Search results for: Gaussian process

Authors: Naime Boudemagh

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In this work, we aim to improve the detection performances of radar systems. To this end, we propose and analyze a novel censoring technique of undesirable samples, of priori unknown positions, that may be present in the environment under investigation. Therefore, we consider heterogeneous backgrounds characterized by the presence of some irregularities such that clutter edge transitions and/or interfering targets. The proposed detector, termed automatic censoring constant false alarm (AC-CFAR), operates exclusively in a Gaussian background. It is built to allow the segmentation of the environment to regions and switch automatically to the appropriate detector; namely, the cell averaging CFAR (CA-CFAR), the censored mean level CFAR (CMLD-CFAR) or the order statistic CFAR (OS-CFAR). Monte Carlo simulations show that the AC-CFAR detector performs like the CA-CFAR in a homogeneous background. Moreover, the proposed processor exhibits considerable robustness in a heterogeneous background.

Keywords: CFAR, automatic censoring, heterogeneous environments, radar systems

Procedia PDF Downloads 603

Authors: Vesna Bosilj Vukšić, Darija Ivandić Vidović, Ljubica Milanović Glavan

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Information technology plays an irreplaceable role in introducing and improving business process orientation in a company. It enables implementation of the theoretical concept, measurement of results achieved and undertaking corrective measures aimed at improvements. Information technology is a key concept in the development and implementation of the business process management systems as it establishes a connection to business operations. Both in the literature and practice, insurance companies are often seen as highly process oriented due to the nature of their business and focus on customers. They are also considered leaders in using information technology for business process management. The research conducted aimed to investigate whether the perceived leadership status of insurance companies is well deserved, i.e. to establish the level of process orientation and explore the practice of information technology use in insurance companies in the region. The main instrument for primary data collection within this research was an electronic survey questionnaire sent to the management of insurance companies in the Republic of Croatia, Bosnia and Herzegovina, Slovenia, Serbia and Macedonia. The conducted research has shown that insurance companies have a satisfactory level of process orientation, but that there is also a huge potential for improvement, especially in the segment of information technology and its connection to business processes.

Keywords: business processes management, process orientation, information technology, insurance companies

Procedia PDF Downloads 383

Authors: Youngmin Kim, Jae-Hwan Ahn, Seog-Ku Kim, Hye-Cheol Oh, Bokjin Lee, Hee-Jun Kang

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The high energy consuming processes such as advanced oxidation and reverse osmosis are used as a reuse process. This study aims at developing an energy efficient reuse process by combination of nanofiltration (NF) and capacitive deionization processes (CDI) processes. Lab scale experiments were conducted by using effluents from a wastewater treatment plant located at Koyang city in Korea. Commercial NF membrane (NE4040-70, Toray Ltd.) and CDI module (E40, Siontech INC.) were tested in series. The pollutant removal efficiencies were evaluated on the basis of Korean water quality criteria for water reuse. In addition, the energy consumptions were also calculated. As a result, the hybrid process showed lower energy consumption than conventional reverse osmosis process even though its effluent did meet the Korean standard. Consequently, this study suggests that the hybrid process is feasible for the energy efficient water reuse.

Keywords: capacitive deionization, energy efficient process, nanofiltration, water reuse

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Authors: Pongchanun Luangpaiboon, Wanwisa Sarasang

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In this paper, a performance of shuffled frog leaping algorithm was investigated on the stealth laser dicing process. Effect of problem on the performance of the algorithm was based on the tolerance of meandering data. From the customer specification it could be less than five microns with the target of zero microns. Currently, the meandering levels are unsatisfactory when compared to the customer specification. Firstly, the two-level factorial design was applied to preliminary study the statistically significant effects of five process variables. In this study one influential process variable is integer. From the experimental results, the new operating condition from the algorithm was superior when compared to the current manufacturing condition.

Keywords: stealth laser dicing process, meandering, meta-heuristics, shuffled frog leaping algorithm

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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: Lakshmidevi Sreeramareddy, Komalpreet Kaur, Nane Pothier

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Graphical-based passwords have existed for decades. Their major advantage is that they are easier to remember than an alphanumeric password. However, their disadvantage (especially recognition-based passwords) is the smaller password space, making them more vulnerable to brute force attacks. Graphical passwords are also highly susceptible to the shoulder-surfing effect. The gesture-based password method that we developed is a grid-free, template-free method. In this study, we evaluated the gesture-based passwords for usability and vulnerability. The results of the study are significant. We developed a gesture-based password application for data collection. Two modes of data collection were used: Creation mode and Replication mode. In creation mode (Session 1), users were asked to create six different passwords and reenter each password five times. In replication mode, users saw a password image created by some other user for a fixed duration of time. Three different duration timers, such as 5 seconds (Session 2), 10 seconds (Session 3), and 15 seconds (Session 4), were used to mimic the shoulder-surfing attack. After the timer expired, the password image was removed, and users were asked to replicate the password. There were 74, 57, 50, and 44 users participated in Session 1, Session 2, Session 3, and Session 4 respectfully. In this study, the machine learning algorithms have been applied to determine whether the person is a genuine user or an imposter based on the password entered. Five different machine learning algorithms were deployed to compare the performance in user authentication: namely, Decision Trees, Linear Discriminant Analysis, Naive Bayes Classifier, Support Vector Machines (SVMs) with Gaussian Radial Basis Kernel function, and K-Nearest Neighbor. Gesture-based password features vary from one entry to the next. It is difficult to distinguish between a creator and an intruder for authentication. For each password entered by the user, four features were extracted: password score, password length, password speed, and password size. All four features were normalized before being fed to a classifier. Three different classifiers were trained using data from all four sessions. Classifiers A, B, and C were trained and tested using data from the password creation session and the password replication with a timer of 5 seconds, 10 seconds, and 15 seconds, respectively. The classification accuracies for Classifier A using five ML algorithms are 72.5%, 71.3%, 71.9%, 74.4%, and 72.9%, respectively. The classification accuracies for Classifier B using five ML algorithms are 69.7%, 67.9%, 70.2%, 73.8%, and 71.2%, respectively. The classification accuracies for Classifier C using five ML algorithms are 68.1%, 64.9%, 68.4%, 71.5%, and 69.8%, respectively. SVMs with Gaussian Radial Basis Kernel outperform other ML algorithms for gesture-based password authentication. Results confirm that the shorter the duration of the shoulder-surfing attack, the higher the authentication accuracy. In conclusion, behavioral features extracted from the gesture-based passwords lead to less vulnerable user authentication.

Keywords: authentication, gesture-based passwords, machine learning algorithms, shoulder-surfing attacks, usability

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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

Procedia PDF Downloads 417

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: 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

Procedia PDF Downloads 388

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

Procedia PDF Downloads 170

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

Procedia PDF Downloads 181

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: 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: 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: Carlos Tapia Cortez, Serkan Saydam, Jeff Coulton, Claude Sammut

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Strategic mineral commodities (SMC) both energetic and metals have long been fundamental for human beings. There is a strong and long-run relation between the mineral resources industry and society's evolution, with the provision of primary raw materials, becoming one of the most significant drivers of economic growth. Due to mineral resources’ relevance for the entire economy and society, an understanding of the SMC market behaviour to simulate price fluctuations has become crucial for governments and firms. For any human activity, SMC price fluctuations are affected by economic, geopolitical, environmental, technological and psychological issues, where cognition has a major role. Cognition is defined as the capacity to store information in memory, processing and decision making for problem-solving or human adaptation. Thus, it has a significant role in those systems that exhibit dynamic equilibrium through time, such as economic growth. Cognition allows not only understanding past behaviours and trends in SCM markets but also supports future expectations of demand/supply levels and prices, although speculations are unavoidable. Technological developments may also be defined as a cognitive system. Since the Industrial Revolution, technological developments have had a significant influence on SMC production costs and prices, likewise allowing co-integration between commodities and market locations. It suggests a close relation between structural breaks, technology and prices evolution. SCM prices forecasting have been commonly addressed by econometrics and Gaussian-probabilistic models. Econometrics models may incorporate the relationship between variables; however, they are statics that leads to an incomplete approach of prices evolution through time. Gaussian-probabilistic models may evolve through time; however, price fluctuations are addressed by the assumption of random behaviour and normal distribution which seems to be far from the real behaviour of both market and prices. Random fluctuation ignores the evolution of market events and the technical and temporal relation between variables, giving the illusion of controlled future events. Normal distribution underestimates price fluctuations by using restricted ranges, curtailing decisions making into a pre-established space. A proper understanding of SMC's price dynamics taking into account the historical-cognitive relation between economic, technological and psychological factors over time is fundamental in attempting to simulate prices. The aim of this paper is to discuss the SMC market cognition hypothesis and empirically demonstrate its dynamic-cognitive capacity. Three of the largest and traded SMC's: oil, copper and gold, will be assessed to examine the economic, technological and psychological cognition respectively.

Keywords: commodity price simulation, commodity price uncertainties, dynamic-cognition, dynamic systems

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Authors: Ketan Mahawer, Abeer Mutto, S. K. Gupta

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The mining wastewater contains inorganic metal salts, which makes it saline and additionally contributes to contaminating the surface and underground freshwater reserves that exist nearby mineral processing industries. Therefore, treatment of wastewater and water recovery is obligatory by any available technology before disposing it into the environment. Currently, reverse osmosis (RO) is the commercially acceptable conventional membrane process for saline wastewater treatment, but consumes an enormous amount of energy and makes the process expensive. To solve this industrial problem with minimum energy consumption, we tested the feasibility of forward osmosis-nanofiltration (FO-NF) hybrid process for the mining wastewater treatment. The FO-NF process experimental results for 0.029M concentration of saline wastewater treated by 0.42 M sodium-sulfate based draw solution shows that specific energy consumption of the FO-NF process compared with standalone NF was slightly above (between 0.5-1 kWh/m3) from conventional process. However, average freshwater recovery was 30% more from standalone NF with same feed and operating conditions. Hence, FO-NF process in place of RO/NF offers a huge possibility for treating mining industry wastewater and concentrates the metals as the by-products without consuming an excessive/large amount of energy and in addition, mitigates the fouling in long periods of treatment, which also decreases the maintenance and replacement cost of the separation process.

Keywords: forward osmosis, nanofiltration, mining, draw solution, divalent solute

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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: Ambrish Singh

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The corrosion inhibition performance of pyran (AP) and benzimidazole (BI) derivatives on J55 steel in 3.5% NaCl solution saturated with CO₂ was investigated by electrochemical, weight loss, surface characterization, and theoretical studies. The electrochemical studies included electrochemical impedance spectroscopy (EIS), potentiodynamic polarization (PDP), electrochemical frequency modulation (EFM), and electrochemical frequency modulation trend (EFMT). Surface characterization was done using contact angle, scanning electron microscopy (SEM), and atomic force microscopy (AFM) techniques. DFT and molecular dynamics (MD) studies were done using Gaussian and Materials Studio softwares. All the studies suggested the good inhibition by the synthesized inhibitors on J55 steel in 3.5% NaCl solution saturated with CO₂ due to the formation of a protective film on the surface. Molecular dynamic simulation was applied to search for the most stable configuration and adsorption energies for the interaction of the inhibitors with Fe (110) surface.

Keywords: corrosion, inhibitor, EFM, AFM, DFT, MD

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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

Procedia PDF Downloads 644

Authors: Carlos Roncero-Parra, Alfonso Parreño-Torres, Jorge Mateo Sotos, Alejandro L. Borja

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In this research, different methods based on machine/deep learning algorithms are presented for the classification and diagnosis of patients with mental disorders such as alzheimer. For this purpose, the signals obtained from 32 unipolar electrodes identified by non-invasive EEG were examined, and their basic properties were obtained. More specifically, different well-known machine learning based classifiers have been used, i.e., support vector machine (SVM), Bayesian linear discriminant analysis (BLDA), decision tree (DT), Gaussian Naïve Bayes (GNB), K-nearest neighbor (KNN) and Convolutional Neural Network (CNN). A total of 668 patients from five different hospitals have been studied in the period from 2011 to 2021. The best accuracy is obtained was around 93 % in both ADM and ADA classifications. It can be concluded that such a classification will enable the training of algorithms that can be used to identify and classify different mental disorders with high accuracy.

Keywords: alzheimer, machine learning, deep learning, EEG

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Authors: W. Schellong

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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

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Authors: Ali Akbar Attari, Ali Asghar Beheshti Shirazi

Abstract:

In this paper, we propose a blind and robust audio watermarking scheme based on spread spectrum in Discrete Wavelet Transform (DWT) domain. Watermarks are embedded in the low-frequency coefficients, which is less audible. The key idea is dividing the audio signal into small frames, and magnitude of the 6^th level of DWT approximation coefficients is modifying based upon the Direct Sequence Spread Spectrum (DSSS) technique. Also, the psychoacoustic model for enhancing in imperceptibility, as well as Savitsky-Golay filter for increasing accuracy in extraction, is used. The experimental results illustrate high robustness against most common attacks, i.e. Gaussian noise addition, Low pass filter, Resampling, Requantizing, MP3 compression, without significant perceptual distortion (ODG is higher than -1). The proposed scheme has about 83 bps data payload.

Keywords: audio watermarking, spread spectrum, discrete wavelet transform, psychoacoustic, Savitsky-Golay filter

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