Search results for: Process Mining

Authors: Salma El Hajjami, Jamal Malki, Alain Bouju, Mohammed Berrada

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With the expansion of machine learning and data mining in the context of Big Data analytics, the common problem that affects data is class imbalance. It refers to an imbalanced distribution of instances belonging to each class. This problem is present in many real world applications such as fraud detection, network intrusion detection, medical diagnostics, etc. In these cases, data instances labeled negatively are significantly more numerous than the instances labeled positively. When this difference is too large, the learning system may face difficulty when tackling this problem, since it is initially designed to work in relatively balanced class distribution scenarios. Another important problem, which usually accompanies these imbalanced data, is the overlapping instances between the two classes. It is commonly referred to as noise or overlapping data. In this article, we propose an approach called: One Side Behavioral Noise Reduction (OSBNR). This approach presents a way to deal with the problem of class imbalance in the presence of a high noise level. OSBNR is based on two steps. Firstly, a cluster analysis is applied to groups similar instances from the minority class into several behavior clusters. Secondly, we select and eliminate the instances of the majority class, considered as behavioral noise, which overlap with behavior clusters of the minority class. The results of experiments carried out on a representative public dataset confirm that the proposed approach is efficient for the treatment of class imbalances in the presence of noise.

Keywords: machine learning, imbalanced data, data mining, big data

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Authors: Lennon Furtado, Sandro Oliveira

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The importance of an effective measurement program lies in the ability to control and predict what can be measured. Thus, the measurement program has the capacity to provide bases in decision-making to support the interests of an organization. Therefore, it is only possible to apply for an effective measurement program with a team of software engineers well trained in the measurement area. However, the literature indicates that are few computer science courses that have in their program the teaching of the software measurement process. And even these, generally present only basic theoretical concepts of said process and little or no measurement in practice, which results in the student's lack of motivation to learn the measurement process. In this context, according to some experts in software process improvements, one of the most used approaches to maintaining the motivation and commitment to software process improvements program is the use of the gamification. Therefore, this paper aims to present a proposal of teaching the measurement process by gamification. Which seeks to improve student motivation and performance in the assimilation of tasks related to software measurement, by incorporating elements of games into the practice of measurement process, making it more attractive for learning. And as a way of validating the proposal will be made a comparison between two distinct groups of 20 students of Software Quality class, a control group, and an experiment group. The control group will be the students that will not make use of the gamification proposal to learn software measurement process, while the experiment group, will be the students that will make use of the gamification proposal to learn software measurement process. Thus, this paper will analyze the objective and subjective results of each group. And as objective result will be analyzed the student grade reached at the end of the course, and as subjective results will be analyzed a post-course questionnaire with the opinion of each student about the teaching method. Finally, this paper aims to prove or refute the following hypothesis: If the gamification proposal to teach software measurement process does appropriate motivate the student, in order to attribute the necessary competence to the practical application of the measurement process.

Keywords: education, gamification, software measurement process, software engineering

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Authors: M. Farhaoui, M. Derraz

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In the drinking water treatment processes, the optimization of the treatment is an issue of particular concern. In general, the process consists of many units as settling, coagulation, flocculation, sedimentation, filtration and disinfection. The optimization of the process consists of some measures to decrease the managing and monitoring expenses and improve the quality of the produced water. The objective of this study is to provide water treatment operators with methods and practices that enable to attain the most effective use of the facility and, in consequence, optimize the of the cubic meter price of the treated water. This paper proposes a review on optimization of drinking water treatment process by analyzing all of the water treatment units and gives some solutions in order to maximize the water treatment performances without compromising the water quality standards. Some solutions and methods are performed in the water treatment plant located in the middle of Morocco (Meknes).

Keywords: coagulation process, optimization, turbidity removal, water treatment

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Authors: Mohamed T. Faheem Saidahmed, Ahmed M. Attiya Ibrahim, Basma GH. Elkilany

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This paper discusses the application of Time Delay Control (TDC) compensation technique in the juice extraction process in a sugar mill. The objective is to improve the control performance of the process and increase extraction efficiency. The paper presents the mathematical model of the juice extraction process and the design of the TDC compensation controller. Simulation results show that the TDC compensation technique can effectively suppress the time delay effect in the process and improve control performance. The extraction efficiency is also significantly increased with the application of the TDC compensation technique. The proposed approach provides a practical solution for improving the juice extraction process in sugar mills using MATLAB Processes.

Keywords: time delay control (TDC), exact and unique state space model, delay compensation, Smith predictor.

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Authors: Muhalim Muhalim

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Drawing on Lakoff’s theory of metaphor conceptualization, this article explores the conceptualization of language two writing (L2W) of ten students-teachers in Indonesia via metaphors. The ten postgraduate English language teaching students and at the same time (former) English teachers received seven days of intervention in teaching and learning L2. Using introspective log and focus group discussion, the results illuminate us that all participants are unanimous on perceiving L2W as process-oriented rather than product-oriented activity. Specifically, the metaphor conceptualizations exhibit three categories of process-oriented L2W: deliberate process, learning process, and problem-solving process. However, it has to be clarified from the outset that this categorization is not rigid because some of the properties of metaphors might belong to other categories. Results of the study and implications for English language teaching will be further discussed.

Keywords: metaphor conceptualisation, second language, learning writing, teaching writing

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Authors: Di Han, Lingfeng Li, Peixue Zhang, Yuzhuo Zhang

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Since natural gas extracted from the wellhead of a gas well, after passing through the throttle valve, causes a rapid decrease in temperature along with a decrease in pressure, which creates conditions for hydrate generation. In order to solve the problem of hydrate generation in the process of wellhead gathering, effective measures should be taken to prevent hydrate generation. In this paper, we firstly introduce the principle of natural gas throttling temperature drop and the theoretical basis of hydrate inhibitor injection calculation, and then use HYSYS software to simulate and calculate the three processes and determine the key process parameters. The hydrate control process applicable to the skid design of natural gas wellhead gathering skids was determined by comparing the hydrate control effect, energy consumption of key equipment and process adaptability.

Keywords: natural gas, hydrate control, skid design, HYSYS

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Authors: U. Sabura Banu, S. K. Lakshmanaprabu

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The improvement of meta-heuristic algorithm encourages control engineer to design an optimal controller for industrial process. Most real-world industrial processes are non-linear multivariable process with high interaction. Even in sub-process unit, thousands of loops are available mostly interacting in nature. Optimal controller design for such process are still challenging task. Closed loop controller design by multiloop PID involves a tedious procedure by performing interaction study and then PID auto-tuning the loop with higher interaction. Finally, detuning the controller to accommodate the effects of the other process variables. Fractional order PID controllers are replacing integer order PID controllers recently. Design of Multiloop Fractional Order (MFO) PID controller is still more complicated. Cuckoo algorithm, a swarm intelligence technique is used to optimally tune the MFO PID controller with easiness minimizing Integral Time Absolute Error. The closed loop performance is tested under servo, regulatory and servo-regulatory conditions.

Keywords: Cuckoo algorithm, mutliloop fractional order PID controller, two Interacting conical tank process

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Authors: Kareem Saber

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Many products’ design instructors search for how to help students to develop their designs simply by reducing design stages and extrapolating simple design process forms to achieve design creativity. So, the researcher extrapolated a new design process form called “hierarchical design” which reduced design process into three stages and he had tried that methodology on about two hundred students. That trial had led to great results as students could develop their designs which characterized by creativity and innovation. That proved the success and effectiveness of the proposed methodology.

Keywords: mind mapping, morphological analysis, product design, design process

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Authors: Melvin Sethobya, Sithule Xanga, Sechaba Lenong, Lunga Nolakana, Gbenga Adesola

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Mining has been the cornerstone of the South African economy for the last century. Most of the gold mining in South Africa was conducted within the Witwatersrand basin, which contributed to the rapid growth of the city of Johannesburg and capitulated the city to becoming the business and wealth capital of the country. But with gradual depletion of resources, a stoppage in the extraction of underground water from mines and other factors relating to survival of the mining operations over a lengthy period, most of the mines were abandoned and left to pollute the local waterways and groundwater with toxins, heavy metal residue and increased acid mine drainage ensued. The Department of Mineral Resources and Energy commissioned a project whose aim is to monitor, maintain, and mitigate the adverse environmental impacts of polluted water mine water flowing into local streams affecting local ecosystems and livelihoods downstream. As part of mitigation efforts, the diagnosis and monitoring of groundwater or surface water polluted sites has become important. Geophysical surveys, in particular, Resistivity and Magnetics surveys, were selected as some of most suitable techniques for investigation of local ingress points along of one the major streams cutting through the Witwatersrand basin, namely the Blesbokspruit, which is found in the eastern part of the basin. The aim of the surveys was to provide information that could be used to assist in determining possible water loss/ ingress from the Blesbokspriut stream. Modelling of geophysical surveys results offered an in-depth insight into the interaction and pathways of polluted water through mapping of possible ingress channels near the Blesbokspruit. The resistivity - depth profile of the surveyed site exhibit a three(3) layered model with low resistivity values (10 to 200 Ω.m) overburden, which is underlain by a moderate resistivity weathered layer (>300 Ω.m), which sits on a more resistive crystalline bedrock (>500 Ω.m). Two locations of potential ingress channels were mapped across the two traverses at the site. The magnetic survey conducted at the site mapped a major NE-SW trending regional linearment with a strong magnetic signature, which was modeled to depth beyond 100m, with the potential to act as a conduit for dispersion of stream water away from the stream, as it shared a similar orientation with the potential ingress channels as mapped using the resistivity method.

Keywords: eletrictrical resistivity, magnetics survey, blesbokspruit, ingress

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Authors: Abdullah Khan, Per Redelius, Nicole Kringos

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The breaking and coalescence process in bitumen emulsion strongly influence the performance of the cold mix asphalt (CMA) and this phase separation process is affected by the physio-chemical changes happening at the bitumen/water interface. In this paper, coalescence experiments of two bitumen droplets in an emulsion environment have been carried out by a newly developed test procedure. In this study, different types of emulsifiers were selected to understand the coalescence process with respect to changes in the water phase surface tension due to addition of different surfactants and other additives such as salts. The research showed that the relaxation kinetics of bitumen droplets varied with the type of emulsifier, its concentration as well as with and without presence of salt in the water phase. Moreover, kinetics of the coalescence process was also investigated with the temperature variation.

Keywords: bitumen emulsions, breaking and coalescence, cold mix asphalt, emulsifiers, relaxation, salts

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Authors: Ali Moarrefzadeh

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In metalworking, rolling is a metal forming process in which metal stock is passed through a pair of rolls. Rolling is classified according to the temperature of the metal rolled. If the temperature of the metal is above its recrystallization temperature, then the process is termed as hot rolling. If the temperature of the metal is below its recrystallization temperature, the process is termed as cold rolling. In terms of usage, hot rolling processes more tonnage than any other manufacturing process, and cold rolling processes the most tonnage out of all cold working processes. This article describes the use of advanced tubing inspection NDT methods for boiler and heat exchanger equipment in the petrochemical industry to supplement major turnaround inspections. The methods presented include remote field eddy current, magnetic flux leakage, internal rotary inspection system and eddy current.

Keywords: hot forming, cold forming, metal, rolling, simulation

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Authors: Parul Sahu

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In recent years, seawater desalination has been emerged as a potential resource to circumvent water scarcity, especially in coastal regions. Among the various methods, thermal evaporation or distillation and membrane operations like Reverse Osmosis (RO) has been exploited at commercial scale. However, the energy cost and maintenance expenses associated with these processes remain high. In this context Freeze Desalination (FD), subjected to the availability of low cost refrigeration, offers an exciting alternative. Liquefied Natural Gas (LNG) regasification terminals provide an opportunity to utilize the refrigeration available with regasification of LNG. This work presents the conceptualization and development of a process scheme integrating the ice and hydrate based FD to the LNG regasification process. This integration overcomes the high energy demand associated with FD processes by utilizing the refrigeration associated with LNG regasification. An optimal process scheme was obtained by performing process simulation using ASPEN PLUS simulator. The results indicated the new proposed process requires only 1 kWh/m³ of energy with the utilization of maximum refrigeration. In addition, a sensitivity analysis was also performed to study the effect of various process parameters on water recovery and energy consumption for the proposed process. The results show that the energy consumption decreases by 30% with an increase in water recovery from 30% to 60%. However, due to operational limitations associated with ice and hydrate handling in seawater, the water recovery cannot be maximized but optimized. The proposed process can be potentially used to desalinate seawater in integration with LNG regasification terminal.

Keywords: freeze desalination, liquefied natural gas regasification, process simulation, refrigeration

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Authors: Nikolaj Troels Graf Von Malotky, Robin Nicolay, Alke Martens

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There exist a plethora of architectures for ITSs (Intelligent Tutoring Systems). A thorough analysis and comparison of the architectures revealed, that in most cases the architecture extensions are evolutionary grown, reflecting state of the art trends of each decade. However, from the perspective of software engineering, the main aspect of an ITS has not been reflected in any of these architectures, yet. From the perspective of cognitive research, the construction of the teaching process is what makes an ITS 'intelligent' regarding the spectrum of interaction with the students. Thus, in our approach, we focus on a behavior based architecture, which is based on the main teaching processes. To create a new general architecture for ITS, we have to define the prerequisites. This paper analyzes the current state of the existing architectures and derives rules for the behavior of ITS. It is presenting a teaching process for ITSs to be used together with the architecture.

Keywords: intelligent tutoring, ITS, tutoring process, system architecture, interaction process

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Authors: Rahmad Wisnu Wardana, Eakachai Warinsiriruk, Sutep Joy-A-Ka

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Selecting the most suitable welding process usually depends on experiences or common application in similar companies. However, this approach generally ignores many criteria that can be affecting the suitable welding process selection. Therefore, knowledge automation through knowledge-based systems will significantly improve the decision-making process. The aims of this research propose integrated data envelopment analysis (DEA) and fuzzy credibility constrained programming approach for identifying the best welding process for stainless steel storage tank in the food and beverage industry. The proposed approach uses fuzzy concept and credibility measure to deal with uncertain data from experts' judgment. Furthermore, 12 parameters are used to determine the most appropriate welding processes among six competitive welding processes.

Keywords: welding process selection, data envelopment analysis, fuzzy credibility constrained programming, storage tank

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Authors: Ramlan Jantan, Norfadilah Kamaruddin, Shahriman Zainal Abidin

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In this era of technology, the co-creation method has become a new development trend. In this light, most design businesses have currently transformed their development strategy from being goods-dominant into service-dominant where more attention is given to the end-users and their roles in the development process. As a result, the conventional development process has been replaced with a more cooperative one. Consequently, numerous studies have been conducted to explore the extension of co-creation method in the design development process and most studies have focused on issues found during the production process. In the meantime, this study aims to investigate potential values established during the pre-production process, which is also known as the ‘circumstances value creation’. User involvement is questioned and crucially debate at the entry level of pre-production process in value in-exchange jointly spheres; thus user experiences took place. Thus, this paper proposed a potential framework of the co-creation method for Malaysian interactive product development. The framework is formulated from both parties involved: the users and designers. The framework will clearly give an explanation of the value of the co-creation method, and it could assist relevant design industries/companies in developing a blueprint for the design process. This paper further contributes to the literature on the co-creation of value and digital ecosystems.

Keywords: co-creation method, co-creation framework, co-creation, co-production

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Authors: Revoti Prasad Bora, Saurabh Yadav, Nikita Katyal

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In the context of educational data mining, the use case of extracting information from images containing both text and diagrams is of high importance. Hence, document analysis requires the extraction of diagrams from such images and processes the text and diagrams separately. To the author’s best knowledge, none among plenty of approaches for extracting tables, figures, etc., suffice the need for real-time processing with high accuracy as needed in multiple applications. In the education domain, diagrams can be of varied characteristics viz. line-based i.e. geometric diagrams, chemical bonds, mathematical formulas, etc. There are two broad categories of approaches that try to solve similar problems viz. traditional computer vision based approaches and deep learning approaches. The traditional computer vision based approaches mainly leverage connected components and distance transform based processing and hence perform well in very limited scenarios. The existing deep learning approaches either leverage YOLO or faster-RCNN architectures. These approaches suffer from a performance-accuracy tradeoff. This paper proposes a U-Net based architecture that formulates the diagram extraction as a segmentation problem. The proposed method provides similar accuracy with a much faster extraction time as compared to the mentioned state-of-the-art approaches. Further, the segmentation mask in this approach allows the extraction of diagrams of irregular shapes.

Keywords: computer vision, deep-learning, educational data mining, faster-RCNN, figure extraction, image segmentation, real-time document analysis, text extraction, U-Net, YOLO

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Authors: Abioye A. Oyenuga, Rao Bhamidiarri

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Hurling a successful Construction and Demolition Waste (C&DW) recycling operation around the globe is a challenge today, predominantly because secondary materials markets are yet to be integrated. Reducing, Reusing and recycling of (C&DW) have been employed over the years, and various techniques have been investigated. However, the economic and environmental viability of its application seems limited. This paper discusses the costs and benefits in using secondary materials and focus on investigating reuse and recycling process for five major types of construction materials: concrete, metal, wood, cardboard/paper, and plasterboard. Data obtained from demolition specialist and contractors are considered and evaluated. With the date source, the research paper found that construction material recovery process fully incorporate the 3R’s process and shows how energy recovery by means of 3R's principles can be evaluated. This scrutiny leads to the empathy of grand challenges in construction material recovery process. Recommendations to deepen material recovery process are also discussed.

Keywords: construction and demolition waste (C&DW), 3R concept, recycling, reuse, waste management, UK

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Authors: H. Z. Ulukan, E. Demircioğlu, M. Erol Genevois

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The scope of this paper and the aim of proposed model were to apply monetary Input –Output (I-O) analysis to point out the importance of reusing know-how and other requirements in order to reduce the production costs in a manufacturing process for a laptop computer. I-O approach using the monetary input-output model is employed to demonstrate the impacts of different factors in a manufacturing process. A sensitivity analysis showing the correlation between these different factors is also presented. It is expected that the recommended model would have an advantageous effect in the cost minimization process.

Keywords: input-output analysis, monetary input-output model, manufacturing process, laptop computer

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Authors: Nareshkumar Harale, B. B. Meshram

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The continued exponential growth of successful cyber intrusions against today’s businesses has made it abundantly clear that traditional perimeter security measures are no longer adequate and effective. We evolved the network trust architecture from trust-untrust to Zero-Trust, With Zero Trust, essential security capabilities are deployed in a way that provides policy enforcement and protection for all users, devices, applications, data resources, and the communications traffic between them, regardless of their location. Information exchange over the Internet, in spite of inclusion of advanced security controls, is always under innovative, inventive and prone to cyberattacks. TCP/IP protocol stack, the adapted standard for communication over network, suffers from inherent design vulnerabilities such as communication and session management protocols, routing protocols and security protocols are the major cause of major attacks. With the explosion of cyber security threats, such as viruses, worms, rootkits, malwares, Denial of Service attacks, accomplishing efficient and effective intrusion detection and prevention is become crucial and challenging too. In this paper, we propose a design and analysis model for next generation network intrusion detection and protection system as part of layered security strategy. The proposed system design provides intrusion detection for wide range of attacks with layered architecture and framework. The proposed network intrusion classification framework deals with cyberattacks on standard TCP/IP protocol, routing protocols and security protocols. It thereby forms the basis for detection of attack classes and applies signature based matching for known cyberattacks and data mining based machine learning approaches for unknown cyberattacks. Our proposed implemented software can effectively detect attacks even when malicious connections are hidden within normal events. The unsupervised learning algorithm applied to network audit data trails results in unknown intrusion detection. Association rule mining algorithms generate new rules from collected audit trail data resulting in increased intrusion prevention though integrated firewall systems. Intrusion response mechanisms can be initiated in real-time thereby minimizing the impact of network intrusions. Finally, we have shown that our approach can be validated and how the analysis results can be used for detecting and protection from the new network anomalies.

Keywords: network intrusion detection, network intrusion prevention, association rule mining, system analysis and design

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Authors: Osman Turkoglu, Alvin Estilo, Ritu Gupta, Liliam Pineda-Salgado, Rajesh Pandey

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Background: Hepatotoxicity can be linked to a variety of clinical symptoms and histopathological signs, posing a great challenge in the surveillance of suspected drug-induced liver injury (DILI) cases in the safety database. Additionally, the majority of such cases are rare, idiosyncratic, highly unpredictable, and tend to demonstrate unique individual susceptibility; these qualities, in turn, lend to a pharmacovigilance monitoring process that is often tedious and time-consuming. Objective: Develop a multifactorial algorithm to assist pharmacovigilance physicians in identifying high-risk hepatotoxicity cases associated with DILI from the sponsor’s safety database (Argus). Methods: Multifactorial selection criteria were established using Structured Query Language (SQL) and the TIBCO Spotfire® visualization tool, via a combination of word fragments, wildcard strings, and mathematical constructs, based on Hy’s law criteria and pattern of injury (R-value). These criteria excluded non-eligible cases from monthly line listings mined from the Argus safety database. The capabilities and limitations of these criteria were verified by comparing a manual review of all monthly cases with system-generated monthly listings over six months. Results: On an average, over a period of six months, the algorithm accurately identified 92% of DILI cases meeting established criteria. The automated process easily compared liver enzyme elevations with baseline values, reducing the screening time to under 15 minutes as opposed to multiple hours exhausted using a cognitively laborious, manual process. Limitations of the algorithm include its inability to identify cases associated with non-standard laboratory tests, naming conventions, and/or incomplete/incorrectly entered laboratory values. Conclusions: The newly developed multifactorial algorithm proved to be extremely useful in detecting potential DILI cases, while heightening the vigilance of the drug safety department. Additionally, the application of this algorithm may be useful in identifying a potential signal for DILI in drugs not yet known to cause liver injury (e.g., drugs in the initial phases of development). This algorithm also carries the potential for universal application, due to its product-agnostic data and keyword mining features. Plans for the tool include improving it into a fully automated application, thereby completely eliminating a manual screening process.

Keywords: automation, drug-induced liver injury, pharmacovigilance, post-marketing

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Authors: Sawsan J. Al-Husseini, Talib A. Dosa

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Transformational leadership has been identified as the most important factor affecting innovation and knowledge sharing; it leads to increased goal-directed behavior exhibited by followers and thus to enhanced performance and innovation for the organization. However, there is a lack of models linking transformational leadership, knowledge sharing, and process innovation within higher education (HE) institutions in general within developing countries, particularly in Iraq. This research aims to examine the mediating role of knowledge sharing in the transformational leadership and process innovation relationship. A quantitative approach was taken and 254 usable questionnaires were collected from public HE institutions in Iraq. Structural equation modelling with AMOS 22 was used to analyze the causal relationships among factors. The research found that knowledge sharing plays a pivotal role in the relationship between transformational leadership and process innovation, and that transformational leadership would be ideal in an educational context, promoting knowledge sharing activities and influencing process innovation in the public HE in Iraq. The research has developed some guidelines for researchers as well as leaders and provided evidence to support the use of TL to increase process innovation within HE environment in developing countries, particularly in Iraq.

Keywords: transformational leadership, knowledge sharing, process innovation, structural equation modelling, developing countries

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Authors: Jeremy Jenrette, Z. Y. C. Liu, Pranav Chimote, Edward Fox, Trevor Hastie, Francesco Ferretti

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Suitable shark conservation depends on well-informed population assessments. Direct methods such as scientific surveys and fisheries monitoring are adequate for defining population statuses, but species-specific indices of abundance and distribution coming from these sources are rare for most shark species. We can rapidly fill these information gaps by boosting media-based remote monitoring efforts with machine learning and automation. We created a database of shark images by sourcing 24,546 images covering 219 species of sharks from the web application spark pulse and the social network Instagram. We used object detection to extract shark features and inflate this database to 53,345 images. We packaged object-detection and image classification models into a Shark Detector bundle. We developed the Shark Detector to recognize and classify sharks from videos and images using transfer learning and convolutional neural networks (CNNs). We applied these models to common data-generation approaches of sharks: boosting training datasets, processing baited remote camera footage and online videos, and data-mining Instagram. We examined the accuracy of each model and tested genus and species prediction correctness as a result of training data quantity. The Shark Detector located sharks in baited remote footage and YouTube videos with an average accuracy of 89\%, and classified located subjects to the species level with 69\% accuracy (n =\ eight species). The Shark Detector sorted heterogeneous datasets of images sourced from Instagram with 91\% accuracy and classified species with 70\% accuracy (n =\ 17 species). Data-mining Instagram can inflate training datasets and increase the Shark Detector’s accuracy as well as facilitate archiving of historical and novel shark observations. Base accuracy of genus prediction was 68\% across 25 genera. The average base accuracy of species prediction within each genus class was 85\%. The Shark Detector can classify 45 species. All data-generation methods were processed without manual interaction. As media-based remote monitoring strives to dominate methods for observing sharks in nature, we developed an open-source Shark Detector to facilitate common identification applications. Prediction accuracy of the software pipeline increases as more images are added to the training dataset. We provide public access to the software on our GitHub page.

Keywords: classification, data mining, Instagram, remote monitoring, sharks

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Authors: Ming Liu, Chong Wu, Bingquan Liu, Lei Chen

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Internet users have to face the massive amount of textual data every day. Organizing texts into categories can help users dig the useful information from large-scale text collection. Clustering, in fact, is one of the most promising tools for categorizing texts due to its unsupervised characteristic. Unfortunately, most of traditional clustering algorithms lose their high qualities on large-scale text collection. This situation mainly attributes to the high- dimensional vectors generated from texts. To effectively and efficiently cluster large-scale text collection, this paper proposes a vector reconstruction based clustering algorithm. Only the features that can represent the cluster are preserved in cluster’s representative vector. This algorithm alternately repeats two sub-processes until it converges. One process is partial tuning sub-process, where feature’s weight is fine-tuned by iterative process. To accelerate clustering velocity, an intersection based similarity measurement and its corresponding neuron adjustment function are proposed and implemented in this sub-process. The other process is overall tuning sub-process, where the features are reallocated among different clusters. In this sub-process, the features useless to represent the cluster are removed from cluster’s representative vector. Experimental results on the three text collections (including two small-scale and one large-scale text collections) demonstrate that our algorithm obtains high quality on both small-scale and large-scale text collections.

Keywords: vector reconstruction, large-scale text clustering, partial tuning sub-process, overall tuning sub-process

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Authors: Serdal Akyüz, Halit Turan, Mehmet Öztürk

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The future security environment will have new battlefield and enemies. The boundaries of battlefield and the identity of enemies cannot be noticed easily. The politicians may not want to lose their soldiers in very risky operations. This approach will pave the way for smart machines like war robots and new drones. These machines will have the decision-making ability and act simultaneously. This ability can change the military targeting process. Military targeting process (MTP) benefits from a wide scope of lethal and non-lethal weapons to reach an intended end-state. This process is now managed by people but in the future smart machines can do it by themselves. At first sight, this development seems useful for humanity owing to decrease the casualties in war. Using robots -which can decide, detect, deliver and asses without human support- for homeland security and against terrorist has very crucial risks and threats. Besides, it can decrease the havoc but also increase the collateral damages. This paper examines the current use of smart war machines, military targeting process and presents a new approach to MTP from lethal autonomy concept's point of view.

Keywords: the autonomous weapon systems, the lethal autonomy, military targeting process (MTP)

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Authors: Hacene Benkhoula, Mohamed Badreddine Benabdella, Hamid Bouzeboudja, Abderrahmane Asraoui

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The wind is a random variable difficult to master, for this, we developed a mathematical and statistical methods enable to modeling and forecast wind power. Gaussian Processes (GP) is one of the most widely used families of stochastic processes for modeling dependent data observed over time, or space or time and space. GP is an underlying process formed by unrecognized operator’s uses to solve a problem. The purpose of this paper is to present how to forecast wind power by using the GP. The Gaussian process method for forecasting are presented. To validate the presented approach, a simulation under the MATLAB environment has been given.

Keywords: wind power, Gaussien process, modelling, forecasting

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Authors: Sheetal Kumar Parwar, J. Deb Barma, A. Majumder

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Submerged arc welding is a very complex process. It is a very efficient and high performance welding process. In this present study an attempt have been done to reduce the welding distortion by increased amount of oxide flux through TiO2 in submerged arc welding process. Care has been taken to avoid the excessiveness of the adding agent for attainment of significant results. Data Envelopment Analysis (DEA) based BAT algorithm is used for the parametric optimization purpose in which DEA Data Envelopment Analysis is used to convert multi response parameters into a single response parameter. The present study also helps to know the effectiveness of the addition of TiO2 in active flux during submerged arc welding process.

Keywords: BAT algorithm, design of experiment, optimization, submerged arc welding

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Authors: K. Raghu, M. N. Vathhsala, Naveen Aradya, Sharth

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River sand is the most preferred fine aggregate for mortar and concrete. River sand is a product of natural weathering of rocks over a period of millions of years and is mined from river beds. Sand mining has disastrous environmental consequences. The excessive mining of river bed is creating an ecological imbalance. This has lead to have restrictions imposed by ministry of environment on sand mining. Driven by the acute need for sand, stone dust or manufactured sand prepared from the crushing and screening of coarse aggregate is being used as sand in the recent past. However manufactured sand is also a natural material and has quarrying and quality issues. To reduce the burden on the environment, alternative materials to be used as fine aggregates are being extensively investigated all over the world. Looking to the quantum of requirements, quality and properties there has been a global consensus on a material – Granulated slags. Granulated slag has been proven as a suitable material for replacing natural sand / crushed fine aggregates. In developed countries, the use of granulated slag as fine aggregate to replace natural sand is well established and is in regular practice. In the present paper Granulated slag has been experimented for usage in mortar. Slags are the main by-products generated during iron and steel production in the steel industry. Over the past decades, the steel production has increased and, consequently, the higher volumes of by-products and residues generated which have driven to the reuse of these materials in an increasingly efficient way. In recent years new technologies have been developed to improve the recovery rates of slags. Increase of slags recovery and use in different fields of applications like cement making, construction and fertilizers help in preserving natural resources. In addition to the environment protection, these practices produced economic benefits, by providing sustainable solutions that can allow the steel industry to achieve its ambitious targets of “zero waste” in coming years. Slags are generated at two different stages of steel production, iron making and steel making known as BF(Blast Furnace) slag and steel slag respectively. The slagging agent or fluxes, such as lime stone, dolomite and quartzite added into BF or steel making furnaces in order to remove impurities from ore, scrap and other ferrous charges during smelting. The slag formation is the result of a complex series of physical and chemical reactions between the non-metallic charge(lime stone, dolomite, fluxes), the energy sources(coal, coke, oxygen, etc.) and refractory materials. Because of the high temperatures (about 15000 C) during their generation, slags do not contain any organic substances. Due to the fact that slags are lighter than the liquid metal, they float and get easily removed. The slags protect the metal bath from atmosphere and maintain temperature through a kind of liquid formation. These slags are in liquid state and solidified in air after dumping in the pit or granulated by impinging water systems. Generally, BF slags are granulated and used in cement making due to its high cementious properties, and steel slags are mostly dumped due to unfavourable physio-chemical conditions. The increasing dump of steel slag not only occupies a plenty of land but also wastes resources and can potentially have an impact on the environment due to water pollution. Since BF slag contains little Fe and can be used directly. BF slag has found a wide application, such as cement production, road construction, Civil Engineering work, fertilizer production, landfill daily cover, soil reclamation, prior to its application outside the iron and steel making process.

Keywords: steel slag, river sand, granulated slag, environmental

Procedia PDF Downloads 245

Authors: W. Schellong

Abstract:

Industry accounts for one-third of global final energy demand. Crossover technologies (e.g. motors, pumps, process heat, and air conditioning) play an important role in improving energy efficiency. These technologies are used in many applications independent of the production branch. Especially electrical power is used by drives, pumps, compressors, and lightning. The paper demonstrates the algorithm of the energy analysis by some selected case studies for typical industrial processes. The energy analysis represents an essential part of energy management systems (EMS). Generally, process control system (PCS) can support EMS. They provide information about the production process, and they organize the maintenance actions. Combining these tools into an integrated process allows the development of an energy critical equipment strategy. Thus, asset and energy management can use the same common data to improve the energy efficiency.

Keywords: crossover technologies, data management, energy analysis, energy efficiency, process control

Procedia PDF Downloads 213

Authors: Chomba Kalunga

Abstract:

Many developing countries have a rich endowment of natural resources. Yet, amidst that wealth, living standards remain poor. At the same time, international markets have been surged with an increase in copper prices in the last twenty years. This is a presentation of the findings on the causal economic impact of Zambia’s copper mines, a country located in sub-Saharan Africa endowed with vast copper deposits on living standards using household data from 1996 to 2010, exploiting an episode where the copper prices on the international market were rising. Using an Instrumental Variable approach and controlling for constituency-level and microeconomic factors, the results show a significant impact of copper production on living standards. After splitting the constituencies close to and far away from the nearest mine, the results document that constituencies close to the mines benefited significantly from the increase in copper production, compared to their counterparts through increased levels of employment. Finally, the results are not consistent with the natural resource curse hypothesis; findings show a positive causal relationship between the presence of natural resources and socioeconomic outcomes in less developed countries, particularly for constituencies close to the mines in Zambia. Some key policy implications follow from the findings. The finding that increased copper production led to an increase in employment suggests that, in Zambias’ context, policies that promote local employment may be more beneficial to residents. Meaning that it is government policies that can help improve the living standards were government needs to work towards making this impact more substantial.

Keywords: copper prices, local development, mining, natural resources

Procedia PDF Downloads 212

Authors: Negin Bayat, Nahid HasanZadeh

Abstract:

Effluents of different industries such as metalworking, battery industry, mining, including heavy metal are considered problematic issues for both humans and the environment. These heavy metals include cadmium, copper, zinc, nickel, chromium, cyanide, lead, etc. Different physicochemical and biological methods are used to remove heavy metals, such as sedimentation, coagulation, flotation, chemical precipitation, filtration, membrane processes (reverse osmosis and nanofiltration), ion exchange, biological methods, adsorption with activated carbon, etc. These methods are generally either expensive or ineffective. In recent years, considerable attention has been given to the removal of heavy metal ions from solution by absorption using discarded and low-cost materials. In this study, nickel removal using an adsorption process by eucalyptus powdered leaves and poplar ash was investigated. This is an applied study. The effect of various parameters on metal removal, such as pH, amount of adsorbent, contact time, and stirring speed, was studied using a discontinuous method. This research was conducted in aqueous solutions on the laboratory scale. Then, optimum absorption conditions were obtained. Then, the study was conducted on real wastewater samples. In addition, the nickel concentration in the wastewater before and after the absorption process was measured. In all experiments, the remaining nickel was measured using an atomic absorption spectrometry device at 382 nm wavelength after an appropriate time and filtration. The results showed that increasing both adsorbent and pH parameters increase the metal removal rate. Nickel removal increased at the first 60 minutes. Then, the absorption rate remained constant and reached equilibrium. A desired removal rate with 40 mg in 100 ml adsorbent solution at pH = 9.5 was observed. According to the obtained results, the best absorption rate was observed at 40 mg dose using a combination of eucalyptus leaves and poplar ash in this study, which was equal to 99.76%. Thus, this combined method can be used as an inexpensive and effective absorbent for the removal of nickel from aqueous solutions.

Keywords: absorption, wastewater, nickel, poplar ash, eucalyptus leaf, treatment

Procedia PDF Downloads 22