Search results for: operations sequence

Authors: Babagana Abubakar, Alhaji Kuya

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Although the field of Space weather science is a young field among the space sciences, but yet history has it that activities related to this science began since the year 1859 when the great solar storm happened which resulted in the disruptions of telegraphs operations around the World at that particular time subsequently making it possible for the scientist Richard Carrington to be able to connect the Solar flare observed a day earlier before the great storm and the great deflection of the Earth’s Magnetic field (geometric storm) simultaneous with the telegraph disruption. However years later as at today with the advent of and the coming into existence of the Explorer 1, the Luna 1 and the establishments of the United States International Space Weather Program, International Geophysical Year (IGY) as well as the International Center for Space Weather Sciences and Education (ICSWSE) have made us understand the Space weather better and enable us well define the field of Space weather science. Despite the successes recorded in the development of Space sciences as a whole over the last century and the coming onboard of specialized bodies/programs on space weather like the International Space Weather Program and the ICSWSE, the majority of Africans including institutions, research organizations and even some governments are still ignorant about the existence of theSpace weather science,because apart from some very few countries like South Africa, Nigeria and Egypt among some few others the majority of the African nations and their academic institutions have no knowledge or idea about the existence of this field of Space science (Space weather).

Keywords: Africa, space, weather, education, science

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Authors: Gloria Ogungbade, Ogaba Oche, Moses Duruji, Chris Ehiobuche, Lady Ajayi

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Human’s continued sustenance on earth and the quality of living are heavily dependent on the environment. The major components of the environment being air, water and land are the supporting pillars of the human existence, which they depend on directly or indirectly for survival and well-being. Unfortunately, due to some of the human activities on the environment, there seems to be a war between humans and the environment, which is evident in his over-exploitation and inadequate management of the basic components of the environment. Since the discovery of crude oil in the Niger Delta, the region has experienced various forms of degradation caused by pollution from oil spillage, gas flaring and other forms of environmental pollution, as a result of reckless way and manner with which oil is being exploited by the International Oil Corporations (IOCs) operating within the region. The Nigerian government on the other, not having strong regulations guiding the activities of the operations of these IOCs, has done almost nothing to curtail the activities of these IOCs because of the revenue generated the IOCs, as such the region is deprived of the basic social amenities and infrastructures. The degree of environmental pollution suffered within the region affects their major sources of livelihood – being fishing and farming, and has also left the region in poverty, which has led to a large number of people migrating to the urban areas to escape poverty. This paper investigates how environment degradation impact urbanization and security in the region.

Keywords: environmental degradation, environmental pollution, gas flaring, oil spillage, urbanization

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Authors: Justin Woulfe

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Siloed logistics and supply chain management systems throughout the Department of Defense (DOD) has led to disparate approaches to modeling and simulation (M&S), a lack of understanding of how one system impacts the whole, and issues with “optimal” solutions that are good for one organization but have dramatic negative impacts on another. Many different systems have evolved to try to understand and account for uncertainty and try to reduce the consequences of the unknown. As the DoD undertakes expansive digital transformation initiatives, there is an opportunity to fuse and leverage traditionally disparate data into a centrally hosted source of truth. With a streamlined process incorporating machine learning (ML) and artificial intelligence (AI), advanced M&S will enable informed decisions guiding program success via optimized operational readiness and improved mission success. One of the current challenges is to leverage the terabytes of data generated by monitored systems to provide actionable information for all levels of users. The implementation of a cloud-based application analyzing data transactions, learning and predicting future states from current and past states in real-time, and communicating those anticipated states is an appropriate solution for the purposes of reduced latency and improved confidence in decisions. Decisions made from an ML and AI application combined with advanced optimization algorithms will improve the mission success and performance of systems, which will improve the overall cost and effectiveness of any program. The Systecon team constructs and employs model-based simulations, cutting across traditional silos of data, aggregating maintenance, and supply data, incorporating sensor information, and applying optimization and simulation methods to an as-maintained digital twin with the ability to aggregate results across a system’s lifecycle and across logical and operational groupings of systems. This coupling of data throughout the enterprise enables tactical, operational, and strategic decision support, detachable and deployable logistics services, and configuration-based automated distribution of digital technical and product data to enhance supply and logistics operations. As a complete solution, this approach significantly reduces program risk by allowing flexible configuration of data, data relationships, business process workflows, and early test and evaluation, especially budget trade-off analyses. A true capability to tie resources (dollars) to weapon system readiness in alignment with the real-world scenarios a warfighter may experience has been an objective yet to be realized to date. By developing and solidifying an organic capability to directly relate dollars to readiness and to inform the digital twin, the decision-maker is now empowered through valuable insight and traceability. This type of educated decision-making provides an advantage over the adversaries who struggle with maintaining system readiness at an affordable cost. The M&S capability developed allows program managers to independently evaluate system design and support decisions by quantifying their impact on operational availability and operations and support cost resulting in the ability to simultaneously optimize readiness and cost. This will allow the stakeholders to make data-driven decisions when trading cost and readiness throughout the life of the program. Finally, sponsors are available to validate product deliverables with efficiency and much higher accuracy than in previous years.

Keywords: artificial intelligence, digital transformation, machine learning, predictive analytics

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Authors: Edu Marcelina, Sule Sheidu A., Nsor Eunice

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As open and distance education is gradually becoming an acceptable means of solving the problem of access in higher education, quality has now become one of the main concerns among institutions and stakeholders of open and distance learning (ODL) and the education sector in general. This study assessed the challenges of academic quality in the open and distance learning (ODL) education in Nigeria using Distance Learning Institute (DLI), University of Lagos and National Open University of Nigeria as a case. In carrying out the study, a descriptive survey research design was employed. A researcher-designed and validated questionnaire was used to elicit responses that translated to the quantitative data for this study. The sample comprised 665 students of the Distance Learning Institute (DLI), and National Open University of Nigeria (NOUN), carefully selected through the method of simple random sampling. Data collected from the study were analyzed using Chi-Square (X2) at 0.05 Level of significance. The results of the analysis revealed that; the use of ICT tools is a factor in ensuring quality in the Open and Distance Learning (ODL) operations; the quality of the materials made available to ODL students will determine the quality of education that will be received by the students; and the time scheduled for students for self-study, online lecturing/interaction and face to face study and the quality of education in Open and Distance Learning Institutions has a lot of impact on the quality of education the students receive. Based on the findings, a number of recommendations were made.

Keywords: open and distance learning, quality, ICT, face-to-face interaction

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Authors: Shi Zhang

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This paper aims to introduce the allopatry of national college entrance examination which allow migrant students enter senior high schools and take college entrance exam where they live, identifies the reasons affect the implementation of this policy in the Chinese context. Most of China’s provinces and municipalities recently have announced new policies regarding national college entrance exams for non-local students. The paper conducts SWOT analysis reveals the opportunities, strength, weakness and challenges of the scheme, so as to discuss the implementation strategies from the perspectives of idea and institution. The research findings imply that the government should take a more positive attitude toward relaxing the allopatry of NCEE policy restrictions, and promote the reform household registration policy and NCEE policy with synchronous operations. Higher education institutions should explore the diversification of enrollment model; the government should issue the authority of universities and colleges to select elite migrant students beyond the restrictions of NCEE. To suit reform policies to local conditions, the big cities such as Beijing, Shanghai and Guangzhou should publish related compensate measures for children of migrant workers access to higher vocational colleges with tuition fee waivered. 

Keywords: college entrance examination, higher education, education policy, education equality

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Authors: Pi-Hsia Hung

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The development of mathematical competency has individual benefits as well as benefits to the wider society. Children who begin school behind their peers in their understanding of number, counting, and simple arithmetic are at high risk of staying behind throughout their schooling. The development of effective strategies for improving the educational trajectory of these individuals will be contingent on identifying areas of early quantitative knowledge that influence later mathematics achievement. A computer-based quantity assessment was developed in this study to investigate the characteristics of 2nd and 3rd grade slow learners in quantity. The concept of quantification involves understanding measurements, counts, magnitudes, units, indicators, relative size, and numerical trends and patterns. Fifty-five tasks of quantitative reasoning—such as number sense, mental calculation, estimation and assessment of reasonableness of results—are included as quantity problem solving. Thus, quantity is defined in this study as applying knowledge of number and number operations in a wide variety of authentic settings. Around 1000 students were tested and categorized into 4 different performance levels. Students’ quantity ability correlated higher with their school math grade than other subjects. Around 20% students are below basic level. The intervention design implications of the preliminary item map constructed are discussed.

Keywords: mathematics assessment, mathematical cognition, quantity, number sense, validity

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Authors: Aicha Majda, Abdelhamid El Hassani

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Lung CT image segmentation is a prerequisite in lung CT image analysis. Most of the conventional methods need a post-processing to deal with the abnormal lung CT scans such as lung nodules or other lesions. The simplest similarity measure in the standard Graph Cuts Algorithm consists of directly comparing the pixel values of the two neighboring regions, which is not accurate because this kind of metrics is extremely sensitive to minor transformations such as noise or other artifacts problems. In this work, we propose an improved version of the standard graph cuts algorithm based on the Patch-Based similarity metric. The boundary penalty term in the graph cut algorithm is defined Based on Patch-Based similarity measurement instead of the simple intensity measurement in the standard method. The weights between each pixel and its neighboring pixels are Based on the obtained new term. The graph is then created using theses weights between its nodes. Finally, the segmentation is completed with the minimum cut/Max-Flow algorithm. Experimental results show that the proposed method is very accurate and efficient, and can directly provide explicit lung regions without any post-processing operations compared to the standard method.

Keywords: graph cuts, lung CT scan, lung parenchyma segmentation, patch-based similarity metric

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Authors: Yujie Zhou, Hee-Seong Byun, Sang-In Bak, Eui-Joon Kil, Kyung Joo Min, Vivek Chavan, Won Kyong Cho, Sukchan Lee, Seung-Woo Hong, Tae-Sun Park

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Fast neutron irradiation (FNI) can cause mutations on plant genome but, in the most of cases, these irradiated plants have not shown significant characteristics phenotypically. In this study, we utilized RNA-Seq to generate a high-resolution transcriptome map of the tomato (Solanum lycopersicum) genome effected by FNI. To quantify the different transcription levels in tomato irradiated by FNI, tomato seeds were irradiated by using MC-50 cyclotron (KIRAMS, Korea) for 0, 30 and 90 minutes, respectively. To investigate the effects on the pre-soaking condition, experimental groups were divided into dry and soaked seeds, which were soaked for 8 hours before irradiation. There was no noticeable difference in the percentage germination (PG) among dry seeds, while irradiated soaked seeds have about 10 % lower PG compared to the unirradiated control group. Using whole transcriptome sequencing by HiSeq 2000, we analyzed the differential gene expression in response to different time of FNI in dry and soaked seeds. More than 1.4 million base pair reads were mapped onto the tomato reference genome and the expression pattern differences between irradiated and unirradiated seeds were assessed. In 0, 30 and 90 minutes irradiation, 12,135, 28,495 and 28,675 transcripts were generated, respectively. Gene ontology analysis suggested the different enrichment of transcripts involved in response to different FNI. The present study showed that FNI effects on plant gene expression, which can become a new parameters for evaluating the responses against FNI on plants. In addition, the comparative analysis of differentially expressed genes in D and S seeds by FNI will also give us a chance to deep explore novel candidate genes for FNI, which could be a good model system to understand the mechanisms behind the adaption of plant to space biology research.

Keywords: tomato (solanum lycopersicum), fast neutron irradiation, RNA-sequence, transcriptome expression

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Authors: Omid Kalatpour, Mohammadreza Ajdari

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This article studied the possible causes of human error-induced incidents in the petrochemical industry maintenance activities by using Human Factors Analysis and Classification System (HFACS). The purpose of the study was anticipating and identifying these causes and proposing corrective and preventive actions. Maintenance department in a petrochemical company was selected for research. A checklist of human error-induced incidents was developed based on four HFACS main levels and nineteen sub-groups. Hierarchical task analysis (HTA) technique was used to identify maintenance activities and tasks. The main causes of possible incidents were identified by checklist and recorded. Corrective and preventive actions were defined depending on priority. Analyzing the worksheets of 444 activities in four levels of HFACS showed 37.6% of the causes were at the level of unsafe actions, 27.5% at the level of unsafe supervision, 20.9% at the level of preconditions for unsafe acts and 14% of the causes were at the level of organizational effects. The HFACS sub-groups showed errors (24.36%) inadequate supervision (14.89%) and violations (13.26%) with the most frequency. According to findings of this study, increasing the training effectiveness of operators and supervision improvement respectively are the most important measures in decreasing the human error-induced incidents in petrochemical industry maintenance.

Keywords: human error, petrochemical industry, maintenance, HFACS

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Authors: Aouina Nabila Yasmina, Zine El Abidine Chaoui

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Recently, understanding the interactions of electrons with the DNA molecule and its components has attracted considerable interest because DNA is the main site damaged by ionizing radiation. The interactions of radiation with DNA induce a variety of molecular damage such as single-strand breaks, double-strand breaks, basic damage, cross-links between proteins and DNA, and others, or the formation of free radicals, which, by chemical reactions with DNA, can also lead to breakage of the strand. One factor that can contribute significantly to these processes is the effect of water hydration on the formation and reaction of radiation induced by these radicals in and / or around DNA. B-DNA requires about 30% by weight of water to maintain its native conformation in the crystalline state. The transformation depends on various factors such as sequence, ion composition, concentration and water activity. Partial dehydration converts it to DNA-A. The present study shows the results of theoretical calculations for positrons and electrons elastic scattering with DNA medium and water over a broad energy range from 10 eV to 100 keV. Indeed, electron elastic cross sections and elastic mean free paths are calculated using a corrected form of the independent atom method, taking into account the geometry of the biomolecule (SCAR macro). Moreover, the elastic scattering of electrons and positrons by atoms of the biomolecule was evaluated by means of relativistic (Dirac) partial wave analysis. Our calculated results are compared with theoretical data available in the literature in the absence of experimental data, in particular for positron. As a central result, our electron elastic cross sections are in good agreement with existing theoretical data in the range of 10 eV to 1 keV.

Keywords: elastic cross scrion, elastic mean free path, scar macro method, electron collision

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Authors: N. Rassoul-ibrahim, E. Siahmed, L. Tadrist

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Water management plays a crucial role in the performance and durability of PEM fuel cells. Whereas the membrane must be hydrated enough, liquid droplets formed by water in excess can block the flow in the gas distribution channels and hinder the fuel cell performance. The main purpose of this work is to increase the understanding of liquid transport and mixing through mini- or micro-channels for various engineering or medical process applications including cool-ing of equipment according to the operations considered. For that purpose and as a first step, a technique was devel-oped to automatically detect and characterize two-phase flow patterns that may appear in such. The investigation, mainly experimental, was conducted on transparent channel with a 1mm x 1mm square cross section and a 0.3mm x 0.3 mm water injection normal to the gas channel. Three main flow patterns were identified liquid slug, bubble flow and annular flow. A flow map has been built accord-ing to the flow rate of both phases. As a sample the follow-ing figures show representative images of the flow struc-tures observed. An analysis and discussion of the flow pattern, in mini-channel, will be provided and compared to the case old micro-channel. . Keywords: Two phase flow, Clean Energy, Minichannels, Fuel Cells. Flow patterns, Maps.

Keywords: two phase flox, T-juncion, Micro and minichannels, clean energy, flow patterns, maps

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Authors: Tei Kim, Brooklynn McNeil, Kathryn Dunn, Douglas I. Walker

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To better characterize the relationship between complex chemical exposures and disease, our laboratory uses an approach that combines low-cost, polydimethylsiloxane (silicone) wristband samplers that absorb many of the chemicals we are exposed to with untargeted high-resolution mass spectrometry (HRMS) to characterize 1000’s of chemicals at a time. In studies with human populations, these wristbands can provide an important measure of our environment: however, there is a need to use this approach in large cohorts to study exposures associated with the disease. To facilitate the use of silicone samplers in large scale population studies, the goal of this research project was to establish automated sample preparation methods that improve throughput, robustness, and scalability of analytical methods for silicone wristbands. Using the Opentron OT2 automated liquid platform, which provides a low-cost and opensource framework for automated pipetting, we created two separate workflows that translate the manual wristband preparation method to a fully automated protocol that requires minor intervention by the operator. These protocols include a sequence generation step, which defines the location of all plates and labware according to user-specified settings, and a transfer protocol that includes all necessary instrument parameters and instructions for automated solvent extraction of wristband samplers. These protocols were written in Python and uploaded to GitHub for use by others in the research community. Results from this project show it is possible to establish automated and open source methods for the preparation of silicone wristband samplers to support profiling of many environmental exposures. Ongoing studies include deployment in longitudinal cohort studies to investigate the relationship between personal chemical exposure and disease.

Keywords: bioinformatics, automation, opentrons, research

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Authors: Fan Li, Chun-Hsien Chen, Li Pheng Khoo

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Operators of vessel traffic service (VTS) center provides three different types of services; namely information service, navigational assistance and traffic organization to vessels. To provide these services, operators monitor vessel traffic through computer interface and provide navigational advice based on the information integrated from multiple sources, including automatic identification system (AIS), radar system, and closed circuit television (CCTV) system. Therefore, this information is crucial in VTS operation. However, what information the VTS operator actually need to efficiently and properly offer services is unclear. The aim of this study is to investigate into information requirements for VTS operation. To achieve this aim, field observation was carried out to elicit the information requirements for VTS operation. The study revealed that the most frequent and important tasks were handling arrival vessel report, potential conflict control and abeam vessel report. Current location and vessel name were used in all tasks. Hazard cargo information was particularly required when operators handle arrival vessel report. The speed, the course, and the distance of two or several vessels were only used in potential conflict control. The information requirements identified in this study can be utilized in designing a human-computer interface that takes into consideration what and when information should be displayed, and might be further used to build the foundation of a decision support system for VTS.

Keywords: vessel traffic service, information requirements, hierarchy task analysis, field observation

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Authors: Zhao Xinlei

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The outbreak of the Ukraine crisis has had an important impact on the global political and economic order, especially the global food crisis and energy crisis, thus aggravating social and political conflicts. At the same time, with the intensification of the Ukraine crisis, the United States and European countries have imposed severe economic sanctions on Russia to prevent and contain Russia's special military operations against Ukraine. The essence of the Ukraine crisis is a geopolitical conflict and competition between Russia and the United States. For a long time, the United States has always regarded Russia as a serious strategic crisis and challenge. Therefore, for the United States, the outbreak of the Ukraine crisis is an extremely important opportunity to condemn and stop Russia's actions from an international perspective. In this process, China plays a very special role. This special positioning is not only reflected in the long-term friendly relationship between China and Russia and mutual support and assistance on the international stage but also in the complex economic relationship and interdependence between China and the United States. Therefore, China has adopted a "hedging strategy" in dealing with the Ukrainian crisis, and the use of the hedging strategy not only plays a special role in safeguarding China's own security and interests but also because China can act as an intermediary to coordinate Russia and the United States to promote the resolution of the Ukrainian crisis in a peaceful manner.

Keywords: Ukraine crisis Russia-Ukraine conflict balanced strategy Sino-US competition

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Authors: Vahid Bayrami Rad

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In this research, common methods and techniques have been investigated with a focus on intelligent fault finding and monitoring systems in the oil industry. In fact, remote and intelligent control methods are considered a necessity for implementing various operations in the oil industry, but benefiting from the knowledge extracted from countless data generated with the help of data mining algorithms. It is a avoid way to speed up the operational process for monitoring and troubleshooting in today's big oil companies. Therefore, by comparing data mining algorithms and checking the efficiency and structure and how these algorithms respond in different conditions, The proposed (Bayesian) algorithm using data clustering and their analysis and data evaluation using a colored Petri net has provided an applicable and dynamic model from the point of view of reliability and response time. Therefore, by using this method, it is possible to achieve a dynamic and consistent model of the remote control system and prevent the occurrence of leakage in oil pipelines and refineries and reduce costs and human and financial errors. Statistical data The data obtained from the evaluation process shows an increase in reliability, availability and high speed compared to other previous methods in this proposed method.

Keywords: wireless sensors, petroleum equipment troubleshooting, Bayesian algorithm, colored Petri net, rapid miner, data mining-reliability

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Authors: Jagul Huma Lashari, Arabella Bhutto

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Last few years have shown increased an interest of researchers in knowledge and technology transfer. However, facts show fewer types of knowledge transfer practices in the developing countries. This article focuses on assessment transfer channels of academic research produced by highly qualified academicians working in universities in Sindh offering degrees in field of an Environment in Sindh Pakistan. The academic field has been chosen because in field of the environment there is alarming need of research into practice for sustainable development. Using case study approach; in this research qualitative interviews have been conducted from PhD faculty members working in the universities offering degrees in field of environment. Obtained data is analyzed using descriptive statistics and chi-square test with the help of statistical packages for social sciences (SPSS). Research explored 31 channels of academic knowledge transfer from detailed review of literature and exploratory interviews with participants. Identified knowledge transfer channels have been grouped together in 6 groups of knowledge transfer channels; As knowledge transfer through publications, networking, mobility of researchers, joint research, intellectual property and co-operations. Results revealed that academic knowledge have been transferred through publications, networking, and co-operation. However, less number of academic knowledge has been transferred through groups of knowledge transfer channels such as Intellectual Property and joint research.

Keywords: environment, research knowledge, transfer channels, universities

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Authors: Satyam Raikwar, Thomas Herlitzius, Jens Fehrmann

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In recent years, the autonomous navigation of orchard and field robots is an emerging technology of the mobile robotics in agriculture. One of the core aspects of autonomous navigation builds upon path planning, which is still a crucial issue. Generally, for simple representation, the path planning for a mobile robot is performed in a two-dimensional space, which creates a path between the start and goal point. This paper presents the automatic path planning approach for robots used in orchards and vineyards using occupancy grid maps with field consideration. The orchards and vineyards are usually structured environment and their topology is assumed to be constant over time; therefore, in this approach, an RGB image of a field is used as a working environment. These images undergone different image processing operations and then discretized into two-dimensional grid matrices. The individual grid or cell of these grid matrices represents the occupancy of the space, whether it is free or occupied. The grid matrix represents the robot workspace for motion and path planning. After the grid matrix is described, a probabilistic roadmap (PRM) path algorithm is used to create the obstacle-free path over these occupancy grids. The path created by this method was successfully verified in the test area. Furthermore, this approach is used in the navigation of the orchard robot.

Keywords: orchard robots, automatic path planning, occupancy grid, probabilistic roadmap

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Authors: Glenda Marie D. Balitaan

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The branch of business management that deals with inventory planning and control is known as inventory management. It comprises keeping track of supply levels and forecasting demand, as well as scheduling when and how to plan. Keeping excess inventory results in a loss of money, takes up physical space, and raises the risk of damage, spoilage, and loss. On the other hand, too little inventory frequently causes operations to be disrupted and raises the possibility of low customer satisfaction, both of which can be detrimental to a company's reputation. The United Victorious Feed mill Corporation's present inventory management practices were assessed in terms of inventory level, warehouse allocation, ordering frequency, shelf life, and production requirement. To help the company achieve their optimal level of inventory, a mathematical model was created using Integer Linear Programming. Due to the season, the goal function was to reduce the cost of purchasing US Soya and Yellow Corn. Warehouse space, annual production requirements, and shelf life were all considered. To ensure that the user only uses one application to record all relevant information, like production output and delivery, the researcher built a Visual Basic system. Additionally, the technology allows management to change the model's parameters.

Keywords: inventory management, integer linear programming, inventory management system, feed mill

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Authors: Yi-Lin Chen, Sheng-Jou Hung, Tsunglin Liu

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Adaptive immune system recognizes a wide range of antigens via expressing a large number of structurally distinct T cell and B cell receptor genes. The distinct receptor genes arise from complex rearrangements called V(D)J recombination, and constitute the immune repertoire. A common method of profiling immune repertoire is via amplifying recombined receptor genes using multiple primers and high-throughput sequencing. This multiplex-PCR approach is efficient; however, the resulting repertoire can be distorted because of primer bias. To eliminate primer bias, 5’ RACE is an alternative amplification approach. However, the application of RACE approach is limited by its low efficiency (i.e., the majority of data are non-regular receptor sequences, e.g., containing intronic segments) and lack of the convenient tool for analysis. We propose a computational tool that can correctly identify non-regular receptor sequences in RACE data via aligning receptor sequences against the whole gene instead of only the exon regions as done in all other tools. Using our tool, the remaining regular data allow for an accurate profiling of immune repertoire. In addition, a RACE approach is improved to yield a higher fraction of regular T-cell receptor sequences. Finally, we quantify the degree of primer bias of a multiplex-PCR approach via comparing it to the RACE approach. The results reveal significant differences in frequency of VJ combination by the two approaches. Together, we provide a new experimental and computation pipeline for an unbiased profiling of immune repertoire. As immune repertoire profiling has many applications, e.g., tracing bacterial and viral infection, detection of T cell lymphoma and minimal residual disease, monitoring cancer immunotherapy, etc., our work should benefit scientists who are interested in the applications.

Keywords: immune repertoire, T-cell receptor, 5' RACE, high-throughput sequencing, sequence alignment

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Authors: D. Kuvshinov, A. Siswanto, W. Zimmerman

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A phorbol-12-myristate-13-acetate (TPA) is a synthetic analogue of phorbol ester (PE), a natural toxic compound of Euphorbiaceae plant. The oil extracted from plants of this family is useful source for primarily biofuel. However this oil can also be used as a food stock due to its significant nutrition content. The limitations for utilizing the oil as a food stock are mainly due to a toxicity of PE. Nowadays a majority of PE detoxification processes are expensive as include multi steps alcohol extraction sequence. Ozone is considered as a strong oxidative agent. It reaction with PE it attacks the carbon double bond of PE. This modification of PE molecular structure results into nontoxic ester with high lipid content. This report presents data on development of simple and cheap PE detoxification process with water application as a buffer and ozone as reactive component. The core of this new technique is a simultaneous application of new microscale plasma unit for ozone production and patented gas oscillation technology. In combination with a reactor design the technology permits ozone injection to the water-TPA mixture in form of microbubbles. The efficacy of a heterogeneous process depends on diffusion coefficient which can be controlled by contact time and interface area. The low velocity of rising microbubbles and high surface to volume ratio allow fast mass transfer to be achieved during the process. Direct injection of ozone is the most efficient process for a highly reactive and short lived chemical. Data on the plasma unit behavior are presented and influence of the gas oscillation technology to the microbubbles production mechanism has been discussed. Data on overall process efficacy for TPA degradation is shown.

Keywords: microbubble, ozonolysis, synthetic phorbol ester, chemical engineering

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Authors: Elsie L. Echeverri-Carroll

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Entrepreneurial ecosystems have become an important concept to explain the birth and sustainability of technology-based entrepreneurship within regions. However, as a theoretical concept, the temporal evolution of entrepreneurship systems remain underdeveloped, making it difficult to understand their dynamic contributions to entrepreneurs. This paper argues that successful technology-based ecosystems go over three cumulative spawning stages: corporate spawning, entrepreneurial spawning, and community spawning. The importance of corporate incubation in vibrant entrepreneurial ecosystems is well documented in the entrepreneurial literature. Similarly, entrepreneurial spawning processes for venture capital-backed startups are well documented in the financial literature. In contrast, there is little understanding of both the third stage of entrepreneurial spawning (when a community of entrepreneurs become a source of firm spawning) and the temporal sequence in which spawning effects occur in a region. We test this three-stage model of entrepreneurial spawning using data from two large databases on firm births—the Secretary of State (160,000 observations) and the National Establishment Time Series (NEST with 150,000 observations)—and information collected from 60 1½-hour interviews with startup founders and representatives of key entrepreneurial organizations. This temporal model is illustrated with case study of Austin, Texas ranked by the Kauffman Foundation as the number one entrepreneurial city in the United States in 2015 and 2016. The 1½-year study founded by the Kauffman Foundation demonstrates the importance of taken into consideration the temporal contributions of both large and entrepreneurial firms in understanding the factors that contribute to the birth and growth of technology-based entrepreneurial regions. More important, these learnings could offer an important road map for regions that pursue to advance their entrepreneurial ecosystems.

Keywords: entrepreneurial ecosystems, entrepreneurial industrial clusters, high-technology, temporal changes

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Authors: Sri Lakshmi Kanniah, Mohd Naz’ri Mahrin

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More and more businesses and services are depending on software to run their daily operations and business services. At the same time, cyber-attacks are becoming more covert and sophisticated, posing threats to software. Vulnerabilities exist in the software due to the lack of security practices during the phases of software development. Implementation of secure software development practices can improve the resistance to attacks. Many methods, models and standards for secure software development have been developed. However, despite the efforts, they still come up against difficulties in their deployment and the processes are not institutionalized. There is a set of factors that influence the successful deployment of secure software development processes. In this study, the methodology and results from a systematic literature review of factors influencing the implementation of secure software development practices is described. A total of 44 primary studies were analysed as a result of the systematic review. As a result of the study, a list of twenty factors has been identified. Some of factors that affect implementation of secure software development practices are: Involvement of the security expert, integration between security and development team, developer’s skill and expertise, development time and communication between stakeholders. The factors were further classified into four categories which are institutional context, people and action, project content and system development process. The results obtained show that it is important to take into account organizational, technical and people issues in order to implement secure software development initiatives.

Keywords: secure software development, software development, software security, systematic literature review

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Authors: M. N. Zelenin, V. S. Mikhailov, R. P. Zhivotovsky

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It is known that residual welding deformations give negative effect to processability and operational quality of welded structures, complicating their assembly and reducing strength. Therefore, selection of optimal technology, ensuring minimum welding deformations, is one of the main goals in developing a technology for manufacturing of welded structures. Through years, JSC SSTC has been developing a theory for estimation of welding deformations and practical activities for reducing and compensating such deformations during welding process. During long time a methodology was used, based on analytic dependence. This methodology allowed defining volumetric changes of metal due to welding heating and subsequent cooling. However, dependences for definition of structures deformations, arising as a result of volumetric changes of metal in the weld area, allowed performing calculations only for simple structures, such as units, flat sections and sections with small curvature. In case of complex 3D structures, estimations on the base of analytic dependences gave significant errors. To eliminate this shortage, it was suggested to use finite elements method for resolving of deformation problem. Here, one shall first calculate volumes of longitudinal and transversal shortenings of welding joints using method of analytic dependences and further, with obtained shortenings, calculate forces, which action is equivalent to the action of active welding stresses. Further, a finite-elements model of the structure is developed and equivalent forces are added to this model. Having results of calculations, an optimal sequence of assembly and welding is selected and special measures to reduce and compensate welding deformations are developed and taken.

Keywords: residual welding deformations, longitudinal and transverse shortenings of welding joints, method of analytic dependences, finite elements method

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Authors: Natascha C. D'Amico, Enzo Grossi, Giovanni Valbusa, Ala Malasevschi, Gianpiero Cardone, Sergio Papa

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Purpose: To characterize, through a radiomic approach, the nature of areas classified PI-RADS (Prostate Imaging Reporting and Data System) 3/5, recognized in multiparametric prostate magnetic resonance with T2-weighted (T2w), diffusion and perfusion sequences with paramagnetic contrast. Methods and Materials: 24 cases undergoing multiparametric prostate MR and biopsy were admitted to this pilot study. Clinical outcome of the PI-RADS 3/5 was found through biopsy, finding 8 malignant tumours. The analysed images were acquired with a Philips achieva 1.5T machine with a CE- T2-weighted sequence in the axial plane. Semi-automatic tumour segmentation was carried out on MR images using 3DSlicer image analysis software. 45 shape-based, intensity-based and texture-based features were extracted and represented the input for preprocessing. An evolutionary algorithm (a TWIST system based on KNN algorithm) was used to subdivide the dataset into training and testing set and select features yielding the maximal amount of information. After this pre-processing 20 input variables were selected and different machine learning systems were used to develop a predictive model based on a training testing crossover procedure. Results: The best machine learning system (three-layers feed-forward neural network) obtained a global accuracy of 90% ( 80 % sensitivity and 100% specificity ) with a ROC of 0.82. Conclusion: Machine learning systems coupled with radiomics show a promising potential in distinguishing benign from malign tumours in PI-RADS 3/5 areas.

Keywords: machine learning, MR prostate, PI-Rads 3, radiomics

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Authors: Mateusz Janas

Abstract:

Innovative implementations in the micro, small, and medium-sized enterprises (MSME) sector are among the essential activities considering the current market realities, technological advancements, and digitization trends. MSMEs play a crucial role and significantly influence the economic conditions of countries, as their competitiveness directly impacts the global economy. Business development and investment in innovation and technology are integral parts of every modern enterprise's strategy, seeking to maintain and achieve a desired competitive position. The instability of the socio-economic environment, along with contemporary changes in artificial intelligence implementation and digitization, requires businesses to adopt increasingly newer solutions and actions. Enterprises must strive to survive in the global market and build competitive positions, especially in uncertain conditions. Being aware of the significance of innovative actions is crucial for MSMEs as it enables them to enhance their operations and expand their scope. It is essential for managers and executives of MSMEs to be focused on development and innovation, as their approach will also impact their employees, emphasizing results and maximizing the company's value. Managers of MSMEs must be aware of various threats, costs, opportunities, and gains that can arise from implementing new technical and organizational solutions. Businesses must view development as an integral part of their strategy and continuously strive for improvement.

Keywords: innovation, SME, develop, management

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Authors: Martynova Alina, Lyubov Buzoleva

Abstract:

Streptococcus pneumoniae is the causative agent of pneumonias and meningitids throught all the world. Having high genetic diversity, this microorganism can cause different clinical forms of pneumococcal infections and microbiologically it is really difficult diagnosed by routine methods. Also, epidemiological surveillance requires more developed methods of molecular typing because the recent method of serotyping doesn't allow to distinguish invasive and non-invasive isolates properly. Non-coding genome of bacteria seems to be the interesting source for seeking of highly distinguishable markers to discriminate the subspecies of such a variable bacteria as Streptococcus pneumoniae. Technically, we proposed scheme of discrimination of S.pneumoniae strains with amplification of non-coding region (SP_1932) with the following restriction with 2 types of enzymes of Alu1 and Mn1. Aim: This research aimed to compare different methods of typing and their application for molecular epidemiology purposes. Methods: we analyzed population of 100 strains of S.pneumoniae isolated from different patients by different molecular epidemiology methods such as pulse-field gel electophoresis (PFGE), restriction polymorphism analysis (RFLP) and multilolocus sequence typing (MLST), and all of them were compared with classic typing method as serotyping. The discriminative power was estimated with Simpson Index (SI). Results: We revealed that the most discriminative typing method is RFLP (SI=0,97, there were distinguished 42 genotypes).PFGE was slightly less discriminative (SI=0,95, we identified 35 genotypes). MLST is still the best reference method (SI=1.0). Classic method of serotyping showed quite weak discriminative power (SI=0,93, 24 genotypes). In addition, sensivity of RFLP was 100%, specificity was 97,09%. Conclusion: the most appropriate method for routine epidemiology surveillance is RFLP with non-coding region of Streptococcsu pneumoniae, then PFGE, though in some cases these results should be obligatory confirmed by MLST.

Keywords: molecular epidemiology typing, non-coding genome, Streptococcus pneumoniae, MLST

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Authors: Zainul A. Khan, Malik Z. Abdin, Jawaid A. Khan

Abstract:

Begomoviruses belonging to the family Geminiviridae, have single-stranded circular DNA genomes that are monopartite or bipartite. The large intergenic region (LIR) of the monopartite and common region (CR) of bipartite begomoviruses possess promoter activity in their genomes. In this study, we have characterized novel bidirectional promoters from Cotton leaf curl Burewala virus (CLCuBuV) genome using high-throughput software and analyzed with PlantCARE, PLACE, Cister and PlantPAN databases. The promoters (Rep and CP promoters) were assayed both in stable and transient expression systems in tobacco as well as cotton plants. Rep and CP-based promoters from the LIR sequence of CLCuBuV and 35S promoter of Cauliflower mosaic virus (CaMV) were tagged with β-glucuronidase (GUS) and green fluorescent protein (GFP) reporter genes to check the efficacy of the promoters. Histochemical staining of GUS in transformed tobacco (Nicotiana tabacum cv. Xanthi) leaves showed higher GUS expression driven by CLCuBuV Rep (complimentary sense) promoter as compared to conventional CaMV 35S promoter and CLCuBuV CP (virion sense) promoter, respectively. GUS activity in individual plant cells driven by CLCuBuV Rep, CLCuBuV CP, and CaMV 35S promoter were quantified through fluorometric GUS assay and reverse transcription quantitative real-time PCR (RT-qPCR). The expression level of GUS tagged with CLCuBuV Rep promoter in the transformed tobacco plants was obtained 2 to 4 fold higher than CaMV 35S promoter. When CLCuBuV CP promoter was used, lower expression level was monitored than that by CaMV 35S promoter. The expression of GFP-tagged with CLCuBuV promoters was also investigated through agroinfiltration. The CLCuBuV Rep promoters showed stronger consistent transient expression in the leaves of N. benthamiana, N. tabacum and Gossypium hirsutum plants when compared with CaMV 35S and CLCuBuV CP promoter.

Keywords: Begmovirus, bidirectional promoter, CaMV 35S promoter, GFP, GUS, qPCR

Procedia PDF Downloads 327

Authors: Mohammadjavad Palimi, D. Y. Li, E. Kuru

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Emulsion-based drilling fluids containing mineral oil are commonly used for drilling operations, which generate a lubricating film to prevent direct contact between moving metal parts, thus reducing friction, wear, and corrosion. For long-lasting lubrication, the thin lubricating film formed on the metal surface should possess good anti-wear and anti-corrosion capabilities. This study aims to investigate the effects of two additives, TERGITOL NP-9 and PEG-10 oleyl phosphate, acting as surfactant and corrosion inhibitor, respectively, on the tribo-corrosion behavior of 1018 carbon steel immersed in 5% KCl solution at room temperature. A pin-on-disc tribometer attached to an electrochemical system was used to investigate the corrosive wear of the steel immersed in emulsion-based fluids containing the surfactant and corrosion inhibitor. The wear track, surface chemistry and composition of the protective film formed on the steel surface were analyzed with an optical profilometer, SEM, and SEM-EDX. Results of the study demonstrate that the performance of the emulsion-based drilling fluids was significantly improved by the corrosion inhibitor by a remarkable reduction in corrosion, coefficient of friction (COF) and wear.

Keywords: corrosion inhibitor, emulsion-based drilling fluid, tribo-corrosion, friction, wear

Procedia PDF Downloads 66

Authors: H.-H. Doh, J.-M. Yu, Y.-J. Kwon, J.-H. Shin, H.-W. Kim, S.-H. Nam, D.-H. Lee

Abstract:

This paper suggests a decision tree based approach for flexible job shop scheduling with multiple process plans, i. e. each job can be processed through alternative operations, each of which can be processed on alternative machines. The main decision variables are: (a) selecting operation/machine pair; and (b) sequencing the jobs assigned to each machine. As an extension of the priority scheduling approach that selects the best priority rule combination after many simulation runs, this study suggests a decision tree based approach in which a decision tree is used to select a priority rule combination adequate for a specific system state and hence the burdens required for developing simulation models and carrying out simulation runs can be eliminated. The decision tree based scheduling approach consists of construction and scheduling modules. In the construction module, a decision tree is constructed using a four-stage algorithm, and in the scheduling module, a priority rule combination is selected using the decision tree. To show the performance of the decision tree based approach suggested in this study, a case study was done on a flexible job shop with reconfigurable manufacturing cells and a conventional job shop, and the results are reported by comparing it with individual priority rule combinations for the objectives of minimizing total flow time and total tardiness.

Keywords: flexible job shop scheduling, decision tree, priority rules, case study

Procedia PDF Downloads 352

Authors: Yujiang Wu

Abstract:

As electrical machine (e-machine) power density re-querulents become more stringent in vehicle electrification, mounting a temperature sensor for e-machine stator windings becomes increasingly difficult. This can lead to higher manufacturing costs, complicated harnesses, and reduced reliability. In this paper, we propose a deep-learning method for predicting electric machine winding temperature, which can either replace the sensor entirely or serve as a backup to the existing sensor. We compare the performance of our method, the stateful long short-term memory networks (LSTM) with truncated backpropagation through time (TBTT), with that of linear regression, as well as stateless LSTM with/without residual connection. Our results demonstrate the strength of combining stateful LSTM and TBTT in tackling nonlinear time series prediction problems with long sequence lengths. Additionally, in industrial applications, high-temperature region prediction accuracy is more important because winding temperature sensing is typically used for derating machine power when the temperature is high. To evaluate the performance of our algorithm, we developed a temperature-stratified MSE. We propose a simple but effective data preprocessing trick to improve the high-temperature region prediction accuracy. Our experimental results demonstrate the effectiveness of our proposed method in accurately predicting winding temperature, particularly in high-temperature regions, while also reducing manufacturing costs and improving reliability.

Keywords: deep learning, electrical machine, functional safety, long short-term memory networks (LSTM), thermal management, time series prediction

Procedia PDF Downloads 93