Search results for: big data markets

Authors: G. R. Navaneesh, E. Nagarajan, C. H. Rajam Raju

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Nowadays the multimedia data are used to store some secure information. All previous methods allocate a space in image for data embedding purpose after encryption. In this paper, we propose a novel method by reserving space in image with a boundary surrounded before encryption with a traditional RDH algorithm, which makes it easy for the data hider to reversibly embed data in the encrypted images. The proposed method can achieve real time performance, that is, data extraction and image recovery are free of any error. A secure transmission process is also discussed in this paper, which improves the efficiency by ten times compared to other processes as discussed.

Keywords: secure communication, reserving room before encryption, least significant bits, image encryption, reversible data hiding

Procedia PDF Downloads 389

Authors: Fuad M. Alkoot

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DNA data have been used in forensics for decades. However, current research looks at using the DNA as a biometric identity verification modality. The goal is to improve the speed of identification. We aim at using gene data that was initially used for autism detection to find if and how accurate is this data for identification applications. Mainly our goal is to find if our data preprocessing technique yields data useful as a biometric identification tool. We experiment with using the nearest neighbor classifier to identify subjects. Results show that optimal classification rate is achieved when the test set is corrupted by normally distributed noise with zero mean and standard deviation of 1. The classification rate is close to optimal at higher noise standard deviation reaching 3. This shows that the data can be used for identity verification with high accuracy using a simple classifier such as the k-nearest neighbor (k-NN). 

Keywords: biometrics, genetic data, identity verification, k nearest neighbor

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Authors: R Palson Kennedy, P.Kiran Sai

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This article introduces machine learning (ML) researchers to the hurdles that geoscience problems present, as well as the opportunities for improvement in both ML and geosciences. This article presents a review from the data life cycle perspective to meet that need. Numerous facets of geosciences present unique difficulties for the study of intelligent systems. Geosciences data is notoriously difficult to analyze since it is frequently unpredictable, intermittent, sparse, multi-resolution, and multi-scale. The first half addresses data science’s essential concepts and theoretical underpinnings, while the second section contains key themes and sharing experiences from current publications focused on each stage of the data life cycle. Finally, themes such as open science, smart data, and team science are considered.

Keywords: Data science, intelligent system, machine learning, big data, data life cycle, recent development, geo science

Procedia PDF Downloads 119

Authors: Mohammad Mehdizadeh, Sara Miri

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In today's world, competition is one of the essential components of different markets. Therefore, in addition to economic factors, social factors can also affect the development and prosperity of businesses. In this regard, social networks are of particular importance and play a critical role in the flourishing and development of Internet businesses. The purpose of this article is to investigate the effect of different social networks in promoting digital entrepreneurship. The research method is the descriptive survey. The results show that social networks have a positive and significant impact on digital entrepreneurship development. Among the social networks studied, Instagram and Facebook have the most positive effect on digital entrepreneurship.

Keywords: entrepreneurship, Facebook, Instagram, social media

Procedia PDF Downloads 323

Authors: Shervin Alaei, Reza Moradi

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Trading in financial markets is subject to risks due to their high volatilities. Here, using an LSTM neural network, and by doing some risk-based feature engineering tasks, we developed a method that can accurately predict trends of the Tehran stock exchange market index from a few days ago. Our test results have shown that the proposed method with an average prediction accuracy of more than 94% is superior to the other common machine learning algorithms. To the best of our knowledge, this is the first work incorporating deep learning and risk factors to accurately predict market trends.

Keywords: deep learning, LSTM, trend prediction, risk management, artificial neural networks

Procedia PDF Downloads 129

Authors: Marc Bachelet, Abhijit Kumar Chatterjee, José Manuel Avila

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Data quality is a key component of any data-driven organization. Without data quality, organizations cannot effectively make data-driven decisions, which often leads to poor business performance. Therefore, it is important for an organization to ensure that the data they use is of high quality. This is where the concept of data mesh comes in. Data mesh is an organizational and architectural decentralized approach to data management that can help organizations improve the quality of data. The concept of data mesh was first introduced in 2020. Its purpose is to decentralize data ownership, making it easier for domain experts to manage the data. This can help organizations improve data quality by reducing the reliance on centralized data teams and allowing domain experts to take charge of their data. This paper intends to discuss how a set of elements, including data mesh, are tools capable of increasing data quality. One of the key benefits of data mesh is improved metadata management. In a traditional data architecture, metadata management is typically centralized, which can lead to data silos and poor data quality. With data mesh, metadata is managed in a decentralized manner, ensuring accurate and up-to-date metadata, thereby improving data quality. Another benefit of data mesh is the clarification of roles and responsibilities. In a traditional data architecture, data teams are responsible for managing all aspects of data, which can lead to confusion and ambiguity in responsibilities. With data mesh, domain experts are responsible for managing their own data, which can help provide clarity in roles and responsibilities and improve data quality. Additionally, data mesh can also contribute to a new form of organization that is more agile and adaptable. By decentralizing data ownership, organizations can respond more quickly to changes in their business environment, which in turn can help improve overall performance by allowing better insights into business as an effect of better reports and visualization tools. Monitoring and analytics are also important aspects of data quality. With data mesh, monitoring, and analytics are decentralized, allowing domain experts to monitor and analyze their own data. This will help in identifying and addressing data quality problems in quick time, leading to improved data quality. Data culture is another major aspect of data quality. With data mesh, domain experts are encouraged to take ownership of their data, which can help create a data-driven culture within the organization. This can lead to improved data quality and better business outcomes. Finally, the paper explores the contribution of AI in the coming years. AI can help enhance data quality by automating many data-related tasks, like data cleaning and data validation. By integrating AI into data mesh, organizations can further enhance the quality of their data. The concepts mentioned above are illustrated by AEKIDEN experience feedback. AEKIDEN is an international data-driven consultancy that has successfully implemented a data mesh approach. By sharing their experience, AEKIDEN can help other organizations understand the benefits and challenges of implementing data mesh and improving data quality.

Keywords: data culture, data-driven organization, data mesh, data quality for business success

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Authors: Johannes Atug, Stefan Braunreuther, Gunther Reinhart

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Volatile markets, as well as increasing global competition in manufacturing, lead to a high demand of flexible and agile production systems. These advanced production systems in turn conduct to high capital expenditure along with high investment risks. Developments in production regarding digitalization and cyber-physical systems result to a merger of informational- and operational technology. The approach of this paper is to benefit from this merger and present a framework of a production network with scalable production capacity and low capital expenditure by adaptation of the IT concept 'everything as a service' into the production environment.

Keywords: digital manufacturing system, everything as a service, reconfigurable production, value network

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Authors: K. Ö. Kartal, L. Maul, M. Hägele

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With the development of new technologies come additional opportunities for the founding of companies and new markets to be created. The barriers to entry are lowered and technology makes old business models obsolete. Incumbent companies have to be adaptable to this quickly changing environment. They have to start the process of digital maturation and they have to be able to adapt quickly to new and drastic changes that might arise. One of the biggest barriers for organizations in order to do so is their culture. This paper shows the core elements of a corporate culture that supports the process of digital maturation in incumbent organizations. Furthermore, it is explored how ideation and innovation can be used in a strategy in order to facilitate these core elements of culture that promote digital maturity. Focus areas are identified for the design of ideation strategies, with the aim to make the facilitation and incitation process more effective, short to long term. Therefore, one in-depth case study is conducted with data collection from interviews, observation, document review and surveys. The findings indicate that digital maturity is connected to cultural shift and 11 relevant elements of digital culture are identified which have to be considered. Based on these 11 core elements, five focus areas that need to be regarded in the design of a strategy that uses ideation and innovation to facilitate the cultural shift are identified. These are: Focus topics, rewards and communication, structure and frequency, regions and new online formats.

Keywords: digital transformation, innovation management, ideation strategy, creativity culture, change

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Authors: Yazdani Saeed, Rafiei Hamed, Nekoofar Farahnaz

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Governments Policies play a major role in national and international Markets. Pistachio is one of the most important non-oil export commodity of Iran. Therefore, in this study the relation between the producer support policies and the export of Pistachio was examined. An econometric model (VAR) was applied to test the study hypothesis. According to the estimated coefficient in VAR model, lag of producer support index has a significant and negative effect on variation of Pistachio’s export in short term. In other word, in short term, export advantage index is dependent on the amount of producers support in previous period.

Keywords: producer support, export advantage, pistachio, Iran

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Authors: Adnan Celik

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Entrepreneurs are people who attempt to do a business and do not hesitate to do so. They are involved in the production of economic goods and services through factors of production. They also find the financial resources necessary for production and the markets where the production will be evaluated. After all, they create economic values. The main function of the entrepreneur in contemporary societies is to realize innovations. From this point, the power of the modern entrepreneur is based on her/his capacity to innovate and transform his innovations into tangible commercial products. In this context, the concept of an entrepreneur is used to mean the person or persons who constantly innovate. Successful entrepreneurs take on the role of the locomotive in the development of their countries. They support economic development with their activities. In addition to production and marketing activities, it also has important contributions to employment. Along with the development of the country, they also try to make the income distribution more balanced. Especially developed country entrepreneurs intensely perform the following functions; “to produce new goods and services or to increase the quality and quality of known goods and services; ability to develop and apply new production methods; establishing new organizations in the industry; reach new markets; to find new sources from which raw materials and similar materials can be obtained”. Entrepreneurs who fully implement business functions are easier to achieve economic efficiency. Thus, they provide great advantages to the business and the national economy. Successful entrepreneurs are people who make money by creating economic values. These revenues are; on the one hand, it is distributed to individuals in the business as wages, premiums, or dividends; It is also used in the growth of companies. Thus, employees, managers, entrepreneurs and the whole country can benefit greatly. In the least developed countries, the guiding effect of traditional value patterns on individuals' attitudes and behaviors varies depending on the socio-economic characteristics of individuals. It is normal for an entrepreneur with a low level of education, who was brought up in a traditional structure, to behave in accordance with traditional value patterns. In fact, this is the primary problem of all countries in the development effort. The solution to this problem will be possible by giving the necessary importance to the social dimension as well as the technical dimension of development. This study mainly focuses on the importance of entrepreneurship for the national economy. This issue has been handled separately in terms of developed and least developed countries. As a result of the study, entrepreneurship suggestions were made, especially to least developed countries, with the goal of national economy and development.

Keywords: entrepreneur, entrepreneurship, national economy, entrepreneurship in developed and least developed countries

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Authors: Ji Eun Shin, Byung Ho Jung, Dong Hoon Lim

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It is almost impossible to store or analyze big data increasing exponentially with traditional technologies. Hadoop is a new technology to make that possible. R programming language is by far the most popular statistical tool for big data analysis based on distributed processing with Hadoop technology. With RHadoop that integrates R and Hadoop environment, we implemented parallel multiple regression analysis with different sizes of actual data. Experimental results showed our RHadoop system was much faster as the number of data nodes increases. We also compared the performance of our RHadoop with lm function and big lm packages available on big memory. The results showed that our RHadoop was faster than other packages owing to paralleling processing with increasing the number of map tasks as the size of data increases.

Keywords: big data, Hadoop, parallel regression analysis, R, RHadoop

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Authors: Doaa H. I. Mahmoud, El-Said M. Elsharkawy, Saad Z. Soliman, Soher E. Mustfa

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The opening of new promising foreign markets is one of the objectives of Egypt’s foreign trade policies, especially for agricultural exports. This study aims at the examination of the commodity structure of the Egyptian agricultural imports and exports with the COMESA countries. In addition, estimation of the surplus/deficit of the Egyptian commodities and agricultural balance with these countries is made. Time series data covering the period 2004-2016 is used. Estimation of the growth function along with the derivation of the annual growth rates of the study’s variables is made. Some of the results of the study period display the following: (1) The average total Egyptian exports to the COMESA (Common Market for Eastern and Southern Africa) countries is estimated at 1,491 million dollars, with an annual growth rate of 14.4% (214.7 million dollars). (2) The average annual Egyptian agricultural exports to these economies is estimated at 555 million dollars, with an annual growth rate of 19.4% (107.7 million dollars). (3) The average annual value of agricultural imports from the COMESA countries is set at 289 Million Dollars, with an annual growth rate of 14.4% (41.6 million dollars). (4) The study shows that there is a continuous surplus in the agricultural balance with these economies, whilst having a deficit in the raw-materials agricultural balance, as well as the balance of input requirements with these countries.

Keywords: COMESA, Egypt, growth rates, trade balance

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Authors: Haojie Wang, Xun Li, Rui Yin

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In order to solve the memorization overfitting in the meta-learning MAML algorithm, a method of generating mutually exclusive tasks based on data augmentation is proposed. This method generates a mutex task by corresponding one feature of the data to multiple labels, so that the generated mutex task is inconsistent with the data distribution in the initial dataset. Because generating mutex tasks for all data will produce a large number of invalid data and, in the worst case, lead to exponential growth of computation, this paper also proposes a key data extraction method, that only extracts part of the data to generate the mutex task. The experiments show that the method of generating mutually exclusive tasks can effectively solve the memorization overfitting in the meta-learning MAML algorithm.

Keywords: data augmentation, mutex task generation, meta-learning, text classification.

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Authors: Sifat Rahman Ahona, Rifat Tasnim, Naima Hassan

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Data aggregation is a helpful technique for reducing the data communication overhead in wireless sensor network. One of the important tasks of data aggregation is positioning of the aggregator points. There are a lot of works done on data aggregation. But, efficient positioning of the aggregators points is not focused so much. In this paper, authors are focusing on the positioning or the placement of the aggregation points in wireless sensor network. Authors proposed an algorithm to select the aggregators positions for a scenario where aggregator nodes are more powerful than sensor nodes.

Keywords: aggregation point, data communication, data aggregation, wireless sensor network

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Authors: Barbora Chmelikova

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Current financial markets offer a wide range of financial products to the consumers. However, access to the financial products is not always provided or guaranteed, particularly in less developed countries. For this reason, financial inclusion is an important component in the modern society. This paper investigates financial inclusion and what financial products are held by university students majoring in finance fields. The OECD methodology was used to examine the awareness and use of financial products. The study was conducted via online questionnaire at Masaryk University in the Czech Republic among finance students. The results show that the students use current and savings accounts more than any other financial products.

Keywords: financial inclusion, financial products, personal finance, university students

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Authors: Paula Simões, Isabel Natário

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This paper reviews a number of theoretical aspects for implementing an explicit spatial perspective in econometrics for modelling non-continuous data, in general, and count data, in particular. It provides an overview of the several spatial econometric approaches that are available to model data that are collected with reference to location in space, from the classical spatial econometrics approaches to the recent developments on spatial econometrics to model count data, in a Bayesian hierarchical setting. Considerable attention is paid to the inferential framework, necessary for structural consistent spatial econometric count models, incorporating spatial lag autocorrelation, to the corresponding estimation and testing procedures for different assumptions, to the constrains and implications embedded in the various specifications in the literature. This review combines insights from the classical spatial econometrics literature as well as from hierarchical modeling and analysis of spatial data, in order to look for new possible directions on the processing of count data, in a spatial hierarchical Bayesian econometric context.

Keywords: spatial data analysis, spatial econometrics, Bayesian hierarchical models, count data

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Authors: Amita Rana

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From the ancient to modern times, the nature of fitness activities has varied. We can choose any form of exercise that is suitable for our particular need. Watchers of fitness trends say that the road to better health is paved with new possibilities along with some old ones that are poised to make a comeback. Educated, certified and experienced fitness professionals; strength training; fitness programmes for older adults; exercise and weight loss; children and obesity; personal training; core training; group personal training; Zumba and other dance workouts; functional fitness; yoga; comprehensive health promotion programmes at worksite; boot-camp; outdoor activities; reaching new markets; spinning; sport-specific training; worker incentive programmes; wellness coaching; and physician referrals are among the fitness trends included in worldwide surveys. However, trends related to fitness in India could be the same or different. Hence, the present paper makes an attempt to analyze the latest fitness trends in India. A total of eighteen (18) surveys were shortlisted on the basis of their relevance to the present topic of study and were arranged in descending order of their chronology. Content analysis was done after the preliminary set of data collection, which formed the basis of a group of data. Further, frequency and percentage were used to statistically represent the data. It can be concluded from the analysis of data regarding recent fitness trends in India that yoga dominates the fitness activity list, followed by numerous other activities including running, Zumba and sh’bam, boot camp, boxing, kickboxing, cycling, swimming, TRX, ass-pocalypse, ballet, biking, bokwa fitness, dance-iso-bic, masala bhangra, outdoor activities, pilates, planks, push-ups, sofa workouts, stairs Workouts, tabata training, and twerking. The body weight/ gym-specified/ strength training as well as high intensity interval training dominate the preferred workouts; followed by mixed work-outs, cross training work-outs, express work-outs, functional fitness, natural body movements, personalized training, and stay-at-home workouts. General areas that featured in the latest fitness trends in India demonstrates that the fitness is making an impact on all sections of the society be it children, women, older adults, senior citizens, worksite fitness. Fitness is becoming the lifestyle of the masses. People are doing exercise for weight-loss, combining diet with exercising; prefer sweating, making groups participate in fitness activities and wellness programmes. Technology is another area which has a high impact on the lives of people. They are using wearable technology for workout tracking and following numerous mobile friendly apps.

Keywords: fitness, India, survey, trend

Procedia PDF Downloads 293

Authors: Gueidi Afef, Gharsellaoui Hamza, Ben Ahmed Samir

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This paper deals with the secret of the continual progression data that new data management solutions have been emerged: The NoSQL databases. They crossed several areas like personalization, profile management, big data in real-time, content management, catalog, view of customers, mobile applications, internet of things, digital communication and fraud detection. Nowadays, these database management systems are increasing. These systems store data very well and with the trend of big data, a new challenge’s store demands new structures and methods for managing enterprise data. The new intelligent machine in the e-learning sector, thrives on more data, so smart machines can learn more and faster. The robotics are our use case to focus on our test. The implementation of NoSQL for Robotics wrestle all the data they acquire into usable form because with the ordinary type of robotics; we are facing very big limits to manage and find the exact information in real-time. Our original proposed approach was demonstrated by experimental studies and running example used as a use case.

Keywords: NoSQL databases, database management systems, robotics, big data

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Authors: C. B. Le, V. N. Pham

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In modern data analysis, multi-source data appears more and more in real applications. Multi-source data clustering has emerged as a important issue in the data mining and machine learning community. Different data sources provide information about different data. Therefore, multi-source data linking is essential to improve clustering performance. However, in practice multi-source data is often heterogeneous, uncertain, and large. This issue is considered a major challenge from multi-source data. Ensemble is a versatile machine learning model in which learning techniques can work in parallel, with big data. Clustering ensemble has been shown to outperform any standard clustering algorithm in terms of accuracy and robustness. However, most of the traditional clustering ensemble approaches are based on single-objective function and single-source data. This paper proposes a new clustering ensemble method for multi-source data analysis. The fuzzy optimized multi-objective clustering ensemble method is called FOMOCE. Firstly, a clustering ensemble mathematical model based on the structure of multi-objective clustering function, multi-source data, and dark knowledge is introduced. Then, rules for extracting dark knowledge from the input data, clustering algorithms, and base clusterings are designed and applied. Finally, a clustering ensemble algorithm is proposed for multi-source data analysis. The experiments were performed on the standard sample data set. The experimental results demonstrate the superior performance of the FOMOCE method compared to the existing clustering ensemble methods and multi-source clustering methods.

Keywords: clustering ensemble, multi-source, multi-objective, fuzzy clustering

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Authors: Meimei Zheng

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Product personalization could not only bring new profits to companies but also provide the direction of long-term development for companies. However, the characteristics of personalized product cause some new problems. This paper investigates how companies make decisions on the supply of personalized products when facing different customer attitudes to personalized product and service, constraints due to limited capacity and updates of personalized demand information. This study will provide optimal decisions for companies to develop personalized markets, resulting in promoting business transformation and improving business competitiveness.

Keywords: demand forecast updating, limited capacity, personalized products, optimization

Procedia PDF Downloads 234

Authors: Eui-Jin Kim, Hasik Lee, Su-Jin Park, Dong-Kyu Kim

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Smart-card data are expected to provide information on activity pattern as an alternative to conventional person trip surveys. The focus of this study is to propose a method for training the person trip surveys to supplement the smart-card data that does not contain the purpose of each trip. We selected only available features from smart card data such as spatiotemporal information on the trip and geographic information system (GIS) data near the stations to train the survey data. XGboost, which is state-of-the-art tree-based ensemble classifier, was used to train data from multiple sources. This classifier uses a more regularized model formalization to control the over-fitting and show very fast execution time with well-performance. The validation results showed that proposed method efficiently estimated the trip purpose. GIS data of station and duration of stay at the destination were significant features in modeling trip purpose.

Keywords: activity pattern, data fusion, smart-card, XGboost

Procedia PDF Downloads 220

Authors: Haojie Wang, Xun Li, Rui Yin

Abstract:

In order to solve the memorization overfitting in the model-agnostic meta-learning MAML algorithm, a method of generating mutually exclusive tasks based on data augmentation is proposed. This method generates a mutex task by corresponding one feature of the data to multiple labels so that the generated mutex task is inconsistent with the data distribution in the initial dataset. Because generating mutex tasks for all data will produce a large number of invalid data and, in the worst case, lead to an exponential growth of computation, this paper also proposes a key data extraction method that only extract part of the data to generate the mutex task. The experiments show that the method of generating mutually exclusive tasks can effectively solve the memorization overfitting in the meta-learning MAML algorithm.

Keywords: mutex task generation, data augmentation, meta-learning, text classification.

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Authors: Milind Chaudhari, Suhail Balasinor

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Due to massive deforestation and an ever-increasing population, the organic content of the soil is depleting at a much faster rate. Due to this, there is a big chance that the entire food production in the world will drop by 40% in the next two decades. Vertical farming can help in aiding food production by leveraging big data and cloud computing to ensure plants are grown naturally by providing the optimum nutrients sunlight by analyzing millions of data points. This paper outlines the most important parameters in vertical farming and how a combination of big data and AI helps in calculating and analyzing these millions of data points. Finally, the paper outlines how different organizations are controlling the indoor environment by leveraging big data in enhancing food quantity and quality.

Keywords: big data, IoT, vertical farming, indoor farming

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Authors: A. Anis, W. Bekheet, A. El Hakim

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Implementing a Road Safety Management System (SMS) in a crowded developing country such as Egypt is a necessity. Beginning a sustainable SMS requires a comprehensive reliable data system for all information pertinent to road crashes. In this paper, a survey for the available data in Egypt and validating it for using in an SMS in Egypt. The research provides some missing data, and refer to the unavailable data in Egypt, looking forward to the contribution of the scientific society, the authorities, and the public in solving the problem of missing or unreliable crash data. The required data for implementing an SMS in Egypt are divided into three categories; the first is available data such as fatality and injury rates and it is proven in this research that it may be inconsistent and unreliable, the second category of data is not available, but it may be estimated, an example of estimating vehicle cost is available in this research, the third is not available and can be measured case by case such as the functional and geometric properties of a facility. Some inquiries are provided in this research for the scientific society, such as how to improve the links among stakeholders of road safety in order to obtain a consistent, non-biased, and reliable data system.

Keywords: road safety management system, road crash, road fatality, road injury

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Authors: Oualid Walid Ben Ali

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Big Data has become one of the buzzwords today. The recent explosion of digital data has led the organization, either private or public, to a new era towards a more efficient decision making. At some point, business decided to use that concept in order to learn what make their clients tick with phrases like ‘sales funnel’ analysis, ‘actionable insights’, and ‘positive business impact’. So, it stands to reason that Big Data was viewed through green (read: money) colored lenses. Somewhere along the line, however someone realized that collecting and processing data doesn’t have to be for business purpose only, but also could be used for other purposes to assist law enforcement or to improve policing or in road safety. This paper presents briefly, how Big Data have been used in the fields of policing order to improve the decision making process in the daily operation of the police. As example, we present a big-data driven system which is sued to accurately dispatch the patrol cars in a geographic environment. The system is also used to allocate, in real-time, the nearest patrol car to the location of an incident. This system has been implemented and applied in the Emirate of Abu Dhabi in the UAE.

Keywords: big data, big data analytics, patrol car allocation, dispatching, GIS, intelligent, Abu Dhabi, police, UAE

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Authors: Baker Ssekitto, Ambrose Mbogo

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The study reveals that indeed agriculture employs over 70% of Uganda’s population, of which majority are youth and women. The study further reveals that over 70% of the farmers are smallholder farmers based in rural areas, whose operations are greatly affected by; climate change, weak digital skills, limited access to productivity knowledge along value chains, limited access to quality farm inputs, weak logistics systems, limited access to quality extension services, weak business intelligence, limited access to quality markets among others. It finds that the emerging 4th industrial revolution powered by artificial intelligence, 5G and data science will provide possibilities of addressing some of these challenges. Furthermore, the study finds that despite rapid development of ICT4Agric Innovation, their uptake is constrained by a number of factors including; limited awareness of these innovations, low internet and smart phone penetration especially in rural areas, lack of appropriate digital skills, inappropriate programmes implementation models which are project and donor driven, limited articulation of value addition to various stakeholders among others. Majority of farmers and other value chain actors lacked knowledge and skills to harness the power of ICTs, especially their application of ICTs in monitoring and evaluation on quality of service in the extension system and farm level processes.

Keywords: artificial intelligence, productivity, ICT4agriculture, value chain, logistics

Procedia PDF Downloads 62

Authors: Aisha M. Memon, Arabella Bhutto, Zahid A. Memon, Adnan Pitafi

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This study aims to identify the existing and non-existing elements in the entrepreneurial ecosystem which include finance, institutions, laws and regulations, human capital, culture, and markets, to measure the level of effectiveness of existing elements and to develop recommendations for improving the ecosystem to facilitate the women entrepreneurs in Jamshoro, Pakistan. The nature of this study is qualitative. Data were drawn from 25 in-depth, semi-structured interviews and a focus group discussion with women entrepreneurs in rural Jamshoro, Pakistan. The findings show the lack of awareness and knowledge among women entrepreneurs about available financial resources, lack of knowledge about laws, an absence of familial and societal support for women in accessing the entrepreneurial ecosystem, the absence of business and innovation enablers in rural areas, communication gaps, and unskilled human capital. The study found that institutions like non-for-profit organizations are playing an active role in the growth of women entrepreneurs. The existing entrepreneurial ecosystem in Jamshoro can be improved through culturally sensitive coordinated approach, interventions aimed at increasing awareness about the resources, promoting an understanding about the laws and regulations, making business enablers more effective, establishing public-private partnerships, and providing the women entrepreneurs easy access to market and financial resources.

Keywords: entrepreneurship, entrepreneurship ecosystem, Pakistan, women entrepreneurs

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Authors: Jamal A. Mayouf, Hashim Salih Al Bayati

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Green tea is one of the most common drinks in all cities of Libyan. Heavy metal contents such as cadmium (Cd), lead (Pb), nickel (Ni) and zinc (Zn) were determined in four green tea samples collected from Libyan market and their tea infusions by using atomic emission spectrophotometry after acid digestion. The results obtained indicate that the concentrations of Cd, Pb, Ni, and Zn in tea infusions samples ranged from 0.07-0.12, 0.19-0.28, 0.09-0.15, 0.18-0.43 mg/l after boiling for 5 min., 0.06-0.08, 0.18-0.23, 0.08-0.14, 0.17-0.27 mg/l after boiling for 10 min., 0.07-0.11, 0.18-0.24, 0.08-0.14, 0.21-0.34 mg/l after boiling for 15 min. respectively. On the other hand, the concentrations of the same element mentioned above obtained in tea leaves ranged from 6.0-18.0, 36.0-42.0, 16.0-20.0, 44.0-132.0 mg/kg respectively. The concentrations of Cd, Pb, Ni and Zn in tea leaves samples were higher than Prevention of Food Adulteration (PFA) limit and World Health Organization(WHO) permissible limit.

Keywords: tea, infusion, metals, Libya

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Authors: Xu Du, Aparna S. Varde

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In this research, we propose to conduct diagnostic and predictive analysis about the key factors and consequences of urban population relocation. To achieve this goal, urban simulation models extract the urban development trends as land use change patterns from a variety of data sources. The results are treated as part of urban big data with other information such as population change and economic conditions. Multiple data mining methods are deployed on this data to analyze nonlinear relationships between parameters. The result determines the driving force of population relocation with respect to urban sprawl and urban sustainability and their related parameters. Experiments so far reveal that data mining methods discover useful knowledge from the multicity urban data. This work sets the stage for developing a comprehensive urban simulation model for catering to specific questions by targeted users. It contributes towards achieving sustainability as a whole.

Keywords: data mining, environmental modeling, sustainability, urban planning

Procedia PDF Downloads 274

Authors: Cupian

Abstract:

The expansion of Islamic banking industry seems to emphasize the banking competition in Indonesia where conventional and Islamic banks coexist. In addition, the 2007/2008 global financial crisis and deregulation have the effect on competitive conditions in Islamic banking market. In this context, this study aims at investigating competitive conditions and market power of Islamic banks in Indonesia using firm level data over the period 2006-2013. The study also attempts to identify the factors that represent the power of banking market to better study the degree of competition in this banking industry. Using samples of 27 Islamic commercial banks, the study uses a variety of structural and non-structural measures related to the traditional approach and the new empirical approach of the industrial organization (NEIO). The methodology is based on the set of measures of the competition and market power. The first measure is a set of concentration ratios (CR4) and Herfindahl-Hirschman index (HHI).The second measures are the Panzar and Ross H-statistic and the Lerner index based on econometric estimations with the aim of evaluating the market structure and measuring its power in terms of price setting. The results of the competition analysis suggest that the Islamic banking markets in Indonesia cannot be characterized by the bipolar cases of either perfect competition or monopoly over 2006-2013. That is, banks earned their revenues operating under conditions of monopolistic competition in that period. Overall, Islamic banks in Indonesia operate in a relatively less competitive environment or in high market power. It is also indicated that Islamic bank that hope to achieve higher returns should operate in the competitive environment.

Keywords: bank competition, islamic banks, market structure, profitability

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