Search results for: NFC data exchange format

Authors: P. Jayashree, S. Rajkumar

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With social networks and smart devices generating a multitude of data, effective data management is the need of the hour for networks and cloud applications. Some applications need effective storage while some other applications need effective communication over networks and data reduction comes as a handy solution to meet out both requirements. Most of the data compression techniques are based on data statistics and may result in either lossy or lossless data reductions. Though lossy reductions produce better compression ratios compared to lossless methods, many applications require data accuracy and miniature details to be preserved. A variety of data compression algorithms does exist in the literature for different forms of data like text, image, and multimedia data. In the proposed work, a generic progressive compression algorithm, based on probabilistic encoding, called PEINS is projected as an enhancement over irrational number stored coding technique to cater to storage issues of increasing data volumes as a cost effective solution, which also offers data security as a secondary outcome to some extent. The proposed work reveals cost effectiveness in terms of better compression ratio with no deterioration in compression time.

Keywords: compression ratio, generic compression, irrational number storage, probabilistic encoding

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Authors: Femi Elegbeleye, Omobayo Esan, Muienge Mbodila, Patrick Bowe

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This paper focused on cost effective storage architecture using fog and cloud data storage gateway and presented the design of the framework for the data privacy model and data analytics framework on a real-time analysis when using machine learning method. The paper began with the system analysis, system architecture and its component design, as well as the overall system operations. The several results obtained from this study on data privacy model shows that when two or more data privacy model is combined we tend to have a more stronger privacy to our data, and when fog storage gateway have several advantages over using the traditional cloud storage, from our result shows fog has reduced latency/delay, low bandwidth consumption, and energy usage when been compare with cloud storage, therefore, fog storage will help to lessen excessive cost. This paper dwelt more on the system descriptions, the researchers focused on the research design and framework design for the data privacy model, data storage, and real-time analytics. This paper also shows the major system components and their framework specification. And lastly, the overall research system architecture was shown, its structure, and its interrelationships.

Keywords: IoT, fog, cloud, data analysis, data privacy

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Authors: Ezeabasili Chibuike Patrick

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The complex situation of construction industries in Nigeria and the risk of failures involved includes cost overrun, time overrun, Corruption, Government influence, Subcontractor challenges, Political influence and Instability, Cultural differences, Human resources deficiencies, cash flow Challenges, foreign exchange issues, inadequate design, Safety, low productivity, late payment, Quality control issues, project management issues, Environmental issues, Force majeure Competition amongst others has made the industry prone to risk and failures. Good project management remains effective in improving decision-making, which minimizes these risk events. This study was done to address these project risks and good decision-making to avert them. A mixed-method approach to research was used to do this study. Data collected by questionnaires and interviews on thirty-two (32) construction professionals was used in analyses to aid the knowledge and management of risks that were identified. The study revealed that there is no good risk management expertise in Nigeria. Also, that the economic/political situation and the recent COVID-19 pandemic has added to the risk and poor management strategies. The contingency theory and cost has therefore surfaced to be the most strategic management method used to reduce these risk issues and they seem to be very effective.

Keywords: strategies, risk management, contingency theory, Nigeria

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Authors: Maja Ruzic-Baf, Mirjana Radetic-Paic

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The use of computers by children has many positive aspects, including the development of memory, learning methods, problem-solving skills and the feeling of one’s own competence and self-confidence. Playing on line video games can encourage hanging out with peers having similar interests as well as communication; it develops coordination, spatial relations and presentation. On the other hand, the Internet enables quick access to different information and the exchange of experiences. How kids use computers and what the negative effects of this can be depends on various factors. ICT has improved and become easy to get for everyone. In the past 12 years so many video games has been made even to that level that some of them are free to play. Young people, even some adults, had simply start to forget about the real outside world because in that other, digital world, they have found something that makes them feal more worthy as a man. This article present the use of ICT, forms of behavior and addictions to on line video games. The use of computers by children has many positive aspects, including the development of memory, learning methods, problem-solving skills and the feeling of one’s own competence and self-confidence. Playing on line video games can encourage hanging out with peers having similar interests as well as communication; it develops coordination, spatial relations and presentation. On the other hand, the Internet enables quick access to different information and the exchange of experiences. How kids use computers and what the negative effects of this can be depends on various factors. ICT has improved and become easy to get for everyone. In the past 12 years so many video games has been made even to that level that some of them are free to play. Young people, even some adults, had simply start to forget about the real outside world because in that other, digital world, they have found something that makes them feal more worthy as a man. This article present the use of ICT, forms of behavior and addictions to on line video games.

Keywords: addiction to video games, behaviour, ICT, young people

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Authors: Nordila Ahmad, Thamer Mohammad, Bruce W. Melville, Zuliziana Suif

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Current methods for predicting local scour at wide bridge piers, were developed on the basis of laboratory studies and very limited scour prediction were tested with field data. Laboratory wide pier scour equation from previous findings with field data were presented. A wide range of field data were used and it consists of both live-bed and clear-water scour. A method for assessing the quality of the data was developed and applied to the data set. Three other wide pier-scour equations from the literature were used to compare the performance of each predictive method. The best-performing scour equation were analyzed using statistical analysis. Comparisons of computed and observed scour depths indicate that the equation from the previous publication produced the smallest discrepancy ratio and RMSE value when compared with the large amount of laboratory and field data.

Keywords: field data, local scour, scour equation, wide piers

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Authors: Sung Ryong Kim, Hyung Sup Han, Jae-Yup Kim

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Many engineering students feel uncomfortable in solving the industry related problems. There are many ways to strengthen the engineering student’s ability to solve the assigned problem when they get a job. Korea National University of Transportation has developed an industry-oriented undergraduate research program (URP). An URP program is designed for engineering students to provide an experience of solving a company’s research problem. The URP project is carried out for 6 months. Each URP team consisted of 1 company mentor, 1 professor, and 3-4 engineering students. A team of different majors is strongly encouraged to integrate different perspectives of multidisciplinary background. The corporate research projects proposed by companies are chosen by the major-related student teams. A company mentor gives the detailed technical background of the project to the students, and he/she also provides a basic data, raw materials and so forth. The company allows students to use the company's research equipment. An assigned professor has adjusted the project scope and level to the student’s ability after discussing with a company mentor. Monthly meeting is used to check the progress, to exchange ideas, and to help the students. It is proven as an effective engineering education program not only to provide an experience of company research but also to motivate the students in their course work. This program provides a premier interdisciplinary platform for undergraduate students to perform the practical challenges encountered in their major-related companies and it is especially helpful for students who want to get a job from a company that proposed the project.

Keywords: company mentor, industry oriented, interdisciplinary platform, undergraduate research program

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Authors: Inkyu Kim, SangMan Moon

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This IEEE 802.11b protocol provides up to 11Mbps data rate, whereas aerospace industry wants to seek higher data rate COTS data link system in the UAV. The Total Maximum Throughput (TMT) and delay time are studied on many researchers in the past years This paper provides theoretical data throughput performance of UAV formation flight data link using the existing 802.11b performance theory. We operate the UAV formation flight with more than 30 quad copters with 802.11b protocol. We may be predicting that UAV formation flight numbers have to bound data link protocol performance limitations.

Keywords: UAV datalink, UAV formation flight datalink, UAV WLAN datalink application, UAV IEEE 802.11b datalink application

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Authors: Radoslav Židek, Veronika Šidlová, Radovan Kasarda, Birgit Fuerst-Waltl

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Machine learning represents a set of topics dealing with the creation and evaluation of algorithms that facilitate pattern recognition, classification, and prediction, based on models derived from existing data. The data can present identification patterns which are used to classify into groups. The result of the analysis is the pattern which can be used for identification of data set without the need to obtain input data used for creation of this pattern. An important requirement in this process is careful data preparation validation of model used and its suitable interpretation. For breeders, it is important to know the origin of animals from the point of the genetic diversity. In case of missing pedigree information, other methods can be used for traceability of animal´s origin. Genetic diversity written in genetic data is holding relatively useful information to identify animals originated from individual countries. We can conclude that the application of data mining for molecular genetic data using supervised learning is an appropriate tool for hypothesis testing and identifying an individual.

Keywords: genetic data, Pinzgau cattle, supervised learning, machine learning

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Authors: Nidhi Gopal

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Routing is the process of moving a packet of data from source to destination and enables messages to pass from one computer to another and eventually reach the target machine. A router is a networking device that forwards data packets between computer networks. It is connected to two or more data lines from different networks (as opposed to a network switch, which connects data lines from one single network). This paper mainly emphasizes upon the study of router device, its top level architecture, and how various sub-modules of router i.e. Register, FIFO, FSM and Synchronizer are synthesized, and simulated and finally connected to its top module.

Keywords: data packets, networking, router, routing

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Authors: Shreyas Srinivas Rangan, Jurgis Porins

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The internet traffic has increased exponentially due to the high demand for data rates by the users, and the constantly increasing metro networks and access networks are focused on improving the maximum transmit distance of the long-reach optical networks. One of the common methods to improve the maximum transmit distance of the long-reach optical networks at the component level is to use broadband optical amplifiers. The Erbium Doped Fiber Amplifier (EDFA) provides high amplification with low noise figure but due to the characteristics of EDFA, its operation is limited to C-band and L-band. In contrast, the Raman amplifier exhibits a wide amplification spectrum, and negative noise figure values can be achieved. To obtain such results, high powered pumping sources are required. Operating Raman amplifiers with such high-powered optical sources may cause fire hazards and it may damage the optical system. In this paper, we implement a hybrid optical amplifier configuration. EDFA and Raman amplifiers are used in this hybrid setup to combine the advantages of both EDFA and Raman amplifiers to improve the reach of the system. Using this setup, we analyze the maximum transmit distance of the network by obtaining a correlation diagram between the length of the single-mode fiber (SMF) and the Bit Error Rate (BER). This hybrid amplifier configuration is implemented in a Wavelength Division Multiplexing (WDM) system with a BER of 10⁻⁹ by using NRZ modulation format, and the gain uniformity noise ratio (signal-to-noise ratio (SNR)), the efficiency of the pumping source, and the optical signal gain efficiency of the amplifier are studied experimentally in a mathematical modelling environment. Numerical simulations were implemented in RSoft OptSim simulation software based on the nonlinear Schrödinger equation using the Split-Step method, the Fourier transform, and the Monte Carlo method for estimating BER.

Keywords: Raman amplifier, erbium doped fibre amplifier, bit error rate, hybrid optical amplifiers

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Authors: Sergey Kopysov, Nikita Nedozhogin, Leonid Tonkov

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The article presents a parallel iterative solver for large sparse linear systems which can be used on a heterogeneous platform. Traditionally, the problem of solving linear systems does not scale well on multi-CPU/multi-GPUs clusters. For example, most of the attempts to implement the classical conjugate gradient method were at best counted in the same amount of time as the problem was enlarged. The paper proposes the pipelined variant of the conjugate gradient method (PCG), a formulation that is potentially better suited for hybrid CPU/GPU computing since it requires only one synchronization point per one iteration instead of two for standard CG. The standard and pipelined CG methods need the vector entries generated by the current GPU and other GPUs for matrix-vector products. So the communication between GPUs becomes a major performance bottleneck on multi GPU cluster. The article presents an approach to minimize the communications between parallel parts of algorithms. Additionally, computation and communication can be overlapped to reduce the impact of data exchange. Using the pipelined version of the CG method with one synchronization point, the possibility of asynchronous calculations and communications, load balancing between the CPU and GPU for solving the large linear systems allows for scalability. The algorithm is implemented with the combined use of technologies: MPI, OpenMP, and CUDA. We show that almost optimum speed up on 8-CPU/2GPU may be reached (relatively to a one GPU execution). The parallelized solver achieves a speedup of up to 5.49 times on 16 NVIDIA Tesla GPUs, as compared to one GPU.

Keywords: conjugate gradient, GPU, parallel programming, pipelined algorithm

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Authors: Julius Onyancha, Valentina Plekhanova

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One of the significant issues facing web users is the amount of noise in web data which hinders the process of finding useful information in relation to their dynamic interests. Current research works consider noise as any data that does not form part of the main web page and propose noise web data reduction tools which mainly focus on eliminating noise in relation to the content and layout of web data. This paper argues that not all data that form part of the main web page is of a user interest and not all noise data is actually noise to a given user. Therefore, learning of noise web data allocated to the user requests ensures not only reduction of noisiness level in a web user profile, but also a decrease in the loss of useful information hence improves the quality of a web user profile. Noise Web Data Learning (NWDL) tool/algorithm capable of learning noise web data in web user profile is proposed. The proposed work considers elimination of noise data in relation to dynamic user interest. In order to validate the performance of the proposed work, an experimental design setup is presented. The results obtained are compared with the current algorithms applied in noise web data reduction process. The experimental results show that the proposed work considers the dynamic change of user interest prior to elimination of noise data. The proposed work contributes towards improving the quality of a web user profile by reducing the amount of useful information eliminated as noise.

Keywords: web log data, web user profile, user interest, noise web data learning, machine learning

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Authors: Sorin Muraru

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Computational generation of carbon nanostructures is still a very demanding process. This work provides an alternative to manual molecular modeling through an algorithm meant to automate the design of such structures. Specifically, carbon nanochimneys are obtained through the bonding of a carbon nanotube with the smaller edge of an open carbon nanocone. The methods of connection rely on mathematical, geometrical and chemical properties. Non-hexagonal rings are used in order to perform the correct bonding of dangling bonds. Once obtained, they are useful for thermal transport, gas storage or other applications such as gas separation. The carbon nanochimneys are meant to produce a less steep connection between structures such as the carbon nanotube and graphene sheet, as in the pillared graphene, but can also provide functionality on its own. The method relies on connecting dangling bonds at the edges of the two carbon nanostructures, employing the use of two different types of auxiliary structures on a case-by-case basis. The code is implemented in Python 3.7 and generates an output file in the .pdb format containing all the system’s coordinates. Acknowledgment: This work was supported by a grant of the Executive Agency for Higher Education, Research, Development and innovation funding (UEFISCDI), project number PN-III-P1-1.1-TE-2016-24-2, contract TE 122/2018.

Keywords: carbon nanochimneys, computational, carbon nanotube, carbon nanocone, molecular modeling, carbon nanostructures

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Authors: Zeba Mahmood

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The modern business organizations are adopting technological advancement to achieve competitive edge and satisfy their consumer. The development in the field of Information technology systems has changed the way of conducting business today. Business operations today rely more on the data they obtained and this data is continuously increasing in volume. The data stored in different locations is difficult to find and use without the effective implementation of Data mining and Knowledge management techniques. Organizations who smartly identify, obtain and then convert data in useful formats for their decision making and operational improvements create additional value for their customers and enhance their operational capabilities. Marketers and Customer relationship departments of firm use Data mining techniques to make relevant decisions, this paper emphasizes on the identification of different data mining and Knowledge management techniques that are applied to different business industries. The challenges and issues of execution of these techniques are also discussed and critically analyzed in this paper.

Keywords: knowledge, knowledge management, knowledge discovery in databases, business, operational, information, data mining

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Authors: Geetanjali Sharma

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There are always provincial variations which deserve more detailed treatment. Before the arrival of modern era, geography and cultural homogeneity were determining factors of human habitat and migration. Boundaries as if we see them, did not exist earlier. The connectivity of the world was also different as of now. The reinforcement of the old silk route will improve economic cooperation and connectivity between Asian, European and African countries, but obviously, it is designed to improve China’s geopolitical and geostrategic position in the world. The paper is based on the secondary sources of data. Analytical and historical approach has been used to clarify the ties between the old silk routes and new One-Belt-One-Road initiative China. The paper begins with an explanation of the historical background of the old Silk Route, its origin and development, trailed by an analysis of latest declarations by the Chinese leaders to revive it. It also discusses the impacts of this initiative on India’s economy and cultural exchange between associated regions. Lastly, the paper sums up the findings and suggestions for keeping a balance between the security and economic relationship between the countries. It concludes that the silk route is an effort in commencing a ‘grand strategy’ for global trade and cooperation with hidden objectives of China to increase the investment of China in other continents as well. The revival of silk route may prove to be a very helpful in reinforcing cooperation and raising it to a new level of economic establishments. However, China has yet to promote the much-needed political and strategic trust.

Keywords: OBOR (One-Belt-One-Road), geopolitics, economic relation, security concerns

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Authors: Adarsh Shroff

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Big data is a collection of dataset so large and complex that it becomes difficult to process using data base management tools. To perform operations like search, analysis, visualization on big data by using data mining; which is the process of extraction of patterns or knowledge from large data set. In recent years, the data mining applications become stale and obsolete over time. Incremental processing is a promising approach to refreshing mining results. It utilizes previously saved states to avoid the expense of re-computation from scratch. This project uses i2MapReduce, an incremental processing extension to Map Reduce, the most widely used framework for mining big data. I2MapReduce performs key-value pair level incremental processing rather than task level re-computation, supports not only one-step computation but also more sophisticated iterative computation, which is widely used in data mining applications, and incorporates a set of novel techniques to reduce I/O overhead for accessing preserved fine-grain computation states. To optimize the mining results, evaluate i2MapReduce using a one-step algorithm and three iterative algorithms with diverse computation characteristics for efficient mining.

Keywords: big data, map reduce, incremental processing, iterative computation

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Authors: Marta Ribo, Ian D. Goodwin, Thomas Mortlock, Phil O’Brien

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Coastal behavior is best investigated using a sediment budget approach, based on the identification of sediment sources and sinks. Grain size distribution over the New South Wales (NSW) continental shelf has been widely characterized since the 1970’s. Coarser sediment has generally accumulated on the outer shelf, and/or nearshore zones, with the latter related to the presence of nearshore reef and bedrocks. The central part of the NSW shelf is characterized by the presence of fine sediments distributed parallel to the coastline. This study presents new grain size distribution maps along the NSW continental shelf, built using all available NSW and Commonwealth Government holdings. All available seabed bathymetric data form prior projects, single and multibeam sonar, and aerial LiDAR surveys were integrated into a single bathymetric surface for the NSW continental shelf. Grain size information was extracted from the sediment sample data collected in more than 30 studies. The information extracted from the sediment collections varied between reports. Thus, given the inconsistency of the grain size data, a common grain size classification was her defined using the phi scale. The new sediment distribution maps produced, together with new detailed seabed bathymetric data enabled us to revise the delineation of sediment compartments to more accurately reflect the true nature of sediment movement on the inner shelf and nearshore. Accordingly, nine primary mega coastal compartments were delineated along the NSW coast and shelf. The sediment compartments are bounded by prominent nearshore headlands and reefs, and major river and estuarine inlets that act as sediment sources and/or sinks. The new sediment grain size distribution was used as an input in the morphological modelling to quantify the sediment transport patterns (and indicative rates of transport), used to investigate sand supply rates and processes from the lower shoreface to the NSW coast. The rate of sand supply to the NSW coast from deep water is a major uncertainty in projecting future coastal response to sea-level rise. Offshore transport of sand is generally expected as beaches respond to rising sea levels but an onshore supply from the lower shoreface has the potential to offset some of the impacts of sea-level rise, such as coastline recession. Sediment exchange between the lower shoreface and sub-aerial beach has been modelled across the south, central, mid-north and far-north coast of NSW. Our model approach is that high-energy storm events are the primary agents of sand transport in deep water, while non-storm conditions are responsible for re-distributing sand within the beach and surf zone.

Keywords: New South Wales coast, off-shore transport, sand supply, sediment distribution maps

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Authors: Jerry Q. Cheng

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Currently, in analyzing large-scale recurrent event data, there are many challenges such as memory limitations, unscalable computing time, etc. In this research, a divide-and-conquer method is proposed using parametric frailty models. Specifically, the data is randomly divided into many subsets, and the maximum likelihood estimator from each individual data set is obtained. Then a weighted method is proposed to combine these individual estimators as the final estimator. It is shown that this divide-and-conquer estimator is asymptotically equivalent to the estimator based on the full data. Simulation studies are conducted to demonstrate the performance of this proposed method. This approach is applied to a large real dataset of repeated heart failure hospitalizations.

Keywords: big data analytics, divide-and-conquer, recurrent event data, statistical computing

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Authors: Wonder Ngezimana, Benjamin Alex Madzivire

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As new public universities are being applauded for being promulgated in Zimbabwe, there is need for comprehensive plan for ensuring sustainable competitive advantages in their niche mandated areas. Unhealthy competition between university faculties for enrolment hinders growth of the newly established universities faculties, especially in the agricultural sciences related disciplines. Blue ocean metaphor is based on creation of competitor-free market unlike 'red oceans', which are well explored and crowded with competitors. This study seeks to explore the potential contribution of blue oceans strategy (BOS) for growth of universities with bias towards faculties of agriculture in public universities in Zimbabwe. Case studies with agricultural sciences related disciplines were selected across three universities for interviewing. Data was collected through 10 open ended questions on academics in different management positions within university faculties of agriculture. Summative analysis was thereafter used during coding and interpretation of the data. Study findings show that there are several important elements for making offerings more comprehendible towards fostering faculty growth and performance with bias towards student enrolment. The results points towards BOS form of value innovations with various elements to consider in faculty offerings. To create valued innovation beyond the red oceans, the cases in this study have to be modelled to foster changes in enrolment, modes of delivery, certification, being research oriented with excellence in teaching, ethics, service to the community and entrepreneurship. There is, therefore, need to rethink strategy towards reshaping inclusive enrolment, industry relevance, affiliations, lifelong learning, sustainable student welfare, ubuntu, exchange programmes, research excellence, alumni support and entrepreneurship. Innovative strategic collaborations and partnerships, anchored on technology boost the strategic offerings henceforth leveraging on various offerings in this study. Areas of further study include the amplitude of blue oceans shown in the university faculty offerings and implementation strategies of BOS.

Keywords: blue oceans strategy, collaborations, faculty offerings, value innovations

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Authors: Ashiff Khan, A. Seetharaman, Abhijit Dasgupta

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The new era of big data (BD) is influencing chemical industries tremendously, providing several opportunities to reshape the way they operate and help them shift towards intelligent manufacturing. Given the availability of free software and the large amount of real-time data generated and stored in process plants, chemical industries are still in the early stages of big data adoption. The industry is just starting to realize the importance of the large amount of data it owns to make the right decisions and support its strategies. This article explores the importance of professional competencies and data science that influence BD in chemical industries to help it move towards intelligent manufacturing fast and reliable. This article utilizes a literature review and identifies potential applications in the chemical industry to move from conventional methods to a data-driven approach. The scope of this document is limited to the adoption of BD in chemical industries and the variables identified in this article. To achieve this objective, government, academia, and industry must work together to overcome all present and future challenges.

Keywords: chemical engineering, big data analytics, industrial revolution, professional competence, data science

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Authors: Jessica Gladden

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Anxiety remains one of the most common mental health disorders in the United States. Many university students report having a high level of anxiety, with additional life stressors that might include being away from home for the first time, being around unfamiliar people, having new expectations placed on them, and often have financial struggles. Universities have the ability and opportunity to form programs that can involve students with activities that reduce stress and teach coping skills. This research includes one example of using a somatic based group format of yoga to teach these skills and assist students in applying these strategies to their daily lives. This study compared a group of 17 students participating in weekly yoga classes to 34 students who did not attend the program. The students who attended the program reported a larger reduction of anxiety on both the BAI and GAD-7 than the control group, and verbally reported additional benefits in relaxation and coping skills. This presentation will review the results of the program as well as detailing the steps taken in creating a yoga program for university students with stress and anxiety. This will include a discussion on the components of trauma-sensitive yoga and the concerns and strategies to consider when developing a program for students.

Keywords: yoga, trauma-sensitive yoga, anxiety, students

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Authors: Augustar Omoze Ehighalua, Itotenaan Henry Ogiri

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As a mono-product economy, Nigeria relies largely on oil revenues for its foreign exchange earnings and the exploration activities of firms operating in the Niger Delta region have left in its wake tales of environmental degradation, poverty and misery. This, no doubt, have created corporate social responsibility issues in the region. The focus of this research is the critical evaluation of the ethical response to Corporate Social Responsibility (CSR) practice by firms operating in Nigeria Delta Swamplands. While CSR is becoming more popular in developed society with effective practice guidelines and reporting benchmark, there is a relatively low level of awareness and selective applicability of existing international guidelines to effectively support CSR practice in Nigeria. This study, haven identified the lack of CSR institutional framework attempts to develop an ethically-driven CSR transparency benchmark laced within a regulatory framework based on international best practices. The research adopts a qualitative methodology and makes use of primary data collected through semi-structured interviews conducted across the six core states of the Niger Delta Region. More importantly, the study adopts an inductive, interpretivist philosophical paradigm that reveal deep phenomenological insights into what local communities, civil society and government officials consider as good ethical benchmark for responsible CSR practice by organizations. The institutional theory provides for the main theoretical foundation, complemented by the stakeholder and legitimacy theories. The Nvivo software was used to analyze the data collected. This study shows that ethical responsibility is lacking in CSR practice by firms in the Niger Delta Region of Nigeria. Furthermore, findings of the study indicate key issues of environmental, health and safety, human rights, and labour as fundamental in developing an effective CSR practice guideline for Nigeria. The study has implications for public policy formulation as well as managerial perspective.

Keywords: corporate social responsibility, CSR, ethics, firms, Niger-Delta Swampland, Nigeria

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Authors: YangHui

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Foreign teachers play an important role in the process of internationalization of higher education in China. Based on the method of literature analysis, firstly study the contents about the mechanism of the foreign teachers’ administration in our country, then secondly analyze the main barriers of the foreign teacher’s administration mechanism. Finally, it is suggested that the international exchange department in universities should constantly improve the employment mechanism, training mechanism, appraisal mechanism and incentive mechanism to promote the internationalization of higher education.

Keywords: internationalization of higher education, mechanism, administration of foreign teachers, colleges and universities, China

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Authors: M. Sumana, K. S. Hareesha

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Secure computations are essential while performing privacy preserving data mining. Distributed privacy preserving data mining involve two to more sites that cannot pool in their data to a third party due to the violation of law regarding the individual. Hence in order to model the private data without compromising privacy and information loss, secure multiparty computations are used. Secure computations of product, mean, variance, dot product, sigmoid function using the additive and multiplicative homomorphic property is discussed. The computations are performed on vertically partitioned data with a single site holding the class value.

Keywords: homomorphic property, secure product, secure mean and variance, secure dot product, vertically partitioned data

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Authors: Gabriela Teodorescu, Ioana Daniela Dulama

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In an ever-changing society, the education system needs to constantly evolve to meet market demands. During its 30 years of existence, Valahia University of Targoviste (VUT) tried to offer its students a series of teaching-learning schemes that would prepare them for a remarkable career. In VUT, the achievement of performance through innovation can be analyzed by reference to several key indicators (i.e., university climate, university resources, and innovative methods applied to classes), but it is possible to differentiate between activities in the classic format: participate to courses; interactive seminars and tutorials; laboratories, workshops, project-based learning; entrepreneurial activities, through simulated enterprises; mentoring activities. Thus, VUT has implemented over time a series of schemes and projects based on innovation and entrepreneurship, and in this paper, some of them will be briefly presented. All these schemes were implemented by facilitating an effective dialog with students and the opportunity to listen to their views at all levels of the University and in all fields of study, as well as by developing a partnership with students to set out priority areas. VUT demonstrates innovation and entrepreneurial capacity through its new activities for higher education, which will attract more partnerships and projects dedicated to students.

Keywords: Romania, project-based learning, entrepreneurial activities, simulated enterprises

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Authors: Mishak Rahul, Naveen Kumar, Bharath Kumar

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Conceived as a high-end engine to revolutionise sustainable agri-food production, the intelligent crop circle (ICC) aims to incorporate the Internet of Things (IoT), blockchain technology and artificial intelligence (AI) to bolster resource efficiency and prevent waste, increase the volume of production and bring about sustainable solutions with long-term ecosystem conservation as the guiding principle. The operating principle of the ICC relies on bringing together multidisciplinary bottom-up collaborations between producers, researchers and consumers. Key elements of the framework include IoT-based smart sensors for sensing soil moisture, temperature, humidity, nutrient and air quality, which provide short-interval and timely data; blockchain technology for data storage on a private chain, which maintains data integrity, traceability and transparency; and AI-based predictive analysis, which actively predicts resource utilisation, plant growth and environment. This data and AI insights are built into the ICC platform, which uses the resulting DSS (Decision Support System) outlined as help in decision making, delivered through an easy-touse mobile app or web-based interface. Farmers are assumed to use such a decision-making aid behind the power of the logic informed by the data pool. Building on existing data available in the farm management systems, the ICC platform is easily interoperable with other IoT devices. ICC facilitates connections and information sharing in real-time between users, including farmers, researchers and industrial partners, enabling them to cooperate in farming innovation and knowledge exchange. Moreover, ICC supports sustainable practice in agriculture by integrating gamification techniques to stimulate farm adopters, deploying VR technologies to model and visualise 3D farm environments and farm conditions, framing the field scenarios using VR headsets and Real-Time 3D engines, and leveraging edge technologies to facilitate secure and fast communication and collaboration between users involved. And through allowing blockchain-based marketplaces, ICC offers traceability from farm to fork – that is: from producer to consumer. It empowers informed decision-making through tailor-made recommendations generated by means of AI-driven analysis and technology democratisation, enabling small-scale and resource-limited farmers to get their voice heard. It connects with traditional knowledge, brings together multi-stakeholder interactions as well as establishes a participatory ecosystem to incentivise continuous growth and development towards more sustainable agro-ecological food systems. This integrated approach leverages the power of emerging technologies to provide sustainable solutions for a resilient food system, ensuring sustainable agriculture worldwide.

Keywords: blockchain, internet of things, artificial intelligence, decision support system, virtual reality, gamification, traceability, sustainable agriculture

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Authors: Nami Takase

Abstract:

Computer-mediated-communication allows people to connect and interact with each other as if they were sharing the same space. The current study examined the effects of using video letters (VLs) on the development of second language speaking skills of Common European Framework of Reference for Languages (CEFR) A1 and CEFR B2 level learners of English as a foreign language. Two groups were formed to measure the impact of VLs. The experimental and control groups were given the same topic, and both groups worked with a native English-speaking university student from the United States of America. Students in the experimental group exchanged VLs, and students in the control group used video conferencing. Pre- and post-tests were conducted to examine the effects of each practice mode. The transcribed speech-text data showed that the VL group had improved speech accuracy scores, while the video conferencing group had increased sentence complexity scores. The use of VLs may be more effective for beginner-level learners because they are able to notice their own errors and replay videos to better understand the native speaker’s speech at their own pace. Both the VL and video conferencing groups provided positive feedback regarding their interactions with native speakers. The results showed how different types of computer-mediated communication impacts different areas of language learning and speaking practice and how each of these types of online communication tool is suited to different teaching objectives.

Keywords: computer-assisted-language-learning, computer-mediated-communication, english as a foreign language, speaking

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Authors: Yu Qin, Wanjiaman Li

Abstract:

The widespread use of mobile electronic devices increases the complexities of mobile security. This thesis aims to provide a secure communication environment for smartphone users. Some research proves that the one-time pad is one of the securest encryption methods, and that the key distribution problem can be solved by using the QKD (quantum key distribution). The objective of this project is to design an Android APP (application) to exchange several random keys between mobile phones. Inspired by QKD, the developed APP uses the quick response (QR) code as a carrier to dispatch large amounts of one-time keys. After evaluating the performance of APP, it allows the mobile phone to capture and decode 1800 bytes of random data in 600ms. The continuous scanning mode of APP is designed to improve the overall transmission performance and user experience, and the maximum transmission rate of this mode is around 2200 bytes/s. The omnidirectional readability and error correction capability of QR code gives it a better real-life application, and the features of adequate storage capacity and quick response optimize overall transmission efficiency. The security of this APP is guaranteed since QR code is exchanged face-to-face, eliminating the risk of being eavesdropped. Also, the id of QR code is the only message that would be transmitted through the whole communication. The experimental results show this project can achieve superior transmission performance, and the correlation between the transmission rate of the system and several parameters, such as the QR code size, has been analyzed. In addition, some existing technologies and the main findings in the context of the project are summarized and critically compared in detail.

Keywords: one-time pad, QKD (quantum key distribution), QR code, application

Procedia PDF Downloads 146

Authors: Chia-Chen Chen, Mu-Yen Chen

Abstract:

In recent years, with the vigorous growth of hardware and software technologies of smart mobile devices coupling with the rapid increase of social network influence, mobile commerce also presents the commercial operation mode of the future mainstream. For the time being, SoLoMo has become one of the very popular commercial models, its full name and meaning mainly refer to that users can obtain three key service types through smart mobile devices (Mobile) and omnipresent network services, and then link to the social (Social) web site platform to obtain the information exchange, again collocating with position and situational awareness technology to get the service suitable for the location (Local), through anytime, anywhere and any personal use of different mobile devices to provide the service concept of seamless integration style, and more deriving infinite opportunities of the future. The study tries to explore the use intention of users with SoLoMo mobile application formula, proposing research model to integrate TAM, ISSM, IDT and network externality, and with questionnaires to collect data and analyze results to verify the hypothesis, results show that perceived ease-of-use (PEOU), perceived usefulness (PU), and network externality have significant impact on the use intention with SoLoMo mobile application formula, and the information quality, relative advantages and observability have impacts on the perceived usefulness, and further affecting the use intention.

Keywords: SoLoMo (social, local, and mobile), technology acceptance model, innovation diffusion theory, network externality

Procedia PDF Downloads 528

Authors: Pradeep Singh, Shrish Verma

Abstract:

Software fault prediction models are created by using the source code, processed metrics from the same or previous version of code and related fault data. Some company do not store and keep track of all artifacts which are required for software fault prediction. To construct fault prediction model for such company, the training data from the other projects can be one potential solution. The earlier we predict the fault the less cost it requires to correct. The training data consists of metrics data and related fault data at function/module level. This paper investigates fault predictions at early stage using the cross-project data focusing on the design metrics. In this study, empirical analysis is carried out to validate design metrics for cross project fault prediction. The machine learning techniques used for evaluation is Naïve Bayes. The design phase metrics of other projects can be used as initial guideline for the projects where no previous fault data is available. We analyze seven data sets from NASA Metrics Data Program which offer design as well as code metrics. Overall, the results of cross project is comparable to the within company data learning.

Keywords: software metrics, fault prediction, cross project, within project.

Procedia PDF Downloads 344