Search results for: regional features
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5436

Search results for: regional features

5286 Using Scale Invariant Feature Transform Features to Recognize Characters in Natural Scene Images

Authors: Belaynesh Chekol, Numan Çelebi

Abstract:

The main purpose of this work is to recognize individual characters extracted from natural scene images using scale invariant feature transform (SIFT) features as an input to K-nearest neighbor (KNN); a classification learner algorithm. For this task, 1,068 and 78 images of English alphabet characters taken from Chars74k data set is used to train and test the classifier respectively. For each character image, We have generated describing features by using SIFT algorithm. This set of features is fed to the learner so that it can recognize and label new images of English characters. Two types of KNN (fine KNN and weighted KNN) were trained and the resulted classification accuracy is 56.9% and 56.5% respectively. The training time taken was the same for both fine and weighted KNN.

Keywords: character recognition, KNN, natural scene image, SIFT

Procedia PDF Downloads 281
5285 A Novel NRIS Index to Evaluate Brain Activity in Prefrontal Regions While Listening to First and Second Languages for Long Time Periods

Authors: Kensho Takahashi, Ko Watanabe, Takashi Kaburagi, Hiroshi Tanaka, Kajiro Watanabe, Yosuke Kurihara

Abstract:

Near-infrared spectroscopy (NIRS) has been widely used as a non-invasive method to measure brain activity, but it is corrupted by baseline drift noise. Here we present a method to measure regional cerebral blood flow as a derivative of NIRS output. We investigate whether, when listening to languages, blood flow can reasonably localize and represent regional brain activity or not. The prefrontal blood flow distribution pattern when advanced second-language listeners listened to a second language (L2) was most similar to that when listening to their first language (L1) among the patterns of mean and standard deviation. In experiments with 25 healthy subjects, the maximum blood flow was localized to the left BA46 of advanced listeners. The blood flow presented is robust to baseline drift and stably localizes regional brain activity.

Keywords: NIRS, oxy-hemoglobin, baseline drift, blood flow, working memory, BA46, first language, second language

Procedia PDF Downloads 559
5284 New Approaches for the Handwritten Digit Image Features Extraction for Recognition

Authors: U. Ravi Babu, Mohd Mastan

Abstract:

The present paper proposes a novel approach for handwritten digit recognition system. The present paper extract digit image features based on distance measure and derives an algorithm to classify the digit images. The distance measure can be performing on the thinned image. Thinning is the one of the preprocessing technique in image processing. The present paper mainly concentrated on an extraction of features from digit image for effective recognition of the numeral. To find the effectiveness of the proposed method tested on MNIST database, CENPARMI, CEDAR, and newly collected data. The proposed method is implemented on more than one lakh digit images and it gets good comparative recognition results. The percentage of the recognition is achieved about 97.32%.

Keywords: handwritten digit recognition, distance measure, MNIST database, image features

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5283 BERT-Based Chinese Coreference Resolution

Authors: Li Xiaoge, Wang Chaodong

Abstract:

We introduce the first Chinese Coreference Resolution Model based on BERT (CCRM-BERT) and show that it significantly outperforms all previous work. The key idea is to consider the features of the mention, such as part of speech, width of spans, distance between spans, etc. And the influence of each features on the model is analyzed. The model computes mention embeddings that combine BERT with features. Compared to the existing state-of-the-art span-ranking approach, our model significantly improves accuracy on the Chinese OntoNotes benchmark.

Keywords: BERT, coreference resolution, deep learning, nature language processing

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5282 Frequency Distribution and Assertive Object Theory: An Exploration of the Late Bronze Age Italian Ceramic Landscape

Authors: Sara Fioretti

Abstract:

In the 2nd millennium BCE, maritime networks became essential to the Mediterranean lifestyle, creating an interconnected world. This phenomenon of interconnected cultures has often been misinterpreted as an “effect” of the Mycenaean “influence” without considering the complexity and role of regional and cross-cultural exchanges. This paper explores the socio-economic relationships, in both cross-cultural and potentially inter-regional settings, present within the archaeological repertoire of the southern Italian Late Bronze Age (LBA 1600 -1140 BCE). The emergence of economic relations within the connectivity of the regional settlements is explored through ceramic contexts found in the case studies Punta di Zambrone, Broglio di Trebisacce, and Nuraghe Antigori. This work-in-progress research is situated in the shifting theoretical views of the last ten years that discuss the Late Bronze Age’s connectivity through Social Networks, Entanglement, and Assertive Objects combined with a comparative statistical study of ceramic frequency distribution. Applying these theoretical frameworks with a quantitative approach demonstrates the specific regional economic relationships that shaped the cultural interactions of the Late Bronze Age. Through this intersection of theory and statistical analysis, the case studies establish a small percentage of pottery as imported, whilst assertive productions have a relatively higher quantity. Overall, the majority still adheres to regional Italian traditions. Therefore, we can dissect the rhizomatic relationships cultivated by the Italian coasts and Mycenaeans and their roles within their networks through the intersection of theoretical and statistical analysis. This research offers a new perspective on the connectivity of the Late Bronze Age relational structures.

Keywords: late bronze age, mediterranean archaeology, exchanges and trade, frequency distribution of ceramic assemblages

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5281 Should Local Governments Expect Benefits from Special Economic Zones: The Case of Poland

Authors: Radosław Pastusiak, Anna Kaźmierska, Magdalena Jasiniak

Abstract:

The impact of Special Economic Zones (SEZs) has been analyzed for many years by researchers. There are lot of theoretical studies proving the SEZs importance for regional development, however, there is lack of empirical studies (and they are mainly focused on China market) that are based on available data. The theoretical studies indicate the various impacts of enterprises operating within SEZs on the economy. The article proves that, in case of Poland, locating SEZs in municipalities is an important part of increasing municipalities’ income. Therefore SEZs have a positive impact on regional development. Municipality income is understood as taxes paid by taxpayers who depend on SEZ companies’ performance. The analysis includes the Corporate Income Tax (CIT), Personal Income Tax (PIT) and real estate tax. The effects of SEZs on regional development were narrowed to a few variables that are most significant for the financial system. The analysis indicates the significant impact of SEZs on the amount of taxes influencing the municipality budget.

Keywords: special economic zone, local finance, municipal finance, government

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5280 Classification of Political Affiliations by Reduced Number of Features

Authors: Vesile Evrim, Aliyu Awwal

Abstract:

By the evolvement in technology, the way of expressing opinions switched the direction to the digital world. The domain of politics as one of the hottest topics of opinion mining research merged together with the behavior analysis for affiliation determination in text which constitutes the subject of this paper. This study aims to classify the text in news/blogs either as Republican or Democrat with the minimum number of features. As an initial set, 68 features which 64 are constituted by Linguistic Inquiry and Word Count (LIWC) features are tested against 14 benchmark classification algorithms. In the later experiments, the dimensions of the feature vector reduced based on the 7 feature selection algorithms. The results show that Decision Tree, Rule Induction and M5 Rule classifiers when used with SVM and IGR feature selection algorithms performed the best up to 82.5% accuracy on a given dataset. Further tests on a single feature and the linguistic based feature sets showed the similar results. The feature “function” as an aggregate feature of the linguistic category, is obtained as the most differentiating feature among the 68 features with 81% accuracy by itself in classifying articles either as Republican or Democrat.

Keywords: feature selection, LIWC, machine learning, politics

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5279 Regional Dynamics of Innovation and Entrepreneurship in the Optics and Photonics Industry

Authors: Mustafa İlhan Akbaş, Özlem Garibay, Ivan Garibay

Abstract:

The economic entities in innovation ecosystems form various industry clusters, in which they compete and cooperate to survive and grow. Within a successful and stable industry cluster, the entities acquire different roles that complement each other in the system. The universities and research centers have been accepted to have a critical role in these systems for the creation and development of innovations. However, the real effect of research institutions on regional economic growth is difficult to assess. In this paper, we present our approach for the identification of the impact of research activities on the regional entrepreneurship for a specific high-tech industry: optics and photonics. The optics and photonics has been defined as an enabling industry, which combines the high-tech photonics technology with the developing optics industry. The recent literature suggests that the growth of optics and photonics firms depends on three important factors: the embedded regional specializations in the labor market, the research and development infrastructure, and a dynamic small firm network capable of absorbing new technologies, products and processes. Therefore, the role of each factor and the dynamics among them must be understood to identify the requirements of the entrepreneurship activities in optics and photonics industry. There are three main contributions of our approach. The recent studies show that the innovation in optics and photonics industry is mostly located around metropolitan areas. There are also studies mentioning the importance of research center locations and universities in the regional development of optics and photonics industry. These studies are mostly limited with the number of patents received within a short period of time or some limited survey results. Therefore the first contribution of our approach is conducting a comprehensive analysis for the state and recent history of the photonics and optics research in the US. For this purpose, both the research centers specialized in optics and photonics and the related research groups in various departments of institutions (e.g. Electrical Engineering, Materials Science) are identified and a geographical study of their locations is presented. The second contribution of the paper is the analysis of regional entrepreneurship activities in optics and photonics in recent years. We use the membership data of the International Society for Optics and Photonics (SPIE) and the regional photonics clusters to identify the optics and photonics companies in the US. Then the profiles and activities of these companies are gathered by extracting and integrating the related data from the National Establishment Time Series (NETS) database, ES-202 database and the data sets from the regional photonics clusters. The number of start-ups, their employee numbers and sales are some examples of the extracted data for the industry. Our third contribution is the utilization of collected data to investigate the impact of research institutions on the regional optics and photonics industry growth and entrepreneurship. In this analysis, the regional and periodical conditions of the overall market are taken into consideration while discovering and quantifying the statistical correlations.

Keywords: entrepreneurship, industrial clusters, optics, photonics, emerging industries, research centers

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5278 Research on the Evaluation of Enterprise-University-Research Cooperation Ability in Hubei Province

Authors: Dongfang Qiu, Yilin Lu

Abstract:

The measurement of enterprise-university-research cooperative efficiency has important meanings in improving the cooperative efficiency, strengthening the effective integration of regional resource, enhancing the ability of regional innovation and promoting the development of regional economy. The paper constructs the DEA method and DEA-Malmquist productivity index method to research the cooperation efficiency of Hubei by making comparisons with other provinces in China. The study found out the index of technology efficiency is 0.52 and the enterprise-university- research cooperative efficiency is Non-DEA efficient. To realize the DEA efficiency of Hubei province, the amount of 1652.596 R&D employees and 638.368 R&D employees’ full time equivalence should be reduced or 137.89 billion yuan of new products’ sales income be increased. Finally, it puts forward policy recommendations on existing problems to strengthen the standings of the cooperation, realize the effective application of the research results, and improve the level of management of enterprise-university-research cooperation efficiency.

Keywords: cooperation ability, DEA method, enterprise-university-research cooperation, Malmquist efficiency index

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5277 A Machine Learning-Based Approach to Capture Extreme Rainfall Events

Authors: Willy Mbenza, Sho Kenjiro

Abstract:

Increasing efforts are directed towards a better understanding and foreknowledge of extreme precipitation likelihood, given the adverse effects associated with their occurrence. This knowledge plays a crucial role in long-term planning and the formulation of effective emergency response. However, predicting extreme events reliably presents a challenge to conventional empirical/statistics due to the involvement of numerous variables spanning different time and space scales. In the recent time, Machine Learning has emerged as a promising tool for predicting the dynamics of extreme precipitation. ML techniques enables the consideration of both local and regional physical variables that have a strong influence on the likelihood of extreme precipitation. These variables encompasses factors such as air temperature, soil moisture, specific humidity, aerosol concentration, among others. In this study, we develop an ML model that incorporates both local and regional variables while establishing a robust relationship between physical variables and precipitation during the downscaling process. Furthermore, the model provides valuable information on the frequency and duration of a given intensity of precipitation.

Keywords: machine learning (ML), predictions, rainfall events, regional variables

Procedia PDF Downloads 88
5276 Analysis of Legal System of Land Use in Archaeological Sites

Authors: Yen-Sheng Ho

Abstract:

It is important to actively adjust the legal system of land use in archaeological sites and the reward system to meet the needs of modern society and to solve the dilemma of government management. Under the principle of administration according to law and the principle of the clarity of law, human rights, legal orders and legitimate expectation shall be regulated. The Cultural Heritage Preservation Act has many norms related to archaeological sites in Taiwan. However, in practice, the preservation of archaeological sites still encounters many challenges. For instance, some archaeological sites have ‘management and maintenance plans’. The restrictions of land uses are not clearly defined making it difficult to determine how planting types and cultivation methods will impact the underground relics. In addition, there are questions as follows. How to coordinate the ‘site preservation plan’ with the Regional Planning Act and the Urban Planning Act? How to define preservation of land, preservation area and other uses of land or area? How to define land use in practice? How to control land use? After selecting three sites for the case investigation, this study will analyze the site’s land use status and propose the direction of land use and control methods. This study suggests that the prerequisite to limit the use of land is to determine the public interest in the preservation of the site. Another prerequisite is to establish a mechanism for permitting the use of the site and for setting the site preservation and zoning maintenance practices according to the Regional Planning Act, Urban Planning Act and other relevant rules, such as, land use zoning, land use control, land management, land maintenance, regional development and management and etc.

Keywords: archaeological site, land use and site preservation plan, regional planning, urban planning

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5275 Effective Texture Features for Segmented Mammogram Images Based on Multi-Region of Interest Segmentation Method

Authors: Ramayanam Suresh, A. Nagaraja Rao, B. Eswara Reddy

Abstract:

Texture features of mammogram images are useful for finding masses or cancer cases in mammography, which have been used by radiologists. Textures are greatly succeeded for segmented images rather than normal images. It is necessary to perform segmentation for exclusive specification of cancer and non-cancer regions separately. Region of interest (ROI) is most commonly used technique for mammogram segmentation. Limitation of this method is that it is unable to explore segmentation for large collection of mammogram images. Therefore, this paper is proposed multi-ROI segmentation for addressing the above limitation. It supports greatly in finding the best texture features of mammogram images. Experimental study demonstrates the effectiveness of proposed work using benchmarked images.

Keywords: texture features, region of interest, multi-ROI segmentation, benchmarked images

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5274 Monitoring Blood Pressure Using Regression Techniques

Authors: Qasem Qananwah, Ahmad Dagamseh, Hiam AlQuran, Khalid Shaker Ibrahim

Abstract:

Blood pressure helps the physicians greatly to have a deep insight into the cardiovascular system. The determination of individual blood pressure is a standard clinical procedure considered for cardiovascular system problems. The conventional techniques to measure blood pressure (e.g. cuff method) allows a limited number of readings for a certain period (e.g. every 5-10 minutes). Additionally, these systems cause turbulence to blood flow; impeding continuous blood pressure monitoring, especially in emergency cases or critically ill persons. In this paper, the most important statistical features in the photoplethysmogram (PPG) signals were extracted to estimate the blood pressure noninvasively. PPG signals from more than 40 subjects were measured and analyzed and 12 features were extracted. The features were fed to principal component analysis (PCA) to find the most important independent features that have the highest correlation with blood pressure. The results show that the stiffness index means and standard deviation for the beat-to-beat heart rate were the most important features. A model representing both features for Systolic Blood Pressure (SBP) and Diastolic Blood Pressure (DBP) was obtained using a statistical regression technique. Surface fitting is used to best fit the series of data and the results show that the error value in estimating the SBP is 4.95% and in estimating the DBP is 3.99%.

Keywords: blood pressure, noninvasive optical system, principal component analysis, PCA, continuous monitoring

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5273 Juxtaposition of the Past and the Present: A Pragmatic Stylistic Analysis of the Short Story “Too Much Happiness” by Alice Munro

Authors: Inas Hussein

Abstract:

Alice Munro is a Canadian short-story writer who has been regarded as one of the greatest writers of fiction. Owing to her great contribution to fiction, she was the first Canadian woman and the only short-story writer ever to be rewarded the Nobel Prize for Literature in 2013. Her literary works include collections of short stories and one book published as a novel. Her stories concentrate on the human condition and the human relationships as seen through the lens of daily life. The setting in most of her stories is her native Canada- small towns much similar to the one where she grew up. Her writing style is not only realistic but is also characterized by autobiographical, historical and regional features. The aim of this research is to analyze one of the key stylistic devices often adopted by Munro in her fictions: the juxtaposition of the past and the present, with reference to the title story in Munro's short story collection Too Much Happiness. The story under exploration is a brief biography of the Russian Mathematician and novelist Sophia Kovalevsky (1850 – 1891), the first woman to be appointed as a professor of Mathematics at a European University in Stockholm. Thus, the story has a historical protagonist and is set on the European continent. Munro dramatizes the severe historical and cultural constraints that hindered the career of the protagonist. A pragmatic stylistic framework is being adopted and the qualitative analysis is supported by textual reference. The stylistic analysis reveals that the juxtaposition of the past and the present is one of the distinctive features that characterize the author; in a typical Munrovian manner, the protagonist often moves between the units of time: the past, the present and, sometimes, the future. Munro's style is simple and direct but cleverly constructed and densely complicated by the presence of deeper layers and stories within the story. Findings of the research reveal that the story under investigation merits reading and analyzing. It is recommended that this story and other stories by Munro are analyzed to further explore the features of her art and style.

Keywords: Alice Munro, Too Much Happiness, style, stylistic analysis

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5272 The Association of Cone-Shaped Epiphysis and Poland Syndrome: A Case Report

Authors: Mohammad Alqattan, Tala Alkhunani, Reema Al, Aldawish, Felwa Almurshard, Abdullah Alzahrani

Abstract:

: Poland’s Syndrome is a congenital anomaly with two clinical features : unilateral agenesis of the pectoralis major and ipsilateral hand symbrachydactyly. Case presentation: We report a rare case of bilateral Poland’s syndrome with several unique features. Discussion: Poland’s syndrome is thought to be due to a vascular insult to the subclavian axis around the 6th week of gestation. Our patient has multiple rare and unique features of Poland’s syndrome. Conclusion: To our best knowledge, for the first time in the literature we associate Poland’s syndrome with cone-shaped epiphysis of the metacarpals of all fingers. Bilaterality, cleft hand deformity, and dextrocardia, were also rare features in our patient.

Keywords: Poland's syndrome, cleft hand deformity, bilaterality, dextrocardia, cone-shaped epiphysis

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5271 A Comparative Study of k-NN and MLP-NN Classifiers Using GA-kNN Based Feature Selection Method for Wood Recognition System

Authors: Uswah Khairuddin, Rubiyah Yusof, Nenny Ruthfalydia Rosli

Abstract:

This paper presents a comparative study between k-Nearest Neighbour (k-NN) and Multi-Layer Perceptron Neural Network (MLP-NN) classifier using Genetic Algorithm (GA) as feature selector for wood recognition system. The features have been extracted from the images using Grey Level Co-Occurrence Matrix (GLCM). The use of GA based feature selection is mainly to ensure that the database used for training the features for the wood species pattern classifier consists of only optimized features. The feature selection process is aimed at selecting only the most discriminating features of the wood species to reduce the confusion for the pattern classifier. This feature selection approach maintains the ‘good’ features that minimizes the inter-class distance and maximizes the intra-class distance. Wrapper GA is used with k-NN classifier as fitness evaluator (GA-kNN). The results shows that k-NN is the best choice of classifier because it uses a very simple distance calculation algorithm and classification tasks can be done in a short time with good classification accuracy.

Keywords: feature selection, genetic algorithm, optimization, wood recognition system

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5270 The Role of Regional Economic Communities in Fighting Terrorism in Africa: The Case of Inter-Governmental Authority on Development (IGAD)

Authors: Memar Ayalew Demeke, Solomon Gebreyohans Gebru

Abstract:

In Africa, Regional Economic Communities (RECs) were initially established to tackle the economic challenges of the continent. However, overtime, they expanded their mandate to deal with the security threats of the continent such as terrorism. In fact, the fight against terrorism has been internationalized following the September 9/11 terrorist attack in the U.S.A. Since then, RECs have been giving considerable attention to preventing and combating terrorism in their respective regions. Similarly, IGAD has been involved in preventing and combating terrorism. So far, however, little has been done with regard to what IGAD has performed in fighting terrorism. Therefore, this study was intended to describe and analyze the legal and practical activities carried out by IGAD in its fight against terrorism in the region general and in Somalia in particular. Both descriptive and analytical methods were employed and data were analyzed through qualitative approach. Finally, based on the findings, the study argues that, instead of over-reliance on hard power as a means of fighting terrorism, IGAD should invest more on the political and socio-economic problems of its member states so as to address the root causes.

Keywords: regional economic communities, IGAD, terrorism, treaties, conventions

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5269 Structural Analysis of Sheep and Goat Farms in Konya Province

Authors: Selda Uzal Seyfi

Abstract:

Goat milk is a quite important in human nutrition. In order to meet the demand to the goat and sheep milk occurring in the recent years, an increase is seen in the demand to housing projects, which will enable animals to be sheltered in the suitable environments. This study was carried out in between 2012 and 2013, in order to identify the existing cases of sheep and goat housings in the province Konya and their possibilities to be developed. In the study, in the province Konya, 25 pieces of sheep and goat farms and 46 pieces of sheep and goat housings (14 sheep housings, 3 goat housings, and 29 housings, in which both sheep and goat are bred ) that are present in the farm were investigated as material. In the study, examining the general features of the farms that are present in the region and structural features of housings that are present in the farms, it is studied whether or not they are suitable for animal breeding. As a result of the study, the barns were evaluated as insufficient in terms of barn design, although 48% of they were built after 2000. In 63% of housings examined, stocking density of resting area was below the value of 1 m2/animal and in 59% of the housings, stocking density of courtyard area was below the 2 m2/animal. Feeding length, in 57% of housings has a value of 0.30 m and below. In the region, it will be possible to obtain the desired productivity level by building new barn designs, developed in accordance with the animal behaviors and welfare. Carrying out the necessary works is an important issue in terms of country and regional economy.

Keywords: barn design, goat housing, sheep housing, structural analysis

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5268 Comparative Analysis of Feature Extraction and Classification Techniques

Authors: R. L. Ujjwal, Abhishek Jain

Abstract:

In the field of computer vision, most facial variations such as identity, expression, emotions and gender have been extensively studied. Automatic age estimation has been rarely explored. With age progression of a human, the features of the face changes. This paper is providing a new comparable study of different type of algorithm to feature extraction [Hybrid features using HAAR cascade & HOG features] & classification [KNN & SVM] training dataset. By using these algorithms we are trying to find out one of the best classification algorithms. Same thing we have done on the feature selection part, we extract the feature by using HAAR cascade and HOG. This work will be done in context of age group classification model.

Keywords: computer vision, age group, face detection

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5267 Analysis of Advancements in Process Modeling and Reengineering at Fars Regional Electric Company, Iran

Authors: Mohammad Arabi

Abstract:

Business Process Reengineering (BPR) is a systematic approach to fundamentally redesign organizational processes to achieve significant improvements in organizational performance. At Fars Regional Electric Company, implementing BPR is deemed essential to increase productivity, reduce costs, and improve service quality. This article examines how BPR can help enhance the performance of Fars Regional Electric Company. The objective of this research is to evaluate and analyze the advancements in process modeling and reengineering at Fars Regional Electric Company and to provide solutions for improving the productivity and efficiency of organizational processes. This study aims to demonstrate how BPR can be used to improve organizational processes and enhance the overall performance of the company. This research employs both qualitative and quantitative research methods and includes interviews with senior managers and experts at Fars Regional Electric Company. The analytical tools include process modeling software such as Bizagi and ARIS, and statistical analysis software such as SPSS and Minitab. Data analysis was conducted using advanced statistical methods. The results indicate that the use of BPR techniques can lead to a significant reduction in process execution time and overall improvement in quality. Implementing BPR at Fars Regional Electric Company has led to increased productivity, reduced costs, and improved overall performance of the company. This study shows that with proper implementation of BPR and the use of modeling tools, the company can achieve significant improvements in its processes. Recommendations: (1) Continuous Training for Staff: Invest in continuous training of staff to enhance their skills and knowledge in BPR. (2) Use of Advanced Technologies: Utilize modeling and analysis software to improve processes. (3) Implementation of Effective Management Systems: Employ knowledge and information management systems to enhance organizational performance. (4) Continuous Monitoring and Review of Processes: Regularly review and revise processes to ensure ongoing improvements. This article highlights the importance of improving organizational processes at Fars Regional Electric Company and recommends that managers and decision-makers at the company seriously consider reengineering processes and utilizing modeling technologies to achieve developmental goals and continuous improvement.

Keywords: business process reengineering, electric company, Fars province, process modeling advancements

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5266 Geopolitics over Ukraine: International Policies and Domestic Problems

Authors: Daniel Silander

Abstract:

This article explores the EU Initiated European Neighborhood Policy (ENP) towards Ukraine. It also explores Russian geopolitics in the region. We argue that Ukraine is sandwiched between two regional powers in the EU and Russia. By analyzing EU democracy promotion towards Ukraine and neighbors, we assess a weak EU normative capacity. Instead of building a “ring of friends”, as argued by the EU Commission, in an enlarged democratic community, the EU has achieved poor democratic records in Ukraine which opened for a revival of Russia in the region and causes the international crisis over Crime of 2014.

Keywords: regional neighborhood policy, European Union, Russia, Ukraine, domestic elites

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5265 The Implementation of Science Park Policy and Their Impacts on Regional Economic Development in Emerging Economy Country: Case of Thailand

Authors: Muttamas Wongwanich, John R. Bryson, Catherine E. Harris

Abstract:

Science parks are an essential component of localized innovation ecosystems. Science Parks have played a critical role in enhancing local innovation ecosystems in developed market economies. Attempts have been made to replicate best practice in other national contexts. To our best knowledge, the study about the development of Science Parks has not been undertaken on the economic impact on the developing countries. Further research is required to understand the adoption of Science Park policies in developing and emerging economies. This study explores the implementation of Science Park policy and its impacts on economic growth and development in Thailand, focusing on the relationship between universities and businesses. The Thailand context is essential. Thailand’s economy is dominated by agriculture and tourism. The Science Park policy is trying to develop an agriculturally orientated innovative ecosystem. Thailand established four Science Parks based on a policy that highlighted the importance of cooperation between government, HEIs, and businesses. These Science Parks are intended to increase small and medium enterprises’ (SMEs) innovativeness, employment, and regional economic growth by promoting collaboration and knowledge transfer between HEIs and the private sector. This study explores one regional Science Park in Thailand with an emphasis on understanding the implementation and operation of a triple helix innovation policy. The analysis explores the establishment of the Science Park and its impacts on firms and the regional economy through interviews with Science Parks directors, firms, academics, universities, and government officials. The analysis will inform Science Park policy development in Thailand to support the national objective to develop an innovation ecosystem based on the integration of technology with innovation policy, supporting technology-based SMEs in the creation of local jobs. The finding shows that the implementation of the Science Park policy in Thailand requires support and promotion from the government. The regional development plan must be related to the regional industry development strategy, considering the strengths and weaknesses of local entrepreneurs. The long time in granting a patent is the major obstacle in achieving the government’s aim in encouraging local economic activity. The regional Science Parks in Thailand are at the early stage of the operation plan. Thus, the impact on the regional economy cannot be measured and need further investigation in a more extended period. However, local businesses realize the vital of research and development (R&D). There have been more requests for funding support in doing R&D. Furthermore, there is the creation of linkages between businesses, HEIs, and government authorities as expected.

Keywords: developing country, emerging economy, regional development, science park, Thailand, triple helix

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5264 The Condition Testing of Damaged Plates Using Acoustic Features and Machine Learning

Authors: Kyle Saltmarsh

Abstract:

Acoustic testing possesses many benefits due to its non-destructive nature and practicality. There hence exists many scenarios in which using acoustic testing for condition testing shows powerful feasibility. A wealth of information is contained within the acoustic and vibration characteristics of structures, allowing the development meaningful features for the classification of their respective condition. In this paper, methods, results, and discussions are presented on the use of non-destructive acoustic testing coupled with acoustic feature extraction and machine learning techniques for the condition testing of manufactured circular steel plates subjected to varied levels of damage.

Keywords: plates, deformation, acoustic features, machine learning

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5263 Measuring Systems Interoperability: A Focal Point for Standardized Assessment of Regional Disaster Resilience

Authors: Joel Thomas, Alexa Squirini

Abstract:

The key argument of this research is that every element of systems interoperability is an enabler of regional disaster resilience, and arguably should become a focal point for standardized measurement of communities’ ability to work together. Few resilience research efforts have focused on the development and application of solutions that measurably improve communities’ ability to work together at a regional level, yet a majority of the most devastating and disruptive disasters are those that have had a regional impact. The key findings of the research include a unique theoretical, mathematical, and operational approach to tangibly and defensibly measure and assess systems interoperability required to support crisis information management activities performed by governments, the private sector, and humanitarian organizations. A most effective way for communities to measurably improve regional disaster resilience is through deliberately executed disaster preparedness activities. Developing interoperable crisis information management capabilities is a crosscutting preparedness activity that greatly affects a community’s readiness and ability to work together in times of crisis. Thus, improving communities’ human and technical posture to work together in advance of a crisis, with the ultimate goal of enabling information sharing to support coordination and the careful management of available resources, is a primary means by which communities may improve regional disaster resilience. This model describes how systems interoperability can be qualitatively and quantitatively assessed when characterized as five forms of capital: governance; standard operating procedures; technology; training and exercises; and usage. The unique measurement framework presented defines the relationships between systems interoperability, information sharing and safeguarding, operational coordination, community preparedness and regional disaster resilience, and offers a means by which to implement real-world solutions and measure progress over the course of a multi-year program. The model is being developed and piloted in partnership with the U.S. Department of Homeland Security (DHS) Science and Technology Directorate (S&T) and the North Atlantic Treaty Organization (NATO) Advanced Regional Civil Emergency Coordination Pilot (ARCECP) with twenty-three organizations in Bosnia and Herzegovina, Croatia, Macedonia, and Montenegro. The intended effect of the model implementation is to enable communities to answer two key questions: 'Have we measurably improved crisis information management capabilities as a result of this effort?' and, 'As a result, are we more resilient?'

Keywords: disaster, interoperability, measurement, resilience

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5262 The Flora of Oyukludag and Its Environs Karaman,Turkey

Authors: Murad Aydin Şanda, Mustafa Küçüködük

Abstract:

The flora and it’s plants ethnobotanical features of Oyukludag were investigated between 2003 and 2006 years; 780 herbarium specimens belonging to 448 taxa, 292 genera and 62 families were collected and identified from the area. The families which have the most taxa in research area are Compositae (Asteraceae) 78 (17%), Leguminosae (Fabaceae) 58 (13%), Cruciferae (Brassicaceae) 34 (8%), Labiatae (Lamiaceae) 33 (7%), Gramineae (Poaceae) 29 (6%), Caryophyllaceae 19 (4%), Umbelliferae (Apiaceae) 18 (4%), Boraginaceae 17 (4%), Liliaceae 16 (4%). The number of cultivated plants are 17. The research area is in the district of Konya and is in the C4 square according to the Grid System. The phytogeographic elements are represented in the study area as follows; Iranian-Turanian (18%), Mediterranean (17%) and Euro-Siberian (2%). The phytogeographic regions of 268 (60%) taxa are either multi-regional or unknown. The number of endemic taxa is 56 (12%).

Keywords: flora, Oyukludag, Yellibel, Karaman, Turkey

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5261 Tectonic Complexity: Out-of-Sequence Thrusting in the Higher Himalaya of Jhakri-Sarahan region, Himachal Pradesh, India

Authors: Rajkumar Ghosh

Abstract:

The study focuses on the tectonics of out-of-sequence thrusting (OOST) in the NW region of the Himalaya, particularly in Himachal Pradesh. The research aims to identify the features and nature of OOST in the field and the associated rock types and lithological boundaries in the field of NW Himalaya, Himachal Pradesh, India. The research employs fieldwork and micro-structure observations, correlations, and analyses to identify and analyze the OOST features and associated rock types. The study reveals the presence of three OOSTs, namely Jhakri Thrust (JT), Sarahan Thrust (ST), and Chaura Thrust (CT), which consist of several branches, some of which are still active. The thrust system exhibits varying internal geometry, including box folds, boudins, scar folds, crenulation cleavages, kink folds, and tension gashes. The CT, which is concealed beneath Jutogh Thrust sheet, represents a steepened downward thrust, while the JT has a western dip and is south-westward verging. The research provides crucial information on the tectonics of OOST in the NW region of the Himalaya, particularly in Himachal Pradesh, which is crucial in understanding the regional geological evolution and associated hazards. The data were collected through fieldwork and micro-structure observations, correlations, and analyses of rock samples. The data were analyzed using tectonic and geochronological techniques to identify the nature and characteristics of OOST. The research addressed the question of identifying Higher Himalayan OOST in the field of NW Himalaya, Himachal Pradesh, India, and the associated rock types and lithological boundaries. The study concludes that there is minimal documentation and a lack of suitable exposure of rocks to generalize the features of OOST in the field in NW Higher Himalaya, Himachal Pradesh. The study recommends more extensive mapping and fieldwork to improve understanding of OOST in the region.

Keywords: out-of-sequence thrust (OOST), main central thrust (MCT), jhakri thrust (JT), sarahan thrust (ST), chaura thrust (CT), higher himalaya (HH)

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5260 A Study on Vitalization Factors of Itaewon Commercial Street-Focused on Itaewon-Ro

Authors: Park, Yoon Hong, Wang, Jung Kab, Choi Seong-Won, Kim, Hong Kyu

Abstract:

Itaewon-Ro is a special place where the Seoul Metropolitan city designated as the fist are of tourism, specially with the commercial supremacy that foreigners may like. It is the place that grew with regional specialty. Study on the vitalization factors of commercialist were analyzed on consumer shop choice factor, Physical environment based on commercial supremacy vitalization, Functional side of the road and regional specialty. However, since Itaewon seemed to take great place in the cultural factor, Because of its regional specialty, Research was processed. This study is the analysis on the vitalization of Itaewon commercialist that looked for important factors with AHP analysis on consumers use as commercialist. Based on the field study and preceded study, top three factors were distinguished with physical factor, cultural factor, landscape factor, and thirteen detail contents were found. This study focused on the choice of the consumer and with a consumer-based questionnaire, we analyzed the importance of vitalization factors. Results of the research are shown in the following paragraphs. In the Itaewon commercial market, mostly women in the 20~30s were the main consumers for meeting and hopping. Vitalization category that the consumer thinks it most importantly was 'attraction', 'various businesses', and 'convenience of transportation'. 'Attraction that cannot be seen in other places', Which was chosen as the most important factor was judged that Itaewon holds cultural identity that is shown in the process of development, Instead of showing artificial and physical composition.

Keywords: commercialist, vitalization factor, regional specialty, cultural factor, AHP analysis

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5259 Effect of Personality Traits on Classification of Political Orientation

Authors: Vesile Evrim, Aliyu Awwal

Abstract:

Today as in the other domains, there are an enormous number of political transcripts available in the Web which is waiting to be mined and used for various purposes such as statistics and recommendations. Therefore, automatically determining the political orientation on these transcripts becomes crucial. The methodologies used by machine learning algorithms to do the automatic classification are based on different features such as Linguistic. Considering the ideology differences between Liberals and Conservatives, in this paper, the effect of Personality Traits on political orientation classification is studied. This is done by considering the correlation between LIWC features and the BIG Five Personality Traits. Several experiments are conducted on Convote U.S. Congressional-Speech dataset with seven benchmark classification algorithms. The different methodologies are applied on selecting different feature sets that constituted by 8 to 64 varying number of features. While Neuroticism is obtained to be the most differentiating personality trait on classification of political polarity, when its top 10 representative features are combined with several classification algorithms, it outperformed the results presented in previous research.

Keywords: politics, personality traits, LIWC, machine learning

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5258 Fused Structure and Texture (FST) Features for Improved Pedestrian Detection

Authors: Hussin K. Ragb, Vijayan K. Asari

Abstract:

In this paper, we present a pedestrian detection descriptor called Fused Structure and Texture (FST) features based on the combination of the local phase information with the texture features. Since the phase of the signal conveys more structural information than the magnitude, the phase congruency concept is used to capture the structural features. On the other hand, the Center-Symmetric Local Binary Pattern (CSLBP) approach is used to capture the texture information of the image. The dimension less quantity of the phase congruency and the robustness of the CSLBP operator on the flat images, as well as the blur and illumination changes, lead the proposed descriptor to be more robust and less sensitive to the light variations. The proposed descriptor can be formed by extracting the phase congruency and the CSLBP values of each pixel of the image with respect to its neighborhood. The histogram of the oriented phase and the histogram of the CSLBP values for the local regions in the image are computed and concatenated to construct the FST descriptor. Several experiments were conducted on INRIA and the low resolution DaimlerChrysler datasets to evaluate the detection performance of the pedestrian detection system that is based on the FST descriptor. A linear Support Vector Machine (SVM) is used to train the pedestrian classifier. These experiments showed that the proposed FST descriptor has better detection performance over a set of state of the art feature extraction methodologies.

Keywords: pedestrian detection, phase congruency, local phase, LBP features, CSLBP features, FST descriptor

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5257 Fusion of Finger Inner Knuckle Print and Hand Geometry Features to Enhance the Performance of Biometric Verification System

Authors: M. L. Anitha, K. A. Radhakrishna Rao

Abstract:

With the advent of modern computing technology, there is an increased demand for developing recognition systems that have the capability of verifying the identity of individuals. Recognition systems are required by several civilian and commercial applications for providing access to secured resources. Traditional recognition systems which are based on physical identities are not sufficiently reliable to satisfy the security requirements due to the use of several advances of forgery and identity impersonation methods. Recognizing individuals based on his/her unique physiological characteristics known as biometric traits is a reliable technique, since these traits are not transferable and they cannot be stolen or lost. Since the performance of biometric based recognition system depends on the particular trait that is utilized, the present work proposes a fusion approach which combines Inner knuckle print (IKP) trait of the middle, ring and index fingers with the geometrical features of hand. The hand image captured from a digital camera is preprocessed to find finger IKP as region of interest (ROI) and hand geometry features. Geometrical features are represented as the distances between different key points and IKP features are extracted by applying local binary pattern descriptor on the IKP ROI. The decision level AND fusion was adopted, which has shown improvement in performance of the combined scheme. The proposed approach is tested on the database collected at our institute. Proposed approach is of significance since both hand geometry and IKP features can be extracted from the palm region of the hand. The fusion of these features yields a false acceptance rate of 0.75%, false rejection rate of 0.86% for verification tests conducted, which is less when compared to the results obtained using individual traits. The results obtained confirm the usefulness of proposed approach and suitability of the selected features for developing biometric based recognition system based on features from palmar region of hand.

Keywords: biometrics, hand geometry features, inner knuckle print, recognition

Procedia PDF Downloads 220