Search results for: panel data analysis.

Authors: Rusudan Kinkladze, Guguli Kurashvili, Ketevan Chitaladze

Abstract:

Foreign direct investment is a driving force in the development of the interdependent national economies, and the study and analysis of investments is an urgent problem. It is particularly important for transitional economies, such as Georgia, and the study and analysis of investments is an urgent problem. Consequently, the goal of the research is the study and analysis of direct foreign investments in Georgia, and identification and forecasting of modern trends, and covers the period of 2006-2015. The study uses the methods of statistical observation, grouping and analysis, the methods of analytical indicators of time series, trend identification and the predicted values are calculated, as well as various literary and Internet sources relevant to the research. The findings showed that modern investment policy In Georgia is favorable for domestic as well as foreign investors. Georgia is still a net importer of investments. In 2015, the top 10 investing countries was led by Azerbaijan, United Kingdom and Netherlands, and the largest share of FDIs were allocated in the transport and communication sector; the financial sector was the second, followed by the health and social work sector, and the same trend will continue in the future. 

Keywords: Foreign Direct Investments, methods, statistics, analysis.

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Authors: Kalum Priyanath Udagepola, Zuo Decheng, Wu Zhibo, Yang Xiaozong

Abstract:

Modern spatial database management systems require a unique Spatial Access Method (SAM) in order solve complex spatial quires efficiently. In this case the spatial data structure takes a prominent place in the SAM. Inadequate data structure leads forming poor algorithmic choices and forging deficient understandings of algorithm behavior on the spatial database. A key step in developing a better semantic spatial object data structure is to quantify the performance effects of semantic and outlier detections that are not reflected in the previous tree structures (R-Tree and its variants). This paper explores a novel SSRO-Tree on SAM to the Topo-Semantic approach. The paper shows how to identify and handle the semantic spatial objects with outlier objects during page overflow/underflow, using gain/loss metrics. We introduce a new SSRO-Tree algorithm which facilitates the achievement of better performance in practice over algorithms that are superior in the R*-Tree and RO-Tree by considering selection queries.

Keywords: Outlier, semantic spatial object, spatial objects, SSRO-Tree, topo-semantic.

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Authors: Balgaisha G. Mukanova, Yelbek B. Utepov, Aida G. Nazarova, Alisher Z. Imanov

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The problem of identifying local noise sources on a construction site using a sensor system is considered. Mathematical modeling of detected signals on sensors was carried out, considering signal decay and signal delay time between the source and detector. Recordings of noises produced by construction tools were used as a dependence of noise on time. Synthetic sensor data was constructed based on these data, and a model of the propagation of acoustic waves from a point source in the three-dimensional space was applied. All sensors and sources are assumed to be located in the same plane. A source localization method is checked based on the signal time delay between two adjacent detectors and plotting the direction of the source. Based on the two direct lines' crossline, the noise source's position is determined. Cases of one dominant source and the case of two sources in the presence of several other sources of lower intensity are considered. The number of detectors varies from three to eight detectors. The intensity of the noise field in the assessed area is plotted. The signal of a two-second duration is considered. The source is located for subsequent parts of the signal with a duration above 0.04 sec; the final result is obtained by computing the average value.

Keywords: Acoustic model, direction of arrival, inverse source problem, sound localization, urban noises.

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Authors: Ali A. Ofoghi

Abstract:

While the shear walls are not economical in buildings, thin shear walls are widely used in the buildings. In the present study, the ratio of different loads to their plasticity and seismic behavior of the wall under different loads have been investigated. Modeling and analysis are carried out by the finite element analysis software ABAQUS. The results show that any increase in the exerted loads will have adverse effects on the seismic behavior of the thin shear walls and causes the wall to collapse by small displacements.

Keywords: Thin shear wall, nonlinear dynamic analysis, reinforced concrete, plasticity.

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Authors: Lara F. Horani, Shurong Tong

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Identification of customer requirements and their preferences are the starting points in the process of product design. Most of design methodologies focus on traditional requirements. But in the previous decade, the green products and the environment requirements have increasingly attracted the attention with the constant increase in the level of consumer awareness towards environmental problems (such as green-house effect, global warming, pollution and energy crisis, and waste management). Determining the importance weights for the customer requirements is an essential and crucial process. This paper used the analytic hierarchy process (AHP) approach to evaluate and rate the customer requirements for green products. With respect to the ultimate goal of customer satisfaction, surveys are conducted using a five-point scale analysis. With the help of this scale, one can derive the weight vectors. This approach can improve the imprecise ranking of customer requirements inherited from studies based on the conventional AHP. Furthermore, the AHP with extent analysis is simple and easy to implement to prioritize customer requirements. The research is based on collected data through a questionnaire survey conducted over a sample of 160 people belonging to different age, marital status, education and income groups in order to identify the customer preferences for green product requirements.

Keywords: Analytic hierarchy process, green product, customer requirements for green design, importance weights for the customer requirements.

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Authors: V. A. C. Vale, E. T. L. Cöuras Ford

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The use of optical technologies in the telecommunications has been increasing due to its ability to transmit large amounts of data over long distances. However, as in all systems of data transmission, optical communication channels suffer from undesirable and non-deterministic effects, being essential to know the same. Thus, this research allows the assessment of these effects, as well as their characterization and beneficial uses of these effects.

Keywords: Optical communication, optical fiber, non-deterministic effects.

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Authors: Rujijan Vichivanives, Kittiya Poonsilp, Canasanan Wanavijit

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This research aims to create mobile tools to analyze rice disease quickly and easily. The principle of object-oriented software engineering and objective-C language were used for software development methodology and the principle of decision tree technique was used for analysis method. Application users can select the features of rice disease or the color appears on the rice leaves for recognition analysis results on iOS mobile screen. After completing the software development, unit testing and integrating testing method were used to check for program validity. In addition, three plant experts and forty farmers have been assessed for usability and benefit of this system. The overall of users’ satisfaction was found in a good level, 57%. The plant experts give a comment on the addition of various disease symptoms in the database for more precise results of the analysis. For further research, it is suggested that image processing system should be developed as a tool that allows users search and analyze for rice diseases more convenient with great accuracy.

Keywords: Rice disease, analysis system, mobile application, iOS operating system.

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Authors: Akanksha Menon, Nesrin Ozalp

Abstract:

Solar energy is not only sustainable but also a clean alternative to be used as source of high temperature heat for many processes and power generation. However, the major drawback of solar energy is its transient nature. Especially in solar thermochemical processing, it is crucial to maintain constant or semiconstant temperatures inside the solar reactor. In our laboratory, we have developed a mechanism allowing us to achieve semi-constant temperature inside the solar reactor. In this paper, we introduce the concept along with some updated designs and provide the optical analysis of the concept under various incoming flux.

Keywords: Aperture, Solar reactor, Optical analysis, Solar thermal

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Authors: Simone C. F. Neves, Lúcio F. A. Campos, Ewaldo Santana, Ginalber L. O. Serra, Allan K. Barros

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We propose a method for discrimination and classification of ovarian with benign, malignant and normal tissue using independent component analysis and neural networks. The method was tested for a proteomic patters set from A database, and radial basis functions neural networks. The best performance was obtained with probabilistic neural networks, resulting I 99% success rate, with 98% of specificity e 100% of sensitivity.

Keywords: Cancer ovarian, Proteomic patterns in serum, independent component analysis and neural networks.

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Authors: D. G. Jung, J. B. Lim, J. H. Kim, J. J. Kim

Abstract:

The international society focuses on the environment protection and natural energy sources control for the global cooperation against weather change and sustainable growth. The study presents the overview of the water shortage status and the necessity of wastewater reuse facility in military facilities and for the possibility of the introduction, compares the economics by means of cost-benefit analysis. The military features such as the number of users of military barracks and the water use were surveyed by the design principles by facility types, the application method of wastewater reuse facility was selected, the feed water, its application and the volume of reuse volume were defined and the expectation was estimated, confirming the possibility of introducing a wastewater reuse possibility by means of cost-benefit analysis.

Keywords: military barracks, wastewater reuse facility, cost-benefit analysis

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Authors: Min Kyung An

Abstract:

In Wireless Sensor Networks which consist of tiny wireless sensor nodes with limited battery power, one of the most fundamental applications is data aggregation which collects nearby environmental conditions and aggregates the data to a designated destination, called a sink node. Important issues concerning the data aggregation are time efficiency and energy consumption due to its limited energy, and therefore, the related problem, named Minimum Latency Aggregation Scheduling (MLAS), has been the focus of many researchers. Its objective is to compute the minimum latency schedule, that is, to compute a schedule with the minimum number of timeslots, such that the sink node can receive the aggregated data from all the other nodes without any collision or interference. For the problem, the two interference models, the graph model and the more realistic physical interference model known as Signal-to-Interference-Noise-Ratio (SINR), have been adopted with different power models, uniform-power and non-uniform power (with power control or without power control), and different antenna models, omni-directional antenna and directional antenna models. In this survey article, as the problem has proven to be NP-hard, we present and compare several state-of-the-art approximation algorithms in various models on the basis of latency as its performance measure.

Keywords: Data aggregation, convergecast, gathering, approximation, interference, omni-directional, directional.

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Authors: Mohamed A. Mahfouz, M. A. Ismail

Abstract:

This paper introduces new algorithms (Fuzzy relative of the CLARANS algorithm FCLARANS and Fuzzy c Medoids based on randomized search FCMRANS) for fuzzy clustering of relational data. Unlike existing fuzzy c-medoids algorithm (FCMdd) in which the within cluster dissimilarity of each cluster is minimized in each iteration by recomputing new medoids given current memberships, FCLARANS minimizes the same objective function minimized by FCMdd by changing current medoids in such away that that the sum of the within cluster dissimilarities is minimized. Computing new medoids may be effected by noise because outliers may join the computation of medoids while the choice of medoids in FCLARANS is dictated by the location of a predominant fraction of points inside a cluster and, therefore, it is less sensitive to the presence of outliers. In FCMRANS the step of computing new medoids in FCMdd is modified to be based on randomized search. Furthermore, a new initialization procedure is developed that add randomness to the initialization procedure used with FCMdd. Both FCLARANS and FCMRANS are compared with the robust and linearized version of fuzzy c-medoids (RFCMdd). Experimental results with different samples of the Reuter-21578, Newsgroups (20NG) and generated datasets with noise show that FCLARANS is more robust than both RFCMdd and FCMRANS. Finally, both FCMRANS and FCLARANS are more efficient and their outputs are almost the same as that of RFCMdd in terms of classification rate.

Keywords: Data Mining, Fuzzy Clustering, Relational Clustering, Medoid-Based Clustering, Cluster Analysis, Unsupervised Learning.

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Authors: B. Selma

Abstract:

The aim of this study is to test the feasibility of SIPINA method to predict the harmfulness parameters controlling the seismic response. The approach developed takes into consideration both the focal depth and the peak ground acceleration. The parameter to determine is displacement. The data used for the learning of this method and analysis nonlinear seismic are described and applied to a class of models damaged to some typical structures of the existing urban infrastructure of Jassy, Romania. The results obtained indicate an influence of the focal depth and the peak ground acceleration on the displacement.

Keywords: SIPINA method, seism, focal depth, peak ground acceleration, displacement.

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Authors: Omar M. Elmabrouk., Roaa Y. Taha., Najat M. Ebrahim, Sabbreen A. Mohammed

Abstract:

Power transformers are the most crucial part of power electrical system, distribution and transmission grid. This part is maintained using predictive or condition-based maintenance approach. The diagnosis of power transformer condition is performed based on Dissolved Gas Analysis (DGA). There are five main methods utilized for analyzing these gases. These methods are International Electrotechnical Commission (IEC) gas ratio, Key Gas, Roger gas ratio, Doernenburg, and Duval Triangle. Moreover, due to the importance of the transformers, there is a need for an accurate technique to diagnose and hence predict the transformer condition. The main objective of this technique is to avoid the transformer faults and hence to maintain the power electrical system, distribution and transmission grid. In this paper, the DGA was utilized based on the data collected from the transformer records available in the General Electricity Company of Libya (GECOL) which is located in Benghazi-Libya. The Fuzzy Logic (FL) technique was implemented as a diagnostic approach based on IEC gas ratio method. The FL technique gave better results and approved to be used as an accurate prediction technique for power transformer faults. Also, this technique is approved to be a quite interesting for the readers and the concern researchers in the area of FL mathematics and power transformer.

Keywords: Fuzzy logic, dissolved gas-in-oil analysis, DGA, prediction, power transformer.

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Authors: O. Vlcek

Abstract:

The paper deals with current issues in research of advanced methods to increase reliability of traditional timber structural elements. It analyses the issue of strengthening of bent timber beams, such as ceiling beams in old (historical) buildings with additional concrete slab in combination with externally bonded fibre - reinforced polymer. The paper describes experimental testing of composite timber-concrete beam with FRP reinforcement and compares results with FEM analysis.

Keywords: Timber-concrete composite, strengthening, fibre-reinforced polymer, experimental analysis.

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Authors: Pongsiri K.

Abstract:

This research aimed to study the competency of health and wellness hotels and resorts in developing use the local natural resources and wisdom to conform to the national health and wellness tourism (HWT) strategy by comparing two independent samples, from Aumpur Muang, Ranong province and Aumpur Muang, Chiangmai province. And also study in the suggestive direct path to lead the organization to the sustainable successful. This research was conduct by using mix methodology; both quantitative and qualitative data were used. The data of competency of health and wellness hotels and resorts (HWHR) in developing use the local natural resources for HWT promoting were collected via 300 set of questionnaires, from 6 hotels and resorts in 2 areas, 3 places from Aumpur Muang, Ranong province and another 3 from Aumpur Muang, Chiangmai province. Thestudy of HWHR’s competency in developing use the local natural resources and wisdom to conform to the national HWT strategycan be divided into fourmain areas, food and beverages service, tourism activity, environmental service, and value adding. The total competency of the Chiangmai sample is importantly scoredp. value 0.01 higher than the Ranong one while the area of safety, Chiangmai’s competency is importantly scored 0.05 higher than the Ranong’scompetency. Others were rated not differently. Since Chiangmai perform better, then it can be a role model in developing HTHR or HWT destination. From the part of qualitative research, content analysis of business contents and its environments were analyzed. The four stages of strategic development and plans, from the smallest scale to the largest scale such a national base were discussed. The HWT: Evolution model and strategy for lodging Business were suggested. All those stages must work harmoniously together. The distinctive result illustrates the need of human resource development as the key point to create the identity of Thainess on Health and wellness service providing. This will add-on the value of services and differentiates ourselves from other competitors. The creative of Thailand’s health and wellness brand possibly increase loyalty customers which agreed to be a path of sustainable development.

Keywords: Health and Wellness Tourism (HWT), Strategic Analysis, Health and Wellness Hotels and Resorts (HWHR), Lodging Firms.

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Authors: Aghamusa Azizov

Abstract:

This study investigates the correlation between solar activity and sentiment in news media coverage, using a large-scale dataset of solar activity since 1750 and over 15 million articles from "The New York Times" dating from 1851 onwards. Employing Pearson's correlation coefficient and multiple Natural Language Processing (NLP) tools—TextBlob, Vader, and DistillBERT—the research examines the extent to which fluctuations in solar phenomena are reflected in the sentiment of historical news narratives. The findings reveal that the correlation between solar activity and media sentiment is generally negligible, suggesting a weak influence of solar patterns on the portrayal of events in news media. Notably, a moderate positive correlation was observed between the sentiments derived from TextBlob and Vader, indicating consistency across NLP tools. The analysis provides insights into the historical impact of solar activity on human affairs and highlights the importance of using multiple analytical methods to understand complex relationships in large datasets. The study contributes to the broader understanding of how extraterrestrial factors may intersect with media-reported events and underlines the intricate nature of interdisciplinary research in the data science and historical domains.

Keywords: Solar Activity Correlation, Media Sentiment Analysis, Natural Language Processing, NLP, Historical Event Patterns.

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Authors: M. Ilyas, M. W. Siddiqi

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This study employs auto-regressive distributed lag (ARDL) bounds approach to cointegration for long run and errorcorrection modeling (ECM) for short run analysis to examine the relationship between revenue gap and economic growth for Pakistan using annual time series data over the period 1980 to 2008. The short and long run results indicate that revenue gap is statistical significant and negatively effect economic growth. The significant and negative coefficient of error correction term in ECM indicates that after a shock, the long rum equilibrium will again converge towards equilibrium about 10.406 percent within a year.

Keywords: ARDL cointegration, Economic Growth, RevenueGap, Pakistan.

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Authors: Norazah Yusof, Andi Besse Firdausiah Mansur

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Social learning network analysis has drawn attention for most researcher on e-learning research domain. This is due to the fact that it has the capability to identify the behavior of student during their social interaction inside e-learning. Normally, the social network analysis (SNA) is treating the students' interaction merely as node and edge with less meaning. This paper focuses on providing an ontology structure of e-learning Moodle that can enrich the relationships among students, as well as between the students and the teacher. This ontology structure brings great benefit to the future development of e-learning system.

Keywords: Ontology, e-learning, © Learning Network, Moodle.

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Authors: Marco Ryll, Svetan Ratchev

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This paper discusses the applicability of the Data Distribution Service (DDS) for the development of automated and modular manufacturing systems which require a flexible and robust communication infrastructure. DDS is an emergent standard for datacentric publish/subscribe middleware systems that provides an infrastructure for platform-independent many-to-many communication. It particularly addresses the needs of real-time systems that require deterministic data transfer, have low memory footprints and high robustness requirements. After an overview of the standard, several aspects of DDS are related to current challenges for the development of modern manufacturing systems with distributed architectures. Finally, an example application is presented based on a modular active fixturing system to illustrate the described aspects.

Keywords: Flexible Manufacturing, Publish/Subscribe, Plug & Produce.

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Authors: Khalid Ali, Manar Jammal

Abstract:

In order to meet the stringent latency and reliability requirements of the upcoming 5G networks, Open Radio Access Networks (O-RAN) have been proposed. The virtualization of O-RAN has allowed it to be treated as a Network Function Virtualization (NFV) architecture, while its components are considered Virtualized Network Functions (VNFs). Hence, intelligent Machine Learning (ML) based solutions can be utilized to apply different resource management and allocation techniques on O-RAN. However, intelligently allocating resources for O-RAN VNFs can prove challenging due to the dynamicity of traffic in mobile networks. Network providers need to dynamically scale the allocated resources in response to the incoming traffic. Elastically allocating resources can provide a higher level of flexibility in the network in addition to reducing the OPerational EXpenditure (OPEX) and increasing the resources utilization. Most of the existing elastic solutions are reactive in nature, despite the fact that proactive approaches are more agile since they scale instances ahead of time by predicting the incoming traffic. In this work, we propose and evaluate traffic forecasting models based on the ML algorithm. The algorithms aim at predicting future O-RAN traffic by using previous traffic data. Detailed analysis of the traffic data was carried out to validate the quality and applicability of the traffic dataset. Hence, two ML models were proposed and evaluated based on their prediction capabilities.

Keywords: O-RAN, traffic forecasting, NFV, ARIMA, LSTM, elasticity.

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Authors: Bin Su

Abstract:

This study focuses on the impact of school building design factors on winter extra energy consumption which mainly includes space heating, water heating and other appliances related to winter indoor thermal conditions. A number of Auckland schools were randomly selected for the study which introduces a method of using real monthly energy consumption data for a year to calculate winter extra energy data of school buildings. The study seeks to identify the relationships between winter extra energy data related to school building design data related to the main architectural features, building envelope and elements of the sample schools. The relationships can be used to estimate the approximate saving in winter extra energy consumption which would result from a changed design datum for future school development, and identify any major energy-efficient design problems. The relationships are also valuable for developing passive design guides for school energy efficiency.

Keywords: Building energy efficiency, Building thermal design, Building thermal performance, School building design.

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Authors: M. Stoklasa, H. Starzyczna, L. Zotykova

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This article deals with consumer ethnocentrism in the Moravian-Silesian region in the Czech Republic. Research was focused on finding out how strong consumer ethnocentrism is in the region and how it depends on demographic factors. The used method is CETSCALE and the data were obtained by questionnaire survey, analyzed by IBM SPSS. From the thousands of respondents the representative sample of 414 for MS region was created based on demographic factors of gender, age, education and income. The research analysis disclosed that consumer ethnocentrism in MS region depends on education and income and is independent on gender and age.

Keywords: Consumer ethnocentrism, demographic factors, foreign products, local products.

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Authors: A. Bagheri Garmarudi, M. Khanmohammadi, N. Khoddami, K. Shabani

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Determination of nano particle size is substantial since the nano particle size exerts a significant effect on various properties of nano materials. Accordingly, proposing non-destructive, accurate and rapid techniques for this aim is of high interest. There are some conventional techniques to investigate the morphology and grain size of nano particles such as scanning electron microscopy (SEM), atomic force microscopy (AFM) and X-ray diffractometry (XRD). Vibrational spectroscopy is utilized to characterize different compounds and applied for evaluation of the average particle size based on relationship between particle size and near infrared spectra [1,4] , but it has never been applied in quantitative morphological analysis of nano materials. So far, the potential application of nearinfrared (NIR) spectroscopy with its ability in rapid analysis of powdered materials with minimal sample preparation, has been suggested for particle size determination of powdered pharmaceuticals. The relationship between particle size and diffuse reflectance (DR) spectra in near infrared region has been applied to introduce a method for estimation of particle size. Back propagation artificial neural network (BP-ANN) as a nonlinear model was applied to estimate average particle size based on near infrared diffuse reflectance spectra. Thirty five different nano TiO2 samples with different particle size were analyzed by DR-FTNIR spectrometry and the obtained data were processed by BP- ANN.

Keywords: near infrared, particle size, chemometrics, neuralnetwork, nano structure.

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Authors: Mohammed Sghir Taleb

Abstract:

Morocco is characterized by a great richness and diversity in aromatic and medicinal plants and it has an ancestral knowledge in the use of plants for medicinal and cosmetic purposes. In effect, the poverty of riparian, specially, mountain populations have greatly contributed to the development of traditional pharmacopoeia in Morocco. The analysis of the bibliographic data showed that a large number of plants in Morocco are exploited for aromatic and medicinal purposes and several of them are commercialized internationally. However, these potentialities of aromatic and medicinal plants are currently subjected to climate change and strong human pressures: Collecting fruits, agriculture development, harvesting plants, urbanization, overgrazing...

Keywords: Aromatic, medicinal, plants, socioeconomy, Morocco.

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Authors: G. Rajesh, B. Vinayaga Sundaram, C. Aarthi

Abstract:

In wireless sensor network, sensor node transmits the sensed data to the sink node in multi-hop communication periodically. This high traffic induces congestion at the node which is present one-hop distance to the sink node. The packet transmission and reception rate of these nodes should be very high, when compared to other sensor nodes in the network. Therefore, the energy consumption of that node is very high and this effect is known as the “funneling effect”. The tree based-data aggregation technique (TBDA) is used to reduce the energy consumption of the node. The throughput of the overall performance shows a considerable decrease in the number of packet transmissions to the sink node. The proposed scheme, TBDA, avoids the funneling effect and extends the lifetime of the wireless sensor network. The average case time complexity for inserting the node in the tree is O(n log n) and for the worst case time complexity is O(n2).

Keywords: Data Aggregation, Funneling Effect, Traffic Congestion, Wireless Sensor Network.

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Authors: Koji Yamanouchi, Masaru Fujieda, Takahiro Murakami, Yoshihisa Ishida

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''Cocktail party problem'' is well known as one of the human auditory abilities. We can recognize the specific sound that we want to listen by this ability even if a lot of undesirable sounds or noises are mixed. Blind source separation (BSS) based on independent component analysis (ICA) is one of the methods by which we can separate only a special signal from their mixed signals with simple hypothesis. In this paper, we propose an online approach for blind source separation using the sliding DFT and the time domain independent component analysis. The proposed method can reduce calculation complexity in comparison with conventional methods, and can be applied to parallel processing by using digital signal processors (DSPs) and so on. We evaluate this method and show its availability.

Keywords: Cocktail party problem, blind Source Separation(BSS), independent component analysis, sliding DFT, onlineprocessing.

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Authors: Ashly Joseph

Abstract:

Cloud computing has become an essential component of enterprises and organizations globally in the current era of digital technology. The cloud has a multitude of advantages, including scalability, flexibility, and cost-effectiveness, rendering it an appealing choice for data storage and processing. The increasing storage of sensitive information in cloud environments has raised significant concerns over the security of such systems. The frequency of cyber threats and attacks specifically aimed at cloud infrastructure has been increasing, presenting substantial dangers to the data, reputation, and financial stability of enterprises. Conventional security methods can become inadequate when confronted with ever intricate and dynamic threats. Artificial Intelligence (AI) technologies possess the capacity to significantly transform cloud security through their ability to promptly identify and thwart assaults, adjust to emerging risks, and offer intelligent perspectives for proactive security actions. The objective of this research study is to investigate the utilization of AI technologies in augmenting the security measures within cloud computing systems. This paper aims to offer significant insights and recommendations for businesses seeking to protect their cloud-based assets by analyzing the present state of cloud security, the capabilities of AI, and the possible advantages and obstacles associated with using AI into cloud security policies.

Keywords: Machine Learning, Natural Learning Processing, Denial-of-Service attacks, Sentiment Analysis, Cloud computing.

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Authors: Asim Majeed, Rehan Bhana, Mak Sharma, Rebecca Goode, Nizam Bolia, Mike, Lloyd-Williams

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This study aims to investigate and explore the underlying causes of security concerns of customers emerged when WHSmith transformed its physical system to virtualized business model through NetSuite. NetSuite is essentially fully integrated software which helps transforming the physical system to virtualized business model. Modern organisations are moving away from traditional business models to cloud based models and consequently it is expected to have a better, secure and innovative environment for customers. The vital issue of the modern age race is the security when transforming virtualized through cloud based models and designers of interactive systems often misunderstand privacy and even often ignore it, thus causing concerns for users. The content analysis approach is being used to collect the qualitative data from 120 online bloggers including TRUSTPILOT. The results and finding provide useful new insights into the nature and form of security concerns of online users after they have used the WHSmith services offered online through their website. Findings have theoretical as well as practical implications for the successful adoption of cloud computing Business-to-Business model and similar systems.

Keywords: Innovation, virtualization, cloud computing, organizational flexibility

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Authors: N. Mahendran, R. Priya

Abstract:

The mobile cloud computing (MCC) with wireless sensor networks (WSNs) technology gets more attraction by research scholars because its combines the sensors data gathering ability with the cloud data processing capacity. This approach overcomes the limitation of data storage capacity and computational ability of sensor nodes. Finally, the stored data are sent to the mobile users when the user sends the request. The most of the integrated sensor-cloud schemes fail to observe the following criteria: 1) The mobile users request the specific data to the cloud based on their present location. 2) Power consumption since most of them are equipped with non-rechargeable batteries. Mostly, the sensors are deployed in hazardous and remote areas. This paper focuses on above observations and introduces an approach known as collaborative location-based sleep scheduling (CLSS) scheme. Both awake and asleep status of each sensor node is dynamically devised by schedulers and the scheduling is done purely based on the of mobile users’ current location; in this manner, large amount of energy consumption is minimized at WSN. CLSS work depends on two different methods; CLSS1 scheme provides lower energy consumption and CLSS2 provides the scalability and robustness of the integrated WSN.

Keywords: Sleep scheduling, mobile cloud computing, wireless sensor network, integration, location, network lifetime.

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