Search results for: imbalance data

Authors: Nikat Parveen, M. Ananthi

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Big data is one of the emerging technology, which collects the data from various sensors and those data will be used in many fields. Data retrieval is one of the major issue where there is a need to extract the exact data as per the need. In this paper, large amount of data set is processed by using the feature selection. Feature selection helps to choose the data which are actually needed to process and execute the task. The key value is the one which helps to point out exact data available in the storage space. Here the available data is streamed and R-Center is proposed to achieve this task.

Keywords: big data, key value, feature selection, retrieval, performance

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Authors: Mahsa Khani Oushani

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Text and image are two important elements in the field of Iranian art, the text component and the image component have always been manifested together. The image narrates the text and the text is the factor in the formation of the image and they are closely related to each other. The connection between text and image is an interactive and two-way connection in the tradition of Iranian manuscript arrangement. The interaction between the narrative description and the image scene is the result of a direct and close connection between the text and the image, which in addition to the decorative aspect, also has a descriptive aspect. In this article the connection between the text element and the image element and its adaptation to the theory of Roland Barthes, the structuralism theorist, in this regard will be discussed. This study tends to investigate the question of how the connection between text and image in illustrated manuscripts of the Jalayrid period is defined according to Barthes’ theory. And what kind of proportion has the artist created in the composition between text and image. Based on the results of reviewing the data of this study, it can be inferred that in the Jalayrid period, the image has a reference connection and although it is of major importance on the page, it also maintains a close connection with the text and is placed in a special proportion. It is not necessarily balanced and symmetrical and sometimes uses imbalance for composition. This research has been done by descriptive-analytical method, which has been done by library collection method.

Keywords: structure, text, image, Jalayrid, painter

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Authors: Farideh K. Khosroushahi, Serkan Erdal, Mucip Geni̇şel

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Soil salinity is one of the major abiotic stress factors that restricts arable land and reduces crop productivity worldwide. High salt concentration adversely affects plant growth and development inducing water deficit, ionic toxicity, nutrient imbalance, and lead to oxidative stress. Although the stimulating role of mammalian sex hormones on various biological and biochemical processes under normal and stress condition have been proven, there is no study regarding with these hormone's effect on modulation of the alternative respiration pathway and AOX gene expression. In this study, changes in alternative respiration pathway in leaves of maize seedlings under salinity and the possible modulating effect of estrogen on these changes were investigated. Maize seedlings were grown in a hydroponic media for 11 days and then were exposed to salt stress for 3 days after being sprayed estrogen. The data obtained from oxygen consumption revealed that salt stress elevated cellular respiration value in the leaves. In addition, a marked increase was observed at alternative respiration level in salt-stressed seedlings. Compared to salt application alone, supplementation with estrogen resulted in a significant rise in alternative oxidase (AOX) activities. Similarly, while salt stress caused to rise in expressions of AOX gene compared to control seedlings, estrogen application resulted in further activation of these genes’ expression compared to stressed-seedlings alone. These data revealed that mitigating role of estrogen against the detrimental effects of salt stress is linked to modulation of alternative respiration pathway.

Keywords: alternative oxidase, estrogen, Ssalt stress, AOX, maize

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Authors: Saba Ebrahimi, Saeed Ahmadian, Hedie Ashrafi

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Selecting appropriate patients for surgery is one of the main issues in thoracic surgery (TS). Both short-term and long-term risks and benefits of surgery must be considered in the patient selection criteria. There are some limitations in the existing datasets of TS patients because of missing values of attributes and imbalanced distribution of survival classes. In this study, a novel ensemble architecture of deep learning networks is proposed based on stacking different linear and non-linear layers to deal with imbalance datasets. The categorical and numerical features are split using different layers with ability to shrink the unnecessary features. Then, after extracting the insight from the raw features, a novel biased-kernel layer is applied to reinforce the gradient of the minority class and cause the network to be trained better comparing the current methods. Finally, the performance and advantages of our proposed model over the existing models are examined for predicting patient survival after thoracic surgery using a real-life clinical data for lung cancer patients.

Keywords: deep learning, ensemble models, imbalanced classification, lung cancer, TS patient selection

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Authors: T. Northcut, A. Rai, N. Perkins

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Background: The COVID-19 pandemic has had a serious impact on academia in general and social work education in particular, changing permanently the way in which we approach educating students. The new reality of the pandemic coupled with the much-needed focus on racism across the country inspired and required educators to get creative with their teaching styles in order to disrupt the power imbalance in the classroom and attend to the multiple layers of needs of diverse students in precarious sociological and economic circumstances. This paper highlights research examining educators with distinctive positionalities and approaches to classroom instruction who use feminist and antiracist pedagogies while adapting to online teaching during the pandemic. Despite being feminist scholars, whose ideologies developed during different waves of feminism, our commitment to having student-led classrooms, liberation, and equity of all, and striving for social change, unified our feminist teaching pedagogies as well as provided interpersonal support. Methodology: Following a narrative qualitative inquiry methodology, the five authors of this paper came together to discuss our pedagogical styles and underlying values using Zoom in a series of six conversations. Narrative inquiry is an appropriate method to use when researchers are bound by common stories or personal experiences. The use of feminist pedagogy in the classroom before and during the pandemic guided the discussions. After six sessions, we reached the point of data saturation. All data from the dialogic process was recorded and transcribed. We used in vivo, narrative, and descriptive coding for the data analytic process. Results: Analysis of the data revealed several themes, which included (1) the influence of our positionalities as an intersection of race, sexual orientation, gender, and years of teaching experience in the classroom, (2) the meaning and variations between different liberatory pedagogical approaches, (3) the tensions between these approaches and institutional policies and practices, (4) the role of self-reflection in everyday teaching, (5) the distinctions between theory and practice and its utility for students, and (6) the challenges of applying a feminist-centered pedagogical approach during the pandemic while utilizing an online platform. As a collective, we discussed several challenges that limited the use of our feminist pedagogical approaches due to instruction through Zoom.

Keywords: feminist, pedagogy, COVID, zoom

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Authors: Faisal Kalota

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Big Data and analytics have gained a huge momentum in recent years. Big Data feeds into the field of Learning Analytics (LA) that may allow academic institutions to better understand the learners’ needs and proactively address them. Hence, it is important to have an understanding of Big Data and its applications. The purpose of this descriptive paper is to provide an overview of Big Data, the technologies used in Big Data, and some of the applications of Big Data in education. Additionally, it discusses some of the concerns related to Big Data and current research trends. While Big Data can provide big benefits, it is important that institutions understand their own needs, infrastructure, resources, and limitation before jumping on the Big Data bandwagon.

Keywords: big data, learning analytics, analytics, big data in education, Hadoop

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Authors: Amine Ait-Ouahmed, Didier Josselin, Fen Zhou

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Free-Float car-sharing is an one-way car-sharing service where cars are available anytime and anywhere in the streets such that no dedicated stations are needed. This means that after driving a car you can park it anywhere. This car-sharing system creates an imbalance car distribution in the cites which can be regulated by staff agents through the redistribution of cars. In this paper, we aim to solve the car-reservation and agents traveling problem so that the number of successful cars’ reservations could be maximized. Beside, we also tend to minimize the distance traveled by agents for cars redistribution. To this end, we present a mixed integer linear programming formulation for the car-sharing problem.

Keywords: one-way car-sharing, vehicle redistribution, car reservation, linear programming

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Authors: Dongqi Sun, Juan Tao, Yingying Wu

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This paper reexamines the appropriateness of contrarian trades as a proxy of informed trades, using high frequency Chinese stock data. Employing this measure for 5 minute intervals, a U-shaped intraday pattern of probability of informed trades (PIN) is found for the CSI300 stocks, which is consistent with previous findings for other markets. However, while dividing the trades into different sizes, a reversed U-shaped PIN from large-sized trades, opposed to the U-shaped pattern for small- and medium-sized trades, is observed. Drawing from the mixed evidence with different trade sizes, the price impact of trades is further investigated. By examining the relationship between trade imbalances and unexpected returns, larges-sized trades are found to have significant price impact. This implies that in those intervals with large trades, it is non-contrarian trades that are more likely to be informed trades. Taking account of the price impact of large-sized trades, non-contrarian trades are used to proxy for informed trading in those intervals with large trades, and contrarian trades are still used to measure informed trading in other intervals. A stronger U-shaped PIN is demonstrated from this modification. Auto-correlation and information advantage tests for robustness also support the modified informed trading measure.

Keywords: contrarian trades, informed trading, price impact, trade imbalance

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Authors: Nathenal Thomas

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In the food chain and in many other agricultural products, corn, also known as maize, which goes by the scientific name Zea mays subsp, is a widely produced agricultural product. Corn has the highest adaptability. It comes in many different types, is employed in many different industrial processes, and is more adaptable to different agro-climatic situations. In Ethiopia, maize is among the most widely grown crop. Small-scale corn farming may be a household's only source of food in developing nations like Ethiopia. The aforementioned data demonstrates that the country's requirement for this crop is excessively high, and conversely, the crop's productivity is very low for a variety of reasons. The most damaging disease that greatly contributes to this imbalance between the crop's supply and demand is the corn disease. The failure to diagnose diseases in maize plant until they are too late is one of the most important factors influencing crop output in Ethiopia. This study will aid in the early detection of such diseases and support farmers during the cultivation process, directly affecting the amount of maize produced. The diseases in maize plants, such as northern leaf blight and cercospora leaf spot, have distinct symptoms that are visible. This study aims to detect the most frequent and degrading maize diseases using the most efficiently used subset of machine learning technology, deep learning so, called Image Processing. Deep learning uses networks that can be trained from unlabeled data without supervision (unsupervised). It is a feature that simulates the exercises the human brain goes through when digesting data. Its applications include speech recognition, language translation, object classification, and decision-making. Convolutional Neural Network (CNN) for Image Processing, also known as convent, is a deep learning class that is widely used for image classification, image detection, face recognition, and other problems. it will also use this algorithm as the state-of-the-art for my research to detect maize diseases by photographing maize leaves using a mobile phone.

Keywords: CNN, zea mays subsp, leaf blight, cercospora leaf spot

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Authors: Sandeep Sharma, Sarabjit Singh

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As per the user demand and growth trends of large free data the storage solutions are now becoming more challenge-able to protect, store and to retrieve data. The days are not so far when the storage companies and organizations are start saying 'no' to store our valuable data or they will start charging a huge amount for its storage and protection. On the other hand as per the environmental conditions it becomes challenge-able to maintain and establish new data warehouses and data centers to protect global warming threats. A challenge of small data is over now, the challenges are big that how to manage the exponential growth of data. In this paper we have analyzed the growth trend of big data and its future implications. We have also focused on the impact of the unstructured data on various concerns and we have also suggested some possible remedies to streamline big data.

Keywords: big data, unstructured data, volume, variety, velocity

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Authors: Yang Bao, Shi Wei Deng, WangQun Lin

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This paper introduces the concept and principle of data cleaning, analyzes the types and causes of dirty data, and proposes several key steps of typical cleaning process, puts forward a well scalability and versatility data cleaning framework, in view of data with attribute dependency relation, designs several of violation data discovery algorithms by formal formula, which can obtain inconsistent data to all target columns with condition attribute dependent no matter data is structured (SQL) or unstructured (NoSQL), and gives 6 data cleaning methods based on these algorithms.

Keywords: data cleaning, dependency rules, violation data discovery, data repair

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Authors: Swati Arun

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The present paper argues that Balance of Power (BOP) needs to conjugate with certain contingencies like geography. It is evident that sea powers (‘insular’ for better clarity) are not balanced (if at all) in the same way as land powers. Its apparent that artificial insularity that the US has achieved reduces the chances of balancing (constant) and helps it maintain preponderance (variable). But how precise is this approach in assessing the dynamics between China’s rise and reaction of other powers and US. The ‘evolved’ theory can be validated by putting China and US in the equation. Systemic Relation between the nations was explained through the Balance of Power theory much before the systems theory was propounded. The BOP is the crux of functionality of ‘power relation’ dynamics which has played its role in the most astounding ways leading to situations of war and peace. Whimsical; but true that, the BOP has remained a complicated and indefinable concepts since Hans. Morganthau to Kenneth Waltz. A challenge of the BOP, however remains; “ that it has too many meanings”. In the recent times it has become evident that the myriad of expectations generated by BOP has not met the practicality of the current world politics. It is for this reason; the BoP has been replaced by Preponderance Theory (PT) to explain prevailing power situation. PT does provide an empirical reasoning for the success of this theory but fails in a abstract logical reasoning required for making a theory universal. Unipolarity clarifies the current system as one where balance of power has become redundant. It seems to reach beyond the contours of BoP, where a superpower does what it must to remain one. The centrality of this arguments pivots around - an exception, every time BOP fails to operate, preponderance of power emerges. PT does not sit well with the primary logic of a theory because it works on an exception. The evolution of such a pattern and system where BOP fails and preponderance emerges is absent. The puzzle here is- if BOP really has become redundant or it needs polishing. The international power structure changed from multipolar to bipolar to unipolar. BOP was looked at to provide inevitable logic behind such changes and answer the dilemma we see today- why US is unchecked, unbalanced? But why was Britain unchecked in 19th century and why China was unbalanced in 13th century? It is the insularity of the state that makes BOP reproduce “imbalance of power”, going a level up from off-shore balancer. This luxury of a state to maintain imbalance in the region of competition or threat is the causal relation between BOP’s and geography. America has applied imbalancing- meaning disequilibrium (in its favor) to maintain the regional balance so that over time the weaker does not get stronger and pose a competition. It could do that due to the significant parity present between the US and the rest.

Keywords: balance of power, china, preponderance of power, US

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Authors: Hamidreza Joudaki, Yousefali Ziari

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The appearance of city and urbanism is one of the important processes which have affected social communities. Being industrialized urbanism developed along with each other in the history. In addition, they have had simple relationship for more than six thousand years, that is, from the appearance of the first cities. In 18th century by coming out of industrial capitalism, progressive development took place in urbanism in the world. In Iran, the city of each region made its decision by itself and the capital of region (downtown) was the only central part and also the regional city without any hierarchy, controlled its realm. However, this method of ruling during these three decays, because of changing in political, social and economic issues that have caused changes in rural and urban relationship. Moreover, it has changed the variety of performance of cities and systematic urban network in Iran. Today, urban system has very vast imbalanced apace and performance. In Isfahan, the trend of urbanism is like the other part of Iran and systematic urban hierarchy is not suitable and normal. This article is a quantitative and analytical. The statistical communities are Isfahan Province cities and the changes in urban network and its hierarchy during the period of fifty years (1956 -2006) has been surveyed. In addition, those data have been analyzed by model of Rank and size and Entropy index. In this article Iran cities and also the factor of entropy of primate city and urban hierarchy of Isfahan Province have been introduced. Urban residents of this Province have been reached from 55 percent to 83% (2006). As we see the analytical data reflects that there is mismatching and imbalance between cities. Because the entropy index was.91 in 1956.And it decreased to.63 in 2006. Isfahan city is the primate city in the whole of these periods. Moreover, the second and the third cities have population gap with regard to the other cities and finally, they do not follow the system of rank-size.

Keywords: urban network, urban hierarchy, primate city, Isfahan province, urbanism, first cities

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Authors: Dewi Tristantini, Jason Jonathan

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Coronary Artery Disease (CAD) is one of the deathliest diseases which is caused by atherosclerosis. Atherosclerosis is a disease that plaque builds up inside the arteries. Plaque is made up of fat, cholesterol, calcium, platelet, and other substances found in blood. The current treatment of atherosclerosis is to provide antiplatelet therapy treatment, but such treatments often cause gastrointestinal irritation, muscle pain and hormonal imbalance. Mimusops elengi L.’s leaves can be utilized as a natural and cheap antiplatelet’s source because it contains flavonoids such as quertecin. Antiplatelet aggregation effect of Mimusops elengi L.’s leaves’ wet extract was measured by bleeding time on DDY strain mice with the test substances were given orally during the period of 8 days. The bleeding time was measured on first day and 9th day. Empirically, the dose which is used for humans is 8.5 g of leaves in 600 ml of water. This dose is equivalent to 2.1 g of leaves in 350 ml of water for mice. The extract was divided into 3 doses for mice: 0.05 ml/day; 0.1 ml/day; 0.2 ml/day. After getting the percentage of the increase in bleeding time, data were analyzed by analysis of variance test (Anova), followed by individual comparison within the groups by LSD test. The test substances above respectively increased bleeding time 21%, 62%, and 128%. As the conclusion, the 0.02 ml/day dose of Mimusops elengi L.’s leaves’ wet extract could increase bleeding time better than clopidogrel as positive controls with 110% increase in bleeding time.

Keywords: antiplatelets, atheroschlerosis, bleeding time, Mimusops elengi

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Authors: Hoda A. Abdel Hafez

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Mining big data represents a big challenge nowadays. Many types of research are concerned with mining massive amounts of data and big data streams. Mining big data faces a lot of challenges including scalability, speed, heterogeneity, accuracy, provenance and privacy. In telecommunication industry, mining big data is like a mining for gold; it represents a big opportunity and maximizing the revenue streams in this industry. This paper discusses the characteristics of big data (volume, variety, velocity and veracity), data mining techniques and tools for handling very large data sets, mining big data in telecommunication and the benefits and opportunities gained from them.

Keywords: mining big data, big data, machine learning, telecommunication

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Authors: Bingying Liu, Dandong Ge, Xinlan Zhang, Haoyang Liang

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Over the past two years, a new generation of No-Pile Bike sharing, represented by the Ofo, Mobike and HelloBike, has sprung up in various cities in China, and spread rapidly in countries such as Britain, Japan, the United States and Singapore. As a new green public transportation mode, bike sharing can bring a series of benefits to urban space. At first, this paper analyzes the specific impact of bike sharing on urban space in China. Based on the market research and data analyzing, it is found that bike sharing can improve the quality of urban space in three aspects: expanding the radius of public transportation service, filling service blind spots, alleviating urban traffic congestion, and enhancing the vitality of urban space. On the other hand, due to the immature market and the imperfect system, bike sharing has gradually revealed some difficulties, such as parking chaos, malicious damage, safety problems, imbalance between supply and demand, and so on. Then the paper investigates the characteristics of shared bikes, business model, operating mechanism on Chinese market currently. Finally, in order to make bike sharing serve urban construction better, this paper puts forward some specific countermeasures from four aspects. In terms of market operations, it is necessary to establish a public-private partnership model and set up a unified bike-sharing integrated management platform. From technical methods level, the paper proposes to develop an intelligent parking system for regulating parking. From policy formulation level, establishing a bike-sharing assessment mechanism would strengthen supervision. As to urban planning, sharing data and redesigning slow roadway is beneficial for transportation and spatial planning.

Keywords: bike sharing, impact analysis, improvement strategy, urban space

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Authors: Kiran P. Chadayamuri, Saransh Bagdi

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Increasing imbalance between energy supply and demand has made nations and companies involved in the energy sector to boost up their research and find suitable solutions. With the high rates at which conventional oil and gas resources are depleting, efficient exploration and exploitation of heavy oil could just be the answer. Heavy oil may be defined as crude oil having API gravity value of less than 20⁰. They are highly viscous, have low hydrogen to carbon ratios and are known to produce high carbon residues. They have high contents of asphaltenes, heavy metals, sulphur and nitrogen in them. Due to these properties extraction, transportation and refining of crude oil have its share of challenges. Lack of suitable technology has hindered its production in the past, but now things are going in a more positive direction. The aim of this paper is to study the various advantages of heavy oil, associated limitations and its feasibility as a fuel of the future.

Keywords: energy, heavy oil, fuel, future

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Authors: Meimei Wen, Chang Nyung Kim

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In the current study, three-dimensional liquid metal (LM) magneto-hydrodynamic (MHD) flows in a manifold with three sub-channels under a uniform magnetic field are numerically investigated. In the manifold, the electrical current can cross channel walls, thus having influence on the flow distribution in each sub-channel. A case with various arrangements of electric conductivity for different parts of channel walls is considered, yielding different current distributions as well as flow distributions in each sub-channel. Here, the imbalance of mass flow rates in the three sub-channels is addressed. Meanwhile, predicted are detailed behaviors of the flow velocity, pressure, current and electric potential of LM MHD flows with three sub-channels. Commercial software CFX is used for the numerical simulation of LM MHD flows.

Keywords: CFX, liquid metal, manifold, MHD flow

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Authors: Theertha Chandroth

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This paper presents a comparative study on how to check JSON (JavaScript Object Notation) data against XML (eXtensible Markup Language) data from a software testing point of view. JSON and XML are widely used data interchange formats, each with its unique syntax and structure. The objective is to explore various techniques and methodologies for validating comparison and integration between JSON data to XML and vice versa. By understanding the process of checking JSON data against XML data, testers, developers and data practitioners can ensure accurate data representation, seamless data interchange, and effective data validation.

Keywords: XML, JSON, data comparison, integration testing, Python, SQL

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Authors: Ebrahim Gharleghi

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This paper aims to examine how customer knowledge management (CKM) can be implemented in Iranian Banks in practice, with the focus on the human resource (people, technology and processes) as important factors of CKM. A conceptual model of an analytical CKM strategy for CKM in this Iranian Banks is developed from the findings and literature review. This article has been based on interviews and distributing the questionnaire. Data were collected from 260 managers from bank managers. The paper finds that hypotheses were tested using student’s t-test (one-sample t-test), Pearson correlation analysis and regression analysis. Test of hypotheses revealed that human, technology and processes factors positively and significantly influenced the implementation of CKM practices. These findings tend to corroborate our conceptual model. Human factor of CKM was found to be more significantly affecting appropriate CKM implementation than others CKM factors, indicating that this factor is more important than the others aspects of CKM. On the other hand, this factor is appropriate in Iranian Banks. Process is in second part and technology is in final part. This indicates that technology infrastructures are so weak in Iranian Banks for CKM implementation. In this paper there is little or no empirical evidence investigating the amount of the execution of the CKM in Iranian Banks. This paper rectifies this imbalance by clarifying the significance human, technology and processes factors in CKM implementation.

Keywords: knowledge management, customer relationship management, customer knowledge management, integration, people, technology, process

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Authors: Bahar Salavati Vie Le Sage, Ismaïl Ben Hariz, Flavien Viguier, Sirine Noura Kahil, Audrey Jacquin, Maxime Convert

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The ballast layer plays a key role in railroad maintenance and the geometry of the track structure. Ballast also holds the track in place as the trains roll over it. Track ballast is packed between the sleepers and on the sides of railway tracks. An imbalance in ballast volume on the tracks can lead to safety issues as well as a quick degradation of the overall quality of the railway segment. If there is a lack of ballast in the track bed during the summer, there is a risk that the rails will expand and buckle slightly due to the high temperatures. Furthermore, the knowledge of the ballast quantities that will be excavated during renewal works is important for efficient ballast management. The volume of excavated ballast per meter of track can be calculated based on excavation depth, excavation width, volume of track skeleton (sleeper and rail) and sleeper spacing. Since 2012, SNCF has been collecting 3D points cloud data covering its entire railway network by using 3D laser scanning technology (LiDAR). This vast amount of data represents a modelization of the entire railway infrastructure, allowing to conduct various simulations for maintenance purposes. This paper aims to present an automated method for ballast volume estimation based on the processing of LiDAR data. The estimation of abnormal volumes in ballast on the tracks is performed by analyzing the cross-section of the track. Further, since the amount of ballast required varies depending on the track configuration, the knowledge of the ballast profile is required. Prior to track rehabilitation, excess ballast is often present in the ballast shoulders. Based on 3D laser scans, a Digital Terrain Model (DTM) was generated and automatic extraction of the ballast profiles from this data is carried out. The surplus in ballast is then estimated by performing a comparison between this ballast profile obtained empirically, and a geometric modelization of the theoretical ballast profile thresholds as dictated by maintenance standards. Ideally, this excess should be removed prior to renewal works and recycled to optimize the output of the ballast renewal machine. Based on these parameters, an application has been developed to allow the automatic measurement of ballast profiles. We evaluated the method on a 108 kilometers segment of railroad LiDAR scans, and the results show that the proposed algorithm detects ballast surplus that amounts to values close to the total quantities of spoil ballast excavated.

Keywords: ballast, railroad, LiDAR , cloud point, track ballast, 3D point

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Authors: Bolin Hua

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In city governance, various data are involved, including city component data, demographic data, housing data and all kinds of business data. These data reflects different aspects of people, events and activities. Data generated from various systems are different in form and data source are different because they may come from different sectors. In order to reflect one or several facets of an event or rule, data from multiple sources need fusion together. Data from different sources using different ways of collection raised several issues which need to be resolved. Problem of data fusion include data update and synchronization, data exchange and sharing, file parsing and entry, duplicate data and its comparison, resource catalogue construction. Governments adopt statistical analysis, time series analysis, extrapolation, monitoring analysis, value mining, scenario prediction in order to achieve pattern discovery, law verification, root cause analysis and public opinion monitoring. The result of Multi-source data fusion is to form a uniform central database, which includes people data, location data, object data, and institution data, business data and space data. We need to use meta data to be referred to and read when application needs to access, manipulate and display the data. A uniform meta data management ensures effectiveness and consistency of data in the process of data exchange, data modeling, data cleansing, data loading, data storing, data analysis, data search and data delivery.

Keywords: multi-source data fusion, urban comprehensive management, information fusion, government data

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Authors: Sajjad Baghernezhad, Saeideh Baghernezhad

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Nowadays considering human involved in increasing data development some methods such as data mining to extract science are unavoidable. One of the discussions of data mining is inherent distribution of the data usually the bases creating or receiving such data belong to corporate or non-corporate persons and do not give their information freely to others. Yet there is no guarantee to enable someone to mine special data without entering in the owner’s privacy. Sending data and then gathering them by each vertical or horizontal software depends on the type of their preserving type and also executed to improve data privacy. In this study it was attempted to compare comprehensively preserving data methods; also general methods such as random data, coding and strong and weak points of each one are examined.

Keywords: data mining, distributed data mining, privacy protection, privacy preserving

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Authors: Mahnaz Hosseinzadeh, Shaghayegh Rezaee Amiri

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This paper presents a methodology for serial production planning problem in wire and cable manufacturing process that addresses the problem of input-output imbalance in different consecutive stations, hoping to minimize the halt of machines in each stage. To this end, a linear Goal Programming (GP) model is developed, in which four main categories of constraints as per the number of runs per machine, machines’ sequences, acceptable inventories of machines at the end of each period, and the necessity of fulfillment of the customers’ orders are considered. The model is formulated based upon on the real data obtained from IKO TAK Company, an important supplier of wire and cable for oil and gas and automotive industries in Iran. By solving the model in GAMS software the optimal number of runs, end-of-period inventories, and the possible minimum idle time for each machine are calculated. The application of the numerical results in the target company has shown the efficiency of the proposed model and the solution in decreasing the lead time of the end product delivery to the customers by 20%. Accordingly, the developed model could be easily applied in wire and cable companies for the aim of optimal production planning to reduce the halt of machines in manufacturing stages.

Keywords: goal programming approach, GP, production planning, serial manufacturing process, wire and cable industry

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Authors: Roman Bieda

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The General Data Protection Regulation (GDPR) will come into force on 25 May 2018 which will create a new legal framework for the protection of personal data in the European Union. Article 20 of GDPR introduces a right to data portability. This right allows for data subjects to receive the personal data which they have provided to a data controller, in a structured, commonly used and machine-readable format, and to transmit this data to another data controller. The right to data portability, by facilitating transferring personal data between IT environments (e.g.: applications), will also facilitate changing the provider of services (e.g. changing a bank or a cloud computing service provider). Therefore, it will contribute to the development of competition and the digital market. The aim of this paper is to discuss the right to data portability and its influence on the development of new digital services.

Keywords: data portability, digital market, GDPR, personal data

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Authors: Mufide Cotuk, Muslim Bakir

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National education in Turkey aims to provide superior education opportunities to students in order to develop their intellectual abilities in accordance with contemporary pedagogy. Physical education (PE) plays an important role in this context. Various factors affect the quality and efficiency of the process of PE. Factors related to governance are crucially important, especially those of authority and responsibility. For educational institutions at high school level, the factors affecting authority and responsibility have not been clearly delineated. Therefore, the aim of this study was to examine authority and responsibility of PE teachers as the balance between them. The study sample consisted of 60 PE teachers (19 women, 41 men) at 57 high schools in Istanbul (65% state and 35% private institutions). All PE teachers completed the study questionnaire collecting demographic and institutional data as knowledge and attitudes regarding authority and responsibility issues. The determination of authority and responsibility of PE teachers has been grounded on the law for government officials, course-passing regulations, and school sports regulations. The PE teachers declared as the primary source of their authority and responsibility ‘school sports regulations’ (56,7% of PE teachers), ‘course-passing regulations’ (36,7% of PE teachers) and ‘the law for government officials’ (30,0% of PE teachers). The PE teachers mentioned that the school administration burdened them with additional responsibilities (58,3% of PE teachers). Such ‘additional’ responsibilities were primarily related to ‘disciplinary regulations’ (21,7% of PE teachers) and ‘maintenance of school order’ (16,0% of PE teachers). In conclusion, authority and responsibility of PE teachers were not well balanced. As authority issues were not clearly stated, ‘compulsory’ responsibilities increased causing this imbalance.

Keywords: authority, PE teacher, responsibility, sport management

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Authors: Shayan Mohajer Hamidi

Abstract:

Federated Learning (FL) has emerged as a promising paradigm for training machine learning models on distributed data without the need for centralized data aggregation. In the realm of wireless communications, FL has the potential to leverage the vast amounts of data generated by wireless devices to improve model performance and enable intelligent applications. However, the fairness aspect of FL in wireless communications remains largely unexplored. This abstract presents an idea for fair federated learning in wireless communications, addressing the challenges of imbalanced data distribution, privacy preservation, and resource allocation. Firstly, the proposed approach aims to tackle the issue of imbalanced data distribution in wireless networks. In typical FL scenarios, the distribution of data across wireless devices can be highly skewed, resulting in unfair model updates. To address this, we propose a weighted aggregation strategy that assigns higher importance to devices with fewer samples during the aggregation process. By incorporating fairness-aware weighting mechanisms, the proposed approach ensures that each participating device's contribution is proportional to its data distribution, thereby mitigating the impact of data imbalance on model performance. Secondly, privacy preservation is a critical concern in federated learning, especially in wireless communications where sensitive user data is involved. The proposed approach incorporates privacy-enhancing techniques, such as differential privacy, to protect user privacy during the model training process. By adding carefully calibrated noise to the gradient updates, the proposed approach ensures that the privacy of individual devices is preserved without compromising the overall model accuracy. Moreover, the approach considers the heterogeneity of devices in terms of computational capabilities and energy constraints, allowing devices to adaptively adjust the level of privacy preservation to strike a balance between privacy and utility. Thirdly, efficient resource allocation is crucial for federated learning in wireless communications, as devices operate under limited bandwidth, energy, and computational resources. The proposed approach leverages optimization techniques to allocate resources effectively among the participating devices, considering factors such as data quality, network conditions, and device capabilities. By intelligently distributing the computational load, communication bandwidth, and energy consumption, the proposed approach minimizes resource wastage and ensures a fair and efficient FL process in wireless networks. To evaluate the performance of the proposed fair federated learning approach, extensive simulations and experiments will be conducted. The experiments will involve a diverse set of wireless devices, ranging from smartphones to Internet of Things (IoT) devices, operating in various scenarios with different data distributions and network conditions. The evaluation metrics will include model accuracy, fairness measures, privacy preservation, and resource utilization. The expected outcomes of this research include improved model performance, fair allocation of resources, enhanced privacy preservation, and a better understanding of the challenges and solutions for fair federated learning in wireless communications. The proposed approach has the potential to revolutionize wireless communication systems by enabling intelligent applications while addressing fairness concerns and preserving user privacy.

Keywords: federated learning, wireless communications, fairness, imbalanced data, privacy preservation, resource allocation, differential privacy, optimization

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Authors: Fahad Hanash Alzahrani

Abstract:

This paper describes some recent advances in a quickly developing area of data storing and processing based on Data Warehouses and Data Mining techniques, which are associated with software, hardware, data mining algorithms and visualisation techniques having common features for any specific problems and tasks of their implementation.

Keywords: data warehouse, data mining, knowledge discovery in databases, on-line analytical processing

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Authors: Mehmet Akif Aslan, Mehmet Simsek, Eyup Sensoy

Abstract:

Big Data stands for today’s cutting-edge technology. As the technology becomes widespread, so does Data. Utilizing massive data sets enable companies to get competitive advantages over their adversaries. Out of many area of Big Data usage, logistics has significance role in both commercial sector and military. This paper lays out what big data is and how it is used in both military and commercial logistics.

Keywords: big data, logistics, operational efficiency, risk management

Procedia PDF Downloads 630

Authors: Oghenerukome Akponovo, Lynda I. Onyebuchukwu

Abstract:

Construction waste, along with that of many other industries, contributes significantly to the world's annual solid waste totals. Most of these materials, such as ash from rice hulls, slags, cement kiln dust, tire ash, plastic waste (PW), and silica fumes, end up in landfills or waterways. Some of them might even end up polluting the air from high in the atmosphere. It's sustainable, cheap, and environmentally friendly to recycle these items into new building supplies. When constructing a "Green" structure, the materials employed have the potential to either exacerbate environmental imbalance or maintain a stable ecosystem. The purpose of this research is to take stock of what is already known about recycling's potential in the construction industry and to identify its deficiencies. Therefore, this study systematically reviews the wide range of recycled materials that go into building construction. Recognizing that the construction industry's use of recycled materials has an influence on the environment and that investigating these materials may have a substantial economic impact if they were discovered

Keywords: building, construction, recycled materials, waste management

Procedia PDF Downloads 91