Search results for: real quantum mechanics
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5948

Search results for: real quantum mechanics

3368 Semi-Supervised Outlier Detection Using a Generative and Adversary Framework

Authors: Jindong Gu, Matthias Schubert, Volker Tresp

Abstract:

In many outlier detection tasks, only training data belonging to one class, i.e., the positive class, is available. The task is then to predict a new data point as belonging either to the positive class or to the negative class, in which case the data point is considered an outlier. For this task, we propose a novel corrupted Generative Adversarial Network (CorGAN). In the adversarial process of training CorGAN, the Generator generates outlier samples for the negative class, and the Discriminator is trained to distinguish the positive training data from the generated negative data. The proposed framework is evaluated using an image dataset and a real-world network intrusion dataset. Our outlier-detection method achieves state-of-the-art performance on both tasks.

Keywords: one-class classification, outlier detection, generative adversary networks, semi-supervised learning

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3367 Unveiling Bengali Women’s Appreciation of Modernizing Japan

Authors: Lopamudra Malek

Abstract:

It is known to all that Japan was closed till 1853 abruptly; Commodore Culbreath Matthew Perry has played a pivotal role in Japan’s exposure to modernization and facing the real world as an Asian entity. As Japan opened its door for the world, Indians, especially four women from Bengal, visited Japan. They were Hariprova Takeda, Sarojnalini Dutta, Santa Devi and Parul Devi. All of them were from different entities, but there were some bewildering similarities also in their depiction. How they penetrated their exposure to modernizing Japan is the motto of the research. It should be mentioned that two of them were directly influenced by Rabindranath Tagore. The methodology that has been followed while doing this research is depending on secondary source materials, like books, articles, etc. Japan was changing herself relentlessly towards modernization and westernization and these four women had witnessed the changing Japan and how the changing Japan has reflected in their write-ups and autobiography is the fundamental part of the research. As all of them were women, they had compared themselves with Japanese women. The finding of the research is, astonishingly, all of them found and comprehended Japan as a country where women were having more financial sovereignty and freedom of thought comparing to India in those days.

Keywords: empowerment, Japan, modernization, women

Procedia PDF Downloads 202
3366 Testing the Change in Correlation Structure across Markets: High-Dimensional Data

Authors: Malay Bhattacharyya, Saparya Suresh

Abstract:

The Correlation Structure associated with a portfolio is subjected to vary across time. Studying the structural breaks in the time-dependent Correlation matrix associated with a collection had been a subject of interest for a better understanding of the market movements, portfolio selection, etc. The current paper proposes a methodology for testing the change in the time-dependent correlation structure of a portfolio in the high dimensional data using the techniques of generalized inverse, singular valued decomposition and multivariate distribution theory which has not been addressed so far. The asymptotic properties of the proposed test are derived. Also, the performance and the validity of the method is tested on a real data set. The proposed test performs well for detecting the change in the dependence of global markets in the context of high dimensional data.

Keywords: correlation structure, high dimensional data, multivariate distribution theory, singular valued decomposition

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3365 Fast and Robust Long-term Tracking with Effective Searching Model

Authors: Thang V. Kieu, Long P. Nguyen

Abstract:

Kernelized Correlation Filter (KCF) based trackers have gained a lot of attention recently because of their accuracy and fast calculation speed. However, this algorithm is not robust in cases where the object is lost by a sudden change of direction, being obscured or going out of view. In order to improve KCF performance in long-term tracking, this paper proposes an anomaly detection method for target loss warning by analyzing the response map of each frame, and a classification algorithm for reliable target re-locating mechanism by using Random fern. Being tested with Visual Tracker Benchmark and Visual Object Tracking datasets, the experimental results indicated that the precision and success rate of the proposed algorithm were 2.92 and 2.61 times higher than that of the original KCF algorithm, respectively. Moreover, the proposed tracker handles occlusion better than many state-of-the-art long-term tracking methods while running at 60 frames per second.

Keywords: correlation filter, long-term tracking, random fern, real-time tracking

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3364 Damage Assessment and Repair for Older Brick Buildings

Authors: Tim D. Sass

Abstract:

The experience of engineers and architects practicing today is typically limited to current building code requirements and modern construction methods and materials. However, many cities have a mix of new and old buildings with many buildings constructed over one hundred years ago when building codes and construction methods were much different. When a brick building sustains damage, a structural engineer is often hired to determine the cause of damage as well as determine the necessary repairs. Forensic studies of dozens of brick buildings shows an appreciation of historical building methods and materials is needed to correctly identify the cause of damage and design an appropriate repair. Damage on an older, brick building can be mistakenly attributed to storms or seismic events when the real source of the damage is deficient original construction. Assessing and remediating damaged brickwork on older brick buildings requires an understanding of the original construction, an understanding of older repair methods, and, an understanding of current building code requirements.

Keywords: brick, damage, deterioration, facade

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3363 Physical Properties of New Perovskite Kgex3 (X = F, Cl and Br) for Photovoltaic Applications

Authors: B. Bouadjemia, M. Houaria, S. Haida, Y. B. Idriss, A, Akham, M. Matouguia, A. Gasmia, T. Lantria, S. Bentataa

Abstract:

It have investigated the structural, optoelectronic, elastic and thermodynamic properties of KGeX₃ (X = F, Cl and Br) using the density functional theory (DFT) with generalized gradient approximation (GGA) for potential exchange correlation. The modified Becke-Johnson (mBJ-GGA) potential approximation is also used for calculating the optoelectronic properties of the material.The results show that the band structure of the metalloid halide perovskites KGeX₃ (X = F, Cl and Br) have a semiconductor behavior with direct band gap at R-R direction, the gap energy values for each compound as following: 2.83, 1.27 and 0.79eV respectively. The optical properties, such as real and imaginary parts of the dielectric functions, refractive index, reflectivity and absorption coefficient, are investigated. As results, these compounds are competent candidates for optoelectronic and photovoltaic devices in this range of the energy spectrum.

Keywords: density functional theory (DFT), semiconductor behavior, metalloid halide perovskites, optical propertie and photovoltaic devices

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3362 Performance Evaluation of Routing Protocols for Video Conference over MPLS VPN Network

Authors: Abdullah Al Mamun, Tarek R. Sheltami

Abstract:

Video conferencing is a highly demanding facility now a days in order to its real time characteristics, but faster communication is the prior requirement of this technology. Multi Protocol Label Switching (MPLS) IP Virtual Private Network (VPN) address this problem and it is able to make a communication faster than others techniques. However, this paper studies the performance comparison of video traffic between two routing protocols namely the Enhanced Interior Gateway Protocol(EIGRP) and Open Shortest Path First (OSPF). The combination of traditional routing and MPLS improve the forwarding mechanism, scalability and overall network performance. We will use GNS3 and OPNET Modeler 14.5 to simulate many different scenarios and metrics such as delay, jitter and mean opinion score (MOS) value are measured. The simulation result will show that OSPF and BGP-MPLS VPN offers best performance for video conferencing application.

Keywords: OSPF, BGP, EIGRP, MPLS, Video conference, Provider router, edge router, layer3 VPN

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3361 Scheduling Algorithm Based on Load-Aware Queue Partitioning in Heterogeneous Multi-Core Systems

Authors: Hong Kai, Zhong Jun Jie, Chen Lin Qi, Wang Chen Guang

Abstract:

There are inefficient global scheduling parallelism and local scheduling parallelism prone to processor starvation in current scheduling algorithms. Regarding this issue, this paper proposed a load-aware queue partitioning scheduling strategy by first allocating the queues according to the number of processor cores, calculating the load factor to specify the load queue capacity, and it assigned the awaiting nodes to the appropriate perceptual queues through the precursor nodes and the communication computation overhead. At the same time, real-time computation of the load factor could effectively prevent the processor from being starved for a long time. Experimental comparison with two classical algorithms shows that there is a certain improvement in both performance metrics of scheduling length and task speedup ratio.

Keywords: load-aware, scheduling algorithm, perceptual queue, heterogeneous multi-core

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3360 Text Similarity in Vector Space Models: A Comparative Study

Authors: Omid Shahmirzadi, Adam Lugowski, Kenneth Younge

Abstract:

Automatic measurement of semantic text similarity is an important task in natural language processing. In this paper, we evaluate the performance of different vector space models to perform this task. We address the real-world problem of modeling patent-to-patent similarity and compare TFIDF (and related extensions), topic models (e.g., latent semantic indexing), and neural models (e.g., paragraph vectors). Contrary to expectations, the added computational cost of text embedding methods is justified only when: 1) the target text is condensed; and 2) the similarity comparison is trivial. Otherwise, TFIDF performs surprisingly well in other cases: in particular for longer and more technical texts or for making finer-grained distinctions between nearest neighbors. Unexpectedly, extensions to the TFIDF method, such as adding noun phrases or calculating term weights incrementally, were not helpful in our context.

Keywords: big data, patent, text embedding, text similarity, vector space model

Procedia PDF Downloads 159
3359 Smoker Recognition from Lung X-Ray Images Using Convolutional Neural Network

Authors: Moumita Chanda, Md. Fazlul Karim Patwary

Abstract:

Smoking is one of the most popular recreational drug use behaviors, and it contributes to birth defects, COPD, heart attacks, and erectile dysfunction. To completely eradicate this disease, it is imperative that it be identified and treated. Numerous smoking cessation programs have been created, and they demonstrate how beneficial it may be to help someone stop smoking at the ideal time. A tomography meter is an effective smoking detector. Other wearables, such as RF-based proximity sensors worn on the collar and wrist to detect when the hand is close to the mouth, have been proposed in the past, but they are not impervious to deceptive variables. In this study, we create a machine that can discriminate between smokers and non-smokers in real-time with high sensitivity and specificity by watching and collecting the human lung and analyzing the X-ray data using machine learning. If it has the highest accuracy, this machine could be utilized in a hospital, in the selection of candidates for the army or police, or in university entrance.

Keywords: CNN, smoker detection, non-smoker detection, OpenCV, artificial Intelligence, X-ray Image detection

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3358 An Analysis of Sequential Pattern Mining on Databases Using Approximate Sequential Patterns

Authors: J. Suneetha, Vijayalaxmi

Abstract:

Sequential Pattern Mining involves applying data mining methods to large data repositories to extract usage patterns. Sequential pattern mining methodologies used to analyze the data and identify patterns. The patterns have been used to implement efficient systems can recommend on previously observed patterns, in making predictions, improve usability of systems, detecting events, and in general help in making strategic product decisions. In this paper, identified performance of approximate sequential pattern mining defines as identifying patterns approximately shared with many sequences. Approximate sequential patterns can effectively summarize and represent the databases by identifying the underlying trends in the data. Conducting an extensive and systematic performance over synthetic and real data. The results demonstrate that ApproxMAP effective and scalable in mining large sequences databases with long patterns.

Keywords: multiple data, performance analysis, sequential pattern, sequence database scalability

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3357 Enhancing Metaverse Security: A Multi-Factor Authentication Scheme

Authors: R. Chinnaiyaprabhu, S. Bharanidharan, V. Dharsana, Rajalavanya

Abstract:

The concept of the Metaverse represents a potential evolution in the realm of cyberspace. In the early stages of Web 2.0, we observed a proliferation of online pseudonyms or 'nyms,' which increased the prevalence of fake accounts and made it challenging to establish unique online identities for various roles. However, in the era of Web 3.0, particularly in the context of the Metaverse, an individual's digital identity is intrinsically linked to their real-world identity. Consequently, actions taken in the Metaverse can carry significant consequences in the physical world. In light of these considerations, we propose the development of an innovative authentication system known as 'Metasec.' This system is designed to enhance security for digital assets, online identities, avatars, and user accounts within the Metaverse. Notably, Metasec operates as a password less authentication solution, relying on a multifaceted approach to security, encompassing device attestation, facial recognition, and pattern-based security keys.

Keywords: metaverse, multifactor authentication, security, facial recognition, patten password

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3356 Computational Insight into a Mechanistic Overview of Water Exchange Kinetics and Thermodynamic Stabilities of Bis and Tris-Aquated Complexes of Lanthanides

Authors: Niharika Keot, Manabendra Sarma

Abstract:

A thorough investigation of Ln3+ complexes with more than one inner-sphere water molecule is crucial for designing high relaxivity contrast agents (CAs) used in magnetic resonance imaging (MRI). This study accomplished a comparative stability analysis of two hexadentate (H3cbda and H3dpaa) and two heptadentate (H4peada and H3tpaa) ligands with Ln3+ ions. The higher stability of the hexadentate H3cbda and heptadentate H4peada ligands has been confirmed by the binding affinity and Gibbs free energy analysis in aqueous solution. In addition, energy decomposition analysis (EDA) reveals the higher binding affinity of the peada4− ligand than the cbda3− ligand towards Ln3+ ions due to the higher charge density of the peada4− ligand. Moreover, a mechanistic overview of water exchange kinetics has been carried out based on the strength of the metal–water bond. The strength of the metal–water bond follows the trend Gd–O47 (w) > Gd–O39 (w) > Gd–O36 (w) in the case of the tris-aquated [Gd(cbda)(H2O)3] and Gd–O43 (w) > Gd–O40 (w) for the bis-aquated [Gd(peada)(H2O)2]− complex, which was confirmed by bond length, electron density (ρ), and electron localization function (ELF) at the corresponding bond critical points. Our analysis also predicts that the activation energy barrier decreases with the decrease in bond strength; hence kex increases. The 17O and 1H hyperfine coupling constant values of all the coordinated water molecules were different, calculated by using the second-order Douglas–Kroll–Hess (DKH2) approach. Furthermore, the ionic nature of the bonding in the metal–ligand (M–L) bond was confirmed by the Quantum Theory of Atoms-In-Molecules (QTAIM) and ELF along with energy decomposition analysis (EDA). We hope that the results can be used as a basis for the design of highly efficient Gd(III)-based high relaxivity MRI contrast agents for medical applications.

Keywords: MRI contrast agents, lanthanide chemistry, thermodynamic stability, water exchange kinetics

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3355 Role of Matric Suction in Mechanics behind Swelling Characteristics of Expansive Soils

Authors: Saloni Pandya, Nikhil Sharma, Ajanta Sachan

Abstract:

Expansive soils in the unsaturated state are part of vadose zone and encountered in several arid and semi-arid parts of the world. Influence of high temperature, low precipitation and alternate cycles of wetting and drying are responsible for the chemical weathering of rocks, which results in the formation of expansive soils. Shrinkage-swelling (expansive) soils cover a substantial portion of area in India. Damages caused by expansive soils to various geotechnical structures are alarming. Matric suction develops in unsaturated soil due to capillarity and surface tension phenomena. Matric suction influences the geometric arrangement of soil skeleton, which induces the volume change behaviour of expansive soil. In the present study, an attempt has been made to evaluate the role of matric suction in the mechanism behind swelling characteristics of expansive soil. Four different soils have been collected from different parts of India for the current research. Soil sample S1, S2, S3 and S4 were collected from Nagpur, Bharuch, Bharuch-Dahej highway and Ahmedabad respectively. DFSI (Differential Free Swell Index) of these soils samples; S1, S2, S3, and S4; were determined to be 134%, 104%, 70% and 30% respectively. X-ray diffraction analysis of samples exhibited that percentage of Montmorillonite mineral present in the soils reduced with the decrease in DFSI. A series of constant volume swell pressure tests and in-contact filter paper tests were performed to evaluate swelling pressure and matric suction of all four soils at 30% saturation and 1.46 g/cc dry density. Results indicated that soils possessing higher DFSI exhibited higher matric suction as compared to lower DFSI expansive soils. Significant influence of matric suction on swelling pressure of expansive soils was observed with varying DFSI values. Higher matric suction of soil might govern the water uptake in the interlayer spaces of Montmorillonite mineral present in expansive soil leading to crystalline swelling.

Keywords: differential free swell index, expansive soils, matric suction, swelling pressure

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3354 Cepstrum Analysis of Human Walking Signal

Authors: Koichi Kurita

Abstract:

In this study, we propose a real-time data collection technique for the detection of human walking motion from the charge generated on the human body. This technique is based on the detection of a sub-picoampere electrostatic induction current, generated by the motion, flowing through the electrode of a wireless portable sensor attached to the subject. An FFT analysis of the wave-forms of the electrostatic induction currents generated by the walking motions showed that the currents generated under normal and restricted walking conditions were different. Moreover, we carried out a cepstrum analysis to detect any differences in the walking style. Results suggest that a slight difference in motion, either due to the individual’s gait or a splinted leg, is directly reflected in the electrostatic induction current generated by the walking motion. The proposed wireless portable sensor enables the detection of even subtle differences in walking motion.

Keywords: human walking motion, motion measurement, current measurement, electrostatic induction

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3353 Adaptive Dehazing Using Fusion Strategy

Authors: M. Ramesh Kanthan, S. Naga Nandini Sujatha

Abstract:

The goal of haze removal algorithms is to enhance and recover details of scene from foggy image. In enhancement the proposed method focus into two main categories: (i) image enhancement based on Adaptive contrast Histogram equalization, and (ii) image edge strengthened Gradient model. Many circumstances accurate haze removal algorithms are needed. The de-fog feature works through a complex algorithm which first determines the fog destiny of the scene, then analyses the obscured image before applying contrast and sharpness adjustments to the video in real-time to produce image the fusion strategy is driven by the intrinsic properties of the original image and is highly dependent on the choice of the inputs and the weights. Then the output haze free image has reconstructed using fusion methodology. In order to increase the accuracy, interpolation method has used in the output reconstruction. A promising retrieval performance is achieved especially in particular examples.

Keywords: single image, fusion, dehazing, multi-scale fusion, per-pixel, weight map

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3352 Modeling and Simulation of Fluid Catalytic Cracking Process

Authors: Sungho Kim, Dae Shik Kim, Jong Min Lee

Abstract:

Fluid catalytic cracking (FCC) process is one of the most important process in modern refinery industry. This paper focuses on the fluid catalytic cracking (FCC) process. As the FCC process is difficult to model well, due to its non linearities and various interactions between its process variables, rigorous process modeling of whole FCC plant is demanded for control and plant-wide optimization of the plant. In this study, a process design for the FCC plant includes riser reactor, main fractionator, and gas processing unit was developed. A reactor model was described based on four-lumped kinetic scheme. Main fractionator, gas processing unit and other process units are designed to simulate real plant data, using a process flow sheet simulator, Aspen PLUS. The custom reactor model was integrated with the process flow sheet simulator to develop an integrated process model.

Keywords: fluid catalytic cracking, simulation, plant data, process design

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3351 Study on the Expression of Drought Tolerant Genes in Water-Stressed Basella Alba and Basella Rubra

Authors: T. O. Ajewole, K. S. Olorunmiaye, D. A. Animasaun, M. Okpeku

Abstract:

Drought impact on the production of food crops for the benefit of mankind cannot be overemphasized. This study shows the different kind of genes expressed at various level of drought regimes on Basella alba and rubra using a real-time PCR machine. The planting was done in the screen house while the gene expression study was carried out in the laboratory. Sandy-loamy soil was collected and four levels of drought regime was used as treatment and a control experiment was set up for the two vegetables. Drought interval of 5, 10, 15 and 20 days were used as treatments while a control experiment which was not starved of water at any point was also set up, five replicates were set up for each treatment. Stress was introduced at 12 Weeks after planting (WAP). From the result of this study, Basella alba shows the highest amplicon size of 34.6 and 52.32 for GmPCS5 and HVA1 respectively which by implication means these genes were expressed the more as the stress period interval increases.

Keywords: water stress, basella alba, basella rubra, HVA1

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3350 Efficient Subsurface Mapping: Automatic Integration of Ground Penetrating Radar with Geographic Information Systems

Authors: Rauf R. Hussein, Devon M. Ramey

Abstract:

Integrating Ground Penetrating Radar (GPR) with Geographic Information Systems (GIS) can provide valuable insights for various applications, such as archaeology, transportation, and utility locating. Although there has been progress toward automating the integration of GPR data with GIS, fully automatic integration has not been achieved yet. Additionally, manually integrating GPR data with GIS can be a time-consuming and error-prone process. In this study, actual, real-world GPR applications are presented, and a software named GPR-GIS 10 is created to interactively extract subsurface targets from GPR radargrams and automatically integrate them into GIS. With this software, it is possible to quickly and reliably integrate the two techniques to create informative subsurface maps. The results indicated that automatic integration of GPR with GIS can be an efficient tool to map and view any subsurface targets in their appropriate location in a 3D space with the needed precision. The findings of this study could help GPR-GIS integrators save time and reduce errors in many GPR-GIS applications.

Keywords: GPR, GIS, GPR-GIS 10, drone technology, automation

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3349 Performance, Need and Discriminatory Allegiance of Employees as Awarding Criteria of Distributive Justice

Authors: B. Gangloff, L. Mayoral, A. Rezrazi

Abstract:

Three types of salary distribution are usually proposed by the theorists of distributive justice: Equality, equity and need. Their influence has been studied, taking into consideration (in terms of equity) the performance of the employees and their degree of allegiance/rebellion in what regards discriminatory hierarchical orders, by taking into account the reasons of such allegiance/rebellion (allegiance out of conviction, legalism or opportunism/ethical rebellion). Conducted in Argentina, the study has confronted 480 students (240 male and 240 female) with a practical case in which they had to advise a manager of a real estate agency on the allocation of a bonus amongst his employees. The latter were characterized according to their respective performance, one of them being further defined as being (or not) in a financial need and as having complied (or not) with a discriminatory hierarchical order regarding foreigners. The results show that the distribution of the bonus only follows the rules of equity and need: The employees more efficient, allegiant or in need, are rewarded more than the others. It is also noteworthy that the allegiant employees are rewarded in the same way, regardless of the reason for their allegiance, and that the employee who refuses to adopt a discriminatory conduct is penalized.

Keywords: distributive justice, equity, performance, allegiance, ethics

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3348 The Emotional Experience of Urban Ruins and the Exploration of Urban Memory

Authors: Yan Jia China

Abstract:

The ruins is a kind of historical intention, which is also the current real existence of developing city. Zen culture of ancient China has a profound esthetic emotion, similarly, the west establish the concept of aesthetics of relic along with the Romanism’s (such as Rousseau etc.) sentiment to historical ruins at the end of 18th century. Nowadays, with the decline of traditional industrial society as well as the rise of post-industrial age, contemporary society must face the ruins and garbage problem which is left by industrial society. Commencing from the perspective of emotion and memory, this paper analyzes the importance for emotional needs as well as their existing status of several projects, such as the Capital Steelworks in Beijing (industrial devastation), the Shibati old section in Chongqing (urban slums) and the Old Hurva Synagogue in Jerusalem (ruins of war). It emphasizes urban design which is started from emotion and the sustainable development of city memory through managing the urban ruins which is criticized by people with the perspective of ecology and art.

Keywords: cultural heritage, urban ruins, ecology, emotion, sustainable urban memory

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3347 Local Investment Climate and the Role of (Sustainable) FDI: The Case Of Georgia

Authors: Vakhtang Charaia

Abstract:

The article focuses on the role of FDI in Georgia’s economic development for the last decade. To attract as much FDI as possible a proper investment climate should be on the place-institutional, policy and regulatory environment. Well-developed investment climate is the chance and motivation for both, local economy and foreign companies, to generate maximum income, create new work places and improve the quality of life. FDI trend is one of the best indicators of country’s economic sustainability and its attractiveness. Especially for small and developing countries, the amount of FDI matters, therefore, most of such countries are trying to compete with each other through improving their investment climate according to different world famous indexes. As a result of impressive reforms since 2003, Georgian economy was benefited with large invasion of FDI. However, the level of per capita GDP is still law in comparison to Eastern European countries and it should be improved. The main idea of the paper is to show a real linkage between FDI and employment ration, on the case of Georgian economy.

Keywords: foreign direct investment, employment, economic growth, taxes, corruption, sustainable development

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3346 Bayesian Prospective Detection of Small Area Health Anomalies Using Kullback Leibler Divergence

Authors: Chawarat Rotejanaprasert, Andrew Lawson

Abstract:

Early detection of unusual health events depends on the ability to detect rapidly any substantial changes in disease, thus facilitating timely public health interventions. To assist public health practitioners to make decisions, statistical methods are adopted to assess unusual events in real time. We introduce a surveillance Kullback-Leibler (SKL) measure for timely detection of disease outbreaks for small area health data. The detection methods are compared with the surveillance conditional predictive ordinate (SCPO) within the framework of Bayesian hierarchical Poisson modeling and applied to a case study of a group of respiratory system diseases observed weekly in South Carolina counties. Properties of the proposed surveillance techniques including timeliness and detection precision are investigated using a simulation study.

Keywords: Bayesian, spatial, temporal, surveillance, prospective

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3345 On the Exergy Analysis of the Aluminum Smelter

Authors: Ayoola T. Brimmo, Mohamed I. Hassan

Abstract:

The push to mitigate the aluminum smelting industry’s enormous energy consumption and high emission releases is now even more persistent with the recent climate change happenings. Common approaches to achieve this have been focused on improving energy efficiency in the pot line and cast house sections of the smelter. However, the conventional energy efficiency analyses are based on the first law of thermodynamics, which do not shed proper light on the smelter’s degradation of energy. This just gives a general idea of the furnace’s performance with no reference to locations where improvement is a possibility based on the second law of thermodynamics. In this study, we apply exergy analyses on the pot line and cast house sections of the smelter to identify the locality and causes of energy degradation. The exergy analyses, which are based on a real life smelter conditions, highlight the possible locations for technology improvement in a typical smelter. With this established, methods of minimizing the smelter’s exergy losses are assessed.

Keywords: exergy analysis, electrolytic cell, furnace, heat transfer

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3344 Parallel Genetic Algorithms Clustering for Handling Recruitment Problem

Authors: Walid Moudani, Ahmad Shahin

Abstract:

This research presents a study to handle the recruitment services system. It aims to enhance a business intelligence system by embedding data mining in its core engine and to facilitate the link between job searchers and recruiters companies. The purpose of this study is to present an intelligent management system for supporting recruitment services based on data mining methods. It consists to apply segmentation on the extracted job postings offered by the different recruiters. The details of the job postings are associated to a set of relevant features that are extracted from the web and which are based on critical criterion in order to define consistent clusters. Thereafter, we assign the job searchers to the best cluster while providing a ranking according to the job postings of the selected cluster. The performance of the proposed model used is analyzed, based on a real case study, with the clustered job postings dataset and classified job searchers dataset by using some metrics.

Keywords: job postings, job searchers, clustering, genetic algorithms, business intelligence

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3343 The Types of Collaboration Models Driven by Public Art Establishment–Case Study of Taichung City

Authors: Cheng-Lung Yu, Ying-His Liao

Abstract:

Some evidence show that public art accelerates local economic growth. Even local governments award the collaboration of public-private partnership to sustain the creation of public art for urban economic development. Through the public-private partnership of public art establishment it is obvious that public construction projects have been led by the governmental policy yet the private developers have played crucial roles to drive the innovative business models such as tourism investment, real estate value up and community participation. This study shows that the types of collaboration have been driven by Taichung city governmental policy from the regulation of public art establishment in the past three years. Through some cases empirical analyzes the authors discover the trends concerning the public art development to support local economic growth in Taiwan.

Keywords: public art, public art establishment regulation, construction management, urban governance

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3342 Generation of Symmetric Key Using Randomness of Hash Function

Authors: Sai Charan Kamana, Harsha Vardhan Nakkina, B.R. Chandavarkar

Abstract:

In a highly secure and robust key generation process, a key role is played by randomness and random numbers when current real-world cryptosystems are observed. Most of the present-day cryptographic protocols depend upon the Random Number Generators (RNG), Pseudo-Random Number Generator (PRNG). These protocols often use noisy channels such as Disk seek time, CPU temperature, Mouse pointer movement, Fan noise to obtain true random values. Despite being cost-effective, these noisy channels may need additional hardware devices to continuously communicate with them. On the other hand, Hash functions are Pseudo-Random (because of their requirements). So, they are a good replacement for these noisy channels and have low hardware requirements. This paper discusses, some of the key generation methodologies, and their drawbacks. This paper explains how hash functions can be used in key generation, how to combine Key Derivation Functions with hash functions.

Keywords: key derivation, hash based key derivation, password based key derivation, symmetric key derivation

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3341 Impact of Very Small Power Producers (VSPP) on Control and Protection System in Distribution Networks

Authors: Noppatee Sabpayakom, Somporn Sirisumrannukul

Abstract:

Due to incentive policies to promote renewable energy and energy efficiency, high penetration levels of very small power producers (VSPP) located in distribution networks have imposed technical barriers and established new requirements for protection and control of the networks. Although VSPPs have economic and environmental benefit, they may introduce negative effects and cause several challenges on the issue of protection and control system. This paper presents comprehensive studies of possible impacts on control and protection systems based on real distribution systems located in a metropolitan area. A number of scenarios were examined primarily focusing on state of islanding, and un-disconnected VSPP during faults. It is shown that without proper measures to address the issues, the system would be unable to maintain its integrity of electricity power supply for disturbance incidents.

Keywords: control and protection systems, distributed generation, renewable energy, very small power producers

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3340 A Model Based Metaheuristic for Hybrid Hierarchical Community Structure in Social Networks

Authors: Radhia Toujani, Jalel Akaichi

Abstract:

In recent years, the study of community detection in social networks has received great attention. The hierarchical structure of the network leads to the emergence of the convergence to a locally optimal community structure. In this paper, we aim to avoid this local optimum in the introduced hybrid hierarchical method. To achieve this purpose, we present an objective function where we incorporate the value of structural and semantic similarity based modularity and a metaheuristic namely bees colonies algorithm to optimize our objective function on both hierarchical level divisive and agglomerative. In order to assess the efficiency and the accuracy of the introduced hybrid bee colony model, we perform an extensive experimental evaluation on both synthetic and real networks.

Keywords: social network, community detection, agglomerative hierarchical clustering, divisive hierarchical clustering, similarity, modularity, metaheuristic, bee colony

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3339 Handling Missing Data by Using Expectation-Maximization and Expectation-Maximization with Bootstrapping for Linear Functional Relationship Model

Authors: Adilah Abdul Ghapor, Yong Zulina Zubairi, A. H. M. R. Imon

Abstract:

Missing value problem is common in statistics and has been of interest for years. This article considers two modern techniques in handling missing data for linear functional relationship model (LFRM) namely the Expectation-Maximization (EM) algorithm and Expectation-Maximization with Bootstrapping (EMB) algorithm using three performance indicators; namely the mean absolute error (MAE), root mean square error (RMSE) and estimated biased (EB). In this study, we applied the methods of imputing missing values in two types of LFRM namely the full model of LFRM and in LFRM when the slope is estimated using a nonparametric method. Results of the simulation study suggest that EMB algorithm performs much better than EM algorithm in both models. We also illustrate the applicability of the approach in a real data set.

Keywords: expectation-maximization, expectation-maximization with bootstrapping, linear functional relationship model, performance indicators

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