Search results for: extreme leaning machine (ELM)

Authors: M. F. Wu, F. T. Cheng, C. S. Wu, M. C. Tan

Abstract:

It is a critical time to upgrade technology and increase value added with manufacturing skills developing and management strategies that will highly satisfy the customers need in the precision machinery global market. In recent years, the supply side, each precision machinery manufacturers in each country are facing the pressures of price reducing from the demand side voices that pushes the high-end precision machinery manufacturers adopts low-cost and high-quality strategy to retrieve the market. Because of the trend of the global market, the manufacturers must take price reducing strategies and upgrade technology of low-end machinery for differentiations to consolidate the market. By using six key success factors (KSFs), customer perceived value, customer satisfaction, customer service, product design, product effectiveness and machine structure quality are causal conditions to explore the impact of competitive advantage of the enterprise, such as overall profitability and product pricing power. This research uses key success paths (KSPs) approach and f/s QCA software to explore various combinations of causal relationships, so as to fully understand the performance level of KSFs and business objectives in order to achieve competitive advantage. In this study, the combination of a causal relationships, are called Key Success Paths (KSPs). The key success paths guide the enterprise to achieve the specific outcomes of business. The findings of this study indicate that there are thirteen KSPs to achieve the overall profitability, sixteen KSPs to achieve the product pricing power and seventeen KSPs to achieve both overall profitability and pricing power of the enterprise. The KSPs provide the directions of resources integration and allocation, improve utilization efficiency of limited resources to realize the continuous vision of the enterprise.

Keywords: precision machinery industry, key success factors (KSFs), key success paths (KSPs), overall profitability, product pricing power, competitive advantages

Procedia PDF Downloads 263

Authors: Bauta J., Raynaud C., Vaca-Medina G., Simon V., Roully A., Vandenbossche V.

Abstract:

Sargassum is a brown algae, originally found in the Sargasso Sea, located in the Caribbean region and the Gulf of Mexico. The flow of Sargassum is becoming a critical environmental problem all over the Caribbean islands particularly. In Guadeloupe alone, around 80,000 tons of seaweed are stranded during the season. Since the appearance of the first waves of Sargassum algae, several measures have been taken to collect them to keep the beaches clean. Nevertheless, 90% of the collected algae are currently stored without recovery. The lack of research initiative demands a more in-depth exploration of Sargassum algae chemistry, targeted towards added value applications and their development. In this context, the aim of the study was to develop a biorefinery process to valorize Sargassum as a source of bioactive natural substances and as raw material to produce biomaterials simultaneously. The technology used was the twin-screw extrusion, which allows to achieve continuously in the same machine different unit fractionation operations. After the identification of the molecules of interest in Sargassum algae, different operating conditions of thermo-mechanical treatment were applied in a twin-screw extruder. The nature of the solvent, the configuration of the extruder, the screw profile, and the temperature profile were studied in order to fractionate the algal biomass and to allow the recovery of a bioactive liquid fraction of interest and a solid residue suitable for the production of biomaterials. Each bioactive liquid fraction was characterized and strategic ways of adding value were proposed. In parallel, the possibility of using the solid residue to produce biomaterials was studied by setting up Dynamic Vapour Sorption (DVS) and basic Pressure-Volume-Temperature (PVT) analyses. The solid residue was molded by compression cooking. The obtained materials were finally characterized mechanically. The results obtained were very comforting and gave some perspectives to find an interesting valorization for the Sargassum algae.

Keywords: seaweeds, twin-screw extrusion, fractionation, bioactive compounds, biomaterials, biomass

Procedia PDF Downloads 122

Authors: Sara Dragisic

Abstract:

Using the theoretical analysis of the birth of biopolitics that Foucault performed through the history of liberalism and neoliberalism, in this paper we will try to show how, precisely through problematizing the role of international institutions, the model of governance differs from previous ways of objectifying body and life. Are the state and its mechanisms still a Leviathan to fight against, or can it be even the driver of resistance against the proponents of modern governance and the biopolitical power? Do paradigmatic examples of biopolitics still appear through sovereignty and (international) law, or is it precisely this sphere that shows a significant dose of incompetence and powerlessness in relation to, not only the economic sphere (Foucault’s critique of neoliberalism) but also the new politics of freedom? Have the struggle for freedom and human rights, as well as the war on terrorism, opened a new spectrum of biopolitical processes, which are manifested precisely through new international institutions and humanitarian discourse? We will try to answer these questions, in the following way. On the one hand, we will show that the views of authors such as Agamben and Hardt and Negri, in whom the state and sovereignty are seen as enemies to be defeated or overcome, fail to see how such attempts could translate into the politicization of life like it is done in many examples through the doctrine of liberal interventionism and humanitarianism. On the other hand, we will point out that it is precisely the humanitarian discourse and the defense of the right to intervention that can be the incentive and basis for the politicization of the category of life and lead to the selective application of human rights. Zizek example of the killing of United Nations workers and doctors in a village during the Vietnam War, who were targeted even before police or soldiers, because they were precisely seen as a powerful instrument of American imperialism (as they were sincerely trying to help the population), will be focus of this part of the analysis. We’ll ask the question whether such interpretation is a kind of liquidation of the extreme left of the political (Laclau) or on this basis can be explained at least in part the need to review the functioning of international organizations, ranging from those dealing with humanitarian aid (and humanitarian military interventions) to those dealing with protection and the security of the population, primarily from growing terrorism. Based on the above examples, we will also explain how the discourse of terrorism itself plays a dual role: it can appear as a tool of liberal biopolitics, although, more superficially, it mostly appears as an enemy that wants to destroy the liberal system and its values. This brings us to the basic problem that this paper will tackle: do the mechanisms of institutional struggle for human rights and freedoms, which is often seen as opposed to the security mechanisms of the state, serve the governance of citizens in such a way that the latter themselves participate in producing biopolitical governmental practices? Is the freedom today "nothing but the correlative development of apparatuses of security" (Foucault)? Or, we can continue this line of Foucault’s argumentation and enhance the interpretation with the important question of what precisely today reflects the change in the rationality of governance in which society is transformed from a passive object into a subject of its own production. Finally, in order to understand the skills of biopolitical governance in modern civil society, it is necessary to pay attention to the status of international organizations, which seem to have become a significant place for the implementation of global governance. In this sense, the power of sovereignty can turn out to be an insufficiently strong power of security policy, which can go hand in hand with freedom policies, through neoliberal governmental techniques.

Keywords: neoliberalism, Foucault, sovereignty, biopolitics, international organizations, NGOs, Agamben, Hardt&Negri, Zizek, security, state power

Procedia PDF Downloads 204

Authors: Lorenzo Casagrande, Antonio Bonati, Ferdinando Auricchio, Antonio Occhiuzzi

Abstract:

This paper summarizes the results of a survey on smart non-structural element dynamic dissipation when installed in modern high-rise mega-frame prototypes. An innovative glazed curtain wall was designed using Shape Memory Alloy (SMA) joints in order to increase the energy dissipation and enhance the seismic/wind response of the structures. The studied buildings consisted of thirty- and sixty-storey planar frames, extracted from reference three-dimensional steel Moment Resisting Frame (MRF) with outriggers and belt trusses. The internal core was composed of a CBF system, whilst outriggers were placed every fifteen stories to limit second order effects and inter-storey drifts. These structural systems were designed in accordance with European rules and numerical FE models were developed with an open-source code, able to account for geometric and material nonlinearities. With regard to the characterization of non-structural building components, full-scale crescendo tests were performed on aluminium/glass curtain wall units at the laboratory of the Construction Technologies Institute (ITC) of the Italian National Research Council (CNR), deriving force-displacement curves. Three-dimensional brick-based inelastic FE models were calibrated according to experimental results, simulating the fac¸ade response. Since recent seismic events and extreme dynamic wind loads have generated the large occurrence of non-structural components failure, which causes sensitive economic losses and represents a hazard for pedestrians safety, a more dissipative glazed curtain wall was studied. Taking advantage of the mechanical properties of SMA, advanced smart joints were designed with the aim to enhance both the dynamic performance of the single non-structural unit and the global behavior. Thus, three-dimensional brick-based plastic FE models were produced, based on the innovated non-structural system, simulating the evolution of mechanical degradation in aluminium-to-glass and SMA-to-glass connections when high deformations occurred. Consequently, equivalent nonlinear links were calibrated to reproduce the behavior of both tested and smart designed units, and implemented on the thirty- and sixty-storey structural planar frame FE models. Nonlinear time history analyses (NLTHAs) were performed to quantify the potential of the new system, when considered in the lateral resisting frame system (LRFS) of modern high-rise MRFs. Sensitivity to the structure height was explored comparing the responses of the two prototypes. Trends in global and local performance were discussed to show that, if accurately designed, advanced materials in non-structural elements provide new sources of energy dissipation.

Keywords: advanced technologies, glazed curtain walls, non-structural elements, seismic-action reduction, shape memory alloy

Procedia PDF Downloads 328

Authors: M. Trousselard, D. Steiler, C. Drogou, P. van-Beers, G. Lamour, S. N. Crosnier, O. Bouilland, P. Dubost, M. Chennaoui, D. Léger

Abstract:

According to published data, undersea navigation for long periods (nuclear-powered ballistic missile submarine, SSBN) constitutes an extreme environment in which crews are subjected to multiple stresses, including the absence of natural light, illuminance below 1,000 lux, and watch schedules that do not respect natural chronobiological rhythms, for a period of 60-80 days. These stresses seem clearly detrimental to the submariners’ sleep, with consequences for their affective (seasonal affective disorder-like) and cognitive functioning. In the long term, there are abundant publications regarding the consequences of sleep disruption for the occurrence of organic cardiovascular, metabolic, immunological or malignant diseases. It seems essential to propose countermeasures for the duration of the patrol in order to reduce the negative physiological effects on the sleep and mood of submariners. Light therapy, the preferred treatment for dysfunctions of the internal biological clock and the resulting seasonal depression, cannot be used without data to assist knowledge of submariners’ chronobiology (melatonin secretion curve) during patrols, given the unusual characteristics of their working environment. These data are not available in the literature. The aim of this project was to assess, in the course of two studies, the benefits of two environmental techniques for managing chronobiological stress: techniques for optimizing potential (TOP; study 1)3, an existing programme to help in the psychophysiological regulation of stress and sleep in the armed forces, and dawn and dusk simulators (DDS, study 2). For each experiment, psychological, physiological (sleep) or biological (melatonin secretion) data were collected on D20 and D50 of patrol. In the first experiment, we studied sleep and depressive distress in 19 submariners in an operational setting on board an SSBM during a first patrol, and assessed the impact of TOP on the quality of sleep and depressive distress in these same submariners over the course of a second patrol. The submariners were trained in TOP between the two patrols for a 2-month period, at a rate of 1 h of training per week, and assigned daily informal exercises. Results show moderate disruptions in sleep pattern and duration associated with the intensity of depressive distress. The use of TOP during the following patrol improved sleep and depressive mood only in submariners who regularly practiced the techniques. In light of these limited benefits, we assessed, in a second experiment, the benefits of DDS on chronobiology (daily secretion of melatonin) and depressive distress. Ninety submariners were randomly allocated to two groups, group 1 using DDS daily, and group 2 constituting the control group. Although the placebo effect was not controlled, results showed a beneficial effect on chronobiology and depressive mood for submariners with a morning chronotype. Conclusions: These findings demonstrate the difficulty of practicing the tools of psychophysiological management in real life. They raise the question of the subjects’ autonomy with respect to using aids that involve regular practice. It seems important to study autonomy in future studies, as a cognitive resource resulting from the interaction between internal positive resources and “coping” resources, to gain a better understanding of compliance problems.

Keywords: chronobiology, light therapy, seasonal affective disorder, sleep, stress, stress management, submarine

Procedia PDF Downloads 453

Authors: Krzysztof Skiba, Zbigniew Czyz, Ksenia Siadkowska, Piotr Borowiec

Abstract:

The article presents selected concepts of technologies that use intelligent materials in aircraft in order to improve their performance. Most of the research focuses on solutions that improve the performance of fixed wing aircraft due to related to their previously dominant market share. Recently, the development of the rotorcraft has been intensive, so there are not only helicopters but also gyroplanes and unmanned aerial vehicles using rotors and vertical take-off and landing. There are many different technologies to change a shape of the aircraft or its elements. Piezoelectric, deformable actuator systems can be applied in the system of an active control of vibration dampening in the aircraft tail structure. Wires made of shape memory alloys (SMA) could be used instead of hydraulic cylinders in the rear part of the aircraft flap. The aircraft made of intelligent materials (piezoelectrics and SMA) is one of the NASA projects which provide the possibility of changing a wing shape coefficient by 200%, a wing surface by 50%, and wing deflections by 20 degrees. Active surfaces made of shape memory alloys could be used to control swirls in the flowing stream. An intelligent control system for helicopter blades is a method for the active adaptation of blades to flight conditions and the reduction of vibrations caused by the rotor. Shape memory alloys are capable of recovering their pre-programmed shapes. They are divided into three groups: nickel-titanium-based, copper-based, and ferromagnetic. Due to the strongest shape memory effect and the best vibration damping ability, a Ni-Ti alloy is the most commercially important. The subject of this work was to prepare a conceptual design of a rotor blade with SMA actuators. The scope of work included 3D design of the supporting rotor blade, 3D design of beams enabling to change the geometry by changing the angle of rotation and FEM (Finite Element Method) analysis. The FEM analysis was performed using NX 12 software in the Pre/Post module, which includes extended finite element modeling tools and visualizations of the obtained results. Calculations are presented for two versions of the blade girders. For FEM analysis, three types of materials were used for comparison purposes (ABS, aluminium alloy 7057, steel C45). The analysis of internal stresses and extreme displacements of crossbars edges was carried out. The internal stresses in all materials were close to the yield point in the solution of girder no. 1. For girder no. 2 solution, the value of stresses decreased by about 45%. As a result of the displacement analysis, it was found that the best solution was the ABS girder no. 1. The displacement of about 0.5 mm was obtained, which resulted in turning the crossbars (upper and lower) by an angle equal to 3.59 degrees. This is the largest deviation of all the tests. The smallest deviation was obtained for beam no. 2 made of steel. The displacement value of the second girder solution was approximately 30% lower than the first solution. Acknowledgement: This work has been financed by the Polish National Centre for Research and Development under the LIDER program, Grant Agreement No. LIDER/45/0177/L-9/17/NCBR/2018.

Keywords: aircraft, helicopters, shape memory alloy, SMA, smart material, unmanned aerial vehicle, UAV

Procedia PDF Downloads 134

Authors: Manish Pandey, Gurinderjit Kaur, Meenu Talwar, Sachin Chauhan, Jagbir Gill

Abstract:

Health-care management systems are a unit of nice connection as a result of the supply a straightforward and fast management of all aspects relating to a patient, not essentially medical. What is more, there are unit additional and additional cases of pathologies during which diagnosing and treatment may be solely allotted by victimization medical imaging techniques. With associate ever-increasing prevalence, medical pictures area unit directly acquired in or regenerate into digital type, for his or her storage additionally as sequent retrieval and process. Data Mining is the process of extracting information from large data sets through using algorithms and Techniques drawn from the field of Statistics, Machine Learning and Data Base Management Systems. Forecasting may be a prediction of what's going to occur within the future, associated it's an unsure method. Owing to the uncertainty, the accuracy of a forecast is as vital because the outcome foretold by foretelling the freelance variables. A forecast management should be wont to establish if the accuracy of the forecast is within satisfactory limits. Fuzzy regression strategies have normally been wont to develop shopper preferences models that correlate the engineering characteristics with shopper preferences relating to a replacement product; the patron preference models offer a platform, wherever by product developers will decide the engineering characteristics so as to satisfy shopper preferences before developing the merchandise. Recent analysis shows that these fuzzy regression strategies area units normally will not to model client preferences. We tend to propose a Testing the strength of Exponential Regression Model over regression toward the mean Model.

Keywords: health-care management systems, fuzzy regression, data mining, forecasting, fuzzy membership function

Procedia PDF Downloads 274

Authors: Hikari Ryu, Yuki Fukuda, Kento Oishi, Chiharu Igarashi, Shogo Kiryu

Abstract:

Recently, wireless power transfer has been developed in various fields. Magnetic coupling is popular for feeding power at a relatively short distance and at a lower frequency. Electro-magnetic wave coupling at a high frequency is used for long-distance power transfer. The wireless power transfer has attracted attention in e-textile fields. Rigid batteries are required for many body-worn electric systems at the present time. The technology enables such batteries to be removed from the systems. Flexible coils have been studied for such applications. Coils with a high Q factor are required in the magnetic-coupling power transfer. Antennas with low return loss are needed for the electro-magnetic coupling. Litz wire is so flexible to fabricate coils and antennas sewn on fabric and has low resistivity. In this study, the electric characteristics of some coils and antennas fabricated with the Litz wire by using two sewing techniques are investigated. As examples, a coil and an antenna are described. Both were fabricated with 330/0.04 mm Litz wire. The coil was a planar coil with a square shape. The outer side was 150 mm, the number of turns was 15, and the pitch interval between each turn was 5 mm. The Litz wire of the coil was overstitched with a sewing machine. The coil was fabricated as a receiver coil for a magnetic coupled wireless power transfer. The Q factor was 200 at a frequency of 800 kHz. A wireless power system was constructed by using the coil. A power oscillator was used in the system. The resonant frequency of the circuit was set to 123 kHz, where the switching loss of power FETs was small. The power efficiencies were 0.44 – 0.99, depending on the distance between the transmitter and receiver coils. As an example of an antenna with a sewing technique, a fractal pattern antenna was stitched on a 500 mm x 500 mm fabric by using a needle punch method. The pattern was the 2nd-oder Vicsec fractal. The return loss of the antenna was -28 dB at a frequency of 144 MHz.

Keywords: e-textile, flexible coils and antennas, Litz wire, wireless power transfer

Procedia PDF Downloads 129

Authors: Maad Kamal Al-Anni

Abstract:

This study is about an algorithmic dependence of Artificial Neural Network on Multilayer Perceptron (MPL) pertaining to the classification and clustering presentations for Mobile Adhoc Network vulnerabilities. Moreover, mobile ad hoc network (MANET) is ubiquitous intelligent internetworking devices in which it has the ability to detect their environment using an autonomous system of mobile nodes that are connected via wireless links. Security affairs are the most important subject in MANET due to the easy penetrative scenarios occurred in such an auto configuration network. One of the powerful techniques used for inspecting the network packets is Intrusion Detection System (IDS); in this article, we are going to show the effectiveness of artificial neural networks used as a machine learning along with stochastic approach (information gain) to classify the malicious behaviors in simulated network with respect to different IDS techniques. The monitoring agent is responsible for detection inference engine, the audit data is collected from collecting agent by simulating the node attack and contrasted outputs with normal behaviors of the framework, whenever. In the event that there is any deviation from the ordinary behaviors then the monitoring agent is considered this event as an attack , in this article we are going to demonstrate the  signature-based IDS approach in a MANET by implementing the back propagation algorithm over ensemble-based Traffic Table (TT), thus the signature of malicious behaviors or undesirable activities are often significantly prognosticated and efficiently figured out, by increasing the parametric set-up of Back propagation algorithm during the experimental results which empirically shown its effectiveness  for the ratio of detection index up to 98.6 percentage. Consequently it is proved in empirical results in this article, the performance matrices are also being included in this article with Xgraph screen show by different through puts like Packet Delivery Ratio (PDR), Through Put(TP), and Average Delay(AD).

Keywords: Intrusion Detection System (IDS), Mobile Adhoc Networks (MANET), Back Propagation Algorithm (BPA), Neural Networks (NN)

Procedia PDF Downloads 191

Authors: Wade Ghribi, Abdelmoty M. Ahmed, Ahmed Said Badawy, Belgacem Bouallegue

Abstract:

In higher education institutions, the most pressing priority is to improve student performance and retention. Large volumes of student data are used in Educational Data Mining techniques to find new hidden information from students' learning behavior, particularly to uncover the early symptom of at-risk pupils. On the other hand, data with noise, outliers, and irrelevant information may provide incorrect conclusions. By identifying features of students' data that have the potential to improve performance prediction results, comparing and identifying the most appropriate ensemble learning technique after preprocessing the data, and optimizing the hyperparameters, this paper aims to develop a reliable students' performance prediction model for Higher Education Institutions. Data was gathered from two different systems: a student information system and an e-learning system for undergraduate students in the College of Computer Science of a Saudi Arabian State University. The cases of 4413 students were used in this article. The process includes data collection, data integration, data preprocessing (such as cleaning, normalization, and transformation), feature selection, pattern extraction, and, finally, model optimization and assessment. Random Forest, Bagging, Stacking, Majority Vote, and two types of Boosting techniques, AdaBoost and XGBoost, are ensemble learning approaches, whereas Decision Tree, Support Vector Machine, and Artificial Neural Network are supervised learning techniques. Hyperparameters for ensemble learning systems will be fine-tuned to provide enhanced performance and optimal output. The findings imply that combining features of students' behavior from e-learning and students' information systems using Majority Vote produced better outcomes than the other ensemble techniques.

Keywords: educational data mining, student performance prediction, e-learning, classification, ensemble learning, higher education

Procedia PDF Downloads 100

Authors: Haider Al-Zubaidy, Xiao-Ling Zhao, Riadh Al-Mahaidi

Abstract:

In recent years, the technique adhesively-bonded fibre reinforced polymer (FRP) composites has found its way into civil engineering applications and it has attracted a widespread attention as a viable alternative strategy for the retrofitting of civil infrastructure such as bridges and buildings. When adopting this method, adhesive has a significant role and controls the general performance and degree of enhancement of the strengthened and/or upgraded structures. This is because the ultimate member strength is highly affected by the failure mode which is considerably dependent on the utilised adhesive. This paper concerns with experimental investigations on the effect of the adhesive used on the bond between CFRP patch and steel plate under medium impact tensile loading. Experiment were conducted using double strap joints and these samples were prepared using two different types of adhesives, Araldite 420 and MBrace saturant. Drop mass rig was used to carry out dynamic tests at impact speeds of 3.35, 4.43 and m/s while quasi-static tests were implemented at 2mm/min using Instrone machine. In this test program, ultimate load-carrying capacity and failure modes were examined for all loading speeds. For both static and dynamic tests, the adhesive type has a significant effect on ultimate joint strength. It was found that the double strap joints prepared using Araldite 420 showed higher strength than those prepared utilising MBrace saturant adhesive. Failure mechanism for joints prepared using Araldite 420 is completely different from those samples prepared utilising MBrace saturant. CFRP failure is the most common failure pattern for joints with Araldite 420, whereas the dominant failure for joints with MBrace saturant adhesive is adhesive failure.

Keywords: CFRP/steel double strap joints, adhesives of different ductility, dynamic tensile loading, bond between CFRP and steel

Procedia PDF Downloads 229

Authors: Getaneh Berie Tarekegn

Abstract:

A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 39 cm, and more than 90% of the errors are less than 82 cm. That is, numerical results proved that, in comparison to traditional methods, the proposed SRCLoc method can significantly improve positioning performance and reduce radio map construction costs.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

Procedia PDF Downloads 68

Authors: Leandros A. Maglaras, Jianmin Jiang

Abstract:

The protection of the national infrastructures from cyberattacks is one of the main issues for national and international security. The funded European Framework-7 (FP7) research project CockpitCI introduces intelligent intrusion detection, analysis and protection techniques for Critical Infrastructures (CI). The paradox is that CIs massively rely on the newest interconnected and vulnerable Information and Communication Technology (ICT), whilst the control equipment, legacy software/hardware, is typically old. Such a combination of factors may lead to very dangerous situations, exposing systems to a wide variety of attacks. To overcome such threats, the CockpitCI project combines machine learning techniques with ICT technologies to produce advanced intrusion detection, analysis and reaction tools to provide intelligence to field equipment. This will allow the field equipment to perform local decisions in order to self-identify and self-react to abnormal situations introduced by cyberattacks. In this paper, an intrusion detection module capable of detecting malicious network traffic in a Supervisory Control and Data Acquisition (SCADA) system is presented. Malicious data in a SCADA system disrupt its correct functioning and tamper with its normal operation. OCSVM is an intrusion detection mechanism that does not need any labeled data for training or any information about the kind of anomaly is expecting for the detection process. This feature makes it ideal for processing SCADA environment data and automates SCADA performance monitoring. The OCSVM module developed is trained by network traces off line and detects anomalies in the system real time. The module is part of an IDS (intrusion detection system) developed under CockpitCI project and communicates with the other parts of the system by the exchange of IDMEF messages that carry information about the source of the incident, the time and a classification of the alarm.

Keywords: cyber-security, SCADA systems, OCSVM, intrusion detection

Procedia PDF Downloads 547

Authors: Marcial Blondet, Malena Serrano, Álvaro Rubiños, Elin Mattsson

Abstract:

In Peru, there are more than two million houses made of adobe (sun dried mud bricks) or rammed earth (35% of the total houses), in which almost 9 million people live, mainly because they cannot afford to purchase industrialized construction materials. Although adobe houses are cheap to build and thermally comfortable, their seismic performance is very poor, and they usually suffer significant damage or collapse with tragic loss of life. Therefore, over the years, researchers at the Pontifical Catholic University of Peru and other institutions have developed many reinforcement techniques as an effort to improve the structural safety of earthen houses located in seismic areas. However, most rural communities live under unacceptable seismic risk conditions because these techniques have not been adopted massively, mainly due to high cost and lack of diffusion. The nylon rope mesh reinforcement technique is simple and low-cost, and two technological transference tools have been developed to diffuse it among rural communities: 1) Scale seismic simulations using a portable shaking table have been designed to prove its effectiveness to protect adobe houses; 2) A step-by-step illustrated construction manual has been developed to guide the complete building process of a nylon rope mesh reinforced adobe house. As a study case, it was selected the district of Pullo: a small rural community in the Peruvian Andes where more than 80% of its inhabitants live in adobe houses and more than 60% are considered to live in poverty or extreme poverty conditions. The research team carried out a one-day workshop in May 2015 and a two-day workshop in September 2015. Results were positive: First, the nylon rope mesh reinforcement procedure was proven simple enough to be replicated by adults, both young and seniors, and participants handled ropes and knots easily as they use them for daily livestock activity. In addition, nylon ropes were proven highly available in the study area as they were found at two local stores in variety of color and size.. Second, the portable shaking table demonstration successfully showed the effectiveness of the nylon rope mesh reinforcement and generated interest on learning about it. On the first workshop, more than 70% of the participants were willing to formally subscribe and sign up for practical training lessons. On the second workshop, more than 80% of the participants returned the second day to receive introductory practical training. Third, community members found illustrations on the construction manual simple and friendly but the roof system illustrations led to misinterpretation so they were improved. The technological transfer tools developed in this project can be used to train rural dwellers on earthquake-resistant self-construction with adobe, which is still very common in the Peruvian Andes. This approach would allow community members to develop skills and capacities to improve safety of their households on their own, thus, mitigating their high seismic risk and preventing tragic losses. Furthermore, proper training in earthquake-resistant self-construction with adobe would prevent rural dwellers from depending on external aid after an earthquake and become agents of their own development.

Keywords: adobe, Peruvian Andes, safe housing, technological transference

Procedia PDF Downloads 290

Authors: P. Serrão, E. Costa, A. Ribeiro, V. Infante

Abstract:

The characteristic sonority of the Portuguese guitar is in great part what makes Fado so distinguishable from other traditional song styles. The Portuguese guitar is a pear-shaped plucked chordophone with six courses of double strings. This study compares the two types of plain strings available for Portuguese guitar and used by the musicians. One is stainless steel spring wire, the other is high carbon spring steel (music wire). Some musicians mention noticeable differences in sound quality between these two string materials, such as a little more brightness and sustain in the steel strings. Experimental tests were performed to characterize string tension at pitch; mechanical strength and tuning stability using the universal testing machine; dimensional control and chemical composition analysis using the scanning electron microscope. The string dynamical behaviour characterization experiments, including frequency response, inharmonicity, transient response, damping phenomena and were made in a monochord test set-up designed and built in-house. Damping factor was determined for the fundamental frequency. As musicians are able to detect very small damping differences, an accurate a characterization of the damping phenomena for all harmonics was necessary. With that purpose, another improved monochord was set and a new system identification methodology applied. Due to the complexity of this task several adjustments were necessary until obtaining good experimental data. In a few cases, dynamical tests were repeated to detect any evolution in damping parameters after break-in period when according to players experience a new string sounds gradually less dull until reaching the typically brilliant timbre. Finally, each set of strings was played on one guitar by a distinguished player and recorded. The recordings which include individual notes, scales, chords and a study piece, will be analysed to potentially characterize timbre variations.

Keywords: damping factor, music wire, portuguese guitar, string dynamics

Procedia PDF Downloads 549

Authors: Vineeth G. Kuriakose, Joseph C. Chen, Ye Li

Abstract:

The research follows a systematic approach to optimize the parameters for parts machined by turning and milling processes. The quality characteristic chosen is surface roughness since the surface finish plays an important role for parts that require surface contact. A tapered cylindrical surface is designed as a test specimen for the research. The material chosen for machining is aluminum alloy 6061 due to its wide variety of industrial and engineering applications. HAAS VF-2 TR computer numerical control (CNC) vertical machining center is used for milling and HAAS ST-20 CNC machine is used for turning in this research. Taguchi analysis is used to optimize the surface roughness of the machined parts. The L₉ Orthogonal Array is designed for four controllable factors with three different levels each, resulting in 18 experimental runs. Signal to Noise (S/N) Ratio is calculated for achieving the specific target value of 75 ± 15 µin. The controllable parameters chosen for turning process are feed rate, depth of cut, coolant flow and finish cut and for milling process are feed rate, spindle speed, step over and coolant flow. The uncontrollable factors are tool geometry for turning process and tool material for milling process. Hypothesis testing is conducted to study the significance of different uncontrollable factors on the surface roughnesses. The optimal parameter settings were identified from the Taguchi analysis and the process capability C_p and the process capability index C_pk were improved from 1.76 and 0.02 to 3.70 and 2.10 respectively for turning process and from 0.87 and 0.19 to 3.85 and 2.70 respectively for the milling process. The surface roughnesses were improved from 60.17 µin to 68.50 µin, reducing the defect rate from 52.39% to 0% for the turning process and from 93.18 µin to 79.49 µin, reducing the defect rate from 71.23% to 0% for the milling process. The purpose of this study is to efficiently utilize the Taguchi design analysis to improve the surface roughness.

Keywords: surface roughness, Taguchi parameter design, CNC turning, CNC milling

Procedia PDF Downloads 153

Authors: D. O. Ramadan, R. S. Dwyer-Joyce

Abstract:

The measurement of the interface conditions in a cutting tool contact is essential information for performance monitoring and control. This interface provides the path for the heat flux to the cutting tool. This elevate in the cutting tool temperature leads to motivate the mechanism of tool wear, thus affect the life of the cutting tool and the productivity. This zone is representative by the tool-chip interface. Therefore, understanding and monitoring this interface is considered an important issue in machining. In this paper, an acoustic emission (AE) technique was used to find the correlation between AE parameters and the tool-chip interface. For this reason, a response surface design (RSD) has been used to analyse and optimize the machining parameters. The experiment design was based on the face centered, central composite design (CCD) in the Minitab environment. According to this design, a series of orthogonal cutting experiments for different cutting conditions were conducted on a Triumph 2500 lathe machine to study the sensitivity of the acoustic emission (AE) signal to change in tool-chip contact length. The cutting parameters investigated were the cutting speed, depth of cut, and feed and the experiments were performed for 6082-T6 aluminium tube. All the orthogonal cutting experiments were conducted unlubricated. The tool-chip contact area was investigated using a scanning electron microscope (SEM). The results obtained in this paper indicate that there is a strong dependence of the root mean square (RMS) on the cutting speed, where the RMS increases with increasing the cutting speed. A dependence on the tool-chip contact length has been also observed. However there was no effect observed of changing the cutting depth and feed on the RMS. These dependencies have been clarified in terms of the strain and temperature in the primary and secondary shear zones, also the tool-chip sticking and sliding phenomenon and the effect of these mechanical variables on dislocation activity at high strain rates. In conclusion, the acoustic emission technique has the potential to monitor in situ the tool-chip interface in turning and consequently could indicate the approaching end of life of a cutting tool.

Keywords: Acoustic emission, tool-chip interface, orthogonal cutting, monitoring

Procedia PDF Downloads 481

Authors: Emir Alaca, Hasbi Apaydin, Rohullah Rahmatullah, Necibe Fusun Oyman Serteller

Abstract:

In recent years, Permanent Magnet Synchronous Motors (PMSMs) have found extensive applications in various industrial sectors, including electric vehicles, wind turbines, and robotics, due to their high performance and low losses. Accurate mathematical modeling of PMSMs is crucial for advanced studies in electric machines. To enhance the effectiveness of graduate-level education, incorporating virtual or real experiments becomes essential to reinforce acquired knowledge. Virtual laboratories have gained popularity as cost-effective alternatives to physical testing, mitigating the risks associated with electrical machine experiments. This study presents a MATLAB-based Graphical User Interface (GUI) for PMSMs. The GUI offers a visual interface that allows users to observe variations in motor outputs corresponding to different input parameters. It enables users to explore healthy motor conditions and the effects of short-circuit faults in the one-phase winding. Additionally, the interface includes menus through which users can access equivalent circuits related to the motor and gain hands-on experience with the mathematical equations used in synchronous motor calculations. The primary objective of this paper is to enhance the learning experience of graduate and doctoral students by providing a GUI-based approach in laboratory studies. This interactive platform empowers students to examine and analyze motor outputs by manipulating input parameters, facilitating a deeper understanding of PMSM operation and control.

Keywords: magnet synchronous motor, mathematical modelling, education tools, winding inter-turn fault

Procedia PDF Downloads 48

Authors: Fathi Kallel, Abdulelah Alabd Uljabbar, Abdulrahman Aldukhail, Abdulaziz Alomran

Abstract:

The brain is an important organ in our body since it is responsible about the majority actions such as vision, memory, etc. However, different diseases such as Alzheimer and tumors could affect the brain and conduct to a partial or full disorder. Regular diagnosis are necessary as a preventive measure and could help doctors to early detect a possible trouble and therefore taking the appropriate treatment, especially in the case of brain tumors. Different imaging modalities are proposed for diagnosis of brain tumor. The powerful and most used modality is the Magnetic Resonance Imaging (MRI). MRI images are analyzed by doctor in order to locate eventual tumor in the brain and describe the appropriate and needed treatment. Diverse image processing methods are also proposed for helping doctors in identifying and analyzing the tumor. In fact, a large Computer Aided Diagnostic (CAD) tools including developed image processing algorithms are proposed and exploited by doctors as a second opinion to analyze and identify the brain tumors. In this paper, we proposed a new advanced CAD for brain tumor identification, classification and feature extraction. Our proposed CAD includes three main parts. Firstly, we load the brain MRI. Secondly, a robust technique for brain tumor extraction is proposed. This technique is based on both Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA). DWT is characterized by its multiresolution analytic property, that’s why it was applied on MRI images with different decomposition levels for feature extraction. Nevertheless, this technique suffers from a main drawback since it necessitates a huge storage and is computationally expensive. To decrease the dimensions of the feature vector and the computing time, PCA technique is considered. In the last stage, according to different extracted features, the brain tumor is classified into either benign or malignant tumor using Support Vector Machine (SVM) algorithm. A CAD tool for brain tumor detection and classification, including all above-mentioned stages, is designed and developed using MATLAB guide user interface.

Keywords: MRI, brain tumor, CAD, feature extraction, DWT, PCA, classification, SVM

Procedia PDF Downloads 242

Authors: Saif Al Ghafri, Thomas Hughes, Armand Karimi, Kumarini Seneviratne, Jordan Oakley, Michael Johns, Eric F. May

Abstract:

Knowledge of the thermophysical properties of complex mixtures at extreme conditions of pressure and temperature have always been essential to the Liquefied Natural Gas (LNG) industry’s evolution because of the tremendous technical challenges present at all stages in the supply chain from production to liquefaction to transport. Each stage is designed using predictions of the mixture’s properties, such as density, viscosity, surface tension, heat capacity and phase behaviour as a function of temperature, pressure, and composition. Unfortunately, currently available models lead to equipment over-designs of 15% or more. To achieve better designs that work more effectively and/or over a wider range of conditions, new fundamental property data are essential, both to resolve discrepancies in our current predictive capabilities and to extend them to the higher-pressure conditions characteristic of many new gas fields. Furthermore, innovative experimental techniques are required to measure different thermophysical properties at high pressures and over a wide range of temperatures, including near the mixture’s critical points where gas and liquid become indistinguishable and most existing predictive fluid property models used breakdown. In this work, we present a wide range of experimental measurements made for different binary and ternary mixtures relevant to LNG processing, with a particular focus on viscosity, surface tension, heat capacity, bubble-points and density. For this purpose, customized and specialized apparatus were designed and validated over the temperature range (200 to 423) K at pressures to 35 MPa. The mixtures studied were (CH4 + C3H8), (CH4 + C3H8 + CO2) and (CH4 + C3H8 + C7H16); in the last of these the heptane contents was up to 10 mol %. Viscosity was measured using a vibrating wire apparatus, while mixture densities were obtained by means of a high-pressure magnetic-suspension densimeter and an isochoric cell apparatus; the latter was also used to determine bubble-points. Surface tensions were measured using the capillary rise method in a visual cell, which also enabled the location of the mixture critical point to be determined from observations of critical opalescence. Mixture heat capacities were measured using a customised high-pressure differential scanning calorimeter (DSC). The combined standard relative uncertainties were less than 0.3% for density, 2% for viscosity, 3% for heat capacity and 3 % for surface tension. The extensive experimental data gathered in this work were compared with a variety of different advanced engineering models frequently used for predicting thermophysical properties of mixtures relevant to LNG processing. In many cases the discrepancies between the predictions of different engineering models for these mixtures was large, and the high quality data allowed erroneous but often widely-used models to be identified. The data enable the development of new or improved models, to be implemented in process simulation software, so that the fluid properties needed for equipment and process design can be predicted reliably. This in turn will enable reduced capital and operational expenditure by the LNG industry. The current work also aided the community of scientists working to advance theoretical descriptions of fluid properties by allowing to identify deficiencies in theoretical descriptions and calculations.

Keywords: LNG, thermophysical, viscosity, density, surface tension, heat capacity, bubble points, models

Procedia PDF Downloads 272

Authors: Altilio Rosa, Chirico Francesco, Foglia Goffredo

Abstract:

In recent years, the number of Unmanned Aerial Vehicles (UAVs) has significantly increased. The rapid development of commercial and recreational drones makes them an important part of our society. Despite the growing list of their applications, these vehicles pose a huge threat to civil and military installations: detection, classification and neutralization of such flying objects become an urgent need. Radar is an effective remote sensing tool for detecting and tracking flying objects, but scenarios characterized by the presence of a high number of tracks related to flying birds make especially challenging the drone detection task: operator PPI is cluttered with a huge number of potential threats and his reaction time can be severely affected. Flying birds compared to UAVs show similar velocity, RADAR cross-section and, in general, similar characteristics. Building from the absence of a single feature that is able to distinguish UAVs and birds, this paper uses a multiple features approach where an original feature selection technique is developed to feed binary classifiers trained to distinguish birds and UAVs. RADAR tracks acquired on the field and related to different UAVs and birds performing various trajectories were used to extract specifically designed target movement-related features based on velocity, trajectory and signal strength. An optimization strategy based on a genetic algorithm is also introduced to select the optimal subset of features and to estimate the performance of several classification algorithms (Neural network, SVM, Logistic regression…) both in terms of the number of selected features and misclassification error. Results show that the proposed methods are able to reduce the dimension of the data space and to remove almost all non-drone false targets with a suitable classification accuracy (higher than 95%).

Keywords: birds, classification, machine learning, UAVs

Procedia PDF Downloads 214

Authors: Meiyan Gao, Zongmin Wang, Haibo Yang, Qiuhua Liang

Abstract:

Under the background of global climate change and rapid development of modern urbanization, the frequency of climate disasters such as extreme precipitation in cities around the world is gradually increasing. In this paper, Hi-PIMS model is used to simulate the "720" flood in Zhengzhou, and the continuous stages of flood resilience are determined with the urban flood stages are divided. The flood resilience curve under the influence of multiple factors were determined and the urban flood toughness was evaluated by combining the results of resilience curves. The flood resilience of urban unit grid was evaluated based on economy, population, road network, hospital distribution and land use type. Firstly, the rainfall data of meteorological stations near Zhengzhou and the remote sensing rainfall data from July 17 to 22, 2021 were collected. The Kriging interpolation method was used to expand the rainfall data of Zhengzhou. According to the rainfall data, the flood process generated by four rainfall events in Zhengzhou was reproduced. Based on the results of the inundation range and inundation depth in different areas, the flood process was divided into four stages: absorption, resistance, overload and recovery based on the once in 50 years rainfall standard. At the same time, based on the levels of slope, GDP, population, hospital affected area, land use type, road network density and other aspects, the resilience curve was applied to evaluate the urban flood resilience of different regional units, and the difference of flood process of different precipitation in "720" rainstorm in Zhengzhou was analyzed. Faced with more than 1,000 years of rainstorm, most areas are quickly entering the stage of overload. The influence levels of factors in different areas are different, some areas with ramps or higher terrain have better resilience, and restore normal social order faster, that is, the recovery stage needs shorter time. Some low-lying areas or special terrain, such as tunnels, will enter the overload stage faster in the case of heavy rainfall. As a result, high levels of flood protection, water level warning systems and faster emergency response are needed in areas with low resilience and high risk. The building density of built-up area, population of densely populated area and road network density all have a certain negative impact on urban flood resistance, and the positive impact of slope on flood resilience is also very obvious. While hospitals can have positive effects on medical treatment, they also have negative effects such as population density and asset density when they encounter floods. The result of a separate comparison of the unit grid of hospitals shows that the resilience of hospitals in the distribution range is low when they encounter floods. Therefore, in addition to improving the flood resistance capacity of cities, through reasonable planning can also increase the flood response capacity of cities. Changes in these influencing factors can further improve urban flood resilience, such as raise design standards and the temporary water storage area when floods occur, train the response speed of emergency personnel and adjust emergency support equipment.

Keywords: urban flood resilience, resilience assessment, hydrodynamic model, resilience curve

Procedia PDF Downloads 37

Authors: Sokkhey Phauk, Takeo Okazaki

Abstract:

The challenging task in educational institutions is to maximize the high performance of students and minimize the failure rate of poor-performing students. An effective method to leverage this task is to know student learning patterns with highly influencing factors and get an early prediction of student learning outcomes at the timely stage for setting up policies for improvement. Educational data mining (EDM) is an emerging disciplinary field of data mining, statistics, and machine learning concerned with extracting useful knowledge and information for the sake of improvement and development in the education environment. The study is of this work is to propose techniques in EDM and integrate it into a web-based system for predicting poor-performing students. A comparative study of prediction models is conducted. Subsequently, high performing models are developed to get higher performance. The hybrid random forest (Hybrid RF) produces the most successful classification. For the context of intervention and improving the learning outcomes, a feature selection method MICHI, which is the combination of mutual information (MI) and chi-square (CHI) algorithms based on the ranked feature scores, is introduced to select a dominant feature set that improves the performance of prediction and uses the obtained dominant set as information for intervention. By using the proposed techniques of EDM, an academic performance prediction system (APPS) is subsequently developed for educational stockholders to get an early prediction of student learning outcomes for timely intervention. Experimental outcomes and evaluation surveys report the effectiveness and usefulness of the developed system. The system is used to help educational stakeholders and related individuals for intervening and improving student performance.

Keywords: academic performance prediction system, educational data mining, dominant factors, feature selection method, prediction model, student performance

Procedia PDF Downloads 104

Authors: S. P. Rana

Abstract:

Objectives: For the manufacture of a very thin strip or a strip with a high-quality finish, the stainless steel sheet that is called billet is re-rolled in re-rolling mill to make stainless steel sheet of 18 gauges. The rolls of re-rolling mill exert tremendous pressure over the sheet and there is likely chance of breaking of stainless steel strip from the sheet. The objective of the study was to minimise the number of accidents in steel re-rolling mills due to ejection of stainless steel strip and to minimize the pollution caused by the pickling process used in these units. Methods: Looking into the high rate of frequency and severity of accidents as well as pollution hazard in re-rolling and pickling mills, it becomes essential to make necessary arrangements for prevention of accidents in such type of industry. The author carried out survey/inspections of a large number of re-rolling and pickling mills and allied units. During the course of inspection, the working of these steel re-rolling and pickling mills was closely studied and monitored. A number of accidents involving re-rolling mills were investigated and subsequently remedial measures to prevent the occurrence of such accidents were suggested. Assessment of occupational safety and health system of these units was carried out and compliance level of the statutory requirements was checked. The workers were medically examined and monitored to ascertain their health conditions. Results: Proper use of safety gadgets by workers, machine guarding and regular training brought down the risk to an acceptable level and discharged effluent pollution was brought down to permissible limits. The fatal accidents have been reduced by 83%. Conclusions: Effective enforcement and implementation of the directions/suggestions given to the managements of such units brought down the no. of accidents to a rational level. The number of fatal accidents has reduced by 83% during the study period. The effective implementation of pollution control device curtailed the pollution level to an acceptable level.

Keywords: re-rolling mill, hazard, accident, health hazards

Procedia PDF Downloads 439

Authors: Rasouli Divkalaee Zeinab, Kalteh Safa, Roudbari Aliakbar

Abstract:

Introduction: Medical waste can lead to the generation and transmission of many infectious and contagious diseases due to the presence of pathogenic agents, thereby necessitating the need for special management to collect, decontaminate, and finally dispose of such products. This study aimed to design a centralized health care (medical) waste management program for the cities of Semnan, Mahdishahr, and Shahmirzad. Methods: This descriptive-analytical study was conducted for six months in the cities of Semnan, Mahdishahr, and Shahmirzad. In this study, the quantitative and qualitative characteristics of the generated wastes were determined by taking samples from all medical waste production centers. Then, the equipment, devices, and machines required for separate collection of the waste from the production centers and for their subsequent decontamination were estimated. Next, the investment costs, current costs, and working capital required for collection, decontamination, and final disposal of the wastes were determined. Finally, the payment for proper waste management of each category of medical waste-producing centers was determined. Results: 1021 kilograms of medical waste are produced daily in the cities of Semnan, Mahdishahr, and Shahmirzad. It was estimated that a 1000-liter autoclave, a machine for collecting medical waste, four 60-liter bins, four 120-liter bins, and four 1200-liter bins were required for implementing the study plan. Also, the estimated total annual medical waste management costs for Semnan City were determined (23,283,903,720 Iranian Rials). Conclusion: The study results showed that establishing a proper management system for medical wastes generated in the three studied cities will cost between 334,280 and 1,253,715 Iranian Rials in fees for the medical centers. The findings of this study provided comprehensive data regarding medical wastes from the generation point to the landfill site, which is vital for the government and the private sector.

Keywords: clinics, decontamination, management, medical waste

Procedia PDF Downloads 75

Authors: S. P. Singh, Priya, Komal Sajwan

Abstract:

With the increasing spread of organic farming in India, costs, returns, efficiency, and social and environmental sustainability of organic vis-a-vis conventional farming systems have become topics of interest among agriculture scientists, economists, and policy analysts. A study on technical efficiency estimation under these farming systems, particularly in the Ganga River Basin, where the promotion of organic farming is incentivized, can help to understand whether the inputs are utilized to their maximum possible level and what measures can be taken to improve the efficiency. This paper, therefore, analyses the technical efficiency of wheat farms operating under organic and conventional farming systems. The study is based on a primary survey of 600 farms (300 organic ad 300 conventional) conducted in 2021 in two districts located in the Middle Ganga River Basin, India. Technical, managerial, and scale efficiencies of individual farms are estimated by applying the data envelopment analysis (DEA) methodology. The per hectare value of wheat production is taken as an output variable, and values of seeds, human labour, machine cost, plant nutrients, farm yard manure (FYM), plant protection, and irrigation charges are considered input variables for estimating the farm-level efficiencies. The post-DEA analysis is conducted using the Tobit regression model to know the efficiency determining factors. The results show that technical efficiency is significantly higher in conventional than organic farming systems due to a higher gap in scale efficiency than managerial efficiency. Further, 9.8% conventional and only 1.0% organic farms are found operating at the most productive scale size (MPSS), and 99% organic and 81% conventional farms at IRS. Organic farms perform well in managerial efficiency, but their technical efficiency is lower than conventional farms, mainly due to their relatively lower scale size. The paper suggests that technical efficiency in organic wheat can be increased by upscaling the farm size by incentivizing group/collective farming in clusters.

Keywords: organic, conventional, technical efficiency, determinants, DEA, Tobit regression

Procedia PDF Downloads 96

Authors: Darius Jakimavicius

Abstract:

Artificial intelligence is the subject of intense debate in the international arena, identified both as a technological breakthrough and as a component of the strategic stability effect. Both the kinetic and non-kinetic development of AI and its application in the national strategies of the great powers may trigger a change in the security situation. Artificial intelligence is generally faster, more capable and more efficient than humans, and there is a temptation to transfer decision-making and control responsibilities to artificial intelligence. Artificial intelligence, which, once activated, can select and act on targets without further intervention by a human operator, blurs the boundary between human or robot (machine) warfare, or perhaps human and robot together. Artificial intelligence acts as a force multiplier that speeds up decision-making and reaction times on the battlefield. The role of humans is increasingly moving away from direct decision-making and away from command and control processes involving the use of force. It is worth noting that the autonomy and precision of AI systems make the process of strategic stability more complex. Deterrence theory is currently in a phase of development in which deterrence is undergoing further strain and crisis due to the complexity of the evolving models enabled by artificial intelligence. Based on the concept of strategic stability and deterrence theory, it is appropriate to develop further research on the development and impact of AI in order to assess AI from both a scientific and technical perspective: to capture a new niche in the scientific literature and academic terminology, to clarify the conditions for deterrence, and to identify the potential uses, impacts and possibly quantities of AI. The research problem is the impact of artificial intelligence developed by great powers on strategic stability. This thesis seeks to assess the impact of AI on strategic stability and deterrence principles, with human exclusion from the decision-making and control loop as a key axis. The interaction between AI and human actions and interests can determine fundamental changes in great powers' defense and deterrence, and the development and application of AI-based great powers strategies can lead to a change in strategic stability.

Keywords: artificial inteligence, strategic stability, deterrence theory, decision making loop

Procedia PDF Downloads 39

Authors: Saraswati Kerketta

Abstract:

Tea industry is one of the oldest organised sector of India. It employs roughly 1.5 million people directly. Since the last decade Indian tea industry, especially in the northern region is experiencing worst crisis in the post-independence period. Due to many reason the prices of tea show steady decline. The workers are paid one of the lowest wage in tea industry in the world (1.5$ a day) below the UN's $2 a day for extreme poverty. The workers rely on addition benefits from plantation which includes food, housing and medical facilities. These have been effective means of enslavement of generations of labourers by the owners. There is hardly any change in the tea estates where the owners determine the fate of workers. When the tea garden is abandoned or is closed all the facilities disappear immediately. The workers are the descendants of tribes from central India also known as 'tea tribes'. Alienated from their native place, the geographical and social isolation compounded their vulnerability of these people. The economy of the region being totally dependent on tea has resulted in absolute unemployment for the workers of these tea gardens. With no other livelihood and no land to grow food, thousands of workers faced hunger and starvation. The Plantation Labour Act which ensures the decent working and living condition is violated continuously. The labours are forced to migrate and are also exposed to the risk of human trafficking. Those who are left behind suffers from starvation, malnutrition and disease. The condition in the sick tea plantation is no better. Wage are not paid regularly, subsidised food, fuel are also not supplied properly. Health care facilities are in very bad shape. Objectives: • To study the socio-cultural and demographic characteristics of the tea garden labourers in the study area. • To examine the social situation of workers in sick estates in dooars region. • To assess the magnitude of deprivation the impact of economic crisis on abandoned and closed tea estates in the region. Data Base: The study is based on data collected from field survey. Methods: Quantative: Cross-Tabulation, Regression analysis. Qualitative: Household Survey, Focussed Group Discussion, In-depth interview of key informants. Findings: Purchasing power parity has declined since in last three decades. There has been many fold increase in migration. Males migrates long distance towards central and west and south India. Females and children migrates both long and short distance. No one has reported to migrate back to the place of origin of their ancestors. Migrant males work mostly as construction labourers and as factory workers whereas females and children work as domestic help and construction labourers. In about 37 cases either they haven't contacted their families in last six months or are not traceable. The families with single earning members are more likely to migrate. Burden of disease and the duration of sickness, abandonment and closure of plantation are closely related. Death tolls are likely to rise 1.5 times in sick tea gardens and three times in closed tea estates. Sixty percent of the people are malnourished in the sick tea gardens and more than eighty five per cent in abandoned and sick tea gardens.

Keywords: migration, trafficking, starvation death, tea garden workers

Procedia PDF Downloads 379

Authors: Verena M. Moock, Darien E. Arce Chávez, Mariana M. Espejel González, Leopoldo Ruíz-Huerta, Crescencio García-Segundo

Abstract:

Uncertainty analysis in industrial computed tomography is commonly related to metrological trace tools, which offer precision measurements of external part features. Unfortunately, there is no such reference tool for internal measurements to profit from the unique imaging potential of X-rays. Uncertainty approximations for computed tomography are still based on general aspects of the industrial machine and do not adapt to acquisition parameters or part characteristics. The present study investigates the impact of the acquisition time on the dimensional uncertainty measuring a stainless steel cylinder with a circular tomography scan. The authors develop the figure difference method for X-ray radiography to evaluate the volumetric differences introduced within the projected absorption maps of the metal workpiece. The dimensional uncertainty is dominantly influenced by photon energy dissipated as heat causing the thermal expansion of the metal, as monitored by an infrared camera within the industrial tomograph. With the proposed methodology, we are able to show evolving temperature differences throughout the tomography acquisition. This is an early study showing that the number of projections in computer tomography induces dimensional error due to energy absorption. The error magnitude would depend on the thermal properties of the sample and the acquisition parameters by placing apparent non-uniform unwanted volumetric expansion. We introduce infrared imaging for the experimental display of metrological uncertainty in a particular metal part of symmetric geometry. We assess that the current results are of fundamental value to reach the balance between the number of projections and uncertainty tolerance when performing analysis with X-ray dimensional exploration in precision measurements with industrial tomography.

Keywords: computed tomography, digital metrology, infrared imaging, thermal expansion

Procedia PDF Downloads 118

Authors: Chih-Jer Lin, Jian-Hong Hou

Abstract:

Industry 4.0 is a vision of integrated industry implemented by artificial intelligent computing, software, and Internet technologies. The main goal of industry 4.0 is to deal with the difficulty owing to competitive pressures in the marketplace. For today’s manufacturing factories, the type of production is changed from mass production (high quantity production with low product variety) to medium quantity-high variety production. To offer flexibility, better quality control, and improved productivity, robot manipulators are used to combine material processing, material handling, and part positioning systems into an integrated manufacturing system. To implement the automated system for sheet metal bending operations, motion planning of a 7-degrees of freedom (DOF) robot is studied in this paper. A virtual reality (VR) environment of a bending cell, which consists of the robot and a bending machine, is established using the virtual robot experimentation platform (V-REP) simulator. For sheet metal bending operations, the robot only needs six DOFs for the pick-and-place or tracking tasks. Therefore, this 7 DOF robot has more DOFs than the required to execute a specified task; it can be called a redundant robot. Therefore, this robot has kinematic redundancies to deal with the task-priority problems. For redundant robots, Pseudo-inverse of the Jacobian is the most popular motion planning method, but the pseudo-inverse methods usually lead to a kind of chaotic motion with unpredictable arm configurations as the Jacobian matrix lose ranks. To overcome the above problem, we proposed a method to formulate the motion planning problems as optimization problem. Moreover, a genetic algorithm (GA) based method is proposed to deal with motion planning of the redundant robot. Simulation results validate the proposed method feasible for motion planning of the redundant robot in an automated sheet-metal bending operations.

Keywords: redundant robot, motion planning, genetic algorithm, obstacle avoidance

Procedia PDF Downloads 143