Search results for: virtual machine migration
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4783

Search results for: virtual machine migration

823 The Effect of Alkaline Treatment on Tensile Strength and Morphological Properties of Kenaf Fibres for Yarn Production

Authors: A. Khalina, K. Shaharuddin, M. S. Wahab, M. P. Saiman, H. A. Aisyah

Abstract:

This paper investigates the effect of alkali treatment and mechanical properties of kenaf (Hibiscus cannabinus) fibre for the development of yarn. Two different fibre sources are used for the yarn production. Kenaf fibres were treated with sodium hydroxide (NaOH) in the concentration of 3, 6, 9, and 12% prior to fibre opening process and tested for their tensile strength and Young’s modulus. Then, the selected fibres were introduced to fibre opener at three different opening processing parameters; namely, speed of roller feeder, small drum, and big drum. The diameter size, surface morphology, and fibre durability towards machine of the fibres were characterized. The results show that concentrations of NaOH used have greater effects on fibre mechanical properties. From this study, the tensile and modulus properties of the treated fibres for both types have improved significantly as compared to untreated fibres, especially at the optimum level of 6% NaOH. It is also interesting to highlight that 6% NaOH is the optimum concentration for the alkaline treatment. The untreated and treated fibres at 6% NaOH were then introduced to fibre opener, and it was found that the treated fibre produced higher fibre diameter with better surface morphology compared to the untreated fibre. Higher speed parameter during opening was found to produce higher yield of opened-kenaf fibres.

Keywords: alkaline treatment, kenaf fibre, tensile strength, yarn production

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822 Rank-Based Chain-Mode Ensemble for Binary Classification

Authors: Chongya Song, Kang Yen, Alexander Pons, Jin Liu

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In the field of machine learning, the ensemble has been employed as a common methodology to improve the performance upon multiple base classifiers. However, the true predictions are often canceled out by the false ones during consensus due to a phenomenon called “curse of correlation” which is represented as the strong interferences among the predictions produced by the base classifiers. In addition, the existing practices are still not able to effectively mitigate the problem of imbalanced classification. Based on the analysis on our experiment results, we conclude that the two problems are caused by some inherent deficiencies in the approach of consensus. Therefore, we create an enhanced ensemble algorithm which adopts a designed rank-based chain-mode consensus to overcome the two problems. In order to evaluate the proposed ensemble algorithm, we employ a well-known benchmark data set NSL-KDD (the improved version of dataset KDDCup99 produced by University of New Brunswick) to make comparisons between the proposed and 8 common ensemble algorithms. Particularly, each compared ensemble classifier uses the same 22 base classifiers, so that the differences in terms of the improvements toward the accuracy and reliability upon the base classifiers can be truly revealed. As a result, the proposed rank-based chain-mode consensus is proved to be a more effective ensemble solution than the traditional consensus approach, which outperforms the 8 ensemble algorithms by 20% on almost all compared metrices which include accuracy, precision, recall, F1-score and area under receiver operating characteristic curve.

Keywords: consensus, curse of correlation, imbalance classification, rank-based chain-mode ensemble

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821 A Virtual Set-Up to Evaluate Augmented Reality Effect on Simulated Driving

Authors: Alicia Yanadira Nava Fuentes, Ilse Cervantes Camacho, Amadeo José Argüelles Cruz, Ana María Balboa Verduzco

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Augmented reality promises being present in future driving, with its immersive technology let to show directions and maps to identify important places indicating with graphic elements when the car driver requires the information. On the other side, driving is considered a multitasking activity and, for some people, a complex activity where different situations commonly occur that require the immediate attention of the car driver to make decisions that contribute to avoid accidents; therefore, the main aim of the project is the instrumentation of a platform with biometric sensors that allows evaluating the performance in driving vehicles with the influence of augmented reality devices to detect the level of attention in drivers, since it is important to know the effect that it produces. In this study, the physiological sensors EPOC X (EEG), ECG06 PRO and EMG Myoware are joined in the driving test platform with a Logitech G29 steering wheel and the simulation software City Car Driving in which the level of traffic can be controlled, as well as the number of pedestrians that exist within the simulation obtaining a driver interaction in real mode and through a MSP430 microcontroller achieves the acquisition of data for storage. The sensors bring a continuous analog signal in time that needs signal conditioning, at this point, a signal amplifier is incorporated due to the acquired signals having a sensitive range of 1.25 mm/mV, also filtering that consists in eliminating the frequency bands of the signal in order to be interpretative and without noise to convert it from an analog signal into a digital signal to analyze the physiological signals of the drivers, these values are stored in a database. Based on this compilation, we work on the extraction of signal features and implement K-NN (k-nearest neighbor) classification methods and decision trees (unsupervised learning) that enable the study of data for the identification of patterns and determine by classification methods different effects of augmented reality on drivers. The expected results of this project include are a test platform instrumented with biometric sensors for data acquisition during driving and a database with the required variables to determine the effect caused by augmented reality on people in simulated driving.

Keywords: augmented reality, driving, physiological signals, test platform

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820 Client Hacked Server

Authors: Bagul Abhijeet

Abstract:

Background: Client-Server model is the backbone of today’s internet communication. In which normal user can not have control over particular website or server? By using the same processing model one can have unauthorized access to particular server. In this paper, we discussed about application scenario of hacking for simple website or server consist of unauthorized way to access the server database. This application emerges to autonomously take direct access of simple website or server and retrieve all essential information maintain by administrator. In this system, IP address of server given as input to retrieve user-id and password of server. This leads to breaking administrative security of server and acquires the control of server database. Whereas virus helps to escape from server security by crashing the whole server. Objective: To control malicious attack and preventing all government website, and also find out illegal work to do hackers activity. Results: After implementing different hacking as well as non-hacking techniques, this system hacks simple web sites with normal security credentials. It provides access to server database and allow attacker to perform database operations from client machine. Above Figure shows the experimental result of this application upon different servers and provides satisfactory results as required. Conclusion: In this paper, we have presented a to view to hack the server which include some hacking as well as non-hacking methods. These algorithms and methods provide efficient way to hack server database. By breaking the network security allow to introduce new and better security framework. The terms “Hacking” not only consider for its illegal activities but also it should be use for strengthen our global network.

Keywords: Hacking, Vulnerabilities, Dummy request, Virus, Server monitoring

Procedia PDF Downloads 237
819 Temperature Evolution, Microstructure and Mechanical Properties of Heat-Treatable Aluminum Alloy Welded by Friction Stir Welding: Comparison with Tungsten Inert Gas

Authors: Saliha Gachi, Mouloud Aissani, Fouad Boubenider

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Friction Stir Welding (FSW) is a solid-state welding technique that can join material without melting the plates to be welded. In this work, we are interested to demonstrate the potentiality of FSW for joining the heat-treatable aluminum alloy 2024-T3 which is reputed as difficult to be welded by fusion techniques. Thereafter, the FSW joint is compared with another one obtained from a conventional fusion process Tungsten Inert Gas (TIG). FSW welds are made up using an FSW tool mounted on a milling machine. Single pass welding was applied to fabricated TIG joint. The comparison between the two processes has been made on the temperature evolution, mechanical and microstructure behavior. The microstructural examination revealed that FSW weld is composed of four zones: Base metal (BM), Heat affected zone (HAZ), Thermo-mechanical affected zone (THAZ) and the nugget zone (NZ). The NZ exhibits a recrystallized equiaxed refined grains that induce better mechanical properties and good ductility compared to TIG joint where the grains have a larger size in the welded region compared with the BM due to the elevated heat input. The microhardness results show that, in FSW weld, the THAZ contains the lowest microhardness values and increase in the NZ; however, in TIG process, the lowest values are localized on the NZ.

Keywords: friction stir welding, tungsten inert gaz, aluminum, microstructure

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818 Upper Jurassic Foraminiferal Assemblages and Palaeoceanographical Changes in the Central Part of the East European Platform

Authors: Clementine Colpaert, Boris L. Nikitenko

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The Upper Jurassic foraminiferal assemblages of the East European Platform have been strongly investigated through the 20th century with biostratigraphical and in smaller degree palaeoecological and palaeobiogeographical purposes. Over the Late Jurassic, the platform was a shallow epicontinental sea that extended from Tethys to the Artic through the Pechora Sea and further toward the northeast in the West Siberian Sea. Foraminiferal assemblages of the Russian Sea were strongly affected by sea-level changes and were controlled by alternated Boreal to Peritethyan influences. The central part of the East European Platform displays very rich and diverse foraminiferal assemblages. Two sections have been analyzed; the Makar'yev Section in the Moscow Depression and the Gorodishi Section in the Yl'yanovsk Depression. Based on the evolution of foraminiferal assemblages, palaeoenvironment has been reconstructed, and sea-level changes have been refined. The aim of this study is to understand palaeoceanographical changes throughout the Oxfordian – Kimmeridgian of the central part of the Russian Sea. The Oxfordian was characterized by a general transgressive event with intermittency of small regressive phases. The platform was connected toward the south with Tethys and Peritethys. During the Middle Oxfordian, opening of a pathway of warmer water from the North-Tethys region to the Boreal Realm favoured the migration of planktonic foraminifera and the appearance of new benthic taxa. It is associated with increased temperature and primary production. During the Late Oxfordian, colder water inputs associated with the microbenthic community crisis may be a response to the closure of this warm-water corridor and the disappearance of planktonic foraminifera. The microbenthic community crisis is probably due to the increased sedimentation rate in the transition from the maximum flooding surface to a second-order regressive event, increasing productivity and inputs of organic matter along with sharp decrease of oxygen into the sediment. It is following during the Early Kimmeridgian by a replacement of foraminiferal assemblages. The almost all Kimmeridgian is characterized by the abundance of many common with Boreal and Subboreal Realm. Connections toward the South began again dominant after a small regressive event recorded during the Late Kimmeridgian and associated with the abundance of many common taxa with Subboreal Realm and Peritethys such as Crimea and Caucasus taxa. Foraminiferal assemblages of the East European Platform are strongly affected by palaeoecological changes and may display a very good model for biofacies typification under Boreal and Subboreal environments. The East European Platform appears to be a key area for the understanding of Upper Jurassic big scale palaeoceanographical changes, being connected with Boreal to Peritethyan basins.

Keywords: foraminifera, palaeoceanography, palaeoecology, upper jurassic

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817 Decision Making System for Clinical Datasets

Authors: P. Bharathiraja

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Computer Aided decision making system is used to enhance diagnosis and prognosis of diseases and also to assist clinicians and junior doctors in clinical decision making. Medical Data used for decision making should be definite and consistent. Data Mining and soft computing techniques are used for cleaning the data and for incorporating human reasoning in decision making systems. Fuzzy rule based inference technique can be used for classification in order to incorporate human reasoning in the decision making process. In this work, missing values are imputed using the mean or mode of the attribute. The data are normalized using min-ma normalization to improve the design and efficiency of the fuzzy inference system. The fuzzy inference system is used to handle the uncertainties that exist in the medical data. Equal-width-partitioning is used to partition the attribute values into appropriate fuzzy intervals. Fuzzy rules are generated using Class Based Associative rule mining algorithm. The system is trained and tested using heart disease data set from the University of California at Irvine (UCI) Machine Learning Repository. The data was split using a hold out approach into training and testing data. From the experimental results it can be inferred that classification using fuzzy inference system performs better than trivial IF-THEN rule based classification approaches. Furthermore it is observed that the use of fuzzy logic and fuzzy inference mechanism handles uncertainty and also resembles human decision making. The system can be used in the absence of a clinical expert to assist junior doctors and clinicians in clinical decision making.

Keywords: decision making, data mining, normalization, fuzzy rule, classification

Procedia PDF Downloads 497
816 Water Body Detection and Estimation from Landsat Satellite Images Using Deep Learning

Authors: M. Devaki, K. B. Jayanthi

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The identification of water bodies from satellite images has recently received a great deal of attention. Different methods have been developed to distinguish water bodies from various satellite images that vary in terms of time and space. Urban water identification issues body manifests in numerous applications with a great deal of certainty. There has been a sharp rise in the usage of satellite images to map natural resources, including urban water bodies and forests, during the past several years. This is because water and forest resources depend on each other so heavily that ongoing monitoring of both is essential to their sustainable management. The relevant elements from satellite pictures have been chosen using a variety of techniques, including machine learning. Then, a convolution neural network (CNN) architecture is created that can identify a superpixel as either one of two classes, one that includes water or doesn't from input data in a complex metropolitan scene. The deep learning technique, CNN, has advanced tremendously in a variety of visual-related tasks. CNN can improve classification performance by reducing the spectral-spatial regularities of the input data and extracting deep features hierarchically from raw pictures. Calculate the water body using the satellite image's resolution. Experimental results demonstrate that the suggested method outperformed conventional approaches in terms of water extraction accuracy from remote-sensing images, with an average overall accuracy of 97%.

Keywords: water body, Deep learning, satellite images, convolution neural network

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815 Network Based Speed Synchronization Control for Multi-Motor via Consensus Theory

Authors: Liqin Zhang, Liang Yan

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This paper addresses the speed synchronization control problem for a network-based multi-motor system from the perspective of cluster consensus theory. Each motor is considered as a single agent connected through fixed and undirected network. This paper presents an improved control protocol from three aspects. First, for the purpose of improving both tracking and synchronization performance, this paper presents a distributed leader-following method. The improved control protocol takes the importance of each motor’s speed into consideration, and all motors are divided into different groups according to speed weights. Specifically, by using control parameters optimization, the synchronization error and tracking error can be regulated and decoupled to some extent. The simulation results demonstrate the effectiveness and superiority of the proposed strategy. In practical engineering, the simplified models are unrealistic, such as single-integrator and double-integrator. And previous algorithms require the acceleration information of the leader available to all followers if the leader has a varying velocity, which is also difficult to realize. Therefore, the method focuses on an observer-based variable structure algorithm for consensus tracking, which gets rid of the leader acceleration. The presented scheme optimizes synchronization performance, as well as provides satisfactory robustness. What’s more, the existing algorithms can obtain a stable synchronous system; however, the obtained stable system may encounter some disturbances that may destroy the synchronization. Focus on this challenging technological problem, a state-dependent-switching approach is introduced. In the presence of unmeasured angular speed and unknown failures, this paper investigates a distributed fault-tolerant consensus tracking algorithm for a group non-identical motors. The failures are modeled by nonlinear functions, and the sliding mode observer is designed to estimate the angular speed and nonlinear failures. The convergence and stability of the given multi-motor system are proved. Simulation results have shown that all followers asymptotically converge to a consistent state when one follower fails to follow the virtual leader during a large enough disturbance, which illustrates the good performance of synchronization control accuracy.

Keywords: consensus control, distributed follow, fault-tolerant control, multi-motor system, speed synchronization

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814 Towards a More Inclusive Society: A Study on the Assimilation and Integration of the Migrant Children in Kerala

Authors: Arun Perumbilavil Anand

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For the past few years, the state of Kerala has been witnessing a large inflow of migrant workers from other states of the country, which emerged as a result of demographic transition and Gulf emigration. The in-migration patterns in Kerala have changed over the time with the migrants having a higher residence history bringing their families to the state, thereby making the process more complicated and divergent in its approach. These developments have led to an increase in the young migrant population at least in some parts of the state, which has opened up doubts and questions related to their future in the host society. At this juncture, the study ponders into the factors that are associated with the assimilation and wellbeing of migrant children in the society of Kerala. As one of the objectives, the study also analyzed the influence and role played by the educational institutions (both public and private) in meeting the needs and aspirations of both the children and their parents. The study gains significance as it tries to identify various impediments that hinder the cognitive skill formation and behaviour patterns of the migrant children in the host society. Data and Methodology: The study is based on the primary data collected through a series of interviews and interactions held with parents, children, and teachers of different educational institutions, including both public and private. The primary survey also made use of research techniques like observation, in-depth interviews, and case study method. The study was conducted in schools in the Kanjikode area of the Palakkad district in Kerala. The findings of the study are on the basis of a survey conducted in four schools and 40 migrant children. Findings: The study found that majority of the children have wholly integrated and assimilated into the host society. The influence of the peer group was quite visible in giving stimulus to the assimilation process. Most of the children do not have any emotional or cultural sentiments attached to their state of origin, and they consider Kerala as their ‘home state’ and the local language (Malayalam) as their ‘mother tongue'. The study could also find that the existing education system in the host society fails to meet the needs and aspirations of migrants as well as that of their children. On a comparative scale, to some extent, private schools have succeeded in fulfiling the special requirements of the migrant children. An interesting point that the study could pinpoint at is that the children of the migrants show better health conditions and wellbeing than compared to the natives, which is usually addressed as an epidemiologic paradox. As a concluding remark, the study recommends the inclusion concept of inclusive education into the education system of the state with giving due emphasis on those who are at higher risk of being excluded or marginalized, along with fostering increased interaction between diverse groups.

Keywords: assimilation, Kerala, migrant children, well-being

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813 Single Atom Manipulation with 4 Scanning Tunneling Microscope Technique

Authors: Jianshu Yang, Delphine Sordes, Marek Kolmer, Christian Joachim

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Nanoelectronics, for example the calculating circuits integrating at molecule scale logic gates, atomic scale circuits, has been constructed and investigated recently. A major challenge is their functional properties characterization because of the connecting problem from atomic scale to micrometer scale. New experimental instruments and new processes have been proposed therefore. To satisfy a precisely measurement at atomic scale and then connecting micrometer scale electrical integration controller, the technique improvement is kept on going. Our new machine, a low temperature high vacuum four scanning tunneling microscope, as a customer required instrument constructed by Omicron GmbH, is expected to be scaling down to atomic scale characterization. Here, we will present our first testified results about the performance of this new instrument. The sample we selected is Au(111) surface. The measurements have been taken at 4.2 K. The atomic resolution surface structure was observed with each of four scanners with noise level better than 3 pm. With a tip-sample distance calibration by I-z spectra, the sample conductance has been derived from its atomic locally I-V spectra. Furthermore, the surface conductance measurement has been performed using two methods, (1) by landing two STM tips on the surface with sample floating; and (2) by sample floating and one of the landed tips turned to be grounding. In addition, single atom manipulation has been achieved with a modified tip design, which is comparable to a conventional LT-STM.

Keywords: low temperature ultra-high vacuum four scanning tunneling microscope, nanoelectronics, point contact, single atom manipulation, tunneling resistance

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812 Mixed Mode Fracture Analyses Using Finite Element Method of Edge Cracked Heavy Spinning Annulus Pulley

Authors: Bijit Kalita, K. V. N. Surendra

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Rotating disk is one of the most indispensable parts of a rotating machine. Rotating disk has found many applications in the diverging field of science and technology. In this paper, we have taken into consideration the problem of a heavy spinning disk mounted on a rotor system acted upon by boundary traction. Finite element modelling is used at various loading condition to determine the mixed mode stress intensity factors. The effect of combined shear and normal traction on the boundary is incorporated in the analysis under the action of gravity. The variation near the crack tip is characterized in terms of the stress intensity factor (SIF) with an aim to find the SIF for a wide range of parameters. The results of the finite element analyses carried out on the compressed disk of a belt pulley arrangement using fracture mechanics concepts are shown. A total of hundred cases of the problem are solved for each of the variations in loading arc parameter and crack orientation using finite element models of the disc under compression. All models were prepared and analyzed for the uncracked disk, disk with a single crack at different orientation emanating from shaft hole as well as for a disc with pair of cracks emerging from the same center hole. Curves are plotted for various loading conditions. Finally, crack propagation paths are determined using kink angle concepts.

Keywords: crack-tip deformations, static loading, stress concentration, stress intensity factor

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811 A Study of Bilingual Development of a Mandarin and English Bilingual Preschool Child from China to Australia

Authors: Qiang Guo, Ruying Qi

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This project aims to trace the developmental patterns of a child's Mandarin and English from China to Australia from age 3; 03 till 5; 06. In childhood bilingual studies, there is an assumption that age 3 is the dividing line between simultaneous bilinguals and sequential bilinguals. Determining similarities and differences between Bilingual First Language Acquisition, Early Second Language Acquisition, and Second Language Acquisition is of great theoretical significance. Studies on Bilingual First Language Acquisition, hereafter, BFLA in the past three decades have shown that the grammatical development of bilingual children progresses through the same developmental trajectories as their monolingual counterparts. Cross-linguistic interaction does not show changes of the basic grammatical knowledge, even in the weaker language. While BFLA studies show consistent results under the conditions of adequate input and meaningful interactional context, the research findings of Early Second Language Acquisition (ESLA) have demonstrated that this cohort proceeds their early English differently from both BFLA and SLA. The different development could be attributed to the age of migration, input pattern, and their Environmental Languages (Lε). In the meantime, the dynamic relationship between the two languages is an issue to invite further attention. The present study attempts to fill this gap. The child in this case study started acquiring L1 Mandarin from birth in China, where the environmental language (Lε) coincided with L1 Mandarin. When she migrated to Australia at 3;06, where the environmental language (Lε) was L2 English, her Mandarin exposure was reduced. On the other hand, she received limited English input starting from 1; 02 in China, where the environmental language (Lε) was L1 Mandarin, a non-English environment. When she relocated to Australia at 3; 06, where the environmental language (Lε) coincided with L2 English, her English exposure significantly increased. The child’s linguistic profile provides an opportunity to explore: (1) What does the child’s English developmental route look like? (2) What does the L1 Mandarin developmental pattern look like in different environmental languages? (3) How do input and environmental language interact in shaping the bilingual child’s linguistic repertoire? In order to answer these questions, two linguistic areas are selected as the focus of the investigation, namely, subject realization and wh-questions. The chosen areas are contrastive in structure but perform the same semantic functions in the two linguistically distant languages and can serve as an ideal testing ground for exploring the developmental path in the two languages. The longitudinal case study adopts a combined approach of qualitative and quantitative analysis. Two years’ Mandarin and English data are examined, and comparisons are made with age-matched monolinguals in each language in CHILDES. To the author’s best knowledge, this study is the first of this kind examining a Mandarin-English bilingual child's bilingual development at a critical age, in different input patterns, and in different environmental languages (Lε). It also expands the scope of the theory of Lε, adding empirical evidence on the relationship between input and Lε in bilingual acquisition.

Keywords: bilingual development, age, input, environmental language (Le)

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810 Convention Refugees in New Zealand: Being Trapped in Immigration Limbo without the Right to Obtain a Visa

Authors: Saska Alexandria Hayes

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Multiple Convention Refugees in New Zealand are stuck in a state of immigration limbo due to a lack of defined immigration policies. The Refugee Convention of 1951 does not give the right to be issued a permanent right to live and work in the country of asylum. A gap in New Zealand's immigration law and policy has left Convention Refugees without the right to obtain a resident or temporary entry visa. The significant lack of literature on this topic suggests that the lack of visa options for Convention Refugees in New Zealand is a widely unknown or unacknowledged issue. Refugees in New Zealand enjoy the right of non-refoulement contained in Article 33 of the Refugee Convention 1951, whether lawful or unlawful. However, a number of rights contained in the Refugee Convention 1951, such as the right to gainful employment and social security, are limited to refugees who maintain lawful immigration status. If a Convention Refugee is denied a resident visa, the only temporary entry visa a Convention Refugee can apply for in New Zealand is discretionary. The appeal cases heard at the Immigration Protection Tribunal establish that Immigration New Zealand has declined resident and discretionary temporary entry visa applications by Convention Refugees for failing to meet the health or character immigration instructions. The inability of a Convention Refugee to gain residency in New Zealand creates a dependence on the issue of discretionary temporary entry visas to maintain lawful status. The appeal cases record that this reliance has led to Convention Refugees' lawful immigration status being in question, temporarily depriving them of the rights contained in the Refugee Convention 1951 of lawful refugees. In one case, the process of applying for a discretionary temporary entry visa led to a lawful Convention Refugee being temporarily deprived of the right to social security, breaching Article 24 of the Refugee Convention 1951. The judiciary has stated a constant reliance on the issue of discretionary temporary entry visas for Convention Refugees can lead to a breach of New Zealand's international obligations under Article 7 of the International Covenant on Civil and Political Rights. The appeal cases suggest that, despite successful judicial proceedings, at least three persons have been made to rely on the issue of discretionary temporary entry visas potentially indefinitely. The appeal cases establish that a Convention Refugee can be denied a discretionary temporary entry visa and become unlawful. Unlawful status could ultimately breach New Zealand's obligations under Article 33 of the Refugee Convention 1951 as it would procedurally deny Convention Refugees asylum. It would force them to choose between the right of non-refoulement or leaving New Zealand to seek the ability to access all the human rights contained in the Universal Declaration of Human Rights elsewhere. This paper discusses how the current system has given rise to these breaches and emphasizes a need to create a designated temporary entry visa category for Convention Refugees.

Keywords: domestic policy, immigration, migration, New Zealand

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809 A Comparative Human Rights Analysis of Deprivation of Citizenship as a Counterterrorism Instrument: An Evaluation of Belgium

Authors: Louise Reyntjens

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In response to Islamic-inspired terrorism and the growing trend of foreign fighters, European governments are increasingly relying on the deprivation of citizenship as a security tool. This development fits within a broader securitization of immigration, where the terrorist threat is perceived as emanating from abroad. As a result, immigration law became more and more ‘securitized’. The European migration crisis has reinforced this trend. This research evaluates the deprivation of citizenship from a human rights perspective. For this, the author selected four European countries for a comparative study: Belgium, France, the United Kingdom and Sweden. All these countries face similar social and security issues, vitalizing (the debate on) deprivation of citizenship as a counterterrorism tool. Yet, they adopt a very different approach on this: The United Kingdom positions itself on the repressive side of the spectrum. Sweden on the other hand, also ‘securitized’ its immigration policy after the recent terrorist hit in Stockholm but remains on the tolerant side of the spectrum. Belgium and France are situated in between. This contribution evaluates the deprivation of citizenship in Belgium. Belgian law has provided the possibility to strip someone of their Belgian citizenship since 1919. However, the provision long remained a dead letter. The 2015 Charlie Hebdo attacks in Paris sparked a series of legislative changes, elevating the deprivation measure to a key security tool in Belgian law. Yet, the measure raises profound human rights issues. Firstly, it infringes the right to private and family life. As provided by Article 8 (2) European Court of Human Right (ECHR), this right can be limited if necessary for national security and public safety. Serious questions can however be raised about the necessity for the national security of depriving an individual of its citizenship. Behavior giving rise to this measure will generally be governed by criminal law. From a security perspective, criminal detention will thus already provide in removing the individual from society. Moreover, simply stripping an individual of its citizenship and deporting them constitutes a failure of criminal law’s responsibility to prosecute criminal behavior. Deprivation of citizenship is also discriminatory, because it differentiates, without a legitimate reason, between those liable to deprivation and those who are not. It thereby installs a secondary class of citizens, violating the European Court of Human Right’s principle that no distinction can be tolerated between children on the basis of the status of their parents. If followed by expulsion, deprivation also seriously jeopardizes the right to life and prohibition of torture. This contribution explores the human rights consequences of citizenship deprivation as a security tool in Belgium. It also offers a critical view on its efficacy for protecting national security.

Keywords: Belgium, counterterrorism strategies, deprivation of citizenship, human rights, immigration law

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808 Automatic Multi-Label Image Annotation System Guided by Firefly Algorithm and Bayesian Method

Authors: Saad M. Darwish, Mohamed A. El-Iskandarani, Guitar M. Shawkat

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Nowadays, the amount of available multimedia data is continuously on the rise. The need to find a required image for an ordinary user is a challenging task. Content based image retrieval (CBIR) computes relevance based on the visual similarity of low-level image features such as color, textures, etc. However, there is a gap between low-level visual features and semantic meanings required by applications. The typical method of bridging the semantic gap is through the automatic image annotation (AIA) that extracts semantic features using machine learning techniques. In this paper, a multi-label image annotation system guided by Firefly and Bayesian method is proposed. Firstly, images are segmented using the maximum variance intra cluster and Firefly algorithm, which is a swarm-based approach with high convergence speed, less computation rate and search for the optimal multiple threshold. Feature extraction techniques based on color features and region properties are applied to obtain the representative features. After that, the images are annotated using translation model based on the Net Bayes system, which is efficient for multi-label learning with high precision and less complexity. Experiments are performed using Corel Database. The results show that the proposed system is better than traditional ones for automatic image annotation and retrieval.

Keywords: feature extraction, feature selection, image annotation, classification

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807 Impact of Non-Parental Early Childhood Education on Digital Friendship Tendency

Authors: Sheel Chakraborty

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Modern society in developed countries has distanced itself from the earlier norm of joint family living, and with the increase of economic pressure, parents' availability for their children during their infant years has been consistently decreasing over the past three decades. During the same time, the pre-primary education system - built mainly on the developmental psychology theory framework of Jean Piaget and Lev Vygotsky, has been promoted in the US through the legislature and funding. Early care and education may have a positive impact on young minds, but a growing number of kids facing social challenges in making friendships in their teenage years raises serious concerns about its effectiveness. The survey-based primary research presented here shows a statistically significant number of millennials between the ages of 10 and 25 prefer to build friendships virtually than face-to-face interactions. Moreover, many teenagers depend more on their virtual friends whom they never met. Contrary to the belief that early social interactions in a non-home setup make the kids confident and more prepared for the real world, many shy-natured kids seem to develop a sense of shakiness in forming social relationships, resulting in loneliness by the time they are young adults. Reflecting on George Mead’s theory of self that is made up of “I” and “Me”, most functioning homes provide the required freedom and forgivable, congenial environment for building the "I" of a toddler; however, daycare or preschools can barely match that. It seems social images created from the expectations perceived by preschoolers “Me" in a non-home setting may interfere and greatly overpower the formation of a confident "I" thus creating a crisis around the inability to form friendships face to face when they grow older. Though the pervasive nature of social media can’t be ignored, the non-parental early care and education practices adopted largely by the urban population have created a favorable platform of teen psychology on which social media popularity thrived, especially providing refuge to shy Gen-Z teenagers. This can explain why young adults today perceive social media as their preferred outlet of expression and a place to form dependable friendships, despite the risk of being cyberbullied.

Keywords: digital socialization, shyness, developmental psychology, friendship, early education

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806 Investigating the Determinants and Growth of Financial Technology Depth of Penetration among the Heterogeneous Africa Economies

Authors: Tochukwu Timothy Okoli, Devi Datt Tewari

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The high rate of Fintech adoption has not transmitted to greater financial inclusion and development in Africa. This problem is attributed to poor Fintech diversification and usefulness in the continent. This concept is referred to as the Fintech depth of penetration in this study. The study, therefore, assessed its determinants and growth process in a panel of three emergings, twenty-four frontiers and five fragile African economies disaggregated with dummies over the period 2004-2018 to allow for heterogeneity between groups. The System Generalized Method of Moments (GMM) technique reveals that the average depth of Mobile banking and automated teller machine (ATM) is a dynamic heterogeneity process. Moreover, users' previous experiences/compatibility, trial-ability/income, and financial development were the major factors that raise its usefulness, whereas perceived risk, financial openness, and inflation rate significantly limit its usefulness. The growth rate of Mobile banking, ATM, and Internet banking in 2018 is, on average 41.82, 0.4, and 20.8 per cent respectively greater than its average rates in 2004. These greater averages after the 2009 financial crisis suggest that countries resort to Fintech as a risk-mitigating tool. This study, therefore, recommends greater Fintech diversification through improved literacy, institutional development, financial liberalization, and continuous innovation.

Keywords: depth of fintech, emerging Africa, financial technology, internet banking, mobile banking

Procedia PDF Downloads 113
805 Stress Concentration Trend for Combined Loading Conditions

Authors: Aderet M. Pantierer, Shmuel Pantierer, Raphael Cordina, Yougashwar Budhoo

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Stress concentration occurs when there is an abrupt change in geometry, a mechanical part under loading. These changes in geometry can include holes, notches, or cracks within the component. The modifications create larger stress within the part. This maximum stress is difficult to determine, as it is directly at the point of the minimum area. Strain gauges have yet to be developed to analyze stresses at such minute areas. Therefore, a stress concentration factor must be utilized. The stress concentration factor is a dimensionless parameter calculated solely on the geometry of a part. The factor is multiplied by the nominal, or average, stress of the component, which can be found analytically or experimentally. Stress concentration graphs exist for common loading conditions and geometrical configurations to aid in the determination of the maximum stress a part can withstand. These graphs were developed from historical data yielded from experimentation. This project seeks to verify a stress concentration graph for combined loading conditions. The aforementioned graph was developed using CATIA Finite Element Analysis software. The results of this analysis will be validated through further testing. The 3D modeled parts will be subjected to further finite element analysis using Patran-Nastran software. The finite element models will then be verified by testing physical specimen using a tensile testing machine. Once the data is validated, the unique stress concentration graph will be submitted for publication so it can aid engineers in future projects.

Keywords: stress concentration, finite element analysis, finite element models, combined loading

Procedia PDF Downloads 415
804 Prediction of Distillation Curve and Reid Vapor Pressure of Dual-Alcohol Gasoline Blends Using Artificial Neural Network for the Determination of Fuel Performance

Authors: Leonard D. Agana, Wendell Ace Dela Cruz, Arjan C. Lingaya, Bonifacio T. Doma Jr.

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The purpose of this paper is to study the predict the fuel performance parameters, which include drivability index (DI), vapor lock index (VLI), and vapor lock potential using distillation curve and Reid vapor pressure (RVP) of dual alcohol-gasoline fuel blends. Distillation curve and Reid vapor pressure were predicted using artificial neural networks (ANN) with macroscopic properties such as boiling points, RVP, and molecular weights as the input layers. The ANN consists of 5 hidden layers and was trained using Bayesian regularization. The training mean square error (MSE) and R-value for the ANN of RVP are 91.4113 and 0.9151, respectively, while the training MSE and R-value for the distillation curve are 33.4867 and 0.9927. Fuel performance analysis of the dual alcohol–gasoline blends indicated that highly volatile gasoline blended with dual alcohols results in non-compliant fuel blends with D4814 standard. Mixtures of low-volatile gasoline and 10% methanol or 10% ethanol can still be blended with up to 10% C3 and C4 alcohols. Intermediate volatile gasoline containing 10% methanol or 10% ethanol can still be blended with C3 and C4 alcohols that have low RVPs, such as 1-propanol, 1-butanol, 2-butanol, and i-butanol. Biography: Graduate School of Chemical, Biological, and Materials Engineering and Sciences, Mapua University, Muralla St., Intramuros, Manila, 1002, Philippines

Keywords: dual alcohol-gasoline blends, distillation curve, machine learning, reid vapor pressure

Procedia PDF Downloads 79
803 Fly ash Contamination in Groundwater and its Implications on Local Climate Change

Authors: Rajkumar Ghosh

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Fly ash, a byproduct of coal combustion, has become a prevalent environmental concern due to its potential impact on both groundwater quality and local climate change. This study aims to provide an in-depth analysis of the various mechanisms through which fly ash contaminates groundwater, as well as the possible consequences of this contamination on local climate change. The presence of fly ash in groundwater not only poses a risk to human health but also has the potential to influence local climate change through complex interactions. Although fly ash has various applications in construction and other industries, improper disposal and lack of containment measures have led to its infiltration into groundwater systems. Through a comprehensive review of existing literature and case studies, the interactions between fly ash and groundwater systems, assess the effects on hydrology, and discuss the implications for the broader climate. This section reviews the pathways through which fly ash enters groundwater, including leaching from disposal sites, infiltration through soil, and migration from surface water bodies. The physical and chemical characteristics of fly ash that contribute to its mobility and persistence in groundwater. The introduction of fly ash into groundwater can alter its chemical composition, leading to an increase in the concentration of heavy metals, metalloids, and other potentially toxic elements. The mechanisms of contaminant transport and highlight the potential risks to human health and ecosystems. Fly ash contamination in groundwater may influence the hydrological cycle through changes in groundwater recharge, discharge, and flow dynamics. This section examines the implications of altered hydrology on local water availability, aquatic habitats, and overall ecosystem health. The presence of fly ash in groundwater may have direct and indirect effects on local climate change. The role of fly ash as a potent greenhouse gas absorber and its contribution to radiative forcing. Additionally, investigation of the possible feedback mechanisms between groundwater contamination and climate change, such as altered vegetation patterns and changes in local temperature and precipitation patterns. In this section, potential mitigation and remediation techniques to minimize fly ash contamination in groundwater are analyzed. These may include improved waste management practices, engineered barriers, groundwater remediation technologies, and sustainable fly ash utilization. This paper highlights the critical link between fly ash contamination in groundwater and its potential contribution to local climate change. It emphasizes the importance of addressing this issue promptly through a combination of preventive measures, effective management strategies, and continuous monitoring. By understanding the interconnections between fly ash contamination, groundwater quality, and local climate, towards creating a more resilient and sustainable environment for future generations. The findings of this research can assist policymakers and environmental managers in formulating sustainable strategies to mitigate fly ash contamination and minimize its contribution to climate change.

Keywords: groundwater, climate, sustainable environment, fly ash contamination

Procedia PDF Downloads 62
802 Procedural Protocol for Dual Energy Computed Tomography (DECT) Inversion

Authors: Rezvan Ravanfar Haghighi, S. Chatterjee, Pratik Kumar, V. C. Vani, Priya Jagia, Sanjiv Sharma, Susama Rani Mandal, R. Lakshmy

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The dual energy computed tomography (DECT) aims at noting the HU(V) values for the sample at two different voltages V=V1, V2 and thus obtain the electron densities (ρe) and effective atomic number (Zeff) of the substance. In the present paper, we aim to obtain a numerical algorithm by which (ρe, Zeff) can be obtained from the HU(100) and HU(140) data, where V=100, 140 kVp. The idea is to use this inversion method to characterize and distinguish between the lipid and fibrous coronary artery plaques.With the idea to develop the inversion algorithm for low Zeff materials, as is the case with non calcified coronary artery plaque, we prepare aqueous samples whose calculated values of (ρe, Zeff) lie in the range (2.65×1023≤ ρe≤ 3.64×1023 per cc ) and (6.80≤ Zeff ≤ 8.90). We fill the phantom with these known samples and experimentally determine HU(100) and HU(140) for the same pixels. Knowing that the HU(V) values are related to the attenuation coefficient of the system, we present an algorithm by which the (ρe, Zeff) is calibrated with respect to (HU(100), HU(140)). The calibration is done with a known set of 20 samples; its accuracy is checked with a different set of 23 known samples. We find that the calibration gives the ρe with an accuracy of ± 4% while Zeff is found within ±1% of the actual value, the confidence being 95%.In this inversion method (ρe, Zeff) of the scanned sample can be found by eliminating the effects of the CT machine and also by ensuring that the determination of the two unknowns (ρe, Zeff) does not interfere with each other. It is found that this algorithm can be used for prediction of chemical characteristic (ρe, Zeff) of unknown scanned materials with 95% confidence level, by inversion of the DECT data.

Keywords: chemical composition, dual-energy computed tomography, inversion algorithm

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801 Hand Gesture Interface for PC Control and SMS Notification Using MEMS Sensors

Authors: Keerthana E., Lohithya S., Harshavardhini K. S., Saranya G., Suganthi S.

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In an epoch of expanding human-machine interaction, the development of innovative interfaces that bridge the gap between physical gestures and digital control has gained significant momentum. This study introduces a distinct solution that leverages a combination of MEMS (Micro-Electro-Mechanical Systems) sensors, an Arduino Mega microcontroller, and a PC to create a hand gesture interface for PC control and SMS notification. The core of the system is an ADXL335 MEMS accelerometer sensor integrated with an Arduino Mega, which communicates with a PC via a USB cable. The ADXL335 provides real-time acceleration data, which is processed by the Arduino to detect specific hand gestures. These gestures, such as left, right, up, down, or custom patterns, are interpreted by the Arduino, and corresponding actions are triggered. In the context of SMS notifications, when a gesture indicative of a new SMS is recognized, the Arduino relays this information to the PC through the serial connection. The PC application, designed to monitor the Arduino's serial port, displays these SMS notifications in the serial monitor. This study offers an engaging and interactive means of interfacing with a PC by translating hand gestures into meaningful actions, opening up opportunities for intuitive computer control. Furthermore, the integration of SMS notifications adds a practical dimension to the system, notifying users of incoming messages as they interact with their computers. The use of MEMS sensors, Arduino, and serial communication serves as a promising foundation for expanding the capabilities of gesture-based control systems.

Keywords: hand gestures, multiple cables, serial communication, sms notification

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800 Landscape Pattern Evolution and Optimization Strategy in Wuhan Urban Development Zone, China

Authors: Feng Yue, Fei Dai

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With the rapid development of urbanization process in China, its environmental protection pressure is severely tested. So, analyzing and optimizing the landscape pattern is an important measure to ease the pressure on the ecological environment. This paper takes Wuhan Urban Development Zone as the research object, and studies its landscape pattern evolution and quantitative optimization strategy. First, remote sensing image data from 1990 to 2015 were interpreted by using Erdas software. Next, the landscape pattern index of landscape level, class level, and patch level was studied based on Fragstats. Then five indicators of ecological environment based on National Environmental Protection Standard of China were selected to evaluate the impact of landscape pattern evolution on the ecological environment. Besides, the cost distance analysis of ArcGIS was applied to simulate wildlife migration thus indirectly measuring the improvement of ecological environment quality. The result shows that the area of land for construction increased 491%. But the bare land, sparse grassland, forest, farmland, water decreased 82%, 47%, 36%, 25% and 11% respectively. They were mainly converted into construction land. On landscape level, the change of landscape index all showed a downward trend. Number of patches (NP), Landscape shape index (LSI), Connection index (CONNECT), Shannon's diversity index (SHDI), Aggregation index (AI) separately decreased by 2778, 25.7, 0.042, 0.6, 29.2%, all of which indicated that the NP, the degree of aggregation and the landscape connectivity declined. On class level, the construction land and forest, CPLAND, TCA, AI and LSI ascended, but the Distribution Statistics Core Area (CORE_AM) decreased. As for farmland, water, sparse grassland, bare land, CPLAND, TCA and DIVISION, the Patch Density (PD) and LSI descended, yet the patch fragmentation and CORE_AM increased. On patch level, patch area, Patch perimeter, Shape index of water, farmland and bare land continued to decline. The three indexes of forest patches increased overall, sparse grassland decreased as a whole, and construction land increased. It is obvious that the urbanization greatly influenced the landscape evolution. Ecological diversity and landscape heterogeneity of ecological patches clearly dropped. The Habitat Quality Index continuously declined by 14%. Therefore, optimization strategy based on greenway network planning is raised for discussion. This paper contributes to the study of landscape pattern evolution in planning and design and to the research on spatial layout of urbanization.

Keywords: landscape pattern, optimization strategy, ArcGIS, Erdas, landscape metrics, landscape architecture

Procedia PDF Downloads 141
799 Visual Speech Perception of Arabic Emphatics

Authors: Maha Saliba Foster

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Speech perception has been recognized as a bi-sensory process involving the auditory and visual channels. Compared to the auditory modality, the contribution of the visual signal to speech perception is not very well understood. Studying how the visual modality affects speech recognition can have pedagogical implications in second language learning, as well as clinical application in speech therapy. The current investigation explores the potential effect of speech visual cues on the perception of Arabic emphatics (AEs). The corpus consists of 36 minimal pairs each containing two contrasting consonants, an AE versus a non-emphatic (NE). Movies of four Lebanese speakers were edited to allow perceivers to have partial view of facial regions: lips only, lips-cheeks, lips-chin, lips-cheeks-chin, lips-cheeks-chin-neck. In the absence of any auditory information and relying solely on visual speech, perceivers were above chance at correctly identifying AEs or NEs across vowel contexts; moreover, the models were able to predict the probability of perceivers’ accuracy in identifying some of the COIs produced by certain speakers; additionally, results showed an overlap between the measurements selected by the computer and those selected by human perceivers. The lack of significant face effect on the perception of AEs seems to point to the lips, present in all of the videos, as the most important and often sufficient facial feature for emphasis recognition. Future investigations will aim at refining the analyses of visual cues used by perceivers by using Principal Component Analysis and including time evolution of facial feature measurements.

Keywords: Arabic emphatics, machine learning, speech perception, visual speech perception

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798 Tomato-Weed Classification by RetinaNet One-Step Neural Network

Authors: Dionisio Andujar, Juan lópez-Correa, Hugo Moreno, Angela Ri

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The increased number of weeds in tomato crops highly lower yields. Weed identification with the aim of machine learning is important to carry out site-specific control. The last advances in computer vision are a powerful tool to face the problem. The analysis of RGB (Red, Green, Blue) images through Artificial Neural Networks had been rapidly developed in the past few years, providing new methods for weed classification. The development of the algorithms for crop and weed species classification looks for a real-time classification system using Object Detection algorithms based on Convolutional Neural Networks. The site study was located in commercial corn fields. The classification system has been tested. The procedure can detect and classify weed seedlings in tomato fields. The input to the Neural Network was a set of 10,000 RGB images with a natural infestation of Cyperus rotundus l., Echinochloa crus galli L., Setaria italica L., Portulaca oeracea L., and Solanum nigrum L. The validation process was done with a random selection of RGB images containing the aforementioned species. The mean average precision (mAP) was established as the metric for object detection. The results showed agreements higher than 95 %. The system will provide the input for an online spraying system. Thus, this work plays an important role in Site Specific Weed Management by reducing herbicide use in a single step.

Keywords: deep learning, object detection, cnn, tomato, weeds

Procedia PDF Downloads 88
797 Strategic Interventions to Combat Socio-economic Impacts of Drought in Thar - A Case Study of Nagarparkar

Authors: Anila Hayat

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Pakistan is one of those developing countries that are least involved in emissions but has the most vulnerable environmental conditions. Pakistan is ranked 8th in most affected countries by climate change on the climate risk index 1992-2011. Pakistan is facing severe water shortages and flooding as a result of changes in rainfall patterns, specifically in the least developed areas such as Tharparkar. Nagarparkar, once an attractive tourist spot located in Tharparkar because of its tropical desert climate, is now facing severe drought conditions for the last few decades. This study investigates the present socio-economic situation of local communities, major impacts of droughts and their underlying causes and current mitigation strategies adopted by local communities. The study uses both secondary (quantitative in nature) and primary (qualitative in nature) methods to understand the impacts and explore causes on the socio-economic life of local communities of the study area. The relevant data has been collected through household surveys using structured questionnaires, focus groups and in-depth interviews of key personnel from local and international NGOs to explore the sensitivity of impacts and adaptation to droughts in the study area. This investigation is limited to four rural communities of union council Pilu of Nagarparkar district, including Bheel, BhojaBhoon, Mohd Rahan Ji Dhani and Yaqub Ji Dhani villages. The results indicate that drought has caused significant economic and social hardships for the local communities as more than 60% of the overall population is dependent on rainfall which has been disturbed by irregular rainfall patterns. The decline in Crop yields has forced the local community to migrate to nearby areas in search of livelihood opportunities. Communities have not undertaken any appropriate adaptive actions to counteract the adverse effect of drought; they are completely dependent on support from the government and external aid for survival. Respondents also reported that poverty is a major cause of their vulnerability to drought. An increase in population, limited livelihood opportunities, caste system, lack of interest from the government sector, unawareness shaped their vulnerability to drought and other social issues. Based on the findings of this study, it is recommended that the local authorities shall create awareness about drought hazards and improve the resilience of communities against drought. It is further suggested to develop, introduce and implement water harvesting practices at the community level to promote drought-resistant crops.

Keywords: migration, vulnerability, awareness, Drought

Procedia PDF Downloads 117
796 Virtual Screening and in Silico Toxicity Property Prediction of Compounds against Mycobacterium tuberculosis Lipoate Protein Ligase B (LipB)

Authors: Junie B. Billones, Maria Constancia O. Carrillo, Voltaire G. Organo, Stephani Joy Y. Macalino, Inno A. Emnacen, Jamie Bernadette A. Sy

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The drug discovery and development process is generally known to be a very lengthy and labor-intensive process. Therefore, in order to be able to deliver prompt and effective responses to cure certain diseases, there is an urgent need to reduce the time and resources needed to design, develop, and optimize potential drugs. Computer-aided drug design (CADD) is able to alleviate this issue by applying computational power in order to streamline the whole drug discovery process, starting from target identification to lead optimization. This drug design approach can be predominantly applied to diseases that cause major public health concerns, such as tuberculosis. Hitherto, there has been no concrete cure for this disease, especially with the continuing emergence of drug resistant strains. In this study, CADD is employed for tuberculosis by first identifying a key enzyme in the mycobacterium’s metabolic pathway that would make a good drug target. One such potential target is the lipoate protein ligase B enzyme (LipB), which is a key enzyme in the M. tuberculosis metabolic pathway involved in the biosynthesis of the lipoic acid cofactor. Its expression is considerably up-regulated in patients with multi-drug resistant tuberculosis (MDR-TB) and it has no known back-up mechanism that can take over its function when inhibited, making it an extremely attractive target. Using cutting-edge computational methods, compounds from AnalytiCon Discovery Natural Derivatives database were screened and docked against the LipB enzyme in order to rank them based on their binding affinities. Compounds which have better binding affinities than LipB’s known inhibitor, decanoic acid, were subjected to in silico toxicity evaluation using the ADMET and TOPKAT protocols. Out of the 31,692 compounds in the database, 112 of these showed better binding energies than decanoic acid. Furthermore, 12 out of the 112 compounds showed highly promising ADMET and TOPKAT properties. Future studies involving in vitro or in vivo bioassays may be done to further confirm the therapeutic efficacy of these 12 compounds, which eventually may then lead to a novel class of anti-tuberculosis drugs.

Keywords: pharmacophore, molecular docking, lipoate protein ligase B (LipB), ADMET, TOPKAT

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795 A Flute Tracking System for Monitoring the Wear of Cutting Tools in Milling Operations

Authors: Hatim Laalej, Salvador Sumohano-Verdeja, Thomas McLeay

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Monitoring of tool wear in milling operations is essential for achieving the desired dimensional accuracy and surface finish of a machined workpiece. Although there are numerous statistical models and artificial intelligence techniques available for monitoring the wear of cutting tools, these techniques cannot pin point which cutting edge of the tool, or which insert in the case of indexable tooling, is worn or broken. Currently, the task of monitoring the wear on the tool cutting edges is carried out by the operator who performs a manual inspection, causing undesirable stoppages of machine tools and consequently resulting in costs incurred from lost productivity. The present study is concerned with the development of a flute tracking system to segment signals related to each physical flute of a cutter with three flutes used in an end milling operation. The purpose of the system is to monitor the cutting condition for individual flutes separately in order to determine their progressive wear rates and to predict imminent tool failure. The results of this study clearly show that signals associated with each flute can be effectively segmented using the proposed flute tracking system. Furthermore, the results illustrate that by segmenting the sensor signal by flutes it is possible to investigate the wear in each physical cutting edge of the cutting tool. These findings are significant in that they facilitate the online condition monitoring of a cutting tool for each specific flute without the need for operators/engineers to perform manual inspections of the tool.

Keywords: machining, milling operation, tool condition monitoring, tool wear prediction

Procedia PDF Downloads 290
794 A Deep Learning Approach to Online Social Network Account Compromisation

Authors: Edward K. Boahen, Brunel E. Bouya-Moko, Changda Wang

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The major threat to online social network (OSN) users is account compromisation. Spammers now spread malicious messages by exploiting the trust relationship established between account owners and their friends. The challenge in detecting a compromised account by service providers is validating the trusted relationship established between the account owners, their friends, and the spammers. Another challenge is the increase in required human interaction with the feature selection. Research available on supervised learning (machine learning) has limitations with the feature selection and accounts that cannot be profiled, like application programming interface (API). Therefore, this paper discusses the various behaviours of the OSN users and the current approaches in detecting a compromised OSN account, emphasizing its limitations and challenges. We propose a deep learning approach that addresses and resolve the constraints faced by the previous schemes. We detailed our proposed optimized nonsymmetric deep auto-encoder (OPT_NDAE) for unsupervised feature learning, which reduces the required human interaction levels in the selection and extraction of features. We evaluated our proposed classifier using the NSL-KDD and KDDCUP'99 datasets in a graphical user interface enabled Weka application. The results obtained indicate that our proposed approach outperformed most of the traditional schemes in OSN compromised account detection with an accuracy rate of 99.86%.

Keywords: computer security, network security, online social network, account compromisation

Procedia PDF Downloads 99