurostat, Pordata, Strategy and Planning Office (GEP), Portuguese Environment Agency (APA), Commission for Coordination and Regional Development (CCDR) and Inter-municipal Community (CIM), as well as dedicated databases. In addition to the collection of statistical data, it was necessary to identify and characterize the different stakeholder groups in the pilot territory that are relevant to the different metabolism components under analysis. The CIIM project also adds the potential of a Geographic Information System (GIS) so that it is be possible to obtain geospatial results of the territorial metabolisms (rural and urban) of the pilot region. This platform will be a powerful visualization tool of flows of products/services that occur within the region and will support the stakeholders, improving their circular performance and identifying new business ideas and symbiotic partnerships.

Keywords: circular economy tools, life cycle assessment macroeconomic metabolism, multicriteria decision analysis, decision support tools, circular entrepreneurship, industrial and regional symbiosis

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Authors: Meet Shah, Ankita Aditya, Dhruv Bindra, V. S. Omkar, Aashruti Seervi

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In today's world, we need documents everywhere for a smooth workflow in the identification process or any other security aspects. The current system and techniques which are used for identification need one thing, that is ‘proof of existence’, which involves valid documents, for example, educational, financial, etc. The main issue with the current identity access management system and digital identification process is that the system is centralized in their network, which makes it inefficient. The paper presents the system which resolves all these cited issues. It is based on ‘blockchain’ technology, which is a 'decentralized system'. It allows transactions in a decentralized and immutable manner. The primary notion of the model is to ‘have everything with nothing’. It involves inter-linking required documents of a person with a single identity card so that a person can go anywhere without having the required documents with him/her. The person just needs to be physically present at a place wherein documents are necessary, and using a fingerprint impression and an iris scan print, the rest of the verification will progress. Furthermore, some technical overheads and advancements are listed. This paper also aims to layout its far-vision scenario of blockchain and its impact on future trends.

Keywords: blockchain, decentralized system, fingerprint impression, identity management, iris scan

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Authors: Razieh Karimi Aghcheh, Christian Kubicek, Joseph Strauss, Gerhard Braus

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Filamentous fungi are of considerable economic and social significance for human health, nutrition and in white biotechnology. These organisms are dominant producers of a range of primary metabolites such as citric acid, microbial lipids (biodiesel) and higher unsaturated fatty acids (HUFAs). In particular, they produce also important but structurally complex secondary metabolites with enormous therapeutic applications in pharmaceutical industry, for example: cephalosporin, penicillin, taxol, zeranol and ergot alkaloids. Several fungal secondary metabolites, which are significantly relevant to human health do not only include antibiotics, but also e.g. lovastatin, a well-known antihypercholesterolemic agent produced by Aspergillus. terreus, or aflatoxin, a carcinogen produced by A. flavus. In addition to their roles for human health and agriculture, some fungi are industrially and commercially important: Species of the ascomycete genus Hypocrea spp. (teleomorph of Trichoderma) have been demonstrated as efficient producer of highly active cellulolytic enzymes. This trait makes them effective in disrupting and depolymerization of lignocellulosic materials and thus applicable tools in number of biotechnological areas as diverse as clothes-washing detergent, animal feed, and pulp and fuel productions. Fungal LaeA/LAE1 (Loss of aflR Expression A) homologs their gene products act at the interphase between secondary metabolisms, cellulase production and development. Lack of the corresponding genes results in significant physiological changes including loss of secondary metabolite and lignocellulose degrading enzymes production. At the molecular level, the encoded proteins are presumably methyltransferases or demethylases which act directly or indirectly at heterochromatin and interact with velvet domain proteins. Velvet proteins bind to DNA and affect expression of secondary metabolites (SMs) genes and cellulases. The dynamic interplay between LaeA/LAE1, velvet proteins and additional interaction partners is the key for an understanding of the coordination of metabolic and morphological functions of fungi and is required for a biotechnological control of the formation of desired bioactive products. Aspergilli and Trichoderma represent different biotechnologically significant species with significant differences in the LaeA/LAE1-Velvet protein machinery and their target proteins. We, therefore, performed a comparative study of the interaction partners of this machinery and the dynamics of the various protein-protein interactions using our robust proteomic and mass spectrometry techniques. This enhances our knowledge about the fungal coordination of secondary metabolism, cellulase production and development and thereby will certainly improve recombinant fungal strain construction for the production of industrial secondary metabolite or lignocellulose hydrolytic enzymes.

Keywords: cellulases, LaeA/1, proteomics, secondary metabolites

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Authors: Mohamed Habireche, Nacer E. Bacha, Mohamed Djeghdjough

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In the brick industry, smooth double roll crusher is used for medium and fine crushing of soft to medium hard material. Due to opposite inward rotation of the rolls, the feed material is nipped between the rolls and crushed by compression. They are subject to intense wear, known as three-body abrasion, due to the action of abrasive products. The production downtime affecting productivity stems from two sources: the bi-monthly rectification of the roll crushers and their replacement when they are completely worn out. Choosing the right material for the roll crushers should result in longer machine cycles, and reduced repair and maintenance costs. All roll crushers are imported from outside Algeria. This results in sometimes very long delivery times which handicap the brickyards, in particular in respecting delivery times and honored the orders made by customers. The aim of this work is to investigate the effect of alloying additions on microstructure and wear behavior of grey lamellar cast iron for smooth roll crushers in brick industry. The base gray iron was melted in an induction furnace with low frequency at a temperature of 1500 °C, in which return cast iron scrap, new cast iron ingot, and steel scrap were added to the melt to generate the desired composition. The chemical analysis of the bar samples was carried out using Emission Spectrometer Systems PV 8050 Series (Philips) except for the carbon, for which a carbon/sulphur analyser Elementrac CS-i was used. Unetched microstructure was used to evaluate the graphite flake morphology using the image comparison measurement method. At least five different fields were selected for quantitative estimation of phase constituents. The samples were observed under X100 magnification with a Zeiss Axiover T40 MAT optical microscope equipped with a digital camera. SEM microscope equipped with EDS was used to characterize the phases present in the microstructure. The hardness (750 kg load, 5mm diameter ball) was measured with a Brinell testing machine for both treated and as-solidified condition test pieces. The test bars were used for tensile strength and metallographic evaluations. Mechanical properties were evaluated using tensile specimens made as per ASTM E8 standards. Two specimens were tested for each alloy. From each rod, a test piece was made for the tensile test. The results showed that the quenched and tempered alloys had best wear resistance at 400 °C for alloyed grey cast iron (containing 0.62%Mn, 0.68%Cr, and 1.09% Cu) due to fine carbides in the tempered matrix. In quenched and tempered condition, increasing Cu content in cast irons improved its wear resistance moderately. Combined addition of Cu and Cr increases hardness and wear resistance for a quenched and tempered hypoeutectic grey cast iron.

Keywords: casting, cast iron, microstructure, heat treating

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Authors: Shriya Shukla, Lachin Fernando

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Pneumonia, a leading cause of mortality in young children globally, presents significant diagnostic challenges, particularly in resource-limited settings. This study presents an approach to diagnosing pediatric pneumonia using Chest X-Ray (CXR) images, employing a lightweight MobileNetV2 model enhanced with synthetic data augmentation. Addressing the challenge of dataset scarcity and imbalance, the study used a Variational Autoencoder-Generative Adversarial Network (VAE-GAN) to generate synthetic CXR images, improving the representation of normal cases in the pediatric dataset. This approach not only addresses the issues of data imbalance and scarcity prevalent in medical imaging but also provides a more accessible and reliable diagnostic tool for early pneumonia detection. The augmented data improved the model’s accuracy and generalization, achieving an overall accuracy of 95% in pneumonia detection. These findings highlight the efficacy of the MobileNetV2 model, offering a computationally efficient yet robust solution well-suited for resource-constrained environments such as mobile health applications. This study demonstrates the potential of synthetic data augmentation in enhancing medical image analysis for critical conditions like pediatric pneumonia.

Keywords: pneumonia, MobileNetV2, image classification, GAN, VAE, deep learning

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Authors: Sufia Khowaja, Nishat Fatima

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Social networking sites are significant for visually impaired to overcome the unique challenges they face and access the resources they need to succeed in their education and beyond which might be difficult to obtain through traditional means. It provides them an opportunity to build relationships, stay connected with their support network as well as to develop social skills which give them emotional support to fell less isolated. In this connection the study is conducted with the aim to determine the use of social networking sites, purpose of using and activities performed by visually impaired at Delhi University, Delhi, Jawaharlal Nehru University, Delhi and Jamia Milia Islamia, Delhi. The study followed survey technique in which structured interview is followed to collect data from 137 visually impaired students and analysed using ‘SPSS ver23’. The findings of the study revealed that mostly used social networking sites are whatsapp by 89.23% students of DU, 95.12% of JNU, 87.09% of JMI, followed by e-mail by 78.46% of DU, 78.04% of JNU, 64.51%; youtube by 73.84% DU, 90.24% JNU, 80.64% JMI. Purpose for using these sites is for academics mentioned by 96.92% DU, 100% JNU, 93.54% JMI. Activities performed on sites are sending and receiving messaging 96.92% DU, 92.68% JNU, 93.55% JMI, communicating with friends and family as well as getting academic information. Findings of the study will be helpful for libraries to disseminate their services and resources as well as latest updates to their visually impaired users with the help of most used tools.

Keywords: social networking sites, visually impaired, Delhi University, Jawaharlal Nehru University, Jamia Milia Islamia

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Authors: Li Shuping, Shu Huaping, Yi Chaofan, Tao Jiang

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Equestrian practice is often considered having a unique effect on improving symptoms in children with autism. This study evaluated and measured the changes in daily behavior, morphological, physical function, and fitness indexes of two group children with autism by means of 12 weeks of equestrian and basketball exercises. 19 clinically diagnosed children with moderate/mild autism were randomly divided into equestrian group (9 children, age=10.11±1.90y) and basketball group (10 children, age=10.70±2.16y). Both the equestrian and basketball groups practiced twice a week for 45 to 60 minutes each time. Three scales, the Autism Behavior Checklist (ABC), the Childhood Autism Rating Scale (CARS) and the Clancy Autism Behavior Scale (CABS) were used to assess their human behavior and psychology. Four morphological, seven physical function and fitness indicators were measured to evaluate the effects of the two exercises on the children’s body. The evaluations were taken by every four weeks ( pre-exercise, the 4th week, the 8th week and 12th week (post exercise). The result showed that the total scores of ABC, CARS and CABS, the dimension scores of ABC on the somatic motor, language and life self-care obtained after exercise were significantly lower than those obtained before 12 week exercises in both groups. The ABC feeling dimension scores of equestrian group and ABC communication dimension score of basketball group were significantly lower,and The upper arm circumference, sitting forward flexion, 40 second sit-up, 15s lateral jump, vital capacity, and single foot standing of both groups were significantly higher than that of before exercise.. The BMI of equestrian group was significantly reduced. The handgrip strength of basketball group was significantly increased. In conclusion, both types of exercises could improve daily behavior, morphological, physical function, and fitness indexes of the children with autism. However, the behavioral psychological scores, body morphology and function indicators and time points were different in the middle and back of the two interventions.But the indicators and the timing of the improvement were different. To the group of equestrian, the improvement of the flexibility occurred at week 4, the improvement of the sensory perception, control and use their own body, and promote the development of core strength endurance, coordination and cardiopulmonary function occurred at week 8，and the improvement of core strength endurance, coordination and cardiopulmonary function occurred at week 12. To the group of basketball, the improvement of the hand strength, balance, flexibility and cardiopulmonary function occurred at week 4, the improvement of the self-care ability and language expression ability, and core strength endurance and coordination occurred at week 8, the improvement of the control and use of their own body and social interaction ability occurred at week 12. In comparison of the exercise effects, the equestrian exercise improved the physical control and application ability appeared earlier than that of basketball group. Basketball exercise improved the language expression ability, self-care ability, balance ability and cardiopulmonary function of autistic children appeared earlier than that of equestrian group.

Keywords: intervention, children with autism, equestrain, basketball

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Authors: Hassan Hussin Zwida

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The liquified LPG (Liquefied Petroleum Gas) drying system at the Complex is designed to remove water and mercaptans from the LPG stream. Upon saturation of the desiccant beds, a regeneration cycle becomes necessary. The original design routed the regeneration gas, produced during the LPG dryer heating cycle, to the sulfur recovery unit to the incineration. However, concerns regarding high temperatures and potential unit disruptions led to a modification where the gas is currently vented to the acid flare for the initial hour before being diverted to the LP network fuel gas system. While this addresses the temperature concerns, it generates significant smoke due to the presence of liquid hydrocarbons. This paper proposes an approach to recover the regeneration gas and redirect it back to the gas plant's (off-gas compressors) instead of sending it to the AC (Acid Flare), by utilizing the existing pipe 6” and connected to off gas compressor KO (Knock-Out ) Drums . This option is simple to operate, flexible, environment-friendly solution as long-term solution, lower in capital expenditure and increase the company's profitability. The feasibility of this proposal is supported by dynamic simulations. The simulations suggest the possibility of operating two out of the three off-gas compressors and LPG (Liquefied petroleum gas) as a liquid phase, is foreseen to be carried over and gathered at the bottom level of the KO (Knock-Out) Drum.

Keywords: thermal incinerator, off-gas compressors, environment, knock-out drums, acid flare

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Authors: Sherin Ahmed El-Badry Sadek

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In this research, it is scientifically examined what contribution the professionalization of teachers can make to the development of a future-oriented vocational education and training system in Egypt. For this purpose, a needs assessment of the Egyptian vocational training system with the central actors and prevailing structures forms the foundation of the study, which theoretically underpinned with the attempt to resolve to some extent the tension between Luhmann's systems theory approach and the actor-centered theory of professional teacher competence. The vocational education system, in particular, must be adaptable and flexible due to the rapidly changing qualification requirements. In view of the pace of technological progress and the associated market changes, vocational training is no longer to be understood only as an educational tool aimed at those who achieve poorer academic performance or are not motivated to take up a degree. Rather, it is to be understood as a cornerstone for the development of society, and international experience shows that it is the core of lifelong learning. But to what extent have the education systems been able to react to these changes in their political, social, and technological systems? And how effective and sustainable are these changes actually? The vocational training system, in particular, has a particular impact on other social systems, which is why the appropriate parameters with the greatest leverage must be identified and adapted. Even if systems and structures are highly relevant, teachers must not hide behind them and must instead strive to develop further and to constantly learn. Despite numerous initiatives and programs to reform vocational training in Egypt, including the EU-funded Technical and Vocational Education and Training (TVET) reform phase I and phase II, the fit of the skilled workers to the needs of the labor market is still insufficient. Surveys show that the majority of employers are very dissatisfied with the graduates that the vocational training system produces. The data was collected through guideline-based interviews with experts from the education system and relevant neighboring systems, which allowed me to reconstruct central in-depth structures, as well as patterns of action and interpretation, in order to subsequently feed these into a matrix of recommendations for action. These recommendations are addressed to different decision-makers and stakeholders and are intended to serve as an impetus for the sustainable improvement of the Egyptian vocational training system. The research findings have shown that education, and in particular vocational training, is a political field that is characterized by a high degree of complexity and which is embedded in a barely manageable, highly branched landscape of structures and actors. At the same time, the vocational training system is not only determined by endogenous factors but also increasingly shaped by the dynamics of the environment and the neighboring social subsystems, with a mutual dependency relationship becoming apparent. These interactions must be taken into account in all decisions, even if prioritization of measures and thus a clear sequence and process orientation are of great urgency.

Keywords: competence orientation, educational policies, education systems, expert interviews, globalization, organizational development, professionalization, systems theory, teacher training, TVET system, vocational training

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Authors: Felix Boehnisch, Alexander Lutz

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Based on the number of users and the amount of content posted daily, Facebook is considered the largest social network in the world. This content includes images or text posts from companies but also private persons, which are also commented on by other users. However, it can sometimes be difficult for companies to keep track of all the posts and the reactions to them, especially when there are several posts a day that contain hundreds to thousands of comments. To facilitate this, the following paper deals with the possible applications of sentiment analysis to social media comments in order to be able to support the work in social media marketing. In a first step, post comments were divided into positive and negative by a subjective rating, then the same comments were checked for their polarity value by the two german python libraries TextBlobDE and SentiWS and also grouped into positive, negative, or even neutral. As a control, the subjective classifications were compared with the machine-generated ones by a confusion matrix, and relevant quality criteria were determined. The accuracy of both libraries was not really meaningful, with 60% to 66%. However, many words or sentences were not evaluated at all, so there seems to be room for optimization to possibly get more accurate results. In future studies, the use of these specific German libraries can be optimized to gain better insights by either applying them to stricter cleaned data or by adding a sentiment value to emojis, which have been removed from the comments in advance, as they are not contained in the libraries.

Keywords: Facebook, German libraries, polarity, sentiment analysis, social media comments

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Authors: Soofiyan Atar, Adil Shaikh, Sahil Rajpurkar, Pragnesh Bhalala, Aniket Desai, Irfan Siddavatam

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Deep reinforcement learning (deep RL) algorithms leverage the symbolic power of complex controllers by automating it by mapping sensory inputs to low-level actions. Deep RL eliminates the complex robot dynamics with minimal engineering. Deep RL provides high-risk involvement by directly implementing it in real-world scenarios and also high sensitivity towards hyperparameters. Tuning of hyperparameters on a pneumatic quadruped robot becomes very expensive through trial-and-error learning. This paper presents an automated learning control for a pneumatic quadruped robot using sample efficient deep Q learning, enabling minimal tuning and very few trials to learn the neural network. Long training hours may degrade the pneumatic cylinder due to jerk actions originated through stochastic weights. We applied this method to the pneumatic quadruped robot, which resulted in a hopping gait. In our process, we eliminated the use of a simulator and acquired a stable gait. This approach evolves so that the resultant gait matures more sturdy towards any stochastic changes in the environment. We further show that our algorithm performed very well as compared to programmed gait using robot dynamics.

Keywords: model-based reinforcement learning, gait stability, supervised learning, pneumatic quadruped

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Authors: Maja Benkovic, Dubravka Novotni, Bojana Voucko, Duska Curic, Damir Jezek, Nikolina Cukelj

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Cryo-grinding is an ultra-fine grinding method used in the pharmaceutical industry, production of herbs and spices and in the production and handling of cereals, due to its ability to produce powders with small particle sizes which maintain their favorable bioactive profile. The aim of this study was to determine the particle size distributions of the proso millet (Panicum miliaceum) bran fraction grinded at cryogenic temperature (using liquid nitrogen (LN₂) cooling, T = - 196 °C), in comparison to non-cooled grinding. Proso millet bran is primarily used as an animal feed, but has a potential in food applications, either as a substrate for extraction of bioactive compounds or raw material in the bakery industry. For both applications finer particle sizes of the bran could be beneficial. Thus, millet bran was ground for 2, 4, 8 and 12 minutes using the ball mill (CryoMill, Retsch GmbH, Haan, Germany) at three grinding modes: (I) without cooling, (II) at cryo-temperature, and (III) at cryo-temperature with included 1 minute of intermediate cryo-cooling step after every 2 minutes of grinding, which is usually applied when samples require longer grinding times. The sample was placed in a 50 mL stainless steel jar containing one grinding ball (Ø 25 mm). The oscillation frequency in all three modes was 30 Hz. Particle size distributions of the bran were determined by a laser diffraction particle sizing method (Mastersizer 2000) using the Scirocco 2000 dry dispersion unit (Malvern Instruments, Malvern, UK). Three main effects of the grinding set-up were visible from the results. Firstly, grinding time at all three modes had a significant effect on all particle size parameters: d(0.1), d(0.5), d(0.9), D[3,2], D[4,3], span and specific surface area. Longer grinding times resulted in lower values of the above-listed parameters, e.g. the averaged d(0.5) of the sample (229.57±1.46 µm) dropped to 51.29±1.28 µm after 2 minutes grinding without LN₂, and additionally to 43.00±1.33 µm after 4 minutes of grinding without LN₂. The only exception was the sample ground for 12 minutes without cooling, where an increase in particle diameters occurred (d(0.5)=62.85±2.20 µm), probably due to particles adhering to one another and forming larger particle clusters. Secondly, samples with LN₂ cooling exhibited lower diameters in comparison to non-cooled. For example, after 8 minutes of non-cooled grinding d(0.5)=46.97±1.05 µm was achieved, while the LN₂ cooling enabled collection of particles with average sizes of d(0.5)=18.57±0.18 µm. Thirdly, the application of intermediate cryo-cooling step resulted in similar particle diameters (d(0.5)=15.83±0.36 µm, 12 min of grinding) as cryo-milling without this step (d(0.5)=16.33±2.09 µm, 12 min of grinding). This indicates that intermediate cooling is not necessary for the current application, which consequently reduces the consumption of LN₂. These results point out the potential beneficial effects of millet bran grinding at cryo-temperatures. Further research will show if the lower particle size achieved in comparison to non-cooled grinding could result in increased bioavailability of bioactive compounds, as well as protein digestibility and solubility of dietary fibers of the proso millet bran fraction.

Keywords: ball mill, cryo-milling, particle size distribution, proso millet (Panicum miliaceum) bran

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Authors: Bandar Alahmadi, Lethia Jackson

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Machine Learning model is used today in many real-life applications. The safety and security of such model is important, so the results of the model are as accurate as possible. One challenge of machine learning model security is the adversarial examples attack. Adversarial examples are designed by the attacker to cause the machine learning model to misclassify the input. We propose a method to generate adversarial examples to attack image classifiers. We are modifying the successfully classified images, so a classifier misclassifies them after the modification. In our method, we do not update the whole image, but instead we detect the important region, modify it, place it back to the original image, and then run it through a classifier. The algorithm modifies the detected region using two methods. First, it will add abstract image matrix on back of the detected image matrix. Then, it will perform a rotation attack to rotate the detected region around its axes, and embed the trace of image in image background. Finally, the attacked region is placed in its original position, from where it was removed, and a smoothing filter is applied to smooth the background with foreground. We test our method in cascade classifier, and the algorithm is efficient, the classifier confident has dropped to almost zero. We also try it in CNN (Convolutional neural network) with higher setting and the algorithm was successfully worked.

Keywords: adversarial examples, attack, computer vision, image processing

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Authors: Hamidreza Ghazvinian, Khosro Ghazvinian, Touba Khodaiean

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The importance of evaporation estimation in water resources and agricultural studies is undeniable. Pan evaporation are used as an indicator to determine the evaporation of lakes and reservoirs around the world due to the ease of interpreting its data. In this research, intelligent models were investigated in estimating pan evaporation on a daily basis. Shahroud and Mayamey were considered as the studied cities. These two cities are located in Semnan province in Iran. The mentioned cities have dry weather conditions that are susceptible to high evaporation potential. Meteorological data of 11 years of synoptic stations of Shahrood and Mayamey cities were used. The intelligent models used in this study are Artificial Neural Network (ANN), Least Squares Support Vector Machine (LSSVM), and M5 tree models. Meteorological parameters of minimum and maximum air temperature (Tmax, Tmin), wind speed (WS), sunshine hours (SH), air pressure (PA), relative humidity (RH) as selected input data and evaporation data from pan (EP) to The output data was considered. 70% of data is used at the education level, and 30 % of the data is used at the test level. Models used with explanation coefficient evaluation (R2) Root of Mean Squares Error (RMSE) and Mean Absolute Error (MAE). The results for the two Shahroud and Mayamey stations showed that the above three models' operations are rather appropriate.

Keywords: pan evaporation, intelligent methods, shahroud, mayamey

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Authors: Emelia Noronha, Milind Malshe

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The phatic function of communication is a vital element of any conversation. This research paper looks into this function with respect to personal blogs maintained by Indian bloggers. This paper is a study into the phenomenon of phatic communication maintained by bloggers through their blogs. Based on a linguistic analysis of the posts of twenty eight Indian bloggers, writing in English, studied over a period of three years, the study indicates that though the blogging phenomenon is not conversational in the same manner as face-to-face communication, it does make ample provision for feedback that is conversational in nature. Ordinary day to day offline conversations use conventionalized phatic utterances; those on the social media are in a perpetual mode of innovation and experimentation in order to sustain contact with its readers. These innovative methods and means are the focus of this study. Though the personal blogger aims to chronicle his/her personal life through the blog, the socializing function is crucial to these bloggers. In comparison to the western personal blogs which focus on the presentation of the ‘bounded individual self’, we find Indian personal bloggers engage in the presentation of their ‘social selves’. These bloggers yearn to reach out to the readers on the internet and the phatic function serves to initiate, sustain and renew social ties on the blogosphere thereby consolidating the social network of readers and bloggers.

Keywords: personal blogs, phatic, social-selves, blog readers

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Authors: O. A. Ajigini, E. N. Mwim

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Cybersecurity is the protection of computers, programs, networks, and data from attack, damage, unauthorised, unintended access, change, or destruction. Organisations collect, process and store their confidential and sensitive information on computers and transmit this data across networks to other computers. Moreover, the advent of internet technologies has led to various cyberattacks resulting in dangerous consequences for organisations. Therefore, with the increase in the volume and sophistication of cyberattacks, there is a need to develop models and make recommendations for the management of cybersecurity threats in organisations. This paper reports on various threats that cause malicious damage to organisations in cyberspace and provides measures on how these threats can be eliminated or reduced. The paper explores various aspects of protection measures against cybersecurity threats such as handling of sensitive data, network security, protection of information assets and cybersecurity awareness. The paper posits a model and recommendations on how to manage cybersecurity threats in organisations effectively. The model and the recommendations can then be utilised by organisations to manage the threats affecting their cyberspace. The paper provides valuable information to assist organisations in managing their cybersecurity threats and hence protect their computers, programs, networks and data in cyberspace. The paper aims to assist organisations to protect their information assets and data from cyberthreats as part of the contributions toward community engagement.

Keywords: confidential information, cyberattacks, cybersecurity, cyberspace, sensitive information

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Authors: Olivia Borgue, Massimo Panarotto, Ola Isaksson

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This article presents a neural networks-based strategy for reducing the need for support structures when designing for additive manufacturing (AM). Additive manufacturing is a relatively new and immature industrial technology, and the information to make confident decisions when designing for AM is limited. This lack of information impacts especially the early stages of engineering design, for instance, it is difficult to actively consider the support structures needed for manufacturing a part. This difficulty is related to the challenge of designing a product geometry accounting for customer requirements, manufacturing constraints and minimization of support structure. The approach presented in this article proposes an automatized geometry modification technique for reducing the use of the support structures while designing for AM. This strategy starts with a neural network-based strategy for shape recognition to achieve product classification, using an STL file of the product as input. Based on the classification, an automatic part geometry modification based on MATLAB© is implemented. At the end of the process, the strategy presents different geometry modification alternatives depending on the type of product to be designed. The geometry alternatives are then evaluated adopting a QFD-like decision support tool.

Keywords: additive manufacturing, engineering design, geometry modification optimization, neural networks

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Authors: Antonis Skouloudis, Georgios Deligiannakis, Panagiotis Vouros, Konstantinos Evangelinos, Loannis Nikolaou

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On November 15th, 2017, a catastrophic flash flood devastated the city of Mandra in Central Greece, resulting in 24 fatalities and extensive damages to the built environment and infrastructure. It was Greece's deadliest and most destructive flood event for the past 40 years. In this paper, we examine the consequences of this event too small and medium-sized enterprises (SMEs) operating in Mandra during the flood event, which were affected by the floodwaters to varying extents. In this context, we conducted semi-structured interviews with business owners-managers of 45 SMEs located in flood inundated areas and are still active nowadays, based on an interview guide that spanned 27 topics. The topics pertained to the disaster experience of the business and business owners-managers, knowledge and attitudes towards climate change and extreme weather, aspects of disaster preparedness and related assistance needs. Our findings reveal that the vast majority of the affected businesses experienced heavy damages in equipment and infrastructure or total destruction, which resulted in business interruption from several weeks up to several months. Assistance from relatives or friends helped for the damage repairs and business recovery, while state compensations were deemed insufficient compared to the extent of the damages. Most interviewees pinpoint flooding as one of the most critical risks, and many connect it with the climate crisis. However, they are either not willing or unable to apply property-level prevention measures in their businesses due to cost considerations or complex and cumbersome bureaucratic processes. In all cases, the business owners are fully aware of the flood hazard implications, and since the recovery from the event, they have engaged in basic mitigation measures and contingency plans in case of future flood events. Such plans include insurance contracts whenever possible (as the vast majority of the affected SMEs were uninsured at the time of the 2017 event) as well as simple relocations of critical equipment within their property. The study offers fruitful insights on latent drivers and barriers of SMEs' resilience capacity to flash flooding. In this respect, findings such as ours, highlighting tensions that underpin behavioral responses and experiences, can feed into a) bottom-up approaches for devising actionable and practical guidelines, manuals and/or standards on business preparedness to flooding, and, ultimately, b) policy-making for an enabling environment towards a flood-resilient SME sector.

Keywords: flash flood, small and medium-sized enterprises, organizational resilience capacity, disaster preparedness, qualitative study

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Authors: Melodi Mbuyi Mata, Blessing Olamide Taiwo, Afolabi Ayodele David

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The purpose of this research is to create empirical models for assessing the profitability of granite aggregate production in Akure, Ondo state aggregate quarries. In addition, an artificial neural network (ANN) model and multivariate predicting models for granite profitability were developed in the study. A formal survey questionnaire was used to collect data for the study. The data extracted from the case study mine for this study includes granite marketing operations, royalty, production costs, and mine production information. The following methods were used to achieve the goal of this study: descriptive statistics, MATLAB 2017, and SPSS16.0 software in analyzing and modeling the data collected from granite traders in the study areas. The ANN and Multi Variant Regression models' prediction accuracy was compared using a coefficient of determination (R²), Root mean square error (RMSE), and mean square error (MSE). Due to the high prediction error, the model evaluation indices revealed that the ANN model was suitable for predicting generated profit in a typical quarry. More quarries in Nigeria's southwest region and other geopolitical zones should be considered to improve ANN prediction accuracy.

Keywords: national development, granite, profitability assessment, ANN models

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Authors: L. Edirisinghe, P. Mukherjee, H. Edirisinghe

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Virtual Container Yard (VCY) is a modern concept that helps to reduce the empty container repositioning cost of carriers. The concept of VCY is based on container interchange between shipping lines. Although this mechanism has been theoretically accepted by the shipping community as a feasible solution, it has not yet achieved the necessary momentum among container shipping lines (CSL). This paper investigates whether there is any legal influence on this industry myopia about the VCY. It is believed that this is the first publication that focuses on the legal aspects of container exchange between carriers. Not much literature on this subject is available. This study establishes with statistical evidence that there is a phobia prevailing in the shipping industry that exchanging containers with other carriers may lead to various legal implications. The complexity of exchange is two faceted. CSLs assume that offering a container to another carrier (obviously, a competitor in terms of commercial context) or using a container offered by another carrier may lead to undue legal implications. This research reveals that this fear is reflected through four types of perceived components, namely: shipping associate; warehouse associate; network associate; and trading associate. These components carry eighteen subcomponents that comprehensively cover the entire process of a container shipment. The statistical explanation has been supported through regression analysis; INCO terms were used to illustrate the shipping process.

Keywords: virtual container yard, legal, maritime law, inventory

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Authors: Prashansa Singh, Manjot Kaur, Rohit Bajaj

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The proliferation of wireless sensor networks and Internet of Things (IoT) devices in the quickly changing digital landscape has highlighted the urgent need for strong security solutions that can handle these systems’ limited resources. A key solution to this problem is the emergence of ultralightweight security protocols, which provide strong security features while respecting the strict computational, energy, and memory constraints imposed on these kinds of devices. This in-depth analysis explores the field of ultralightweight security protocols, offering a thorough examination of their evolution, salient features, and the particular security issues they resolve. We carefully examine and contrast different protocols, pointing out their advantages and disadvantages as well as the compromises between resource limitations and security resilience. We also study these protocols’ application domains, including the Internet of Things, RFID systems, and wireless sensor networks, to name a few. In addition, the review highlights recent developments and advancements in the field, pointing out new trends and possible avenues for future research. This paper aims to be a useful resource for researchers, practitioners, and developers, guiding the design and implementation of safe, effective, and scalable systems in the Internet of Things era by providing a comprehensive overview of ultralightweight security protocols.

Keywords: wireless sensor network, machine-to-machine, MQTT broker, server, ultralightweight, TCP/IP

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Authors: Farhat Jabeen, Muhammad Asad

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The study assessed the curative potential of Moringa olifera seeds against copper oxide nanoparticles induced toxicity in Oreochromis mossambicus. In order to investigate the curative potential of M. olifera seeds, firstly we examine its chemical composition, secondary metabolites, and bioactive compounds including hydroxyl-cinnamic acids, flavanols and hydroxybenzoic acids through standard methods and high performance liquid chromatography. In current study, the potential sub-lethal toxic dose of CuO-NPs (0.12 mg/l) was investigated through pilot experiment and three non-lethal doses (low=32, medium=48 and high=96 mg/l) of M. olifera were selected on the basis of its LC50 value for O. mossambicus. The experimental fish, O. mossambicus (n=100 of approximately 20 g each) were procured from Manawan Fisheries Complex, Lahore, and acclimatized for two weeks in glass aquaria. Experiment was conducted in accordance with the guidelines of Institutional Animal Ethics Committee, Government College University Faisalabad, Pakistan. During acclimatization and experimental period, fish received the commercial fish feed at 2.5% body weight daily. In order to assess the curative effect of M. olifera against CuO NPs induced toxicity, O. mossambicus were randomly divided into five groups and were designated as control (C) without any treatment, positive control (G*) exposed to potential toxic dose of CuO-NPs at 0.12 mg/l, and three treated groups namely G1, G2, and G3 co-treated with 0.12 mg/l of CuO-NPs plus different doses of M. olifera seed extract at 32, 48, and 96 mg/l, respectively for 56 days. Fish were exposed to waterborne CuO NPs and M. olifera seed extract. CuO-NPs treatment was ceased after 28 days but the doses of M. olifera were continued for 56 days. Blood was taken after 28 and 56 days through caudal venipuncture. Liver and intestine were taken for oxidative stress and histological studies after 56 days. In M. olifera seeds, moisture contents, crude protein, lipids, carbohydrates and ash were recorded as 3.8, 37.83, 32.52, 46.12, and 7.75%, respectively on dry weight basis. Total energy was recorded as 627.36 kcal/100g. Qualitative analysis of M. olifera seeds showed the presence of terpenoids, saponins, flavonoids, alkaloids and phenolics, while its quantitative analysis showed the considerable amount of total phenolics, flavonoids, saponins, and alkaloids as 134.75, 170.15, 1.57, and 0.4 µg/mg, respectively. Analysis of bioactive compounds in M. olifera seeds showed the presence of hydroxy-cinnamic acids (6.07 µg/ml), flavanols (71.72 µg/ml), and hydroxyl benzoic acids (97.82 µg/ml). The results showed that M. oliefera seed extract at 48 and 56 mg/l was able to cure against the toxic effects of CuO-NPs. The significant changes were observed in G* and G1 for sero-hepatic enzymes, anti-oxidants and histological profile. The investigations of this study showed that M. olifera is a good curative agent against potential induced toxicity of CuO-NPs in O. mossambicus. The curative effect of M. olifera is attributed to the presence of higher amount of secondary metabolites and bioactive compounds. This study suggested the use of M. olifera to curate different ailments in fish and other organisms.

Keywords: CuO nanoparticles, curative, Moringa olifera, Oreochromis mossambicus

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Authors: Dermot O'Brien, Vasileios Christaras, Georgios Fontaras, Igor Nai Fovino, Ioannis Kounelis

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With the rise of the Internet of Things (IoT), 5G, and blockchain (BC) technologies, vehicles are becoming ever increasingly connected and are already transmitting substantial amounts of data to the original equipment manufacturers (OEMs) servers. This data could be used to help detect mileage fraud and enable more accurate vehicle emissions monitoring. This would not only help regulators but could enable applications such as permitting efficient drivers to pay less tax, geofencing for air quality improvement, as well as pollution tolling and trading platforms for transport-related businesses and EU citizens. Other applications could include traffic management and shared mobility systems. BC enables the transmission of data with additional security and removes single points of failure while maintaining data provenance, identity ownership, and the possibility to retain varying levels of privacy depending on the requirements of the applied use case. This research performs simulations of vehicles interacting with European member state authorities and European Commission BC nodes that are running hyperleger fabric and explores whether the technology is currently feasible for transport applications such as the emission monitoring use-case.

Keywords: future transportation systems, technological innovations, policy approaches for transportation future, economic and regulatory trends, blockchain

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Authors: Aritra Majumdar

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While organizations strive to expand their new customer base, retaining existing relationships is a key aspect of improving overall profitability and also showcasing how successful an organization is in holding on to its customers. It is an experimentally proven fact that the lion’s share of profit always comes from existing customers. Hence seamless management of renewal journeys across different channels goes a long way in improving trust in the brand. From a quality assurance standpoint, time travel testing provides an approach to both business and technology teams to enhance the customer experience when they look to extend their partnership with the organization for a defined phase of time. This whitepaper will focus on key pillars of time travel testing: time travel planning, time travel data preparation, and enterprise automation. Along with that, it will call out some of the best practices and common accelerator implementation ideas which are generic across verticals like healthcare, insurance, etc. In this abstract document, a high-level snapshot of these pillars will be provided. Time Travel Planning: The first step of setting up a time travel testing roadmap is appropriate planning. Planning will include identifying the impacted systems that need to be time traveled backward or forward depending on the business requirement, aligning time travel with other releases, frequency of time travel testing, preparedness for handling renewal issues in production after time travel testing is done and most importantly planning for test automation testing during time travel testing. Time Travel Data Preparation: One of the most complex areas in time travel testing is test data coverage. Aligning test data to cover required customer segments and narrowing it down to multiple offer sequencing based on defined parameters are keys for successful time travel testing. Another aspect is the availability of sufficient data for similar combinations to support activities like defect retesting, regression testing, post-production testing (if required), etc. This section will talk about the necessary steps for suitable data coverage and sufficient data availability from a time travel testing perspective. Enterprise Automation: Time travel testing is never restricted to a single application. The workflow needs to be validated in the downstream applications to ensure consistency across the board. Along with that, the correctness of offers across different digital channels needs to be checked in order to ensure a smooth customer experience. This section will talk about the focus areas of enterprise automation and how automation testing can be leveraged to improve the overall quality without compromising on the project schedule. Along with the above-mentioned items, the white paper will elaborate on the best practices that need to be followed during time travel testing and some ideas pertaining to accelerator implementation. To sum it up, this paper will be written based on the real-time experience author had on time travel testing. While actual customer names and program-related details will not be disclosed, the paper will highlight the key learnings which will help other teams to implement time travel testing successfully.

Keywords: time travel planning, time travel data preparation, enterprise automation, best practices, accelerator implementation ideas

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Authors: Elieder P. Romanzini, Lutti M. Delevatti, Rhaony G. Leite, Ricardo A. Reis, Euclides B. Malheiros

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Brazilian beef cattle production systems are an important profitability source for the national gross domestic product. The main characteristic of these systems is forage utilization as the exclusive feed source. Forage utilization had been causing on owners the false feeling of low production costs. However, this low cost is followed to low profit causing a lot times worst animal index what can result in activities changes or until land sold. Aiming to evaluate economic impacts into Brazilian beef cattle systems were evaluated four nitrogen fertilizer (N) application levels (0, 90, 180 and 270 kg per hectare [kg.ha-1]). Research was developed during 2015 into Forage Crops and Grasslands section of São Paulo State University, “Júlio de Mesquita Filho” (Unesp) (Jaboticabal, São Paulo, Brazil). Pastures were seeded with Brachiaria brizantha Stapf. ‘Marandu’ (Palisade grass) handled using continuous grazing system, with variable stocking rate, sward height maintained at 25 cm. The economic evaluation was developed in rearing e finishing phases. We evaluated the cash flows inside each phase on different N levels. Economic valuations were considering: cost-effective operating (CEO), cost-total operating (CTO), gross revenue (GR), operating profit (OP) and net income (NI), every measured in US$. Complementary analyses were developed, profitability was calculated by [OP/GR]. Pay back (measured in years) was calculated considering average capital stocktaking pondered by area in use (ACS) divided by [GR-CEO]. And the internal rate of return (IRR) was calculated by 100/(pay back). Input prices were prices during 2015 and were obtained from Anuário Brasileiro da Pecuária, Centro de Estudos Avançados em Economia Aplicada and quotation in the same region of animal production (northeast São Paulo State) during the period above mentioned. Values were calculated in US$ according exchange rate US$1.00 equal R$3.34. The CEO, CTO, GR, OP and NI per hectare for each N level were respectively US$1,919.66; US$2,048.47; US$2,905.72; US$857.25 and US$986.06 to 0 kg.ha-1; US$2,403.20; US$2,551.80; US$3,530.19; US$978.39 and US$1,126.99 to 90 kg.ha-1; US$3,180.42; US$3,364.81; US$4,985.03; US$1,620.23 and US$1,804.62 to 180 kg.ha-1andUS$3,709.14; US$3,915.15; US$5,554.95; US$1,639.80 and US$1,845.81 to 270 kg.ha-1. Relationship to another economic indexes, profitability, pay back and IRR, the results were respectively 29.50%, 6.44 and 15.54% to 0 kg.ha-1; 27.72%, 6.88 and 14.54% to 90 kg.ha-1; 32.50%, 4.08 and 24.50% to 180 kg.ha-1 and 29.52%, 3.42 and 29.27% to 270 kg.ha-1. Values previously presented in this evaluation allowing to affirm that the best result was obtained to N level 270 kg.ha-1. These results among all N levels evaluated could be explained by improve occurred on stocking rate caused by increase on N level. However, a crucial information about high N level application into pastures is the efficiency of N utilization (associated to environmental impacts) that normally decrease with the increase on N level. Hence, considering all situations (efficiency of N utilization and economic results) into tropical pastures used to beef cattle production could be recommended N level equal to 180kg.ha-1, which had better profitability and cause lesser environmental impacts, proved by other studies developed in the same area.

Keywords: Brachiaria brizantha, cost-total operating, gross revenue, profitability

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